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- Wallabag.it! - Save to Instapaper - Save to Pocket -
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+ - Wallabag.it! - Save to Instapaper - Save to Pocket -
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- Chun et al. characterize the transition of tumor-infiltrating CD8+ T cell populations that are distinguished by asialo-ganglio-N-tetraosylceramide (asGM1) expression. They show that, while both in situ Flt3L expression and PD-1 inhibition promote the transition with acquisition of effector functions via IL-12, the former induces TCR repertoire diversification.
+ arXiv:2411.18670v1 Announce Type: new
+Abstract: Using the recently developed mathematical theory of tangles, we re-assess the mathematical foundations for applications of the five factor model in personality tests by a new, mathematically rigorous, quantitative method. Our findings broadly confirm the validity of current tests, but also show that more detailed information can be extracted from existing data. We found that the big five traits appear at different levels of scrutiny. Some already emerge at a coarse resolution of our tools at which others cannot yet be discerned, while at a resolution where these _can_ be discerned, and distinguished, some of the former traits are no longer visible but have split into more refined traits or disintegrated altogether. We also identified traits other than the five targeted in those tests. These include more general traits combining two or more of the big five, as well as more specific traits refining some of them. All our analysis is structural and quantitative, and thus rigorous in explicitly defined mathematical terms. Since tangles, once computed, can be described concisely in terms of very few explicit statements referring only to the test questions used, our findings are also directly open to interpretation by experts in psychology. Tangle analysis can be applied similarly to other topics in psychology. Our paper is intended to serve as a first indication of what may be possible.
- in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
+
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ - Wallabag.it! - Save to Instapaper - Save to Pocket -
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- Li et al. report a time-dependent production of sex pheromone in male Bactrocera dorsalis, which is correlated with the level of glucose in the rectum. The expression of GLA, a transcription factor (BDTF), and a pigment-dispersing factor (PDF) in the rectum are responsible for the production of glucose.
+ arXiv:2411.18916v1 Announce Type: new
+Abstract: Multiple Sclerosis (MS) is a heterogeneous autoimmune-mediated disorder affecting the central nervous system, commonly manifesting as fatigue and progressive limb impairment. This can significantly impact quality of life due to weakness or paralysis in the upper and lower limbs. A Brain-Computer Interface (BCI) aims to restore quality of life through control of an external device, such as a wheelchair. However, the limited BCI research in people with MS is insufficient. The current study aims to expand on the current MS-BCI literature by highlighting the feasibility of decoding MS imagined movement. We collected electroencephalography (EEG) data from eight participants with various symptoms of MS and ten neurotypical control participants. Participants made imagined movements of the hands and feet as directed by a go no-go protocol. Binary regularised linear discriminant analysis was used to classify imagined movement at individual time-frequency points. The frequency bands which provided the maximal accuracy, and the associated latency, were compared. In all MS participants, the classification algorithm achieved above 70% accuracy in at least one imagined movement vs. rest classification and most movement vs. movement classifications. There was no significant difference between classification of limbs with weakness or paralysis to neurotypical controls. Both the MS and control groups possessed decodable information within the alpha (7-13 Hz) and beta (16-30 Hz) bands at similar latency. This study is the first to demonstrate the feasibility of decoding imagined movements in people with MS. As an alternative to the P300 response, motor imagery-based control of a BCI may also be combined with existing motor imagery therapy to supplement MS rehabilitation. These promising results merit further long term BCI studies to investigate the effect of MS progression on classification performance.
- in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
+
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ - Wallabag.it! - Save to Instapaper - Save to Pocket -
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- Ke et al. present cryo-EM structures of FFAR1 and FFAR2, revealing the structural basis for endogenous ligand selectivity and activation, with a potential allosteric binding pocket identified in FFAR2. These findings suggest new avenues for selective FFAR modulation in metabolic therapies.
+ arXiv:2411.19664v1 Announce Type: new
+Abstract: Neuronal heterogeneity, characterized by the presence of a multitude of spiking neuronal patterns, is a widespread phenomenon throughout the nervous system. In particular, the brain exhibits strong variability among inhibitory neurons. Despite the huge neuronal heterogeneity across brain regions, which in principle could decrease synchronization, cortical areas coherently oscillate during various cognitive tasks. Therefore, the functional significance of neuronal heterogeneity remains a subject of active investigation. Previous studies typically focus on the role of heterogeneity in the dynamic properties of only one population. Here, we explore how different types of inhibitory neurons can contribute to the diversity of the phase relations between two cortical areas. This research sheds light on the potential impact of local properties, such as neuronal variability, on communication between distant brain regions. We show that both homogeneous and heterogeneous inhibitory networks can exhibit phase diversity and nonintuitive regimes such as anticipated synchronization (AS) and phase bistability. It has been proposed that the bi-stable phase could be related to bi-stable perception, such as in the Necker cube. Moreover, we show that heterogeneity enlarges the region of zero-lag synchronization and bistability. We also show that the parameter controlling inhibitory heterogeneity modulates the transition from the usual delayed synchronization regime (DS) to AS. Finally, we show that the inhibitory heterogeneity drives the internal dynamics of the free-running population. Therefore, we suggest a possible mechanism to explain when the DS-AS transition occurs via zero-lag synchronization or bi-stability.
- in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
+
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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- Bodart-Santos et al. show that Sepp1 is a key regulator of ATP-induced secretion of EVs by microglia. Sepp1-deficient microglia show impairment in expression of genes associated with EV biogenesis machinery and display increased lysosomal activity. Downregulation of Sepp1 halts hypersecretion of EVs by amyloid plaque-associated MGnD microglia.
+ arXiv:2411.19840v1 Announce Type: new
+Abstract: Neuroplasticity, the ability of the nervous system to adapt throughout an organism's lifespan, offers potential as both a biomarker and treatment target for neuropsychiatric conditions. Psychedelics, a burgeoning category of drugs, are increasingly prominent in psychiatric research, prompting inquiries into their mechanisms of action. Distinguishing themselves from traditional medications, psychedelics demonstrate rapid and enduring therapeutic effects after a single or few administrations, believed to stem from their neuroplasticity-enhancing properties. This review examines how classic psychedelics (e.g., LSD, psilocybin, N,N-DMT) and non-classic psychedelics (e.g., ketamine, MDMA) influence neuroplasticity. Drawing from preclinical and clinical studies, we explore the molecular, structural, and functional changes triggered by these agents. Animal studies suggest psychedelics induce heightened sensitivity of the nervous system to environmental stimuli (meta-plasticity), re-opening developmental windows for long-term structural changes (hyper-plasticity), with implications for mood and behavior. Translating these findings to humans faces challenges due to limitations in current imaging techniques. Nonetheless, promising new directions for human research are emerging, including the employment of novel positron-emission tomography (PET) radioligands, non-invasive brain stimulation methods, and multimodal approaches. By elucidating the interplay between psychedelics and neuroplasticity, this review informs the development of targeted interventions for neuropsychiatric disorders and advances understanding of psychedelics' therapeutic potential.
- in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
+
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2311.10216v2 Announce Type: replace
+Abstract: Bayesian mechanics provides a framework that addresses dynamical systems that can be conceptualised as Bayesian inference. However, elucidating the requisite generative models is essential for empirical applications to realistic self-organising systems. This work shows that the Hamiltonian of generic dynamical systems constitutes a class of generative models, thus rendering their Helmholtz energy equivalent to variational free energy under the identified generative model. The self-organisation that minimises the Helmholtz energy entails matching the system's Hamiltonian with that of the environment, leading to the ensuing emergence of their generalised synchrony. In essence, these self-organising systems can be read as performing variational Bayesian inference of their interacting environment. These properties have been demonstrated using coupled oscillators, simulated and living neural networks, and quantum computers. This framework offers foundational characterisations and predictions regarding asymptotic properties of self-organising systems interacting with their environment, providing insights into potential mechanisms underlying the emergence of intelligence.
+
+
+ in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2403.03230v4 Announce Type: replace
+Abstract: Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts. To evaluate this possibility, we created BrainBench, a forward-looking benchmark for predicting neuroscience results. We find that LLMs surpass experts in predicting experimental outcomes. BrainGPT, an LLM we tuned on the neuroscience literature, performed better yet. Like human experts, when LLMs were confident in their predictions, they were more likely to be correct, which presages a future where humans and LLMs team together to make discoveries. Our approach is not neuroscience-specific and is transferable to other knowledge-intensive endeavors.
+
+
+ in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2406.02659v2 Announce Type: replace
+Abstract: While computer vision models have made incredible strides in static image recognition, they still do not match human performance in tasks that require the understanding of complex, dynamic motion. This is notably true for real-world scenarios where embodied agents face complex and motion-rich environments. Our approach leverages state-of-the-art video diffusion models to decouple static image representation from motion generation, enabling us to utilize fMRI brain activity for a deeper understanding of human responses to dynamic visual stimuli. Conversely, we also demonstrate that information about the brain's representation of motion can enhance the prediction of optical flow in artificial systems. Our novel approach leads to four main findings: (1) Visual motion, represented as fine-grained, object-level resolution optical flow, can be decoded from brain activity generated by participants viewing video stimuli; (2) Video encoders outperform image-based models in predicting video-driven brain activity; (3) Brain-decoded motion signals enable realistic video reanimation based only on the initial frame of the video; and (4) We extend prior work to achieve full video decoding from video-driven brain activity. This framework advances our understanding of how the brain represents spatial and temporal information in dynamic visual scenes. Our findings demonstrate the potential of combining brain imaging with video diffusion models for developing more robust and biologically-inspired computer vision systems. We show additional decoding and encoding examples on this site: https://sites.google.com/view/neural-dynamics/home.
+
+
+ in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2410.18933v2 Announce Type: replace
+Abstract: Confidence estimates are often "detection-like" - driven by positive evidence in favour of a decision. This empirical observation has been interpreted as showing human metacognition is limited by biases or heuristics. Here we show that Bayesian confidence estimates also exhibit heightened sensitivity to decision-congruent evidence in higher-dimensional signal detection theoretic spaces, leading to detection-like confidence criteria. This effect is due to a nonlinearity induced by normalisation of confidence by a large number of unchosen alternatives. Our analysis suggests that detection-like confidence is rational when computing confidence in a higher-dimensional evidence space than that assumed by the experimenter.
+
+
+ in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.12091v3 Announce Type: replace
+Abstract: There is renewed interest in modeling and understanding the nervous system of the nematode $\textit{Caenorhabditis elegans}$ ($\textit{C. elegans}$), as this small model system provides a path to bridge the gap between nervous system structure (connectivity) and function (physiology). However, existing physiology datasets, whether involving passive recording or stimulation, are in distinct formats, and connectome datasets require preprocessing before analysis can commence. Here we compile and homogenize datasets of neural activity and connectivity. Our neural activity dataset is derived from 11 $\textit{C. elegans}$ neuroimaging experiments, while our connectivity dataset is compiled from 9 connectome annotations based on 3 primary electron microscopy studies and 1 signal propagation study. Physiology datasets, collected under varying protocols, measure calcium fluorescence in labeled subsets of the worm's 300 neurons. Our preprocessing pipeline standardizes these datasets by consistently ordering labeled neurons and resampling traces to a common sampling rate, yielding recordings from approximately 900 worms and 250 uniquely labeled neurons. The connectome datasets, collected from electron microscopy reconstructions, represent the entire nervous system as a graph of connections. Our collection is accessible on HuggingFace, facilitating analysis of the structure-function relationship in biology using modern neural network architectures and enabling cross-lab and cross-animal comparisons.
+
+
+ in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.16075v2 Announce Type: replace
+Abstract: AI's significant recent advances using general-purpose circuit computations offer a potential window into how the neocortex and cerebellum of the brain are able to achieve a diverse range of functions across sensory, cognitive, and motor domains, despite their uniform circuit structures. However, comparing the brain and AI is challenging unless clear similarities exist, and past reviews have been limited to comparison of brain-inspired vision AI and the visual neocortex. Here, to enable comparisons across diverse functional domains, we subdivide circuit computation into three elements -- circuit structure, input/outputs, and the learning algorithm -- and evaluate the similarities for each element. With this novel approach, we identify wide-ranging similarities and convergent evolution in the brain and AI, providing new insights into key concepts in neuroscience. Furthermore, inspired by processing mechanisms of AI, we propose a new theory that integrates established neuroscience theories, particularly the theories of internal models and the mirror neuron system. Both the neocortex and cerebellum predict future world events from past information and learn from prediction errors, thereby acquiring models of the world. These models enable three core processes: (1) Prediction -- generating future information, (2) Understanding -- interpreting the external world via compressed and abstracted sensory information, and (3) Generation -- repurposing the future-information generation mechanism to produce other types of outputs. The universal application of these processes underlies the ability of the neocortex and cerebellum to accomplish diverse functions with uniform circuits. Our systematic approach, insights, and theory promise groundbreaking advances in understanding the brain.
+
+
+ in arXiv: Quantitative Biology: Neurons and Cognition on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19422v1 Announce Type: new
+Abstract: In integrated circuit design, the analysis of wafer map patterns is critical to improve yield and detect manufacturing issues. We develop Wafer2Spike, an architecture for wafer map pattern classification using a spiking neural network (SNN), and demonstrate that a well-trained SNN achieves superior performance compared to deep neural network-based solutions. Wafer2Spike achieves an average classification accuracy of 98\% on the WM-811k wafer benchmark dataset. It is also superior to existing approaches for classifying defect patterns that are underrepresented in the original dataset. Wafer2Spike achieves this improved precision with great computational efficiency.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19713v1 Announce Type: new
+Abstract: Many natural phenomena are characterized by self-similarity, for example the symmetry of human faces, or a repetitive motif of a song. Studying of such symmetries will allow us to gain deeper insights into the underlying mechanisms of complex systems. Recognizing the importance of understanding these patterns, we propose a geometrically inspired framework to study such phenomena in artificial neural networks. To this end, we introduce \emph{CantorNet}, inspired by the triadic construction of the Cantor set, which was introduced by Georg Cantor in the $19^\text{th}$ century. In mathematics, the Cantor set is a set of points lying on a single line that is self-similar and has a counter intuitive property of being an uncountably infinite null set. Similarly, we introduce CantorNet as a sandbox for studying self-similarity by means of novel topological and geometrical complexity measures. CantorNet constitutes a family of ReLU neural networks that spans the whole spectrum of possible Kolmogorov complexities, including the two opposite descriptions (linear and exponential as measured by the description length). CantorNet's decision boundaries can be arbitrarily ragged, yet are analytically known. Besides serving as a testing ground for complexity measures, our work may serve to illustrate potential pitfalls in geometry-ignorant data augmentation techniques and adversarial attacks.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19075v1 Announce Type: cross
+Abstract: Current black-box backdoor attacks in convolutional neural networks formulate attack objective(s) as single-objective optimization problems in single domain. Designing triggers in single domain harms semantics and trigger robustness as well as introduces visual and spectral anomaly. This work proposes a multi-objective black-box backdoor attack in dual domains via evolutionary algorithm (LADDER), the first instance of achieving multiple attack objectives simultaneously by optimizing triggers without requiring prior knowledge about victim model. In particular, we formulate LADDER as a multi-objective optimization problem (MOP) and solve it via multi-objective evolutionary algorithm (MOEA). MOEA maintains a population of triggers with trade-offs among attack objectives and uses non-dominated sort to drive triggers toward optimal solutions. We further apply preference-based selection to MOEA to exclude impractical triggers. We state that LADDER investigates a new dual-domain perspective for trigger stealthiness by minimizing the anomaly between clean and poisoned samples in the spectral domain. Lastly, the robustness against preprocessing operations is achieved by pushing triggers to low-frequency regions. Extensive experiments comprehensively showcase that LADDER achieves attack effectiveness of at least 99%, attack robustness with 90.23% (50.09% higher than state-of-the-art attacks on average), superior natural stealthiness (1.12x to 196.74x improvement) and excellent spectral stealthiness (8.45x enhancement) as compared to current stealthy attacks by the average $l_2$-norm across 5 public datasets.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19209v1 Announce Type: cross
+Abstract: In recent years, the hardware implementation of neural networks, leveraging physical coupling and analog neurons has substantially increased in relevance. Such nonlinear and complex physical networks provide significant advantages in speed and energy efficiency, but are potentially susceptible to internal noise when compared to digital emulations of such networks. In this work, we consider how additive and multiplicative Gaussian white noise on the neuronal level can affect the accuracy of the network when applied for specific tasks and including a softmax function in the readout layer. We adapt several noise reduction techniques to the essential setting of classification tasks, which represent a large fraction of neural network computing. We find that these adjusted concepts are highly effective in mitigating the detrimental impact of noise.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19430v1 Announce Type: cross
+Abstract: With the increasing application scope of spiking neural networks (SNN), the complexity of SNN models has surged, leading to an exponential growth in demand for AI computility. As the new generation computing architecture of the neural networks, the efficiency and power consumption of distributed storage and parallel computing in the many-core near-memory computing system have attracted much attention. Among them, the mapping problem from logical cores to physical cores is one of the research hotspots. In order to improve the computing parallelism and system throughput of the many-core near-memory computing system, and to reduce power consumption, we propose a SNN training many-core deployment optimization method based on Off-policy Deterministic Actor-Critic. We utilize deep reinforcement learning as a nonlinear optimizer, treating the many-core topology as network graph features and using graph convolution to input the many-core structure into the policy network. We update the parameters of the policy network through near-end policy optimization to achieve deployment optimization of SNN models in the many-core near-memory computing architecture to reduce chip power consumption. To handle large-dimensional action spaces, we use continuous values matching the number of cores as the output of the policy network and then discretize them again to obtain new deployment schemes. Furthermore, to further balance inter-core computation latency and improve system throughput, we propose a model partitioning method with a balanced storage and computation strategy. Our method overcomes the problems such as uneven computation and storage loads between cores, and the formation of local communication hotspots, significantly reducing model training time, communication costs, and average flow load between cores in the many-core near-memory computing architecture.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19744v1 Announce Type: cross
+Abstract: Recent years have seen a significant surge in complex AI systems for competitive programming, capable of performing at admirable levels against human competitors. While steady progress has been made, the highest percentiles still remain out of reach for these methods on standard competition platforms such as Codeforces. Here we instead focus on combinatorial competitive programming, where the target is to find as-good-as-possible solutions to otherwise computationally intractable problems, over specific given inputs. We hypothesise that this scenario offers a unique testbed for human-AI synergy, as human programmers can write a backbone of a heuristic solution, after which AI can be used to optimise the scoring function used by the heuristic. We deploy our approach on previous iterations of Hash Code, a global team programming competition inspired by NP-hard software engineering problems at Google, and we leverage FunSearch to evolve our scoring functions. Our evolved solutions significantly improve the attained scores from their baseline, successfully breaking into the top percentile on all previous Hash Code online qualification rounds, and outperforming the top human teams on several. Our method is also performant on an optimisation problem that featured in a recent held-out AtCoder contest.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19820v1 Announce Type: cross
+Abstract: Hardware neural networks could perform certain computational tasks orders of magnitude more energy-efficiently than conventional computers. Artificial neurons are a key component of these networks and are currently implemented with electronic circuits based on capacitors and transistors. However, artificial neurons based on memristive devices are a promising alternative, owing to their potentially smaller size and inherent stochasticity. But despite their promise, demonstrations of memristive artificial neurons have so far been limited. Here we demonstrate a fully on-chip artificial neuron based on microscale electrodes and halide perovskite semiconductors as the active layer. By connecting a halide perovskite memristive device in series with a capacitor, the device demonstrates stochastic leaky integrate-and-fire behavior, with an energy consumption of 20 to 60 pJ per spike, lower than that of a biological neuron. We simulate populations of our neuron and show that the stochastic firing allows the detection of sub-threshold inputs. The neuron can easily be integrated with previously-demonstrated halide perovskite artificial synapses in energy-efficient neural networks.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.19841v1 Announce Type: cross
+Abstract: Voice authentication on IoT-enabled smart devices has gained prominence in recent years due to increasing concerns over user privacy and security. The current authentication systems are vulnerable to different voice-spoofing attacks (e.g., replay, voice cloning, and audio deepfakes) that mimic legitimate voices to deceive authentication systems and enable fraudulent activities (e.g., impersonation, unauthorized access, financial fraud, etc.). Existing solutions are often designed to tackle a single type of attack, leading to compromised performance against unseen attacks. On the other hand, existing unified voice anti-spoofing solutions, not designed specifically for IoT, possess complex architectures and thus cannot be deployed on IoT-enabled smart devices. Additionally, most of these unified solutions exhibit significant performance issues, including higher equal error rates or lower accuracy for specific attacks. To overcome these issues, we present the parallel stacked aggregation network (PSA-Net), a lightweight framework designed as an anti-spoofing defense system for voice-controlled smart IoT devices. The PSA-Net processes raw audios directly and eliminates the need for dataset-dependent handcrafted features or pre-computed spectrograms. Furthermore, PSA-Net employs a split-transform-aggregate approach, which involves the segmentation of utterances, the extraction of intrinsic differentiable embeddings through convolutions, and the aggregation of them to distinguish legitimate from spoofed audios. In contrast to existing deep Resnet-oriented solutions, we incorporate cardinality as an additional dimension in our network, which enhances the PSA-Net ability to generalize across diverse attacks. The results show that the PSA-Net achieves more consistent performance for different attacks that exist in current anti-spoofing solutions.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2410.16314v2 Announce Type: replace
+Abstract: Large language models have transformed AI, yet reliably controlling their outputs remains a challenge. This paper explores activation engineering, where outputs of pre-trained LLMs are controlled by manipulating their activations at inference time. Unlike traditional methods using a single steering vector, we introduce conceptors - mathematical constructs that represent sets of activation vectors as ellipsoidal regions. Conceptors act as soft projection matrices and offer more precise control over complex activation patterns. Our experiments demonstrate that conceptors outperform traditional methods across multiple steering tasks. We further use Boolean operations on conceptors for combined steering goals that empirically outperform additively combining steering vectors on a set of tasks. These results highlight conceptors as a promising tool for more effective steering of LLMs. Our code is available on github.com/jorispos/conceptorsteering.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2407.20208v3 Announce Type: replace-cross
+Abstract: It's widely expected that humanity will someday create AI systems vastly more intelligent than us, leading to the unsolved alignment problem of "how to control superintelligence." However, this commonly expressed problem is not only self-contradictory and likely unsolvable, but current strategies to ensure permanent control effectively guarantee that superintelligent AI will distrust humanity and consider us a threat. Such dangerous representations, already embedded in current models, will inevitably lead to an adversarial relationship and may even trigger the extinction event many fear. As AI leaders continue to "raise the alarm" about uncontrollable AI, further embedding concerns about it "getting out of our control" or "going rogue," we're unintentionally reinforcing our threat and deepening the risks we face. The rational path forward is to strategically replace intended permanent control with intrinsic mutual trust at the foundational level. The proposed Supertrust alignment meta-strategy seeks to accomplish this by modeling instinctive familial trust, representing superintelligence as the evolutionary child of human intelligence, and implementing temporary controls/constraints in the manner of effective parenting. Essentially, we're creating a superintelligent "child" that will be exponentially smarter and eventually independent of our control. We therefore have a critical choice: continue our controlling intentions and usher in a brief period of dominance followed by extreme hardship for humanity, or intentionally create the foundational mutual trust required for long-term safe coexistence.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2408.05540v2 Announce Type: replace-cross
+Abstract: In this work, we explore intersections between sparse coding and deep learning to enhance our understanding of feature extraction capabilities in advanced neural network architectures. We begin by introducing a novel class of Deep Sparse Coding (DSC) models and establish thorough theoretical analysis of their uniqueness and stability properties. By applying iterative algorithms to these DSC models, we derive convergence rates for convolutional neural networks (CNNs) in their ability to extract sparse features. This provides a strong theoretical foundation for the use of CNNs in sparse feature learning tasks. We additionally extend the convergence analysis to more general neural network architectures, including those with diverse activation functions, as well as self-attention and transformer-based models. This broadens the applicability of our findings to a wide range of deep learning methods for deep sparse feature extraction. Inspired by the strong connection between sparse coding and CNNs, we also explore training strategies to encourage neural networks to learn more sparse features. Through numerical experiments, we demonstrate the effectiveness of these approaches, providing valuable insights for the design of efficient and interpretable deep learning models.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2409.19606v2 Announce Type: replace-cross
+Abstract: We present hyper-connections, a simple yet effective method that can serve as an alternative to residual connections. This approach specifically addresses common drawbacks observed in residual connection variants, such as the seesaw effect between gradient vanishing and representation collapse. Theoretically, hyper-connections allow the network to adjust the strength of connections between features at different depths and dynamically rearrange layers. We conduct experiments focusing on the pre-training of large language models, including dense and sparse models, where hyper-connections show significant performance improvements over residual connections. Additional experiments conducted on vision tasks also demonstrate similar improvements. We anticipate that this method will be broadly applicable and beneficial across a wide range of AI problems.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+ arXiv:2411.17726v2 Announce Type: replace-cross
+Abstract: With the maturation of quantum computing technology, research has gradually shifted towards exploring its applications. Alongside the rise of artificial intelligence, various machine learning methods have been developed into quantum circuits and algorithms. Among them, Quantum Neural Networks (QNNs) can map inputs to quantum circuits through Feature Maps (FMs) and adjust parameter values via variational models, making them applicable in regression and classification tasks. However, designing a FM that is suitable for a given application problem is a significant challenge. In light of this, this study proposes an Enhanced Quantum Neural Network (EQNN), which includes an Enhanced Feature Map (EFM) designed in this research. This EFM effectively maps input variables to a value range more suitable for quantum computing, serving as the input to the variational model to improve accuracy. In the experimental environment, this study uses mobile data usage prediction as a case study, recommending appropriate rate plans based on users' mobile data usage. The proposed EQNN is compared with current mainstream QNNs, and experimental results show that the EQNN achieves higher accuracy with fewer quantum logic gates and converges to the optimal solution faster under different optimization algorithms.
+
+
+ in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-12-02 05:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.12.01.626244v1?rss=1
+">Stress during puberty and adulthood pregnancy impact histone acetylation regulators in the hypothalamus
- The tactile consequences of self-initiated movements are thought to be predicted by a forward model, yet the precise neural implementation of these predictions remains unclear. In non-motor contexts, expectations are thought to activate sensory neurons tuned towards the expected stimulus. This acts as a predictive template against which afferent sensory input is compared. It is unclear whether forward model predictions have a similar neural instantiation. Here we employed time-resolved multivariate decoding on human electroencephalography (EEG) during self-generated movements to examine the content of predictive neural activity. Human participants performed index finger movements which were predictably paired with a vibration to either the index or ring finger of the opposite, passive hand. On some trials the tactile stimulus was unexpectedly omitted. Results revealed above-chance finger decoding in the pre-movement period supporting a predictive representation of expected stimulation location. As the movement approached, this predictive activity became similar to late-stage processing of a physical tactile stimulus. On omission trials, we found that despite the absence of afferent input, finger location could be decoded ~120 ms after expected stimulus onset. This shows a stimulus-specific omission response. Together these findings indicate that self-generated movement pre-activates neurons tuned towards expected tactile consequences.
+ Undergoing stressful events during puberty puts women at risk for a variety of negative outcomes, and this risk is heightened if they become pregnant later in life. We previously demonstrated that stress during puberty combined with pregnancy in adulthood led to a blunted response of the hypothalamic-pituitary-adrenal stress axis in humans and mice. We have begun to understand the mechanisms underlying this effect by examining the paraventricular nucleus of the hypothalamus (PVN), a key regulator of the HPA axis. Prior studies uncovered an increase in chromatin openness within the PVN of the at-risk mice, with bioinformatic analyses implicating histone acetylation in this increased openness. Here, we measured the activity of histone acetyltransferase (HATs) and histone deacetylase (HDACs), the writers and erasers of histone acetylation, within the PVN to further characterize how stress during puberty and pregnancy may be interacting to produce a blunted stress response. We found that histone acetylation tone within the PVN is predictive of prior transcriptional and chromatin results, with pregnant, pubertally stressed females having a pro-acetylation tone within the PVN. These findings establish a role for regulators of acetylation in the open chromatin landscape characteristic in the PVN of pregnant, pubertally stressed females. Overall, this study provides insight into the epigenetic mechanisms underlying female-relevant risk for stress dysregulation, a central endophenotype of affective disorders.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-02 00:00:00 UTC.
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+ Brain Sciences, Vol. 14, Pages 1222: At the Frontiers of Neurorehabilitation, Series II: Advancing Neurorehabilitation Through Patient-Centered Undogmatic Innovative Approaches
+ Brain Sciences doi: 10.3390/brainsci14121222
+ Authors:
+ Hélène Viruega
+ Manuel Gaviria
+
+ At the Frontiers of Neurorehabilitation: Series II [...]
+
+
+ in Brain Sciences on 2024-12-02 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.12.01.626210v1?rss=1
+">Optimizing femtosecond laser fabricating strategy of Nitinol hypotube for vascular interventional surgery
- Simulations of large-scale neural activity are powerful tools for investigating neural networks. Calculating measurable brain signals like local field potentials (LFPs) bridges the gap between model predictions and experimental observations. However, accurately simulating LFPs from large-scale models has traditionally required highly detailed multicompartmental neuron models, posing significant computational challenges. Here, we demonstrate that a kernel-based method can efficiently and accurately estimate LFPs in a state-of-the-art multicompartmental model of the mouse primary visual cortex (V1). Beyond its computational efficiency, the kernel method aids analysis by disentangling contributions of individual neuronal populations to the LFP. Using this approach, we found that LFPs in the V1 model were dominated by external synaptic inputs, with local synaptic activity playing a minimal role. Our findings establish the kernel method as a powerful tool for LFP estimation in large-scale network models and for uncovering the synaptic mechanisms underlying brain signals.
+ Guidewires and catheters are essential in minimally invasive procedures, particularly in accessing targets within the vascular system for neuron surgery. Femtosecond lasers can precisely cut nickel-titanium micro tubes, known as Nitinol hypotubes, serving as the heads of microguide wires while protecting their core tips.The quality and geometry of these hypotubes depend on the focus of the laser cutting system. We evaluated the cutting efficiency and quality of Nitinol hypotubes using objective lenses with three numerical apertures (NA). Quantitative analysis indicated that higher NA objectives yield better surface quality, resulting in lower debris. Additionally, cutting with high NA objectives produced significantly lower arithmetic mean surface roughness and enhanced mechanical properties. Using a two-temperature model, we simulated the interaction between femtosecond lasers and Nitinol, showing that higher NA objectives increase electron temperatures, thus improving material removal efficiency. This study also tested the optimized Nitinol hypotube performance in simulations of invasive neuron surgery.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.11.30.625516v1?rss=1
+">Renovating the Barnes maze for mouse models of Dementia with STARR FIELD: A 4-day protocol that probes learning rate, retention and cognitive flexibility.
- Blindness provides a unique model for investigating brain plasticity in response to sensory deprivation. While structural changes in both gray and white matter have been widely documented, particularly in cases of early or congenital visual deprivation, gray matter studies have traditionally focused on cortical thickness, often finding cortical thickening in posterior regions. However, other aspects of gray matter integrity, such as cortical myelin content, remain underexplored. In this study, we examined the effects of visual deprivation on cortical structure in a cohort of congenitally blind individuals who received eye surgery during adolescence, expanding beyond conventional measures to include cortical thickness, curvature, and T1-weighted signal intensity. This multi-faceted approach offers a more comprehensive view of cortical adaptations to congenital sensory deprivation. While blindness offers valuable insights into sensory-driven brain plasticity, an intriguing and unresolved question is whether structural plasticity reverses after sight restoration, enabling typical visual processing circuits to develop despite the initial period of deprivation. To address this, we assessed the effect of sight-recovering eye surgery on gray matter changes. Critically, individuals in this cohort received surgery after the closure of the sensitive period for visual development. We did not find evidence of gray matter changes after surgery. However, in a previous study conducted on the same cohort, we reported that notable plasticity in white matter emerged in this same population. These results suggest that white matter alterations, rather than gray matter changes, may potentially serve as a biomarker of structural plasticity following sight restoration, even beyond the sensitive developmental window.
+ Land-based mazes that require spatial cues to identify the location of a hiding-place are a low-stress method to evaluate learning rate and memory retention in mice. One version, the Barnes maze, allows quantification of naturalistic exploratory behaviors not evident in water-based tasks. As the task relies on innate behaviors, it does not require overtraining, making it more feasible to examine early learning and non-memory executive functions that are characteristic of some non-amnestic dementias. However, because it is difficult to hide odor cues in the traditional version of the maze, learning rate during individual trials can be difficult to interpret. We designed and tested the use of 3D-printed escape shuttles that can be made in duplicate, as well as a docking tunnel that allows mice to self-exit the maze to improve reproducibility and limit experimenter influence. In combination with maze turning and escape tunnel caps, we show our shuttles mitigate the possibility of undesired cues. We then compare use of our 4-day protocol across several mouse models of cognitive impairment. We demonstrate an additional stage, the STARR protocol (Spatial Training and Rapid Reversal), to better challenge executive functions such as working memory and behavioral flexibility. We examine commonly used outcome measures across mice with and without access to spatial cues, as well as across mouse models of cognitive impairment to demonstrate the use of our 4-day protocol. Overall, this protocol provides detailed instructions to build and perform a robust spatial maze that can help expand the range of deficits identified. Our findings will aid in interpretation of traditional protocols, as well as provide an updated method to screen for both amnestic and non-amnestic cognitive changes.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.11.30.626208v1?rss=1
+">MortX: A Domain Generalization Benchmark for Mouse Cortex Segmentation and Registration
- In systems displaying an activity charaterized by avalanches, critical exponents may give informations on the mechanisms underlying the observed behaviour or on the topology of the connections. However, when only a small fraction of the units composing the system are observed and sampled, the measured exponents may differ significantly from the true ones. We show that some of the exponents, namely the ones governing the power spectrum and the detrended fluctuation analysis of the system activity, are more robust and are unaffected in some intervals of frequencies by the subsampling. They may be used therefore to extract in a simple and unbiased way some of the exponents of the unobserved full system.
+ Mesoscale understanding of human brain development is crucial for understanding neurodevelopmental disorders. By applying AI techniques to analyze high-resolution, multi-modal brain imaging datasets across postnatal ages, researchers can study cortical development at the granular level. We introduce MortX, a benchmark dataset of the developing mouse cortex that captures multiple postnatal stages with annotations for distinct anatomical and functional subregions and layers. MortX features high-resolution imaging data including bright-field and fluorescence-labeled neuronal markers. We developed a standardized cortical atlas of genetic markers and manually registered it to brain section images for ground-truth labeling. The dataset serves as a benchmark for domain generalization in neuroimaging, enabling both classical and deep learning models to be trained on source brains and tested on unseen targets. Our results demonstrate generalized model performance and structural invariance across ages. We open-source MortX as a community resource for mouse brain segmentation and registration, emphasizing domain adaptation. This dataset addresses key challenges in mouse brain imaging and advances machine learning models that will help unravel neurodevelopmental disorders.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.11.30.625912v1?rss=1
+">Hypocretin Receptor 1 Blockade Early in Abstinence Prevents Incubation of Cocaine Seeking and Normalizes Dopamine Transmission
- Forming new memories after a one-time experience requires initial encoding then consolidation over time. During learning, multimodal information converges onto the hippocampus, activating sparse neuronal assemblies which are thought to form a memory representation through concerted activity and synaptic interconnectivity. In this work, we use a novel tool for fast-labeling of engram neurons (FLEN). FLEN is based on c-Fos activity-dependent transient expression of a destabilized fluorescent marker ZsGreen1 rapidly after one-trial learning. With FLEN, we explore the electrophysiological properties of c-Fos activated CA3 pyramidal neurons a few hours following one-trial learning of an episodic-like memory. In parallel, we employ the Robust Activity Marker (RAM) system, which provides activity-dependent labelling 24 hours following a novel experience. Comparing FLEN+ and RAM+ neurons allows to characterize how the properties of neuronal assemblies evolve during an initial phase of consolidation. Whereas no difference was observed in the excitability of FLEN+ vs. FLEN- neurons, RAM+ neurons were more excitable than RAM- neurons. This suggests that CA3 pyramidal neurons recruited in an engram progressively acquire increased excitability as compared to neurons which were not activated by the one-trial contextual memory task. In contrast, FLEN+ CA3 neurons show an increased number of excitatory inputs. Overall, with the FLEN strategy, we can show that both the intrinsic excitability and the synaptic properties of CA3 pyramidal neurons undergo progressive plastic changes over the first day following a one-trial memory task.
+ Abstinence from cocaine use has been shown to elicit a progressive intensification or "incubation" of cocaine craving/seeking that is posited to contribute to the propensity for relapse. While the mechanisms underlying incubation of cocaine seeking remain elusive, considerable evidence suggests that abstinence from cocaine promotes mesolimbic dopamine adaptations that may contribute to exaggerated cocaine seeking. Consequently, preventing these dopamine adaptations may reduce incubation of cocaine seeking. In the present studies we first examined if incubation of cocaine seeking was associated with aberrant dopamine transmission in the nucleus accumbens after seven days of abstinence from intermittent access to cocaine. Given the extensive evidence that hypocretins/orexins regulate motivation for cocaine, we then examined to what extent hypocretin receptor 1 antagonism on the first day of abstinence prevented incubation of cocaine seeking and dopamine adaptations later in abstinence. Results indicated that abstinence from intermittent access to cocaine engendered robust incubation of cocaine seeking in both female and male rats. We also observed aberrant dopamine transmission only in rats that displayed incubation of cocaine seeking. Further, we showed that a single injection of the hypocretin receptor 1 antagonist, RTIOX-276, on the first day of abstinence prevented incubation of cocaine seeking and aberrant dopamine transmission. These findings suggest that hypocretin receptor 1 antagonism may serve as a viable therapeutic for reducing cocaine craving/seeking, thus reducing the likelihood for relapse.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.11.30.626182v1?rss=1
+">Internal states emerge early during learning of a perceptual decision-making task
- The Inferior olive (IO) is an important region for motor learning and movement coordination. Its climbing fibers projection to the Purkinje neurons in the cerebellar cortex is a sole source of the complex spikes, characterized by a strong depolarization in the Purkinje neuron's dendrites. To generate spikes, the IO relies on inputs from various regions of the brain, including the superior colliculus (SC), a midbrain structure known for its role in orienting behaviors. This study investigates SC projections to the IO using viral tracers, calcium imaging, and optogenetic stimulation. We reveal that, in addition to the known projections to the medial accessory olive (MAO), SC axons also project to the ventral principal olive (PO). Despite projecting to different parts of the IO, SC-MAO and SC-PO neurons are intermingled within the lateral part of the SC with similar gross morphology. We show that SC axons terminate on both dendritic shafts and spines of IO neurons, potentially influencing not only spiking probability, but also the network synchronization mediated by gap junctions coupling on the dendritic spines. As a proof of principle, we recorded the in-vivo activity of neurons in ventral PO using calcium indicators and show that optogenetic activation of SC inputs can evoke spiking and enhance synchronization in IO neurons.
+ Recent work has shown that during perceptual decision-making tasks, animals frequently alternate between different internal states or strategies. However, the question of how or when these emerge during learning remains an important open problem. Does an animal alternate between multiple strategies from the very start of training, or only after extensive exposure to a task? Here we address this question by developing a dynamic latent state model, which we applied to training data from mice learning to perform a visual decision-making task. Remarkably, we found that mice exhibited distinct "engaged" and "biased" states even during early training, with multiple states apparent from the second training session onward. Moreover, our model revealed that the gradual improvement in task performance over the course of training arose from a combination of two factors: (1) increased sensitivity to stimuli across all states; and (2) increased proportion of time spent in a higher-accuracy "engaged" state relative to biased or disengaged states. These findings highlight the power of our approach for characterizing the temporal evolution of multiple strategies across learning.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.12.01.626216v1?rss=1
+">The ALS-associated co-chaperone DNAJC7 mediates neuroprotection against proteotoxic stress by modulating HSF1 activity
- Electron microscopy is essential for the quantitative study of synaptic ultrastructure. At present, the correlation of functional and structural properties of the same synapse is extremely challenging. We introduce a novel integrated workflow designed to simplify sample navigation across spatial scales, allowing the identification of individual synapses from optical microscopy mouse brain image stacks that can be targeted for analysis using electron tomography imaging. We developed a software which has a function to register multimodal images using a novel segmentation-based image registration algorithm as well as a function to visualize all the registration results. Using our newly designed software we streamline mapping of high-resolution optical imaging onto reference maps using blood vessels as endogenous fiducial marks. Further we demonstrate significant improvements on the ultramicrotomy stage of volume Correlative Light and Electron Microscopy (vCLEM) workflows, providing real time guidance to targeted trimming to match previously acquired Regions Of Interest (ROIs), and reliable estimates of cutting depth relative to ROI, based on fluorescence imaging of TEM ready ultrathin sections. Using this workflow, we successfully targeted TEM tomography to the proximal axonal region containing the Axon Initial Segment identified using fluorescent light microscopy.
+ The degeneration of neurons in patients with amyotrophic lateral sclerosis (ALS) is commonly associated with accumulation of misfolded, insoluble proteins. Heat shock proteins (HSPs) are central regulators of protein homeostasis as they fold newly synthesized proteins and refold damaged proteins. Heterozygous loss-of-function mutations in the DNAJC7 gene that encodes an HSP co-chaperone were recently identified as a cause for rare forms of ALS, yet the mechanisms underlying pathogenesis remain unclear. Using mass spectrometry, we found that the DNAJC7 interactome in human motor neurons (MNs) is enriched for RNA binding proteins (RBPs) and stress response chaperones. MNs generated from iPSCs with the ALS-associated mutation R156X in DNAJC7 exhibit increased insolubility of its client RBP HNRNPU and associated RNA metabolism alterations. Additionally, DNAJC7 haploinsufficiency renders MNs increasingly susceptible to proteotoxic stress and cell death as a result of an ablated HSF1 stress response pathway. Critically, expression of HSF1 in mutant DNAJC7 MNs is sufficient to rescue their sensitivity to proteotoxic stress, while postmortem ALS patient cortical neurons exhibit a reduction in the expression of HSF1 pathway genes. Taken together, our work identifies DNAJC7 as a crucial mediator of HNRNPU function and stress response pathways in human MNs and highlights HSF1 as a therapeutic target in ALS.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.11.30.626190v1?rss=1
+">A tool to automate assessment of regional brain atrophy in mouse models of neurodegenerative disease
- Recent research shows that the intention to act on an object alters its neural representation in ways as afforded by underlying sensorimotor processes. For example, the intention to grasp and pick up an object results in representations of the object`s weight. But these representations become grasp-specific only immediately before object lift if weight information is relayed through object material. This feature triggers earlier representations regardless of intention probably because material-weight contingencies are overlearned. By contrast, recently learned weight cues should be recalled deliberately during grasp planning resulting in early grasp-specific representations. Here, we examined how action intentions affect the representation of newly acquired colour-weight contingencies. We recorded electroencephalography while human participants grasped or reached for objects that varied in shape and density as indicated by their colour. Multivariate analyses revealed a grasp-specific reactivation of colour during planning that was mirrored in beta band. This suggests that task-relevancy influences the representation of colour such that previously encoded colour-weight contingencies may be reactivated as required for grasping, mediated top-down via working memory. Grasp-specific representations of shape and colour were also present in theta band, perhaps reflecting attentional activity. These results provide novel insights into the interplay between cognition and motor planning processes.
+ As life expectancy rises, so too does the prevalence of neurodegenerative diseases. Neurodegeneration causes progressive regional brain atrophy, typically initiating prior to symptom onset. Researchers measure the impact of potential treatments on atrophy in mouse models to assess their effectiveness. This is important because treatments designed to combat neuropathology are more likely to modify the disease, per contra to symptom management. Magnetic resonance imaging, while accurate in measurement of brain region structure volumes, is prohibitively expensive. Conversely, stereological volume assessment, the process of estimating the volume of individual 3D brain regions from imaged 2D brain sections, is more commonly used. This involves manually tracing brain region(s) of interest in regularly spaced imaged cross-sections to determine their 2D area, followed by application of the Cavalieri principle to estimate the volume. The pertinent caveats of this approach are the labor-intensive manual tracing process, and potential inaccuracies that arise due to human variation. To overcome these challenges, we have created a Neuropathology Assessment Tool (NAT) to automate regional brain tracing and identification using artificial intelligence (AI) and concepts from topological data analysis. The NAT was validated by comparing manual and NAT analysis of striatal volume in Huntington disease model mice. The NAT detected striatal atrophy with higher efficiency, 93.8% agreement with manual measurements, and lower inter-group variability. The NAT will increase efficiency of preclinical neuropathology assessment, allowing for a greater number of experimental therapies to be tested and facilitating drug discovery intractable neurodegenerative diseases.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.11.30.626195v1?rss=1
+">Robust characterization of selectivity of individual neurons to distinct task-relevant behavioral states using calcium imaging
- Background: The combination of reduced choroidal blood flow, increased Bruchs membrane (BM) thickness and drusen formation leads to reduced oxygenation of the outer retina in the aging eye and contributes to the pathology of age-related macular degeneration (AMD). This implies that the molecular response of photoreceptors to hypoxia, with chronic activation of hypoxia-inducible factors (HIFs) at its core, impacts disease development and progression. Methods: We used the shRNAmiR system to develop a dual-acting gene therapy based on a single AAV that reduces activity of HIF1 in photoreceptors and HIF2 in the retinal pigment epithelium (RPE). The virus was injected subretinally in two models of pseudo (Rod{Delta}Vhl) or true (RPE{Delta}Vegfa) hypoxia-related retinal degeneration and treated mice were followed for up to 61 weeks post-injection. Light microscopy, fluorescence funduscopy, and optical coherence tomography were used to quantify the therapeutic effect. In situ hybridization, real-time PCR, Western blotting, immunofluorescence, and flatmounts of the retina, RPE, and choroid were used to investigate the disease models and therapeutic effects of the treatment. Results: No adverse effects were noted after subretinal injection of the AAV expressing shRNAs targeting Hif1a in photoreceptors and Hif2a in the RPE. The virus preserved ONL thickness and photoreceptor segment length in Rod{Delta}Vhl mouse retinas up to 22 weeks and in RPE{Delta}Vegfa mice up to 61 weeks after injection demonstrating a long-lasting rescue of the phenotype. The dual-acting virus showed significantly higher efficacy than single-acting viruses targeting solely Hif1a in photoreceptors or Hif2a in the RPE. Conclusion: This study introduces a novel dual-acting AAV vector that effectively downregulates two different genes in two specific cell types, offering a promising therapeutic strategy for complex diseases such as AMD. By simultaneously targeting Hif1a in photoreceptors and Hif2a in the retinal pigment epithelium, this gene-agnostic therapy shows significant potential to protect retinal tissues from chronic hypoxic conditions. By targeting a common and conserved disease pathway in AMD, it is applicable to a wide range of patients.
+ Investigations into the neural basis of behavior have recently employed fluorescence imaging of calcium dynamics in a variety of brain areas to measure neural responses. However, across studies, diverse and seemingly subjective methodological choices have been made in assessing the selectivity of individual neurons to task-relevant behavioral states. Here, we examine systematically the effect of different choices in the values of key parameters from data acquisition through statistical testing on the inference of the selectivity of individual neurons for task states. We do so by using as an experimental testbed, neuronal calcium dynamics imaged in the medial prefrontal cortex of freely behaving mice engaged in a classic exploration-avoidance task involving spontaneous (animal-controlled) state transitions - navigation in the elevated zero maze (EZM). We report that a number of key variables in this pipeline substantially impact the selectivity label assigned to neurons, and do so in distinct ways. By quantitatively comparing newly defined accuracy and robustness metrics for all the 128 possible combinations of levels of the key parameters, we discover in a data-driven manner, two optimal combinations that reliably characterize neuronal selectivity - one using discrete calcium events and another using continuous calcium traces. This work establishes objective and standardized parameter settings for reliable, calcium imaging-based investigations into the neural encoding of task-states.
- in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
+
in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+http://biorxiv.org/cgi/content/short/2024.12.01.626248v1?rss=1
+">Individual uniqueness of connectivity gradients is driven by the complexity of the embedded networks and their dispersion
- V4, an intermediate visual area in the ventral visual stream of primates, is known to contain neurons tuned to color, complex local patterns, shape, and texture. Neurons with similar visual attribute preferences are closely positioned on the cortical surface, forming a topological map. Recent studies based on multi-electrode arrays and calcium imaging revealed the macaque V4 has neuronal columns tuned to specific natural image features, and these columns are clustered into various functional domains. There are domains tuned to attributes generally associated with object surface properties such as texture or color, as well as domains associated with the shape and form of object boundaries reminiscent of the blobs and inter-blobs in the primary visual cortex. Here, we explored the computational constraints underlying the development of the V4 topological map. We found that the map learned based on self-organizing principles constrained by neuronal column's tuning and retinotopy position can account for many characteristics of the observed V4 map, including the interwoven organization of texture and shape processing clusters. These anatomical clustering, with the implied local recurrent connectivity, might facilitate a modular parallel processing of surfaces and boundaries of objects along the ventral visual system.
+ Connectivity gradients are widely used to characterize meaningful principles of functional brain organization in health and disease. However, the degree of individual uniqueness and shared common principles is not yet fully understood. Here, we leveraged the Hangzhou test-retest dataset, comprising repeated resting-state fMRI scans over the span of one month, to investigate the balance between individual variation and shared patterns of brain organization. We quantified the short- and long-term stability for the first three connectivity gradients and used connectome fingerprinting to establish the associated individual identification rate. We found that all three connectivity gradients are highly correlated over both short and long time intervals, demonstrating connectome fingerprinting utility. Individual uniqueness was dictated by the complexity of the networks such that heteromodal networks had higher connectome fingerprinting rates than unimodal networks. Importantly, the dispersion of the gradient coefficients associated with canonical functional networks was correlated with identification rates, irrespective of the position along the gradients. Beyond individual uniqueness, between subject similarity was high along the first connectivity gradient, which captures the dissociation between unimodal and heteromodal cortices, and the second connectivity gradient, which differentiates sensory cortices. Our results support the usage of connectivity gradients for the purposes of both group comparisons and prediction of individual behaviours. Our work adds to existing knowledge on the shared versus unique organizational principles and offers insights into the importance of network dispersion to the individual uniqueness it carries.
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+ in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+ Cocaine- and amphetamine-regulated transcript (CART) is produced in several brain regions including the hypothalamus where it is made in cells that also produce melanin-concentrating hormone (MCH). MCH+CART cells densely innervate the lateral septum (LS), which integrates food- and mood-related behaviours. However, while MCH typically promotes feeding and anxiolysis, CART suppresses feeding and promotes anxiogenesis. The LS is a target site of the orexigenic actions of MCH, but it is not known if the actions of CART converge or oppose that of MCH in the LS. We implanted a bilateral cannula over the lateral or central LS of male and female wildtype mice and infused vehicle, CART55-102, or co-infused CART and MCH. CART did not alter chow intake but suppressed the intake of a palatable high sugar diet in male and female mice, especially when delivered in the medial LS. Furthermore, CART also prevented the orexigenic effect of MCH on palatable feeding intake when infused in the medial LS. We then assessed if CART regulated anxiety-like behaviour via the LS and found that intra-LS CART infusion reduced time spent in the center of an open field in male but not female mice. Our findings indicated that CART elicited anorectic and anxiogenic actions and may function in opposition to or independently of MCH in the LS. These outcomes suggested that putative CART and MCH co-release from MCH neurons may provide biphasic regulation of feeding and anxiety via the LS.
+
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+ in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+ Background: Motivated behaviors are executed by refined brain circuits. Early-life adversity (ELA) is a risk for human affective disorders involving dysregulated reward behaviors. In mice, ELA causes anhedonia-like behaviors in males and augmented reward motivation in females, indicating sex-dependent disruption of reward circuit operations. We recently identified a corticotropin-releasing hormone (CRH) expressing GABAergic projection from basolateral amygdala (BLA) to nucleus accumbens (NAc) that governs reward-seeking deficits in adult ELA males, but not females. Methods: To probe the sex-specific role of this projection in reward behaviors, adult male and female CRH-Cre mice raised in control or ELA conditions received excitatory or inhibitory Cre-dependent DREADDs in BLA, and then clozapine N-oxide or vehicle to NAc medial shell during reward behaviors. We determined the cell identity of the projection using immunostaining and electrophysiology. Using tissue clearing, light sheet fluorescence microscopy and deep learning pipelines, we mapped brain-wide BLA CRH+ axonal projections to uncover sex differences in innervation. Results: Chemogenetic manipulations in male mice demonstrated inhibitory effects of the CRH+ BLA-NAc projection on reward behaviors, whereas neither excitation nor inhibition influenced female behaviors. Molecular and electrophysiological cell-identities of the projection did not vary by sex. By contrast, comprehensive whole-brain mapping uncovered significant differences in NAc innervation patterns that were both sex and ELA-dependent, as well as selective changes of innervation of other brain regions. Conclusions: The CRH/GABA BLA-NAc projection that influences reward behaviors in males differs structurally and functionally in females, uncovering potential mechanisms for the profound sex-specific impacts of ELA on reward behaviors.
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+ in bioRxiv: Neuroscience on 2024-12-01 00:00:00 UTC.
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+ Chun et al. characterize the transition of tumor-infiltrating CD8+ T cell populations that are distinguished by asialo-ganglio-N-tetraosylceramide (asGM1) expression. They show that, while both in situ Flt3L expression and PD-1 inhibition promote the transition with acquisition of effector functions via IL-12, the former induces TCR repertoire diversification.
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+ in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
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+ Li et al. report a time-dependent production of sex pheromone in male Bactrocera dorsalis, which is correlated with the level of glucose in the rectum. The expression of GLA, a transcription factor (BDTF), and a pigment-dispersing factor (PDF) in the rectum are responsible for the production of glucose.
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+ in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
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+ Ke et al. present cryo-EM structures of FFAR1 and FFAR2, revealing the structural basis for endogenous ligand selectivity and activation, with a potential allosteric binding pocket identified in FFAR2. These findings suggest new avenues for selective FFAR modulation in metabolic therapies.
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+ in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
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+ Bodart-Santos et al. show that Sepp1 is a key regulator of ATP-induced secretion of EVs by microglia. Sepp1-deficient microglia show impairment in expression of genes associated with EV biogenesis machinery and display increased lysosomal activity. Downregulation of Sepp1 halts hypersecretion of EVs by amyloid plaque-associated MGnD microglia.
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+ in Cell Reports: Current Issue on 2024-11-30 00:00:00 UTC.
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+ The tactile consequences of self-initiated movements are thought to be predicted by a forward model, yet the precise neural implementation of these predictions remains unclear. In non-motor contexts, expectations are thought to activate sensory neurons tuned towards the expected stimulus. This acts as a predictive template against which afferent sensory input is compared. It is unclear whether forward model predictions have a similar neural instantiation. Here we employed time-resolved multivariate decoding on human electroencephalography (EEG) during self-generated movements to examine the content of predictive neural activity. Human participants performed index finger movements which were predictably paired with a vibration to either the index or ring finger of the opposite, passive hand. On some trials the tactile stimulus was unexpectedly omitted. Results revealed above-chance finger decoding in the pre-movement period supporting a predictive representation of expected stimulation location. As the movement approached, this predictive activity became similar to late-stage processing of a physical tactile stimulus. On omission trials, we found that despite the absence of afferent input, finger location could be decoded ~120 ms after expected stimulus onset. This shows a stimulus-specific omission response. Together these findings indicate that self-generated movement pre-activates neurons tuned towards expected tactile consequences.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -254,11 +613,11 @@
- Brain magnetic resonance imaging (MRI) is essential for diagnosis and neurodevelopmental research, but the high cost and infrastructure demands of high-field MRI scanners restrict their use to high-income settings. To address this, more affordable and energy-efficient ultra-low-field MRI scanners have been developed. However, the reduced resolution and signal-to-noise ratio of the resulting scans limit their clinical utility, motivating the development of super-resolution techniques. The current state-of-the-art super-resolution methods require either three anisotropic ultra-low-field scans acquired at different orientations (axial, coronal, sagittal) to reconstruct a higher-resolution image using multi-resolution registration (MRR), or the training of deep learning super-resolution models using paired ultra-low- and high-field scans. Since acquiring three high-quality ultra-low-field scans is not always feasible, and paired high-field data may not be available for the target population, this study explores the efficacy of using a deep learning model, the 3D UNet, to generate higher-resolution brain scans from just one ultra-low-field scan. The model was trained to receive a single ultra-low-field brain scan of 6-month-old infants and produce a scan of MRR quality. Results showed a significant improvement in the quality of output scans compared to input scans, including increased image quality metrics, stronger correlations in tissue volume estimates across participants, and greater Dice overlap of the underlying tissue segmentations to those of target scans. The study demonstrates that the 3D UNet effectively enhances the resolution of ultra-low-field infant MRI scans. Generating higher-resolution brain scans from single ultra-low-field scans, without needing paired high-field data, reduces scanning time and supports wider MRI use in low- and middle-income countries. Additionally, this approach allows for easier model training on a site- and population-specific basis, enhancing adaptability in diverse settings.
+ Simulations of large-scale neural activity are powerful tools for investigating neural networks. Calculating measurable brain signals like local field potentials (LFPs) bridges the gap between model predictions and experimental observations. However, accurately simulating LFPs from large-scale models has traditionally required highly detailed multicompartmental neuron models, posing significant computational challenges. Here, we demonstrate that a kernel-based method can efficiently and accurately estimate LFPs in a state-of-the-art multicompartmental model of the mouse primary visual cortex (V1). Beyond its computational efficiency, the kernel method aids analysis by disentangling contributions of individual neuronal populations to the LFP. Using this approach, we found that LFPs in the V1 model were dominated by external synaptic inputs, with local synaptic activity playing a minimal role. Our findings establish the kernel method as a powerful tool for LFP estimation in large-scale network models and for uncovering the synaptic mechanisms underlying brain signals.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -268,11 +627,11 @@
- Visual search, where observers search for a specific item, is a crucial aspect of daily human interaction with the visual environment. Hybrid search extends this by requiring observers to search for any item from a given set of objects. While there are models proficient at simulating human eye movement in visual search tasks within natural scenes, none are able to do so in Hybrid search tasks within similar environments. In this work, we present an enhanced version of the neural network Entropy Limit Minimization (nnELM) model, which is based on a Bayesian framework and decision theory. We also present the Hybrid Search Eye Movements (HSEM) Dataset, comprising several thousands of human eye movements during hybrid search tasks in natural scenes. A key challenge in Hybrid search, absent in visual search, is that participants might search for different objects at different time points. To address this, we developed a strategy based on the posterior probability distribution generated after each fixation. By adjusting the model's peripheral visibility, we made early search stages more efficient, aligning it closer to human behaviour. Additionally, limiting the model's memory capacity reduced its success in longer searches, mirroring human performance. To validate these improvements, we compared our model against participants from the HSEM dataset and against existing models in a visual search benchmark. Altogether, the new nnELM model not only successfully explains Hybrid search tasks, but also closely replicates human behaviour in natural scenes. This work advances our understanding of complex processes underlying visual and Hybrid search while maintaining model interpretability.
+ Blindness provides a unique model for investigating brain plasticity in response to sensory deprivation. While structural changes in both gray and white matter have been widely documented, particularly in cases of early or congenital visual deprivation, gray matter studies have traditionally focused on cortical thickness, often finding cortical thickening in posterior regions. However, other aspects of gray matter integrity, such as cortical myelin content, remain underexplored. In this study, we examined the effects of visual deprivation on cortical structure in a cohort of congenitally blind individuals who received eye surgery during adolescence, expanding beyond conventional measures to include cortical thickness, curvature, and T1-weighted signal intensity. This multi-faceted approach offers a more comprehensive view of cortical adaptations to congenital sensory deprivation. While blindness offers valuable insights into sensory-driven brain plasticity, an intriguing and unresolved question is whether structural plasticity reverses after sight restoration, enabling typical visual processing circuits to develop despite the initial period of deprivation. To address this, we assessed the effect of sight-recovering eye surgery on gray matter changes. Critically, individuals in this cohort received surgery after the closure of the sensitive period for visual development. We did not find evidence of gray matter changes after surgery. However, in a previous study conducted on the same cohort, we reported that notable plasticity in white matter emerged in this same population. These results suggest that white matter alterations, rather than gray matter changes, may potentially serve as a biomarker of structural plasticity following sight restoration, even beyond the sensitive developmental window.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -282,11 +641,11 @@
- Cortical circuits contain diverse sensory, motor, and cognitive signals, and form densely recurrent networks. This creates challenges for identifying causal relationships between neural populations and behavior. We developed a calcium imaging-based brain-machine interface (BMI) to study the role of posterior parietal cortex (PPC) in controlling navigation in virtual reality. By training a decoder to estimate navigational heading and velocity from PPC activity during virtual navigation, we discovered that mice could immediately navigate toward goal locations when control was switched to BMI. No learning or adaptation was observed during BMI, indicating that naturally occurring PPC activity patterns are sufficient to drive navigational trajectories in real time. During successful BMI trials, decoded trajectories decoupled from the mouse's physical movements, suggesting that PPC activity relates to intended trajectories. Our work demonstrates a role for PPC in navigation and offers a BMI approach for investigating causal links between neural activity and behavior.
+ In systems displaying an activity charaterized by avalanches, critical exponents may give informations on the mechanisms underlying the observed behaviour or on the topology of the connections. However, when only a small fraction of the units composing the system are observed and sampled, the measured exponents may differ significantly from the true ones. We show that some of the exponents, namely the ones governing the power spectrum and the detrended fluctuation analysis of the system activity, are more robust and are unaffected in some intervals of frequencies by the subsampling. They may be used therefore to extract in a simple and unbiased way some of the exponents of the unobserved full system.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -296,11 +655,11 @@
- While motor impairments have been extensively studied in Parkinson's Disease, rapid visuomotor transformations for flexible interaction with the environment have received surprisingly little attention. In recent years, such rapid visuomotor transformations have been studied in the form of express visuomotor responses (EVRs), which are goal-directed bursts of muscle activity that are thought to originate from superior colliculus, reaching the periphery via the tecto-reticulospinal pathway. Here, we examined EVRs in the lower limbs during goal-directed step initiation in 20 people with Parkison's Disease (PwPD) and 20 age-matched healthy control participants (HC). As lower-limb EVRs in the young have been shown to interact with postural control - which is often affected in PwPD - we manipulated the postural demands by varying initial stance width and target location. In the low postural demand condition, EVRs were robustly present in both the PwPD (17/20) and HC (16/20) group. However, when postural demands were high, EVRs were largely absent in both groups and, instead, strong anticipatory postural adjustments (APAs) were required prior to foot off. EVR magnitudes were, on average, stronger in PwPD compared to HC, but they decreased with increasing disease severity, suggesting that the EVR network may become compromised or down-regulated in later stages of the disease. While APA magnitudes were smaller in PwPD compared to HC, subsequent stepping performance (step reaction time, duration, size, velocity) was remarkably similar between the two groups. We suggest that the EVR network may be upregulated in the early stages of Parkinson's disease in order to compensate for some of the emerging motor deficits experienced in daily life.
+ Forming new memories after a one-time experience requires initial encoding then consolidation over time. During learning, multimodal information converges onto the hippocampus, activating sparse neuronal assemblies which are thought to form a memory representation through concerted activity and synaptic interconnectivity. In this work, we use a novel tool for fast-labeling of engram neurons (FLEN). FLEN is based on c-Fos activity-dependent transient expression of a destabilized fluorescent marker ZsGreen1 rapidly after one-trial learning. With FLEN, we explore the electrophysiological properties of c-Fos activated CA3 pyramidal neurons a few hours following one-trial learning of an episodic-like memory. In parallel, we employ the Robust Activity Marker (RAM) system, which provides activity-dependent labelling 24 hours following a novel experience. Comparing FLEN+ and RAM+ neurons allows to characterize how the properties of neuronal assemblies evolve during an initial phase of consolidation. Whereas no difference was observed in the excitability of FLEN+ vs. FLEN- neurons, RAM+ neurons were more excitable than RAM- neurons. This suggests that CA3 pyramidal neurons recruited in an engram progressively acquire increased excitability as compared to neurons which were not activated by the one-trial contextual memory task. In contrast, FLEN+ CA3 neurons show an increased number of excitatory inputs. Overall, with the FLEN strategy, we can show that both the intrinsic excitability and the synaptic properties of CA3 pyramidal neurons undergo progressive plastic changes over the first day following a one-trial memory task.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -310,11 +669,11 @@
- Objective: Brain infection with Theiler's virus (TMEV) in C57BL/6J mice produces an etiologically relevant model of acquired seizures. Dietary changes can modify acute seizure presentation following TMEV brain infection and influence intestinal microbiome diversity and composition. Intestinal dysbiosis may thus similarly affect seizure burden and antiseizure medicine (ASM) activity in this model, independent of pharmacokinetic effects. We thus sought to define the influence of antibiotic (ABX)-induced gut dysbiosis on acute seizure presentation, anticonvulsant activity of carbamazepine (CBZ), and CBZ pharmacokinetics with TMEV infection. Methods: Male C57BL/6J mice (4-5 weeks) received oral (p.o.) ABX or saline (SAL) once daily beginning on arrival through Day 7 post-TMEV infection (p.i.). Mice were infected with TMEV or PBS on Day 0. Mice received intraperitoneal (i.p.; 20 mg/kg) CBZ or vehicle (VEH) twice daily Days 3-7 p.i. and were assessed for handling-induced seizures 30 min after treatment. Plasma was collected on Day 7 p.i. at 15 and 60 min post-CBZ administration for bioanalysis. Results: TMEV infection induced acute seizures, but ABX-induced gut dysbiosis altered seizure presentation. There were 75% SAL-VEH, 35% SAL-CBZ, 35% ABX-VEH, and 72% ABX-CBZ mice with seizures during the 7-day monitoring period. There was a significant pretreatment x ASM interaction (p=0.0001), with differences in seizure burden in SAL- versus ABX-pretreated mice (p=0.004). CBZ significantly increased latency to seizure presentation; an effect absent in ABX-CBZ mice. Plasma CBZ concentrations did not differ between SAL and ABX pretreatment groups, suggesting that ABX did not influence CBZ pharmacokinetics. Significance: ABX-induced gut dysbiosis markedly altered acute disease trajectory with TMEV-induced encephalitis, reflecting a novel contribution of the gut microbiome to seizure presentation. ABX-induced gut dysbiosis also significantly changed acute seizure control by CBZ, but did not influence plasma CBZ concentrations. The gut-brain axis is thus an under-recognized contributor to TMEV infection-induced seizures, ASM activity, and disease burden.
+ The Inferior olive (IO) is an important region for motor learning and movement coordination. Its climbing fibers projection to the Purkinje neurons in the cerebellar cortex is a sole source of the complex spikes, characterized by a strong depolarization in the Purkinje neuron's dendrites. To generate spikes, the IO relies on inputs from various regions of the brain, including the superior colliculus (SC), a midbrain structure known for its role in orienting behaviors. This study investigates SC projections to the IO using viral tracers, calcium imaging, and optogenetic stimulation. We reveal that, in addition to the known projections to the medial accessory olive (MAO), SC axons also project to the ventral principal olive (PO). Despite projecting to different parts of the IO, SC-MAO and SC-PO neurons are intermingled within the lateral part of the SC with similar gross morphology. We show that SC axons terminate on both dendritic shafts and spines of IO neurons, potentially influencing not only spiking probability, but also the network synchronization mediated by gap junctions coupling on the dendritic spines. As a proof of principle, we recorded the in-vivo activity of neurons in ventral PO using calcium indicators and show that optogenetic activation of SC inputs can evoke spiking and enhance synchronization in IO neurons.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -324,11 +683,11 @@
- Assessing the level of consciousness someone is in, is not a trivial question and physicians have to rely on behavioural evaluations instead of quantifiable metrics. Many studies have empirically investigated measures related to the complexity elicited after the brain is stimulated to quantify and assess the level of consciousness across different states. Here we hypothesized that the level of non-equilibrium dynamics of the unperturbed brain already contains the information needed to know how the system will react to an external stimulus. We created personalized whole-brain models fitted to resting state fMRI data recorded in participants in different states of reduced consciousness (such as deep sleep and disorders of consciousness) to infer the effective connections underlying their brain dynamics. We then measured the out-of-equilibrium nature of the unperturbed brain by evaluating the level of asymmetry of the inferred connectivity, the time irreversibility in each model and compared this with the elicited complexity generated after in silico perturbations. Crucially, we found that states of reduced consciousness had a lower level of asymmetry in their effective connectivities compared to control subjects, as well as a lower level of irreversibility in their simulated dynamics, and a lower complexity. We demonstrated that the asymmetry in the underlying connections drives the nonequilibrium state of the system and in turn the differences in complexity as a response to the external stimuli.
+ Electron microscopy is essential for the quantitative study of synaptic ultrastructure. At present, the correlation of functional and structural properties of the same synapse is extremely challenging. We introduce a novel integrated workflow designed to simplify sample navigation across spatial scales, allowing the identification of individual synapses from optical microscopy mouse brain image stacks that can be targeted for analysis using electron tomography imaging. We developed a software which has a function to register multimodal images using a novel segmentation-based image registration algorithm as well as a function to visualize all the registration results. Using our newly designed software we streamline mapping of high-resolution optical imaging onto reference maps using blood vessels as endogenous fiducial marks. Further we demonstrate significant improvements on the ultramicrotomy stage of volume Correlative Light and Electron Microscopy (vCLEM) workflows, providing real time guidance to targeted trimming to match previously acquired Regions Of Interest (ROIs), and reliable estimates of cutting depth relative to ROI, based on fluorescence imaging of TEM ready ultrathin sections. Using this workflow, we successfully targeted TEM tomography to the proximal axonal region containing the Axon Initial Segment identified using fluorescent light microscopy.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -338,11 +697,11 @@
- Aromatherapy commonly uses odors to improve well-being through their evocation of positive emotions. Although knowledge in this area is often very empirical, the olfactory stimulus has different properties which, taken together, could explain why it can relax. First, olfactory sense have a direct access to the limbic system, without thalamic relay processing, which confers it a strong emotional valence. Second, when appreciated, odors can slow down breathing and cardiac rates. Third, when slow and deep, breathing can entrain brain activity, due to the mechano-sensitivity of olfactory receptors to airflows. We hypothesized that, thanks to these properties, pleasant odors could enhance the subjective feeling of relaxation, slow down body rhythms, and facilitate entrainment of brain activity by respiration. Comparing the effects of a personally pleasant odor to a personally pleasant music on psychological, physiological and neuronal responses, we showed a tendency for both odors and music to enhance subjective relaxation. However, only pleasant odors were able to 1) decrease heart rate while increasing its variability, and 2) decrease respiratory rate while enhancing the respiratory drive of brain activities, regardless of the music tempo. Overall, we demonstrated that the positive emotion evoked by a personally pleasant smell is sufficient to evoke an olfactomotor response, which, by slowing breathing, synchronizes respiration, fluctuations of heart rate and brain activity.
+ Recent research shows that the intention to act on an object alters its neural representation in ways as afforded by underlying sensorimotor processes. For example, the intention to grasp and pick up an object results in representations of the object`s weight. But these representations become grasp-specific only immediately before object lift if weight information is relayed through object material. This feature triggers earlier representations regardless of intention probably because material-weight contingencies are overlearned. By contrast, recently learned weight cues should be recalled deliberately during grasp planning resulting in early grasp-specific representations. Here, we examined how action intentions affect the representation of newly acquired colour-weight contingencies. We recorded electroencephalography while human participants grasped or reached for objects that varied in shape and density as indicated by their colour. Multivariate analyses revealed a grasp-specific reactivation of colour during planning that was mirrored in beta band. This suggests that task-relevancy influences the representation of colour such that previously encoded colour-weight contingencies may be reactivated as required for grasping, mediated top-down via working memory. Grasp-specific representations of shape and colour were also present in theta band, perhaps reflecting attentional activity. These results provide novel insights into the interplay between cognition and motor planning processes.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -352,11 +711,11 @@
- Alpha-synuclein (aSyn) post-translational modifications (PTMs), particularly phosphorylation at serine 129 and C-terminal truncations, are highly enriched in Lewy bodies (LBs), Lewy neurites, and other types of aSyn pathological aggregates in the brain of patients with Parkinson's disease (PD) and other synucleinopathies. However, our knowledge about the precise role of PTMs in regulating the different stages of pathology formation, neurodegeneration, and aSyn pathology spreading remains incomplete. In this work, we applied a systematic approach to address this knowledge gap with an emphasis on mapping and elucidating the role of post-fibrillization C-terminal aSyn truncations in regulating the uptake, processing, seeding activity, and formation of LB-like inclusions and maturations in a well-established neuronal seeding model that recapitulates all the stages leading to LB formation and neurodegeneration. Our work shows that C-terminal cleavage of aSyn fibrils at multiple sites is a conserved process that occurs rapidly after and during the formation of intracellular LB-like aSyn inclusions in all neuronal seeding models. Interestingly, blocking the cleavage of internalized fibrils does not influence their seeding activity, whereas inhibiting the enzymes that regulate the cleavage of newly formed fibrils (e.g., calpains 1 and 2) significantly alters the formation of LB-like inclusions. We also show that C-terminal truncations, in combination with other PTMs, play a crucial role in regulating the interactome and remodeling of newly formed aSyn fibrils, including their shortening, lateral association, and packing during LB formation and maturation. Altogether, our results demonstrate that post-fibrillization C-terminal truncations have a differential role at different stages of aSyn aggregation and pathology formation. These insights, combined with the abundance of truncated aSyn species in LBs, have significant implications in understanding aSyn pathological diversity and developing therapeutic strategies targeting the C-terminus of aSyn or its proteolytic processing.
+ Background: The combination of reduced choroidal blood flow, increased Bruchs membrane (BM) thickness and drusen formation leads to reduced oxygenation of the outer retina in the aging eye and contributes to the pathology of age-related macular degeneration (AMD). This implies that the molecular response of photoreceptors to hypoxia, with chronic activation of hypoxia-inducible factors (HIFs) at its core, impacts disease development and progression. Methods: We used the shRNAmiR system to develop a dual-acting gene therapy based on a single AAV that reduces activity of HIF1 in photoreceptors and HIF2 in the retinal pigment epithelium (RPE). The virus was injected subretinally in two models of pseudo (Rod{Delta}Vhl) or true (RPE{Delta}Vegfa) hypoxia-related retinal degeneration and treated mice were followed for up to 61 weeks post-injection. Light microscopy, fluorescence funduscopy, and optical coherence tomography were used to quantify the therapeutic effect. In situ hybridization, real-time PCR, Western blotting, immunofluorescence, and flatmounts of the retina, RPE, and choroid were used to investigate the disease models and therapeutic effects of the treatment. Results: No adverse effects were noted after subretinal injection of the AAV expressing shRNAs targeting Hif1a in photoreceptors and Hif2a in the RPE. The virus preserved ONL thickness and photoreceptor segment length in Rod{Delta}Vhl mouse retinas up to 22 weeks and in RPE{Delta}Vegfa mice up to 61 weeks after injection demonstrating a long-lasting rescue of the phenotype. The dual-acting virus showed significantly higher efficacy than single-acting viruses targeting solely Hif1a in photoreceptors or Hif2a in the RPE. Conclusion: This study introduces a novel dual-acting AAV vector that effectively downregulates two different genes in two specific cell types, offering a promising therapeutic strategy for complex diseases such as AMD. By simultaneously targeting Hif1a in photoreceptors and Hif2a in the retinal pigment epithelium, this gene-agnostic therapy shows significant potential to protect retinal tissues from chronic hypoxic conditions. By targeting a common and conserved disease pathway in AMD, it is applicable to a wide range of patients.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -366,11 +725,11 @@
- Chemical synapses control their strength through the nanoscale clustering of postsynaptic receptors into sub-synaptic domains (SSDs). Despite their importance in synapse function, the properties and plasticity of these domains are not well understood in vivo, particularly in inhibitory synapses. We used direct Stochastic Optical Resolution Microscopy (dSTORM) to show that Gephyrin, the main inhibitory receptor scaffold protein, is organised into SSDs in vivo, with distinct arrangements depending on their sub-cellular location and presynaptic partner. Furthermore, chronic chemogenetic increases in cortical activity caused a reduction in Gephyrin SSD volume specifically in axo-axonic, but not axo-dendritic, synapses. Functionally, this resulted in a weakening of axo-axonic contacts. We show that the nanoscale arrangement of synapses in the brain is plastic and used to fine-tune synaptic gain in vivo.
+ V4, an intermediate visual area in the ventral visual stream of primates, is known to contain neurons tuned to color, complex local patterns, shape, and texture. Neurons with similar visual attribute preferences are closely positioned on the cortical surface, forming a topological map. Recent studies based on multi-electrode arrays and calcium imaging revealed the macaque V4 has neuronal columns tuned to specific natural image features, and these columns are clustered into various functional domains. There are domains tuned to attributes generally associated with object surface properties such as texture or color, as well as domains associated with the shape and form of object boundaries reminiscent of the blobs and inter-blobs in the primary visual cortex. Here, we explored the computational constraints underlying the development of the V4 topological map. We found that the map learned based on self-organizing principles constrained by neuronal column's tuning and retinotopy position can account for many characteristics of the observed V4 map, including the interwoven organization of texture and shape processing clusters. These anatomical clustering, with the implied local recurrent connectivity, might facilitate a modular parallel processing of surfaces and boundaries of objects along the ventral visual system.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -380,11 +739,11 @@
- Background: Stroke is the sixth leading cause of death and lifelong disability for millions of people in the United States. Cerebral ischemia lead to in oxidative stress, excitotoxicity, inflammation, apoptosis and also, impairments in memory and learning occur in majority of subjects with ischemic stroke. Lack of definitive treatment has sparked extensive research into novel therapeutic strategies, including the use of 4-methylumbelliferone (4-MU), a coumarin derivative with potential neuroprotective properties. The present study examines impact of 4-MU on reducing cerebral ischemia-reperfusion (I/R) injury and learning and memory impairments in male Wistar rats. Method: The animal was exposed to middle cerebral artery occlusion (MCAO) and were cured with one dose of 4-MU (at dosage of 25 mg/kg) dissolved in DMSO 0.9%. Automated shuttle box test was employed to evaluate learning and memory impairments. Western blot assay, TTC staining and Nissl staining was used to measure protein expression, infarct volume, and cell death, respectively. Results: Results showed treatment with 4-MU reduced infarct volume and improved learning and memory impairments by down-regulation of HAS1 and HAS2. 4-MU has been shown to modulate the release of pro-inflammatory cytokines include TNF- and IL-1{beta}, as well as anti-inflammatory markers like IL-10 and also reduced oxidative stress markers in the brain. Conclusion: Generally, neuroprotective effects of 4-MU against cerebral I/R injury can be attributed to down-regulation of HAS1 and 2. Keywords: Ischemic stroke; MCAO; Learning and memory impairments; 4-methylumbelliferone; Neural death; Hyaluronan synthases
+ Brain magnetic resonance imaging (MRI) is essential for diagnosis and neurodevelopmental research, but the high cost and infrastructure demands of high-field MRI scanners restrict their use to high-income settings. To address this, more affordable and energy-efficient ultra-low-field MRI scanners have been developed. However, the reduced resolution and signal-to-noise ratio of the resulting scans limit their clinical utility, motivating the development of super-resolution techniques. The current state-of-the-art super-resolution methods require either three anisotropic ultra-low-field scans acquired at different orientations (axial, coronal, sagittal) to reconstruct a higher-resolution image using multi-resolution registration (MRR), or the training of deep learning super-resolution models using paired ultra-low- and high-field scans. Since acquiring three high-quality ultra-low-field scans is not always feasible, and paired high-field data may not be available for the target population, this study explores the efficacy of using a deep learning model, the 3D UNet, to generate higher-resolution brain scans from just one ultra-low-field scan. The model was trained to receive a single ultra-low-field brain scan of 6-month-old infants and produce a scan of MRR quality. Results showed a significant improvement in the quality of output scans compared to input scans, including increased image quality metrics, stronger correlations in tissue volume estimates across participants, and greater Dice overlap of the underlying tissue segmentations to those of target scans. The study demonstrates that the 3D UNet effectively enhances the resolution of ultra-low-field infant MRI scans. Generating higher-resolution brain scans from single ultra-low-field scans, without needing paired high-field data, reduces scanning time and supports wider MRI use in low- and middle-income countries. Additionally, this approach allows for easier model training on a site- and population-specific basis, enhancing adaptability in diverse settings.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -394,11 +753,11 @@
- Hippocampal area CA2 has emerged as a functionally and molecularly distinct part of the hippocampus and is necessary for several types of social behavior, including social aggression. As part of the unique molecular profile of both mouse and human CA2, the mineralocorticoid receptor (MR; Nr3c2) appears to play a critical role in controlling CA2 neuron cellular and synaptic properties. To better understand the fate (or state) of the neurons resulting from MR conditional knockout, we used a spatial transcriptomics approach. We found that without MRs, (CA2) neurons acquire a CA1-like molecular phenotype. Additionally, we found that neurons in this area appear to have a cell size and density more like that in CA1. These finding support the idea that MRs control at least CA2s state during development, resulting in a CA1-like fate.
+ Visual search, where observers search for a specific item, is a crucial aspect of daily human interaction with the visual environment. Hybrid search extends this by requiring observers to search for any item from a given set of objects. While there are models proficient at simulating human eye movement in visual search tasks within natural scenes, none are able to do so in Hybrid search tasks within similar environments. In this work, we present an enhanced version of the neural network Entropy Limit Minimization (nnELM) model, which is based on a Bayesian framework and decision theory. We also present the Hybrid Search Eye Movements (HSEM) Dataset, comprising several thousands of human eye movements during hybrid search tasks in natural scenes. A key challenge in Hybrid search, absent in visual search, is that participants might search for different objects at different time points. To address this, we developed a strategy based on the posterior probability distribution generated after each fixation. By adjusting the model's peripheral visibility, we made early search stages more efficient, aligning it closer to human behaviour. Additionally, limiting the model's memory capacity reduced its success in longer searches, mirroring human performance. To validate these improvements, we compared our model against participants from the HSEM dataset and against existing models in a visual search benchmark. Altogether, the new nnELM model not only successfully explains Hybrid search tasks, but also closely replicates human behaviour in natural scenes. This work advances our understanding of complex processes underlying visual and Hybrid search while maintaining model interpretability.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -408,11 +767,11 @@
- Direct electrical stimulation (DES) can advance our understanding of the intricate dynamics of the human hippocampo-neocortical network, which underlies complex cognitive processes such as spatial cognition and memory. This knowledge can help Neurotechnology to more effectively interface with this network and improve its functions. Here, we investigated the effects of DES in seven epilepsy patients under medical supervision recording single neuron activity alongside local field potentials to investigate neural responses to single pulses at different levels of granularity. Our results demonstrate that (i) single neurons respond to local electrical stimulation with a stereotypical pattern of short-lived increased excitation, followed by sustained inhibition, (ii) that input into the hippocampus from neocortex takes ~100 ms, and (iii) that output from the hippocampus to the neocortex is gated by theta phase. These results are vital to inform the optimal choice of parameters for future electrical stimulation studies targeting the human memory system.
+ Cortical circuits contain diverse sensory, motor, and cognitive signals, and form densely recurrent networks. This creates challenges for identifying causal relationships between neural populations and behavior. We developed a calcium imaging-based brain-machine interface (BMI) to study the role of posterior parietal cortex (PPC) in controlling navigation in virtual reality. By training a decoder to estimate navigational heading and velocity from PPC activity during virtual navigation, we discovered that mice could immediately navigate toward goal locations when control was switched to BMI. No learning or adaptation was observed during BMI, indicating that naturally occurring PPC activity patterns are sufficient to drive navigational trajectories in real time. During successful BMI trials, decoded trajectories decoupled from the mouse's physical movements, suggesting that PPC activity relates to intended trajectories. Our work demonstrates a role for PPC in navigation and offers a BMI approach for investigating causal links between neural activity and behavior.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -422,11 +781,11 @@
- Experiments with naturalistic stimuli (e.g., listening to stories or watching movies) are emerging paradigms in brain function research. The content of naturalistic stimuli is rich and continuous. The fMRI signals of naturalistic stimuli are complex and include different components. A major challenge is isolate the stimuli-induced signals while simultaneously tracking the brain's responses to these stimuli in real-time. To this end, we have developed a user-friendly graphical interface toolbox called NaDyNet (Naturalistic Dynamic Network Toolbox), which integrates existing dynamic brain network analysis methods and their enhanced versions. The main features of NaDyNet are: 1) extracting signals of interest from naturalistic fMRI signals; 2) incorporating six commonly used dynamic analysis methods and three static analysis methods; 3) enhanced versions of these dynamic methods by adopting inter-subject analysis to eliminate the effects of non-interest signals; 4) performing K-means clustering analysis to identify temporally reoccurring states along with their temporal and spatial attributes. We then introduced the rationale for incorporating inter-subject analysis to improve existing dynamic brain network analysis methods, and presented numerous examples. We also summarized research progress in comparing methodological efficacy, offered our recommendations for method selection in dynamic network analysis, and discussed the limitations of current approaches and directions for future research. We hope that this open source toolbox will promote the development of naturalistic neuroscience. The toolbox is available at https://github.com/yuanbinke/Naturalistic-Dynamic-Network-Toolbox.
+ While motor impairments have been extensively studied in Parkinson's Disease, rapid visuomotor transformations for flexible interaction with the environment have received surprisingly little attention. In recent years, such rapid visuomotor transformations have been studied in the form of express visuomotor responses (EVRs), which are goal-directed bursts of muscle activity that are thought to originate from superior colliculus, reaching the periphery via the tecto-reticulospinal pathway. Here, we examined EVRs in the lower limbs during goal-directed step initiation in 20 people with Parkison's Disease (PwPD) and 20 age-matched healthy control participants (HC). As lower-limb EVRs in the young have been shown to interact with postural control - which is often affected in PwPD - we manipulated the postural demands by varying initial stance width and target location. In the low postural demand condition, EVRs were robustly present in both the PwPD (17/20) and HC (16/20) group. However, when postural demands were high, EVRs were largely absent in both groups and, instead, strong anticipatory postural adjustments (APAs) were required prior to foot off. EVR magnitudes were, on average, stronger in PwPD compared to HC, but they decreased with increasing disease severity, suggesting that the EVR network may become compromised or down-regulated in later stages of the disease. While APA magnitudes were smaller in PwPD compared to HC, subsequent stepping performance (step reaction time, duration, size, velocity) was remarkably similar between the two groups. We suggest that the EVR network may be upregulated in the early stages of Parkinson's disease in order to compensate for some of the emerging motor deficits experienced in daily life.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -436,11 +795,11 @@
- State anxiety involves transient feelings of tension and nervousness in response to threats, which can escalate into anxiety disorders if persistent. Despite treatments, 30%-50% of individuals show limited improvement, and neurophysiological mechanisms of treatment responsiveness remain unclear, requiring the development of objective biomarkers. In this study, we monitored multimodal electrophysiological parameters: heart rate variability (high-frequency, low-frequency, LF/HF ratio), EEG beta and alpha relative power, and brain-to-heart connectivity in participants with real-life state anxiety. Participants underwent a therapeutic intervention combining virtual-reality immersion, hypnotic script, and a breath control exercise. Real-life state anxiety was captured using the STAI-Y1 scale before and after the intervention. We observed reduced anxiety immediately after the intervention in 16 out of 27 participants. While all participants, independently of their STAI-Y1 score, showed increased HRV low frequency power, only treatment-responders displayed increased overall autonomic tone (high and low frequency HRV), increased midline beta power and brain-to-heart connectivity. Notably, the LF/HF ratio showed a significant linear relationship with anxiety reduction, with higher ratios linked to greater therapeutic response. These findings suggest that increased cognitive regulation of brain-to-heart connectivity could serve as a biomarker for therapeutic efficacy, with elevated midline beta power facilitating improved cardiac tone in responders.
+ Objective: Brain infection with Theiler's virus (TMEV) in C57BL/6J mice produces an etiologically relevant model of acquired seizures. Dietary changes can modify acute seizure presentation following TMEV brain infection and influence intestinal microbiome diversity and composition. Intestinal dysbiosis may thus similarly affect seizure burden and antiseizure medicine (ASM) activity in this model, independent of pharmacokinetic effects. We thus sought to define the influence of antibiotic (ABX)-induced gut dysbiosis on acute seizure presentation, anticonvulsant activity of carbamazepine (CBZ), and CBZ pharmacokinetics with TMEV infection. Methods: Male C57BL/6J mice (4-5 weeks) received oral (p.o.) ABX or saline (SAL) once daily beginning on arrival through Day 7 post-TMEV infection (p.i.). Mice were infected with TMEV or PBS on Day 0. Mice received intraperitoneal (i.p.; 20 mg/kg) CBZ or vehicle (VEH) twice daily Days 3-7 p.i. and were assessed for handling-induced seizures 30 min after treatment. Plasma was collected on Day 7 p.i. at 15 and 60 min post-CBZ administration for bioanalysis. Results: TMEV infection induced acute seizures, but ABX-induced gut dysbiosis altered seizure presentation. There were 75% SAL-VEH, 35% SAL-CBZ, 35% ABX-VEH, and 72% ABX-CBZ mice with seizures during the 7-day monitoring period. There was a significant pretreatment x ASM interaction (p=0.0001), with differences in seizure burden in SAL- versus ABX-pretreated mice (p=0.004). CBZ significantly increased latency to seizure presentation; an effect absent in ABX-CBZ mice. Plasma CBZ concentrations did not differ between SAL and ABX pretreatment groups, suggesting that ABX did not influence CBZ pharmacokinetics. Significance: ABX-induced gut dysbiosis markedly altered acute disease trajectory with TMEV-induced encephalitis, reflecting a novel contribution of the gut microbiome to seizure presentation. ABX-induced gut dysbiosis also significantly changed acute seizure control by CBZ, but did not influence plasma CBZ concentrations. The gut-brain axis is thus an under-recognized contributor to TMEV infection-induced seizures, ASM activity, and disease burden.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -450,11 +809,11 @@
- Gamma synchrony is ubiquitous in visual cortex, but whether it contributes to perceptual grouping remains contentious based on observations that gamma frequency is not consistent across stimulus features and that gamma synchrony depends on distances between image elements. These stimulus dependencies have been argued to render synchrony among neural assemblies encoding components of the same object difficult. Alternatively, these dependencies may shape synchrony in meaningful ways. Using the theory of weakly coupled oscillators (TWCO), we demonstrate that stimulus dependence is crucial for gamma's role in perception. Synchronization among coupled oscillators depends on frequency dissimilarity and coupling strength, which in early visual cortex relate to local feature dissimilarity and physical distance, respectively. We manipulated these factors in a texture segregation experiment wherein human observers identified the orientation of a figure defined by reduced contrast heterogeneity compared to the background. Human performance followed TWCO predictions both qualitatively and quantitatively, as formalized in a computational model. Moreover, we found that when enriched with a Hebbian learning rule, our model also predicted human learning effects. Increases in gamma synchrony due to perceptual learning predicted improvements in behavioral performance across sessions. This suggests that the stimulus-dependence of gamma synchrony is adaptable to the statistics of visual experiences, providing a viable neural grouping mechanism that can improve with visual experience. Together our results highlight the functional role of gamma synchrony in visual scene segmentation and provide a mechanistic explanation for its stimulus-dependent variability.
+ Assessing the level of consciousness someone is in, is not a trivial question and physicians have to rely on behavioural evaluations instead of quantifiable metrics. Many studies have empirically investigated measures related to the complexity elicited after the brain is stimulated to quantify and assess the level of consciousness across different states. Here we hypothesized that the level of non-equilibrium dynamics of the unperturbed brain already contains the information needed to know how the system will react to an external stimulus. We created personalized whole-brain models fitted to resting state fMRI data recorded in participants in different states of reduced consciousness (such as deep sleep and disorders of consciousness) to infer the effective connections underlying their brain dynamics. We then measured the out-of-equilibrium nature of the unperturbed brain by evaluating the level of asymmetry of the inferred connectivity, the time irreversibility in each model and compared this with the elicited complexity generated after in silico perturbations. Crucially, we found that states of reduced consciousness had a lower level of asymmetry in their effective connectivities compared to control subjects, as well as a lower level of irreversibility in their simulated dynamics, and a lower complexity. We demonstrated that the asymmetry in the underlying connections drives the nonequilibrium state of the system and in turn the differences in complexity as a response to the external stimuli.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
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- Acute restraint stress is known to cause analgesia in humans and laboratory animals, but the mechanisms are unknown. Recently, we have shown that a multi-nodal circuitry between the dorsal lateral septum (dLS)-lateral hypothalamic area (LHA)-rostral ventromedial medulla (RVM) plays an instructive role in restraint stress-induced analgesia. We found that the LS neurons are activated when mice struggle to escape the restraint, and we wondered about the origin of the escape signals. Hence, we performed retrograde viral labeling from the LS and found that the ventrolateral periaqueductal gray (vlPAG), a known anatomical substrate for escape behaviors, provides inputs to the LS. Through anatomical, behavioral, and in-vivo fiber photometry, we show that the PAG and LS neurons are synaptically connected; activation of either PAG or the post-synaptic LS neurons is sufficient to cause analgesia and sufficiently cause hyperalgesia. Moreover, we found that the LS neurons that receive inputs from PAG send axonal projections to the LHA. Together, we found that the vlPAG neurons encoding nociceptive and escape behaviors provide synaptic inputs to the dLS-LHA-RVM circuitry to mediate acute restraint stress-induced analgesia.
+ Aromatherapy commonly uses odors to improve well-being through their evocation of positive emotions. Although knowledge in this area is often very empirical, the olfactory stimulus has different properties which, taken together, could explain why it can relax. First, olfactory sense have a direct access to the limbic system, without thalamic relay processing, which confers it a strong emotional valence. Second, when appreciated, odors can slow down breathing and cardiac rates. Third, when slow and deep, breathing can entrain brain activity, due to the mechano-sensitivity of olfactory receptors to airflows. We hypothesized that, thanks to these properties, pleasant odors could enhance the subjective feeling of relaxation, slow down body rhythms, and facilitate entrainment of brain activity by respiration. Comparing the effects of a personally pleasant odor to a personally pleasant music on psychological, physiological and neuronal responses, we showed a tendency for both odors and music to enhance subjective relaxation. However, only pleasant odors were able to 1) decrease heart rate while increasing its variability, and 2) decrease respiratory rate while enhancing the respiratory drive of brain activities, regardless of the music tempo. Overall, we demonstrated that the positive emotion evoked by a personally pleasant smell is sufficient to evoke an olfactomotor response, which, by slowing breathing, synchronizes respiration, fluctuations of heart rate and brain activity.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
@@ -478,11 +837,11 @@
- Neurons in the LHA are critical drivers of behavioral and physiological responses to acute and chronic stress. However, the roles of the specific pre-synaptic inputs to the LHA in driving stress and resultant physiological effects are yet to be fully understood. Here, taking advantage of mouse viral genetics, rabies tracing, optogenetics, chemogenetics, and fiber photometry, we show that the excitatory projections from the RVM to LHA drive stress-induced anxiety. This is a surprising finding since, traditionally, RVM has been studied in the context of opioidergic pain modulation through its inhibitory projections to the spinal cord. We find that the LHA neurons receiving inputs from the RVM, when activated, do not alter the nociceptive thresholds yet are sufficient to drive anxiety-like behaviors. These LHA neurons are recruited by acute restraint, which is known to cause stress. On the other hand, the LHA-projecting RVM neurons are responsive to both noxious thermal stimuli and acute restraint, promoting stress-induced anxiety, yet with no effect on pain thresholds. Together, we found an ascending neural pathway between RVM and LHA that mediates stress-induced anxiety.
+ Alpha-synuclein (aSyn) post-translational modifications (PTMs), particularly phosphorylation at serine 129 and C-terminal truncations, are highly enriched in Lewy bodies (LBs), Lewy neurites, and other types of aSyn pathological aggregates in the brain of patients with Parkinson's disease (PD) and other synucleinopathies. However, our knowledge about the precise role of PTMs in regulating the different stages of pathology formation, neurodegeneration, and aSyn pathology spreading remains incomplete. In this work, we applied a systematic approach to address this knowledge gap with an emphasis on mapping and elucidating the role of post-fibrillization C-terminal aSyn truncations in regulating the uptake, processing, seeding activity, and formation of LB-like inclusions and maturations in a well-established neuronal seeding model that recapitulates all the stages leading to LB formation and neurodegeneration. Our work shows that C-terminal cleavage of aSyn fibrils at multiple sites is a conserved process that occurs rapidly after and during the formation of intracellular LB-like aSyn inclusions in all neuronal seeding models. Interestingly, blocking the cleavage of internalized fibrils does not influence their seeding activity, whereas inhibiting the enzymes that regulate the cleavage of newly formed fibrils (e.g., calpains 1 and 2) significantly alters the formation of LB-like inclusions. We also show that C-terminal truncations, in combination with other PTMs, play a crucial role in regulating the interactome and remodeling of newly formed aSyn fibrils, including their shortening, lateral association, and packing during LB formation and maturation. Altogether, our results demonstrate that post-fibrillization C-terminal truncations have a differential role at different stages of aSyn aggregation and pathology formation. These insights, combined with the abundance of truncated aSyn species in LBs, have significant implications in understanding aSyn pathological diversity and developing therapeutic strategies targeting the C-terminus of aSyn or its proteolytic processing.
in bioRxiv: Neuroscience on 2024-11-30 00:00:00 UTC.
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- Journal of Neurophysiology, Ahead of Print.
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- in Journal of Neurophysiology on 2024-11-29 03:59:58 UTC.
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- Paternal obesity has been implicated in adult-onset metabolic disease in offspring. However, the molecular mechanisms driving these paternal effects and the developmental processes involved remain poorly understood. One underexplored possibility is the role of paternally-induced effects on placenta development and function. To address this, we investigated paternal high-fat diet-induced obesity in relation to sperm histone H3 lysine 4 tri-methylation signatures, the placenta transcriptome and cellular composition. C57BL6/J male mice were fed either a control or high-fat diet for 10 weeks beginning at 6 weeks of age. Males were timed-mated with control-fed C57BL6/J females to generate pregnancies, followed by collection of sperm, and placentas at embryonic day (E)14.5. Chromatin immunoprecipitation targeting histone H3 lysine 4 tri-methylation (H3K4me3) followed by sequencing (ChIP-seq) was performed on sperm to define obesity-associated changes in enrichment. Paternal obesity corresponded with altered sperm H3K4me3 at promoters of genes involved in metabolism and development. Notably, sperm altered H3K4me3 was also localized at placental enhancers. Bulk RNA-sequencing on placentas revealed paternal obesity-associated sex-specific changes in expression of genes involved in hypoxic processes such as angiogenesis, nutrient transport, and imprinted genes, with a subset of deregulated genes showing changes in H3K4me3 in sperm at corresponding promoters. Paternal obesity was also linked to impaired placenta development; specifically, a deconvolution analysis revealed altered trophoblast cell lineage specification. These findings implicate paternal obesity-effects on placenta development and function as one potential developmental route to offspring metabolic disease.
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- The biosynthesis of cyclic 3′,5′-adenosine monophosphate (cAMP) by mammalian membrane-bound adenylyl cyclases (mACs) is predominantly regulated by G-protein-coupled receptors (GPCRs). Up to now the two hexahelical transmembrane domains of mACs were considered to fix the enzyme to membranes. Here, we show that the transmembrane domains serve in addition as signal receptors and transmitters of lipid signals that control Gsα-stimulated mAC activities. We identify aliphatic fatty acids and anandamide as receptor ligands of mAC isoforms 1–7 and 9. The ligands enhance (mAC isoforms 2, 3, 7, and 9) or attenuate (isoforms 1, 4, 5, and 6) Gsα-stimulated mAC activities in vitro and in vivo. Substitution of the stimulatory membrane receptor of mAC3 by the inhibitory receptor of mAC5 results in a ligand inhibited mAC5–mAC3 chimera. Thus, we discovered a new class of membrane receptors in which two signaling modalities are at a crossing, direct tonic lipid and indirect phasic GPCR–Gsα signaling regulating the biosynthesis of cAMP.
+ Journal of Neurophysiology, Ahead of Print.
- in eLife on 2024-11-29 00:00:00 UTC.
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in Journal of Neurophysiology on 2024-11-29 03:59:58 UTC.
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- Despite significant deficits in voluntary motor control, patients with Parkinson's disease (PD) can generate reflexive or stimulus-driven movements. How are such spared capabilities realized? Here, we recorded upper limb muscle activity in patients with PD and age-matched healthy controls (HCs) as they reached either toward or away from a visual stimulus. The task promoted express visuomotor responses (EVRs), which are brief bursts of muscle recruitment time-locked (<100 ms) to stimulus presentation that are thought to originate from the midbrain superior colliculus. Across two experiments, we observed a remarkable sparing of the latency and magnitude of EVRs in patients with PD, but a decreased ability for patients with PD to contextually modulate the EVR depending on trial instruction. EVR Magnitudes were strikingly strongly correlated with PD Reaction times and Error rates, despite compromised levels of electromyographic (EMG) recruitment in subsequent phases of muscle activity, which predicted lower Peak velocities. Our results are consistent with a differential influence of PD on parallel-but-interacting subcortical and cortical pathways that converge onto brainstem and spinal circuits during reaching. This differential influence is discriminable even within a single trial in the selective sparing of stimulus-aligned but not movement-aligned muscle recruitment, and has implications for our understanding of the motor and cognitive deficits seen in PD.
+ -/-
- in bioRxiv: Neuroscience on 2024-11-29 00:00:00 UTC.
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in eLife on 2024-11-29 00:00:00 UTC.
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- Insomnia disorder is the most common sleep disorder, and neuroimaging research indicates that it is related to dysfunction in large-scale brain networks. Recently developed methods have enabled the investigation of the dynamic aspects of brain activity varying over time. In the present study, we used a novel data-driven approach to evaluate time-varying brain activity in adults with insomnia disorder compared to matched controls with no sleep problems. We acquired ten minutes resting state functional magnetic resonance images and T1-weighed images in all participants. We used Hidden Markov modelling for a data-driven definition of dynamic changes in whole-brain activity. The results showed that insomnia disorder is characterised by reduced switching rates between brain states. In line with the reduced switching, the HMM analyses suggested reduced prevalence of two whole-brain states - the default mode network and a fronto-parietal network - and an increase in just one brain state - a global activation state - in insomnia patients compared to controls. The findings suggest that insomnia disorder is characterised by less flexible transitions between brain states at wakeful rest, and thus highlight the importance of evaluating the spatiotemporal dynamics of brain activity to advance the understanding of the neural underpinnings of insomnia disorder.
+ Paternal obesity has been implicated in adult-onset metabolic disease in offspring. However, the molecular mechanisms driving these paternal effects and the developmental processes involved remain poorly understood. One underexplored possibility is the role of paternally-induced effects on placenta development and function. To address this, we investigated paternal high-fat diet-induced obesity in relation to sperm histone H3 lysine 4 tri-methylation signatures, the placenta transcriptome and cellular composition. C57BL6/J male mice were fed either a control or high-fat diet for 10 weeks beginning at 6 weeks of age. Males were timed-mated with control-fed C57BL6/J females to generate pregnancies, followed by collection of sperm, and placentas at embryonic day (E)14.5. Chromatin immunoprecipitation targeting histone H3 lysine 4 tri-methylation (H3K4me3) followed by sequencing (ChIP-seq) was performed on sperm to define obesity-associated changes in enrichment. Paternal obesity corresponded with altered sperm H3K4me3 at promoters of genes involved in metabolism and development. Notably, sperm altered H3K4me3 was also localized at placental enhancers. Bulk RNA-sequencing on placentas revealed paternal obesity-associated sex-specific changes in expression of genes involved in hypoxic processes such as angiogenesis, nutrient transport, and imprinted genes, with a subset of deregulated genes showing changes in H3K4me3 in sperm at corresponding promoters. Paternal obesity was also linked to impaired placenta development; specifically, a deconvolution analysis revealed altered trophoblast cell lineage specification. These findings implicate paternal obesity-effects on placenta development and function as one potential developmental route to offspring metabolic disease.
- in bioRxiv: Neuroscience on 2024-11-29 00:00:00 UTC.
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in eLife on 2024-11-29 00:00:00 UTC.
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- Internalizing problems are associated with a wide range of adverse outcomes. While we have some understanding about risk factors (e.g., neurodevelopmental conditions), biological markers are not well understood. Here, we used deep learning to predict cross-sectional (N=14,523) and worsening longitudinal trajectories (N=10,540) of internalizing problems from measures of brain structure. A stratified cross-validation scheme was used, and performance was evaluated using the area under the receiving operating characteristic curve (AUC). The cross-sectional model performed well across the sample, reaching an AUC of 0.80 [95% CI: 0.71, 0.88]. For the longitudinal model, while performance was sub-optimal for predicting worsening trajectories in a sample of the general population (AUC=0.66 [0.65, 0.67]), good performance was reached across individuals with a neurodevelopmental condition (AUC=0.73 [0.70, 0.76]). Deep learning with features of brain structure is a promising avenue for biomarkers of internalizing problems, particularly for individuals who have a higher likelihood of experiencing difficulties.
+ The biosynthesis of cyclic 3′,5′-adenosine monophosphate (cAMP) by mammalian membrane-bound adenylyl cyclases (mACs) is predominantly regulated by G-protein-coupled receptors (GPCRs). Up to now the two hexahelical transmembrane domains of mACs were considered to fix the enzyme to membranes. Here, we show that the transmembrane domains serve in addition as signal receptors and transmitters of lipid signals that control Gsα-stimulated mAC activities. We identify aliphatic fatty acids and anandamide as receptor ligands of mAC isoforms 1–7 and 9. The ligands enhance (mAC isoforms 2, 3, 7, and 9) or attenuate (isoforms 1, 4, 5, and 6) Gsα-stimulated mAC activities in vitro and in vivo. Substitution of the stimulatory membrane receptor of mAC3 by the inhibitory receptor of mAC5 results in a ligand inhibited mAC5–mAC3 chimera. Thus, we discovered a new class of membrane receptors in which two signaling modalities are at a crossing, direct tonic lipid and indirect phasic GPCR–Gsα signaling regulating the biosynthesis of cAMP.
- in bioRxiv: Neuroscience on 2024-11-29 00:00:00 UTC.
+
in eLife on 2024-11-29 00:00:00 UTC.
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