diff --git a/docs/src/tutorials/spectralDCM.jl b/docs/src/tutorials/spectralDCM.jl
index d92c9560..b1781f0b 100644
--- a/docs/src/tutorials/spectralDCM.jl
+++ b/docs/src/tutorials/spectralDCM.jl
@@ -72,7 +72,7 @@ end
 
 # ## Run the simulation and plot the results
 
-# setup simulation of the model, time in milliseconds
+# setup simulation of the model, time in seconds
 tspan = (0.0, 512.0)
 prob = SDEProblem(simmodel, [], tspan)
 dt = 2   # 2 seconds (units are milliseconds) as measurement interval for fMRI
@@ -155,7 +155,7 @@ for (i, idx) in enumerate(CartesianIndices(A_prior))
 end
 # we avoid simplification of the model in order to exclude some parameters from fitting
 @named fitmodel = system_from_graph(g, simplify=false)
-# With the function `changetune` we can provide a dictionary of parameters whose tunable flag should be changed, for instance set to false to exclude them from the optimizatoin procedure.
+# With the function `changetune`` we can provide a dictionary of parameters whose tunable flag should be changed, for instance set to false to exclude them from the optimizatoin procedure.
 # For instance the the effective connections that are set to zero in the simulation:
 untune = Dict(A[3] => false, A[7] => false)
 fitmodel = changetune(fitmodel, untune)                 # 3 and 7 are not present in the simulation model
diff --git a/src/datafitting/spDCM_VL.jl b/src/datafitting/spDCM_VL.jl
index 75d2cfd2..3594d92e 100644
--- a/src/datafitting/spDCM_VL.jl
+++ b/src/datafitting/spDCM_VL.jl
@@ -311,7 +311,7 @@ function integration_step(dfdx, f, v, solenoid=false)
         Q  = Q/opnorm(Q, 2)/8;
 
         f  = f  - Q*f;
-        dfdx = dfdx - Q*dfdx;
+        dfdx = dfdx - Q*dfdx;        
     end
 
     # (expm(dfdx*t) - I)*inv(dfdx)*f ~~~ could also be done with expv (expv(t, dFdθθ, dFdθθ \ dFdθ) - dFdθθ \ dFdθ) but doesn't work with Dual.
@@ -320,9 +320,9 @@ function integration_step(dfdx, f, v, solenoid=false)
     t = exp(v - spm_logdet(dfdx)/n)
 
     if t > exp(16)
-        dx = - dfdx \ f    # -inv(dfdx)*f
+        dx = - dfdx \ f   # -inv(dfdx)*f
     else
-        dx = (exp(t * dfdx) - I) * inv(dfdx)*f    # (expm(dfdx*t) - I)*inv(dfdx)*f
+        dx = (exp(t * dfdx) - I) * inv(dfdx)*f # (expm(dfdx*t) - I)*inv(dfdx)*f
     end
 
     return dx