Topic: Dynamic Causal Model

Selective attention implements the preferential routing of attended stimuli, likely through increasing the gain of the respective synaptic inputs to higher-area neurons. As the synaptic inputs conveying competing stimuli converge and intermingle on postsynaptic neurons, impeding selective attentional addressing, presynaptic circuits might be the best target of top-down signals from higher areas of attentional control. If those signals enabled presynaptic circuits to selectively entrain postsynaptic neurons, this would be a mechanism for selective routing in accordance with the Communication-th

The characterization of brain activity has become a cornerstone of neuroscience to study cognition and neuropathologies. Here we focus on models of neural masses that aim to fit neurophysiological signals like EEG and MEG, in particular by optimizing interactions between brain regions, following previous work on the dynamic causal model (DCM) . We compare several modern Bayesian inference schemes for model inversion on simulated data . We benchmark the identifiability of local parameters governing the interplay between several neuronal populations in each region, as well as global parameters t