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Abstract

In this work we propose a biologically realistic local cortical circuit model (LCCM), based on neural masses, that incorporates
important aspects of the functional organization of the brain that have not been covered by previous models: (1) activity
dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2) realistic interlaminar
dynamics via laminar-specific distribution of and connections between neural populations. The potential of the
LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using
Bayesian inference. It was found that: (1) besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer
5/6), there exists a parallel ‘‘short-cut’’ pathway (layer 4 to layer 5/6), (2) the excitatory signal flow from the pyramidal cells to
the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory
interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3) the habituation rates of the
connections are unsymmetrical: forward connections (from layer 4 to layer 2/3) are more strongly habituated than backward
connections (from Layer 5/6 to layer 4). Our evaluation demonstrates that the novel features of the LCCM are of crucial
importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes
them applicable to modeling based on macroscopic data (like EEG or MEG), which are usually available in human
experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function.