Example of a brain constrained network and its corresponding cortical areas. The network is used for simulating word processing and semantic learning in the human brain. For explanation, please see text below (adapted from Pulvermüller et al., 2021).

The brain model used in the MatCo project consists of twelve cortical areas. The perisylvian language network is represented by three auditory (primary auditory cortex, auditory belt, modality-general parabelt) and three articulatory areas (primary motor cortex, inferior premotor cortex, multimodal prefrontal motor cortex). In addition to the perisylvian language network, we model several extrasylvian sensorimotor areas that have been shown to contribute to language processing: three visual (primary visual cortex, temporo-occipital areas, anterior-temporal areas) and three motor areas (lateral primary motor cortex, premotor cortex, prefrontal cortex).

The areas are connected according to existing anatomical pathways in the brain, utilizing direct neighbor-to-neighbor connections (black arrows), long-distance cortico-cortical connections (purple arrows) and 'jumping' links connecting non-adjacent areas (blue arrows).

The black rectangles in the diagram display neuronal activity in the respective cortical area for a network learning action and object words: each colored pixel is an active neuron.