The differentiation of neural activity in the primary visual cortex (V1) for the edges and surface regions of stimuli is a key feature in representing visual information. This differentiation is closely related to the phenomenon of surface inhibition, where neural activity in central surface regions is suppressed relative to edges of square stimuli. However, due to the challenges in manipulating biological experiments and the limitations of simplified models, the detailed synaptic-level analysis of the regulatory mechanisms underlying this differentiation has not been revealed. In this study, a visual information transmission pathway from visual stimuli to the lateral geniculate nucleus (LGN) of the thalamus, and further to the input and output layers of V1, is constructed by using real biological anatomical data to investigate the regulatory mechanisms underlying the aforementioned neural activity differentiation. The model successfully replicates the surface inhibition characteristics observed in biological experiments: the input layer exhibits relatively uniform responses to both surface and edge stimuli, while the output layer shows strong activity in edge regions and suppressed activity in central surface regions, creating a "hole" effect. Through control experiments—specifically, by eliminating long-range connections in L2/3—we find that long-range connections in layer 2/3 of V1 are the necessary conditions for generating the surface inhibition phenomenon within this layer. Furthermore, modulating either the proportion or the spatial distribution of long-range connections in L2/3 can exert regulatory effects on the surface inhibition phenomenon. This not only facilitates our understanding of the neural mechanisms underlying visual processing but also demonstrates the advantages of computational modeling in elucidating internal cortical mechanisms that are difficult to manipulate in biological experiments.

Biological experiments targeting the mammalian primary visual cortex have shown that neuronal response to a preferred orientation grating is cross-inhibited by an orthogonal orientation mask grating. The plaid formed by the overlap of the two gratings not only causes a decrease in the neuronal firing rate but also shifts the gamma oscillation to a weaker oscillation at a higher frequency. The mechanism for the above phenomena is unclarified. In this paper, a large-scale cortical neuronal network model with biological details is constructed. In this model, two modes of connectivity that may contribute to cross-inhibition are considered: the thalamo-cortical feedforward pathway and the push-pull organization of cortical layer 4. Based on this model, the modulation of firing rate and gamma oscillation by a plaid stimulation are successfully reproduced, which is consistent with biological experiments and suggests that it is the thalamo-cortical feedforward pathway that leads to cross-inhibition. Furthermore, our analysis of the neuronal spike clusters and current fluctuations suggests that the push-pull organization leads to an increase in gamma frequency during the transition of visual stimuli from grating to plaid by modulating the source of synaptic inhibition in local neuronal populations. Such results will help to understand the visual processing under multi-input integration.