Neural circuit models for computations in early visual cortex

Some cortical circuit models study the mechanisms of the transforms from visual inputs to neural responses. They model neural properties such as feature tunings, pattern sensitivities, and how they depend on intracortical connections and contextual inputs. Other cortical circuit models are more concerned with computational goals of the transform from visual inputs to neural responses, or the roles of the neural responses in the visual behavior. The appropriate complexity of a cortical circuit model depends on the question asked. Modeling neural circuits of many interacting hypercolumns is a necessary challenge, which is providing insights to cortical computations, such as visual saliency computation, and linking physiology with global visual cognitive behavior such as bottom-up attentional selection.

► Three examples of cortical circuit models are presented, their complexity ranges from low to high. ► The complexity of a cortical circuit model should be suitable to the research question asked. ► Some models focus on the mapping from visual inputs to responses in single neurons. ► Some models are interested in linking global neural population responses to visual cognition. ► Modeling neural circuits of many interacting hypercolumns is a necessary and promising challenge.