To understand the representation, storage, and processing of information by neural systems, it is essential to study the dynamic behavior of large populations of coupled neurons. These studies are augmented by techniques for decoding information represented in neuronal spike trains. Neural population decoding methods have been applied to studies of motor, posterior parietal, and inferotemporal cortex in monkeys. Using this approach we have proposed a mechanism by which attention can modulate visual receptive fields for object recognition. We have also developed a model of primary visual cortex in which recurrent network connections generate complex cell responses.
Synapses exhibit different forms of plasticity over a wide range of time scales.
Methods have been developed for accurately describing the short-term plasticity seen at intracortical synapses. The resulting descriptions have been incorporated into a model of simple cells in primary visual cortex to explore the origins of direction selectivity and contrast adaptation. Synaptic depression and cortical gain control. Synaptic Depression and the Temporal Response Characteristics of V1 Simple Cells. Complex Cells as Simple Cells at High Cortical Gain.