title: Role of interneuron diversity in the cortical microcircuit for attention.
abstract: Receptive fields of neurons in cortical area V4 are large enough to fit multiple stimuli, making V4 the ideal place to study the effects of selective attention at the single-neuron level. Experiments have revealed evidence for stimulus competition and have characterized the effect thereon of spatial and feature-based attention. We developed a biophysical model with spiking neurons and conductance-based synapses. To account for the comprehensive set of experimental results, it was necessary to include in the model, in addition to regular spiking excitatory (E) cells, two types of interneurons: feedforward interneurons (FFI) and top-down interneurons (TDI). Feature-based attention was mediated by a projection of the TDI to the FFI, stimulus competition was mediated by a cross-columnar excitatory connection to the FFI, whereas spatial attention was mediated by an increase in activity of the feedforward inputs from cortical area V2. The model predicts that spatial attention increases the FFI firing rate, whereas feature-based attention decreases the FFI firing rate and increases the TDI firing rate. During strong stimulus competition, the E cells were synchronous in the beta frequency range (15-35 Hz), but with feature-based attention, they became synchronous in the gamma frequency range (35-50 Hz). We propose that the FFI correspond to fast-spiking, parvalbumin-positive basket cells and that the TDI correspond to cells with a double-bouquet morphology that are immunoreactive to calbindin or calretinin. Taken together, the model results provide an experimentally testable hypothesis for the behavior of two interneuron types under attentional modulation.
authors.affiliation: Computational Neurophysics Laboratory, Physics and Astronomy Department, University of North Carolina, Chapel Hill, NC 27599-3255, USA.
authors.forename: Calin I
authors.initials: CI
authors.lastname: Buia
authors.forename: Paul H
authors.initials: PH
authors.lastname: Tiesinga
mesh_terms: D000465:Algorithms; D001288:Attention / Q000502:physiology*; D001611:Beta Rhythm; D064032:Calbindin 2; D064026:Calbindins; D015350:Contrast Sensitivity; D004594:Electrophysiology; D005246:Feedback / Q000502:physiology; D005556:Form Perception / Q000502:physiology; D007395:Interneurons / Q000502:physiology*; D008564:Membrane Potentials / Q000502:physiology; D016571:Neural Networks, Computer; D010775:Photic Stimulation; D011963:Receptors, GABA-A / Q000502:physiology; D064030:S100 Calcium Binding Protein G / Q000502:physiology; D013028:Space Perception / Q000502:physiology; D014793:Visual Cortex / Q000166:cytology / Q000502:physiology*
chemical_list: D064032:Calbindin 2; D064026:Calbindins; D011963:Receptors, GABA-A; D064030:S100 Calcium Binding Protein G