title: Dynamic properties of recurrent inhibition in primary visual cortex: contrast and orientation dependence of contextual effects.
abstract: A fundamental feature of neural circuitry in the primary visual cortex (V1) is the existence of recurrent excitatory connections between spiny neurons, recurrent inhibitory connections between smooth neurons, and local connections between excitatory and inhibitory neurons. We modeled the dynamic behavior of intermixed excitatory and inhibitory populations of cells in V1 that receive input from the classical receptive field (the receptive field center) through feedforward thalamocortical afferents, as well as input from outside the classical receptive field (the receptive field surround) via long-range intracortical connections. A counterintuitive result is that the response of oriented cells can be facilitated beyond optimal levels when the surround stimulus is cross-oriented with respect to the center and suppressed when the surround stimulus is iso-oriented. This effect is primarily due to changes in recurrent inhibition within a local circuit. Cross-oriented surround stimulation leads to a reduction of presynaptic inhibition and a supraoptimal response, whereas iso-oriented surround stimulation has the opposite effect. This mechanism is used to explain the orientation and contrast dependence of contextual interactions in primary visual cortex: responses to a center stimulus can be both strongly suppressed and supraoptimally facilitated as a function of surround orientation, and these effects diminish as stimulus contrast decreases.
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
authors.forename: V
authors.initials: V
authors.lastname: Dragoi
authors.forename: M
authors.initials: M
authors.lastname: Sur
mesh_terms: D000818:Animals; D003198:Computer Simulation; D005829:Geniculate Bodies / Q000166:cytology / Q000502:physiology; D009433:Neural Inhibition / Q000502:physiology*; D016571:Neural Networks, Computer; D009475:Neurons, Afferent / Q000502:physiology; D009949:Orientation / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D014793:Visual Cortex / Q000166:cytology / Q000502:physiology*; D014795:Visual Pathways / Q000166:cytology / Q000502:physiology