Inhibition, spike threshold, and stimulus selectivity in primary visual cortex.

By Nicholas J. Priebe, D. Ferster. 2008

380 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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Citations in the corpus

Normalization as a canonical neural computation (2011, background): “This operation has multiple key roles: maintaining sensory selectivit”
Foundations of Vision (2018, background): “…cells in the feedforward input layer of V1 retain their strong orientation selectivity after V1 is cooled or silenced, implying that the sum of excitatory inputs from LGN to V1 is enough to create this oriented receptive-field structure (Ferster, Chung, & Wheat, 1996; Priebe & Ferster, 2008).”
How Inhibition Shapes Cortical Activity (2011, positive): “…of stimulus features still applies to cortical tuning: namely, that synaptic excitation to a preferred stimulus roughly shapes the tuning of a cell's spike output and that tuning is further sharpened by robust synaptic inhibition in response to nonpreferred stimuli (Priebe and Ferster, 2008).”
Odor representations in olfactory cortex: "sparse" coding, global inhibition, and oscillations. (2009, background): “This difference in the relative timing of excitation and inhibition is proposed to shape stimulus selectivity and precisely timed spike output (Priebe and Ferster, 2008; Wehr and Zador, 2003; Wilent and Contreras, 2005).”
Inhibitory Stabilization of the Cortical Network Underlies Visual Surround Suppression (2009, background): “Lateral inhibition may thus be implemented through a network mechanism that leads to a reduction in local recurrent excitation together with a paradoxical decrease in synaptic inhibition, rather than the expected increase in inhibition.”
Highly Selective Receptive Fields in Mouse Visual Cortex (2008, background): “Numerous factors have been identified that could explain this property, including recurrent connectivity, inhibition, membrane potential fluctuations attributable to background activity, and the spike threshold, among others (Sompolinsky and Shapley, 1997; Ferster and Miller, 2000; Shapley et al., 2”
GABAA inhibition controls response gain in visual cortex (2011, positive): “Intracellular measurements support this notion but also indicate that noise in the membrane potential (which we ignored) smoothes the threshold and turns it into an exponent (Carandini and Ferster, 2000; Carandini, 2004; Priebe and Ferster, 2008).”
The Normalization Model of Attention (2009, background): “It can be implemented either through feedforward (Carandini et al., 2002; Priebe and Ferster, 2008) or feedback connections (Carandini et al.”