This concise idea has become a central frame of reference for understanding cortical computation. Yet, it stands in contrast to many models of sensory processing. Since Hartline first described lateral inhibition in the retina

(Hartline, 1949), lateral inhibition has been either found experimentally or proposed on theoretical grounds to operate in almost every sensory modality, and at every level of the brain, from the sensory periphery to cognitive and perceptual processing. It has been invoked to sculpt the crude selectivity of excitatory inputs for everything from sound frequency, to odorants, to phonemes. Hubel and Wiesel’s model, by its omission, raises the question find more of whether, and how, inhibition contributes to generating the quintessential feature of cortical receptive fields. A number of cortical receptive field properties have seemed at odds with the simple account provided by Hubel and Wiesel. These response properties have challenged the essence of the feedforward model and forced a critical evaluation of the mechanisms underlying cortical computation. Most of the nonlinear response properties discussed here can be described quantitatively within a theoretical framework in which the feedforward synaptic drive is normalized by a signal related to stimulus

contrast (Carandini and Heeger, 2012, Carandini et al., 1997, Geisler and Albrecht, 1992 and Heeger, 1992). Formally,

the response, R, of a cortical neuron can be described as: R=Rmax[hcc502+c2]nwhere h is the linear, orientation-selective, feedforward drive, c is stimulus SKI-606 ic50 contrast, and c50 is the contrast at which R reaches half its maximal value (Rmax). With proper selection of parameters, this one equation can fit the complete array of simple cell behaviors, including contrast saturation, cross-orientation inhibition, and surround suppression. The equation itself is agnostic regarding the mechanism underlying contrast-dependent normalization; the normalization computation fits simple cell behavior well regardless of the origin of the contrast-dependent normalization signal (Carandini and Heeger, 1994). One widely discussed mechanism is shunting inhibition, in which contrast-dependent changes in input resistance scale the depolarization Olopatadine generated by the feedforward drive. Inhibition could arise either from pooling the input from orientation-specific interneurons with a range of preferred orientations or from interneurons that are unselective for orientation (Azouz et al., 1997, Cardin et al., 2007 and Hirsch et al., 2003). In addition, the change in input conductance, through its effect on the membrane time constant, τ, could account for the temporal nonlinearities of simple cells (contrast-dependent changes in preferred temporal frequency and response phase).