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Synaptic learning rules for local synaptic interactions : theory and application to direction selectivity

Mo, Chunhui (2003) Synaptic learning rules for local synaptic interactions : theory and application to direction selectivity. PhD thesis, California Institute of Technology.

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This thesis is organized in two parts, both concerned with local synaptic interactions within the dendritic tree. The first part is focused on how specific synaptic arrangements that can be used to compute direct ion selectivity can be learned in an unsupervised manner. The second part consists of a double synaptic veto model that can account for the observed reverse-phi selectivity of direction-selective cells. We propose an activity-based, local learning model that may account for the direction selectivity in neurons in the visual cortex based on the local veto operation among excitation and inhibition. We implement the learning rule with local calcium concentration changes and a BCM type learning curve (Bienenstock, Cooper and Munro, 1982). Our biophysical simulations suggest that a model cell implementing our learning algorithm develops direction selectivity organically after unsupervised training. The learning rule is also applicable to cells with multiple direction-selective subunits on dendrites and is stable under a number of starting conditions. Reverse-phi motion is the illusory reversal of perceived direction of movement when the stimulus contrast is reversed in successive frames. Livingstone (2000) showed that direction-selective cells in striate cortex of the alert macaque monkey showed reversed excitatory and inhibitory regions when two different contrast bars were flashed sequentially during a two-bar interaction analysis. We carry out detailed biophysical simulations of a direction-selective cell model implementing a synaptic shunting scheme. Our results suggest that a simple synaptic-veto mechanism with strong direction selectivity for normal motion cannot account for the observed reverse phi-motion effect. A direct interaction between the ON and OFF pathway, missing in the original shunting-inhibition model, is essential to account for the reversal of response. We propose a double synaptic-veto mechanism in which ON excitatory synapses are gated by both delayed ON inhibition at their null side and by delayed OFF inhibition at their preferred side. The converse applies to OFF excitatory synapses. Mapping this scheme onto the dendrites of a direction-selective neuron permits the model to respond best to normal motion in its preferred direction and to reverse-phi motion in its null direction.

Item Type:Thesis (PhD)
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URLURL TypeDescription ItemCaltechTHESIS
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Group:Koch Laboratory (KLAB)
Subject Keywords:direction selective; learning; modeling; motion; reverse-phi
Record Number:CaltechAUTHORS:20130816-103257003
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:40594
Deposited By: KLAB Import
Deposited On:16 Jan 2008 02:09
Last Modified:03 Oct 2019 05:14

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