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" Analyzing Statistical Dependencies in Neural Populations "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 150837
Doc. No : ET22629
Main Entry : Ilan N. Goodman
Title Proper : Analyzing Statistical Dependencies in Neural Populations
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Neurobiologists recently developed tools to record from large populations of neurons,and early results suggest that neurons interact to encode information jointly. However, tra-ditional statistical analysis techniques are inadequate to elucidate these interactions. Thisthesis develops two multivariate statistical dependence measures that, unlike traditionalmeasures, encompass all high-order and non-linear interactions. These measures decom-pose the contributions of distinct subpopulations to the total dependence. Applying thedependence analysis to recordings from the crayfish visual system, I show that neural pop-ulations exhibit complex dependencies that vary with the stimulus. Using Fisher infor-mation to analyze the effectiveness of population codes, I show that optimal rate coding....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL45853.pdf
Title and statement of responsibility and : Analyzing Statistical Dependencies in Neural Populations [Thesis]
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TL45853.pdf
TL45853.pdf
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