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Scene VisionMaking Sense of What We See$
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Kestutis Kveraga and Moshe Bar

Print publication date: 2014

Print ISBN-13: 9780262027854

Published to MIT Press Scholarship Online: May 2015

DOI: 10.7551/mitpress/9780262027854.001.0001

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A Statistical Modeling Framework for Investigating Visual Scene Processing in the Human Brain

A Statistical Modeling Framework for Investigating Visual Scene Processing in the Human Brain

Chapter:
(p.225) 11 A Statistical Modeling Framework for Investigating Visual Scene Processing in the Human Brain
Source:
Scene Vision
Author(s):

Dustin E. Stansbury

Jack L. Gallant

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262027854.003.0011

This chapter presents an effective framework for developing models of visual processing based on natural scene statistics to examine the representation of natural scene categories in the later stages of the human visual system. Integrating statistical analysis of natural scenes (SANS) into the network offers an unbiased method for creating hypothetical feature spaces that match linearized modeling. Meanwhile, the linearized encoding model (LEM) can be used directly to compare multiple competing hypotheses on the same data. With the addition of the two new approaches, the improved framework can be a great help in future studies of sensory and cognitive processing in the human brain.

Keywords:   natural scenes, SANS, statistical analysis, linearized modeling, LEM

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