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Building and Evaluating Computational Models of the Mammalian Visual System.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Building and Evaluating Computational Models of the Mammalian Visual System./
Author:	Kong, Nathan C.L.
Description:	1 online resource (168 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Contained By:	Dissertations Abstracts International85-04B.
Subject:	Euclidean space. -
Online resource:	click for full text (PQDT)
ISBN:	9798380481595

Building and Evaluating Computational Models of the Mammalian Visual System.
Kong, Nathan C.L.

Building and Evaluating Computational Models of the Mammalian Visual System. - 1 online resource (168 pages)

Source: Dissertations Abstracts International, Volume: 85-04, Section: B.

Thesis (Ph.D.)--Stanford University, 2023.

Includes bibliographical references

Animals continuously and dynamically process sensory information in service of both flexible and inflexible behaviours. To understand the brain's complex information-processing pipeline by which such behaviours arise, we must first understand how the brain transforms sensory information from its raw form. This will then allow us determine what information is accessible downstream in the process. In this dissertation, we try to understand how the brain processes visual information, which entails building and evaluating computational models that can predict how the animal will respond to novel visual inputs. We focus on a class of models known as convolutional neural networks (CNNs) and demonstrate ways in which they can be evaluated against and be built for primates and for rodents to better understand how the mammalian visual system supports behaviour. We first demonstrate a time-resolved correspondence between a feedforward CNN and whole-brain neural responses during human object processing and develop a data-driven optimization approach to improve upon correlations achieved between the model and the neural data. Motivated by extensive empirical work in rodents on navigational and on decision-making behaviours and by the desire to integrate models of cortical and of subcortical areas that support these behaviours, we build quantitatively accurate CNN models of the mouse visual system. Although CNNs are state-of-the-art models of primate and of rodent visual processing, they are extremely brittle. We therefore examine the nature of their brittleness and show the existence of representational di↵erences between primary visual cortex of non-human primates and the models. Finally, we suggest that building lessbrittle models will require us to incorporate the temporally-continuous nature of the visual inputs that animals receive. Looking forward, we hope that models of sensory cortex can be integrated with computational models of downstream cortical and subcortical areas, so that we can better understand how flexible and inflexible behaviours arise.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380481595Subjects--Topical Terms:

1474738
Euclidean space.
Index Terms--Genre/Form:

554714
Electronic books.

Building and Evaluating Computational Models of the Mammalian Visual System.
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