Stimulus- and goal-oriented frameworks for understanding natural vision

Maxwell H. Turner, Luis Gonzalo Sanchez Giraldo, Odelia Schwartz, Fred Rieke

Research output: Contribution to journalReview article

3 Citations (Scopus)

Abstract

Our knowledge of sensory processing has advanced dramatically in the last few decades, but this understanding remains far from complete, especially for stimuli with the large dynamic range and strong temporal and spatial correlations characteristic of natural visual inputs. Here we describe some of the issues that make understanding the encoding of natural images a challenge. We highlight two broad strategies for approaching this problem: a stimulus-oriented framework and a goal-oriented one. Different contexts can call for one framework or the other. Looking forward, recent advances, particularly those based in machine learning, show promise in borrowing key strengths of both frameworks and by doing so illuminating a path to a more comprehensive understanding of the encoding of natural stimuli.

Original languageEnglish (US)
Pages (from-to)15-24
Number of pages10
JournalNature Neuroscience
Volume22
Issue number1
DOIs
StatePublished - Jan 1 2019

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Machine Learning

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Stimulus- and goal-oriented frameworks for understanding natural vision. / Turner, Maxwell H.; Sanchez Giraldo, Luis Gonzalo; Schwartz, Odelia; Rieke, Fred.

In: Nature Neuroscience, Vol. 22, No. 1, 01.01.2019, p. 15-24.

Research output: Contribution to journalReview article

Turner, Maxwell H. ; Sanchez Giraldo, Luis Gonzalo ; Schwartz, Odelia ; Rieke, Fred. / Stimulus- and goal-oriented frameworks for understanding natural vision. In: Nature Neuroscience. 2019 ; Vol. 22, No. 1. pp. 15-24.
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