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 articlepeer-review

33 Scopus citations


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
Pages (from-to)15-24
Number of pages10
JournalNature Neuroscience
Issue number1
StatePublished - Jan 1 2019

Bibliographical note

Publisher Copyright:
© 2018, Springer Nature America, Inc.

ASJC Scopus subject areas

  • General Neuroscience


Dive into the research topics of 'Stimulus- and goal-oriented frameworks for understanding natural vision'. Together they form a unique fingerprint.

Cite this