Flies and humans share a motion estimation strategy that exploits natural scene statistics

Autoren

Damon A Clark
James E Fitzgerald
Justin M Ales
Daryl M Gohl
Marion A Silies
Anthony M Norcia
Thomas R Clandinin

DOI

10.1038/nn.3600

eISSN

1546-1726

ISSN

1097-6256

Ausgabe der Veröffentlichung

2

Zeitschrift

Nature Neuroscience

Sprache

en

Online publication date

2014

Paginierung

296 - 303

Datum der Veröffentlichung

2014

Status

Published

Herausgeber

Springer Science and Business Media LLC

Herausgeber URL

http://dx.doi.org/10.1038/nn.3600

Datum der Datenerfassung

2023

Titel

Flies and humans share a motion estimation strategy that exploits natural scene statistics

Ausgabe der Zeitschrift

17

Datenquelle: Crossref

Abstract

Sighted animals extract motion information from visual scenes by processing spatiotemporal patterns of light falling on the retina. The dominant models for motion estimation exploit intensity correlations only between pairs of points in space and time. Moving natural scenes, however, contain more complex correlations. We found that fly and human visual systems encode the combined direction and contrast polarity of moving edges using triple correlations that enhance motion estimation in natural environments. Both species extracted triple correlations with neural substrates tuned for light or dark edges, and sensitivity to specific triple correlations was retained even as light and dark edge motion signals were combined. Thus, both species separately process light and dark image contrasts to capture motion signatures that can improve estimation accuracy. This convergence argues that statistical structures in natural scenes have greatly affected visual processing, driving a common computational strategy over 500 million years of evolution.

Addresses

1] Department of Neurobiology, Stanford University, Stanford, California, USA. [2] [3].

Autoren

Damon A Clark
James E Fitzgerald
Justin M Ales
Daryl M Gohl
Marion A Silies
Anthony M Norcia
Thomas R Clandinin

DOI

10.1038/nn.3600

eISSN

1546-1726

Externe Identifier

PubMed Identifier: 24390225
PubMed Central ID: PMC3993001

Funding acknowledgements

NEI NIH HHS: EY015790
NEI NIH HHS: R01 EY022638
NEI NIH HHS: R56 EY015790
NIH HHS: DP1 OD003530
NEI NIH HHS: R01 EY015790

Open access

true

ISSN

1097-6256

Ausgabe der Veröffentlichung

2

Zeitschrift

Nature neuroscience

Schlüsselwörter

Animals
Humans
Drosophila
Electroencephalography
Photic Stimulation
Pattern Recognition, Visual
Motion Perception
Contrast Sensitivity
Psychophysics
Adaptation, Physiological
Evoked Potentials, Visual
Genotype
Models, Neurological

Sprache

eng

Medium

Print-Electronic

Online publication date

2014

Open access status

Open Access

Paginierung

296 - 303

Datum der Veröffentlichung

2014

Status

Published

Datum der Datenerfassung

2014

Titel

Flies and humans share a motion estimation strategy that exploits natural scene statistics.

Sub types

Research Support, Non-U.S. Gov't
research-article
Research Support, U.S. Gov't, Non-P.H.S.
Journal Article
Research Support, N.I.H., Extramural

Ausgabe der Zeitschrift

17

Files

https://europepmc.org/articles/pmc3993001?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24390225/pdf/?tool=EBI

Datenquelle: Europe PubMed Central

Abstract

Sighted animals extract motion information from visual scenes by processing spatiotemporal patterns of light falling on the retina. The dominant models for motion estimation exploit intensity correlations only between pairs of points in space and time. Moving natural scenes, however, contain more complex correlations. We found that fly and human visual systems encode the combined direction and contrast polarity of moving edges using triple correlations that enhance motion estimation in natural environments. Both species extracted triple correlations with neural substrates tuned for light or dark edges, and sensitivity to specific triple correlations was retained even as light and dark edge motion signals were combined. Thus, both species separately process light and dark image contrasts to capture motion signatures that can improve estimation accuracy. This convergence argues that statistical structures in natural scenes have greatly affected visual processing, driving a common computational strategy over 500 million years of evolution.

Date of acceptance

2013

Autoren

Damon A Clark
James E Fitzgerald
Justin M Ales
Daryl M Gohl
Marion A Silies
Anthony M Norcia
Thomas R Clandinin

Autoren-URL

https://www.ncbi.nlm.nih.gov/pubmed/24390225

DOI

10.1038/nn.3600

eISSN

1546-1726

Externe Identifier

NIH Manuscript Submission ID: NIHMS560023
PubMed Central ID: PMC3993001

Funding acknowledgements

NIH HHS: DP1 OD003530
NEI NIH HHS: R56 EY015790
NEI NIH HHS: R01 EY015790
NEI NIH HHS: EY015790
NEI NIH HHS: R01 EY022638

Ausgabe der Veröffentlichung

2

Zeitschrift

Nat Neurosci

Schlüsselwörter

Adaptation, Physiological
Animals
Contrast Sensitivity
Drosophila
Electroencephalography
Evoked Potentials, Visual
Genotype
Humans
Models, Neurological
Motion Perception
Pattern Recognition, Visual
Photic Stimulation
Psychophysics

Sprache

eng

Country

United States

Paginierung

296 - 303

PII

nn.3600

Datum der Veröffentlichung

2014

Status

Published

Datum, an dem der Datensatz öffentlich gemacht wurde

2014

Titel

Flies and humans share a motion estimation strategy that exploits natural scene statistics.

Sub types

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Ausgabe der Zeitschrift

17

Datenquelle: PubMed

Flies and humans share a motion estimation strategy that exploits natural scene statistics

Files

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