CoChat
Sign Up
Cited by 860Visual perception and processing mechanismsNeural dynamics and brain functionNeuroscience and Neuropharmacology Research

An emergent model of orientation selectivity in cat visual cortical simple cells

Open access
Somers, DC, Nelson, SB, Sur, M·1995·The Journal of Neuroscience
DOI 10.1523/jneurosci.15-08-05448.1995PMC PMC6577625
Open this paper in CoChat — free accountOpen PDF

Abstract

It is well known that visual cortical neurons respond vigorously to a limited range of stimulus orientations, while their primary afferent inputs, neurons in the lateral geniculate nucleus (LGN), respond well to all orientations. Mechanisms based on intracortical inhibition and/or converging thalamocortical afferents have previously been suggested to underlie the generation of cortical orientation selectivity; however, these models conflict with experimental data. Here, a 1:4 scale model of a 1700 microns by 200 microms region of layer IV of cat primary visual cortex (area 17) is presented to demonstrate that local intracortical excitation may provide the dominant source of orientation-selective input. In agreement with experiment, model cortical cells exhibit sharp orientation selectivity despite receiving strong iso-orientation inhibition, weak cross- orientation inhibition, no shunting inhibition, and weakly tuned thalamocortical excitation. Sharp tuning is provided by recurrent cortical excitation. As this tuning signal arises from the same pool of neurons that it excites, orientation selectivity in the model is shown to be an emergent property of the cortical feedback circuitry. In the model, as in experiment, sharpness of orientation tuning is independent of stimulus contrast and persists with silencing of ON-type subfields. The model also provides a unified account of intracellular and extracellular inhibitory blockade experiments that had previously appeared to conflict over the role of inhibition. It is suggested that intracortical inhibition acts nonspecifically and indirectly to maintain the selectivity of individual neurons by balancing strong intracortical excitation at the columnar level.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1523/jneurosci.15-08-05448.1995

Cites

111 of 111 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration.

    “Neurons in many cortical and subcortical brain areas exhibit robust gain modulation that may contribute to multiple cognitive functions, including attention, learning, sensory processing and multimodal integration1–3,7,8,13–17.”

    From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [15]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Bonds AB (1993) The encoding of cortical contrast gain control. In: Contrast sensitivity (Shapley RM, Lam D-K, eds), pp 215-230. Cam- bridge, MA: MIT Press.
  2. Koch C, Poggio T (1985) The synaptic veto mechanism: does it un- derlie direction and orientation selectivity in the visual cortex? In: Models of the visual cortex (Rose DR, Dobson VG, eds), pp 408- 419. New York: Wiley.

Cited by

Sorted by citations

Related

Authors
Somers, D., Nelson, S., & Sur, M.
Affiliations
Massachusetts Institute of Technology (US)
ORCID
Sur, M
Venue
The Journal of Neuroscience
Publisher
Society for Neuroscience
Published
1995-08-01
Volume
15
Issue
8
Pages
5448-5465
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
DOI
10.1523/jneurosci.15-08-05448.1995
PMC
PMC6577625
OpenAlex
W1867287134
Cited by
860
References
111
Citations by year
2026: 3 · 2025: 16 · 2024: 13 · 2023: 5 · 2022: 14 · 2021: 13 · 2020: 18 · 2019: 15 · 2018: 13 · 2017: 16 · 2016: 22 · 2015: 25 · 2014: 35 · 2013: 38 · 2012: 34
FWCI
22.64
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health
  • Advanced Research Projects Agency
  • National Institute of Mental Health (MH-10671, F32MH010671)
  • National Eye Institute (EY07023, EY-06363)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
Keywords
orientation selectivity, simple cells, primary visual cortex, cats, intracortical inhibition, lateral geniculate nucleus, thalamocortical afferents, layer 4, orientation tuning
MeSH terms
Aminobutyrates, Animals, Bicuculline, Cats, Computer Simulation, Models, Neurological, Neural Inhibition, Neurons, Reference Values, Visual Cortex, 4,4'-Diisothiocyanostilbene-2,2'-Disulfonic Acid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review