The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Visual Adaptation: Physiology, Mechanisms, and Functional Benefits
Abstract
Recent sensory experience affects both perception and the response properties of visual neurons. Here I review a rapid form of experience-dependent plasticity that follows adaptation, the presentation of a particular stimulus or ensemble of stimuli for periods ranging from tens of milliseconds to minutes. Adaptation has a rich history in psychophysics, where it is often used as a tool for dissecting the perceptual mechanisms of vision. Although we know comparatively little about the neurophysiological effects of adaptation, work in the last decade has revealed a rich repertoire of effects. This review focuses on this recent physiological work, the cellular and biophysical mechanisms that may underlie the observed effects, and the functional benefit that they may afford. I conclude with a brief discussion of some important open questions in the field.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Recanzone, G., Schreiner, C., & Merzenich, M. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-01-00087.1993 · Cited by 1,266
The cost of cortical computation.
Lennie, P. (2003) · Current Biology · doi:10.1016/s0960-9822(03)00135-0 · Cited by 1,134
Processing of low-probability sounds by cortical neurons
Ulanovsky, N., Las, L., & Nelken, I. (2003) · Nature Neuroscience · doi:10.1038/nn1032 · Cited by 1,049
Predictive coding: a fresh view of inhibition in the retina
Srinivasan, M. V., Laughlin, S. B., & Dubs, A. (1982) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1982.0085 · Cited by 1,042
STRUCTURE AND FUNCTION OF VISUAL AREA MT
Born, R. T., & Bradley, D. C. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131052 · Cited by 1,023 · cited 2×
“…for adaptation studies because the basic properties of its cells have been well-characterized, its activity has been strongly linked to perception (Born and Bradley 2005), and adaptation to visual motion has profound perceptual consequences (e.g., the motion aftereffect) (Mather et al. 1998).”
BackgroundDifferential regulation of neocortical synapses by neuromodulators and activity
Gil, Z., Connors, B. W., & Amitai, Y. (1997) · Neuron · doi:10.1016/s0896-6273(00)80380-3 · Cited by 553
Chung, S., Li, X., & Nelson, S. B. (2002) · Neuron · doi:10.1016/s0896-6273(02)00659-1 · Cited by 530
Dynamic predictive coding by the retina
Hosoya, T., Baccus, S. A., & Meister, M. (2005) · Nature · doi:10.1038/nature03689 · Cited by 468
Neuronal Adaptation to Visual Motion in Area MT of the Macaque
Kohn, A., & Movshon, J. A. (2003) · Neuron · doi:10.1016/s0896-6273(03)00438-0 · Cited by 353 · cited 6×
“Using compound stimuli composed of a preferred and null grating, Kohn and Movshon (2003) showed that null adaptation reduces the strength of opponent inhibition.”
BackgroundResultInfluentialSelf-citation
Cited by
How does the brain solve visual object recognition?
DiCarlo, J. J., Zoccolan, D., & Rust, N. C. (2012) · Neuron · doi:10.1016/j.neuron.2012.01.010 · Cited by 1,790
When the world becomes ‘too real’: a Bayesian explanation of autistic perception
Pellicano, E., & Burr, D. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.08.009 · Cited by 1,156
Mismatch negativity (MMN), the deviance-elicited auditory deflection, explained
May, P. J. C., & Tiitinen, H. (2010) · Psychophysiology · doi:10.1111/j.1469-8986.2009.00856.x · Cited by 549
Visual mismatch negativity: a predictive coding view
Stefanics, G., KremláÄek, J., & Czigler, I. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00666 · Cited by 340
Serial Dependence in the Perception of Faces
Liberman, A., Fischer, J., & Whitney, D. (2014) · Current Biology · doi:10.1016/j.cub.2014.09.025 · Cited by 324
Metadata
- Authors
- Kohn, A.
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2007-05
- Volume
- 97
- Issue
- 5
- Pages
- 3155-3164
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- OpenAlex
- W2155744172
- Cited by
- 822
- References
- 9
- FWCI
- 13.92
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Visual Adaptation: Physiology, Mechanisms, and Functional Benefits. https://app.cochat.ai/papers/10.1152/jn.00086.2007
- The paper
- Kohn, A. (2007). Visual Adaptation: Physiology, Mechanisms, and Functional Benefits. Journal of Neurophysiology. https://doi.org/10.1152/jn.00086.2007
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.