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Impact of learning on representation of parts and wholes in monkey inferotemporal cortex
Open accessAbstract
Here we investigated the impact of visual discrimination training on neuronal responses to parts of images and to whole images in inferotemporal (IT) cortex. Monkeys were trained to discriminate among 'baton' stimuli consisting of discrete top and bottom parts joined by a vertical stem. With separate features at each end, we were able to manipulate the two parts of each baton independently. After training the monkeys, we used single-cell recording to compare neuronal responses to learned and unlearned batons. Responses to learned batons, though not enhanced in strength, were enhanced in selectivity for both individual parts and for whole batons. Whole-baton selectivity arose from a form of conjunctive encoding whereby two parts together exerted a greater influence on neuronal activity than predicted by the additive influence of each part considered individually. These results indicate a possible neural mechanism for holistic or configural effects in expert versus novice observers.
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“Binding of letters may also be based on more holistic coding, as suggested by the recent demonstration that single IT neurons develop selectivity for learned complex shapes, above and beyond what could be expected from the additive influence of their component parts (Baker et al., 2002).”
From Specialization within the ventral stream: the case for the visual word form area (2004) · cites this paper as Baker et al., 2002
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Metadata
- Authors
- Baker, C. I., Behrmann, M., & Olson, C. R.
- Affiliations
- Center for the Neural Basis of Cognition (US)
- University of Pittsburgh (US)
- Corresponding author
- Baker, Chris I.
- Venue
- Nature Neuroscience
- Published
- 2002-10-15
- Volume
- 5
- Issue
- 11
- Pages
- 1210-1216
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2092661421
- Cited by
- 293
- References
- 44
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 7 · 2023: 4 · 2022: 6 · 2021: 9 · 2020: 7 · 2019: 5 · 2018: 8 · 2017: 6 · 2016: 13 · 2015: 14 · 2014: 12 · 2013: 15 · 2012: 12
- FWCI
- 5.86
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Licence
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- KiltHub Repository (submittedVersion)
- Figshare (submittedVersion, cc-by)
- KiltHub Repository
- Funders
- National Institutes of Health
- National Eye Institute (R01 EY-11831, R01EY011831)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
- Keywords
- inferotemporal cortex, visual discrimination learning, holistic processing, object recognition, single neuron responses
- MeSH terms
- Animals, Haplorhini, Discrimination Learning, Electrophysiology, Neurons, Pattern Recognition, Visual, Photic Stimulation, Temporal Lobe, Visual Fields
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 ›
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