Neural Correlates of Category Learning in Monkey Inferior Temporal Cortex Article Swipe
Jonah E Pearl
,
Narihisa Matsumoto
,
Kazuko Hayashi
,
Keiji Matsuda
,
Kenichiro Miura
,
Yuji Nagai
,
Naohisa Miyakawa
,
Takafumi Minanimoto
,
Richard C. Saunders
,
Yasuko Sugase-Miyamoto
,
Barry J. Richmond
,
Mark A. G. Eldridge
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1523/jneurosci.0312-24.2024
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1523/jneurosci.0312-24.2024
Area TE is required for normal learning of visual categories based on perceptual similarity. To evaluate whether category learning changes neural activity in area TE, we trained two monkeys (both male) implanted with multielectrode arrays to categorize natural images of cats and dogs. Neural activity during a passive viewing task was compared pre- and post-training. After the category training, the accuracy of abstract category decoding improved. Single units became more category selective, the proportion of single units with category selectivity increased, and units sustained their category-specific responses for longer. Visual category learning thus appears to enhance category separability in area TE by driving changes in the stimulus selectivity of individual neurons and by recruiting more units to the active network.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1523/jneurosci.0312-24.2024
- OA Status
- green
- Cited By
- 2
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403533825
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4403533825Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1523/jneurosci.0312-24.2024Digital Object Identifier
- Title
-
Neural Correlates of Category Learning in Monkey Inferior Temporal CortexWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-10-18Full publication date if available
- Authors
-
Jonah E Pearl, Narihisa Matsumoto, Kazuko Hayashi, Keiji Matsuda, Kenichiro Miura, Yuji Nagai, Naohisa Miyakawa, Takafumi Minanimoto, Richard C. Saunders, Yasuko Sugase-Miyamoto, Barry J. Richmond, Mark A. G. EldridgeList of authors in order
- Landing page
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https://doi.org/10.1523/jneurosci.0312-24.2024Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.ncbi.nlm.nih.gov/pmc/articles/11622174Direct OA link when available
- Concepts
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Categorization, Stimulus (psychology), Visual cortex, Psychology, Visual perception, Perception, Neuroscience, Communication, Cognitive psychology, Pattern recognition (psychology), Artificial intelligence, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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35Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.was | 50 |
| abstract_inverted_index.Area | 0 |
| abstract_inverted_index.area | 23, 99 |
| abstract_inverted_index.cats | 40 |
| abstract_inverted_index.more | 69, 114 |
| abstract_inverted_index.pre- | 52 |
| abstract_inverted_index.task | 49 |
| abstract_inverted_index.thus | 92 |
| abstract_inverted_index.with | 32, 77 |
| abstract_inverted_index.(both | 29 |
| abstract_inverted_index.After | 55 |
| abstract_inverted_index.based | 10 |
| abstract_inverted_index.dogs. | 42 |
| abstract_inverted_index.male) | 30 |
| abstract_inverted_index.their | 84 |
| abstract_inverted_index.units | 67, 76, 82, 115 |
| abstract_inverted_index.Neural | 43 |
| abstract_inverted_index.Single | 66 |
| abstract_inverted_index.Visual | 89 |
| abstract_inverted_index.active | 118 |
| abstract_inverted_index.arrays | 34 |
| abstract_inverted_index.became | 68 |
| abstract_inverted_index.during | 45 |
| abstract_inverted_index.images | 38 |
| abstract_inverted_index.neural | 20 |
| abstract_inverted_index.normal | 5 |
| abstract_inverted_index.single | 75 |
| abstract_inverted_index.visual | 8 |
| abstract_inverted_index.appears | 93 |
| abstract_inverted_index.changes | 19, 103 |
| abstract_inverted_index.driving | 102 |
| abstract_inverted_index.enhance | 95 |
| abstract_inverted_index.longer. | 88 |
| abstract_inverted_index.monkeys | 28 |
| abstract_inverted_index.natural | 37 |
| abstract_inverted_index.neurons | 110 |
| abstract_inverted_index.passive | 47 |
| abstract_inverted_index.trained | 26 |
| abstract_inverted_index.viewing | 48 |
| abstract_inverted_index.whether | 16 |
| abstract_inverted_index.abstract | 62 |
| abstract_inverted_index.accuracy | 60 |
| abstract_inverted_index.activity | 21, 44 |
| abstract_inverted_index.category | 17, 57, 63, 70, 78, 90, 96 |
| abstract_inverted_index.compared | 51 |
| abstract_inverted_index.decoding | 64 |
| abstract_inverted_index.evaluate | 15 |
| abstract_inverted_index.learning | 6, 18, 91 |
| abstract_inverted_index.network. | 119 |
| abstract_inverted_index.required | 3 |
| abstract_inverted_index.stimulus | 106 |
| abstract_inverted_index.implanted | 31 |
| abstract_inverted_index.improved. | 65 |
| abstract_inverted_index.responses | 86 |
| abstract_inverted_index.sustained | 83 |
| abstract_inverted_index.training, | 58 |
| abstract_inverted_index.categories | 9 |
| abstract_inverted_index.categorize | 36 |
| abstract_inverted_index.increased, | 80 |
| abstract_inverted_index.individual | 109 |
| abstract_inverted_index.perceptual | 12 |
| abstract_inverted_index.proportion | 73 |
| abstract_inverted_index.recruiting | 113 |
| abstract_inverted_index.selective, | 71 |
| abstract_inverted_index.selectivity | 79, 107 |
| abstract_inverted_index.similarity. | 13 |
| abstract_inverted_index.separability | 97 |
| abstract_inverted_index.multielectrode | 33 |
| abstract_inverted_index.post-training. | 54 |
| abstract_inverted_index.category-specific | 85 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 12 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.75069629 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |