Evidence map›Paper›PMID 38168336›Full record

ArticlebioRxiv : the preprint server for biology2023

Neural correlates of category learning in monkey inferior temporal cortex.

Jonah E Pearl, Narihisa Matsumoto, Kazuko Hayashi, Keiji Matsuda, Kenichiro Miura, Yuji Nagai, Naohisa Miyakawa, Takafumi Minanimoto, Richard C Saunders, Yasuko Sugase-Miyamoto and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Jonah E PearlLaboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, United States.ORCID 0000-0001-9300-1552
Narihisa MatsumotoHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.ORCID 0000-0002-6837-1444
Kazuko HayashiHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
Keiji MatsudaHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.ORCID 0000-0003-2529-0019
Kenichiro MiuraDepartment of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
Yuji NagaiDepartment of Functional Brain Imaging, National Institutes for Quantum Science and Technology, (QST), Inage, Chiba 263-8555, Japan.
Naohisa MiyakawaDepartment of Functional Brain Imaging, National Institutes for Quantum Science and Technology, (QST), Inage, Chiba 263-8555, Japan.
Takafumi MinanimotoDepartment of Functional Brain Imaging, National Institutes for Quantum Science and Technology, (QST), Inage, Chiba 263-8555, Japan.ORCID 0000-0003-4305-0174
Richard C SaundersLaboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, United States.
Yasuko Sugase-MiyamotoHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
Barry J RichmondLaboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, United States.
Mark A G EldridgeLaboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, United States.

Funding

Neural Coding Of Visual StimuliZIAMH002032 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI RICHMOND, BARRY J · 2009 to 2025
$20.5M
Intramural NIH HHS ZIA MH002032
6 · The paper itself

Abstract

We trained two monkeys implanted with multi-electrode arrays to categorize natural images of cats and dogs, in order to observe changes in neural activity related to category learning. We recorded neural activity from area TE, which is required for normal learning of visual categories based on perceptual similarity. Neural activity during a passive viewing task was compared pre- and post-training. After the category training, the accuracy of abstract category decoding improved. Specifically, 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.

Identifiers

PMID38168336
PMCPMC10760203

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.