Evidence map›Paper›PMID 33468673›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Environment-based object values learned by local network in the striatum tail.

Jun Kunimatsu, Shinya Yamamoto, Kazutaka Maeda, Okihide Hikosaka

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jun KunimatsuLaboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20892; kunimatsu.jun@gmail.com.ORCID https://orcid.org/0000-0002-8003-0650
Shinya YamamotoIntegrative Neuroscience, Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 305-8568 Tsukuba, Japan.ORCID https://orcid.org/0000-0002-0505-8848
Kazutaka MaedaLaboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20892.ORCID https://orcid.org/0000-0001-8543-5289
Okihide HikosakaLaboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20892.ORCID https://orcid.org/0000-0003-2458-7187

Funding

Neuronal networks for control of eye movementZIAEY000415 · NEI · NATIONAL EYE INSTITUTE · PI HIKOSAKA, OKIHIDE · 2009 to 2025
$35.3M
6 · The paper itself

Abstract

Basal ganglia contribute to object-value learning, which is critical for survival. The underlying neuronal mechanism is the association of each object with its rewarding outcome. However, object values may change in different environments and we then need to choose different objects accordingly. The mechanism of this environment-based value learning is unknown. To address this question, we created an environment-based value task in which the value of each object was reversed depending on the two scene-environments (X and Y). After experiencing this task repeatedly, the monkeys became able to switch the choice of object when the scene-environment changed unexpectedly. When we blocked the inhibitory input from fast-spiking interneurons (FSIs) to medium spiny projection neurons (MSNs) in the striatum tail by locally injecting IEM-1460, the monkeys became unable to learn scene-selective object values. We then studied the mechanism of the FSI-MSN connection. Before and during this learning, FSIs responded to the scenes selectively, but were insensitive to object values. In contrast, MSNs became able to discriminate the objects (i.e., stronger response to good objects), but this occurred clearly in one of the two scenes (X or Y). This was caused by the scene-selective inhibition by FSI. As a whole, MSNs were divided into two groups that were sensitive to object values in scene X or in scene Y. These data indicate that the local network of striatum tail controls the learning of object values that are selective to the scene-environment. This mechanism may support our flexible switching behavior in various environments.

Indexed as

AdamantaneAnimalsBasal GangliaCorpus StriatumEnvironmentHumansInterneuronsLearningMacaca mulattaMalePrimatesSaccadesAdamantaneIEM 1460local networkprimatesaccadescene-environmentstriatum tail

Identifiers

PMID33468673
PMCPMC7848585

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Registered trials

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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.