Evidence map›Paper›PMID 34588436›Full record

ArticleNature communications2021

Zebrafish capable of generating future state prediction error show improved active avoidance behavior in virtual reality.

Makio Torigoe, Tanvir Islam, Hisaya Kakinuma, Chi Chung Alan Fung, Takuya Isomura, Hideaki Shimazaki, Tazu Aoki, Tomoki Fukai, Hitoshi Okamoto

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  20. An Overview of In Vitro Biological Neural Networks for Robot Intelligence.Cyborg and bionic systems (Washington, D.C.) · 2023
    Review
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

9 authors.

Makio TorigoeLab. for Neural Circuit Dynamics of Decision Making, RIKEN Center for Brain Science, Wako, Saitama, 351-0198, Japan.ORCID 0000-0001-8208-4823
Tanvir IslamLab. for Neural Circuit Dynamics of Decision Making, RIKEN Center for Brain Science, Wako, Saitama, 351-0198, Japan.
Hisaya KakinumaLab. for Neural Circuit Dynamics of Decision Making, RIKEN Center for Brain Science, Wako, Saitama, 351-0198, Japan.
Chi Chung Alan FungNeural Coding and Brain Computing Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, 904-0495, Japan.
Takuya IsomuraBrain Intelligence Theory Unit, RIKEN Center for Brain Science, Wako, Saitama, 351-0198, Japan.ORCID 0000-0003-2960-4919
Hideaki ShimazakiCenter for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University, Sapporo, Hokkaido, 060-0812, Japan.ORCID 0000-0001-7794-3064
Tazu AokiLab. for Neural Circuit Dynamics of Decision Making, RIKEN Center for Brain Science, Wako, Saitama, 351-0198, Japan.
Tomoki FukaiNeural Coding and Brain Computing Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, 904-0495, Japan.ORCID 0000-0001-6977-5638
Hitoshi OkamotoLab. for Neural Circuit Dynamics of Decision Making, RIKEN Center for Brain Science, Wako, Saitama, 351-0198, Japan. hitoshi.okamoto@riken.jp.ORCID 0000-0002-7512-8549

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animals make decisions under the principle of reward value maximization and surprise minimization. It is still unclear how these principles are represented in the brain and are reflected in behavior. We addressed this question using a closed-loop virtual reality system to train adult zebrafish for active avoidance. Analysis of the neural activity of the dorsal pallium during training revealed neural ensembles assigning rules to the colors of the surrounding walls. Additionally, one third of fish generated another ensemble that becomes activated only when the real perceived scenery shows discrepancy from the predicted favorable scenery. The fish with the latter ensemble escape more efficiently than the fish with the former ensembles alone, even though both fish have successfully learned to escape, consistent with the hypothesis that the latter ensemble guides zebrafish to take action to minimize this prediction error. Our results suggest that zebrafish can use both principles of goal-directed behavior, but with different behavioral consequences depending on the repertoire of the adopted principles.

Indexed as

RewardAnimalsAvoidance LearningBehavior, AnimalIntravital MicroscopyMicroscopy, Fluorescence, MultiphotonNeocortexNeural Networks, ComputerNeuronsPhotic StimulationStereotaxic TechniquesVirtual RealityZebrafish

Identifiers

PMID34588436
PMCPMC8481257

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.