Evidence map›Paper›PMID 41457177›Full record

ArticleNature communications2025

Biomimetic model of corticostriatal micro-assemblies discovers a neural code.

Anand Pathak, Scott L Brincat, Haris Organtzidis, Helmut H Strey, Sageanne Senneff, Evan G Antzoulatos, Lilianne R Mujica-Parodi, Earl K Miller, Richard Granger

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Anand PathakDept. of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.ORCID http://orcid.org/0000-0002-2972-2520
Scott L BrincatThe Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-7777-7294
Haris OrgantzidisDept. of Biomedical Engineering, Laufer Center for Physical and Quantitative Biology, State University of New York at Stony Brook, Stony Brook, NY, USA.
Helmut H StreyDept. of Biomedical Engineering, Laufer Center for Physical and Quantitative Biology, State University of New York at Stony Brook, Stony Brook, NY, USA.ORCID http://orcid.org/0000-0002-6554-5322
Sageanne SenneffDept. of Biomedical Engineering, Laufer Center for Physical and Quantitative Biology, State University of New York at Stony Brook, Stony Brook, NY, USA.
Evan G AntzoulatosThe Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-7366-2078
Lilianne R Mujica-ParodiDept. of Biomedical Engineering, Laufer Center for Physical and Quantitative Biology, State University of New York at Stony Brook, Stony Brook, NY, USA.ORCID http://orcid.org/0000-0002-3752-5519
Earl K MillerThe Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-0582-6958
Richard GrangerDept. of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA. Richard.Granger@gmail.com.ORCID http://orcid.org/0000-0003-3765-174X

Funding

Layer-specific manipulation to test feedforward/feedback cortical circuitryR01MH131715 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI EARL K MILLER · 2023 to 2026
$1.2M
NIMH NIH HHS R01 MH131715United States Department of Defense | United States Navy | Office of Naval Research (ONR) MURI N00014-23-1-2768United States Department of Defense | United States Navy | Office of Naval Research (ONR) MURI W911NF2410228United States Department of Defense | United States Navy | Office of Naval Research (ONR) N00014-21-1-2290U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) 1R01MH131715-01
6 · The paper itself

Abstract

Although computational models have deepened our understanding of neuroscience, it is still highly challenging to link actual low-level physiological activity (spiking, field potentials) and biochemistry (transmitters and receptors) directly with high-level cognitive abilities (decision-making, working memory) and associated disorders. Here, we introduce a mechanistically accurate multi-scale model directly generating simulated physiology from which extended neural and cognitive phenomena emerge. The model produces spiking, fields, phase synchronies, and synaptic change, directly generating working memory, decisions, and categorization. These were then validated on extensive experimental macaque data from which the model received no prior training of any kind. Moreover, the simulation uncovered a previously unknown neural code ("incongruent neurons") that specifically predicts upcoming erroneous behaviors, also subsequently confirmed in empirical data. The biomimetic model thus directly and predictively links decision and reinforcement signals, of computational interest, with spiking and field codes, of neurobiological importance.

Indexed as

BiomimeticsCerebral CortexCorpus StriatumModels, NeurologicalNeuronsAction PotentialsAnimalsCognitionComputer SimulationDecision MakingMemory, Short-Term

Identifiers

PMID41457177
PMCPMC12796379

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.