Evidence map›Paper›PMID 38826351›Full record

ArticlebioRxiv : the preprint server for biology2025

Parietal cortex is causally required for state-dependent decisions.

Akhil C Bandi, John P McCann, Rachel M Carpenter, Mason J Lower, Jordyn N Long, Caroline A Runyan

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

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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

6 authors.

Akhil C BandiNeuroscience Institute, Carnegie Mellon University, Pittsburgh, PA.ORCID 0000-0002-2239-8799
John P McCannDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA.
Rachel M CarpenterDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA.
Mason J LowerDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA.
Jordyn N LongDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA.
Caroline A RunyanDepartment of Neuroscience, University of Pittsburgh, Pittsburgh, PA.

Funding

Topological bridges between circuits, models, and behaviorRF1NS121913 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COHEN, MARLENE ROCHELLE, MORRISON, JOHN H · 2021 to 2022
$3.2M
Supplement to Communication between Networks: Context, Inhibition, and NeuromodulationDP2MH122404 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI RUNYAN, CAROLINE ANNE · 2019 to 2022
$2.5M
Topological bridges between circuits, models, and behaviorR01NS121913 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COHEN, MARLENE ROCHELLE, HUANG, CHENGCHENG · 2024 to 2025
$1.9M
Training Program in Big Data Systems NeuroscienceT32NS126122 · NINDS · CARNEGIE-MELLON UNIVERSITY · PI Aryn Hilary Gittis · 2022 to 2026
$971k
NIMH NIH HHS DP2 MH122404NINDS NIH HHS R01 NS121913NINDS NIH HHS RF1 NS121913NINDS NIH HHS T32 NS126122
6 · The paper itself

Abstract

During perceptual decision-making tasks, behavioral performance and its neural correlates vary with changes in internal states such as arousal, motivation, and strategy. It is not yet clear whether these state fluctuations differently impact the distributed neural processes that underlie task performance, from sensory processing to control of motor outputs. The posterior parietal cortex (PPC) is an association-level cortical region implicated in sensorimotor transformations, but evidence of its causal requirement in decision-making tasks has been contradictory. We trained mice to perform a navigation-based sound localization task and asked how natural fluctuations in behavioral state related to neural processing in association areas during decision-making. Behavioral performance in expert-level mice was not static but instead transitioned between periods of near-perfect performance and biased, less accurate performance. Using a hidden Markov model, we could reliably define these as distinct strategies that included a high-performance state where mice used relevant stimulus information to inform choices, and two biased states where mice weighted stimulus information less strongly. Optogenetic inactivation of PPC decreased task performance accuracy, and the model captured the resulting change in behavioral strategy as a reduction in the weighting of the auditory cues and an increase in behavioral bias, in predicting mice's decisions. Two-photon calcium imaging revealed that performance states strongly influenced population activity patterns in PPC, but not primary auditory cortex (AC). Surprisingly, activity of individual PPC neurons was better explained by external inputs and behavioral variables during biased behavioral performance, while shared variability across neurons in PPC was strongest in the high-performance state. Together, these findings suggest that neural activity in parietal cortex is causally required for decisions and is linked to behavioral performance states.

Identifiers

PMID38826351
PMCPMC11142168

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.