Evidence map›Paper›PMID 37494185›Full record

ArticleCell reports2023

Electrophysiological signatures of inequity-dependent reward encoding in the human OFC.

Deborah Marciano, Brooke R Staveland, Jack J Lin, Ignacio Saez, Ming Hsu, Robert T Knight

Open access · goldAbstract read
In one paragraph

Article in Cell reports, 2023. 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
3.0field-weighted citation impact, top 8% of its field
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, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Human Substantia Nigra Neurons Encode Reward Expectations.bioRxiv : the preprint server for biology · 2024
    Article
  7. Encoding of Predictive Associations in Human Prefrontal and Medial Temporal Neurons During Pavlovian Appetitive Conditioning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    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

6 authors at 3 institutions in 1 country.

Deborah MarcianoHelen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Haas School of Business, University of California, Berkeley, Berkeley, CA 94720, USA.
Brooke R StavelandHelen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
Jack J LinDepartment of Neurology, University of California, Davis, Davis, CA 95616, USA; Center for Mind and Brain, University of California, Davis, Davis, CA 95616, USA.
Ignacio SaezDepartments of Neuroscience, Neurosurgery and Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: ignacio.saez@mssm.edu.
Ming HsuHelen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Haas School of Business, University of California, Berkeley, Berkeley, CA 94720, USA. Electronic address: mhsu@haas.berkeley.edu.
Robert T KnightHelen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA. Electronic address: rtknight@berkeley.edu.
University of California, Berkeley · USIcahn School of Medicine at Mount Sinai · USUniversity of California, Davis · US

Funding

Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI Michael Peter Milham, CHARLES E SCHROEDER · 2017 to 2026
$25.3M
Neural circuit theory and trained recurrent network modeling of rapid learningU19NS107609 · NINDS · UNIVERSITY OF WASHINGTON · PI FAIRHALL, ADRIENNE L · 2018 to 2022
$12.6M
Attention, Orientation and the Human Prefrontal CortexR01NS021135 · NINDS · UNIVERSITY OF CALIFORNIA DAVIS · PI Robert Thomas Knight · 1985 to 2026
$6.5M
Invasive decoding and stimulation of altered reward computations in depressionR01MH124763 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SAEZ, IGNACIO · 2021 to 2025
$3.9M
Electrocorticography of human prefrontal cortex during value-based decision-makingK01MH108815 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI SAEZ, IGNACIO · 2016 to 2019
$742k
Cortical Oscillatory Dynamics and Human Decision-MakingR21MH109851 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI HSU, MING, KNIGHT, ROBERT THOMAS · 2016 to 2017
$432k
NIMH NIH HHS K01 MH108815NIMH NIH HHS P50 MH109429NIMH NIH HHS R01 MH124763NIMH NIH HHS R21 MH109851NINDS NIH HHS R01 NS021135NINDS NIH HHS U19 NS107609
6 · The paper itself

Abstract

Social decision making requires the integration of reward valuation and social cognition systems, both dependent on the orbitofrontal cortex (OFC). How these two OFC functions interact is largely unknown. We recorded intracranial activity from the OFC of ten patients making choices in a social context where reward inequity with a social counterpart varied and could be either advantageous or disadvantageous. We find that OFC high-frequency activity (HFA; 70-150 Hz) encodes self-reward, consistent with previous reports. We also observe encoding of the social counterpart's reward, as well as the type of inequity being experienced. Additionally, we find evidence of inequity-dependent reward encoding: depending on the type of inequity, electrodes rapidly and reversibly switch between different reward-encoding profiles. These results provide direct evidence for encoding of self- and other rewards in the human OFC and highlight the dynamic nature of encoding in the OFC as a function of social context.

Indexed as

NeuronsPrefrontal CortexHumansRewardcontextCP: Neurosciencedecision makingHFAiEEGinequityneuroscienceorbitofrontal cortexsocial valuation

Identifiers

PMID37494185
PMCPMC12199477
OpenAlexW4385294935

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.