Evidence map›Paper›PMID 38106228›Full record

ArticlebioRxiv : the preprint server for biology2023

INDUCING REPRESENTATIONAL CHANGE IN THE HIPPOCAMPUS THROUGH REAL-TIME NEUROFEEDBACK.

Kailong Peng, Jeffrey D Wammes, Alex Nguyen, Marius Cătălin Iordan, Kenneth A Norman, Nicholas B Turk-Browne

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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

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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 3 countries.

Kailong PengDepartment of Psychology, Interdepartmental Neuroscience Program, Yale University.ORCID 0000-0002-9339-0786
Jeffrey D WammesDepartment of Psychology, Centre for Neuroscience Studies, Queen's University.
Alex NguyenDepartment of Psychology, Princeton Neuroscience Institute, Princeton University.
Marius Cătălin IordanDepartment of Brain and Cognitive Sciences, Department of Neuroscience, University of Rochester.
Kenneth A NormanDepartment of Psychology, Princeton Neuroscience Institute, Princeton University.ORCID 0000-0002-5887-9682
Nicholas B Turk-BrowneDepartment of Psychology, Wu Tsai Institute, Yale University.
Princeton University · USYale University · USQueen's University · CAUniversity of Rochester · US

Funding

Modeling the Neural Basis of Episodic MemoryR01MH069456 · NIMH · PRINCETON UNIVERSITY · PI KENNETH A NORMAN, Nicholas Benjamin Turk-Browne · 2004 to 2026
$7.2M
NIMH NIH HHS R01 MH069456
6 · The paper itself

Abstract

When you perceive or remember one thing, other related things come to mind. This competition has consequences for how these items are later perceived, attended, or remembered. Such behavioral consequences result from changes in how much the neural representations of the items overlap, especially in the hippocampus. These changes can reflect increased (integration) or decreased (differentiation) overlap; previous studies have posited that the amount of coactivation between competing representations in cortex determines which will occur: high coactivation leads to hippocampal integration, medium coactivation leads to differentiation, and low coactivation is inert. However, those studies used indirect proxies for coactivation, by manipulating stimulus similarity or task demands. Here we induce coactivation of competing memories in visual cortex more directly using closed-loop neurofeedback from real-time fMRI. While viewing one object, participants were rewarded for implicitly activating the representation of another object as strongly as possible. Across multiple real-time fMRI training sessions, they succeeded in using the neurofeedback to induce coactivation. Compared with untrained objects, this coactivation led to behavioral and neural integration: The trained objects became harder for participants to discriminate in a categorical perception task and harder to decode from patterns of fMRI activity in the hippocampus.

Indexed as

Closed-loop neurofeedbackHigh-performance computingMachine learningNonmonotonic plasticityPsychophysicsReal-time fMRI

Identifiers

PMID38106228
PMCPMC10723264
OpenAlexW4389302645

What OpenQuestion holds

Textmetadata
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.