Evidence map›Paper›PMID 38106094›Full record

ArticlebioRxiv : the preprint server for biology2023

Trying harder: how cognitive effort sculpts neural representations during working memory.

Sarah L Master, Shanshan Li, Clayton E Curtis

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, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Sarah L MasterDepartment of Psychology, New York University.ORCID 0000-0003-2726-4586
Shanshan LiDepartment of Psychology, New York University.ORCID 0009-0006-8086-5814
Clayton E CurtisDepartment of Psychology, New York University.ORCID 0000-0003-0702-1499
New York University · US

Funding

Putting Priority Map Theory to the TestR01EY016407 · NEI · NEW YORK UNIVERSITY · PI CURTIS, CLAYTON E · 2006 to 2023
$5.8M
TRAINING IN VISUAL NEUROSCIENCET32EY007136 · NEI · NEW YORK UNIVERSITY · PI J ANTHONY MOVSHON · 1993 to 2026
$5.3M
The Nature of Working Memory RepresentationsR01EY033925 · NEI · NEW YORK UNIVERSITY · PI CURTIS, CLAYTON E · 2022 to 2025
$1.5M
Neural decoding of working memoryR01EY027925 · NEI · NEW YORK UNIVERSITY · PI CURTIS, CLAYTON E, MA, WEI JI · 2017 to 2020
$1.3M
NEI NIH HHS R01 EY016407NEI NIH HHS R01 EY027925NEI NIH HHS R01 EY033925NEI NIH HHS T32 EY007136
6 · The paper itself

Abstract

The neural mechanisms by which motivational factors influence cognition remain unknown. Using fMRI, we tested how cognitive effort impacts working memory (WM). Participants were precued whether WM difficulty would be hard or easy. Hard trials demanded more effort as a later decision required finer mnemonic precision. Behaviorally, pupil size was larger and response times were slower on hard trials suggesting our manipulation of effort succeeded. Neurally, we observed robust persistent activity in prefrontal cortex, especially during hard trials. We found strong decoding of location in visual cortex, where accuracy was higher on hard trials. Connecting these across-region effects, we found that the amplitude of delay period activity in frontal cortex predicted decoded accuracy in visual cortex on a trial-wise basis. We conclude that the gain of persistent activity in frontal cortex may be the source of effort-related feedback signals that improve the quality of WM representations stored in visual cortex.

Indexed as

cognitive effortdecodingfMRIhumanmodelingretinotopyworking memory

Identifiers

PMID38106094
PMCPMC10723420
OpenAlexW4389497563

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.