Evidence map›Paper›PMID 41792202›Full record

ArticleScientific reports2026

Cognitive biotypes identified through ECG-derived workload and behavioral accuracy.

Sarah Conklin, Golshan Kargosha, Jenny Tu, Kanika Bansal, Quang Dang, Justin Brooks, Murat Kucukosmanoglu

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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.

No citing paper in PubMed yet.

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

7 authors.

Sarah ConklinCenter for Women's Biobehavioral Health Research, Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, PA, 15219, USA.
Golshan KargoshaD-Prime LLC, McLean, VA, 22101, USA.
Jenny TuD-Prime LLC, McLean, VA, 22101, USA.
Kanika BansalArmy DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, 21005, MD, USA.
Quang DangDepartment of Computer Science and Electrical Engineering, University of Maryland, 1000 Hilltop Rd, Baltimore County, Baltimore, MD, 21250, USA.
Justin BrooksD-Prime LLC, McLean, VA, 22101, USA.
Murat KucukosmanogluD-Prime LLC, McLean, VA, 22101, USA. murat.kucukosmanoglu@dprime.ai.

Funding

University of Maryland, Baltimore County MIPS0022: 002186-00001
6 · The paper itself

Abstract

Individual differences in physiological effort during cognitive workload, which we define as mental effort during task execution, are well established, yet self-reports often fail to reflect actual physiological effort. We hypothesized that combining cognitive performance with ECG-derived workload would reveal distinct biotypes of performance and physiological effort and that these biotypes would differ in how closely subjective appraisals align with objective measures. Participants completed cognitive tasks while ECG data were analyzed in real time using a validated workload classification algorithm. Clustering based on standardized performance accuracy and cognitive workload revealed three biotypes: (1) high performers with low workload, (2) average-to-high accuracy with high workload, and (3) low performers with variable workload. These biotypes exhibited distinct patterns of perceptual bias: Clusters 1 and 3 showed smaller discrepancies between subjective and objective workload, while Cluster 1 notably underestimated task success relative to their actual performance. These findings demonstrate that clustering behavioral and physiological data can reveal meaningful cognitive stress response profiles and suggest that subjective-objective misalignment may serve as a potential marker of cognitive resilience or poor interoception. This taxonomy may aid future efforts to personalize assessments or interventions aimed at optimizing performance under stress.

Indexed as

CognitionElectrocardiographyWorkloadAlgorithmsClustering AlgorithmsFemaleHumansMaleTask Performance and AnalysisYoung AdultClusteringCognitive biotypesCognitive workloadECGPerceptual bias

Identifiers

PMID41792202
PMCPMC13022197

What Socratic 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 Socratic graph.