arxiv: 2604.22796 · v1 · submitted 2026-04-13 · 🧬 q-bio.NC

Recognition: unknown

Relationship between the level of mental fatigue induced by a prolonged cognitive task and the degree of balance disturbance

Fr\'ed\'eric No\'e (MEPS) , Betty Hachard (MEPS) , Hadrien Ceyte (DevAH , ISM) , No\"elle Bru (LMAP) , Thierry Paillard (MEPS)

Authors on Pith no claims yet

Pith reviewed 2026-05-10 15:11 UTC · model grok-4.3

classification 🧬 q-bio.NC

keywords mental fatiguebalance controlpostural stabilityAX-CPTinter-individual differencesvisual attentioncluster analysissensory context

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The pith

Mental fatigue from a long cognitive task impairs balance only when eyes are open, due to individual differences in visual reliance.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tests whether mental fatigue induced by a 90-minute AX-CPT task produces consistent effects on standing balance or instead varies sharply across people. Researchers measured balance before and after the task in both eyes-open and eyes-closed conditions on a force platform, then used cluster analysis to group participants by how much their behavior deteriorated. A clear link between the amount of fatigue and the amount of balance disturbance appeared only in the eyes-open condition. This pattern implies that some individuals depend more on vision for stability, making their posture more sensitive to fatigue-induced drops in attention. The work therefore shows that averaging across people can hide important differences in how cognitive load translates into physical instability.

Core claim

The completion of the same prolonged demanding cognitive task induces a strong heterogeneity in subjects' responses, with marked individual differences in mental fatigue vulnerability that affect balance control differently according to the sensory context, specifically showing a significant relationship between the level of mental fatigue and the degree of balance disturbance only when participants stood with the eyes open.

What carries the argument

Hierarchical cluster analysis of behavioral deterioration after the AX-CPT, applied to pre/post force-platform measures of postural sway in eyes-open versus eyes-closed stance.

If this is right

The same cognitive task produces wide variation in both fatigue level and balance impairment across healthy young adults.
The fatigue-balance link is conditional on sensory context and appears only when visual information is available.
Individual differences likely trace to how much each person engages visual attention or relies on visual cues for posture.
Group-level averages can mask the fact that some people experience large balance effects while others show little change.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

Training people to reduce visual field dependence might lower their risk of fatigue-related unsteadiness in daily tasks.
Real-world activities that combine mental effort with standing, such as prolonged driving or monitoring, may show similar selective effects on vision-reliant individuals.
Future experiments could test whether brief visual-attention resets during the cognitive task reduce the observed balance disturbance.

Load-bearing premise

The cluster analysis on how behavior changed after the task correctly sorts people into subgroups that truly differ in fatigue vulnerability rather than reflecting unmeasured differences in fitness or effort.

What would settle it

A follow-up study that repeats the exact AX-CPT and balance protocol but finds no eyes-open-specific correlation between subjective fatigue scores and sway changes, or that the same participants are assigned to different clusters when the analysis method is varied.

Figures

Figures reproduced from arXiv: 2604.22796 by Betty Hachard (MEPS), Fr\'ed\'eric No\'e (MEPS), Hadrien Ceyte (DevAH, ISM), No\"elle Bru (LMAP), Thierry Paillard (MEPS).

**Figure 1.** Figure 1: Illustration of the experimental protocol. MF intervention consisted of performing a 90-min continuous demanding cognitive task (AXCPT). Balance control and performance during the AX-CPT (CR: percentage of correct responses; RT: reaction time) were assessed at baseline (PRE) and at the end of the MF intervention (POST). The relative differences (RD =100*[POST-PRE]/PRE) was calculated in order to character… view at source ↗

read the original abstract

This study investigated the effects of mental fatigue (MF) induced by a 90-min AX-continuous performance test (AX-CPT) on balance control by addressing the issue of the heterogeneity of individuals' responses. Twenty healthy young active participants were recruited. They had to carry out two balance tasks (sway as little as possible on a stable support with the eyes open and closed) when standing on a force platform before and after performing a 90-min AX-CPT. The NASA-TLX test was used to assess the subjective manifestations of MF. Objective cognitive performance was measured using results from the AX-CPT. Inter-individual differences in behavioral deterioration due to MF were analyzed with a hierarchical cluster analysis, which categorizes participants' behaviors into subgroups with similar characteristics. The cluster analysis revealed that the achievement of the AX-CPT induced various levels of MF and balance impairments within the whole sample. A significant relationship between the level of MF and the degree of balance disturbance was observed only when participants stood with the eyes open, thus suggesting that inter-individual differences in vulnerability to MF could stem from differences between subjects in the level of engagement of visual attention and/or from differences in field dependency for balance control. These findings show that the completion of the same prolonged demanding cognitive task induces a strong heterogeneity in subjects' responses, with marked individual differences in MF vulnerability that affect balance control differently according to the sensory context.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper finds mental fatigue correlates with balance issues only eyes-open after using clustering to flag individual differences, but n=20 makes the subgroups fragile.

read the letter

The main point here is that after a 90-minute AX-CPT task, the level of mental fatigue tracked with balance sway only when eyes were open, not closed, and the authors used hierarchical clustering on performance drop and NASA-TLX scores to show this relationship is not uniform across people. That eyes-open specificity is the clearest new angle, suggesting visual attention or field dependence as a possible source of the differences. The work does a decent job of moving past group averages, which is still common in fatigue-posture studies, and the force-platform setup with both sensory conditions is straightforward. The sample is twenty young active adults, which is typical for this kind of lab work but thin for clustering. The abstract does not mention any stability checks, silhouette scores, or bootstrap validation on the clusters, so it is easy to worry that the subgroups are sensitive to the exact variables or linkage method chosen. If those clusters are noisy, the conditional correlation in the eyes-open condition loses force, and unmeasured factors like baseline fitness or motivation could explain the pattern instead. The citation list is not heavy on self-reference, and the design is purely empirical with no circular math. This is useful reading for labs that already work on cognitive load and postural control, especially if they care about why some people show bigger effects than others. It is not a field-changer, but the sensory-context finding is worth checking. I would send it to referees so they can examine the full cluster diagnostics and raw distributions rather than desk-reject it outright.

Referee Report

2 major / 2 minor

Summary. The manuscript reports results from an experiment with 20 healthy young active participants who performed a 90-min AX-CPT to induce mental fatigue (MF), followed by pre/post assessments of balance control (force-platform sway with eyes open and closed) and subjective MF via NASA-TLX. Hierarchical cluster analysis on behavioral deterioration (AX-CPT performance plus NASA-TLX) is used to partition participants into subgroups showing heterogeneous responses; the central empirical claim is that MF level correlates significantly with balance disturbance only in the eyes-open condition, interpreted as evidence for inter-individual differences in visual attention engagement or field dependency.

Significance. If the clustering and conditional correlations prove robust, the work usefully highlights that group-average analyses can mask important individual variability in how MF affects postural control, with sensory-context specificity (eyes-open vs. closed). This could inform applied domains such as ergonomics or fall-risk assessment under cognitive load. The combination of objective cognitive metrics, subjective scales, and dual balance conditions is a methodological strength.

major comments (2)

[Methods and Results (cluster analysis)] The hierarchical cluster analysis (described in the Methods and Results sections) is performed on n=20 without any reported stability or validation metrics (silhouette score, cophenetic correlation, bootstrap resampling, or sensitivity to linkage/distance choices). Because the subsequent MF-balance correlation is conditioned on the derived subgroups, this omission is load-bearing: unstable partitions could artifactually produce the eyes-open-only significance.
[Results (correlation analysis)] The claim of a significant MF-balance relationship 'only when participants stood with the eyes open' (Results) does not specify whether the eyes-open vs. eyes-closed contrast was pre-registered or emerged post-clustering, nor does it report effect sizes, exact p-values, or correction for multiple comparisons. With small n and post-hoc subgrouping, this risks inflated Type I error and undermines the interpretation regarding visual attention or field dependency.

minor comments (2)

[Abstract and Methods] The abstract and Methods should explicitly state the exact distance metric and linkage method used for hierarchical clustering, as these choices directly affect cluster stability.
[Figures and Tables] Figure legends and tables reporting the cluster dendrogram or subgroup statistics would benefit from clearer labeling of participant IDs or raw deterioration scores to allow readers to assess the partitioning.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments, which highlight important issues in the statistical reporting and robustness of our analyses. We address each major comment below and indicate the revisions we will implement.

read point-by-point responses

Referee: The hierarchical cluster analysis (described in the Methods and Results sections) is performed on n=20 without any reported stability or validation metrics (silhouette score, cophenetic correlation, bootstrap resampling, or sensitivity to linkage/distance choices). Because the subsequent MF-balance correlation is conditioned on the derived subgroups, this omission is load-bearing: unstable partitions could artifactually produce the eyes-open-only significance.

Authors: We agree that validation metrics are important for transparency given the sample size. The hierarchical clustering was applied to the combined behavioral deterioration measures (AX-CPT performance decline and NASA-TLX scores) solely to demonstrate inter-individual heterogeneity in MF responses across the full cohort; the MF-balance correlations were computed separately on the entire sample for each sensory condition and were not conditioned on cluster membership. In the revised manuscript we will add silhouette scores, cophenetic correlation values, bootstrap resampling results (e.g., 1000 iterations with Jaccard similarity), and sensitivity checks across linkage methods and distance metrics to quantify partition stability. revision: yes
Referee: The claim of a significant MF-balance relationship 'only when participants stood with the eyes open' (Results) does not specify whether the eyes-open vs. eyes-closed contrast was pre-registered or emerged post-clustering, nor does it report effect sizes, exact p-values, or correction for multiple comparisons. With small n and post-hoc subgrouping, this risks inflated Type I error and undermines the interpretation regarding visual attention or field dependency.

Authors: The two balance conditions (eyes open and eyes closed) were included in the original experimental protocol to allow direct comparison of sensory contexts; the differential correlation pattern was therefore anticipated in the study design rather than arising solely from post-clustering inspection. We did not pre-register the protocol, which we will now state explicitly as a limitation. In revision we will report exact p-values, Pearson r effect sizes with 95% confidence intervals, and apply a multiple-comparison correction (FDR) across the two conditions. We will also clarify in the text that correlations were performed on the full n=20 sample per condition, with clustering used only for descriptive illustration of heterogeneity, thereby removing any implication of post-hoc subgroup conditioning. revision: partial

Circularity Check

0 steps flagged

No circularity: purely empirical data analysis

full rationale

The paper reports an experimental protocol (AX-CPT task, force-platform balance measures, NASA-TLX) followed by standard hierarchical cluster analysis on observed behavioral changes and subsequent correlation tests. No equations, fitted parameters renamed as predictions, self-referential definitions, or load-bearing self-citations appear in the derivation of the central claim. The eyes-open-only correlation is a direct statistical outcome of the measured data partitioned by the clustering step; it does not reduce to its own inputs by construction. The analysis is self-contained against external benchmarks and contains no mathematical chain that could be circular.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The study rests on standard assumptions from cognitive psychology and biomechanics; no new entities are postulated and no free parameters are introduced beyond the choice of clustering method.

axioms (2)

domain assumption The 90-min AX-CPT reliably induces measurable mental fatigue in healthy young adults
Invoked in the methods and results sections to interpret performance decline and subjective scores as fatigue.
domain assumption Hierarchical cluster analysis on behavioral change scores produces stable, meaningful subgroups without overfitting
Used to categorize participants; no validation metrics or sensitivity checks are mentioned in the abstract.

pith-pipeline@v0.9.0 · 5590 in / 1363 out tokens · 50174 ms · 2026-05-10T15:11:13.161384+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

2 extracted references · 2 canonical work pages

[1]

Lê S, Josse J, Husson F (2008) FactoMineR: An R package for multivariate analysis

https://doi.org/ 10.1016/j.jelekin.2018.09.002. Lê S, Josse J, Husson F (2008) FactoMineR: An R package for multivariate analysis. J Stat Softw 25:1-18. https://doi.org/0.18637/jss.v025.i01. Ma J, Yao YJ, Ma RM, Li JQ, Wang T, Li XJ, Han WQ, Hu WD, Zhang ZM (2009) Effects of sleep deprivation on human postural control, subjective fatigue assessment and ps...

work page doi:10.1016/j.jelekin.2018.09.002 2018
[2]

https://doi.org/10.1007/s40279-016-0672-0. Van Dongen HPA, Baynard MD, Maislin G, Dinges DF (2004) Systematic inter- individual differences in neurobehavioral impairment from sleep loss: evidence of trait-like differential vulnerability. Sleep 27:423-433. https://doi.org/10.1093/sleep/27.3.423. Van Dongen HPA (2005) Brain activation patterns and individua...

work page doi:10.1007/s40279-016-0672-0 2004