# Quantifying motor–cognitive reserve using a novel multi-modal stress test

**Authors:** Tal Kozlovski, Inbal Maidan, Eran Gazit, Amgad Droby, Avner Thaler, Jeffrey M Hausdorff, Nir Giladi, Yoav Benjamini, Anat Mirelman

PMC · DOI: 10.1093/braincomms/fcaf412 · Brain Communications · 2025-10-24

## TL;DR

Researchers developed a new stress test to measure combined motor and cognitive reserve, showing it effectively identifies neurological deficits and predicts decline in neurodegenerative diseases.

## Contribution

A novel multi-modal stress test and machine learning-based MCR index that quantifies motor-cognitive reserve with high sensitivity and validity.

## Key findings

- The MCR index showed decreased performance with increased motor and cognitive challenges (P < 0.001).
- The index accurately discriminated between healthy controls and neurological conditions with an AUC of 0.89.
- The MCR index correlated significantly with brain volumes and cognitive/motor proxies (all P < 0.05).

## Abstract

Reserve is a physiological capacity used under demanding situations. The concept was developed to account for the discrepancy between pathology and clinical manifestation. In neuroscience, motor, brain and cognitive reserves are abstract measures, conceptually defined yet elusive to quantify. Reserve is indirectly assessed using proxies such as years of education and brain volume, limiting its utility. Moreover, the dichotomy in definitions of cognitive and motor reserves is artificial, as daily function requires an intricate network of connections between these domains. Here, we assessed the validity of a newly developed graded motor cognitive ‘stress test’ to quantify the combined motor and cognitive reserve (MCR). The study included 144 participants (ages between 18 and 85, 50% women) with a range of reserve capacities (i.e. healthy young and older adults and individuals with Parkinson's disease, Alzheimer’s disease, dementia with Lewy bodies and mild cognitive impairment). The assessment included walking on a treadmill while negotiating motor and cognitive challenges delivered using virtual reality. To establish an MCR index score, we used a semi-supervised machine learning algorithm. The model includes performance measures from completing the stress test and measures obtained from wearable sensors used during the test. Validation of the proposed MCR index was examined through: (i) model face validity–reflecting decline of performance as challenge increased; (ii) known-groups validity—classification of scores according to neurological status; (iii) construct validity (convergent)—association with common MCRs proxies as well as MRI-derived regional brain volumes. The model's face validity revealed decreased performance with increased motor and cognitive challenges (both domains P < 0.001). The index accurately discriminated between healthy controls and those diagnosed with neurological conditions with an area under the curve of 0.89 [95% CI: 0.79–0.99] which was significantly higher than all other commonly used proxies. Statistically significant Spearman's ρ correlations were observed with all commonly used motor and cognitive proxies (0.56 ≤ r ≤ 0.79, after multiplicity correction all P < 0.05), reflecting construct validity. In addition, statistically significant correlations were observed between the MCR index and whole-brain grey matter and white matter volumes (r = 0.63 and 0.55), as well as the pre-defined left and right caudate nucleus (r = 0.56 and 0.68) and inferior-frontal gyrus (r = 0.47 and 0.58). This proof-of-concept study shows that the novel MCR index is valid, with high sensitivity to neurological deficits and is able to quantify reserve on an individual level. This new innovative tool can assist in screening for motor cognitive deficits and potentially, for predicting motor and cognitive decline associated with neurodegenerative disease.

Kozlovski et al. present a novel motor–cognitive stress test that yields a score index aimed at capturing motor–cognitive reserve capacity. The authors validated the index across three aspects: face validity, discriminant validity and construct validity, supporting its potential for identifying individuals at risk for neurodegenerative diseases.

Graphical Abstract

## Linked entities

- **Diseases:** Parkinson's disease (MONDO:0005180), Alzheimer’s disease (MONDO:0004975), dementia with Lewy bodies (MONDO:0007488)

## Full-text entities

- **Diseases:** cognitive decline (MESH:D003072), neurodegenerative disease (MESH:D019636), dementia with Lewy bodies (MESH:D020961), neurological deficits (MESH:D009461), Alzheimer's disease (MESH:D000544), Parkinson's disease (MESH:D010300)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

79 references — full list in the complete paper: https://tomesphere.com/paper/PMC12613160/full.md

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Source: https://tomesphere.com/paper/PMC12613160