Evidence map›Paper›PMID 40002482›Full record

ReviewBrain sciences2025

Eye-Tracking Metrics as a Digital Biomarker for Neurocognitive Disorders in Multiple Sclerosis: A Scoping Review.

Sonja Cecchetti, Andrew T Duchowski, Marco Cavallo

Abstract readReview
In one paragraph

Review in Brain sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
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

3 authors.

Sonja CecchettiDepartment of Theoretical and Applied Sciences, eCampus University, 22060 Novedrate, Italy.ORCID 0009-0008-2439-0361
Andrew T DuchowskiSchool of Computing, Clemson University, Clemson, SC 29634, USA.ORCID 0000-0003-1681-7878
Marco CavalloDepartment of Theoretical and Applied Sciences, eCampus University, 22060 Novedrate, Italy.ORCID 0000-0002-4784-0803

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) is an autoimmune disease classified as neurodegenerative because it can be associated with the more or less progressive development of neurological symptoms and cognitive deficits. In recent years, various studies have started to investigate eye movements in relation to cognitive impairment in persons with MS by means of eye-tracking equipment. However, the high heterogeneity of the paradigms used in different studies, as well as the different methodologies included, makes it difficult to provide a complete and precise picture of this important research and clinical issue. The purpose of the present in-depth scoping review was to map the existing literature in this field to determine which metrics may be relevant when dealing with the neurocognitive profile of people with MS. From the analyses of the included studies, the anti-saccade latency and errors were the most frequently proposed metrics. Correlation analyses between these metrics and cognitive measures showed significant associations between them, calling for a deeper investigation of this promising research and clinical field. The results of the present scoping review strongly suggest that eye tracking may play a crucial role in clinical practice during the early detection of neurocognitive disorders. There is a great need for primary research that addresses the full complexity of MS in its different phenotypes and the disease-related variables from a multidisciplinary perspective. Future research should clarify whether oculomotor dysfunction in MS follows or precedes cognitive deficits.

Indexed as

cognitive taskdigital biomarkereye movementseye trackingmetricsmultiple sclerosisneurodegenerative disorderoculomotor systemsaccades

Identifiers

PMID40002482
PMCPMC11852410

What OpenQuestion holds

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Registered trials

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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.