Evidence map›Paper›PMID 42331397›Full record

ReviewThe European journal of neuroscience2026

Deciphering Freezing of Gait: What Neuropathology Reveals About an Episodic Phenomenon.

Gabor G Kovacs

Abstract readReview
In one paragraph

Review in The European journal of neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

1 author.

Gabor G KovacsTanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada.ORCID 0000-0003-3841-5511

Funding

Rossy Family Foundation
6 · The paper itself

Abstract

Freezing of gait (FoG) is an episodic, debilitating motor phenomenon defined as paroxysmal episodes wherein there is an inability to step effectively, despite attempting to do so. Although FoG is most commonly associated with Parkinson's disease, it manifests across a spectrum of progressive neurodegenerative and potentially transient non-neurodegenerative conditions that affect overlapping locomotor circuits. The episodic nature of FoG implies transient disruptions of a distributed locomotor network rather than fixed structural lesions, rendering its neuropathological basis particularly challenging to define. This review synthesizes current knowledge of the structural, neurochemical and proteinopathic substrates that precondition and precipitate FoG. The principal disease categories implicated in FoG are reviewed, including Lewy body diseases, progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration and argyrophilic grain disease, as well as non-neurodegenerative conditions such as cerebrovascular disease and metabolic encephalopathy. Mixed and overlapping pathologies are common. Across these disorders, different disease stages and phases, and their frequent combinations, interact with selective vulnerability of distinct neuronal and glial populations, giving rise to a complex pathophysiological landscape. It is proposed that this convergence results in heightened network susceptibility, whereby cumulative damage to cortical, subcortical and brainstem locomotor nodes progressively lowers the threshold for episodic circuit failure. Understanding these multilevel neuropathological determinants is essential for developing targeted therapeutic strategies aimed at stabilizing the locomotor network and reducing FoG burden.

Indexed as

BrainGait Disorders, NeurologicNeurodegenerative DiseasesAnimalsHumansastrogliafreezing of gaitlimbic systemmixed pathologyneurodegenerative proteinopathyneuropathology

Identifiers

PMID42331397
PMCPMC13286701

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.