Evidence map›Paper›PMID 41627573›Full record

ArticleBrain topography2026

Exploring Dynamic Alpha Band Connectivity in Parkinson's Disease: A Novel Approach to Postural Control Assessment Using the BioVRSea Paradigm.

Federica Pescaglia, Lorena Guerrini, Carmine Gelormini, Romain Aubonnet, Gylfi Örn Thormar, Giorgio Di Lorenzo, Halldór Jónsson, Mahmoud Hassan, Hannes Petersen, Vincenzo Minutolo and 1 more

Abstract read
In one paragraph

Article in Brain topography, 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. 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

11 authors.

Federica Pescaglia *Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland.
Lorena Guerrini *Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland.
Carmine GelorminiInstitute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland.
Romain AubonnetLaboratory of Psychophysiology and Cognitive Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy.
Gylfi Örn ThormarDepartment of Neurology, Landspitali University Hospital, Reykjavik, Iceland.
Giorgio Di LorenzoLaboratory of Psychophysiology and Cognitive Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy.
Halldór JónssonInstitute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland.
Mahmoud HassanInstitute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland.
Hannes PetersenDepartment of Anatomy, School of Health Sciences, Biochemistry, University of Iceland, Reykjavik, Iceland.
Vincenzo MinutoloDepartment of Mathematics, Physics and Engineering Applications, University of Campania L. Vanvitelli, Caserta, Italy.
Paolo GargiuloInstitute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland. paolo@ru.is.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's Disease (PD) is a neurological disorder characterized by impaired postural control (PC) and balance issues. To date, few studies have explored the relationship between brain activity and responses during specific tasks designed to challenge balance in individuals with PD. Our exploratory research employs an innovative paradigm to assess PC by integrating virtual reality (VR) and electroencephalography (EEG). In the study, 20 individuals diagnosed with PD who self-reported postural instability participated in the BioVRSea paradigm. This paradigm tested their PC using visuomotor stimuli and collected EEG signals to assess brain responses throughout the experiment. The results of the Parkinson's group were compared with those of 22 age-matched healthy controls (CTR). From the functional connectivity between brain regions, we extracted brain network states (BNSs) using the k-means++ clustering algorithm. These BNSs capture the dynamic organization of brain activity and were compared with canonical resting-state networks (RSNs) to investigate neural alterations in individuals with PD. Six distinct BNSs were identified, with the dorsal attention network (DAN) dominant in five states. A significant reduction in the coverage of BNS2 was observed in PD patients during both the PRE (adjusted p-value = 0.019) and MOV (adjusted p-value = 0.036) phases compared to CTR. This reduced BNS2 coverage suggests impaired visuomotor integration in PD patients during PC tasks. DAN dominance highlights its crucial role in maintaining attentional control during the task. The findings of this study highlight the potential of using brain dynamics as a biomarker of neural dysfunction in PD, especially during specific PC tasks. Altered BNSs, particularly in networks associated with attention and sensorimotor integration, reveal key neural deficits related to PD.

Indexed as

Alpha RhythmBrainParkinson DiseasePostural BalanceAgedBrain MappingElectroencephalographyFemaleHumansMaleMiddle AgedNeural PathwaysVirtual RealityBrain Network StatesElectroencephalographyParkinson’s DiseasePostural Control

Identifiers

PMID41627573
PMCPMC12864210

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.