Neurophysiological and Behavioral Study of the Cognitive Deficits Associated With Cerebral Small Vessel Disease in the SHIVA Cohort - SHIVA-CogNeurophys

Status: Recruiting
Location: See location...
Intervention Type: Device
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY

Cerebral small vessel disease (cSVD) is characterized by an alteration of the structure and function of small penetrating brain arteries. Highly prevalent in older individuals from the general population, it represents a leading cause of stroke and a major contributor to cognitive decline and risk of dementia. Better detection and management of covert cSVD would have a major impact on preventing disability and costs related to stroke, cognitive impairment and dementia. The aim of the present study is to identify novel electroencephalographic (EEG) biomarkers of the cognitive deficits associated with cSVD, and how these biomarkers and cognitive performance are affected by personalized cognitive training or transcranial alternating current stimulation (tACS), a non-invasvie brain stimulation technique.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Healthy Volunteers: f
View:

• Patients included or previously included in the SHIVA cohort

• Basic computer skills (ability to open a browser, use a mouse and keyboard)

• Access to a personal computer with an internet connection

• Independent in Activities of Daily Living (ADL) with a score ≥ 5/6, and in Instrumental Activities of Daily Living (IADL) with a score ≥ 4/8

• Informed and written consent signed by the participant and the investigating physician for this study

Locations
Other Locations
France
CHU de Bordeaux, Hôpital Pellegrin, Unité Neurovasculaire
RECRUITING
Bordeaux
Contact Information
Primary
IGOR SIBON, MD, PhD
igor.sibon@chu-bordeaux.fr
0556795313
Time Frame
Start Date: 2025-08-07
Estimated Completion Date: 2028-03-07
Participants
Target number of participants: 80
Treatments
Experimental: Personalized cognitive training using an AI algorithmwith a non-linear learning path adapted to each
Personalized cognitive training using an AI algorithm (zone of proximal development and empirical success - ZPDES - multi-arm algorithm), with a non-linear learning path adapted to each participant.
Active_comparator: Traditional cognitive training
Traditional cognitive training using a staircase method, featuring a linear progression.
Related Therapeutic Areas
Sponsors
Leads: University Hospital, Bordeaux

This content was sourced from clinicaltrials.gov