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{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D059345', 'term': 'Cerebral Small Vessel Diseases'}, {'id': 'D020521', 'term': 'Stroke'}, {'id': 'D060825', 'term': 'Cognitive Dysfunction'}, {'id': 'D003704', 'term': 'Dementia'}], 'ancestors': [{'id': 'D002561', 'term': 'Cerebrovascular Disorders'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D003072', 'term': 'Cognition Disorders'}, {'id': 'D019965', 'term': 'Neurocognitive Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 80}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-07-09', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-07', 'completionDateStruct': {'date': '2025-07-09', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-07-15', 'studyFirstSubmitDate': '2025-07-04', 'studyFirstSubmitQcDate': '2025-07-15', 'lastUpdatePostDateStruct': {'date': '2025-07-16', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-07-16', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-07-09', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'EEG signal power', 'timeFrame': 'Day 0, Day 26, Day 33', 'description': 'The primary outcome measure is the average EEG signal power (across different frequency bands and for various electrodes) between the two participant groups with either minor or extensive cSVD'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Cognitive decline', 'dementia', 'stroke', 'small vessel disease', 'healthy brain aging', 'electroencephalography', 'neuromodulation', 'transcranial alternating current stimulation', 'cognitive training', 'cognitive rehabilitation'], 'conditions': ['Cerebral Small Vessel Disease', 'Stroke', 'Cognitive Complaint']}, 'descriptionModule': {'briefSummary': '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.\n\nBetter 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.', 'detailedDescription': 'cSVD is by far the most prevalent vascular contributor to cognitive impairment in the population. However, accurate quantitative estimates of the predictive ability of cSVD for risk of dementia are lacking. Moreover, stratification of cognitive decline and risk of dementia in cSVD patients according to imaging characteristics as well as evidence of coexisting neurodegenerative disease and vascular comorbidity are lacking. Moreover, there is currently no specific mechanism-based treatment, leading to empirical and heterogeneous clinical practice, which in most instances consists of ignoring these lesions. This clinical blind spot represents a major "missed opportunity" for the prevention of cognitive decline and dementia.\n\nThis study aims to explore the electroencephalographic (EEG) characteristics of patients with either extensive or minimal neurovascular lesions due to cSVD in 80 patients above 60 years old. The main goal is to identify EEG biomarkers that characterize these lesions and the associated cognitive deficits. Secondary objectives aim to assess the potential impact of cognitive training paradigms and non-invasive brain stimulation (namely transcranial alternating current stimulation - tACS) on these biomarkers and on cognitive performance.\n\nParticipants will be divided into two groups. The first group will consist of patients with no or minor white matter hyperintensities on brain MRI (i.e. features of minor cSVD) , while the second group will include patients with moderate to severe white matter hyperintensities (i.e., features of extensive cSVD).\n\nThis exploratory study leverages the uniqueness of the SHIVA cohort, a deeply characterized resource for investigation of cSVD. To our knowledge, the combination of EEG recordings, cognitive training, and noninvasive brain stimulation in cSVD patients is entirely novel'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients included or previously included in the SHIVA cohort\n* Basic computer skills (ability to open a browser, use a mouse and keyboard)\n* Access to a personal computer with an internet connection\n* 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\n* Informed and written consent signed by the participant and the investigating physician for this study\n\nExclusion Criteria:\n\n* Motor impairments preventing the use of a keyboard and mouse (e.g., motor issues related to severe hand osteoarthritis)\n* Depressive symptoms indicated by a score of 2 to 4 on the mini Geriatric Depression Scale (mini GDS), which includes 4 items\n* Age-related macular degeneration (AMD)\n* Untreated glaucoma\n* Untreated psychiatric conditions that interfere with cognitive assessments\n* Diagnosed attention deficit disorder with or without hyperactivity or patients who could not complete all cognitive tests required in the SHIVA cohort\n* Systemic diseases that cause cognitive changes, such as obesity and metabolic disorders\n* History of epilepsy or seizures\n* Scalp sensitivity or skin lesions (dermatitis, wounds, etc.)\n\nContraindications for the use of electrical stimulation:\n\n* Surgical clips, metal sutures, staples, stents\n* Osteosynthesis material in the head or neck\n* Pacemaker\n* Implanted hearing aid\n* Ocular foreign bodies, shrapnel, bullets\n* Metalworker\n* Pacemaker or neurostimulator\n* Heart valve or endovascular material\n* Ventricular shunt valve\n\n * Recent exposure (\\< 6 months) to brain stimulation (tDCS, TMS, etc.)\n * Ongoing participation in a clinical trial or cognitive training program'}, 'identificationModule': {'nctId': 'NCT07068620', 'acronym': 'SHIVA-CogNeuro', 'briefTitle': 'Neurophysiological and Behavioral Study of the Cognitive Deficits Associated With Cerebral Small Vessel Disease in the SHIVA Cohort. SHIVA-CogNeurophys', 'organization': {'class': 'OTHER', 'fullName': 'University Hospital, Bordeaux'}, 'officialTitle': 'Neurophysiological and Behavioral Study of the Cognitive Deficits Associated With Cerebral Small Vessel Disease in the SHIVA Cohort - SHIVA-CogNeurophys', 'orgStudyIdInfo': {'id': 'CHUBX 2024-81'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Personalized cognitive training using an AI algorithmwith a non-linear learning path adapted to each', 'description': '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.', 'interventionNames': ['Device: Home-based cognitive training']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Traditional cognitive training', 'description': 'Traditional cognitive training using a "staircase" method, featuring a linear progression.', 'interventionNames': ['Device: Home-based cognitive training']}], 'interventions': [{'name': 'Home-based cognitive training', 'type': 'DEVICE', 'description': 'All interventions will be carried out for both groups of participants, with either minimal or extensive cSVD.\n\nUpon enrollment, each participant will undergo two hospital visits (visit 1 at day 0, visit 2 at day 7), followed by a home-based cognitive training across 10 days (days 15-24), two more hospital visits (visit 3 at day 26, visit 4 at day 33), and finally a follow-up cognitive testing at home after 6 months.', 'armGroupLabels': ['Personalized cognitive training using an AI algorithmwith a non-linear learning path adapted to each', 'Traditional cognitive training']}]}, 'contactsLocationsModule': {'locations': [{'zip': '33000', 'city': 'Bordeaux', 'country': 'France', 'contacts': [{'name': 'IGOR SIBON, MD, PhD', 'role': 'CONTACT', 'email': 'igor.sibon@chu-bordeaux.fr', 'phone': '0556795313', 'phoneExt': '+33'}, {'name': 'Jean-Sébastien LIEGEY, MD', 'role': 'CONTACT', 'email': 'jean-sebastien.liegey@chu-bordeaux.fr', 'phone': '0557656325', 'phoneExt': '+33'}, {'name': 'iGOR SIBON, MD,PhD', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': 'CHU de Bordeaux, Hôpital Pellegrin, Unité Neurovasculaire', 'geoPoint': {'lat': 44.84124, 'lon': -0.58046}}], 'centralContacts': [{'name': 'IGOR SIBON, MD, PhD', 'role': 'CONTACT', 'email': 'igor.sibon@chu-bordeaux.fr', 'phone': '0556795313', 'phoneExt': '+33'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University Hospital, Bordeaux', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}