Study Results
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Basic Information
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RECRUITING
NA
14 participants
INTERVENTIONAL
2025-11-17
2028-04-30
Brief Summary
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Previous training methods have focused on maximizing brain activity during a task. However, new findings show that the best performance is achieved when the brain is already in a state of high communication before the task. Our research shows that people can learn to increase communication between brain regions through neurofeedback.
Studies have shown that neurofeedback can help people after a stroke: it improves the coordination of brain areas that are important for movement, thereby helping to increase mobility. Building on these findings, this study investigates whether EEG neurofeedback can support the visual centers in the brain to improve vision in patients with chronic visual field defects. The main objective of the study is to evaluate the effectiveness of neurofeedback in improving visual field defects. More specifically, the investigators are investigating the development of visual ability (expansion of the visual field, contrast sensitivity).
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
CROSSOVER
TREATMENT
DOUBLE
Study Groups
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Active phase
During the active phase, patients will receive real-time audio feedback on spontaneous alpha-band functional connectivity between ipsilesional associative visual areas and the rest of the brain. This will allow them to learn to improve their pathological brain interactions. The neurofeedback training will last about 40 minutes, with frequent breaks. It will be followed by visual stimulation of the affected visual field according to recommendations for inducing steady-state visual evoked potentials.
neurofeedback
The proposed neurofeedback approach relies on high-density electroencephalography (EEG) combined with advanced source localization algorithms. Data will be analyzed in real-time and simultaneously recorded for offline analysis. During each update, a data segment will be filtered between 1 and 20 Hz. The beamformer, computed at the beginning of the session, will be used to project the signal to the gray-matter voxels.
The investigators will compute the alpha-band absolute imaginary coherence between a visual target area and the rest of the brain as index of functional connectivity. Global functional connectivity in the alpha band (8-13 Hz) between the voxels in the target region and the rest of the brain will be calculated.
control phase
The control phase is structured identically to the active period, except that the acoustic neurofeedback is synthetically generated and not linked to the subject's actual functional connectivity, while still resembling its dynamic characteristics to ensure effective blinding. The training will last about 40 minutes, with frequent breaks. The training will be followed by visual stimulation of the affected visual field, just as in the active condition.
neurofeedback
The proposed neurofeedback approach relies on high-density electroencephalography (EEG) combined with advanced source localization algorithms. Data will be analyzed in real-time and simultaneously recorded for offline analysis. During each update, a data segment will be filtered between 1 and 20 Hz. The beamformer, computed at the beginning of the session, will be used to project the signal to the gray-matter voxels.
The investigators will compute the alpha-band absolute imaginary coherence between a visual target area and the rest of the brain as index of functional connectivity. Global functional connectivity in the alpha band (8-13 Hz) between the voxels in the target region and the rest of the brain will be calculated.
Interventions
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neurofeedback
The proposed neurofeedback approach relies on high-density electroencephalography (EEG) combined with advanced source localization algorithms. Data will be analyzed in real-time and simultaneously recorded for offline analysis. During each update, a data segment will be filtered between 1 and 20 Hz. The beamformer, computed at the beginning of the session, will be used to project the signal to the gray-matter voxels.
The investigators will compute the alpha-band absolute imaginary coherence between a visual target area and the rest of the brain as index of functional connectivity. Global functional connectivity in the alpha band (8-13 Hz) between the voxels in the target region and the rest of the brain will be calculated.
Eligibility Criteria
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Inclusion Criteria
* 12 months or more after stroke
* Age range 50-70
* Ability to provide informed consent
Exclusion Criteria
* Eye disease with impact on visual field or acuity
* Presence of non-MRI safe metal in the body
* New stroke during study period
* Hemispatial neglect
50 Years
70 Years
ALL
No
Sponsors
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Adrian Guggisberg
OTHER
Responsible Party
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Adrian Guggisberg
Full Professor
Locations
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Inselspital
Bern, Canton of Bern, Switzerland
Division of Neurorehabilitation, University Hospital of Geneva
Geneva, Canton of Geneva, Switzerland
Countries
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Central Contacts
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Facility Contacts
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References
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Sabel BA, Henrich-Noack P, Fedorov A, Gall C. Vision restoration after brain and retina damage: the "residual vision activation theory". Prog Brain Res. 2011;192:199-262. doi: 10.1016/B978-0-444-53355-5.00013-0.
Mottaz A, Corbet T, Doganci N, Magnin C, Nicolo P, Schnider A, Guggisberg AG. Modulating functional connectivity after stroke with neurofeedback: Effect on motor deficits in a controlled cross-over study. Neuroimage Clin. 2018 Jul 30;20:336-346. doi: 10.1016/j.nicl.2018.07.029. eCollection 2018.
Allaman L, Mottaz A, Kleinschmidt A, Guggisberg AG. Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations. J Neurosci. 2020 Dec 9;40(50):9663-9675. doi: 10.1523/JNEUROSCI.1166-20.2020. Epub 2020 Nov 6.
Allaman L, Mottaz A, Guggisberg AG. Disrupted resting-state EEG alpha-band interactions as a novel marker for the severity of visual field deficits after brain lesion. Clin Neurophysiol. 2021 Sep;132(9):2101-2109. doi: 10.1016/j.clinph.2021.05.029. Epub 2021 Jun 28.
Other Identifiers
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2025-00765
Identifier Type: -
Identifier Source: org_study_id
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