A brain-computer interface-oriented neural perturbation tACS sleep brain network individualized closed-loop regulation method and system
By constructing a fusion brain functional connectivity matrix and a Transformer neurodynamic prediction model, and optimizing tACS stimulation parameters, the problem of individual differences and directional information flow being difficult to characterize in existing technologies was solved, realizing individualized and interpretable sleep brain network regulation and improving sleep memory consolidation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHONGQING UNIV OF POSTS & TELECOMM
- Filing Date
- 2026-06-11
- Publication Date
- 2026-07-17
AI Technical Summary
Existing tACS sleep regulation protocols fail to account for individual differences, resulting in unstable stimulation effects, a lack of interpretable parameters, and difficulty in achieving individualized and dynamic adjustments. Traditional sleep EEG analysis cannot characterize the directional causal relationship between excitation and inhibition information flow.
We construct a personalized closed-loop modulation method for the tACS sleep brain network based on brain-computer interfaces. By acquiring EEG data and cognitive task behavior data from the entire night's sleep, we construct a fusion brain function connectivity matrix and optimize stimulation parameters using the Transformer neurodynamic prediction model to achieve individualized neuromodulation.
It achieves individualized neuromodulation, improves the scientific validity and interpretability of stimulation parameters, and can dynamically adjust stimulation according to the real-time brain network state, thereby enhancing the consolidation effect of sleep memory.
Smart Images
Figure CN122399247A_ABST