2026-10-14T21:33:48Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34054644 2026-10-02T05:37:49Z category_15 portal_316 item_type_3 month_year_10_2026

Supplementary file 1_Tensor decomposition reveals discrete cortical reorganization under graded propofol anesthesia.docx Chuan-Di Tong (25162731) Yun Wang (32846) Zhou-Jing Yang (25162734) Jie-Lu Yu (25162737) Jie-Chun Huang (25162740) Dong-Li Li (8935814) Meng-Fan Hu (25162743) Chen Li (54018) Ruo-Yu Xia (25162746) Xue-Ying Li (1432198) Yi-Qi Wu (20883682) Ruo-Ying Xie (25162749) Neuroscience bicoherence electroencephalography general anesthesia propofol tensor decomposition Background<p>Although propofol-induced anesthesia is known to suppress consciousness by promoting low-frequency frontal oscillations through thalamocortical circuits, a comprehensive understanding of its whole-brain coupling feature set remains elusive. Specifically, the global reorganization of nonlinear cross-frequency coupling remains poorly characterized due to analytical limitations.</p>Methods<p>We analyzed 64-channel EEG data from 17 participants across five states (awake and target propofol concentrations of 1, 2, 3, and 4 mcg/ml, defined as States 1 to 5). After computing time-frequency representation (TFR) and bicoherence, Parallel Factor Analysis (PARAFAC) was used to extract unbiased spatio-spectral components from both linear and nonlinear measures.</p>Results<p>PARAFAC decomposition isolated distinct linear and nonlinear neurodynamic components driving the anesthetic transition. While linear spectral features and signal complexity transitioned in a gradual, monotonic manner. PARAFAC tensor decomposition of high-dimensional whole-brain bicoherence identified two robust, intrinsically decoupled nonlinear components with distinct spatial-spectral profiles. Model comparison demonstrated that frontal slow-wave self-coupling (Component 1) undergoes a discrete, stepwise state-space reconfiguration during loss of consciousness, whereas posterior alpha coupling (Component 2) exhibits a smooth, continuous decay with propofol titration. Phase-space kinetic trajectories confirmed a highly directed transition at unconsciousness onset, followed by confined local oscillations during deep anesthesia.</p>Conclusion<p>This multi-dimensional decomposition framework captures discrete versus continuous neural dynamics, providing objective, state-sensitive biomarkers for precisely monitoring anesthesia depth and cortical state transitions.</p> 2026-10-02T05:37:49Z Dataset Dataset 10.3389/fnins.2026.1950745.s001 https://figshare.com/articles/dataset/Supplementary_file_1_Tensor_decomposition_reveals_discrete_cortical_reorganization_under_graded_propofol_anesthesia_docx/34054644 CC BY 4.0