{"paper":{"title":"Interpretable Electrophysiological Features of Resting-State EEG Capture Cortical Network Dynamics in Parkinsons Disease","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"Interpretable EEG features distinguish Parkinsonian neural states from healthy controls and track medication effects through standard and dynamical descriptors.","cross_cats":["q-bio.QM"],"primary_cat":"q-bio.NC","authors_text":"Antonios G. Dougalis","submitted_at":"2026-04-01T23:31:38Z","abstract_excerpt":"Parkinsons disease (PD) alters cortical neural dynamics, yet reliable non-invasive electrophysiological biomarkers remain elusive. This study examined whether interpretable EEG features capturing complementary aspects of neural dynamics can discriminate Parkinsonian neural states. A comprehensive set of interpretable features was extracted and grouped into Standard descriptors (spectral power, phase synchronization, time-domain statistics) and Dynamical descriptors (aperiodic activity, cross-frequency coupling, scale-free dynamics, neuronal avalanche statistics, and instantaneous frequency mea"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"These findings support multivariate EEG representations as a promising framework for developing non-invasive biomarkers of PD.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the extracted interpretable features, particularly the dynamical descriptors, faithfully capture underlying cortical network dynamics without substantial contamination from recording artifacts, volume conduction, or unaccounted individual variability in a clinical population.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Resting-state EEG features grouped into standard and dynamical sets discriminate Parkinson's disease from controls and off-medication from on-medication states via transformer classification.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Interpretable EEG features distinguish Parkinsonian neural states from healthy controls and track medication effects through standard and dynamical descriptors.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"c330f9f03e5a6335b5b44fb7b5d7d1366ae51c1934b3a9ad0f197de101f20855"},"source":{"id":"2604.01475","kind":"arxiv","version":3},"verdict":{"id":"8c79fe07-bf3d-4fe2-b771-64bee68f5799","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-13T21:15:11.055922Z","strongest_claim":"These findings support multivariate EEG representations as a promising framework for developing non-invasive biomarkers of PD.","one_line_summary":"Resting-state EEG features grouped into standard and dynamical sets discriminate Parkinson's disease from controls and off-medication from on-medication states via transformer classification.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the extracted interpretable features, particularly the dynamical descriptors, faithfully capture underlying cortical network dynamics without substantial contamination from recording artifacts, volume conduction, or unaccounted individual variability in a clinical population.","pith_extraction_headline":"Interpretable EEG features distinguish Parkinsonian neural states from healthy controls and track medication effects through standard and dynamical descriptors."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.01475/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"2401604db74a846835ce2a6215b76b60d2819e6096a4ecb4e569d60ab18882a4"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}