Quantifying Consciousness

MSc thesis: EEG complexity measures for Disorders of Consciousness — 183 subjects, 732 datasets, two methods, consciousness as criticality.

Problem

• Misdiagnosis rates for Disorders of Consciousness sit around 40% with bedside behavioral exams.
• Patients are routinely classified as Vegetative when they retain awareness, or vice versa.

Approach

• Lempel-Ziv Complexity computed per channel after Hilbert transform and rate-binarization.
• Neuronal avalanche analysis — power-law fits extracting α, τ, σ (branching ratio), and a cutoff scale.
• A custom heartbeat-artifact detector rejecting cardiac-related ICA components — a confound prior work had not removed.
• Both metrics computed on 183 subjects × 4 tasks = 732 datasets.

Outcome

• LZC discriminates monotonically along the consciousness spectrum (F = 48.99, p < 10⁻²⁵).
• All DOC groups are significantly subcritical (σ < 1); healthy controls sit near σ ≈ 1.05 — the knife edge of criticality.
• The σ–LZC relationship is non-linear (Pearson R = 0.09, n.s.) — consistent with a phase-transition picture of consciousness.