EEG Marker May Predict Consciousness and Recovery

Peripersonal space index was associated with conscious states and outcomes in patients with brain injury

By
Andrea Surnit
April 21, 2026
3 min

Conexiant

Overview

An EEG-based peripersonal space (PPS) index derived from high-beta oscillations distinguishes conscious from unconscious states and predicts recovery in patients with disorders of consciousness. The PPS index correlates with clinical scales and brain network integrity, showing higher predictive value than behavioral assessments alone.

Background

Disorders of consciousness (DoC) pose challenges in assessing patient awareness and predicting recovery. Traditional behavioral assessments can be limited by patients' responsiveness. Electroencephalography (EEG) offers a non-invasive method to detect neural markers of consciousness. This study investigated a PPS index based on multisensory integration measured by high-beta EEG oscillations during an audiotactile paradigm to differentiate conscious states and predict clinical outcomes.

Data Highlights

Measure	Correlation (R)	Predictive Value	Specificity
PPS index vs Coma Recovery Scale–Revised	0.35
PPS index vs Clinical Outcome at Discharge	0.43
Positive Predictive Value (PPS index)		86%	98%
Positive Predictive Value (Behavioral Assessment)		67%	89%
PPS index vs Forebrain Mesocircuit Integrity (subset)	0.71
PPS index vs DMN-DAN Coupling (subset)	-0.59

Key Findings

The PPS index is present during wakefulness and dreaming but absent during dreamless sleep in healthy individuals.
The PPS index differentiates conscious (dreaming) from unconscious (no-experience) sleep states.
In patients with disorders of consciousness, the PPS index correlates positively with clinical consciousness scales and predicts better recovery outcomes.
The PPS index has higher positive predictive value (86%) and specificity (98%) for recovery than behavioral assessments alone.
Combining PPS index with behavioral assessments improves sensitivity and overall predictive performance.
The PPS index correlates with forebrain mesocircuit integrity and inversely with default mode network–dorsal attention network coupling, linking it to brain network function.

Clinical Implications

The PPS index offers a bedside-compatible electrophysiological marker to detect covert consciousness in non-responsive patients, potentially improving diagnosis and prognostication. Incorporating this EEG measure alongside behavioral assessments may enhance prediction accuracy for recovery in disorders of consciousness. Further refinement and validation could facilitate its clinical adoption.

Conclusion

The PPS index derived from high-beta EEG oscillations represents a promising tool for distinguishing conscious states and predicting recovery in patients with disorders of consciousness. This marker may complement existing clinical assessments to guide patient management.