Normalized Power Variance: A New Field Orthogonal to Power in EEG Analysis

Abstract To date, electroencephalogram (EEG) has been used in the diagnosis of epilepsy, dementia, and disturbance of consciousness via the inspection of EEG waves. In addition, EEG power analysis combined with a source estimation method like exact-low-resolution-brain-electromagnetic-tomography (eLORETA), which calculates the power of cortical electrical activity from EEG data, has been widely used to investigate cortical electrical activity in both healthy individuals and neuropsychiatric patients. However, the recently developed field of mathematics “information geometry” indicates that EEG has another dimension orthogonal to power dimension — that of normalized power variance (NPV). By also introducing the idea of information geometry, a significantly faster convergent estimator of NPV was obtained. In this study, we applied this NPV analysis of eLORETA to idiopathic normal pressure hydrocephalus (iNPH) patients prior to a cerebrospinal fluid (CSF) shunt operation, where traditional power analysis could not detect any difference associated with CSF shunt operation outcome. NPV analysis detected significantly higher NPV values at the high convexity area in the beta frequency band between 17 shunt responders and 19 non-responders. Our findings demonstrated that EEG has another dimension — that of NPV, which contains a great deal of information about cortical electrical activity that can be useful in clinical practice.