Recent functional magnetic resonance imaging (fMRI) studies have shown that functional networks can be extracted even from resting state data, the so called “Resting State independent Networks” (RS-independent-Ns) by applying independent component analysis (ICA). However, compared to fMRI, electroencephalography (EEG) and magnetoencephalography (MEG) have much higher temporal resolution and provide a direct estimation of cortical activity. To date, MEG studies have applied ICA for separate frequency bands only, disregarding cross-frequency couplings. In this study, we aimed to detect EEG-RS-independent-Ns and their interactions in all frequency bands. We applied exact low resolution brain electromagnetic tomography-ICA (eLORETA-ICA) to resting-state EEG data in 80 healthy subjects using five frequency bands (delta, theta, alpha, beta and gamma band) and found five RS-independent-Ns in alpha, beta and gamma frequency bands. Next, taking into account previous neuroimaging findings, five RS-independent-Ns were identified: (1) the visual network in alpha frequency band, (2) dual-process of visual perception network, characterized by a negative correlation between the right ventral visual pathway (VVP) in alpha and beta frequency bands and left posterior dorsal visual pathway (DVP) in alpha frequency band, (3) self-referential processing network, characterized by a negative correlation between the medial prefrontal cortex (mPFC) in beta frequency band and right temporoparietal junction (TPJ) in alpha frequency band, (4) dual-process of memory perception network, functionally related to a negative correlation between the left VVP and the precuneus in alpha frequency band; and (5) sensorimotor network in beta and gamma frequency bands. We selected eLORETA-ICA which has many advantages over the other network visualization methods and overall findings indicate that eLORETA-ICA with EEG data can identify five RS-independent-Ns in their intrinsic frequency bands, and correct correlations within RS-independent-Ns.

Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric syndrome characterized by gait disturbance, cognitive impairment and urinary incontinence that affect elderly individuals. These symptoms can potentially be reversed by cerebrospinal fluid (CSF) drainage or shunt operation. Prior to shunt operation, drainage of a small amount of CSF or “CSF tapping” is usually performed to ascertain the effect of the operation. Unfortunately, conventional neuroimaging methods such as single photon emission computed tomography (SPECT) and functional magnetic resonance imaging (fMRI), as well as electroencephalogram (EEG) power analysis seem to have failed to detect the effect of CSF tapping on brain function. In this work, we propose the use of Neuronal Activity Topography (NAT) analysis, which calculates normalized power variance (NPV) of EEG waves, to detect cortical functional changes induced by CSF tapping in iNPH. Based on clinical improvement by CSF tapping and shunt operation, we classified 24 iNPH patients into responders (N = 11) and nonresponders (N = 13), and performed both EEG power analysis and NAT analysis. We also assessed correlations between changes in NPV and changes in functional scores on gait and cognition scales before and after CSF tapping. NAT analysis showed that after CSF tapping there was a significant decrease in alpha NPV at the medial frontal cortex (FC) (Fz) in responders, while nonresponders exhibited an increase in alpha NPV at the right dorsolateral prefrontal cortex (DLPFC) (F8). Furthermore, we found correlations between cortical functional changes and clinical symptoms. In particular, delta and alpha NPV changes in the left-dorsal FC (F3) correlated with changes in gait status, while alpha and beta NPV changes in the right anterior prefrontal cortex (PFC) (Fp2) and left DLPFC (F7) as well as alpha NPV changes in the medial FC (Fz) correlated with changes in gait velocity. In addition, alpha NPV changes in the right DLPFC (F8) correlated with changes in WMS-R Mental Control scores in iNPH patients. An additional analysis combining the changes in values of alpha NPV over the left-dorsal FC (∆alpha-F3-NPV) and the medial FC (∆alpha-Fz-NPV) induced by CSF tapping (cut-off value of ∆alpha-F3-NPV + ∆alpha-Fz-NPV = 0), could correctly identified “shunt responders” and “shunt nonresponders” with a positive predictive value of 100% (10/10) and a negative predictive value of 66% (2/3). In contrast, EEG power spectral analysis showed no function related changes in cortical activity at the frontal cortex before and after CSF tapping. These results indicate that the clinical changes in gait and response suppression induced by CSF tapping in iNPH patients manifest as NPV changes, particularly in the alpha band, rather than as EEG power changes. Our findings suggest that NAT analysis can detect CSF tapping-induced functional changes in cortical activity, in a way that no other neuroimaging methods have been able to do so far, and can predict clinical response to shunt operation in patients ...

A pair of markers, sNAT and vNAT, is derived from the electroencephalogram (EEG) power spectra (PS) recorded for 5 min with 21 electrodes (4-20 Hz) arranged according to the 10-20 standard. These markers form a new diagnosis tool "NAT" aiming at characterizing various brain disorders. Each signal sequence is divided into segments of 0.64 s and its discrete PS consists of eleven frequency components from 4.68 (3 × 1.56) Hz through 20.34 (13 × 1.56) Hz. PS is normalized to its mean and the bias of PS components on each frequency component across the 21 signal channels is reset to zero. The marker sNAT consists of ten frequency components on 21 channels, characterizing neuronal hyperactivity or hypoactivity as compared with NLc (normal controls). The marker vNAT consists of ten ratios between adjacent PS components denoting the over- or undersynchrony of collective neuronal activities as compared with NLc. The likelihood of a test subject to a specified brain disease is defined in terms of the normalized distance to the template NAT state of the disease in the NAT space. Separation of MCI-AD patients (developing AD in 12-18 months) from NLc is made with a false alarm rate of 15%. Locations with neuronal hypoactivity and undersynchrony of AD patients agree with locations of rCBF reduction measured by SPECT. The 2-D diagram composed of the binary likelihoods between ADc and NLc in the two representations of sNAT and vNAT enables tracing the NAT state of a test subject approaching the AD area, and the follow-up of the treatment effects.

Variance of state variables shifts due to phase-instability and may serve as an early-warning signal of phase transition of complex systems such as an epileptic seizure of brain cortical activity. Neuronal Activity Topology (NAT) analysis calculates a normalized-power-variance (NPV) of electroencephalogram (EEG) data in each frequency band to obtain relative values comparable among different power states.

Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by gait disturbance, cognitive deterioration and urinary incontinence in elderly individuals. These symptoms can be improved by shunt operation in some but not all patients. Therefore, discovering predictive factors for the surgical outcome is of great clinical importance. We used normalized power variance (NPV) of electroencephalography (EEG) waves, a sensitive measure of the instability of cortical electrical activity, and found significantly higher NPV in beta frequency band at the right fronto-temporo-occipital electrodes (Fp2, T4 and O2) in shunt responders compared to non-responders. By utilizing these differences, we were able to correctly identify responders and non-responders to shunt operation with a positive predictive value of 80% and a negative predictive value of 88%. Our findings indicate that NPV can be useful in noninvasively predicting the clinical outcome of shunt operation in patients with iNPH.