Functional connectivity analysis in EEG source space: The choice of method.

Functional connectivity (FC) is among the most informative features derived from EEG. However, the most straightforward sensor-space analysis of FC is unreliable owing to volume conductance effects. An alternative-source-space analysis of FC-is optimal for high- and mid-density EEG (hdEEG, mdEEG); however, it is questionable for widely used low-density EEG (ldEEG) because of inadequate surface sampling. Here, using simulations, we investigate the performance of the two source FC methods, the inverse-based source FC (ISFC) and the cortical partial coherence (CPC). To examine the effects of localization errors of the inverse method on the FC estimation, we simulated an oscillatory source with varying locations and SNRs. To compare the FC estimations by the two methods, we simulated two synchronized sources with varying between-source distance and SNR. The simulations were implemented for hdEEG, mdEEG, and ldEEG. We showed that the performance of both methods deteriorates for deep sources owing to their inaccurate localization and smoothing. The accuracy of both methods improves with the increasing between-source distance. The best ISFC performance was achieved using hd/mdEEG, while the best CPC performance was observed with ldEEG. In conclusion, with hdEEG, ISFC outperforms CPC and therefore should be the preferred method. In the studies based on ldEEG, the CPC is a method of choice

Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures.

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness (SW) metrics, respectively. Yet the number of PNES attacks per month correlated with a weakness of local connectedness and a skewed balance between local and global connectedness quantified with SW, all in EEG alpha band. In beta band, patients demonstrated above-normal resiliency, measured with assortativity coefficient, which also correlated with the frequency of PNES attacks. This interictal EEG phenotype may help improve differentiation between PNES and epilepsy. The results also suggest that local connectivity could be a target for therapeutic interventions in PNES. Selective modulation (strengthening) of local connectivity might improve the skewed balance between local and global connectivity and so prevent PNES events

Fine Structure of Posterior Alpha Rhythm in Human EEG: Frequency Components, Their Cortical Sources, and Temporal Behavior.

Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon. We decomposed the posterior AR in the cortical source space with a 3-way PARAFAC technique, taking into account the spatial, frequency, and temporal aspects of mid-density EEG. We found a multicomponent AR structure in 90% of a group of 29 healthy adults. The typical resting-state structure consisted of a high-frequency occipito-parietal component of the AR (ARC1) and a low-frequency occipito-temporal component (ARC2), characterized by individual dynamics in time. In a few cases, we found a 3-component structure, with two ARC1s and one ARC2. The AR structures were stable in their frequency and spatial features over weeks to months, thus representing individual EEG alpha phenotypes. Cortical topography, individual stability, and similarity to the primate AR organization link ARC1 to the dorsal visual stream and ARC2 to the ventral one. Understanding how many and what kind of posterior AR components contribute to the EEG is essential for clinical neuroscience as an objective basis for AR segmentation and for interpreting AR dynamics under various conditions, both normal and pathological, which can selectively affect individual components

Aging of human alpha rhythm.

Alpha rhythm (AR) changes are the most pronounced electroencephalogram phenomenon in the aging brain. We analyzed them based on the inherent AR structure obtained by parallel factor analysis decomposition in the cortical source space. AR showed a stable multicomponent structure in 78% of sixty 20- to 81-year-old healthy adults. Typically, it consists of 2 components. The distribution of the higher frequency occipito-parietal component widens with age, with its maximum moving from BA18/19 to BA37. The low-frequency component originating from the occipito-temporal regions in young adults also moves anteriorly with age, while maintaining its maximum within BA37. Both components slow down by 1 Hz over the adult lifespan. The multicomponent AR is more common in younger subjects, whereas a single-component AR in older subjects. This uneven occurrence as well as the increasing spatial and frequency overlaps between components suggest transformation of the multicomponent AR into the single-component AR with age. A detailed knowledge of AR component structure would be useful to monitor age-related neurodegenerative processes in humans

Perception-related EEG is more sensitive to Alzheimer's disease effects than resting EEG.

To characterize the effects of Alzheimer's disease (AD) on cortical functional connectivity in perception, we analyzed interhemispheric lagged synchronization (ILS) in the source space of high-density EEG recorded in aged controls and patients with amnestic mild cognitive impairment (aMCI) or AD while they viewed collinear and noncollinear bilateral moving gratings. Beta-band ILS was lower in aMCI and AD compared with controls in a large region centered on BA39. As previously reported, in young adults, collinear iso-oriented gratings versus noncollinear gratings synchronizes EEG reflecting perceptual grouping. Only aged controls showed the expected beta-band ILS increase originating in the dorsal visual stream (BA18). The aMCI group only showed a theta-band increase in an adjacent region (BA19). In AD patients, there was no ILS increase. Regression analysis revealed that the posterior callosal area and EEG slowing predict reduction of beta but not emergence of theta ILS response. Considering that we found no between-group differences in resting ILS, perception-related EEG appears to be more sensitive to AD effects, including ILS signs of neurodegeneration and compensation

Weakened functional connectivity in patients with psychogenic non-epileptic seizures (PNES) converges on basal ganglia.

BACKGROUND: Psychogenic non-epileptic seizures (PNES) are involuntary paroxysmal events that are unaccompanied by epileptiform EEG discharges. We hypothesised that PNES are a disorder of distributed brain networks resulting from their functional disconnection.The disconnection may underlie a dissociation mechanism that weakens the influence of unconsciously presented traumatising information but exerts maladaptive effects leading to episodic failures of behavioural control manifested by psychogenic 'seizures'. METHODS: To test this hypothesis, we compared functional connectivity (FC) derived from resting state high-density EEGs of 18 patients with PNES and 18 age-matched and gender-matched controls. To this end, the EEGs were transformed into source space using the local autoregressive average inverse solution. FC was estimated with a multivariate measure of lagged synchronisation in the θ, α and β frequency bands for 66 brain sites clustered into 18 regions. A multiple comparison permutation test was applied to deduce significant between-group differences in inter-regional and intraregional FC. RESULTS: The significant effect of PNES-a decrease in lagged FC between the basal ganglia and limbic, prefrontal, temporal, parietal and occipital regions-was found in the α band. CONCLUSION: We believe that this finding reveals a possible neurobiological substrate of PNES, which explains both attenuation of the effect of potentially disturbing mental representations and the occurrence of PNES episodes. By improving understanding of the aetiology of this condition, our results suggest a potential refinement of diagnostic criteria and management principles