Evaluation of Electroencephalogram Using Exact Low-Resolution Electromagnetic Tomography During Photic Driving Response in Patients with Migraine.

BACKGROUND: Photophobia is a common feature of migraine, which may involve abnormal cortical information processing. In electroencephalograms (EEG), photic driving is known as a reaction to visual stimulation. Both photophobia and photic driving response are present during light stimulation. We hypothesized that cortical response to photic stimulation would differ between migraine patients with and without aura. METHODS: We recruited 50 migraine patients (migraine with aura [MWA] = 21; migraine without aura [MWOA] = 29). Spontaneous eyes-closed resting EEG from 20 electrodes on the scalp during the interictal phase was recorded. After recording, each photic stimulation was separately selected. We analyzed EEG by fast Fourier transform and observed the spectrum frequency peaks and topographies in response to photic stimulation. Exact low-resolution electromagnetic tomography (eLORETA) was used to compute the 3-dimensional intracerebral distribution of EEG activity. RESULTS: Photic stimulation at frequencies 5, 8, 15, and 20 Hz showed significant differences between migraine patients with and without aura. MWOA patients consistently had a stronger response to photic stimulation than MWA patients. In all patients, the differential response was located in the visual cortex, except for the stimulation at 20 Hz, where the difference at subharmonic 10 Hz was located in the parietal cortex (Brodmann Area 7). CONCLUSION: We confirmed high incidences of photic hypersensitivity and photic driving responses in migraine patients. We suggest that repeated occurrences of cortical spreading depression in MWA may suppress cortical function, thus contributing to a weaker visual cortical response to photic stimulation in MWA patients compared with MWOA patients.

Automated Source Estimation of Scalp EEG Epileptic Activity Using eLORETA Kurtosis Analysis.

OBJECTIVES: eLORETA (exact low-resolution brain electromagnetic tomography) is a technique created by Pascual-Marqui et al. [Int J Psychophysiol. 1994 Oct; 18(1): 49-65] for the 3-dimensional representation of current source density in the brain by electroencephalography (EEG) data. Kurtosis analysis allows for the identification of spiky activity in the brain. In this study, we focused on the evaluation of the reliability of eLORETA kurtosis analysis. For this purpose, the results of eLORETA kurtosis source localization of paroxysmal activity in EEG were compared with those of eLORETA current source density (CSD) analysis of EEG data in 3 epilepsy patients with partial seizures. METHODS: EEG was measured using a digital EEG system with 19 channels. We set the bandpass filter at traditional frequency band settings (1-4, 4-8, 8-15, 15-30, and 30-60 Hz) and 5-10 and 20-70 Hz and performed eLORETA kurtosis to compare the source localization of paroxysmal activity with that of visual interpretation of EEG data and CSD analysis of eLORETA in focal epilepsy patients. RESULTS: The eLORETA kurtosis analysis of EEG data preprocessed by bandpass filtering from 20 to 70 Hz and traditional frequency band settings did not show any discrete paroxysmal source activity compatible with the results of CSD analysis of eLORETA. In all 3 cases, eLORETA kurtosis analysis filtered at 5-10 Hz showed paroxysmal activities in the theta band, which were all consistent with the visual inspection results and the CSD analysis results. DISCUSSION: Our findings suggested that eLORETA kurtosis analysis of EEG data might be useful for the identification of spiky paroxysmal activity sources in epilepsy patients. Since EEG is widely used in the clinical practice of epilepsy, eLORETA kurtosis analysis is a promising method that can be applied to epileptic activity mapping.

Hyperactivation of the Frontal Control Network Revealed by Symptom Provocation in Obsessive-Compulsive Disorder Using EEG Microstate and sLORETA Analyses.

The aim of this study was to investigate the changes of brain electric field induced by symptom provocation in patients with obsessive-compulsive disorder (OCD) in comparison to healthy controls in the resting state. For this purpose, EEG recordings in conditions of initial rest, clean control, symptom provocation by imaginal exposure, and final rest were used for computing spatiotemporal activity characteristics based on microstate segmentation. Within-group comparisons were significant for the symptom provocation condition: OCD showed high global field power (GFP) and transition rates into a medial frontal microstate, whereas healthy controls showed high frequency of occurrence and high percent of dwelling time for a medial occipitoparietal microstate. Between-group comparisons demonstrated significantly lower GFP and dwelling time for the medial occipitoparietal microstate in OCD in several conditions including initial rest and symptom provocation. In addition, OCD compared to healthy controls showed significant instability of the medial occipitoparietal microstate, with high preference for transitions into the medial frontal microstate. In conclusion, during rest and symptom provocation, OCD patients make preferential use of a medial frontal brain network, with concomitant reduction of use of a medial occipitoparietal network, as shown by dwelling times, explained variance, and dynamic transition rates. These findings support the idea of a possible biological marker for OCD, which might correspond to pathological hyperactivation of the frontal control network.

Mapping Slow Waves by EEG Topography and Source Localization: Effects of Sleep Deprivation.

Slow waves are a salient feature of the electroencephalogram (EEG) during non-rapid eye movement (non-REM) sleep. The aim of this study was to assess the topography of EEG power and the activation of brain structures during slow wave sleep under normal conditions and after sleep deprivation. Sleep EEG recordings during baseline and recovery sleep after 40 h of sustained wakefulness were analyzed (eight healthy young men, 27 channel EEG). Power maps were computed for the first non-REM sleep episode (where sleep pressure is highest) in baseline and recovery sleep, at frequencies between 0.5 and 2 Hz. Power maps had a frontal predominance at all frequencies between 0.5 and 2 Hz. An additional occipital focus of activity was observed below 1 Hz. Power maps ≤ 1 Hz were not affected by sleep deprivation, whereas an increase in power was observed in the maps ≥ 1.25 Hz. Based on the response to sleep deprivation, low-delta (0.5-1 Hz) and mid-delta activity (1.25-2 Hz) were dissociated. Electrical sources within the cortex of low- and mid-delta activity were estimated using eLORETA. Source localization revealed a predominantly frontal distribution of activity for low-delta and mid-delta activity. Sleep deprivation resulted in an increase in source strength only for mid-delta activity, mainly in parietal and frontal regions. Low-delta activity dominated in occipital and temporal regions and mid-delta activity in limbic and frontal regions independent of the level of sleep pressure. Both, power maps and electrical sources exhibited trait-like aspects.

Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.

Emotion Regulation of Neuroticism: Emotional Information Processing Related to Psychosomatic State Evaluated by Electroencephalography and Exact Low-Resolution Brain Electromagnetic Tomography.

Emotion regulation is the process that adjusts the type or amount of emotion when we experience an emotional situation. The aim of this study was to reveal quantitative changes in brain activity during emotional information processing related to psychosomatic states and to determine electrophysiological features of neuroticism. Twenty-two healthy subjects (mean age 25 years, 14 males and 8 females) were registered. Electroencephalography (EEG) was measured during an emotional audiovisual memory task under three conditions (neutral, pleasant and unpleasant sessions). We divided the subjects into two groups using the Cornell Medical Index (CMI): (CMI-I: control group, n = 10: CMI-II, III or IV: neuroticism group, n = 12). We analyzed the digital EEG data using exact low-resolution brain electromagnetic tomography (eLORETA) current source density (CSD) and functional connectivity analysis in several frequency bands (δ, θ, α, ß, γ and whole band). In all subjects, bilateral frontal α CSD in the unpleasant session increased compared to the pleasant session, especially in the control group (p < 0.05). CSD of the neuroticism group was significantly higher than that of the control group in the full band at the amygdala and inferior temporal gyrus, and in the α band at the right temporal lobe (p < 0.05). Additionally, we found an increase in functional connectivity between the left insular cortex and right superior temporal gyrus in all subjects during the unpleasant session compared to the pleasant session (p < 0.05). In this study, using EEG analysis, we could find a novel cortical network related to brain mechanisms underlying emotion regulation. Overall findings indicate that it is possible to characterize neuroticism electrophysiologically, which may serve as a neurophysiological marker of this personality trait. © 2015 S. Karger AG, Basel.

Zazen meditation and no-task resting EEG compared with LORETA intracortical source localization.

Meditation is a self-induced and willfully initiated practice that alters the state of consciousness. The meditation practice of Zazen, like many other meditation practices, aims at disregarding intrusive thoughts while controlling body posture. It is an open monitoring meditation characterized by detached moment-to-moment awareness and reduced conceptual thinking and self-reference. Which brain areas differ in electric activity during Zazen compared to task-free resting? Since scalp electroencephalography (EEG) waveforms are reference-dependent, conclusions about the localization of active brain areas are ambiguous. Computing intracerebral source models from the scalp EEG data solves this problem. In the present study, we applied source modeling using low resolution brain electromagnetic tomography (LORETA) to 58-channel scalp EEG data recorded from 15 experienced Zen meditators during Zazen and no-task resting. Zazen compared to no-task resting showed increased alpha-1 and alpha-2 frequency activity in an exclusively right-lateralized cluster extending from prefrontal areas including the insula to parts of the somatosensory and motor cortices and temporal areas. Zazen also showed decreased alpha and beta-2 activity in the left angular gyrus and decreased beta-1 and beta-2 activity in a large bilateral posterior cluster comprising the visual cortex, the posterior cingulate cortex and the parietal cortex. The results include parts of the default mode network and suggest enhanced automatic memory and emotion processing, reduced conceptual thinking and self-reference on a less judgmental, i.e., more detached moment-to-moment basis during Zazen compared to no-task resting.

Association of cerebrospinal fluid tap-related oscillatory activity and shunt outcome in idiopathic normal-pressure hydrocephalus.

BACKGROUND: Idiopathic normal-pressure hydrocephalus (iNPH) is a neuropsychiatric syndrome characterized by the clinical triad of gait disturbance, urinary dysfunction, and cognitive impairment. The aim of the present study was to find specific EEG patterns associated with shunt response in iNPH. METHODS: Twenty five iNPH patients (10 shunt responders and 15 non-responders) were enrolled in this study. We performed current source density (CSD) analysis in several frequency bands (delta: 2-4 Hz, theta: 4-8 Hz, alpha: 8-13 Hz, beta: 13-30 Hz, gamma: 30-60 Hz) using exact Low Resolution Brain Electromagnetic Tomography (eLORETA). CSD distribution was compared between shunt responders and non-responders for each frequency band before and after CSF tap test. RESULTS: Shunt responders showed increased gamma CSD in the left temporal cortex before CSF tapping relative to non-responders. However, after CSF tapping, shunt response was associated with significantly higher CSDs in several frequency bands, specifically theta, alpha, beta and gamma, involving mainly the frontal and temporal areas. Using eLORETA analysis, we were able to identify cortical oscillatory activity before and after CSF tap test related to clinical recovery due to shunt operation in iNPH. CONCLUSION: Our findings support and extend the results of previous studies examining the effects of CSF tap test and shunt operation in patients with iNPH, possibly indicating electrophysiological features of shunt response in this disease. These findings warrant future studies to use EEG for prediction of shunt response in iNPH.

Brain electrical source imaging in manic and depressive episodes of bipolar disorder.

OBJECTIVE: Bipolar disorder (BD) electroencephalographic (EEG) studies have reported varying results. The present study compared EEG in BD during manic and depressive episodes, using brain electrical source imaging [standardized low-resolution electromagnetic tomography (sLORETA)] to assess the cortical spatial distribution of the sources of EEG oscillation frequencies. METHODS: Two independent datasets (a total of 95 patients with bipolar I disorder, of whom 59 were female) were analyzed. Dataset #1 comprised 14 patients in a manic as well as a depressive episode. Dataset #2 comprised 26 patients in a manic episode and 55 patients in a depressive episode. From the head surface-recorded EEG, sLORETA cortical activity was computed in eight EEG frequency bands, and compared between mood states in both datasets. The results from the two datasets were combined using conjunction analysis. RESULTS: Conjunction analysis yielded significant differences between mood states: In manic compared to depressive states, patients had lesser theta frequency band activity (right-hemispheric lateral lower prefrontal and anterior temporal, mainly Brodmann areas 13, 38, and 47), and greater beta-2 and beta-3 frequency band activity (extended bilateral prefrontal-to-parietal, mainly Brodmann area 6, and the cingulate). CONCLUSIONS: The spatial organization of the brain's electrical oscillations differed in patients with BD between manic and depressive mood states. The brain areas implementing the main functions that show opposing abnormalities during manic and depressive episodes were affected by unduly increased or decreased activity (beta or theta). The discussion considers that facilitating (beta) or inhibiting (theta) electrical activity can in either case result in behavioral facilitation or inhibition, depending on the function of the brain area.

Neural substrates of normal and impaired preattentive sensory discrimination in large cohorts of nonpsychiatric subjects and schizophrenia patients as indexed by MMN and P3a change detection responses.

OBJECTIVE: Schizophrenia (SZ) patients have information processing deficits, spanning from low level sensory processing to higher-order cognitive functions. Mismatch negativity (MMN) and P3a are event-related potential (ERP) components that are automatically elicited in response to unattended changes in ongoing, repetitive stimuli that provide a window into abnormal information processing in SZ. MMN and P3a are among the most robust and consistently identified deficits in SZ, yet the neural substrates of these responses and their associated deficits in SZ are not fully understood. This study examined the neural sources of MMN and P3a components in a large cohort of SZ and nonpsychiatric control subjects (NCS) using Exact Low Resolution Electromagnetic Tomography Analyses (eLORETA) in order to identify the neural sources of MMN and P3a as well as the brain regions associated with deficits commonly observed among SZ patients. METHODS: 410 SZ and 247 NCS underwent EEG testing using a duration-deviant auditory oddball paradigm (1-kHz tones, 500ms SOA; standard p=0.90, 50-ms duration; deviant tones P=0.10, 100-ms duration) while passively watching a silent video. Voxel-by-voxel within- (MMN vs. P3a) and between-group (SZ vs. NCS) comparisons were performed using eLORETA. RESULTS: SZ had robust deficits in MMN and P3a responses measured at scalp electrodes consistent with other studies. These components mapped onto neural sources broadly distributed across temporal, frontal, and parietal regions. MMN deficits in SZ were associated with reduced activations in discrete medial frontal brain regions, including the anterior-posterior cingulate and medial frontal gyri. These early sensory discriminatory MMN impairments were followed by P3a deficits associated with widespread reductions in the activation of attentional networks (frontal, temporal, parietal regions), reflecting impaired orienting or shifts of attention to the infrequent stimuli. CONCLUSIONS: MMN and P3a are dissociable responses associated with broadly distributed patterns of neural activation. MMN deficits among SZ patients appear to be primarily accounted for by reductions in medial prefrontal brain regions that are followed by widespread dysfunction across cortical networks associated with P3a in a manner that is consistent with hierarchical information processing models of cognitive deficits in SZ patients. Impairments in automatic stimulus discrimination may contribute to higher-order cognitive and psychosocial deficits in SZ.

Visual activation of auditory cortex reflects maladaptive plasticity in cochlear implant users.

Cross-modal reorganization in the auditory cortex has been reported in deaf individuals. However, it is not well understood whether this compensatory reorganization induced by auditory deprivation recedes once the sensation of hearing is partially restored through a cochlear implant. The current study used electroencephalography source localization to examine cross-modal reorganization in the auditory cortex of post-lingually deafened cochlear implant users. We analysed visual-evoked potentials to parametrically modulated reversing chequerboard images between cochlear implant users (n = 11) and normal-hearing listeners (n = 11). The results revealed smaller P100 amplitudes and reduced visual cortex activation in cochlear implant users compared with normal-hearing listeners. At the P100 latency, cochlear implant users also showed activation in the right auditory cortex, which was inversely related to speech recognition ability with the cochlear implant. These results confirm a visual take-over in the auditory cortex of cochlear implant users. Incomplete reversal of this deafness-induced cortical reorganization might limit clinical benefit from a cochlear implant and help explain the high inter-subject variability in auditory speech comprehension.

Normalized Power Variance: A new Field Orthogonal to Power in EEG Analysis.

To date, electroencephalogram (EEG) has been used in the diagnosis of epilepsy, dementia, and disturbance of consciousness via the inspection of EEG waves and identification of abnormal electrical discharges and slowing of basic 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 neuropsychiatric diseases. 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). In addition, by introducing the idea of information geometry, a significantly faster convergent estimator of NPV was obtained. Research into this NPV coordinate has been limited thus far. 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. Our NPV analysis of eLORETA detected significantly higher NPV values at the high convexity area in the beta frequency band between 17 shunt responders and 19 non-responders. Considering our present and past research findings about NPV, we also discuss the advantage of this application of NPV representing a sensitive early warning signal of cortical impairment. Overall, our findings demonstrated that EEG has another dimension - that of NPV, which contains a lot of information about cortical electrical activity that can be useful in clinical practice.

EEG resting-state networks in Alzheimer's disease associated with clinical symptoms.

Alzheimer's disease (AD) is a progressive neuropsychiatric disease affecting many elderly people and is characterized by progressive cognitive impairment of memory, visuospatial, and executive functions. As the elderly population is growing, the number of AD patients is increasing considerably. There is currently growing interest in determining AD's cognitive dysfunction markers. We used exact low-resolution-brain-electromagnetic-tomography independent-component-analysis (eLORETA-ICA) to assess activities of five electroencephalography resting-state-networks (EEG-RSNs) in 90 drug-free AD patients and 11 drug-free patients with mild-cognitive-impairment due to AD (ADMCI). Compared to 147 healthy subjects, the AD/ADMCI patients showed significantly decreased activities in the memory network and occipital alpha activity, where the age difference between the AD/ADMCI and healthy groups was corrected by linear regression analysis. Furthermore, the age-corrected EEG-RSN activities showed correlations with cognitive function test scores in AD/ADMCI. In particular, decreased memory network activity showed correlations with worse total cognitive scores for both Mini-Mental-State-Examination (MMSE) and Alzheimer's Disease-Assessment-Scale-cognitive-component-Japanese version (ADAS-J cog) including worse sub-scores for orientation, registration, repetition, word recognition and ideational praxis. Our results indicate that AD affects specific EEG-RSNs and deteriorated network activity causes symptoms. Overall, eLORETA-ICA is a useful, non-invasive tool for assessing EEG-functional-network activities and provides better understanding of the neurophysiological mechanisms underlying the disease.

Reduced functional connectivity between cortical sources in five meditation traditions detected with lagged coherence using EEG tomography.

Brain functional states are established by functional connectivities between brain regions. In experienced meditators (13 Tibetan Buddhists, 15 QiGong, 14 Sahaja Yoga, 14 Ananda Marga Yoga, 15 Zen), 19-channel EEG was recorded before, during and after that meditation exercise which their respective tradition regards as route to the most desirable meditative state. The head surface EEG data were recomputed (sLORETA) into 19 cortical regional source model time series. All 171 functional connectivities between regions were computed as 'lagged coherence' for the eight EEG frequency bands (delta through gamma). This analysis removes ambiguities of localization, volume conduction-induced inflation of coherence, and reference-dependence. All significant differences (corrected for multiple testing) between meditation compared to no-task rest before and after meditation showed lower coherence during meditation, in all five traditions and eight (inhibitory as well as excitatory) frequency bands. Conventional coherence between the original head surface EEG time series very predominantly also showed reduced coherence during meditation. The topography of the functional connectivities was examined via PCA-based computation of principal connectivities. When going into and out of meditation, significantly different connectivities revealed clearly different topographies in the delta frequency band and minor differences in the beta-2 band. The globally reduced functional interdependence between brain regions in meditation suggests that interaction between the self process functions is minimized, and that constraints on the self process by other processes are minimized, thereby leading to the subjective experience of non-involvement, detachment and letting go, as well as of all-oneness and dissolution of ego borders during meditation.

EEG source imaging during two Qigong meditations.

Experienced Qigong meditators who regularly perform the exercises "Thinking of Nothing" and "Qigong" were studied with multichannel EEG source imaging during their meditations. The intracerebral localization of brain electric activity during the two meditation conditions was compared using sLORETA functional EEG tomography. Differences between conditions were assessed using t statistics (corrected for multiple testing) on the normalized and log-transformed current density values of the sLORETA images. In the EEG alpha-2 frequency, 125 voxels differed significantly; all were more active during "Qigong" than "Thinking of Nothing," forming a single cluster in parietal Brodmann areas 5, 7, 31, and 40, all in the right hemisphere. In the EEG beta-1 frequency, 37 voxels differed significantly; all were more active during "Thinking of Nothing" than "Qigong," forming a single cluster in prefrontal Brodmann areas 6, 8, and 9, all in the left hemisphere. Compared to combined initial-final no-task resting, "Qigong" showed activation in posterior areas whereas "Thinking of Nothing" showed activation in anterior areas. The stronger activity of posterior (right) parietal areas during "Qigong" and anterior (left) prefrontal areas during "Thinking of Nothing" may reflect a predominance of self-reference, attention and input-centered processing in the "Qigong" meditation, and of control-centered processing in the "Thinking of Nothing" meditation.

Fatigue-induced increase in intracortical communication between mid/anterior insular and motor cortex during cycling exercise.

In the present study, intracortical communication between mid/anterior insular and motor cortex was investigated during a fatiguing cycling exercise. From 16 healthy male subjects performing a constant-load test at 60% peak oxygen consumption (VO(2peak)) until volitional exhaustion, electroencephalography data were analysed during repetitive, artefact-free periods of 1-min duration. To quantify fatigue-induced intracortical communication, mean intra-hemispheric lagged phase synchronization between mid/anterior insular and motor cortex was calculated: (i) at the beginning of cycling; (ii) at the end of cycling; and (iii) during recovery cycling. Results revealed significantly increased lagged phase synchronization at the end of cycling, which returned to baseline during recovery cycling after subjects' cessation of exercise. Following previous imaging studies reporting the mid/anterior insular cortex as an essential instance processing a variety of sensory stimuli and signalling forthcoming physiological threat, our results provide further evidence that during a fatiguing exercise this structure might not only integrate and evaluate sensory information from the periphery, but also act in communication with the motor cortex. To the best of our knowledge, this is the first study to empirically demonstrate that muscle fatigue leads to changes in interaction between structures of a brain's neural network.

Mindfulness augmentation for anxiety through concurrent use of transcranial direct current stimulation: a randomized double-blind study.

Transcranial direct current stimulation (tDCS) have revealed the capability to augment various types of behavioural interventions. We aimed to augment the effects of mindfulness, suggested for reducing anxiety, with concurrent use of tDCS. We conducted a double-blind randomized study with 58 healthy individuals. We introduced treadmill walking for focused meditation and active or sham tDCS on the left dorsolateral prefrontal cortex for 20 min. We evaluated outcomes using State-Trait Anxiety Inventory-State Anxiety (STAI) before the intervention as well as immediately, 60 min, and 1 week after the intervention, and current density from electroencephalograms (EEG) before and after the intervention. The linear mixed-effect models demonstrated that STAI-state anxiety showed a significant interaction effect between 1 week after the intervention and tDCS groups. As for alpha-band EEG activity, the current density in the rostral anterior cingulate cortex (rACC) was significantly reduced in the active compared with the sham stimulation group, and a significant correlation was seen between changes in STAI-trait anxiety and the current density of the rACC in the active stimulation group. Our study provided that despite this being a one-shot and short intervention, the reduction in anxiety lasts for one week, and EEG could potentially help predict its anxiolytic effect.

Fundamentally altered global- and microstate EEG characteristics in Huntington's disease.

OBJECTIVE: Huntington's disease (HD) is characterized by psychiatric, cognitive, and motor disturbances. The study aimed to determine electroencephalography (EEG) global state and microstate changes in HD and their relationship with cognitive and behavioral impairments. METHODS: EEGs from 20 unmedicated HD patients and 20 controls were compared using global state properties (connectivity and dimensionality) and microstate properties (EEG microstate analysis). For four microstate classes (A, B, C, D), three parameters were computed: duration, occurrence, coverage. Global- and microstate properties were compared between groups and correlated with cognitive test scores for patients. RESULTS: Global state analysis showed reduced connectivity in HD and an increasing dimensionality with increasing HD severity. Microstate analysis revealed parameter increases for classes A and B (coverage), decreases for C (occurrence) and D (coverage and occurrence). Disease severity and poorer test performances correlated with parameter increases for class A (coverage and occurrence), decreases for C (coverage and duration) and a dimensionality increase. CONCLUSIONS: Global state changes may reflect higher functional dissociation between brain areas and the complex microstate changes possibly the widespread neuronal death and corresponding functional deficits in brain regions associated with HD symptomatology. SIGNIFICANCE: Combining global- and microstate analyses can be useful for a better understanding of progressive brain deterioration in HD.

Core networks for visual-concrete and abstract thought content: a brain electric microstate analysis.

Commonality of activation of spontaneously forming and stimulus-induced mental representations is an often made but rarely tested assumption in neuroscience. In a conjunction analysis of two earlier studies, brain electric activity during visual-concrete and abstract thoughts was studied. The conditions were: in study 1, spontaneous stimulus-independent thinking (post-hoc, visual imagery or abstract thought were identified); in study 2, reading of single nouns ranking high or low on a visual imagery scale. In both studies, subjects' tasks were similar: when prompted, they had to recall the last thought (study 1) or the last word (study 2). In both studies, subjects had no instruction to classify or to visually imagine their thoughts, and accordingly were not aware of the studies' aim. Brain electric data were analyzed into functional topographic brain images (using LORETA) of the last microstate before the prompt (study 1) and of the word-type discriminating event-related microstate after word onset (study 2). Conjunction analysis across the two studies yielded commonality of activation of core networks for abstract thought content in left anterior superior regions, and for visual-concrete thought content in right temporal-posterior inferior regions. The results suggest that two different core networks are automatedly activated when abstract or visual-concrete information, respectively, enters working memory, without a subject task or instruction about the two classes of information, and regardless of internal or external origin, and of input modality. These core machineries of working memory thus are invariant to source or modality of input when treating the two types of information.

Normalized power variance of eLORETA at high-convexity area predicts shunt response in idiopathic normal pressure hydrocephalus.

Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric disease characterized by gait disturbance, cognitive deterioration and urinary incontinence associated with excessive accumulation of cerebrospinal fluid (CSF) in the brain ventricles. These symptoms, in particular gait disturbance, can be potentially improved by shunt operation in the early stage of the disease, and the intervention associates with a worse outcome when performed late during the course of the disease. Despite the variable outcome of shunt operation, noninvasive presurgical prediction methods of shunt response have not been established yet. In the present study, we used normalized power variance (NPV), a sensitive measure of the instability of cortical electrical activity, to analyze cortical electrical activity derived from EEG data using exact-low-resolution-electromagnetic-tomography (eLORETA) in 15 shunt responders and 19 non-responders. We found that shunt responders showed significantly higher NPV values at high-convexity areas in beta frequency band than non-responders. In addition, using this difference, we could discriminate shunt responders from non-responders with leave-one-subject-out cross-validation accuracy of 67.6% (23/34) [positive predictive value of 61.1% (11/18) and negative predictive value of 75.0% (12/16)]. Our findings indicate that eLORETA-NPV can be a useful tool for noninvasive prediction of clinical response to shunt operation in patients with iNPH.