Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA)

Decomposing loss aversion from a single neural signal

People often display stronger aversion to losses than appetite for equivalent gains, a widespread phenomenon known as loss aversion. The prevailing theory attributes loss aversion to a valuation bias that amplifies losses relative to gains. An alternative account attributes loss aversion to a response bias that avoids choices that might result in loss. By modeling the temporal dynamics of scalp electrical activity during decisions to accept or reject gambles within a sequential sampling framework, we decomposed valuation bias and response bias from a single event-related neural signal, the P3. Specifically, we found valuation bias manifested as larger sensitivity of P3 to losses than gains, which was localizable to reward-related brain regions. By contrast, response bias manifested as larger P3 preceding gamble acceptance than rejection and was localizable to motor cortex. Our study reveals the dissociable neural biomarkers of response bias and valuation bias underpinning loss-averse decisions.

Brain Active Areas Associated with a Mental Arithmetic Task: An eLORETA Study

The neural underpinnings of mental calculation, the fundamentals of arithmetic representations and processes, and the development of arithmetic abilities have been explored by researchers over the years. In the present work, we report a study that analyzes the brain-activated areas of a group of 35 healthy subjects (9 males, 26 females, mean age ± SD = 18.23 ± 2.20 years) who performed a serial subtraction arithmetic task. In contrast to most of the studies in the literature based on fMRI, we performed the brain active source reconstruction starting from EEG signals by means of the eLORETA method. In particular, the subjects were classified as bad counters or good counters, according to the results of the task, and the brain activity of the two groups was compared. The results were statistically significant only in the beta band, revealing that the left limbic lobe was found to be more active in people showing better performance. The limbic lobe is involved in visuospatial processing, memory, arithmetic fact retrieval, and emotions. However, the role of the limbic lobe in mental arithmetic has been barely explored, so these interesting findings could represent a starting point for future in-depth analyses. Since there is evidence in the literature that the motor system is affected by the execution of arithmetic tasks, a more extensive knowledge of the brain activation associated with arithmetic tasks could be exploited not only for the assessment of mathematical skills but also in the evaluation of motor impairments and, consequently, in rehabilitation for motor disorders.

Effect of total sleep deprivation on effective EEG connectivity for young male in resting-state networks in different eye states

Background

Many studies have investigated the effect of total sleep deprivation (TSD) on resting-state functional networks, especially the default mode network (DMN) and sensorimotor network (SMN), using functional connectivity. While it is known that the activities of these networks differ based on eye state, it remains unclear how TSD affects them in different eye states. Therefore, we aimed to examine the effect of TSD on DMN and SMN in different eye states using effective functional connectivity via isolated effective coherence (iCoh) in exact low-resolution brain electromagnetic tomography (eLORETA).

Methods

Resting-state electroencephalogram (EEG) signals were collected from 24 male college students, and each participant completed a psychomotor vigilance task (PVT) while behavioral data were acquired. Each participant underwent 36-h TSD, and the data were acquired in two sleep-deprivation times (rested wakefulness, RW: 0 h; and TSD: 36 h) and two eye states (eyes closed, EC; and eyes open, EO). Changes in neural oscillations and effective connectivity were compared based on paired t-test.

Results

The behavioral results showed that PVT reaction time was significantly longer in TSD compared with that of RW. The EEG results showed that in the EO state, the activity of high-frequency bands in the DMN and SMN were enhanced compared to those of the EC state. Furthermore, when compared with the DMN and SMN of RW, in TSD, the activity of DMN was decreased, and SMN was increased. Moreover, the changed effective connectivity in the DMN and SMN after TSD was positively correlated with an increased PVT reaction time. In addition, the effective connectivity in the different network (EO-EC) of the SMN was reduced in the β band after TSD compared with that of RW.

Conclusion

These findings indicate that TSD impairs alertness and sensory information input in the SMN to a greater extent in an EO than in an EC state.

Open Eyes Increase Neural Oscillation and Enhance Effective Brain Connectivity of the Default Mode Network: Resting-State Electroencephalogram Research

The default mode network (DMN) has a unique activity pattern in the resting brain. Studies on resting-state brain activity are helpful to identify various brain dynamic characteristics of patients with mental diseases and those of healthy people. The brain produces a series of changes in different eye states. However, the relationship between eye states and the DMN, which is closely related to the resting state, has not been widely examined. This study recruited 42 healthy students aged 17–22. Participants completed the Profile of Mood States questionnaire. Thereafter, the electroencephalogram data was collected with the patients’ eyes open and closed. Changes in neural oscillation and the DMN’s information transmission during different eye openness states were compared. The results showed that the neural oscillation activities of the parietal-occipital network such as the superior parietal lobule and precuneus were significantly enhanced in the eyes open state. In addition, the effective connectivity within the DMN was enhanced during opened eyes, especially from the left precuneus to the left posterior cingulate cortex, and this connectivity was negatively correlated with the Vigor-Activity mood state in the eyes open state. The activity of the DMN in the resting-state is regulated by eye states, which may relate to mood and emotional perception.

Variability and effect sizes of intracranial current source density estimations during pain: Systematic review, experimental findings, and future perspectives

Pain arises from the integration of sensory and cognitive processes in the brain, resulting in specific patterns of neural oscillations that can be characterized by measuring electrical brain activity. Current source density (CSD) estimation from low-resolution brain electromagnetic tomography (LORETA) and its standardized (sLORETA) and exact (eLORETA) variants, is a common approach to identify the spatiotemporal dynamics of the brain sources in physiological and pathological pain-related conditions. However, there is no consensus on the magnitude and variability of clinically or experimentally relevant effects for CSD estimations. Here, we systematically examined reports of sample size calculations and effect size estimations in all studies that included the keywords pain, and LORETA, sLORETA, or eLORETA in Scopus and PubMed. We also assessed the reliability of LORETA CSD estimations during non-painful and painful conditions to estimate hypothetical sample sizes for future experiments using CSD estimations. We found that none of the studies included in the systematic review reported sample size calculations, and less than 20% reported measures of central tendency and dispersion, which are necessary to estimate effect sizes. Based on these data and our experimental results, we determined that sample sizes commonly used in pain studies using CSD estimations are suitable to detect medium and large effect sizes in crossover designs and only large effects in parallel designs. These results provide a comprehensive summary of the effect sizes observed using LORETA in pain research, and this information can be used by clinicians and researchers to improve settings and designs of future pain studies.

Changes in background electroencephalographic activity in benign childhood epilepsy with centrotemporal spikes after oxcarbazepine treatment: a standardized low-resolution brain electromagnetic tomography (sLORETA) study

Background

Several neuroimaging studies have reported neurophysiological alterations in patients with benign childhood epilepsy with centrotemporal spikes (BCECTS). However, reported outcomes have been inconsistent, and the progression of these changes in the brain remains unresolved. Moreover, background electroencephalography (EEG) in cases of BCECTS has not been performed often.

Methods

We investigated background EEG activity changes after six months of oxcarbazepine treatment to better understand the neurophysiological alterations and progression that occur in BCECTS. In 18 children with BCECTS, non-parametric statistical analyses using standardized low resolution brain electromagnetic tomography (sLORETA) were performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between untreated and treated conditions.

Results

Background EEG activity for the delta frequency band was significantly decreased in the fronto-temporal and limbic regions of the left hemisphere after oxcarbazepine treatment (threshold log-F-ratio = ±2.729, P < 0.01). The maximum current density difference was found in the parahippocampal gyrus of the left limbic lobe (Montreal Neurological Institute coordinate [x, y, z = 25, − 20, − 10], Brodmann area 28) (log-F-ratio = 3.081, P < 0.01).

Conclusions

Our results indicate the involvement of the fronto-temporal and limbic cortices in BCECTS, and limbic lobe involvement, including the parahippocampal gyrus, was noted. In addition to evidence of the involvement of the fronto-temporal and limbic cortices in BCECTS, this study also found that an antiepileptic drug could reduce the delta frequency activity of the background EEG in these regions.

Comparative analysis of background EEG activity in childhood absence epilepsy during valproate treatment: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study

Valproate (VPA) is an antiepileptic drug (AED) used for initial monotherapy in treating childhood absence epilepsy (CAE). EEG might be an alternative approach to explore the effects of AEDs on the central nervous system. We performed a comparative analysis of background EEG activity during VPA treatment by using standardized, low-resolution, brain electromagnetic tomography (sLORETA) to explore the effect of VPA in patients with CAE. In 17 children with CAE, non-parametric statistical analyses using sLORETA were performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between the untreated and treated condition. Maximum differences in current density were found in the left inferior frontal gyrus for the delta frequency band (log-F-ratio = -1.390, P > 0.05), the left medial frontal gyrus for the theta frequency band (log-F-ratio = -0.940, P > 0.05), the left inferior frontal gyrus for the alpha frequency band (log-F-ratio = -0.590, P > 0.05), and the left anterior cingulate for the beta frequency band (log-F-ratio = -1.318, P > 0.05). However, none of these differences were significant (threshold log-F-ratio = ±1.888, P < 0.01; threshold log-F-ratio = ±1.722, P < 0.05). Because EEG background is accepted as normal in CAE, VPA would not be expected to significantly change abnormal thalamocortical oscillations on a normal EEG background. Therefore, our results agree with currently accepted concepts but are not consistent with findings in some previous studies.

The Learning Curve in neurofeedback of Peter Van Deusen: A review article

The Learning Curve (TLC) in neurofeedback concept emerged after Peter Van Deusen compiled the results of articles on the expected electrical activity of the brain. This concept was subsequently tested on patients at four clinics in Atlanta between 1994 and 2001. The aim of this paper was to report the historical aspects of TLC. Articles published on the electronic databases MEDLINE/PubMed and Web of Science were reviewed. During patient evaluation, TLC investigates categories called disconnected, hot temporal lobes, reversal of alpha and beta waves, blocking, locking, and filtering or processing. This enables neuroscientists to use their training designs and, by means of behavioral psychology, to work on neuroregulation, as self-regulation for patients. TLC shows the relationships between electrical, mental and behavioral activity in patients. It also identifies details of patterns that can assist physicians in their choice of treatment.

The crossroads of anxiety: distinct neurophysiological maps for different symptomatic groups

BACKGROUND

Despite the devastating impact of anxiety disorders (ADs) worldwide, long-lasting debates on causes and remedies have not solved the clinician's puzzle: who should be treated and how? Psychiatric classifications conceptualize ADs as distinct entities, with strong support from neuroscience fields. Yet, comorbidity and pharmacological response suggest a single "serotonin dysfunction" dimension. Whether AD is one or several disorders goes beyond academic quarrels, and the distinction has therapeutic relevance. Addressing the underlying dysfunctions should improve treatment response. By its own nature, neurophysiology can be the best tool to address dysfunctional processes.

PURPOSE

To search for neurophysiological dysfunctions and differences among panic disorder (PD), agoraphobia-social-specific phobia, obsessive-compulsive disorder (OCD) and generalized anxiety disorder.

METHODS

A sample population of 192 unmedicated patients and 30 aged-matched controls partook in this study. Hypothesis-related neurophysiological variables were combined into ten independent factors: 1) dysrhythmic patterns, 2) delta, 3) theta, 4) alpha, 5) beta (whole-head absolute power z-scores), 6) event-related potential (ERP) combined latency, 7) ERP combined amplitude (z-scores), 8) magnitude, 9) site, and 10) site of hyperactive networks. Combining single variables into representative factors was necessary because, as in all real-life phenomena, the complexity of interactive processes cannot be addressed through single variables and the multiplicity of potentially implicated variables would demand an extremely large sample size for statistical analysis.

RESULTS

The nonparametric analysis correctly classified 81% of the sample. Dysrhythmic patterns, decreased delta, and increased beta differentiated AD from controls. Shorter ERP latencies were found in several individual patients, mostly from the OCD group. Hyperactivities were found at the right frontorbital-striatal network in OCD and at the panic circuit in PD.

CONCLUSIONS

Our findings support diffuse cortical instability in AD in general, with individual differences in information processing deficits and regional hyperactivities in OCD and PD. Study limitations and the rationale behind the variable selection and combination strategy will be discussed before addressing the therapeutic implications of our findings.

Neuroenhancement of Memory for Children with Autism by a Mind-Body Exercise

The memory deficits found in individuals with autism spectrum disorder (ASD) may be caused by the lack of an effective strategy to aid memory. The executive control of memory processing is mediated largely by the timely coupling between frontal and posterior brain regions. The present study aimed to explore the potential effect of a Chinese mind–body exercise, namely Nei Gong, for enhancing learning and memory in children with ASD, and the possible neural basis of the improvement. Sixty-six children with ASD were randomly assigned to groups receiving Nei Gong training (NGT), progressive muscle relaxation (PMR) training, or no training for 1 month. Before and after training, the participants were tested individually on a computerized visual memory task while EEG signals were acquired during the memory encoding phase. Children in the NGT group demonstrated significantly enhanced memory performance and more effective use of a memory strategy, which was not observed in the other two groups. Furthermore, the improved memory after NGT was consistent with findings of elevated EEG theta coherence between frontal and posterior brain regions, a measure of functional coupling. The scalp EEG signals were localized by the standardized low resolution brain electromagnetic tomography method and found to originate from a neural network that promotes effective memory processing, including the prefrontal cortex, the parietal cortex, and the medial and inferior temporal cortex. This alteration in neural processing was not found in children receiving PMR or in those who received no training. The present findings suggest that the mind–body exercise program may have the potential effect on modulating neural functional connectivity underlying memory processing and hence enhance memory functions in individuals with autism.

EMOTION-PROCESSING BIASES AND RESTING EEG ACTIVITY IN DEPRESSED ADOLESCENTS

BACKGROUND

Although theorists have posited that adolescent depression is characterized by emotion-processing biases (greater propensity to identify sad than happy facial expressions), findings have been mixed. Additionally, the neural correlates associated with putative emotion-processing biases remain largely unknown. Our aim was to identify emotion-processing biases in depressed adolescents and examine neural abnormalities related to these biases using high-density resting EEG and source localization.

METHODS

Healthy (n = 36) and depressed (n = 23) female adolescents, aged 13-18 years, completed a facial recognition task in which they identified happy, sad, fear, and angry expressions across intensities from 10% (low) to 100% (high). Additionally, 128-channel resting (i.e., task-free) EEG was recorded and analyzed using a distributed source localization technique (low-resolution electromagnetic tomography (LORETA)). Given research implicating the dorsolateral prefrontal cortex (DLPFC) in depression and emotion processing, analyses focused on this region.

RESULTS

Relative to healthy youth, depressed adolescents were more accurate for sad and less accurate for happy, particularly low-intensity happy faces. No differences emerged for fearful or angry facial expressions. Further, LORETA analyses revealed greater theta and alpha current density (i.e., reduced brain activity) in depressed versus healthy adolescents, particularly in the left DLPFC (BA9/BA46). Theta and alpha current density were positively correlated, and greater current density predicted reduced accuracy for happy faces.

CONCLUSION

Depressed female adolescents were characterized by emotion-processing biases in favor of sad emotions and reduced recognition of happiness, especially when cues of happiness were subtle. Blunted recognition of happy was associated with left DLPFC resting hypoactivity.

LORETA EEG phase reset of the default mode network

Objectives: The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG).

Methods: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences.

Results: Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300–350 ms and (2) 350–450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas.

Conclusions: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a “shutter” that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

Quantitative EEG and neurofeedback in children and adolescents: anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury

This article explores the science surrounding neurofeedback. Both surface neurofeedback (using 2-4 electrodes) and newer interventions, such as real-time z-score neurofeedback (electroencephalogram [EEG] biofeedback) and low-resolution electromagnetic tomography neurofeedback, are reviewed. The limited literature on neurofeedback research in children and adolescents is discussed regarding treatment of anxiety, mood, addiction (with comorbid attention-deficit/hyperactivity disorder), and traumatic brain injury. Future potential applications, the use of quantitative EEG for determining which patients will be responsive to medications, the role of randomized controlled studies in neurofeedback research, and sensible clinical guidelines are considered.

Low and then high frequency oscillations of distinct right cortical networks are progressively enhanced by medium and long term Satyananda Yoga meditation practice

Meditation proficiency is related to trait-like (learned) effects on brain function, developed over time. Previous studies show increases in EEG power in lower frequency bands (theta, alpha) in experienced meditators in both meditation states and baseline conditions. Higher gamma band power has been found in advanced Buddhist meditators, yet it is not known if this occurs in Yoga meditation practices. This study used eLORETA to compare differences in cortical source activity underlying scalp EEG from intermediate (mean experience 4 years) and advanced (mean experience 30 years) Australian meditators from the Satyananda Yoga tradition during a body-steadiness meditation, mantra meditation, and non-meditation mental calculation condition. Intermediate Yoga meditators showed greater source activity in low frequencies (particularly theta and alpha1) during mental calculation, body-steadiness and mantra meditation. A similar spatial pattern of significant differences was found in all conditions but the number of significant voxels was double during body-steadiness and mantra meditation than in the non-meditation (calculation) condition. These differences were greatest in right (R) superior frontal and R precentral gyri and extended back to include the R parietal and occipital lobes. Advanced Yoga meditators showed greater activity in high frequencies (beta and especially gamma) in all conditions but greatly expanded during meditation practice. Across all conditions (meditation and non-meditation) differences were greatest in the same regions: R insula, R inferior frontal gyrus and R anterior temporal lobe. Distinct R core networks were identified in alpha1 (8-10 Hz) and gamma (25-42 Hz) bands, respectively. The voxels recruited to these networks greatly expanded during meditation practice to include homologous regions of the left hemisphere. Functional interpretation parallels traditionally described stages of development in Yoga proficiency.

From early sensory specialization to later perceptual generalization: dynamic temporal progression in perceiving individual threats

Threat evokes a variety of negative emotions such as fear, anger, and disgust. Whereas they elicit distinct and even opposite facial, sensory, and autonomic reflexes, threat-related emotions often converge in the actions they prompt (e.g., negative evaluation and avoidance). Here, we tested a unifying hypothesis that threat processing initially involves specialized encoding of individual subtypes to support discrete reflexive operations that later gives way to generalized elaborate analysis to facilitate convergent defensive behavior. Combining event-related potentials (ERPs) and a defensive context in human subjects, we compared temporal courses of perceptual analysis of two threat subtypes-fear and disgust. Indeed, fear enhanced and disgust suppressed early (115 ms) response in visual cortex, accentuating specialized sensory encoding of threat subtypes in accordance with the opposite behavioral and autonomic reflexes they typically elicit. By contrast, later ERP waveforms evoked by fear and disgust merged gradually over time (130-425 ms). Consistently, visual ERPs to anthropomorphic Greeble objects presented after fear versus disgust images also overlapped despite their clear departure from the neutral condition, paralleled by comparable exaggeration in Greeble imminence perception in the two threat (vs neutral) conditions. This later confluence of neural and behavioral response between fear and disgust thus highlights general threat categorization in high-level, downstream perception of threat. By delineating the temporal dynamics in perceiving individual threat emotions, our findings thus provide some of the first evidence to reconcile multidimensional and unidimensional aspects of information processing within the domain of threat, shedding new light on symptom heterogeneity across the anxiety disorder spectrum.

EEG current source density and the phenomenology of the default network

In recent years, there has been an increasing line of research dedicated to the investigation of the default mode network (DMN) of the brain and resting state networks. However, the mental activity of the DMN has not been rigorously assessed to date. The specific aims of the current study were 2-fold: First, we sought to determine whether the current source density (CSD) levels in the DMN would correspond to other neuroimaging techniques. Second, we sought to understand the subjective mental activity of the DMN during baseline recordings. This study was conducted with 63 nonclinical participants, 34 female and 29 males with a mean age of 19.2 years (standard deviation = 2.0). The participants were recorded in 8 conditions. First, 4-minute eyes-closed baseline (ECB) and eyes-opened baseline (EOB) were obtained. The participants then completed 3 assessment instruments and 3 image conditions while the electroencephalography (EEG) was continuously recorded. Participants completed subjective reports for baselines and image conditions. These were rated by 3 independent raters and compared for reliability using a random effects model with an absolute agreement definition. The mean CSD between all conditions differed significantly, in many but not all regions of interest in the DMN. Interestingly, as suggested by other studies, the DMN appears preferential to self-relevant, self-specific, or self-perceptive processes. The reliability analyses show α for interrater agreement for ECB at .95 and EOB at .96. The subjective reports obtained from the participants regarding the mental activities employed during baseline recordings correspond to attentional and self-regulatory processes, which may also implicate the resting state or DMN as playing a direct role in the maintenance of a complex behavior (eg, being still, attending, and self-regulating). Thus, attention and self-regulation constitute the phenomenology of the resting state (DMN) in this study. The results also demonstrate that EEG CSD is a useful method to examine the DMN during concept-specific tasks to elucidate the neural activity associated with these concepts. Standardized low-resolution electromagnetic tomography (sLORETA) can localize to 5 mm(3), which is comparable to the findings in functional magnetic resonance imaging (fMRI). However, sLORETA can provide data about the difference in activity between groups, individuals, or populations which in many cases fMRI cannot provide.

Reduced source activity of event-related potentials for affective facial pictures in schizophrenia patients

The ability to recognize facial affect is impaired in schizophrenia patients. This study compared source activities of the event-related potentials (ERPs) for affective facial pictures between schizophrenia patients and healthy controls. Twenty-three schizophrenia patients (11 females) and 24 healthy controls (12 females) were recruited. The standardized low-resolution brain electromagnetic tomography (sLORETA) source activities of four ERP components (P100, N170, N250, and P300) were compared between schizophrenia patients and healthy controls in response to fearful, happy, and neutral facial expressions. Group differences of sLORETA source activities were found only for the N170 component in response to the fearful face. Source activities in the middle frontal gyrus and inferior frontal gyrus were lower in schizophrenia patients compared to healthy controls. Source activity in the insula was lower in male schizophrenia patients compared to male healthy controls. Source activities in the superior temporal gyrus, middle temporal gyrus, insula and inferior frontal gyrus were lower in male compared to female schizophrenia patients. However, there was no gender difference on ERP source activities in the healthy controls. These results support the hypothesis that schizophrenia patients have reduced N170 current source density in response to fearful faces. The area exhibiting reduced current source density includes the frontal and temporal cortex. The present results suggest that there may be gender differences in facial affect processing in schizophrenia patients.

A data-driven process for the development of an eyes-closed EEG normative database

A normative database constitutes a representative sample of a neurologically and clinically healthy population. The practical utility of a normative EEG database is to evaluate the clinical status of a subject whose EEG patterns statistically diverge from average population patterns. These normative data are daily used in clinical practice and in the evaluation of therapeutical interventions. The main obstacle of all normative databases developed to date is inter-individual variability. Such difficulty has been addressed by stratifying the population by age and then using regression in the EEG groups to bound variability, which is always an approximation. This paper describes the first data-driven EEG normative database that explicitly deals with EEG variability by stratifying the population based on their EEG patterns. The database has been constructed for 84 subjects in eyes-closed condition and has been validated by cross validation, leading to a global specificity of 100%.

Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules

OBJECTIVES

The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity.

METHODS

Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules.

RESULTS

The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density.

CONCLUSIONS

EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging.

Amygdalar hyperactivity, a fear-related link between panic disorder and mesiotemporal epilepsy

The sudden onset, short duration and stereotyped features of panic attacks, and the fear aura of seizures starting at the mesial aspects of the temporal lobe, suggest common mechanisms underlying panic disorder (PD) and mesiotemporal epilepsy (MTLE). However, current consensus emphasizes the importance of differentiating the two entities based on 1) intact consciousness in panic attacks, 2) poor response to antiepileptics, and 3) unsuccessful electrophysiological attempts to demonstrate a relationship. We report two cases with a diagnosis of PD that had been partially responsive to first line treatments. During the EEG session, both patients developed panic symptoms with minimal EEG changes in response to paper bag-hyperventilation (PB-HV), and several minutes later presented a clear ictal EEG pattern associated with very different clinical symptoms, but both with strong fear content. Z-scored LORETA analysis showed increased current source densities (CSD) at the right amygdala in both subjects during the induced panic symptoms. Several areas were involved during the seizure, different in each subject. Yet, a very significant increase at the amygdala was found in both cases. The LORETA Z-scored source correlation (LSC) analysis also showed similar abnormal patterns during the panic symptoms in both patients, and marked differences during the seizure. These findings show a major role of amygdalar hyperactivity in both fear-related conditions for the two patients, and are discussed in relation to existing models of PD in general. Abnormal overactivation at mesiotemporal regions is poorly represented at the surface recordings but can be detected by the appropriate analytical techniques.

Validation of ICA-based myogenic artifact correction for scalp and source-localized EEG

Muscle electrical activity, or "electromyogenic" (EMG) artifact, poses a serious threat to the validity of electroencephalography (EEG) investigations in the frequency domain. EMG is sensitive to a variety of psychological processes and can mask genuine effects or masquerade as legitimate neurogenic effects across the scalp in frequencies at least as low as the alpha band (8-13 Hz). Although several techniques for correcting myogenic activity have been described, most are subjected to only limited validation attempts. Attempts to gauge the impact of EMG correction on intracerebral source models (source "localization" analyses) are rarer still. Accordingly, we assessed the sensitivity and specificity of one prominent correction tool, independent component analysis (ICA), on the scalp and in the source-space using high-resolution EEG. Data were collected from 17 participants while neurogenic and myogenic activity was independently varied. Several protocols for classifying and discarding components classified as myogenic and non-myogenic artifact (e.g., ocular) were systematically assessed, leading to the exclusion of one-third to as much as three-quarters of the variance in the EEG. Some, but not all, of these protocols showed adequate performance on the scalp. Indeed, performance was superior to previously validated regression-based techniques. Nevertheless, ICA-based EMG correction exhibited low validity in the intracerebral source-space, likely owing to incomplete separation of neurogenic from myogenic sources. Taken with prior work, this indicates that EMG artifact can substantially distort estimates of intracerebral spectral activity. Neither regression- nor ICA-based EMG correction techniques provide complete safeguards against such distortions. In light of these results, several practical suggestions and recommendations are made for intelligently using ICA to minimize EMG and other common artifacts.

Antipsychotic effect of electroconvulsive therapy is related to normalization of subgenual cingulate theta activity in psychotic depression

OBJECTIVE

Electroconvulsive therapy (ECT) is one of the most effective options available for treating depressive and psychotic symptoms in a variety of disorders. While the exact mechanism of ECT is unclear, it is known to increase metabolism and blood flow specifically in the anterior cingulate cortex (ACC). The ACC is a cortical generator of theta rhythms, which are abnormal in patients with depression and psychotic disorders. Since patients with psychotic depression are known to respond particularly robustly to ECT, we investigated whether the therapeutic effect of ECT in this population was related to normalization of abnormal theta activity in the ACC.

METHOD

We obtained 19-lead electroencephalography (EEG) data from 17 participants with psychotic depression before and 2-3 weeks after a full course of ECT. EEG data was analyzed with quantitative measures and low-resolution electromagnetic tomography (LORETA) compared to an age-adjusted normative database.

RESULTS

Quantitative EEG analyses revealed that theta band (4-7 Hz) activity was the only frequency band that changed with ECT. LORETA analyses revealed that the primary site of theta activity change was within the subgenual ACC (Brodmann area 25). There was a positive association between increased subgenual ACC theta activity and decreased psychotic symptoms. The degree of low theta activity in the subgenual ACC prior to ECT predicted the antipsychotic response of ECT.

CONCLUSIONS

The antipsychotic effect of ECT is related to normalization of subgenual ACC theta hypoactivity.

Evaluation and validity of a LORETA normative EEG database

To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.