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This study in cognitively healthy women showed that decreased cognitive performance is associated with increased neural network correlations, particularly involving the temporal cortices. As healthy brain function relies on dynamic neural network communication, these findings suggest that subtle increases in correlated neural network activity may be a useful early indicator of decrements in cognitive function.

Previous research has demonstrated highly accurate classification of veterans with posttraumatic stress disorder (PTSD) and controls based on synchronous neural interactions (SNI), highlighting the utility of SNI as a biomarker of PTSD. Here we extend that research to classify additional trauma-related outcomes including subthreshold PTSD, partial recovery, and full recovery according to SNI. A total of 219 U.S. veterans completed diagnostic interviews and underwent a magnetoencephalography (MEG) scan from which SNI was computed. Linear discriminant analysis was used to classify the PTSD and control brains, achieving 100% accuracy. That discriminant function was then used to classify each brain in the subthreshold PTSD, partial recovery, and full recovery diagnostic groups as PTSD or Control. All of the subthreshold PTSD diagnostic group were classified as PTSD, as were three-quarters of the partial recovery group. Findings regarding the full recovery group were mixed, documenting variability in the functional brain status of PTSD recovery. The results of the present study add to the literature supporting the discriminatory power of MEG SNI and demonstrate the utility of SNI as a biomarker of various PTSD-related trajectories.

Recent evidence documented a protective effect of Class II human leukocyte antigen (HLA) DRB1*13 on brain health across the lifespan including evidence of reduced neural network variability relative to non-carriers. Here, in an extension of those findings, we evaluated the influence of a large number of Class I and Class II HLA alleles on aging-related changes in neural network variability. Cognitively healthy women (N = 178) ranging in age from 28 to 99 years old underwent a magnetoencephalography scan from which neural network variability was calculated and provided a blood sample from which HLA and apolipoprotein E (ApoE) genotype were determined. The primary analyses assessed the dependence of network variability on age in carriers of a specific HLA allele compared to non-carriers. Effects were considered protective if there was a significant increase of network variability with age in the absence of a given HLA allele but not in its presence, and were considered to confer susceptibility if the converse was documented; HLA alleles that did not influence the dependence of network variability on age in their presence or absence were considered neutral. Of 50 alleles investigated, 22 were found to be protective, 7 were found to confer susceptibility, and 21 were neutral. The frequencies of those 50 alleles were not associated significantly with ApoE genotype. The findings, which document the influence of HLA on age-related brain changes and highlight the role of HLA in healthy brain function, are discussed in terms of the role of HLA in the human immune response to foreign antigens.

GWI has affected a substantial number of Gulf War (GW) veterans. The disease involves several organ systems among which the brain is most prominent. Neurological, cognitive and mood-related (NCM) symptoms frequently dominate and are at the root of chronic ill-health and disability in veterans suffering from GWI. In addition, such symptoms frequently co-occur with diagnosable mental health disorders, predominantly posttraumatic stress disorder (PTSD). Here we investigated the possibility that increased GWI severity leads, above a threshold, to a diagnosable mental health disorder (excluding psychosis). For this purpose, we used, in separate analyses, symptom severity scores and resting-state brain functional connectivity patterns, as determined by magnetoencephalography (MEG). Two-hundred-thirty GW-era veterans participated in this study. They completed diagnostic interviews to establish the presence of GWI and assess mental health status. This distinguished 3 groups: healthy controls (N = 41), veterans with GWI and no mental illness (GWI group, N = 91), and veterans with both GWI and mental health disorder (GWI+MH, N = 98). For each veteran, symptom severity scores in the 6 GWI domains (fatigue, pain, NCM, skin, gastrointestinal, respiratory) were available as well as 9 summary measures of the distribution of Synchronous Neural Interactions (SNI) derived from the MEG recordings. We tested the hypothesis that, in the presence of GWI, the appearance of a diagnosable mental health disorder may depend on GWI symptom severity. For that purpose, we performed a logistic regression on the GWI population, where the presence (or absence) of the MH disorder was the dependent variable and the age- and gender-adjusted GWI severity in the 6-symptom domains were the predictors. The outcome was the probability that a participant will have MH disorder or not. Similarly, we tested the hypothesis that the presence of the MH disorder can be predicted by the SNI distribution patterns by performing a second logistic regression as above but with the 9 SNI measures as predictors. We found GWI symptom severity differed significantly across groups (GWI+MH > GWI > Control). SNI distributions of the GWI group also differed significantly from the other groups in a systematic hemispheric pattern, such that the presence of GWI involved predominantly the left hemisphere, and presence of mental health disorders involved, in addition, the right hemisphere. Both logistic regressions yielded highly significant outcomes, demonstrating that both GWI symptom severity and SNI distribution measures can predict the presence of MH disorder in GWI. Remarkably, the prediction probabilities for MH presence derived from the symptom-based and SNI-based logistic regressions were positively and highly statistically significantly correlated. Taken together, both objective (neural) and subjective (symptoms) indices suggest that GWI is distinct from healthy controls and varies in severity in a continuum that leads, at the higher end, to a diagnosable MH disorder. The positive correlation between the GWI symptom-based and brain-based predicted classifications provides a key link between GWI symptom severity and synchronous neural interactions in the context of mental illness.

Background Age-related brain changes are well-documented and influenced by genetics. Extensive research links apolipoprotein E (apoE) to brain function, with the E4 allele serving as a risk factor for brain disease, including Alzheimer's disease, and the E2 allele conferring protection. Recent evidence also supports protective effects of another gene, human leukocyte antigen (HLA) DRB1*13, on brain disease and age-related brain atrophy in cognitively healthy adults. Here we investigated the effects of apoE and HLA DRB1*13 on brain function by examining changes in neural network properties with age in healthy adults. Methods One hundred seventy-eight cognitively healthy women (28–99 y old) underwent a magnetoencephalography scan and provided a blood sample for genetic analysis. Age-related changes in neural network variability in genetic subgroups of DRB1*13 × apoE genotype combinations were assessed using linear regression of network variability against age. Findings For individuals lacking a DRB1*13 allele and/or carrying an apoE4 allele, network variability increased significantly with age. In contrast, no such increase was observed in the presence of DRB1*13 and/or apoE2. Interpretation These findings extend previous research documenting the protective effect of DRB1*13 on brain structure to include protection against age-related changes in brain function, and demonstrate similar protective effects on neural network variability for either DRB1*13 or apoE2. These protective effects could be due to reduction or elimination of factors known to disrupt brain function, including neuroinflammation and amyloid beta protein. Funding U.S. Department of Veterans Affairs, and University of Minnesota.

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), includes an empirically supported dimensional model of personality pathology that is assessed via the Personality Inventory for the DSM-5 (PID-5). Here we used magnetoencephalography (MEG; 248 sensors) to evaluate resting-state neural network properties associated with the five primary DSM-5 maladaptive personality domains (negative affect, detachment, antagonism, disinhibition, and psychoticism) in 150 healthy veterans ("control" group) and 179 veterans with various psychiatric disorders ("psychopathology" group). Since a fundamental network property is the strength of functional connectivity among network elements, we used the absolute value of the pairwise correlation coefficient (aCC) between prewhitened MEG sensor time series as a measure of neural functional connectivity and assessed its relations to the quantitative PID-5 scores in a linear regression model, where the log-transformed aCC was the dependent variable and individual PID scores, age, and gender were the independent variables. The partial regression coefficient (pRC) for a specific PID-5 score in that model provided information concerning the direction (positive, negative) and size (absolute value) of the PID effect on the strength of neural correlations. We found that, overall, PID domains had a negative effect (i.e., negative pRC; decorrelation) on aCC in the control group, but a positive one (i.e., positive pRC; hyper-correlation) in the psychopathology group. This dissociation of PID effects on aCC was especially pronounced for disinhibition, psychoticism, and negative affect. These results document for the first time a fundamental difference in neural-PID relations between control and psychopathology groups.

Intact cognitive functions rely on synchronous neural activity; conversely, alterations in synchrony are thought to underlie psychopathology. We recently demonstrated that anomalies in synchronous neural interactions (SNI) determined by magnetoencephalography represent a putative PTSD biomarker. Here we develop and apply a regression-based diagnostic algorithm to further validate SNI as a PTSD biomarker in 432 veterans (235 controls; 138 pure PTSD; 59 PTSD plus comorbid disorders). Correlation coefficients served as proximities in multidimensional scaling (MDS) to obtain a two-dimensional representation of the data. In addition, least absolute shrinkage and selection operator (LASSO) regression was used to derive a diagnostic algorithm for PTSD. Performance of this algorithm was assessed by the area under the receiver operating characteristic (ROC) curves, sensitivity, and specificity in 1000 randomly divided testing and validation datasets and in independent samples. MDS revealed that individuals with PTSD, regardless of comorbid psychiatric conditions, are highly distinct from controls. Similarly, application of the LASSO regression-derived prediction model demonstrated remarkable classification accuracy (AUCs≥0.93 for men, AUC=0.82 for women). Neural functioning in individuals with PTSD, regardless of comorbid psychiatric diagnoses, can be used as a diagnostic test to determine patient disease status, further validating SNI as a PTSD biomarker.

Gulf War illness (GWI) is a chronic disease characterized by the involvement of several organs, including the brain (Christova et al., Exp Brain Res doi: 10.1007/s00221-017-5010-8 , 2017). In a previous study (Georgopoulos et al., J Neural Eng 4:349–355, 2015), we identified six protective alleles from Class II human leukocyte antigen (HLA) genes, and more recently, we investigated the brain correlates of this protection (James et al., EBioMedicine 13:72–79, 2016). Those and other studies (Israeli, Lupus, 21:190–194, 2012) suggested an involvement of the immune system in GWI. In a recent study (Engdahl et al., EBioMedicine doi: 10.1016/j.ebiom.2016.08.030 , 2016), we showed that the brain pattern of synchronous neural interactions (SNI; Georgopoulos et al., J Neural Eng 4:349–355, 2007) in GWI is distinctly different from that in healthy controls. Here we focused on the SNI itself, as a basic measure of neural communication (irrespective of specific connections) and compared it between GWI and seven other diseases that cover a broad spectrum of etiology and pathophysiology. Specifically, we sought to determine which, if any, of those diseases might resemble GWI SNI, overall and within the HLA protective domain, and thus gain further knowledge regarding the nature of GWI brain abnormality. We studied a total of 962 participants from a healthy control population (N = 583) and eight different diseases, including GWI (N = 40), schizophrenia (SZ; N = 21), Alzheimer’s disease (AD; N = 66), posttraumatic stress disorder (PTSD; N = 159), major depressive disorder (MDD; N = 10), relapsing–remitting multiple sclerosis (RRMS; N = 43), Sjogren’s syndrome (SS; N = 32), and rheumatoid arthritis (RA; N = 8). They all underwent a resting-state magnetoencephalographic (MEG) scan to calculate SNIs. Data were analyzed using analysis of covariance (ANCOVA) with disease as fixed factor, and sex and age as covariates. We found that GWI SNIs differed significantly from control SZ, AD, PTSD and MDD but not from RRMS, SS and RA. In addition, we compared GWI to RRMS, SS and RA with respect to SNIs of MEG sensor pairs that were related to the HLA alleles protective for GWI (James et al., EBioMedicine 13:72–79, 2016). We found that GWI SNIs did not differ significantly from any of these three diseases but they did so from control SZ, AD, PTSD and MDD. These findings indicate that (a) GWI brain synchronicity does not differ significantly from that of known immune-related diseases (RRMS, SS, RA), and (b) that this SNI similarity is present within the HLA-related SNIs. In contrast, GWI SNIs differed significantly from those of the other diseases. We conclude that altered brain communication in GWI likely reflects immune-related processes, as postulated previously (James et al., EBioMedicine 13:72–79, 2016). By extension, these findings also indicate that functional brain abnormalities in RRMS, SS and RA might be, in part, due to lack of protective HLA alleles as documented for GWI (Georgopoulos et al., EBioMedicine 3:79–85, 2015).

Apolipoprotein E (apoE) is involved in lipid metabolism in the brain, but its effects on brain function are not understood. Three apoE isoforms (E4, E3, and E2) are the result of cysteine-arginine interchanges at two sites: there are zero interchanges in E4, one interchange in E3, and two interchanges in E2. The resulting six apoE genotypes (E4/4, E4/3, E4/2, E3/3, E3/2, E2/2) yield five groups with respect to the number of cysteine residues per mole (CysR/mole), as follows. ApoE4/4 has zero cysteine residues per mole (0-CysR/mole), E4/3 has one (1-CysR/mole), E4/2 and E3/3 each has two (2-CysR/mole), E3/2 has three (3-CysR/mole), and E2/2 has four (4-CysR/mole). The use of the number of CysR/mole to characterize the apoE molecule converts the categorical apoE genotype scale, consisting of 6 distinct genotypes above, to a 5-point continuous scale (0-4 CysR/mole). This allows the use of statistical analyses suitable for continuous variables (e.g. regression) to quantify the relations between various variables and apoE. Using such analyses, here, we show for the first time that apoE affects in a graded and orderly manner neural communication, as assessed by analyzing the relation between the number of CysR/mole and synchronous neural interactions (SNI) measured by magnetoencephalography (MEG) in 130 cognitively healthy women. At the one end of the CysR/mole range, the 4-CysR/mole (E2/2) SNI distribution had the highest mean, lowest variance, lowest range, and lowest coefficient of variation, whereas at the other end, 0-CysR/mole (E4/4) SNI distribution had the lowest mean, highest variance, highest range, and highest coefficient of variation. The special status of the 4-CysR/mole distribution was reinforced by the results of a hierarchical tree analysis where the 4-CysR/mole (E2/2) SNI distribution occupied a separate branch by itself and the remaining CysR/mole SNI distributions were placed at increasing distances from the 4-CysR/mole distribution, according to their number of CysR/mole, with the 0-CysR/mole (E4/4) being farthest away. These findings suggest that the 4-CysR/mole (E2/2) SNI distribution could serve as a reference distribution. When the SNI distributions of individual women were expressed as distances from this reference distribution, there was a substantial overlap among women of various CysR/mole. This refocuses the placement of individual brains along a continuous distance from the 4-CysR/mole SNI distribution, in contrast to the common categorical assignment to a specific apoE genotype. Finally, the orderly variation of SNI with the number of CysR/mole found here is in keeping with recent advances and ideas regarding the molecular mechanisms underlying the differential effects of apoE in the brain which emphasize the healthier stability conferred on the apoE molecule by the increasing number of cysteine-arginine interchanges, with 4-CysR/mole (E2/2) being the best case, as opposed to the instability and increased chance of toxic fragmentation of the apoE molecule with lower number of CysR/mole, with 0-CysR/mole (E4/4) as the worst case (Mahley and Huang in Neuron 76:871-885, 2012a). However, our results also document the appreciable variation of SNI properties within the various CysR/mole groups and individuals which points to the existence and important role of other factors involved in shaping brain function at the network level.

Background We recently reported that six alleles from class II genes of the Human Leukocyte Antigen (HLA) confer protection from Gulf War Illness (GWI) (Georgopoulos et al., 2015). The most significant effect is exerted on Neurological-Cognitive-Mood (NCM), Pain, and Fatigue symptoms, such that higher number of copies of the protective alleles are associated with lower symptom severity. Here we tested the hypothesis that this effect is exerted by modulating the strength of neural synchronicity. Methods Eighty-one Gulf War veterans (65 with GWI and 16 healthy controls) underwent a magnetoencephalography (MEG) scan to assess the strength of brain synchronicity by computing zero-lag crosscorrelations (and their Fisher z transforms) between prewhitened MEG time series. A high-resolution HLA genotyping determined the number of copies, k, of the 6 protective alleles above in each participant. We tested the hypothesis above by regressing NCM, Pain and Fatigue symptom severity against the interaction term, k × z (HLA-related effect), while including z (non-HLA-related effect), gender and age as covariates. The k × z and z terms assessed HLA- and non-HLA-related effects, respectively, of neural synchronicity on symptom severity. The distributions of these effects in sensor space were visualized using statistical heatmaps. Findings We found significant, graded HLA- and non-HLA-related effects: (a) NCM > Pain > Fatigue for HLA-related effects, (b) NCM > Fatigue > Pain for non-HLA-related effects, and (c) HLA-related > non-HLA-related effects for all symptoms. These effects had widespread but distinct distributions in sensor space that allowed the orderly separation of the 6 terms (3 symptom domains × 2 HLA factors) in a multidimensional plot, where one dimension separated the symptoms and the other the HLA relation. Interpretation These findings demonstrate the presence of substantial, widespread, distinct and orderly HLA- and non-HLA-related neural influences on NCM, Pain and Fatigue symptom severity in GWI. Funding U.S. Department of Veterans Affairs and University of Minnesota., Highlights • Genetic modulation of neural synchronicity is investigated in Gulf War Illness (GWI). • GWI symptom severity is highly related to specific Human Leukocyte Antigen (HLA) alleles. • The distribution of HLA-related effects on brain regions differed across GWI symptoms. • Non-HLA genetic effects on brain functioning were also observed. Gulf War Illness (GWI) is a chronic and debilitating condition that has affected a large number of veterans who served during the 1990–91 Persian Gulf War. We have recently reported evidence of brain anomalies in GWI and identified a genetic immune protection the lack of which confers susceptibility, and, hence, risk for developing GWI symptoms. In this study, we evaluated the interaction of immunity (Human Leukocyte Antigen, HLA) genes and brain functioning in veterans with and without GWI using magnetoencephalography. The findings indicate genetic modulation of brain functioning on GWI symptoms, particularly with genes involving the HLA immune system. These findings document symptom-related interactions between HLA genes and brain function, thus forging a link between HLA genes, brain function and GWI.

Continuous and sequential movements are controlled by widely distributed brain regions. A series of studies have contributed to understanding the functional role of these regions in a variety of visuomotor tasks. However, little is known about the neural interactions underpinning continuous movements. In the current study, we examine the spatiotemporal neural interactions underlying continuous drawing movements and the association of them with behavioral components. We conducted an experiment in which subjects copied a pentagon continuously for ~45 s using an XY joystick, while neuromagnetic fluxes were recorded from their head using a 248-sensor whole-head magnetoencephalography (MEG) device. Each sensor time series was rendered stationary and non-autocorrelated by applying an autoregressive integrated moving average model and taking the residuals. We used the directional variability of the movement as a behavioral measure of the controls generated. The main objective of this study was to assess the relation between neural interactions and the variability of movement direction. That is, we divided the continuous recordings into consecutive periods (i.e., time-bins) of 51 steps duration and computed the pairwise cross-correlations between the prewhitened time series in each time-bin. The circular standard deviation of the movement direction within each time-bin provides an estimate of the directional variability of the 51-ms trajectory segment. We looked at the association between neural interactions and variability of movement direction, separately for each pair of sensors, by running a cross-correlation analysis between the strength of the MEG pairwise cross-correlations and the circular standard deviations. We identified two types of neuronal networks: in one, the neural interactions are correlated with the directional variability of the movement at negative time-lags (feedforward), and in the other, the neural interactions are correlated with the directional variability of the movement at positive time-lags (feedback). Sensors associated mostly with feedforward processes are distributed in the left hemisphere and the right occipital-temporal junction, whereas sensors related to feedback processes are distributed in the right hemisphere and the left cerebellar hemisphere. These results are in line with findings from a series of previous studies showing that specific brain regions are involved in feedforward and feedback control processes to plan, perform, and correct movements. Additionally, we looked at whether changes in movement direction modulate the neural interactions. Interestingly, we found a preponderance of sensors associated with changes in movement direction over the right hemisphere-ipsilateral to the moving hand. These sensors exhibit stronger coupling with the rest of the sensors for trajectory segments with high rather than low directional movement variability. We interpret these results as evidence that ipsilateral cortical regions are recruited for continuous movements when the curvature of the trajectory increases. To the best of our knowledge, this is the first study that shows how neural interactions are associated with a behavioral control parameter in continuous and sequential movements.

Cognitive operations engage neural generators oscillating at different frequencies distributed in time and space. Accordingly, oscillatory activity detected by magnetoencephalography (MEG)/electroencephalography (EEG) should be analyzed along frequency, time, and spatial dimensions. MEG data were obtained from 19 healthy individuals while performing a modified Sternberg paradigm. The stimuli were letters, which constituted words or pronounceable nonwords. We applied tridimensional analysis of oscillations and also computed event-related fields (ERFs) in areas where significant changes in oscillatory activity were observed. Verbal working memory for visual verbal stimuli was associated with oscillatory interplay between the bilateral occipital lobes and the left frontoparietotemporal areas. Spatially stable occipital desynchrony was noted during information encoding, while a left hemisphere desynchronization, increasing in amplitude and spatial extent over time, was observed during information encoding and maintenance. No ERF changes were detected during information maintenance. Oscillatory activity associated with verbal working memory is consistent with the above hypothesis. These findings underscore the importance of multidimensional evaluation of oscillations. The findings also indicate that combining electrophysiological methods increase the chance of signal detection.

We studied visual perception using an annular random-dot motion stimulus called the racetrack. We recorded neural activity using magnetoencephalography while subjects viewed variants of this stimulus that contained no inherent motion or various degrees of embedded motion. Subjects reported seeing rotary motion during viewing of all stimuli. We found that, in the absence of any motion signals, patterns of brain activity differed between states of motion perception and nonperception. Furthermore, when subjects perceived motion, activity states within the brain did not differ across stimuli of different amounts of embedded motion. In contrast, we found that during periods of nonperception brain-activity states varied with the amount of motion signal embedded in the stimulus. Taken together, these results suggest that during perception the brain may lock into a stable state in which lower-level signals are suppressed.

Many factors can influence, or bias, human decision making. A considerable amount of research has investigated the neural correlates of such biases, mostly correlating hemodynamic responses in brain areas with some aspect of the decision. These studies, typically done using functional magnetic resonance imaging or positron emission tomography, have provided useful information about the location of processing in the brain. However, comparatively little research has examined when these processes occur. The present experiment addressed this question by using magnetoencephalography (MEG) to record brain activity while subjects chose preferred options from decision sets. We found that MEG signal deviations for biased decisions occurred as early as 250-750 ms following stimulus onset. Such deviations occurred earliest in sensors over the right anterior cortex. These findings improve our understanding of temporal dynamics of decision biases and suggest ways that existing explanations for this bias could be refined.

We used magnetoencephalography (MEG) in 10 healthy human subjects to study cortical responses to tactile stimuli applied to the fingertips of digits 2-5 of the right hand. Each stimulus lasted 50 ms and was produced by air-driven elastic membranes. Four-hundred stimuli were delivered on each finger in three temporal patterns (conditions). In the "Discrete" condition, stimuli were applied to each finger repetitively with an interstimulus interval (ISI) of 1-2 s. In the "Continuous" condition, stimuli were applied to the fingers sequentially as four-stimulus trains with zero ISI and 1-2 s intervening between trains. Finally, in the "Gap" condition, stimuli were applied as in the Continuous condition but with an ISI of 50 ms. A sensation of tactile motion across fingers (digit 2 --digit 5) was reported by all subjects in the Continuous and Gap conditions. Cortical responses were extracted as single equivalent current dipoles over a period of 1 s following stimulus onset. In all three conditions, initial responses in left primary somatosensory cortex (SI) were observed ~20 to 50 ms after stimulus onset and were followed by additional left SI responses and bilateral responses in the secondary somatosensory cortex (SII). In addition, in the Continuous and Gap conditions, there was an activation of the precentral gyrus, the temporal aspects of which depended on the temporal relation of the administered stimuli, as follows. An ISI of 0 ms led to activation of the precentral gyrus shortly after the second stimulation, whereas an ISI of 50 ms led to activation of the precentral gyrus after the third stimulation. The current findings support results from previous studies on temporal activity patterns in SI and SII, verify the participation of the precentral gyrus during tactile motion perception and, in addition, reveal aspects of integration of sequential sensory stimulations over nonadjacent areas as well as temporal activity patterns in the postcentral and precentral gyri.

We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCC(ij)(0)) and their z-transforms (z(ij)(0)) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of z(ij)(0) successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results.

Pooling of magnetoencephalography (MEG) data across laboratories is non-trivial because of differences in hardware, software, and environmental noise levels. To investigate these issues, we conducted a study with the same five subjects at three sites with different MEG arrays: Elekta-Neuromag Vectorview (Boston), VSM MedTech Omega 275 (Albuquerque), and 4D Neuroimaging Magnes 3600 WH (Minneapolis). Subjects were run in a simple somatosensory paradigm. Phantom data were also taken at each site. We developed software to allow comparisons of test/retest reliability across subjects, machines, and analysis methods. Preliminary analyses showed excellent test/retest results within subjects across instruments. Analysis of phantom data showed a localization error of less than 2 mm across multiple software packages. Our results show that (1) instruments from different manufacturers yield similar results for somatosensory data, and that (2) multiple software packages produce very accurate results for simple source configurations.

We report on the effects of prenatal alcohol exposure on resting-state brain activity as measured by magnetoencephalography (MEG). We studied 37 subjects diagnosed with fetal alcohol spectrum disorder in one of three categories: fetal alcohol syndrome, partial fetal alcohol syndrome, and alcohol-related neurodevelopmental disorder. For each subject, the MEG signal was recorded for 60 s during rest while subjects lay supine. Using time series analysis, we calculated the synchronous neural interactions for all pair-wise combinations of 248 MEG sensors resulting in 30,628 partial correlations for each subject. We found significant differences from control subjects in 6.19 % of the partial zero-lag crosscorrelations (synchronous neural interactions; Georgopoulos et al. in J Neural Eng 4:349-355, 2007), with these differences localized in the right posterior frontal, right parietal, and left parietal/posterior frontal regions. These results show that MEG can detect functional brain differences in the individuals affected by prenatal exposure to alcohol. Furthermore, these differences may serve as a biomarker for future studies linking symptoms and signs to specific brain areas. This may lead to new insights into the neuropathology of fetal alcohol spectrum disorders.

Children learn the words for above-below relations earlier than for left-right relations, despite treating these equally well in a simple visual categorization task. Even as adults--conflicts in congruency, such as when a stimulus is depicted in a spatially incongruent manner with respect to salient global cues--can be challenging. Here we investigated the neural correlates of encoding and maintaining in working memory above-below and left-right relational planes in 12 adults using magnetoencephalography in order to discover whether above-below relations are represented by the brain differently than left-right relations. Adults performed perfectly on the task behaviorally, so any differences in neural activity were attributed to the stimuli's cognitive attributes. In comparing above-below to left-right relations during stimulus encoding, we found the greatest differences in neural activity in areas associated with space and movement. In comparing congruent to incongruent trials, we found the greatest differential activity in premotor areas. For both contrasts, brain areas involved in the encoding phase were also involved in the maintenance phase, which provides evidence that those brain areas are particularly important in representing the relational planes or congruency types throughout the trial. When comparing neural activity associated with the relational planes during working memory, additional right posterior areas were implicated, whereas the congruent-incongruent contrast implicated additional bilateral frontal and temporal areas. These findings are consistent with the hypothesis left-right relations are represented differently than above-below relations.

We visualized synchronous dynamic brain networks by using prewhitened (stationary) magnetoencephalography signals. Data were acquired from 248 axial gradiometers while 10 subjects fixated on a spot of light for 45 s. After fitting an autoregressive integrative moving average model and taking the residuals, all pairwise, zero-lag, partial cross-correlations ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}PCC_{ij}^{0}\end{equation*}\end{document} ) between the i and j sensors were calculated, providing estimates of the strength and sign (positive and negative) of direct synchronous coupling between neuronal populations at a 1-ms temporal resolution. Overall, 51.4% of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}PCC_{ij}^{0}\end{equation*}\end{document} were positive, and 48.6% were negative. Positive \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}PCC_{ij}^{0}\end{equation*}\end{document} occurred more frequently at shorter intersensor distances and were 72% stronger than negative ones, on the average. On the basis of the estimated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}PCC_{ij}^{0}\end{equation*}\end{document} , dynamic neural networks were constructed (one per subject) that showed distinct features, including several local interactions. These features were robust across subjects and could serve as a blueprint for evaluating dynamic brain function.

High density, whole head magnetoencephalography (MEG) was used to study ten healthy human subjects (five females and five males) participating in a continuous shape-copying task. The task was performed with eyes open and fixated. The three-part task began with 45 s of fixation on a blue dot, after which the dot turned red, and a pentagon was presented around it. Subjects continued to fixate on the red dot for 45 s, after which it turned green. The green dot instructed subjects to begin copying the shape continuously for 45 s, without visual feedback, using a joystick mounted at arm's length. Data were collected at 1,017.25 Hz with a 248 sensor axial-gradiometer system. After cardiac artifact subtraction (Leuthold 2003), each corner was identified, and 1 s epochs (centered on each corner) were averaged and filtered from 1 to 44 Hz. Grand average flux maps demonstrated dipolar distributions identifying the most relevant sensors. With these sensors, which were located over flux extrema (Valaki et al. 2004), dipole models were used for source localization within subjects. Consistent dipole locations included the left motor cortex, bilateral parietal, frontal and temporal regions, and the occipital cortex. These results indicate that MEG source-localization may be derived from a limited number of trials of continuous data, and that visual cortex activity may be consistently present during continuous motor activity despite the absence of novel visual stimulation and eye-movements.

Brain-machine interface (BMI) efforts have been focused on using either invasive implanted electrodes or training-extensive conscious manipulation of brain rhythms to control prosthetic devices. Here we demonstrate an excellent prediction of movement trajectory by real-time magnetoencephalography (MEG). Ten human subjects copied a pentagon for 45 s using an X-Y joystick while MEG signals were being recorded from 248 sensors. A linear summation of weighted contributions of the MEG signals yielded a predicted movement trajectory of high congruence to the actual trajectory (median correlation coefficient: r = 0.91 and 0.97 for unsmoothed and smoothed predictions, respectively). This congruence was robust since it remained high in cross-validation analyses (based on the first half of data to predict the second half; median correlation coefficient: r = 0.76 and 0.85 for unsmoothed and smoothed predictions, respectively).

The electrical activity of the human stomach, which normally shows a frequency of about 0.05 Hz, may be studied non-invasively by either cutaneous electrogastrography (EGG) or surface magnetogastrography (MGG). Detection of changes in frequency with time may be useful to characterize gastric disorders. The fast Fourier transform (FFT) has been the most commonly used method for the automated spectral analysis of the signals obtained from the EGG or the MGG. We have used an autoregressive (AR) parametric spectrum estimator to analyse simulated signals of gastric electrical activity, and to evaluate the results of human studies using EGG and MGG. In comparison with the FFT, our results showed that the AR spectrum estimator provided more detailed qualitative information about frequency variations of short duration simulated signals than the FFT. In the human studies, the AR estimator was as good as the conventional FFT methods in detecting physiological changes in frequency and in identifying abnormal recordings. We conclude that the AR spectral estimator may provide a better qualitative analysis of frequency variations in small portions of the signal, and is as useful as the FFT to analyse human EGG or MGG studies.

The neural mechanisms underlying spatial cognition in the context of exploring realistic city maps are unknown. We conducted a novel brain imaging study to address the question of whether and how features of special importance for map exploration are encoded in the brain to make a spatial decision. Subjects explored by eyes small city maps exemplifying five different street network types in order to locate a hypothetical City Hall, while neural activity was recorded continuously by 248 magnetoencephalography (MEG) sensors at high temporal resolution. Monitoring subjects’ eye positions, we locally characterized the maps by computing three spatial parameters of the areas that were explored. We computed the number of street intersections, the total street length, and the regularity index in the circular areas of 6 degrees of visual angle radius centered on instantaneous eye positions. We tested the hypothesis that neural activity during exploration is associated with the spatial parameters and modulated by street network type. All time series were rendered stationary and nonautocorrelated by applying an autoregressive integrated moving average model and taking the residuals. We then assessed the associations between the prewhitened time-varying MEG time series from 248 sensors and the prewhitened spatial parameters time series, for each street network type, using multiple linear regression analyses. In accord with our hypothesis, ongoing neural activity was strongly associated with the spatial parameters through localized and distributed networks, and neural processing of these parameters depended on the type of street network. Overall, processing of the spatial parameters seems to predominantly involve right frontal and prefrontal areas, but not for all street network layouts. These results are in line with findings from a series of previous studies showing that frontal and prefrontal areas are involved in the processing of spatial information and decision making. Modulation of neural processing of the spatial parameters by street network type suggests that some street network layouts may contain other types of spatial information that subjects use to explore maps and make spatial decisions.

Foetal electrocardiograms (fECGs) and foetal magnetocardiograms (fMCGs) were recorded in the 26th, 29th and 31st weeks of gestation from a foetus with ectopia cordis-a rare condition in which the heart lies outside the chest wall. This provided an opportunity to study foetal cardiograms uninfluenced by the insulating effects of the foetal skin and vernix caseosa. The fECG of the ectopia cordis foetus was striking. Unlike recordings from age-matched normal foetuses, recordings from this subject had very high signal-to-noise ratio and showed no anomalous signal transmission properties. In contrast, fMCGs recorded from the ectopia cordis foetus and normal foetuses were largely similar. Both showed high signal-to-noise ratio and signal transmission properties consistent with volume conduction. The findings corroborate the hypothesis that high foetal skin resistance due primarily to the vernix caseosa is responsible for the low amplitude and anomalous transmission properties of the normal fECG, and demonstrate that the fMCG is relatively insensitive to conductivity inhomogeneities.

It has been known for many years that the power of beta-band oscillatory activity in motor-related brain regions decreases during the preparation and execution of voluntary movements. However, it is not clear yet whether the amplitude of this desynchronization is modulated by any parameter of the motor task. Here, we examined whether the degree of uncertainty about the upcoming movement direction modulated beta-band desynchronization during motor preparation. To this end, we recorded whole-head neuromagnetic signals while human subjects performed an instructed-delay reaching task with one, two, or three possible target directions. We found that the reduction of power of beta-band activity (16–28 Hz) during motor preparation was scaled relative to directional uncertainty. Furthermore, we show that the change of beta-band power correlates with the change of latency of response associated with response uncertainty. Finally, we show that the main source of beta-band desynchronization was located in the peri-Rolandic region. The results establish directional uncertainty as an important determinant of beta-band power during motor preparation and indicate that neural activity in the sensorimotor cortex during motor preparation covaries with directional uncertainty.

We used magnetoencephalography (MEG) to investigate the cortical processing of an innocuous facial tactile stimulus in healthy subjects and in a group of subjects suffering from chronic temporomandibular disorder (TMD). Equivalent current dipoles (ECDs) were extracted for a time period of 1 s following stimulus application, and their location, duration and onset time determined. The counts of ECDs extracted did not differ significantly between the two groups. In contrast, we found statistically significant differences in ECD duration and onset time. Specifically, ECD duration was longer in the TMD group in the precentral gyrus, and ECD onset time was earlier in the parietal operculum. In addition, we found differences in the internal organization and clustering of the brain areas involved indicating a less tight association and a less coordinated stimulus information processing in the TMD group. Altogether, these results show that an innocuous facial tactile stimulus is differently processed in the brain of TMD subjects, when compared to controls, reflecting altered brain mechanisms due to chronic pain.

Traumatic experiences can produce post-traumatic stress disorder (PTSD) which is a debilitating condition and for which no biomarker currently exists (Institute of Medicine (US) 2006 Posttraumatic Stress Disorder: Diagnosis and Assessment (Washington, DC: National Academies)). Here we show that the synchronous neural interactions (SNI) test which assesses the functional interactions among neural populations derived from magnetoencephalographic (MEG) recordings (Georgopoulos A P et al 2007 J. Neural Eng. 4 349–55) can successfully differentiate PTSD patients from healthy control subjects. Externally cross-validated, bootstrap-based analyses yielded >90% overall accuracy of classification. In addition, all but one of 18 patients who were not receiving medications for their disease were correctly classified. Altogether, these findings document robust differences in brain function between the PTSD and control groups that can be used for differential diagnosis and which possess the potential for assessing and monitoring disease progression and effects of therapy.

For sequential information, the first (primacy) and last (recency) items are better remembered than items in the middle of the sequence. The cognitive operations and neural correlates for the primacy and recency effects are unclear. In this paper, we investigate brain oscillations associated with these effects. MEG recordings were obtained on 19 subjects performing a modified Sternberg paradigm. Correlation analyses were performed between brain oscillatory activity and primacy and recency indices. Oscillatory activity during information maintenance, not encoding, was correlated with the primacy and recency effects. The primacy effect was associated with occipital post-desynchrony, and temporal post-synchrony. The recency effect was associated with parietal and temporal desynchrony. Differences were also observed according to the maintenance strategy. These data indicate that the primacy and recency effects are related to different neural, and likely cognitive, operations that are dependant on the strategy for information maintenance.

The studies of the neural correlates of verbal working memory in schizophrenia are somewhat inconsistent. This could be related to experimental paradigms that engage differentially working memory components or methodological limitations in terms of characterization of brain activity. Magnetoencephalographic recordings were obtained on 10 schizophrenia patients and 11 healthy controls while performing a modified Sternberg paradigm to investigate subprocesses of verbal working memory. A new method for temporospatial characterization of brain oscillations was applied to whole head recordings and a 1–48 Hz frequency range. Patients differed from controls in event-related synchronization/desynchronization (ERS/ERD) patterns during the encode phase, the mid-maintain phase, and the end of the maintain phase. During the encode phase, patients did not show 1–4 Hz ERS in the left anterior frontal and left parietal lobes. In the mid-maintain phase, the left anterior frontal and left parietal lobes 1–4 Hz ERS, and the bilateral occipital lobes 8–32 Hz ERS were not observed in patients. At the end of the maintain phase, patients did not exhibit 12–48 Hz ERD in the left frontal and parietal lobes. The behavioral data showed reduced primacy effect In schizophrenia, the encode and maintain subprocesses were associated with less ERS and less ERD, respectively. These ERS/ERD abnormalities had specificity in terms of frequency and spatial location. Less ERD reflects reduced complexity of the neural activity, while reduced ERS reflects failure of the neural systems to resume idle state. The impaired primacy effect appears related to specific ERS/ERD patterns in the encode and maintain phases.

Despite substantial efforts to connect cognitive-linguistic models with appropriate anatomical correlates, the question of which cognitive model best accounts for the neuropsychological and functional neuroimaging evidence remains open. The two most popular models are grounded in conceptually different bases and thus make quasi-distinct predictions in regard to the patterns of activation that should be observed in imaging investigations of linguistic processing. Dual-mechanism models propose that high-frequency regular and irregular words are processed through a lexicon-based word code, which facilitates their processing and pronunciation latencies relative to pseudowords. In contrast, single-mechanism models suggest the same behavioral effects can be explained through semantic mediation without the existence of a lexicon. In most previous studies, words and pronounceable pseudowords were presented in lexical-decision or word reading paradigms, and hemodynamic techniques were utilized to distinguish involved anatomical areas. The results typically indicated that both word classes activated largely congruent tissues, with a magnitude advantage for pseudowords in most or all activated regions. However, since the dual-mechanism model predicts both word types utilize the entire linguistic network, but that certain operations are merely obligatorily involved, these results do not sharply refute nor clearly support the model's main tenets. In the current study, we approach the dual- versus single-mechanism question differently by focusing on the temporal dynamics of MEG imaged neuronal activity, during performance of an oddball version of continuous lexical-decision, to determine whether the onset latency of any cortical language region shows effects of word class that are indicative of preferential versus obligatory processing pathways. The most remarkable aspect of our results indicated that both words and pseudowords initially activate the left posterior fusiform region, but that the spatiotemporal dynamics clearly distinguish the two word classes thereafter. For words, this left fusiform activation was followed by engagement of the left posterior inferior temporal, and subsequently activation reached the left posterior superior temporal region. For pseudowords, this sequential order of left temporal area activations was reversed, as activity proceeded from the left fusiform to the left superior temporal and then the left inferior temporal region. For both classes, this dynamic sequential spread manifested within the first 300 ms of stimulus processing. We contend these results provide strong support for the existence of dual-mechanisms underlying reading in a deep orthographic language (i.e., English).

Atrial and ventricular fetal heart rate tracings from a patient with isolated congenital complete heart block treated with dexamethasone showed a remarkable degree of correlation and greater reactivity for the ventricular than the atrial fetal heart rate. Ventriculophasic sinus arrhythmia was present continually in the atrial fetal heart rate tracings.

Magnetoencephalography was used to noninvasively record auditory evoked responses from fetuses in utero at 34 to 37 weeks' gestation. The recordings were similar to auditory evoked responses from neonates at age 7 to 14 days.

Previous research documented letter-string specific cortices in the ventral visual stream near the left occipitotemporal junction (i.e., anterior fusiform gyrus). These neural areas potentially code the perceptual elements comprising orthographic stimuli, and thus function as feature detectors in high-level vision. While abundant evidence supports this region’s role in detecting isomorphic perceptual features, any influence cognitive dimensions (e.g., the lexicality of letter-strings) may play in modulating this area’s processing remains an open question. To investigate this, we examined the spatiotemporal dynamics of high-density magnetoencephalographic signals, recorded as subjects completed a rhyme-judgment task on stimuli varying in the cognitive property of lexicality. Our data demonstrate that the time course of occipitotemporal cortices discriminates cognitive attributes of orthographic stimuli. The dynamics in this brain region may indicate interactive processes unfolding later in the time course, when more anterior fronto-temporal circuits are activated by semantic correlates of real words.

We used standard time series modeling to analyze magnetoencephalographic (MEG) data acquired during three tasks. Each task lasted 45 s, for a total data acquisition period of 135 s. Ten healthy human subjects fixated their eyes on a central blue point for 45 s (fixation only, "F" task). Then a pentagon (visual template) appeared surrounding the fixation point which simultaneously became red (fixation + template, "FT" task). After 45 s, the fixation point changed to green, which was the "go" signal for the subjects to begin continuously copying the pentagon for 45 s using a joystick and without visual feedback of their movement trajectory (fixation + template + copying, "FTC" task). MEG data were acquired continuously from 248 axial gradiometers at a sampling rate of 1017.25 Hz. After removal of cardiac artifacts and rejection of records with eyeblink artifacts, a Box-Jenkins autoregressive integrative moving average (ARIMA) analysis was applied to the unsmoothed, unaveraged MEG time series for model identification and estimation within 25 time lags (approximately 25 ms). We found that an ARIMA model of 25th order autoregressive, first order differencing, and first order moving average (p=25, d=1, q=1) adequately modeled the series and yielded residuals practically stationary with respect to their mean, variance, and autocorrelation structure. These "prewhitened" residuals were then used for assessing pairwise associations between series using crosscorrelation analysis with +/-25 time lags (approximately +/-25 ms). The cross-correlograms thus obtained revealed rich and consistent patterns of interactions between series with respect to positive and/or negative correlations. The overall prevalence of these patterns was very similar in the three tasks used, and, for particular sensor pairs, they tended to be preserved across tasks.

Illuminating the neural mechanisms subserving lexico-semantic processing is requisite to further understanding the neurophysiological basis of the dyslexias. Yet, despite numerous functional neuroimaging experiments, the location and temporal behavior of brain regions mediating word-level language processing remain an area of debate. Such investigations typically utilize the word/pseudoword contrast within hemodynamic measurements, and report several left hemisphere regions that respond more strongly to pseudowords but fail to replicate neural areas unique to real word processing. The present experiment addressed this problem from a different perspective. Mainly, we hypothesized that the time course, but not the neuroanatomy, would show within-subject across-condition disparities. For that purpose, we applied dipole-modeling techniques to high-density magnetoencephalographic recordings of healthy subjects, and utilized excellent spatiotemporal accuracy to demonstrate significant across-condition differences in the time domain, along with indistinguishable neural correlates within-subject. In all participants, both words and pseudowords elicited activity in left perisylvian language areas, with words consistently activating these regions approximately 100 ms earlier than pseudowords. Considerable functional heterogeneity was also observed, and this might underlie the inconsistencies among previous studies. We conclude that the neural distinction in word/pseudoword processing is not in spatial localization, but is better conceptualized as a dynamic difference in processing time.

A simple thermally-controlled superconducting switch was developed for switching low-level low-frequency signals. The device was fabricated and tested using different materials for superconductor, control line, and insulating layer. Refractory materials yielded the best combination of performance and ruggedness. Switching speeds of 1 MHz and control currents of 0.3 mA were achieved. >

A simple thermally controlled, thin‐film superconducting switch was developed for the purpose of multiplexing superconducting quantum interference device detection coils. Switching speeds of a few microseconds were achieved and multiplexing at low frequencies was demonstrated.

We report high precision assessment of fetal rhythm in utero in a case of isolated congenital complete heart block using fetal magnetocardiography. The recordings reveal a remarkably strong tendency for the atria and ventricles to synchronize, which is manifested by the continual presence of ventriculophasic sinus arrhythmia and frequent episodes of accrochage and isorhythmic AV dissociation.

The first studies of fetal neuromagnetism and fetal cardiomagnetism were published more than ten and twenty years ago, respectively [1,2]. Despite considerable interest generated by these reports, relatively few follow-up studies appeared. In retrospect, this is somewhat surprising given that 1) in several respects, magnetic detection is almost uniquely suited to intrauterine evaluation, and 2) there is a paucity of alternate fetal evaluation techniques that provide functional information. During the last few years, interest in fetal biomagnetism has reemerged, as a number of groups have reported findings at meetings and in the literature. This paper presents fetal MCG and fetal MEG studies performed recently by our group at the University of Wisconsin-Madison.

Fetal cardiac waveform intervals were assessed from fetal magnetocardiogram (FMCG) recordings taken from 59 pregnant women at 17-41 weeks gestation. Beyond 27 weeks' gestation PR and QRS intervals, measured from averaged waveforms, could be obtained from all subjects; however, prior to 21 weeks' gestation the success rate was 50% or less due to low signal-to-noise ratio. QT interval could not be assessed accurately in most subjects. Weak, but statistically significant, correlations with gestational age were found for PR interval (n = 145, R2 = 0.033, P = 0.028) and QRS interval (n = 145, R2 = 0.140, P < 0.0005). Abnormal waveform morphology was documented in several patients with cardiac malformations.

Magnetocardiographic recordings from a fetus at 34 weeks' gestation with a complex heart malformation revealed an unusual fetal arrhythmia, where the rhythm was observed to alternate between extended periods of sinus and junctional rhythms. Fetal heart rate measurement showed that the junctional rhythm was strongly associated with respiratory arrhythmia. We hypothesize that changes in autonomic balance due to the onset and cessation of fetal breathing movements were largely responsible for the rhythm alternations. To our knowledge this is the first report of a fetal junction rhythm and the first observation of fetal respiratory arrhythmia during nonsinus rhythm.

Importance Posttraumatic stress disorder (PTSD) and resilience reflect 2 distinct outcomes after exposure to potentially traumatic events. The neural mechanisms underlying these different outcomes are not well understood. Objective To examine the effect of trauma on synchronous neural interactions for veterans with PTSD and resilient controls using magnetoencephalography. Design Participants underwent diagnostic interviews, a measure of exposure to potentially traumatic events, and magnetoencephalography. Setting US Department of Veterans Affairs medical center. Participants Eighty-six veterans with PTSD and 113 resilient control veterans recruited from a large Midwestern medical center. Main Outcome Measures Multiple regression analyses were performed to examine the effect of lifetime trauma on global and local synchronous neural interactions. In analyses examining the local synchronous neural interactions, the partial regression coefficient indicates the strength and direction of the effect of trauma on the synchronous interactions between the 2 neural signals recorded by a pair of sensors. The partial regression coefficient, or slope, is the primary outcome measure for these analyses. Results Global synchronous neural interactions were significantly modulated downward with increasing lifetime trauma scores in resilient control veterans (P = .003) but not in veterans with PTSD (P = .91). This effect, which was primarily characterized by negative slopes (ie, decorrelations) in small neural networks, was strongest in the right superior temporal gyrus. Significant negative slopes were more common, stronger, and observed between sensors at shorter distances than positive slopes in both hemispheres (P Conclusions Neural modulation involving decorrelation of neural networks in the right superior temporal gyrus and, to a lesser extent, other areas distinguishes resilient veterans from those with PTSD and is postulated to have an important role in healthy response to trauma.