J. Christopher Edgar

Comparison of different cortical connectivity estimators for high-resolution EEG recordings

The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high‐resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal‐to‐noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high‐resolution EEG data recorded during the well‐known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high‐resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF. Hum. Brain Mapp, 2007.

Validating γ Oscillations and Delayed Auditory Responses as Translational Biomarkers of Autism

BACKGROUND Difficulty modeling complex behavioral phenotypes in rodents (e.g., language) has hindered pathophysiological investigation and treatment development for autism spectrum disorders. Recent human neuroimaging studies, however, have identified functional biomarkers that can be more directly related to the abnormal neural dynamics of autism spectrum disorders. This study assessed the translational potential of auditory evoked-response endophenotypes of autism in parallel mouse and human studies of autism. METHODS Whole-cortex magnetoencephalography was recorded in 17 typically developing and 25 autistic children during auditory pure-tone presentation. Superior temporal gyrus activity was analyzed in time and frequency domains. Auditory evoked potentials were recorded in mice prenatally exposed to valproic acid (VPA) and analyzed with analogous methods. RESULTS The VPA-exposed mice demonstrated selective behavioral alterations related to autism, including reduced social interactions and ultrasonic vocalizations, increased repetitive self-grooming, and prepulse inhibition deficits. Autistic subjects and VPA-exposed mice showed a similar 10% latency delay in the N1/M100 evoked response and a reduction in γ frequency (30-50 Hz) phase-locking factor. Electrophysiological measures were associated with mouse behavioral deficits. In mice, γ phase-locking factor was correlated with expression of the autism risk gene neuroligin-3 and neural deficits were modulated by the mGluR5-receptor antagonist MPEP. CONCLUSIONS Results demonstrate a novel preclinical approach toward mechanistic understanding and treatment development for autism.

MEG detection of delayed auditory evoked responses in autism spectrum disorders: towards an imaging biomarker for autism

Motivated by auditory and speech deficits in autism spectrum disorders (ASD), the frequency dependence of superior temporal gyrus (STG) 50 msec (M50) and 100 msec (M100) neuromagnetic auditory evoked field responses in children with ASD and typically developing controls were evaluated. Whole‐cortex magnetoencephalography (MEG) was obtained from 17 typically developing children and 25 children with ASD. Subjects were presented tones with frequencies of 200, 300, 500, and 1,000 Hz, and left and right STG M50 and M100 STG activity was examined. No M50 latency or amplitude Group differences were observed. In the right hemisphere, a Group×Frequency ANOVA on M100 latency produced a main effect for Group (P=0.01), with an average M100 latency delay of 11 msec in children with ASD. In addition, only in the control group was the expected association of earlier M100 latencies in older than younger children observed. Group latency differences remained significant when hierarchical regression analyses partialed out M100 variance associated with age, IQ, and language ability (all P‐values <0.05). Examining the right‐hemisphere 500 Hz condition (where the largest latency differences were observed), a sensitivity of 75%, a specificity of 81%, and a positive predictive value (PPV) of 86% was obtained at a threshold of 116 msec. The M100 latency delay indicates disruption of encoding simple sensory information. Given similar findings in language impaired and nonlanguage impaired ASD subjects, a right‐hemisphere M100 latency delay appears to be an electrophysiological endophenotype for autism.

The time course of activity in dorsolateral prefrontal cortex and anterior cingulate cortex during top-down attentional control

A network of brain regions has been implicated in top-down attentional control, including left dorsolateral prefrontal cortex (LDLPFC) and dorsal anterior cingulate cortex (dACC). The present experiment evaluated predictions of the cascade-of-control model (Banich, 2009), which predicts that during attentionally-demanding tasks, LDLPFC imposes a top-down attentional set which precedes late-stage selection performed by dACC. Furthermore, the cascade-of-control model argues that dACC must increase its activity to compensate when top-down control by LDLPFC is poor. The present study tested these hypotheses using fMRI and dense-array ERP data collected from the same 80 participants in separate sessions. fMRI results guided ERP source modeling to characterize the time course of activity in LDLPFC and dACC. As predicted, dACC activity subsequent to LDLPFC activity distinguished congruent and incongruent conditions on the Stroop task. Furthermore, when LDLPFC activity was low, the level of dACC activity was related to performance outcome. These results demonstrate that dACC responds to attentional demand in a flexible manner that is dependent on the level of LDLPFC activity earlier in a trial. Overall, results were consistent with the temporal course of regional brain function proposed by the cascade-of-control model.

Time course of attentional bias in anxiety: Emotion and gender specificity

Anxiety is characterized by cognitive biases, including attentional bias to emotional (especially threatening) stimuli. Accounts differ on the time course of attention to threat, but the literature generally confounds emotional valence and arousal and overlooks gender effects, both addressed in the present study. Nonpatients high in self-reported anxious apprehension, anxious arousal, or neither completed an emotion-word Stroop task during event-related potential (ERP) recording. Hypotheses differentiated time course of preferential attention to emotional stimuli. Individuals high in anxious apprehension and anxious arousal showed distinct early ERP evidence of preferential processing of emotionally arousing stimuli along with some evidence for gender differences in processing. Healthy controls showed gender differences at both early and later processing stages. The conjunction of valence, arousal, and gender is critical in the time course of attentional bias.

Auditory Magnetic Mismatch Field Latency: A Biomarker for Language Impairment in Autism

BACKGROUND Auditory processing abnormalities are frequently observed in autism spectrum disorders (ASD), and these abnormalities may have sequelae in terms of clinical language impairment (LI). The present study assessed associations between language impairment and the amplitude and latency of the superior temporal gyrus magnetic mismatch field (MMF) in response to changes in an auditory stream of tones or vowels. METHODS Fifty-one children with ASD, and 27 neurotypical control subjects, all aged 6 to 15 years, underwent neuropsychological evaluation, including tests of language function, as well as magnetoencephalographic recording during presentation of tones and vowels. The MMF was identified in the difference waveform obtained from subtraction of responses to standard from deviant stimuli. RESULTS Magnetic mismatch field latency was significantly prolonged (p < .001) in children with ASD, compared with neurotypical control subjects. Furthermore, this delay was most pronounced (∼50 msec) in children with concomitant LI, with significant differences in latency between children with ASD with LI and those without (p < .01). Receiver operator characteristic analysis indicated a sensitivity of 82.4% and specificity of 71.2% for diagnosing LI based on MMF latency. CONCLUSIONS Neural correlates of auditory change detection (the MMF) are significantly delayed in children with ASD, and especially those with concomitant LI, suggesting a neurobiological basis as well as a clinical biomarker for LI in ASD.

A parietal-frontal network studied by somatosensory oddball MEG responses, and its cross-modal consistency.

Previous studies using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) of the brain have found that a distributed parietal-frontal neuronal network is activated in normals during both auditory and visual oddball tasks. The common cortical regions in this network are inferior parietal lobule (IPL)/supramarginal gyrus (SMG), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). It is not clear whether the same network is activated by oddball tasks during somatosensory stimulation. The present study addressed this question by testing healthy adults as they performed a novel median-nerve oddball paradigm while undergoing magnetoencephalography (MEG). An automated multiple dipole analysis technique, the Multi-Start Spatio-Temporal (MSST) algorithm, localized multiple neuronal generators, and identified their time-courses. IPL/SMG, ACC, and DLPFC were reliably localized in the MEG median-nerve oddball responses, with IPL/SMG activation significantly preceding ACC and DLPFC activation. Thus, the same parietal-frontal neuronal network that shows activation during auditory and visual oddball tests is activated in a median-nerve oddball paradigm. Regions uniquely related to somatosensory oddball responses (e.g., primary and secondary somatosensory, dorsal premotor, primary motor, and supplementary motor areas) were also localized. Since the parietal-frontal network supports attentional allocation during performance of the task, this study may provide a novel method, as well as normative baseline data, for examining attention-related deficits in the somatosensory system of patients with neurological or psychiatric disorders.

The temporal dynamics of insula activity to disgust and happy facial expressions: A magnetoencephalography study

The insula has consistently been shown to be involved in processing stimuli that evoke the emotional response of disgust. Recently, its specificity for processing disgust has been challenged and a broader role of the insula in the representation of interoceptive information has been suggested. Studying the temporal dynamics of insula activation during emotional processing can contribute valuable information pertaining to this issue. Few studies have addressed the insulas putative specificity to disgust and the dynamics of its underlying neural processes. In the present study, neuromagnetic responses of 13 subjects performing an emotional continuous performance task (CPT) to faces with disgust, happy, and neutral expressions were obtained. Magnetic field tomography extracted the time course of bilateral insula activities. Right insula activation was stronger to disgust and happy than neutral facial expressions at about 200 ms after stimulus onset. Later only at about 350 ms after stimulus onset the right insula was activated stronger to disgust than happy facial expressions. Thus, the early right insula response reflects activation to emotionally arousing stimuli regardless of valence, and the later right insula response differentiates disgust from happy facial expressions. Behavioral performance but not the insula activity differed between 100 ms and 1000 ms presentation conditions. Present findings support the notion that the insula is involved in the representation of interoceptive information.

Effect of Catechol O-Methyltransferase Val158Met Polymorphism on the P50 Gating Endophenotype in Schizophrenia

BACKGROUND Studies have implicated prefrontal dopamine in cortical information filtering. Deficit in stimulus filtering, an endophenotype of schizophrenia, can be demonstrated using the auditory P50 paired-click gating paradigm. The role of prefrontal dopamine on P50 gating was investigated, using catechol-O-methyltransferase (COMT) valine (val)(158)methionine (met) polymorphism as a predictor of prefrontal dopamine activity. METHODS Twenty-five comparison and 42 schizophrenia subjects underwent P50 gating measurement and COMT genotyping. RESULTS In the combined sample, COMT polymorphism accounted for a unique 10% of gating variance (p = .02), after variance due to diagnosis, smoking status, and antipsychotic use was removed. Valine homozygous individuals exhibited the greatest gating deficit. CONCLUSIONS Valine homozygous individuals are more likely to have gating deficits, supporting COMT as a genetic determinant of the P50 endophenotype, as well as a role for prefrontal dopamine in auditory filtering.

Joint analysis of band-specific functional connectivity and signal complexity in autism.

Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD. Multi-scale entropy was computed to quantify the signal complexity, and synchronization likelihood was used to evaluate functional connectivity (FC), with node strength values providing a sensor-level measure of connectivity to facilitate comparisons with complexity. Sensor level analysis of complexity and connectivity was performed at different frequency bands computed from resting state MEG from 26 children with ASD and 22 typically developing controls (TD). Analyses revealed band-specific group differences in each measure that agreed with other functional studies in fMRI and EEG: higher complexity in TD than ASD, in frontal regions in the delta band and occipital-parietal regions in the alpha band, and lower complexity in TD than in ASD in delta (parietal regions), theta (central and temporal regions) and gamma (frontal-central boundary regions); increased short-range connectivity in ASD in the frontal lobe in the delta band and long-range connectivity in the temporal, parietal and occipital lobes in the alpha band. Finally, and perhaps most strikingly, group differences between ASD and TD in complexity and FC appear spatially complementary, such that where FC was elevated in ASD, complexity was reduced (and vice versa). The correlation of regional average complexity and connectivity node strength with symptom severity scores of ASD subjects supported the overall complementarity (with opposing sign) of connectivity and complexity measures, pointing to either diminished connectivity leading to elevated entropy due to poor inhibitory regulation or chaotic signals prohibiting effective measure of connectivity.