Background Difficulty modeling complex behavioral phenotypes in rodents (e.g., language) has hindered pathophysiological investigation and treatment development for autism spectrum disorders (ASD). Recent human neuroimaging studies, however, have identified functional biomarkers that can be more directly related to the abnormal neural dynamics of ASD. 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 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 gamma frequency (30–50 Hz) phase-locking factor (PLF). Electrophysiological measures were associated with mouse behavioral deficits. In mice, gamma PLF was correlated with expression of the autism risk gene neuroligin-3 and neural deficits were modulated by the mGluR5-receptor antagonist MPEP. Conclusion Results demonstrate a novel preclinical approach toward mechanistic understanding and treatment development 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 5 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.

Abstract: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 28:143-157, 2007.

The human motor cortex exhibits characteristic beta (15-30 Hz) and gamma oscillations (60-90 Hz), typically observed in the context of transient finger movement tasks. The functional significance of these oscillations, such as post-movement beta rebound (PMBR) and movement-related gamma synchrony (MRGS) remain unclear. Considerable animal and human non-invasive studies, however, suggest that the networks supporting these motor cortex oscillations depend critically on the inhibitory neurotransmitter γ-Aminobutyric acid (GABA). Despite such speculation, a direct relation between MEG measured motor cortex oscillatory power and frequency with resting GABA concentrations has not been demonstrated. In the present study, motor cortical responses were measured from 9 healthy adults while they performed a cued button-press task using their right index finger. In each participant, PMBR and MRGS measures were obtained from time-frequency plots obtained from primary motor (MI) sources, localized using beamformer differential source localization. For each participant, complimentary magnetic resonance spectroscopy (MRS) GABA measures aligned to the motor hand knob of the left central sulcus were also obtained. GABA concentration was estimated as the ratio of the motor cortex GABA integral to a cortical reference NAA resonance at 2 ppm. A significant linear relation was observed between MI GABA concentration and MRGS frequency (R2 = 0.46, p<0.05), with no association observed between GABA concentration and MRGS power. Conversely, a significant linear relation was observed between MI GABA concentration and PMBR power (R2 = 0.34, p<0.05), with no relation observed for GABA concentration and PMBR frequency. Finally, a significant negative linear relation between the participant’s age and MI gamma frequency was observed, such that older participants had a lower gamma frequency (R2 = 0.40, p < 0.05). Present findings support a role for GABA in the generation and modulation of endogenous motor cortex rhythmic beta and gamma activity.