Background: Recent brain imaging findings suggest that there are widely distributed abnormalities affecting the brain connectivity in individuals with autism spectrum disorder (ASD). Using graph theoretical analysis, it is possible to investigate both global and local properties of brain's wiring diagram, i.e., the connectome. Methods: We acquired diffusion-weighted magnetic resonance imaging data from 14 adult males with high-functioning ASD and 19 age-, gender-, and IQ-matched controls. As with diffusion tensor imaging-based tractography, it is not possible to detect complex (e.g., crossing) fiber configurations, present in 60-90 % of white matter voxels; we performed constrained spherical deconvolution-based whole brain tractography. Unweighted and weighted structural brain networks were then reconstructed from these tractography data and analyzed with graph theoretical measures. Results: In subjects with ASD, global efficiency was significantly decreased both in the unweighted and the weighted networks, normalized characteristic path length was significantly increased in the unweighted networks, and strength was significantly decreased in the weighted networks. In the local analyses, betweenness centrality of the right caudate was significantly increased in the weighted networks, and the strength of the right superior temporal pole was significantly decreased in the unweighted networks in subjects with ASD. Conclusions: Our findings provide new insights into understanding ASD by showing that the integration of structural brain networks is decreased and that there are abnormalities in the connectivity of the right caudate and right superior temporal pole in subjects with ASD.

Objective: To assess how the recording montage in the neonatal EEG influences the detection of cortical source signals and their phase interactions. Methods: Scalp EEG was simulated by forward modeling 20-200 simultaneously active sources covering the cortical surface of a realistic neonatal head model. We assessed systematically how the number of scalp electrodes (11-85), analysis montage, or the size of cortical sources affect the detection of cortical phase synchrony. Statistical metrics were developed for quantifying the resolution and reliability of the montages. Results: The findings converge to show that an increase in the number of recording electrodes leads to a systematic improvement in the detection of true cortical phase synchrony. While there is always a ceiling effect with respect to discernible cortical details, we show that the average and Laplacian montages exhibit superior specificity and sensitivity as compared to other conventional montages. Conclusions: Reliability in assessing true neonatal cortical synchrony is directly related to the choice of EEG recording and analysis configurations. Because of the high conductivity of the neonatal skull, the conventional neonatal EEG recordings are spatially far too sparse for pertinent studies, and this loss of information cannot be recovered by re-montaging during analysis. Significance: Future neonatal EEG studies will need prospective planning of recording configuration to allow analysis of spatial details required by each study question. Our findings also advice about the level of details in brain synchrony that can be studied with existing datasets or by using conventional EEG recordings. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Background: Psychotic disorders have been suggested to derive from dysfunctional integration of signaling between brain regions. Earlier studies have found several changes in functional network synchronization as well as altered network topology in patients with psychotic disorders. However, studies have used mainly resting-state that makes it more difficult to link functional alterations to any specific stimulus or experience. We set out to examine functional connectivity as well as graph (topological) measures and their association to symptoms in first-episode psychosis patients during movie viewing. Our goal was to understand whole-brain functional dynamics of complex naturalistic information processing in psychosis and changes in brain functional organization related to symptoms. Methods: 71 first-episode psychosis patients and 57 control subjects watched scenes from the movie Alice in Wonderland during 3 T fMRI. We compared functional connectivity and graph measures indicating integration, segregation and centrality between groups, and examined the association between topology and symptom scores in the patient group. Results: We identified a subnetwork with predominantly decreased links of functional connectivity in firstepisode psychosis patients. The subnetwork was mainly comprised of nodes of and links between the cinguloopercular, sensorimotor and default-mode networks. In topological measures, we observed between-group differences in properties of centrality. Conclusions: Functional brain networks are affected during naturalistic information processing already in the early stages of psychosis, concentrated in salience- and cognitive control-related hubs and subnetworks. Understanding these aberrant dynamics could add to better targeted cognitive and behavioral interventions in the early stages of psychotic disorders.

Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha-band (8-14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention-related modulations of alpha-band amplitudes and behavior. We investigated whether large-scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter-areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long-range synchronization of cortical oscillations exclusively in the high-alpha (10-14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low-alpha (6-9 Hz) band oscillations in visual cortex. Furthermore, stronger high-alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha-band amplitudes. These results thus show that high-alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention.

The disruption of brain networks is characteristic of neurodegenerative dementias. However, it is controversial whether changes in connectivity reflect only the functional anatomy of disease, with selective vulnerability of brain networks, or the specific neurophysiological consequences of different neuropathologies within brain networks. We proposed that the oscillatory dynamics of cortical circuits reflect the tuning of local neural interactions, such that different pathologies are selective in their impact on the frequency spectrum of oscillations, whereas clinical syndromes reflect the anatomical distribution of pathology and physiological change. To test this hypothesis, we used magnetoencephalography from five patient groups, representing dissociated pathological subtypes and distributions across frontal, parietal and temporal lobes: amnestic Alzheimer's disease, posterior cortical atrophy, and three syndromes associated with frontotemporal lobar degeneration. We measured effective connectivity with graph theory-based measures of local efficiency, using partial directed coherence between sensors. As expected, each disease caused large-scale changes of neurophysiological brain networks, with reductions in local efficiency compared to controls. Critically however, the frequency range of altered connectivity was consistent across clinical syndromes that shared a likely underlying pathology, whilst the localization of changes differed between clinical syndromes. Multivariate pattern analysis of the frequency-specific topographies of local efficiency separated the disorders from each other and from controls (accuracy 62% to 100%, according to the groups' differences in likely pathology and clinical syndrome). The data indicate that magnetoencephalography has the potential to reveal specific changes in neurophysiology resulting from neurodegenerative disease. Our findings confirm that while clinical syndromes have characteristic anatomical patterns of abnormal connectivity that may be identified with other methods like structural brain imaging, the different mechanisms of neurodegeneration also cause characteristic spectral signatures of physiological coupling that are not accessible with structural imaging nor confounded by the neurovascular signalling of functional MRI. We suggest that these spectral characteristics of altered connectivity are the result of differential disruption of neuronal microstructure and synaptic physiology by Alzheimer's disease versus frontotemporal lobar degeneration.

Objective: To develop methods for recording and analysing infant's proximal muscle activations. Methods: Surface electromyography (sEMG) of truncal muscles was recorded in three months old infants (N = 18) during spontaneous movement and controlled postural changes. The infants were also divided into two groups according to motor performance. We developed an efficient method for removing dynamic cardiac artefacts to allow i) accurate estimation of individual muscle activations, as well as ii) quantitative characterization of muscle networks. Results: The automated removal of cardiac artefacts allowed quantitation of truncal muscle activity, which showed predictable effects during postural changes, and there were differences between high and low performing infants. The muscle networks showed consistent change in network density during spontaneous movements between supine and prone position. Moreover, activity correlations in individual pairs of back muscles linked to infant́s motor performance. Conclusions: The hereby developed sEMG analysis methodology is feasible and may disclose differences between high and low performing infants. Analysis of the muscle networks may provide novel insight to central control of motility. Significance: Quantitative analysis of infant's muscle activity and muscle networks holds promise for an objective neurodevelopmental assessment of motor system.

The capacity of visual attention determines how many visual objects may be perceived at any moment. This capacity can be investigated with multiple object tracking (MOT) tasks, which have shown that it varies greatly between individuals. The neuronal mechanisms underlying capacity limits have remained poorly understood. Phase synchronization of cortical oscillations coordinates neuronal communication within the fronto-parietal attention network and between the visual regions during endogenous visual attention. We tested a hypothesis that attentional capacity is predicted by the strength of pretarget synchronization within attention-related cortical regions. We recorded cortical activity with magneto- and electroencephalography (M/EEG) while measuring attentional capacity with MOT tasks and identified large-scale synchronized networks from source-reconstructed M/EEG data. Individual attentional capacity was correlated with load-dependent strengthening of theta (3-8 Hz), alpha (8-10 Hz), and gamma-band (30-120 Hz) synchronization that connected the visual cortex with posterior parietal and prefrontal cortices. Individual memory capacity was also preceded by crossfrequency phase-phase and phase-amplitude coupling of alpha oscillation phase with beta and gamma oscillations. Our results show that good attentional capacity is preceded by efficient dynamic functional coupling and decoupling within brain regions and across frequencies, which may enable efficient communication and routing of information between sensory and attentional systems.