15Accumulating evidence across species indicates that brain oscillations are superimposed 16 upon an aperiodic 1/# -like power spectrum. Maturational changes in neuronal oscillations 17 have not been assessed in tandem with this underlying aperiodic spectrum. The current study 18 uncovers co-maturation of the aperiodic component alongside the periodic components 19 (oscillations) in spontaneous magnetoencephalography (MEG) data. Beamformer-20 reconstructed MEG time-series allowed a direct comparison of power in the source domain 21 between 24 children (8.0 ± 2.5 years, 17 males) and 24 adults (40.6 ± 17.4 years, 16 males). 22Our results suggest that the redistribution of oscillatory power from lower to higher frequencies 23 that is observed in childhood does not hold once the age-related changes in the aperiodic 24 signal are controlled for. When estimating both the periodic and aperiodic components, we 25 found that power increases with age in the beta band only, and that the 1/# signal is flattened 26 in adults compared to children. These results suggest a pattern of co-maturing beta oscillatory 27 power with the aperiodic

The posterior cingulate cortex (pCC) often deactivates during complex tasks, and at rest is often only weakly correlated with regions that play a general role in the control of cognition. These observations led to the hypothesis that pCC contributes to automatic aspects of memory retrieval and cognition. Recent work, however, has suggested that the pCC may support both automatic and controlled forms of memory processing and may do so by changing its communication with regions that are important in the control of cognition across multiple domains. The current study examined these alternative views by characterising the functional coupling of the pCC in easy semantic decisions (based on strong global associations) and in harder semantic tasks (matching words on the basis of specific non-dominant features). Increasingly difficult semantic decisions led to the expected pattern of deactivation in the pCC; however, psychophysiological interaction analysis revealed that, under these conditions, the pCC exhibited greater connectivity with dorsolateral prefrontal cortex (PFC), relative to both easier semantic decisions and to a period of rest. In a second experiment using different participants, we found that functional coupling at rest between the pCC and the same region of dorsolateral PFC was stronger for participants who were more efficient at semantic tasks when assessed in a subsequent laboratory session. Thus, although overall levels of activity in the pCC are reduced during external tasks, this region may show greater coupling with executive control regions when information is retrieved from memory in a goal-directed manner.

Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.HighlightsSensory and perceptual aberrations are becoming a core feature of the ASD symptom prolife.Brain oscillations and functional connectivity are consistently affected in ASD.Relationships (coupling) between high and low frequencies are also deficient.Novel framework proposes the ASD brain is marked by local dysregulation and reduced top-down connectivityThe ASD brain’s ability to predict stimuli and events in the environment may be affectedThis may underlie perceptual sensitives and cascade into social processing deficits in ASD

There is increasing interest in understanding how the phase and amplitude of distinct neural oscillations might interact to support dynamic communication within the brain. In particular, previous work has demonstrated a coupling between the phase of low frequency oscillations and the amplitude (or power) of high frequency oscillations during certain tasks, termed phase amplitude coupling (PAC). For instance, during visual processing in humans, PAC has been reliably observed between ongoing alpha (8–13 Hz) and gamma-band (>40 Hz) activity. However, the application of PAC metrics to electrophysiological data can be challenging due to numerous methodological issues and lack of coherent approaches within the field. Therefore, in this article we outline the various analysis steps involved in detecting PAC, using an openly available MEG dataset from 16 participants performing an interactive visual task. Firstly, we localized gamma and alpha-band power using the Fieldtrip toolbox, and extracted time courses from area V1, defined using a multimodal parcelation scheme. These V1 responses were analyzed for changes in alpha-gamma PAC, using four common algorithms. Results showed an increase in alpha (7–13 Hz)–gamma (40–100 Hz) PAC in response to the visual grating stimulus, though specific patterns of coupling were somewhat dependent upon the algorithm employed. Additionally, post-hoc analyses showed that these results were not driven by the presence of non-sinusoidal oscillations, and that trial length was sufficient to obtain reliable PAC estimates. Finally, throughout the article, methodological issues and practical guidelines for ongoing PAC research will be discussed.

Please cite this article as: Kessler, K., Seymour, R.A., Rippon, G., Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling.Neuroscience and Biobehavioral Reviews http://dx.doi.org/10. 1016/j.neubiorev.2016.10.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Abstract:Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains.Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.

Autism Spectrum Disorder is increasingly associated with atypical perceptual and sensory symptoms. Here we explore the hypothesis that aberrant sensory processing in Autism Spectrum Disorder could be linked to atypical intra-(local) and inter-regional (global) brain connectivity. To elucidate oscillatory dynamics and connectivity in the visual domain we used magnetoencephalography and a simple visual grating paradigm with a group of 18 adolescent autistic participants and 18 typically developing controls. Both groups showed similar increases in gamma (40-80Hz) and decreases in alpha (8-13Hz) frequency power in occipital cortex. However, systematic group differences emerged when analysing intra-and inter-regional connectivity in detail. Firstly, directed connectivity was estimated using nonparametric Granger causality between visual areas V1 and V4. Feedforward V1-to-V4 connectivity, mediated by gamma oscillations, was equivalent between Autism Spectrum Disorder and control groups, but importantly, feedback V4-to-V1 connectivity, mediated by alpha (8-13Hz) oscillations, was significantly reduced in the Autism Spectrum Disorder group. This reduction was positively correlated with autistic quotient scores, consistent with an atypical visual hierarchy in autism, characterised by reduced top-down modulation of visual input via alpha-band oscillations. Secondly, at the local level in V1, coupling of alphaphase to gamma amplitude (alpha-gamma phase amplitude coupling, PAC) was reduced in the Autism Spectrum Disorder group. This implies dysregulated local visual processing, with gamma oscillations decoupled from patterns of wider alpha-band phase synchrony (i.e. reduced PAC), possibly due to an excitation-inhibition imbalance. More generally, these results are in agreement with predictive coding accounts of neurotypical perception and indicate that visual processes in autism are less modulated by contextual feedback information.

Autism Spectrum Disorder is often accompanied by sensory symptoms. Using magnetoencephalography to measure gamma and alpha band cortical activity in affected individuals, Seymour et al. corroborate the hypothesis that aberrant sensory processing is linked to atypical functional connectivity within and between areas of the visual system.

Optically pumped magnetometer-based magnetoencephalography (OP-MEG) can be used to measure neuromagnetic fields while participants move in a magnetically shielded room. Head movements in previous OP-MEG studies have been up to 20 cm translation and ∼30° rotation in a sitting position. While this represents a step-change over stationary MEG systems, naturalistic head movement is likely to exceed these limits, particularly when participants are standing up. In this proof-of-concept study, we sought to push the movement limits of OP-MEG even further. Using a 90 channel (45-sensor) whole-head OP-MEG system and concurrent motion capture, we recorded auditory evoked fields while participants were: (i) sitting still, (ii) standing up and still, and (iii) standing up and making large natural head movements continuously throughout the recording – maximum translation 120 cm, maximum rotation 198°. Following pre-processing, movement artefacts were substantially reduced but not eliminated. However, upon utilisation of a beamformer, the M100 event-related field localised to primary auditory regions. Furthermore, the event-related fields from auditory cortex were remarkably consistent across the three conditions. These results suggest that a wide range of movement is possible with current OP-MEG systems. This in turn underscores the exciting potential of OP-MEG for recording neural activity during naturalistic paradigms that involve movement (e.g. navigation), and for scanning populations who are difficult to study with stationary MEG (e.g. young children).