Siân E. Robson

Measuring temporal, spectral and spatial changes in electrophysiological brain network connectivity.

The topic of functional connectivity in neuroimaging is expanding rapidly and many studies now focus on coupling between spatially separate brain regions. These studies show that a relatively small number of large scale networks exist within the brain, and that healthy function of these networks is disrupted in many clinical populations. To date, the vast majority of studies probing connectivity employ techniques that compute time averaged correlation over several minutes, and between specific pre-defined brain locations. However, increasing evidence suggests that functional connectivity is non-stationary in time. Further, electrophysiological measurements show that connectivity is dependent on the frequency band of neural oscillations. It is also conceivable that networks exhibit a degree of spatial inhomogeneity, i.e. the large scale networks that we observe may result from the time average of multiple transiently synchronised sub-networks, each with their own spatial signature. This means that the next generation of neuroimaging tools to compute functional connectivity must account for spatial inhomogeneity, spectral non-uniformity and temporal non-stationarity. Here, we present a means to achieve this via application of windowed canonical correlation analysis (CCA) to source space projected MEG data. We describe the generation of time-frequency connectivity plots, showing the temporal and spectral distribution of coupling between brain regions. Moreover, CCA over voxels provides a means to assess spatial non-uniformity within short time-frequency windows. The feasibility of this technique is demonstrated in simulation and in a resting state MEG experiment where we elucidate multiple distinct spatio-temporal-spectral modes of covariation between the left and right sensorimotor areas.

Subtraction artifacts and frequency (Mis‐)alignment in J‐difference GABA editing

To compare the repeatability of γ‐aminobutyric acid (GABA) measurements using J‐difference editing, before and after spectral realignment—a technique which has previously been demonstrated to improve the quality of J‐difference GABA spectra.

Abnormal salience signaling in schizophrenia: The role of integrative beta oscillations

Aberrant salience attribution and cerebral dysconnectivity both have strong evidential support as core dysfunctions in schizophrenia. Aberrant salience arising from an excess of dopamine activity has been implicated in delusions and hallucinations, exaggerating the significance of everyday occurrences and thus leading to perceptual distortions and delusional causal inferences. Meanwhile, abnormalities in key nodes of a salience brain network have been implicated in other characteristic symptoms, including the disorganization and impoverishment of mental activity. A substantial body of literature reports disruption to brain network connectivity in schizophrenia. Electrical oscillations likely play a key role in the coordination of brain activity at spatially remote sites, and evidence implicates beta band oscillations in long‐range integrative processes. We used magnetoencephalography and a task designed to disambiguate responses to relevant from irrelevant stimuli to investigate beta oscillations in nodes of a network implicated in salience detection and previously shown to be structurally and functionally abnormal in schizophrenia. Healthy participants, as expected, produced an enhanced beta synchronization to behaviorally relevant, as compared to irrelevant, stimuli, while patients with schizophrenia showed the reverse pattern: a greater beta synchronization in response to irrelevant than to relevant stimuli. These findings not only support both the aberrant salience and disconnectivity hypotheses, but indicate a common mechanism that allows us to integrate them into a single framework for understanding schizophrenia in terms of disrupted recruitment of contextually appropriate brain networks. Hum Brain Mapp 37:1361‐1374, 2016.

Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions.

Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typically measured using haemodynamic signals) and electrophysiology has been explored using functional Magnetic Resonance Imaging (fMRI) and magnetoencephalography (MEG). Significant progress has been made, with similar spatial structure observable in both modalities. However, there is a pressing need to understand this relationship beyond simple visual similarity of RSN patterns. Here, we introduce a mathematical model to predict fMRI-based RSNs using MEG. Our unique model, based upon a multivariate Taylor series, incorporates both phase and amplitude based MEG connectivity metrics, as well as linear and non-linear interactions within and between neural oscillations measured in multiple frequency bands. We show that including non-linear interactions, multiple frequency bands and cross-frequency terms significantly improves fMRI network prediction. This shows that fMRI connectivity is not only the result of direct electrophysiological connections, but is also driven by the overlap of connectivity profiles between separate regions. Our results indicate that a complete understanding of the electrophysiological basis of RSNs goes beyond simple frequency-specific analysis, and further exploration of non-linear and cross-frequency interactions will shed new light on distributed network connectivity, and its perturbation in pathology.

Complexity measures in magnetoencephalography: measuring "disorder" in schizophrenia.

This paper details a methodology which, when applied to magnetoencephalography (MEG) data, is capable of measuring the spatio-temporal dynamics of ‘disorder’ in the human brain. Our method, which is based upon signal entropy, shows that spatially separate brain regions (or networks) generate temporally independent entropy time-courses. These time-courses are modulated by cognitive tasks, with an increase in local neural processing characterised by localised and transient increases in entropy in the neural signal. We explore the relationship between entropy and the more established time-frequency decomposition methods, which elucidate the temporal evolution of neural oscillations. We observe a direct but complex relationship between entropy and oscillatory amplitude, which suggests that these metrics are complementary. Finally, we provide a demonstration of the clinical utility of our method, using it to shed light on aberrant neurophysiological processing in schizophrenia. We demonstrate significantly increased task induced entropy change in patients (compared to controls) in multiple brain regions, including a cingulo-insula network, bilateral insula cortices and a right fronto-parietal network. These findings demonstrate potential clinical utility for our method and support a recent hypothesis that schizophrenia can be characterised by abnormalities in the salience network (a well characterised distributed network comprising bilateral insula and cingulate cortices).

Abnormal visuomotor processing in schizophrenia

Subtle disturbances of visual and motor function are known features of schizophrenia and can greatly impact quality of life; however, few studies investigate these abnormalities using simple visuomotor stimuli. In healthy people, electrophysiological data show that beta band oscillations in sensorimotor cortex decrease during movement execution (event-related beta desynchronisation (ERBD)), then increase above baseline for a short time after the movement (post-movement beta rebound (PMBR)); whilst in visual cortex, gamma oscillations are increased throughout stimulus presentation. In this study, we used a self-paced visuomotor paradigm and magnetoencephalography (MEG) to contrast these responses in patients with schizophrenia and control volunteers. We found significant reductions in the peak-to-peak change in amplitude from ERBD to PMBR in schizophrenia compared with controls. This effect was strongest in patients who made fewer movements, whereas beta was not modulated by movement in controls. There was no significant difference in the amplitude of visual gamma between patients and controls. These data demonstrate that clear abnormalities in basic sensorimotor processing in schizophrenia can be observed using a very simple MEG paradigm.

Structural and neurochemical correlates of individual differences in gamma frequency oscillations in human visual cortex

Neuronal oscillations in the gamma frequency range play an important role in stimulus processing in the brain. The frequency of these oscillations can vary widely between participants and is strongly genetically determined, but the cause of this variability is not understood. Previous studies have reported correlations between individual differences in gamma frequency and the concentration of the inhibitory neurotransmitter, gamma‐aminobutyric acid (GABA), as well as with age and primary visual cortex (V1) area and thickness. This study assessed the relationships between all of these variables in the same group of participants. There were no significant correlations between gamma frequency and GABA+ concentration, V1 area or V1 thickness, although the relationship with GABA+/Cr approached significance. Considering age as a covariate further reduced the strength of all correlations and, in an additional dataset with a larger age range, gamma frequency was strongly inversely correlated with age but not V1 thickness or area, suggesting that age modulates gamma frequency via an additional, as yet unknown, mechanism. Consistent with other recent studies, these findings do not demonstrate a clear relationship between gamma frequency and GABA+ concentration. Further investigation of additional variables and the interactions between them will be necessary in order to more accurately determine predictors of the frequency of gamma oscillations.

Glutathione and glutamate in schizophrenia: a 7T MRS study

In schizophrenia, abnormal neural metabolite concentrations may arise from cortical damage following neuroinflammatory processes implicated in acute episodes. Inflammation is associated with increased glutamate, whereas the antioxidant glutathione may protect against inflammation-induced oxidative stress. We hypothesized that patients with stable schizophrenia would exhibit a reduction in glutathione, glutamate, and/or glutamine in the cerebral cortex, consistent with a post-inflammatory response, and that this reduction would be most marked in patients with “residual schizophrenia”, in whom an early stage with positive psychotic symptoms has progressed to a late stage characterized by long-term negative symptoms and impairments. We recruited 28 patients with stable schizophrenia and 45 healthy participants matched for age, gender, and parental socio-economic status. We measured glutathione, glutamate and glutamine concentrations in the anterior cingulate cortex (ACC), left insula, and visual cortex using 7T proton magnetic resonance spectroscopy (MRS). Glutathione and glutamate were significantly correlated in all three voxels. Glutamine concentrations across the three voxels were significantly correlated with each other. Principal components analysis (PCA) produced three clear components: an ACC glutathione–glutamate component; an insula-visual glutathione–glutamate component; and a glutamine component. Patients with stable schizophrenia had significantly lower scores on the ACC glutathione–glutamate component, an effect almost entirely leveraged by the sub-group of patients with residual schizophrenia. All three metabolite concentration values in the ACC were significantly reduced in this group. These findings are consistent with the hypothesis that excitotoxicity during the acute phase of illness leads to reduced glutathione and glutamate in the residual phase of the illness.

T144. THE ROLE OF TRANSIENT BETA OSCILLATIONS IN ABERRANT SELECTIVE ATTENTION TO SALIENT EVENTS IN SCHIZOPHRENIA

Abstract Background Selective attention to situationally salient information is aberrant in schizophrenia. Following the presentation of behaviourally relevant stimuli, oscillatory power in the beta-band (13-30Hz) typically decreases (Event-Related Desynchronisation – ERD) then increases (Event-Related Synchronisation – ERS). The ERD-ERS pattern is a potential marker for the processing of behaviourally salient events. In a previous magnetoencephalography (MEG) study (Liddle et al Hum. Brain Mapp. 2016; 37:1361–74) we found that in people with schizophrenia, ERS was reduced. Recently, Jones (Curr. Opin. Neurobiol, 2016; 40: 72–80) proposed that the relatively continuous beta-synchronisation observed in trial-averaged data may reflect the probability distribution of transient beta events discernible in single trial data. She cited both animal and human data consistent with a neural model in which these beta bursts are generated by transient input to pyramidal neurons via distal dendrites concurrent with input to deeper layers presumed to be from thalamus. External stimuli are less likely to be perceived during the time period immediately following a transient beta event. The model is consistent with the hypothesis that transient beta bursts are an index of top-down modulation of the processing of perceptual information, and raises the possibility that aberrant control over this modulation might contribute to aberrant selective attention in schizophrenia. We hypothesized that in relevant trials, the beta-burst probability distribution would be skewed towards the latter part of the trial, reflecting a period of suppressed beta-burst probability, and thus of enhanced stimulus perception, followed by a period of increased burst probability, possibly reflecting sensory suppression following stimulus processing. Methods We recorded MEG data in 23 patients with schizophrenia and 37 healthy controls during the performance of a relevance modulation task designed to assess neural effects of situational salience. Data were recorded using a 275-channel CTF system (Coquitlam, Canada). Visual stimuli that were either task-relevant or task-irrelevant were presented in alternating, predictable, order. Beamformed data time courses were computed for 8 previously defined brain networks. Time-frequency spectrograms were computed for each trial, from 0 to 1500 ms following stimulus presentation. A 2-D peak-detection algorithm was used to identify transient increases in oscillatory power. The time point of any peak occurring within the beta band (~15–25 Hz) was recorded, and the median of these time-points computed for each trial. These medians were averaged within each participant for each trial type (relevant; irrelevant) as a measure of central tendency of the probability distribution of the beta-bursts. Results On average, between one or two beta-bursts were recorded per trial. As predicted, these occurred significantly later during behaviorally relevant trials than during irrelevant trials, in all networks, F(1,58)= 93.5, p<0.001), consistent with normal post-event beta enhancement. This effect was significantly attenuated in schizophrenia, F(1,58)=6.01, p=.017. Discussion These findings add to the evidence that patients with schizophrenia have reduced ability to allocate attention to behaviorally relevant information. Furthermore, the demonstration of an abnormality potentially accounted for by neural modelling of top-down influence on perceptual processing opens the way to understanding the relevant neural mechanism and to developing neuromodulatory treatments that might alleviate aberrant selective attention in schizophrenia.

Changes in electrophysiological markers of cognitive control after administration of galantamine

The healthy brain is able to maintain a stable balance between bottom-up sensory processing and top-down cognitive control. The neurotransmitter acetylcholine plays a substantial role in this. Disruption of this balance could contribute to symptoms occurring in psychosis, including subtle disruption of motor control and aberrant appropriation of salience to external stimuli; however the pathological mechanisms are poorly understood. On account of the role beta oscillations play in mediating cognitive control, investigation of beta oscillations is potentially informative about such mechanisms. Here, we used magnetoencephalography to investigate the effect of the acetylcholinesterase-inhibitor, galantamine, on beta oscillations within the sensorimotor region during both a sensorimotor task and a relevance–modulation task in healthy participants, employing a double blind randomized placebo controlled cross-over design. In the galantamine condition, we found a significant reduction in the post-movement beta rebound in the case of executed movements and also in a planned but not executed movement. In the latter case, the effect was significantly greater following task-relevant compared with irrelevant stimuli. The results suggest that the action of galantamine reduces the influence of top-down cognitive processing relative to bottom-up perceptual processing in a manner resembling changes previously reported in schizophrenia.