Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity.

Development of human electrophysiological brain networks.

Functional activity in the human brain is intrinsically organized into independently active, connected brain regions. These networks include sensorimotor systems, as well as higher-order cognitive networks such as the default mode network (DMN), which dominates activity when the brain is at rest, and the frontoparietal (FPN) and salience (SN) networks, which are often engaged during demanding tasks. Evidence from functional magnetic resonance imaging (fMRI) suggests that although sensory systems are mature by the end of childhood, the integrity of the FPN and SN develops throughout adolescence. There has been little work to corroborate these findings with electrophysiology. Using magnetoencephalography (MEG) recordings of 48 participants (aged 9-25 yr) at rest, we find that beta-band functional connectivity within the FPN, SN, and DMN continues to increase through adolescence, whereas connectivity in the visual system is mature by late childhood. In contrast to fMRI results, but replicating the MEG findings of Schäfer et al. (Schäfer CB, Morgan BR, Ye AX, Taylor MJ, Doesburg SM. Hum Brain Mapp 35: 5249-5261, 2014), we also see that connectivity between networks increases rather than decreases with age. This suggests that the development of coordinated beta-band oscillations within and between higher-order cognitive networks through adolescence might contribute to the developing abilities of adolescents to focus their attention and coordinate diverse aspects of mental activity. NEW & NOTEWORTHY Using magnetoencephalography to assess beta frequency oscillations, we show that functional connectivity within higher-order cognitive networks increases from childhood, reaching adult values by age 20 yr. In contrast, connectivity within a primary sensory (visual) network reaches adult values by age 14 yr. In contrast to functional MRI findings, connectivity between cognitive networks matures at a rate similar to within-network connectivity, suggesting that coordination of beta oscillations both within and between networks is associated with maturation of cognitive skills.

Measurement of dynamic task related functional networks using MEG.

The characterisation of dynamic electrophysiological brain networks, which form and dissolve in order to support ongoing cognitive function, is one of the most important goals in neuroscience. Here, we introduce a method for measuring such networks in the human brain using magnetoencephalography (MEG). Previous network analyses look for brain regions that share a common temporal profile of activity. Here distinctly, we exploit the high spatio-temporal resolution of MEG to measure the temporal evolution of connectivity between pairs of parcellated brain regions. We then use an ICA based procedure to identify networks of connections whose temporal dynamics covary. We validate our method using MEG data recorded during a finger movement task, identifying a transient network of connections linking somatosensory and primary motor regions, which modulates during the task. Next, we use our method to image the networks which support cognition during a Sternberg working memory task. We generate a novel neuroscientific picture of cognitive processing, showing the formation and dissolution of multiple networks which relate to semantic processing, pattern recognition and language as well as vision and movement. Our method tracks the dynamics of functional connectivity in the brain on a timescale commensurate to the task they are undertaking.

Altered cortical beta-band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis.

Continuous rhythmic neuronal oscillations underpin local and regional cortical communication. The impact of the motor system neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) on the neuronal oscillations subserving movement might therefore serve as a sensitive marker of disease activity. Movement preparation and execution are consistently associated with modulations to neuronal oscillation beta (15-30 Hz) power. Cortical beta-band oscillations were measured using magnetoencephalography (MEG) during preparation for, execution, and completion of a visually cued, lateralized motor task that included movement inhibition trials. Eleven "classical" ALS patients, 9 with the primary lateral sclerosis (PLS) phenotype, and 12 asymptomatic carriers of ALS-associated gene mutations were compared with age-similar healthy control groups. Augmented beta desynchronization was observed in both contra- and ipsilateral motor cortices of ALS patients during motor preparation. Movement execution coincided with excess beta desynchronization in asymptomatic mutation carriers. Movement completion was followed by a slowed rebound of beta power in all symptomatic patients, further reflected in delayed hemispheric lateralization for beta rebound in the PLS group. This may correspond to the particular involvement of interhemispheric fibers of the corpus callosum previously demonstrated in diffusion tensor imaging studies. We conclude that the ALS spectrum is characterized by intensified cortical beta desynchronization followed by delayed rebound, concordant with a broader concept of cortical hyperexcitability, possibly through loss of inhibitory interneuronal influences. MEG may potentially detect cortical dysfunction prior to the development of overt symptoms, and thus be able to contribute to the assessment of future neuroprotective strategies. Hum Brain Mapp 38:237-254, 2017. © 2016 Wiley Periodicals, Inc.

Cognitive training enhances intrinsic brain connectivity in childhood.

In human participants, the intensive practice of particular cognitive activities can induce sustained improvements in cognitive performance, which in some cases transfer to benefits on untrained activities. Despite the growing body of research examining the behavioral effects of cognitive training in children, no studies have explored directly the neural basis of these training effects in a systematic, controlled fashion. Therefore, the impact of training on brain neurophysiology in childhood, and the mechanisms by which benefits may be achieved, are unknown. Here, we apply new methods to examine dynamic neurophysiological connectivity in the context of a randomized trial of adaptive working memory training undertaken in children. After training, connectivity between frontoparietal networks and both lateral occipital complex and inferior temporal cortex was altered. Furthermore, improvements in working memory after training were associated with increased strength of neural connectivity at rest, with the magnitude of these specific neurophysiological changes being mirrored by individual gains in untrained working memory performance.

Electrophysiological measures of resting state functional connectivity and their relationship with working memory capacity in childhood.

Functional connectivity is the statistical association of neuronal activity time courses across distinct brain regions, supporting specific cognitive processes. This coordination of activity is likely to be highly important for complex aspects of cognition, such as the communication of fluctuating task goals from higher-order control regions to lower-order, functionally specific regions. Some of these functional connections are identifiable even when relevant cognitive tasks are not being performed (i.e. at rest). We used magnetoencephalographic recordings projected into source space to demonstrate that resting state networks in childhood have electrophysiological underpinnings that are evident in the spontaneous fluctuations of oscillatory brain activity. Using the temporal structure of these oscillatory patterns we were able to identify a number of functional resting state networks analogous to those reported in the adult literature. In a second analysis we fused this dynamic temporal information with the spatial information from a functional magnetic resonance imaging analysis of functional connectivity, to demonstrate that inter-subject variability in these electrophysiological measures of functional connectivity is correlated with individual differences in cognitive ability: the strength of connectivity between a fronto-parietal network and lower-level processing areas in inferior temporal cortex was associated with spatial working memory capacity, as measured outside the scanner with educationally relevant standardized assessments. This study represents the first exploration of the electrophysiological mechanisms underpinning resting state functional connectivity in source space in childhood, and the extent to which the strength of particular connections is associated with cognitive ability.

Modulation of hippocampal theta and hippocampal-prefrontal cortex function by a schizophrenia risk gene.

Hippocampal theta-band oscillations are thought to facilitate the co-ordination of brain activity across distributed networks, including between the hippocampus and prefrontal cortex (PFC). Impairments in hippocampus-PFC functional connectivity are implicated in schizophrenia and are associated with a polymorphism within the ZNF804A gene that shows a genome-wide significant association with schizophrenia. However, the mechanisms by which ZNF804A affects hippocampus-PFC connectivity are unknown. We used a multimodal imaging approach to investigate the impact of the ZNF804A polymorphism on hippocampal theta and hippocampal network coactivity. Healthy volunteers homozygous for the ZNF804A rs1344706 (A[risk]/C[nonrisk]) polymorphism were imaged at rest using both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). A dual-regression approach was used to investigate coactivations between the hippocampal network and other brain regions for both modalities, focusing on the theta band in the case of MEG. We found a significant decrease in intrahippocampal theta (using MEG) and greater coactivation of the superior frontal gyrus with the hippocampal network (using fMRI) in risk versus nonrisk homozygotes. Furthermore, these measures showed a significant negative correlation. Our demonstration of an inverse relationship between hippocampal theta and hippocampus-PFC coactivation supports a role for hippocampal theta in coordinating hippocampal-prefrontal activity. The ZNF804A-related differences that we find in hippocampus-PFC coactivation are consistent with previously reported associations with functional connectivity and with these changes lying downstream of altered hippocampal theta. Changes in hippocampal-PFC co-ordination, driven by differences in oscillatory activity, may be one mechanism by which ZNF804A impacts on brain function and risk for psychosis.

Increased cerebral functional connectivity in ALS: A resting-state magnetoencephalography study.

OBJECTIVE: We sought to assess cortical function in amyotrophic lateral sclerosis (ALS) using noninvasive neural signal recording. METHODS: Resting-state magnetoencephalography was used to measure power fluctuations in neuronal oscillations from distributed cortical parcels in 24 patients with ALS and 24 healthy controls. A further 9 patients with primary lateral sclerosis and a group of 15 asymptomatic carriers of genetic mutations associated with ALS were also studied. RESULTS: Increased functional connectivity, particularly from the posterior cingulate cortex, was demonstrated in both patient groups compared to healthy controls. Directionally similar patterns were also evident in the asymptomatic genetic mutation carrier group. CONCLUSION: Increased cortical functional connectivity elevation is a quantitative marker that reflects ALS pathology across its clinical spectrum, and may develop during the presymptomatic period. The amelioration of pathologic magnetoencephalography signals might be a marker sensitive enough to provide proof-of-principle in the development of future neuroprotective therapeutics.

Impaired corticomuscular and interhemispheric cortical beta oscillation coupling in amyotrophic lateral sclerosis.

OBJECTIVES: The neural activity of the primary motor cortex is variably synchronised with contralateral peripheral electromyographic signals, which is thought to facilitate long-range communication through the motor system. Such corticomuscular coherence (CMC) is typically observed in the beta-band (15-30 Hz) range during steady force production. We aimed to measure pathological alteration to CMC resulting from ALS. METHODS: CMC was appraised during a forearm grip task in 17 ALS patients contrasted against age-matched healthy controls. An exploratory comparison with a group of asymptomatic ALS gene carriers and neuropathy disease mimics was also undertaken. Neural signals were acquired by whole-head magnetoencephalography and localised via structural MRI to the motor cortices. RESULTS: During light voluntary muscular contraction, beta-band CMC was significantly reduced in ALS patients compared to healthy controls. Propagation of motoric beta rhythms across the cortical hemispheres was also shown to be impaired in ALS patients. CMC was preserved in the asymptomatic gene carrier and did not distinguish ALS patients from neuropathy mimics. CONCLUSION: Functional connectivity metrics reveal an ALS-related decrease in both corticomuscular and interhemispheric communication during bilateral grip force production. SIGNIFICANCE: MEG-derived beta oscillation coupling may be a potential biomarker of motor system dysfunction in ALS, against which to measure future therapeutic efficacy.

The heritability of multi-modal connectivity in human brain activity.

Patterns of intrinsic human brain activity exhibit a profile of functional connectivity that is associated with behaviour and cognitive performance, and deteriorates with disease. This paper investigates the relative importance of genetic factors and the common environment between twins in determining this functional connectivity profile. Using functional magnetic resonance imaging (fMRI) on 820 subjects from the Human Connectome Project, and magnetoencephalographic (MEG) recordings from a subset, the heritability of connectivity among 39 cortical regions was estimated. On average over all connections, genes account for about 15% of the observed variance in fMRI connectivity (and about 10% in alpha-band and 20% in beta-band oscillatory power synchronisation), which substantially exceeds the contribution from the environment shared between twins. Therefore, insofar as twins share a common upbringing, it appears that genes, rather than the developmental environment, have the dominant role in determining the coupling of neuronal activity.