Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called ‘resting-state’ (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localised EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Despite its widespread use in cognitive studies, there is still limited understanding of whether and how transcranial direct current stimulation (tDCS) modulates brain network function. To clarify its physiological effects, we assessed brain network function using functional magnetic resonance imaging (fMRI) simultaneously acquired during tDCS stimulation. Cognitive state was manipulated by having subjects perform a Choice Reaction Task or being at “rest.” A novel factorial design was used to assess the effects of brain state and polarity. Anodal and cathodal tDCS were applied to the right inferior frontal gyrus (rIFG), a region involved in controlling activity large‐scale intrinsic connectivity networks during switches of cognitive state. tDCS produced widespread modulation of brain activity in a polarity and brain state dependent manner. In the absence of task, the main effect of tDCS was to accentuate default mode network (DMN) activation and salience network (SN) deactivation. In contrast, during task performance, tDCS increased SN activation. In the absence of task, the main effect of anodal tDCS was more pronounced, whereas cathodal tDCS had a greater effect during task performance. Cathodal tDCS also accentuated the within‐DMN connectivity associated with task performance. There were minimal main effects of stimulation on network connectivity. These results demonstrate that rIFG tDCS can modulate the activity and functional connectivity of large‐scale brain networks involved in cognitive function, in a brain state and polarity dependent manner. This study provides an important insight into mechanisms by which tDCS may modulate cognitive function, and also has implications for the design of future stimulation studies.

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.

The analysis of neuronal avalanches supports the hypothesis that the human cortex operates with critical neural dynamics. Here, we investigate the relationship between cascades of activity in electroencephalogram data, cognitive state, and reaction time in humans using a multimodal approach. We recruited 18 healthy volunteers for the acquisition of simultaneous electroencephalogram and functional magnetic resonance imaging during both rest and during a visuomotor cognitive task. We compared distributions of electroencephalogram-derived cascades to reference power laws for task and rest conditions. We then explored the large-scale spatial correspondence of these cascades in the simultaneously acquired functional magnetic resonance imaging data. Furthermore, we investigated whether individual variability in reaction times is associated with the amount of deviation from power law form. We found that while resting state cascades are associated with approximate power law form, the task state is associated with subcritical dynamics. Furthermore, we found that electroencephalogram cascades are related to blood oxygen level-dependent activation, predominantly in sensorimotor brain regions. Finally, we found that decreased reaction times during the task condition are associated with increased proximity to power law form of cascade distributions. These findings suggest that the resting state is associated with near-critical dynamics, in which a high dynamic range and a large repertoire of brain states may be advantageous. In contrast, a focused cognitive task induces subcritical dynamics, which is associated with a lower dynamic range, which in turn may reduce elements of interference affecting task performance.