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Neutron detection is of great importance in many fields spanning from scientific research, to nuclear science, and to medical application. The development of silicon-based neutron detectors with enhanced neutron detection efficiency can offer several advantages such as spatial resolution, enhanced dynamic range and background discrimination. In this work, increased detection efficiency is pursued by fabricating high aspect ratio 3D micro-structures filled with neutron converting materials (B4C) on planar silicon detectors. An in-depth feasibility study was carried out in all aspects of the sensor fabrication technology. Passivation of the etched structures was studied in detail, to ensure good electrical performance. The conformal deposition of B4C with a newly developed process showed excellent results. Preliminary electrical characterisation of the completed devices is promising, and detectors have been mounted on dedicated boards in view of the upcoming tests with neutrons. Funding Agencies|Research Council of Norway [289437]; Swedish Research Council [2018-05499]; Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials (AFM) at Linkoping University (Faculty Grant SFO Mat LiU) [2009 00971]

Background: Evidence of initiatives to support General Practitioners (GPs) during the Covid-19 pandemic is scant. Aim: To understand the impact of a novel method of providing support in the early stages of the pandemic. Design and setting: A mixed-methods study of GPs working in a socially deprived area of Belfast. Method: A survey was distributed to GPs who had attended a series of educational meetings at the beginning of the COVID-19 pandemic. The survey incorporated the Warwick Edinburgh Mental Wellbeing Scale and questions about the virtual meetings. Follow-up interviews were undertaken with five GPs to further explore their lived experiences and their perceptions of the virtual support forum. Results: The Covid-19 pandemic resulted in a measurable diminution of emotional well-being in GPs in North and West Belfast. Attendees rated a series of virtual meetings highly and described the following themes (and subthemes): a sudden traumatic change (emotional response, fight or flight, painful reminders of the status of general practice in the NHS); a coming together (stepping up to take responsibility, sharing of information, feeling of affirmation); reflections on what worked (calming facilitation, careful selection of speakers, creating the right atmosphere, ownership and autonomy) and building future direction (defining future direction, capitalising on lesson learned). Conclusion: The virtual meetings harnessed the instinct to come together witnessed at the beginning of the pandemic, and as well as sharing valuable information, also provided emotional support along with a sense of comradeship, ownership and autonomy. How this fits in: GPs did not feel included or supported at the outset of the pandemic. Coming together with fellow professionals was a welcome source of support. Professional support can be delivered using a virtual platform. Continued professional development is more acceptable than explicit emotional support, but when done well can bolster resilience and emotional well-being.

Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural network. Recent work has suggested that the eigenmodes of the structural network might serve as a basis set for functional network patterns in the case of functional MRI. Here, we take this notion further in the context of frequency band specific MEG networks. We show that a selected set of eigenmodes of the structural network can predict different frequency band specific networks in the resting state, ranging from delta (1–4 Hz) to the high gamma band (40–70 Hz). These predictions outperform predictions based from surrogate data, suggesting a genuine relationship between eigenmodes of the structural network and frequency specific MEG networks. We then show that the relevant set of eigenmodes can be excited in a network of neural mass models using linear stability analysis only by including delays. Excitation of an eigenmode in this context refers to a dynamic instability of a network steady state to a spatial pattern with a corresponding coherent temporal oscillation. Simulations verify the results from linear stability analysis and suggest that theta, alpha and beta band networks emerge very near to the bifurcation. The delta and gamma bands in the resting state emerges further away from the bifurcation. These results show for the first time how delayed interactions can excite the relevant set of eigenmodes that give rise to frequency specific functional connectivity patterns.

Movement induced modulation of the beta rhythm is one of the most robust neural oscillatory phenomena in the brain. In the preparation and execution phases of movement, a loss in beta amplitude is observed [movement related beta decrease (MRBD)]. This is followed by a rebound above baseline on movement cessation [post movement beta rebound (PMBR)]. These effects have been measured widely, and recent work suggests that they may have significant importance. Specifically, they have potential to form the basis of biomarkers for disease, and have been used in neuroscience applications ranging from brain computer interfaces to markers of neural plasticity. However, despite the robust nature of both MRBD and PMBR, the phenomena themselves are poorly understood. In this study, we characterise MRBD and PMBR during a carefully controlled isometric wrist flexion paradigm, isolating two fundamental movement parameters; force output, and the rate of force development (RFD). Our results show that neither altered force output nor RFD has a significant effect on MRBD. In contrast, PMBR was altered by both parameters. Higher force output results in greater PMBR amplitude, and greater RFD results in a PMBR which is higher in amplitude and shorter in duration. These findings demonstrate that careful control of movement parameters can systematically change PMBR. Further, for temporally protracted movements, the PMBR can be over 7 s in duration. This means accurate control of movement and judicious selection of paradigm parameters are critical in future clinical and basic neuroscientific studies of sensorimotor beta oscillations. Hum Brain Mapp 37:2493–2511, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc

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. Keywords: Beta oscillations, PMBR, Acetylcholine, Magnetoencephalography, Schizophrenia

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease., Highlights • The sensorimotor network consists of a series of transiently synchronising subnetworks. • These subnetworks are robust across multiple tasks. • The occurrence of these subnetworks is modulated by the current mental state.