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BackgroundNeurocognitive impairment linked to head impact exposure in otherwise healthy, non-concussed athletes may be associated with adverse long-term outcomes. The primary purpose of this study was to evaluate whether a dietary supplement, SynaquellTM, supports brain function and structure in male Junior A ice hockey players over the course of a season.MethodsPlayers underwent pre-season testing, were randomized into a placebo or dietary supplement group, then were retested after the season. Objective tests included: NeuroCatch®portable evoked potential platform, King-Devick Test of rapid number naming, and blood biomarker assay for neurofilament light chain (NfL).ResultsMultivariate analysis revealed significant differences in neurocognitive changes between groups from pre to postseason after controlling for covariates related to head impact exposure. Post-hoc tests showed significant within-subject differences between groups from pre- to post-season in both N100 latency (p = 0.005) and King-Devick score (p = 0.043). Univariate tests of the NeuroCatch results replicated prior findings of a N400 amplitude decrease (p = 0.017) and N100 latency increase (p = 0.049) in the placebo group, but not in the dietary supplement group.ConclusionsThis prospective, randomized trial showed that, compared to the placebo group, a multi-ingredient dietary supplement significantly affected objective measures of brain function and structure in Junior A ice hockey players from pre- to post-season. Further investigation into the effects of dietary supplementation on the contact athlete’s brain is warranted.

Magnetic resonance imaging (MRI) studies are sensitive to biological mechanisms of neuroplasticity in white matter (WM). In particular, diffusion tensor imaging (DTI) has been used to investigate structural changes. Historically, functional MRI (fMRI) neuroplasticity studies have been restricted to gray matter, as fMRI studies have only recently expanded to WM. The current study evaluated WM neuroplasticity pre–post motor training in healthy adults, focusing on motor learning in the non-dominant hand. Neuroplasticity changes were evaluated in two established WM regions-of-interest: the internal capsule and the corpus callosum. Behavioral improvements following training were greater for the non-dominant hand, which corresponded with MRI-based neuroplasticity changes in the internal capsule for DTI fractional anisotropy, fMRI hemodynamic response functions, and low-frequency oscillations (LFOs). In the corpus callosum, MRI-based neuroplasticity changes were detected in LFOs, DTI, and functional correlation tensors (FCT). Taken together, the LFO results converged as significant amplitude reductions, implicating a common underlying mechanism of optimized transmission through altered myelination. The structural and functional neuroplasticity findings open new avenues for direct WM investigations into mapping connectomes and advancing MRI clinical applications. Supplementary Information The online version contains supplementary material available at 10.1007/s00429-021-02407-4.

Contextual processing (or context processing; CP) is an integral component of cognition. CP allows people to manage their thoughts and actions by adjusting to surroundings. CP involves the formation of an internal representation of context in relation to the environment, maintenance of this information over a period of time, and the updating of mental representations to reflect changes in the environment. Each of these functions can be affected by aging and associated conditions. Here, we introduced contextual processing research and summarized the literature studying the impact of normal aging and neurodegeneration-related cognitive decline on CP. Through searching the PubMed, PsycINFO, and Google Scholar databases, 23 studies were retrieved that focused on the impact of aging, mild cogniitve impairment (MCI), Alzheimer’s disease (AD), and Parkinson’s disease (PD) on CP. Results indicated that CP is particularly vulnerable to aging and neurodegeneration. Older adults had a delayed onset and reduced amplitude of electrophysiological response to information detection, comparison, and execution. MCI patients demonstrated clear signs of impaired CP compared to normal aging. The only study on AD suggested a decreased proactive control in AD participants in maintaining contextual information, but seemingly intact reactive control. Studies on PD restricted to non-demented older participants, who showed limited ability to use contextual information in cognitive and motor processes, exhibiting impaired reactive control but more or less intact proactive control. These data suggest that the decline in CP with age is further impacted by accelerated aging and neurodegeneration, providing insights for improving intervention strategies. This review highlights the need for increased attention to research this important but understudied field.

Background In a recent high-profile case study, we used functional magnetic resonance imaging (fMRI) to monitor improvements in motor function related to neuroplasticity following rehabilitation for severe traumatic brain injury (TBI). The findings demonstrated that motor function improvements can occur years beyond current established limits. The current study extends the functional imaging investigation to characterize neuromodulation effects on neuroplasticity to further push the limits. Methods Canadian Soldier Captain (retired) Trevor Greene (TG) survived a severe open-TBI when attacked with an axe during a 2006 combat tour in Afghanistan. TG has since continued intensive daily rehabilitation to recover motor function, experiencing an extended plateau using conventional physical therapy. To overcome this plateau, we paired translingual neurostimulation (TLNS) with the continuing rehabilitation program. Results Combining TLNS with rehabilitation resulted in demonstrable clinical improvements along with corresponding changes in movement evoked electro-encephalography (EEG) activity. High-density magneto-encephalography (MEG) characterized cortical activation changes in corresponding beta frequency range (27 Hz). MEG activation changes corresponded with reduced interhemispheric inhibition in the post-central gyri regions together with increased right superior/middle frontal activation suggesting large scale network level changes. Conclusions The findings provide valuable insight into the potential importance of non-invasive neuromodulation to enhance neuroplasticity mechanisms for recovery beyond the perceived limits of rehabilitation.

Blink-related oscillations derived from electroencephalography (EEG) have recently emerged as an important measure of awareness. Combined with portable EEG hardware with low-density electrode arrays, this neural marker may crucially augment the existing bedside assessments of consciousness in unresponsive patients. Nonetheless, the close relationship between signal characteristics of the neural response of interest and blink-induced oculomotor artifacts poses particular challenges when measuring blink-related oscillations using a point-of-care platform. This study presents a novel denoising approach based on time-frequency (TF) filtering that exploits the differential temporal and spectral features to isolate the neural response from ocular artifact in a low-density array.We investigated the effectiveness of the TF filtering technique using 64-channel EEG data collected in healthy adults, with focal analysis of the Pz and POz channels.TF filtering showed comparable performance in denoising the signal relative to the established gold-standard independent component analysis approach, with strong similarities in morphological characteristics as measured by intraclass correlations (p0.001), extent of artifact rejection based on the ocular contamination index (p0.006), as well as time- and frequency-domain signal capture (p0.05). Results are robust at the individual and group levels, and are crucially validated using raw data from only four electrodes comprising Pz, POz, Fp2, and T7.These results demonstrate for the first time that TF filtering enables the successful capture and isolation of the blink-related oscillations response using a four-electrode array.This significantly advances the translation of the blink-related oscillations marker to a point-of-care platform for eventual bedside applications.

The size of our pupils changes continuously in response to variations in ambient light levels, a process known as the pupillary light reflex (PLR). The PLR is not a simple reflex as its function is modulated by cognitive brain function and any long-term changes in brain function secondary to injury should cause a change in the parameters of the PLR. We performed a retrospective clinical review of the PLR of our patients using the BrightLamp Reflex iPhone app. The PLR variables of latency, maximum pupil diameter (MaxPD), minimum pupil diameter (MinPD), maximum constriction velocity (MCV), and the 75% recovery time (75% PRT) were associated with significant differences between subjects who had suffered a concussion and those that had not. There were also significant differences in PLR metrics over the life span and between genders and those subjects with and without symptoms. The differences in PLR metrics are modulated not only by concussion history but also by gender and whether or not the person has symptoms associated with a head injury. A concussive injury to the brain is associated with changes in the PLR that persist over the life span, representing biomarkers that might be used in clinical diagnosis, treatment, and decision making.

Background: Electroencephalography (EEG)-derived event-related potentials (ERPs) provide information about a variety of brain functions, but often suffer from low inherent signal-to-noise ratio (SNR). To overcome the low SNR, techniques that pool data from multiple sensors have been applied. However, such pooling implicitly assumes that the SNR among sensors is equal, which is not necessarily valid. This study presents a novel approach for signal pooling that accounts for differential SNR among sensors. Methods: The new technique involves pooling together signals from multiple EEG channels weighted by their respective SNRs relative to the overall SNR of all channels. We compared ERP responses derived using this new technique with those derived using both individual channels as well as traditional averaged-based channel pooling. The outcomes were evaluated in both simulated data and real data from healthy adult volunteers (n = 37). Responses corresponding to a range of ERP components indexing auditory sensation (N100), attention (P300) and language processing (N400) were evaluated. Results: Simulation results demonstrate that, compared to traditional pooling technique, the new SNR-weighted channel pooling technique improved ERP response effect size in cases of unequal noise among channels (p’s &lt, 0.001). Similarly, results from real-world experimental data showed that the new technique resulted in significantly greater ERP effect sizes compared to either traditional pooling or individual channel approach for all three ERP components (p’s &lt, 0.001). Furthermore, the new channel pooling approach also resulted in larger ERP signal amplitudes as well as greater differences among experimental conditions (p’s &lt, 0.001). Conclusion: These results suggest that the new technique improves the capture of ERP responses relative to traditional techniques. As such, SNR-weighted channel pooling can further enable widespread applications of ERP techniques, especially those that require rapid assessments in noisy out-of-laboratory environments.

Objectives The Ice Hockey Summit III provided updated scientific evidence on concussions in hockey to inform these 5 objectives: (1) describe sport related concussion (SRC) epidemiology; (2) classify prevention strategies; (3) define objective, diagnostic tests; (4) identify treatment; and (5) integrate science and clinical care into prioritized action plans and policy. Methods Our action plan evolved from 40 scientific presentations. The 155 attendees (physicians, athletic trainers, physical therapists, nurses, neuropsychologists, scientists, engineers, coaches, and officials) voted to prioritize these action items in the final Summit session. Results To (1) establish a national and international hockey database for SRCs at all levels; (2) eliminate body checking in Bantam youth hockey games; (3) expand a behavior modification program (Fair Play) to all youth hockey levels; (4) enforce game ejection penalties for fighting in Junior A and professional hockey leagues; (5) establish objective tests to diagnose concussion at point of care; and (6) mandate baseline testing to improve concussion diagnosis for all age groups. Conclusions Expedient implementation of the Summit III prioritized action items is necessary to reduce the risk, severity, and consequences of concussion in the sport of ice hockey.

Background Adopting a better understanding of how both older adults and health care providers view the community management of frailty is necessary for improving home health, especially facing the coronavirus disease 2019 (COVID‐19) pandemic. We conducted a qualitative focus group study to assess how both older adults and health care providers view frailty and virtual health care in home health. Methods Two focus groups enrolled home‐living older adults and health care professionals, respectively (n = 15). Questions targeting the use of virtual / telehealth technologies in‐home care for frail older adults were administered at audio‐recorded group interviews. Transcribed discussions were coded and analyzed using NVivo software. Results The older adult group emphasized the autonomy related to increasing frailty and social isolation and the need for transparent dissemination of health care planning. They were optimistic about remote technology‐based supports and suggested that telehealth / health‐monitoring/tracking were in high demand. Health care professionals emphasized the importance of a holistic biopsychosocial approach to frailty management. They highlighted the need for standardized early assessment and management of frailty. Conclusions The integrated perspectives provided an updated understanding of what older adults and practitioners value in home‐living supports. This knowledge is helpful to advancing virtual home care, providing better care for frail individuals with complex health care needs., The study represents an updated understanding of supporting home care of older adults in the new era, by integrating perspectives of both care providers and receivers. It highlights improving virtual technology adaptation for care services and early management of frailty.

Multiple structural brain changes in Alzheimer's disease (AD) and mild cognitive impairment (MCI) have been revealed on magnetic resonance imaging (MRI). There is a fast-growing effort in applying artificial intelligence (AI) to analyze these data. Here, we review and evaluate the AI studies in brain MRI analysis with synthesis.A systematic review of the literature, spanning the years from 2009 to 2020, was completed using the PubMed database. AI studies using MRI imaging to investigate normal aging, mild cognitive impairment, and AD-dementia were retrieved for review. Bias assessment was completed using the PROBAST criteria.97 relevant studies were included in the review. The studies were typically focused on the classification of AD, MCI, and normal aging (71% of the reported studies) and the prediction of MCI conversion to AD (25%). The best performance was achieved by using the deep learning-based convolution neural network algorithms (weighted average accuracy 89%), in contrast to 76-86% using Logistic Regression, Support Vector Machines, and other AI methods.The synthesized evidence is paramount to developing sophisticated AI approaches to reliably capture and quantify multiple subtle MRI changes in the whole brain that exemplify the complexity and heterogeneity of AD and brain aging.

Purpose/objective(s) Gliomas are uniformly fatal brain tumours with significant neurological and quality of life detriment to patients. Improvement in outcomes has remained largely unchanged in nearly 20 years. MRI (magnetic resonance imaging) is often used in diagnosis and management. Machine learning analyses of large-scale MRI data are pivotal in advancing the diagnosis, management and improve outcomes in neuro-oncology. A common challenge to robust machine learning approaches is the lack of large ‘ground truth’ datasets in supervised learning for building classification and prediction models. The creation of these datasets relies on human-expert input and is time-consuming and subjective error-prone, limiting effective machine learning applications. Simulation of mechanistic aspects such as geometry, location and physical properties of brain tumours can generate large-scale ground-truth datasets allowing for comparison of analysis techniques in clinical applications. We aimed to develop a transparent and convenient method for building ‘ground truth’ presentations of simulated glioma lesions on anatomical MRI. Materials/methods The simulation workflow was created using the Feature Manipulation Engine (FME®), a data integration platform specializing in the spatial data processing. By compiling and integrating FME’s functions to read, integrate, transform, validate, save, and display MRI data, and experimenting with ways to manipulate the parameters concerning location, size, shape, and signal intensity with the presentations of glioma, we were able to generate simulated appearances of high-grade gliomas on gadolinium-based high-resolution 3D T1-weighted MRI (1 mm3). Data of patients with canonical high-grade tumours were used as real-world tumours for validating the accuracy of the simulation. Twenty raters who are experienced with brain tumour interpretation on MRI independently completed a survey, designed to distinguish simulated and real-world brain tumours. Sensitivity and specificity were calculated for assessing the performance of the approach with the binary classification of simulated vs real-world tumours. Correlation and regression were used in run time analysis, assessing the software toolset’s efficiency in producing different numbers of simulated lesions. Differences in the group means were examined using the non-parametric Kruskal-Wallis test. Results The simulation method was developed as an interpretable and useful workflow for the easy creation of tumour simulations and incorporation into 3D MRI. A linear increase in the running time and memory usage was observed with an increasing number of generated lesions. The respondents' accuracy rate ranged between 33.3 and 83.3 %. The sensitivity and specificity were low for a human expert to differentiate simulated lesions from real gliomas (0.43 and 0.58) or vice versa (0.65 and 0.62). The mean scores ranking the real-world gliomas did not differ between the simulated and real tumours. Conclusion The reliable and user-friendly software method can allow for robust simulation of high-grade glioma on MRI. Ongoing research efforts include optimizing the workflow for generating glioma datasets as well as adapting it to simulating additional MRI brain changes.

Background: Brain function assessments based on event-related potentials (ERPs) derived from electroencephalography (EEG) are increasingly being conducted in realistic out-of-the-laboratory settings for clinical and non-clinical uses. For rapid testing and practical limitations, such applications require the use of low-density electrode arrays. A major impediment to their use in these applications is the lack of denoising techniques capable of removing artefactual contamination and isolating the ERPs features of interest within low-density arrays. Methods: A novel denoising technique combining empirical mode decomposition (EMD) with template matching procedure is developed and applied to individual-channel data, and the results of this new approach are compared to the results of a conventional (independent component analysis) denoising approach. Both whole-epoch morphological comparisons and specific ERP feature amplitude comparisons were undertaken at the group and individual level for a variety of ERPs indexing sensory (N100), attention (P300) and language processing (N400) using data from 31 healthy adults. Results: The new denoising technique successfully enables the capture of ERPs ranging from low-level sensation to attention to language processing (all p, 2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), September 9-12, 2020, Vancouver, BC, Canada

Motor function assessment is crucial in quantifying motor recovery following stroke. In the rehabilitation field, motor function is usually assessed using questionnaire-based assessments, which are not completely objective and require prior training for the examiners. Some research groups have reported that electroencephalography (EEG) data have the potential to be a good indicator of motor function. However, those motor function scores based on EEG data were not evaluated in a longitudinal paradigm. The ability of the motor function scores from EEG data to track the motor function changes in long-term clinical applications is still unclear. In order to investigate the feasibility of using EEG to score motor function in a longitudinal paradigm, a convolutional neural network (CNN) EEG model and a residual neural network (ResNet) EEG model were previously generated to translate EEG data into motor function scores. To validate applications in monitoring rehabilitation following stroke, the pre-established models were evaluated using an initial small sample of individuals in an active 14-week rehabilitation program. Longitudinal performances of CNN and ResNet were evaluated through comparison with standard Fugl&ndash, Meyer Assessment (FMA) scores of upper extremity collected in the assessment sessions. The results showed good accuracy and robustness with both proposed networks (average difference: 1.22 points for CNN, 1.03 points for ResNet), providing preliminary evidence for the proposed method in objective evaluation of motor function of upper extremity in long-term clinical applications.

Introduction Previous studies have shown that simulation is an acceptable method of training in nursing education. The objectives of this study were to determine the effectiveness of tablet-based simulation in learning neurosurgical instruments and to assess whether skills learnt in the simulation environment are transferred to a real clinical task and retained over time. Methods A randomised controlled trial was conducted. Perioperative nurses completed three consecutive sessions of a simulation. Group A performed simulation tasks prior to identifying real instruments, whereas Group B (control group) was asked to identify real instruments prior to the simulation tasks. Both groups were reassessed for knowledge recall after 1 week. Results Ninety-three nurses completed the study. Participants in Group A, who had received tablet-based simulation, were 23% quicker in identifying real instruments and did so with better accuracy (93.2% vs 80.6%, p Conclusion This is the first study to assess the effectiveness of tablet-based simulation training for instrument recognition by perioperative nurses. Our results demonstrate that instrument knowledge acquired through tablet-based simulation training results in improved identification and retained recognition of real instruments.

The brain vital signs framework is a portable, objective, neurophysiological evaluation of brain function at point-of-care. We investigated brain vital signs at pre- and post-season for age 14 or under (Bantam) and age 16–20 (Junior-A) male ice hockey players to (i) further investigate previously published brain vital sign results showing subconcussive cognitive deficits and (ii) validate these findings through comparison with head-impact data obtained from instrumented accelerometers. With a longitudinal study design, 23 male ice hockey players in Bantam (n = 13; age 13.63 ± 0.62) and Tier II Junior-A (n = 10; age 18.62 ± 0.86) divisions were assessed at pre- and post-season. None were diagnosed with a concussion during the season. Cognitive evoked potential measures of Auditory sensation (N100), Basic attention (P300) and Cognitive processing (N400) were analysed as changes in peak amplitudes and latencies (six standard scores total). A regression analysis examined the relationship between brain vital signs and the number of head impacts received during the study season. Significant pre/post differences in brain vital signs were detected for both groups. Bantam and Junior-A players also differed in number of head impacts (Bantam: 32.92 ± 17.68; Junior-A: 195.00 ± 61.08; P, The brain vital signs framework is a portable, neurophysiological evaluation of brain function. Fickling et al. observed a strong, significant linear relationship between changes in brain vital signs and the total number of subconcussive head impacts sustained over the course of a playing season in male ice hockey players., Graphical Abstract Graphical Abstract

Blink-related oscillations (BROs) are a recently discovered neurophysiological response associated with spontaneous blinking, distinct from the well-known oculomotor and visual suppression effects. BROs strongly activate the bilateral precuneus along with other cortical regions involved in visuospatial processing and associative episodic memory, and are believed to represent environmental monitoring processes that occur following blink-induced visual interruptions. Although these responses have been reported across multiple imaging modalities under both resting and cognitive loading conditions, it is yet unknown whether these responses also exist under external sensory stimulation conditions. To address this, we investigated BRO responses in healthy adults using 64-channel electroencephalography (EEG), while participants underwent passive external auditory and visual stimulation. Our results showed that BRO responses are present under both auditory and visual stimulation conditions (p ​

Cognitive decline with aging and dementia is especially poignant with regard to the executive functioning that is necessary for activities of daily independent living. The relationship between age‐related neurodegeneration in the prefrontal cortex and executive functioning has been uniquely investigated using task‐phase functional magnetic resonance imaging (fMRI) to detect brain activity in response to stimuli; however, a comprehensive list of task designs that have been implemented to task‐phase fMRI is absent in the literature. The purpose of this review was to recognize what methods have been used to study executive functions with aging and dementia in fMRI tasks, and to describe and categorize them. The following cognitive subdomains were emphasized: cognitive flexibility, planning and decision‐making, working memory, cognitive control/inhibition, semantic processing, attention and concentration, emotional functioning, and multitasking. Over 30 different task‐phase fMRI designs were found to have been implemented in the literature, all adopted from standard neuropsychological assessments. Cognitive set‐shifting and decision‐making tasks were particularly well studied in regard to age‐related neurodegeneration, while emotional functioning and multitasking designs were found to be the least utilized. Summarizing the information on which tasks have shown the greatest usability will assist in the future design and implementation of effective fMRI experiments targeting executive functioning.

There have been many attempts to assess the elements of age‐ and dementia‐ related neurodegenerative changes in the brain using MRI; however, traditionally assessments focus only on single deficit. Over the past few years, our group has worked to create and validate the Brain Atrophy and Lesion Index (BALI) as an MRI‐based whole‐brain structural degeneration rating scale. The BALI can be used for applications in aging and dementia across the entire brain and can be applied to common clinical MR images. As a whole‐brain structural health assessment, the BALI gives a more representative picture of how the brain ages. During the aging process, multiple elements of degeneration accumulate and interact to overwhelm repair processes and cause high‐level failure in the function of the brain. To reflect this process, the BALI combines the assessment of several neurodegeneration changes into one scale. The BALI evaluation can be performed quickly and has been validated for use by non‐neuroradiology expert raters trained with the method. This review gives a brief overview of the content of the BALI; covers the development, refinement, and application of the method; and provides insights about future development and clinical implementation of MRI‐based whole‐brain health assessment in aging and dementia.

Detection of functional magnetic resonance imaging (fMRI) activation in white matter has been increasingly reported despite historically being controversial. Much of the development work to-date has used high-field 4 T MRI and specialized pulse sequences. In the current study, we utilized conventional 3 T MRI and a commonly applied gradient-echo-planar imaging sequence to evaluate white matter (WM) fMRI sensitivity within a common framework. Functional WM activity was replicated in target regions of interest within the corpus callosum, at the group and individual levels. As expected there was a reduction in overall WM activation sensitivity. Individual analyses revealed that 8 of the 13 individuals showed white matter activation, showing a lower percentage of individuals with WM activation detected. Importantly, WM activation results were sensitive to analyses that applied alternate hemodynamic response functions, with an increase in the group level cluster when hemodynamic response function (HRF) onset slope was reduced. The findings supported the growing evidence that WM activation is detectable, with activation levels are closer to thresholds used for routine 3T MRI studies. Optimization factors, such as the HRF model, appear to be important to further enhance the characterization of WM activity in fMRI.

Tao Gu,1,2 Lei Lin,3 Yun Jiang,4 Juan Chen,1 Ryan CN D’Arcy,2,5,6 Min Chen,1 Xiaowei Song2,5,6 1Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China; 2Simon Fraser University ImageTech Laboratory, Surrey Memorial Hospital, Surrey, BC, Canada; 3Department of Acupuncture and Moxibustion, Beijing Hospital, National Centre of Gerontology, Beijing, China; 4Department of Neurology, Beijing Hospital, NationalCentre of Gerontology, Beijing, China; 5Department of AppliedSciences and Computing Science, Simon Fraser University, Burnaby, BC, Canada; 6Health Sciences and Innovation, Surrey Memorial Hospital, Fraser Health Authority, Surrey, BC, Canada Background: Acupuncture has been proven to be effective as an alternative therapy in treating migraine, but the pathophysiological mechanisms of the treatment remain unclear. This study investigated possible neurochemical responses to acupuncture treatment. Patients and methods: Proton magnetic resonance spectroscopy imaging was used to investigate biochemical levels pre- and post-acupuncture treatment. Participants (N=45) included subjects diagnosed with: 1) migraine without aura; 2) cervicogenic headache; and 3) healthy controls. Participants in the two patient groups received verum acupuncture using acupoints that target migraine without aura but not cervicogenic headache, while the healthy controls received a sham treatment. All participants had magnetic resonance spectroscopy scans before and after the acupuncture therapy. Levels of brain metabolites were examined in relation to clinical headache assessment scores. Results: A significant increase in N-acetylaspartate/creatine was observed in bilateral thalamus in migraine without aura after the acupuncture treatment, which was significantly correlated with the headache intensity score. Conclusion: The data demonstrate brain biochemical changes underlying the effect of acupuncture treatment of migraine. Keywords: acupuncture, metabolites, migraine, magnetic resonance spectroscopy imaging, brain, pain transmission pathways

Alzheimer's disease (AD) is the most common cause of late‐life dementia. Characterized by progressive neurodegeneration, the disease is expressed as gradual memory loss together with decline in cognitive abilities and other brain functions. Despite extensive research over the past decade, the cause and cure of AD both remain largely unknown. Several AD‐associated deficits have been targeted for interventions, including those based on amyloid‐beta, tau, and inflammation hypotheses. Only 2 types of medications—cholinesterase inhibitors and memantine—have been approved, to control the cognitive symptoms of AD such as the loss of memory, language, and executive function. Noninvasive in vivo functional magnetic resonance imaging (MRI) technologies, including the blood oxygen level‐dependent functional MRI, arterial spin labeling‐based perfusion MRI, and the proton magnetic resonance spectroscopy have been used to study the effect of ChEIs and memantine in the brain. Most of these studies have demonstrated increased functional activation and connectivity, increased regional brain blood flow and volume post‐treatment, and positive responses of critical brain metabolites reflecting neuronal status and functionality in patients with AD and mild cognitive impairment. The findings have contributed to the understanding of the mechanisms underlying the medication treatments and support the crucial role of functional MRI technologies in the development and refinement of AD medication therapies.

Hui Guo,1,2 William Siu,1,3 Ryan CN D’Arcy,1,4 Sandra E Black,5,6 Lukas A Grajauskas,1,4 Sonia Singh,7,8 Yunting Zhang,2 Kenneth Rockwood,9,10 Xiaowei Song1,4,9 On behalf of The Alzheimer’s Disease Neuroimaging Initiative and the National Alzheimer’s Coordinating Center 1Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada; 2Department of Diagnostic Imaging, Tianjin Medical University General Hospital, Tianjin, China; 3Department of Medical Imaging, Fraser Health Authority, Surrey, 4Departments of Applied Sciences and Computing Science, Simon Fraser University, Burnaby, BC, 5Department of Medicine (Neurology), 6LC Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre& University of Toronto, Toronto, ON, 7Department of Family Medicine, University of British Columbia, Vancouver, BC, 8Department of Research and Evaluation, Fraser Health, Surrey, BC, 9Department of Medicine (Geriatric Medicine), Dalhousie University, 10Centre for Healthcare of the Elderly, Nova Scotia Health Authority, Halifax, NS, Canada Purpose: One of the central features of brain aging is the accumulation of multiple age-related structural changes, which occur heterogeneously in individuals and can have immediate or potential clinical consequences. Each of these deficits can coexist and interact, producing both independent and additive impacts on brain health. Many of the changes can be visualized using MRI. To collectively assess whole-brain structural changes, the MRI-based Brain Atrophy and Lesion Index (BALI) has been developed. In this study, we validate this whole-brain health assessment approach using several clinical MRI examinations.Materials and methods: Data came from three independent studies: the Alzheimer’s Disease Neuroimaging Initiative Phase II (n=950; women =47.9%; age =72.7±7.4 years); the National Alzheimer’s Coordinating Center (n=722; women =55.1%; age =72.7±9.9 years); and the Tianjin Medical University General Hospital Research database on older adults (n=170; women =60.0%; age =62.9±9.3 years). The 3.0-Tesla MRI scans were evaluated using the BALI rating scheme on the basis of T1-weighted (T1WI), T2-weighted (T2WI), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and T2*-weighted gradient-recalled echo (T2*GRE) images.Results: Atrophy and lesion changes were commonly seen in each MRI test. The BALI scores based on different sequences were highly correlated (Spearman r2>0.69; P0.29; P26.48, P

Translating EEG technology into real world applications is limited by a variety of challenges, one of which is signal noise from portable, low-density EEG devices operating in uncontrolled environments. We have developed an automated general-purpose framework, the EEG Quality Index, for the objective assessment of EEG signal quality. This framework currently uses 6 metrics that are shown to be highly sensitive to various typical artifacts. Normalized scores for each metric can be used in a framework to provide indications of the overall quality of the recorded EEG signal. Using simulated clean and artifact-contaminated EEG in a Support Vector Machine classifier, the EEG Quality Index metrics can identify artifact-contaminated EEG with 90.75% accuracy, 97.7% sensitivity, and 83.8% specificity. This is the first demonstration of a general-purpose framework for the automated and objective assessment of the quality of EEG data. With portable, low-density EEG systems being increasingly adopted in real-world clinical applications, this type of quality assessment is important.

Background Despite growing evidence of a critical link between neuromodulation technologies and neuroplastic recovery, the underlying mechanisms of these technologies remain elusive. Objective To investigate physiological evidence of central nervous system (CNS) changes in humans during translingual neurostimulation (TLNS). Methods We used high-density electroencephalography (EEG) to measure changes in resting brain activity before, during, and after high frequency (HF) and low frequency (LF) TLNS. Results Wavelet power analysis around Cz and microstate analysis revealed significant changes after 20 min of stimulation compared to baseline. A secondary effect of exposure order was also identified, indicating a differential neuromodulatory influence of HF TLNS relative to LF TLNS on alpha and theta signal power. Conclusions These results further our understanding of the effects of TLNS on underlying resting brain activity, which in the long-term may contribute to the critical link between clinical effect and changes in brain activity.

OBJECTIVE Motor function of chronic stroke survivors is generally accessed using clinical motor assessments. These motor assessments are partially subjective and require prior training for the examiners. Additionally, those motor function assessments require the health professionals to be present in person. The method proposed in this paper has the potential to radically change the way motor function is assessed. APPROACH This work investigates the feasibility of automatically scoring upper-extremity motor function from EEG using artificial neural networks. Twelve healthy participants and fourteen participants with chronic stroke participated in this study. EEG data were recorded while the participants were clicking a button. Convolutional neural network models were trained based on the participants' Fugl Meyer motor assessment score. MAIN RESULTS The result showed that the proposed method achieved high prediction accuracy both within (n = 14, r = 0.9921, p = 3.3907 × 10-12) and cross (n = 14, r = 0.9867, p = 7.9342 × 10-11) participant testing. SIGNIFICANCE This evidence suggests the proposed method is feasible to be used as a stable and objective measurement for motor function assessment.

Objectives The Ice Hockey Summit III provided updated scientific evidence on concussions in hockey to inform these five objectives: (1) describe sport related concussion (SRC) epidemiology, (2) classify prevention strategies, (3) define objective, diagnostic tests, (4) identify treatment and (5) integrate science and clinical care into prioritized action plans and policy. Methods Our action plan evolved from 40 scientific presentations. The 155 attendees (physicians, athletic trainers, physical therapists, nurses, neuropsychologists, scientists, engineers, coaches and officials) voted to prioritize these action items in the final Summit session. Results (1) establish a national and international hockey data base for SRCs at all levels; (2) eliminate body checking in Bantam youth hockey games; (3) expand a behavior modification program (Fair Play) to all youth hockey levels; (4) enforce game ejection penalties for fighting in Junior A and professional hockey leagues; (5) establish objective tests to diagnose concussion at point of care (POC); and (6) mandate baseline testing to improve concussion diagnosis for all age groups. Conclusions Expedient implementation of the Summit III prioritized action items is necessary to reduce the risk, severity and consequences of concussion in the sport of ice hockey.

Introduction Waist circumference is associated with type 2 diabetes (T2D) and cognition, yet the relationship between waist circumference and cognition in individuals with T2D is not well understood. Methods We studied the relationship of waist circumference with five cognitive outcomes (executive functioning, language/semantic categorization, attention/working memory, episodic memory, and an overall cognition measure) in 845 cognitively normal elderly with type 2 diabetes (T2D). Results In women, waist circumference was correlated with significantly lower language and/or semantic categorization performance ( P P = .026), and overall cognition ( P = .003) after controlling for age, education, BMI, and cardiovascular, diabetes-related, APOE e4, and inflammatory potential confounders. Attention/working memory ( P = .532) and episodic memory ( P = .144) were not associated with waist circumference. These correlations were not found in men. Discussion These results suggest that central adiposity in elderly women with T2D may increase their risk for dementia.

Survivors of severe brain injury may remain in a decreased state of conscious awareness for an extended period of time. Clinical scales are used to describe levels of consciousness but rely on behavioural responses, precipitating misdiagnosis. We have previously utilized event-related potentials (ERPs) to circumvent reliance on behavioural responses. However, practical implementation barriers limit the clinical utility of ERP assessment at point-of-care (POC). To address this challenge, we developed the Halifax Consciousness Scanner (HCS)—a rapid, semi-automated electroencephalography system. The current study evaluated: (i) HCS feasibility in sub-acute, POC settings nationwide; (ii) ERP P300 responses in patients with acquired brain injury versus healthy controls; and (iii) correlations within and between clinical measures and P300 latencies. We assessed 28 patients with severe, chronic impairments from brain injuries and contrasted the results with healthy control data (n = 100). Correlational analyses examined relationships between P300 latencies and the commonly used clinical scales. P300 latencies were significantly delayed in patients compared to healthy controls (P

Blink-related oscillations (BROs) have been linked with environmental monitoring processes associated with blinking, with cortical activations in the bilateral precuneus. Although BROs have been described under resting and passive fixation conditions, little is known about their characteristics under cognitive loading. To address this, we investigated BRO effects during both mental arithmetic (MA) and passive fixation (PF) tasks using magnetoencephalography (n =20), while maintaining the same sensory environment in both tasks. Our results confirmed the presence of BRO effects in both MA and PF tasks, with similar characteristics including blink-related increase in global field power and blink-related activation of the bilateral precuneus. In addition, cognitive loading due to MA also modulated BRO effects by decreasing BRO-induced cortical activations in key brain regions including the bilateral anterior precuneus. Interestingly, blinking during MA-but not PF-activated regions of the ventral attention network (i.e., right supramarginal gyrus and inferior frontal gyrus), suggesting possible recruitment of these areas for blink processing under cognitive loading conditions. Time-frequency analysis revealed a consistent pattern of BRO-related effects in the precuneus in both tasks, but with task-related functional segregation within the anterior and posterior subregions. Based on these findings, we postulate a potential neurocognitive mechanism for blink processing in the precuneus. This study is the first investigation of BRO effects under cognitive loading, and our results provide compelling new evidence for the important cognitive implications of blink-related processing in the human brain.

Background For nearly four decades, the N400 has been an important brainwave marker of semantic processing. It can be recorded non-invasively from the scalp using electrical and/or magnetic sensors, but largely within the restricted domain of research laboratories specialized to run specific N400 experiments. However, there is increasing evidence of significant clinical utility for the N400 in neurological evaluation, particularly at the individual level. To enable clinical applications, we recently reported a rapid evaluation framework known as “brain vital signs” that successfully incorporated the N400 response as one of the core components for cognitive function evaluation. The current study characterized the rapidly evoked N400 response to demonstrate that it shares consistent features with traditional N400 responses acquired in research laboratory settings—thereby enabling its translation into brain vital signs applications. Methods Data were collected from 17 healthy individuals using magnetoencephalography (MEG) and electroencephalography (EEG), with analysis of sensor-level effects as well as evaluation of brain sources. Individual-level N400 responses were classified using machine learning to determine the percentage of participants in whom the response was successfully detected. Results The N400 response was observed in both M/EEG modalities showing significant differences to incongruent versus congruent condition in the expected time range (p

Advances in MRI technology have significantly contributed to our ability to understand the process of brain ageing, allowing us to track and assess changes that occur during normal ageing and neurological conditions. This paper focuses on reviewing structural changes of the ageing brain that are commonly seen using MRI, summarizing the pathophysiology, prevalence, and neuroanatomical distribution of changes including atrophy, lacunes, white matter lesions, and dilated perivascular spaces. We also review the clinically accessible methodology for assessing these MRI-based changes, covering visual rating scales, as well computer-aided and fully automated methods. Subsequently, we consider novel assessment methods designed to evaluate changes across the whole brain, and finally discuss new directions in this field of research.

There is growing demand for tools to objectively evaluate concussion. Fickling et al. develop a portable, easy-to-use, evoked potential framework to extract ‘brain vital signs’ at point-of-care using electroencephalography. Monitoring of brain vital signs reveals persistent neurophysiological changes in athletes cleared for return-to-play with current concussion management protocols., There is a growing demand for objective evaluations of concussion. We developed a portable evoked potential framework to extract ‘brain vital signs’ using electroencephalography. Brain vital signs were derived from well established evoked responses representing auditory sensation (N100), basic attention (P300), and cognitive processing (N400) amplitudes and latencies, converted to normative metrics (six total). The study evaluated whether concussion-related neurophysiological impairments were detected over the duration of ice hockey seasons using brain vital signs. Forty-seven Tier III, Junior A, male ice hockey players were monitored over two seasons. Twelve sustained concussions after baseline testing then completed post-injury and return-to-play assessments. Twenty-three were not diagnosed with a concussion during the season and completed both baseline and post-season testing. Scores were evaluated using a repeated-measures analysis of variance with post hoc two-tailed paired t-tests. Concussion resulted in significantly increased amplitude and delayed latency scores for all six brain vital signs (P < 0.0001). Importantly, significant changes at return-to-play were also detected in basic attention (P300) amplitude, indicating persistent subclinical impairment. In the non-concussed group, there was also a significant change between baseline and post-season (P = 0.0047), with specific decreases in cognitive processing (N400) speed (P = 0.011) and overall total score (P = 0.002).

Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) are neuroimaging techniques that measure inherently different physiological processes, resulting in complementary estimates of brain activity in different regions. Combining the maps generated by each technique could thus provide a richer understanding of brain activation. However, present approaches to integration rely on a priori assumptions, such as expected patterns of brain activation in a task, or use fMRI to bias localization of MEG sources, diminishing fMRI-invisible sources. We aimed to optimize sensitivity to neural activity by developing a novel method of integrating data from the two imaging techniques. We present a data-driven method of integration that weights fMRI and MEG imaging data by estimates of data quality for each technique and region. This method was applied to a verbal object recognition task. As predicted, the two imaging techniques demonstrated sensitivity to activation in different regions. Activity was seen using fMRI, but not MEG, throughout the medial temporal lobes. Conversely, activation was seen using MEG, but not fMRI, in more lateral and anterior temporal lobe regions. Both imaging techniques were sensitive to activation in the inferior frontal gyrus. Importantly, integration maps retained activation from individual activation maps, and showed an increase in the extent of activation, owing to greater sensitivity of the integration map than either fMRI or MEG alone.

Background Event-related potentials (ERPs) may provide a non-invasive index of brain function for a range of clinical applications. However, as a lab-based technique, ERPs are limited by technical challenges that prevent full integration into clinical settings. New method To translate ERP capabilities from the lab to clinical applications, we have developed methods like the Halifax Consciousness Scanner (HCS). HCS is essentially a rapid, automated ERP evaluation of brain functional status. The present study describes the ERP components evoked from auditory tones and speech stimuli. ERP results were obtained using a 5-min test in 100 healthy individuals. The HCS sequence was designed to evoke the N100, the mismatch negativity (MMN), P300, the early negative enhancement (ENE), and the N400. These components reflected sensation, perception, attention, memory, and language perception, respectively. Component detection was examined at group and individual levels, and evaluated across both statistical and classification approaches. Results All ERP components were robustly detected at the group level. At the individual level, nonparametric statistical analyses showed reduced accuracy relative to support vector (SVM) machine classification, particularly for speech-based ERPs. Optimized SVM results were MMN: 95.6%; P300: 99.0%; ENE: 91.8%; and N400: 92.3%. Conclusions A spectrum of individual-level ERPs can be obtained in a very short time. Machine learning classification improved detection accuracy across a large healthy control sample. Translating ERPs into clinical applications is increasingly possible at the individual level.

Spontaneous blinking occurs 15–20 times per minute. Although blinking has often been associated with its physiological role of corneal lubrication, there is now increasing behavioral evidence suggesting that blinks are also modulated by cognitive processes such as attention and information processing. Recent low-density electroencephalography (EEG) studies have reported so-called blink-related oscillations (BROs) associated with spontaneous blinking at rest. Delta-band (0.5–4 Hz) BROs are thought to originate from the precuneus region involved in environmental monitoring and awareness, with potential clinical utility in evaluation of disorders of consciousness. However, the neural mechanisms of BROs have not been elucidated. Using magnetoencephalography (MEG), we characterized delta-band BROs in 36 healthy individuals while controlling for background brain activity. Results showed that, compared to pre-blink baseline, delta-band BROs resulted in increased global field power (p < 0.001) and time-frequency spectral power (p < 0.05) at the sensor level, peaking at ~250 ms post-blink maximum. Source localization showed that spontaneous blinks activated the bilateral precuneus (p < 0.05 FWE), and source activity within the precuneus was also consistent with sensor-space results. Crucially, these effects were only observed in the blink condition and were absent in the control condition, demonstrating that results were due to spontaneous blinks rather than as part of the inherent brain activity. The current study represents the first MEG examination of BROs. Our findings suggest that spontaneous blinks activate the precuneus regions consistent with environmental monitoring and awareness, and provide important neuroimaging support for the cognitive role of spontaneous blinks.

A non-magnetic MEG compatible device has been developed that provides continuous force and velocity information. Combined with MEG, this device may find utility in characterizing brain regions associated with force and velocity relative to individual digits or movement pattern. 15 healthy right-handed participants were given visual cues to perform random finger movements on the prototype finger sensor for 21 s and then rest for 21 s (7 times). Respective finger flexion data were obtained, during 151-channel MEG brain scanning, by feeding the signal from finger sensor into four input Analog to Digital Converter (ADC) channels in the MEG hardware. The source activity was reconstructed in beta band using a Linearly Constrained Minimum Variance (LCMV) beamformer in the beta band. The ADC channels were used as regressors for a continuous time General Linear Model (GLM) and a Region of Interest (ROI) was identified to examine activity. MEG analysis showed bilateral activation in the primary motor cortex region. Because individual digits could be isolated in the ADC data, somatotopy of the fingers were observed consistent with the homunculus except pinky finger. The total span was calculated to be 5.5662 mm. The study confirms that the finger sensor is magnetically compatible with MEG measurements and may potentially provide a means to study complex sensorimotor functions. Improved isolation of individual digit information along with the use of machine learning algorithms can help retrieve more accurate results.

Event-related potentials (ERPs) are tiny electrical brain responses in the human electroencephalogram that are typically not detectable until they are isolated by a process of signal averaging. Owing to the extremely smallsize of ERP components (ranging from less than 1 μV to tens of μV), compared to background brain rhythms, statistical analyses of ERPs are predominantly carried out in groups of subjects. This limitation is a barrier to the translation of ERP-based neuroscience to applications such as medical diagnostics. We show here that support vector machines (SVMs) are a useful method to detect ERP components in individual subjects with a small set of electrodes and a small number of trials for a mismatch negativity (MMN) ERP component. Such a reduced experiment setup is important for clinical applications. One hundred healthy individuals were presented with an auditory pattern containing pattern-violating deviants to evoke the MMN. Two-class SVMs were then trained to classify averaged ERP waveforms in response to the standard tone (tones that match the pattern) and deviant tone stimuli (tones that violate the pattern). The influence of kernel type, number of epochs, electrode selection, and temporal window size in the averaged waveform were explored. When using all electrodes, averages of all available epochs, and a temporal window from 0 to 900-ms post-stimulus, a linear SVM achieved 94.5 % accuracy. Further analyses using SVMs trained with narrower, sliding temporal windows confirmed the sensitivity of the SVM to data in the latency range associated with the MMN.

Alzheimer's disease (AD) affects several important molecules in brain metabolism. The resulting neurochemical changes can be quantified non-invasively in localized brain regions using in vivo single-voxel proton magnetic resonance spectroscopy (SV 1H MRS). Although the often heralded diagnostic potential of MRS in AD largely remains unfulfilled, more recent use of high magnetic fields has led to significantly improved signal-to-noise ratios and spectral resolutions, thereby allowing clinical applications with increased measurement reliability. The present article provides a comprehensive review of SV 1H MRS studies on AD at high magnetic fields (3.0 Tesla and above). This review suggests that patterned regional differences and longitudinal alterations in several neurometabolites are associated with clinically established AD. Changes in multiple metabolites are identifiable even at early stages of AD development. By combining information of neurochemicals in different brain regions revealing either pathological or compensatory changes, high field MRS can be evaluated in AD diagnosis and in the detection of treatment effects. To achieve this, standardization of data acquisition and analytical approaches is needed.

Frailty and the decline in ability to maintain independent living may be forestalled through discussions with healthcare providers and seniors about managing health at home. In addition, the use of technology in supplementing doctors’ visits to assess frailty progression may be easily adopted by some but not others. We conducted this qualitative study to elucidate the context in which seniors access care at home and current barriers to independent living, from the perspectives of both seniors and practitioners. Pre-approved discussion questions were administered to two audio-recorded focus group sessions of 14 participants. The first group were community-dwelling older adults and informal caregivers, while the second consisted of healthcare practitioners. Group members were sampled to include a range of health backgrounds and levels of technological expertise. Thematic analysis with NVivo Software was used to parse out key discussion topics from the audio transcripts. The caregiver/patient group emphasized the stigma of frailty and age-related isolation, desiring transparency and advocacy from care teams. Practitioners/researchers discussed the importance of a holistic biopsychosocial approach to frailty management and the need for standardized frailty measurement. Patients/caregivers used health-tracking devices at home and were more optimistic about telehealth/video-conferencing than practitioners. Awareness of contextual factors surrounding “aging in place” and what aspects of care are valued by patients and practitioners is key to advancing home health and paving the way for new evidence-based services in the home.