Explore the vast range of titles available.

In 2014, the National Institutes of Health (NIH) began funding an ambitious research program, the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, with the singular focus of advancing our understanding of brain circuits though development and application of breakthrough neurotechnologies. As we approach the halfway mark of this 10-year effort aimed at revolutionizing our understanding of information processing in the human brain, it is timely to review the progress and the future trajectory of BRAIN Initiative research.

Studies supporting a strong association between tau deposition and neuronal loss, neurodegeneration, and cognitive decline have heightened the allure of tau and tau-related mechanisms as therapeutic targets. In February 2020, leading tau experts from around the world convened for the first-ever Tau2020 Global Conference in Washington, DC, co-organized and cosponsored by the Rainwater Charitable Foundation, the Alzheimer's Association, and CurePSP. Representing academia, industry, government, and the philanthropic sector, presenters and attendees discussed recent advances and current directions in tau research. The meeting provided a unique opportunity to move tau research forward by fostering global partnerships among academia, industry, and other stakeholders and by providing support for new drug discovery programs, groundbreaking research, and emerging tau researchers. The meeting also provided an opportunity for experts to present critical research-advancing tools and insights that are now rapidly accelerating the pace of tau research.

Abstract Chronic traumatic encephalopathy (CTE) is a neurodegenerative disorder associated with exposure to head trauma. In 2015, a panel of neuropathologists funded by the NINDS/NIBIB defined preliminary consensus neuropathological criteria for CTE, including the pathognomonic lesion of CTE as “an accumulation of abnormal hyperphosphorylated tau (p-tau) in neurons and astroglia distributed around small blood vessels at the depths of cortical sulci and in an irregular pattern,” based on review of 25 tauopathy cases. In 2016, the consensus panel met again to review and refine the preliminary criteria, with consideration around the minimum threshold for diagnosis and the reproducibility of a proposed pathological staging scheme. Eight neuropathologists evaluated 27 cases of tauopathies (17 CTE cases), blinded to clinical and demographic information. Generalized estimating equation analyses showed a statistically significant association between the raters and CTE diagnosis for both the blinded (OR = 72.11, 95% CI = 19.5–267.0) and unblinded rounds (OR = 256.91, 95% CI = 63.6–1558.6). Based on the challenges in assigning CTE stage, the panel proposed a working protocol including a minimum threshold for CTE diagnosis and an algorithm for the assessment of CTE severity as “Low CTE” or “High CTE” for use in future clinical, pathological, and molecular studies.

To highlight worldwide efforts to fund neuroscience research and address the growing threat of brain disorders, Nature Neuroscience asked leaders of six global brain initiatives to write about their programs.

Liping Liu and colleagues discuss the challenges of global collaboration for brain health research and promising future opportunities for improvement of brain health worldwide

The opioid crisis constitutes a public health challenge at the intersection of two interrelated medical problems — opioid addiction and chronic pain. Overlap of the reward and pain circuits in the brain underlies the frequent comorbidity of chronic pain and opioid addiction, whereas inadequate support, treatment and health-care reimbursement for both of these conditions are major contributors underlying the magnitude of the problem. Neurologists are uniquely positioned to help address the opioid crisis, not only through their involvement in the management of chronic pain conditions but also because they can screen for and manage opioid use disorders. The new NIH Helping to End Addiction Long-term (HEAL) Initiative will support research into pain and opioid use disorders to help address the opioid crisis. Neurologists’ involvement in basic, translational and clinical research is needed for the development of new pain therapeutics and biomarkers and interventions to prevent chronic pain and to prevent and treat opioid addiction.The opioid crisis constitutes a public health challenge at the intersection of two interrelated medical problems — opioid addiction and chronic pain. In this Perspectives article, Volkow and Koroschetz discuss how neurologists are uniquely positioned to help address the opioid crisis.

The World Health Organization reports that 47.5 million people are affected by dementia worldwide. With aging populations and 7.7 million new cases each year, the burden of illness due to dementia approaches crisis proportions. Despite significant advances in our understanding of the biology of Alzheimer’s disease (AD), the leading dementia diagnosis, the actual causes of dementia in affected individuals are unknown except for rare fully penetrant genetic forms. Evidence from epidemiology and pathology studies indicates that damage to the vascular system is associated with an increased risk of many types of dementia. Both Alzheimer’s pathology and cerebrovascular disease increase with age. How AD affects small blood vessel function and how vascular dysfunction contributes to the molecular pathology of Alzheimer’s are areas of intense research. The science of vascular contributions to cognitive impairment and dementia (VCID) integrates diverse aspects of biology and incorporates the roles of multiple cell types that support the function of neural tissue. Because of the proven ability to prevent and treat cardiovascular disease and hypertension with population benefits for heart and stroke outcomes, it is proposed that understanding and targeting the biological mechanisms of VCID can have a similarly positive impact on public health.

The All of Us Research Program has prioritized the enrollment of people from backgrounds that are historically under-represented in medical research to bring precision medicine to the full diversity of the US population and to improve health outcomes for all.

Simply lowering blood pressure would reduce the risk of both stroke and age-related cognitive impairment, says Walter J. Koroshetz.

Background Accessible tools to efficiently detect and segment diffusion abnormalities in acute strokes are highly anticipated by the clinical and research communities. Methods We developed a tool with deep learning networks trained and tested on a large dataset of 2,348 clinical diffusion weighted MRIs of patients with acute and sub-acute ischemic strokes, and further tested for generalization on 280 MRIs of an external dataset (STIR). Results Our proposed model outperforms generic networks and DeepMedic, particularly in small lesions, with lower false positive rate, balanced precision and sensitivity, and robustness to data perturbs (e.g., artefacts, low resolution, technical heterogeneity). The agreement with human delineation rivals the inter-evaluator agreement; the automated lesion quantification of volume and contrast has virtually total agreement with human quantification. Conclusion Our tool is fast, public, accessible to non-experts, with minimal computational requirements, to detect and segment lesions via a single command line. Therefore, it fulfills the conditions to perform large scale, reliable and reproducible clinical and translational research. Plain language summary Determining the volume and location of lesions caused by acute ischemic strokes - in which blood flow is restricted to part of the brain - is crucial to guide treatment and patient prognosis. However, this process is time-consuming and labor-intensive for clinicians. Here, using brain imaging datasets from patients with ischemic strokes, we create an artificial intelligence-based tool to quickly and accurately determine the volume and location of stroke lesions. Our tool outperforms some similar existing approaches, it is fast, publicly available, accessible to non-experts, and it runs on normal computers with minimal computational requirements. As such, it may be useful both for clinicians treating patients and researchers studying ischemic stroke. Liu et al. develop a deep learning-based tool to detect and segment diffusion abnormalities seen on magnetic resonance imaging (MRI) in acute ischemic stroke. The tool is tested in two clinical MRI datasets and outperforms existing algorithms in the detection of small lesions, potentially allowing clinicians and clinical researchers to more quickly and accurately diagnose and assess ischemic strokes.