Explore the vast range of titles available.

Subarachnoid haemorrhage is an uncommon and severe subtype of stroke affecting patients at a mean age of 55 years, leading to loss of many years of productive life. The rupture of an intracranial aneurysm is the underlining cause in 85% of cases. Survival from aneurysmal subarachnoid haemorrhage has increased by 17% in the past few decades, probably because of better diagnosis, early aneurysm repair, prescription of nimodipine, and advanced intensive care support. Nevertheless, survivors commonly have cognitive impairments, which in turn affect patients' daily functionality, working capacity, and quality of life. Additionally, those deficits are frequently accompanied by mood disorders, fatigue, and sleep disturbances. Management requires specialised neurological intensive care units and multidisciplinary clinical expertise, which is better provided in high-volume centres. Many clinical trials have been done, but only two interventions are shown to improve outcome. Challenges that remain relate to prevention of subarachnoid haemorrhage by improved screening and development of lower-risk methods to repair or stabilise aneurysms that have not yet ruptured. Multicentre cooperative efforts might increase the knowledge that can be gained from clinical trials, which is often limited by small studies with differing criteria and endpoints that are done in single centres. Outcome assessments that incorporate finer assessment of neurocognitive function and validated surrogate imaging or biomarkers for outcome could also help to advance the specialty.

Resting state functional magnetic resonance imaging (rs-fMRI) has become an indispensable tool in neuroscience research. Despite this, rs-fMRI signals are easily contaminated by artifacts arising from movement of the head during data collection. The artifacts can be problematic even for motions on the millimeter scale, with complex spatiotemporal properties that can lead to substantial errors in functional connectivity estimates. Effective correction methods must be employed, therefore, to distinguish true functional networks from motion-related noise. Research over the last three decades has produced numerous correction methods, many of which must be applied in combination to achieve satisfactory data quality. Subject instruction, training, and mild restraints are helpful at the outset, but usually insufficient. Improvements come from applying multiple motion correction algorithms retrospectively after rs-fMRI data are collected, although residual artifacts can still remain in cases of elevated motion, which are especially prevalent in patient populations. Although not commonly adopted at present, \"real-time\" correction methods are emerging that can be combined with retrospective methods and that promise better correction and increased rs-fMRI signal sensitivity. While the search for the ideal motion correction protocol continues, rs-fMRI research will benefit from good disclosure practices, such as: (1) reporting motion-related quality control metrics to provide better comparison between studies; and (2) including motion covariates in group-level analyses to limit the extent of motion-related confounds when studying group differences.

Music interventions have been widely adopted as a potential non-pharmacological therapy for patients with Alzheimer's disease (AD) to treat cognitive and/or behavioral symptoms of the disease. In spite of the prevalence of such therapies, evidence for their effectiveness report mixed results in the literature. The purpose of this narrative review is to investigate the effectiveness of various intervention strategies (music therapy vs. music listening techniques) and music type used in the intervention (individualized vs. non-individualized music) on cognitive and behavioral outcomes for persons with AD. Databases were searched for studies using either active music therapy or music listening techniques over the last 10 years. These studies were in English, included persons with AD dementia, and whose protocol gathered pre- and post-intervention outcome measures. We initially identified 206 papers which were then reduced to 167 after removing duplicates. Further review yielded 13 papers which were extensively reviewed, resulting in a final sample of six papers. Our analysis of these papers suggested that, regardless of the music intervention approach, individualized music regimens provided the best outcomes for the patient. Furthermore, music listening may act as a relaxation technique and therefore provide a long-term impact for the patient, while active music therapy may acts to engage participants through social interaction and provide acute benefits. Our findings suggest that music techniques can be utilized in various ways to improve behavior and cognition.

The trail-making test (TMT) is a popular neuropsychological test, which is used extensively to measure cognitive impairment associated with neurodegenerative disorders in older adults. Behavioural performance on the TMT has been investigated in older populations, but there is limited research on task-related brain activity in older adults. The current study administered a naturalistic version of the TMT to a healthy older-aged population in an MRI environment using a novel, MRI-compatible tablet. Functional MRI was conducted during task completion, allowing characterization of the brain activity associated with the TMT. Performance on the TMT was evaluated using number of errors and seconds per completion of each link. Results are reported for 36 cognitively healthy older adults between the ages of 52 and 85. Task-related activation was observed in extensive regions of the bilateral frontal, parietal, temporal and occipital lobes as well as key motor areas. Increased age was associated with reduced brain activity and worse task performance. Specifically, older age was correlated with decreased task-related activity in the bilateral occipital, temporal and parietal lobes. These results suggest that healthy older aging significantly affects brain function during the TMT, which consequently may result in performance decrements. The current study reveals the brain activation patterns underlying TMT performance in a healthy older aging population, which functions as an important, clinically-relevant control to compare to pathological aging in future investigations.

Driving motor vehicles is a complex task that depends heavily on how visual stimuli are received and subsequently processed by the brain. The potential impact of distraction on driving performance is well known and poses a safety concern - especially for individuals with cognitive impairments who may be clinically unfit to drive. The present study is the first to combine functional magnetic resonance imaging (fMRI) and eye-tracking during simulated driving with distraction, providing oculomotor metrics to enhance scientific understanding of the brain activity that supports driving performance. As initial work, twelve healthy young, right-handed participants performed turns ranging in complexity, including simple right and left turns without oncoming traffic, and left turns with oncoming traffic. Distraction was introduced as an auditory task during straight driving, and during left turns with oncoming traffic. Eye-tracking data were recorded during fMRI to characterize fixations, saccades, pupil diameter and blink rate. Brain activation maps for right turns, left turns without oncoming traffic, left turns with oncoming traffic, and the distraction conditions were largely consistent with previous literature reporting the neural correlates of simulated driving. When the effects of distraction were evaluated for left turns with oncoming traffic, increased activation was observed in areas involved in executive function (e.g., middle and inferior frontal gyri) as well as decreased activation in the posterior brain (e.g., middle and superior occipital gyri). Whereas driving performance remained mostly unchanged (e.g., turn speed, time to turn, collisions), the oculomotor measures showed that distraction resulted in more consistent gaze at oncoming traffic in a small area of the visual scene; less time spent gazing at off-road targets (e.g., speedometer, rear-view mirror); more time spent performing saccadic eye movements; and decreased blink rate. Oculomotor behavior modulated with driving task complexity and distraction in a manner consistent with the brain activation features revealed by fMRI. The results suggest that eye-tracking technology should be included in future fMRI studies of simulated driving behavior in targeted populations, such as the elderly and individuals with cognitive complaints - ultimately toward developing better technology to assess and enhance fitness to drive.

Objectives: Guidelines on return-to-driving after traumatic brain injury (TBI) are scarce. Since driving requires the coordination of multiple cognitive, perceptual, and psychomotor functions, neuropsychological testing may offer an estimate of driving ability. To examine this, a meta-analysis of the relationship between neuropsychological testing and driving ability after TBI was performed. Methods: Hedge’s g and 95% confidence intervals were calculated using a random effects model. Analyses were performed on cognitive domains and individual tests. Meta-regressions examined the influence of study design, demographic, and clinical factors on effect sizes. Results: Eleven studies were included in the meta-analysis. Executive functions had the largest effect size (g = 0.60 [0.39–0.80]), followed by verbal memory (g = 0.49 [0.27–0.71]), processing speed/attention (g = 0.48 [0.29–0.67]), and visual memory (g = 0.43 [0.14–0.71]). Of the individual tests, Useful Field of Vision (UFOV) divided attention (g = 1.12 [0.52–1.72]), Trail Making Test B (g = 0.75 [0.42–1.08]), and UFOV selective attention (g = 0.67 [0.22–1.12]) had the largest effects. The effect sizes for Choice Reaction Time test and Trail Making Test A were g = 0.63 (0.09–1.16) and g = 0.58 (0.10–1.06), respectively. Years post injury (β = 0.11 [0.02–0.21] and age (β = 0.05 [0.009–0.09]) emerged as significant predictors of effect sizes (both p < .05). Conclusions: These results provide preliminary evidence of associations between neuropsychological test performance and driving ability after moderate to severe TBI and highlight moderating effects of demographic and clinical factors.

Neuroimaging has been used to describe the pathophysiology of sport-related concussion during early injury, with effects that may persist beyond medical clearance to return-to-play (RTP). However, studies are typically cross-sectional, comparing groups of concussed and uninjured athletes. It is important to determine whether these findings are consistent with longitudinal change at the individual level, relative to their own pre-injury baseline. A cohort of N = 123 university-level athletes were scanned with magnetic resonance imaging (MRI). Of this group, N = 12 acquired a concussion and were re-scanned at early symptomatic injury and at RTP. A sub-group of N = 44 uninjured athletes were also re-imaged, providing a normative reference group. Among concussed athletes, abnormalities were identified for white matter fractional anisotropy and mean diffusivity, along with grey matter cerebral blood flow, using both cross-sectional (CS) and longitudinal (LNG) approaches. The spatial patterns of abnormality for CS and LNG were distinct, with median fractional overlap below 0.10 and significant differences in the percentage of abnormal voxels. However, the analysis methods did not differ in the amount of change from symptomatic injury to RTP and in the direction of observed abnormalities. These results highlight the impact of using pre-injury baseline data when evaluating concussion-related brain abnormalities at the individual level.

Non-invasive measurements of brain activity have an important role to play in understanding driving ability. The current study aimed to identify the neural underpinnings of human driving behavior by visualizing the areas of the brain involved in driving under different levels of demand, such as driving while distracted or making left turns at busy intersections. To capture brain activity during driving, we placed a driving simulator with a fully functional steering wheel and pedals in a 3.0 Tesla functional magnetic resonance imaging (fMRI) system. To identify the brain areas involved while performing different real-world driving maneuvers, participants completed tasks ranging from simple (right turns) to more complex (left turns at busy intersections). To assess the effects of driving while distracted, participants were asked to perform an auditory task while driving analogous to speaking on a hands-free device and driving. A widely distributed brain network was identified, especially when making left turns at busy intersections compared to more simple driving tasks. During distracted driving, brain activation shifted dramatically from the posterior, visual and spatial areas to the prefrontal cortex. Our findings suggest that the distracted brain sacrificed areas in the posterior brain important for visual attention and alertness to recruit enough brain resources to perform a secondary, cognitive task. The present findings offer important new insights into the scientific understanding of the neuro-cognitive mechanisms of driving behavior and lay down an important foundation for future clinical research.

Functional magnetic resonance imaging (fMRI) continues to develop as a clinical tool for patients with brain cancer, offering data that may directly influence surgical decisions. Unfortunately, routine integration of preoperative fMRI has been limited by concerns about reliability. Many pertinent studies have been undertaken involving healthy controls, but work involving brain tumor patients has been limited. To develop fMRI fully as a clinical tool, it will be critical to examine these reliability issues among patients with brain tumors. The present work is the first to extensively characterize differences in activation map quality between brain tumor patients and healthy controls, including the effects of tumor grade and the chosen behavioral testing paradigm on reliability outcomes. Test-retest data were collected for a group of low-grade (n = 6) and high-grade glioma (n = 6) patients, and for matched healthy controls (n = 12), who performed motor and language tasks during a single fMRI session. Reliability was characterized by the spatial overlap and displacement of brain activity clusters, BOLD signal stability, and the laterality index. Significance testing was performed to assess differences in reliability between the patients and controls, and low-grade and high-grade patients; as well as between different fMRI testing paradigms. There were few significant differences in fMRI reliability measures between patients and controls. Reliability was significantly lower when comparing high-grade tumor patients to controls, or to low-grade tumor patients. The motor task produced more reliable activation patterns than the language tasks, as did the rhyming task in comparison to the phonemic fluency task. In low-grade glioma patients, fMRI data are as reliable as healthy control subjects. For high-grade glioma patients, further investigation is required to determine the underlying causes of reduced reliability. To maximize reliability outcomes, testing paradigms should be carefully selected to generate robust activation patterns.

Concussion is associated with disrupted cerebral blood flow (CBF), although there appears to be substantial inter-individual variability in CBF response. At present, the mechanisms of variable CBF response remain incompletely understood, but one potential contributor is matrix metalloproteinase (MMP) expression. In more severe forms of acquired brain injury, MMP up-regulation contributes to CBF impairments via increased blood-brain barrier permeability. A similar relationship is hypothesized for concussion, where recently concussed individuals with higher MMP levels have lower CBF. To test this hypothesis, 35 concussed athletes were assessed longitudinally at early symptomatic injury (median: 5 days post-injury) and at medical clearance (median: 24 days post-injury), along with 71 athletic controls. For all athletes, plasma MMPs were measured and arterial spin labelling was used to measure CBF. Consistent with our hypothesis, higher concentrations of MMP-2 and MMP-3 were correlated with lower global CBF. The correlations between MMPs and global CBF were also significantly diminished for concussed athletes at medical clearance and for athletic controls. These results indicate an inverse relationship between plasma MMP levels and CBF that is specific to the symptomatic phase of concussion. Analyses of regional CBF further showed that correlations with MMP levels exhibited some spatial specificity, with greatest effects in occipital, parietal and temporal lobes. These findings provide new insights into the mechanisms of post-concussion cerebrovascular dysfunction.