Reading on the right when there’s nothing left? Probabilistic tractography reveals hemispheric asymmetry in pure alexia

We present a patient with reading inexpertise and right hemianopia following left posterior cerebral artery (PCA) stroke. We examine the extent of disruption to reading performance and the extent of white matter tract damage relative to a patient with more limited PCA infarction and isolated right hemianopia. We show white matter disconnection of the temporal occipital fusiform cortex in our pure alexia patient. Connectivity-based laterality indices revealed right hemisphere laterality in the alexia patient; this was not associated with improved reading function. We speculate that the degree of premorbid laterality may be a critical factor affecting the extent of reading dysfunction in alexia

Disentangling input and output-related components of spatial neglect

Spatial neglect is a heterogeneous disorder with a multitude of manifestations and subtypes. Common clinical paper and pencil neglect tests fail to differentiate between these subtypes. For example, neglect patients typically bisect lines to the right. This bias can be caused by an underestimation of the left half of the line (input-related deficit), by the failure to direct actions toward the left side of space (output-related deficit), or by a mixture of these impairments. To disentangle these impairments, we used a test consisting of a line bisection task on a touch screen monitor (manual motor task) and the subsequent judgment of one's own bisection performance (visual perceptual task). It was hypothesized that patients with mainly output-related neglect should be better able to recognize their misbisected lines than patients with purely input-related neglect. In a group of 16 patients suffering from spatial neglect after right brain damage, we found that patients were three times more likely to suffer from a predominantly input-related than from an output-related subtype. The results thus suggest that neglect is typically an input-related impairment. Additional analysis of the line bisection task revealed that temporal (slowness in initiation and execution of contralateral movements) and spatial (insufficient movement amplitude toward the contralesional side) aspects of output-related neglect were mutually unrelated. This independence raises the possibility that a fine-grained differentiation of output-related neglect is required. That is, impairments in lateralized temporal and spatial aspects of movements may underlie different neglect subtypes

Plasma neurofilament light in behavioural variant frontotemporal dementia compared to mood and psychotic disorders

OBJECTIVE: Blood biomarkers of neuronal injury such as neurofilament light (NfL) show promise to improve diagnosis of neurodegenerative disorders and distinguish neurodegenerative from primary psychiatric disorders (PPD). This study investigated the diagnostic utility of plasma NfL to differentiate behavioural variant frontotemporal dementia (bvFTD, a neurodegenerative disorder commonly misdiagnosed initially as PPD), from PPD, and performance of large normative/reference data sets and models. METHODS: Plasma NfL was analysed in major depressive disorder (MDD, n = 42), bipolar affective disorder (BPAD, n = 121), treatment-resistant schizophrenia (TRS, n = 82), bvFTD (n = 22), and compared to the reference cohort (Control Group 2, n = 1926, using GAMLSS modelling), and age-matched controls (Control Group 1, n = 96, using general linear models). RESULTS: Large differences were seen between bvFTD (mean NfL 34.9 pg/mL) and all PPDs and controls (all < 11 pg/mL). NfL distinguished bvFTD from PPD with high accuracy, sensitivity (86%), and specificity (88%). GAMLSS models using reference Control Group 2 facilitated precision interpretation of individual levels, while performing equally to or outperforming models using local controls. Slightly higher NfL levels were found in BPAD, compared to controls and TRS. CONCLUSIONS: This study adds further evidence on the diagnostic utility of NfL to distinguish bvFTD from PPD of high clinical relevance to a bvFTD differential diagnosis, and includes the largest cohort of BPAD to date. Using large reference cohorts, GAMLSS modelling and the interactive Internet-based application we developed, may have important implications for future research and clinical translation. Studies are underway investigating utility of plasma NfL in diverse neurodegenerative and primary psychiatric conditions in real-world clinical settings

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Train Smart Study: protocol for a randomised trial investigating the role of exercise training dose on markers of brain health in sedentary middle-aged adults

Introduction Regular aerobic exercise is associated with improved cognitive function, implicating it as a strategy to reduce dementia risk. This is reinforced by the association between greater cardiorespiratory fitness and larger brain volume, superior cognitive performance and lower dementia risk. However, the optimal aerobic exercise dose, namely the intensity and mode of delivery, to improve brain health and lower dementia risk has received less attention. We aim to determine the effect of different doses of aerobic exercise training on markers of brain health in sedentary middle-aged adults, hypothesising that high-intensity interval training (HIIT) will be more beneficial than moderate-intensity continuous training (MICT). Methods and analysis In this two-group parallel, open-label blinded endpoint randomised trial, 70 sedentary middle-aged (45-65 years) adults will be randomly allocated to one of two 12-week aerobic exercise training interventions matched for total exercise training volume: (1) MICT (n=35) or HIIT (n=35). Participants will perform ∼50 min exercise training sessions, 3 days per week, for 12 weeks. The primary outcome will be measured as between-group difference in cardiorespiratory fitness (peak oxygen uptake) change from baseline to the end of training. Secondary outcomes include between-group differences in cognitive function and ultra-high field MRI (7T) measured markers of brain health (brain blood flow, cerebrovascular function, brain volume, white matter microstructural integrity and resting state functional brain activity) changes from baseline to the end of training. Ethics and dissemination The Victoria University Human Research Ethics Committee (VUHREC) has approved this study (HRE20178), and all protocol modifications will be communicated to the relevant parties (eg, VUHREC, trial registry). Findings from this study will be disseminated via peer-review publications, conference presentations, clinical communications and both mainstream and social media. Trial registration number ANZCTR12621000144819

A Human Depression Circuit Derived From Focal Brain Lesions

Background: Focal brain lesions can lend insight into the causal neuroanatomical substrate of depression in the human brain. However, studies of lesion location have led to inconsistent results.Methods: Five independent datasets with different lesion etiologies and measures of postlesion depression were collated (N = 461). Each 3-dimensional lesion location was mapped to a common brain atlas. We used voxel lesion symptom mapping to test for associations between depression and lesion locations. Next, we computed the network of regions functionally connected to each lesion location using a large normative connectome dataset (N = 1000). We used these lesion network maps to test for associations between depression and connected brain circuits. Reproducibility was assessed using a rigorous leave-one-dataset-out validation. Finally, we tested whether lesion locations associated with depression fell within the same circuit as brain stimulation sites that were effective for improving poststroke depression.Results: Lesion locations associated with depression were highly heterogeneous, and no single brain region was consistently implicated. However, these same lesion locations mapped to a connected brain circuit, centered on the left dorsolateral prefrontal cortex. Results were robust to leave-one-dataset-out cross-validation. Finally, our depression circuit derived from brain lesions aligned with brain stimulation sites that were effective for improving poststroke depression.Conclusions: Lesion locations associated with depression fail to map to a specific brain region but do map to a specific brain circuit. This circuit may have prognostic utility in identifying patients at risk for poststroke depression and therapeutic utility in refining brain stimulation targets.</p

Profile of and risk factors for poststroke cognitive impairment in diverse ethno-regional groups

OBJECTIVE: To address the variability in prevalence estimates and inconsistencies in potential risk factors for poststroke cognitive impairment (PSCI) using a standardized approach and individual participant data (IPD) from international cohorts in the Stroke and Cognition Consortium (STROKOG) consortium. METHODS: We harmonized data from 13 studies based in 8 countries. Neuropsychological test scores 2 to 6 months after stroke or TIA and appropriate normative data were used to calculate standardized cognitive domain scores. Domain-specific impairment was based on percentile cutoffs from normative groups, and associations between domain scores and risk factors were examined with 1-stage IPD meta-analysis. RESULTS: In a combined sample of 3,146 participants admitted to hospital for stroke (97%) or TIA (3%), 44% were impaired in global cognition and 30% to 35% were impaired in individual domains 2 to 6 months after the index event. Diabetes mellitus and a history of stroke were strongly associated with poorer cognitive function after covariate adjustments; hypertension, smoking, and atrial fibrillation had weaker domain-specific associations. While there were no significant differences in domain impairment among ethno-racial groups, some interethnic differences were found in the effects of risk factors on cognition. CONCLUSIONS: This study confirms the high prevalence of PSCI in diverse populations, highlights common risk factors, in particular diabetes mellitus, and points to ethno-racial differences that warrant attention in the development of prevention strategies.OBJECTIVE: To address the variability in prevalence estimates and inconsistencies in potential risk factors for poststroke cognitive impairment (PSCI) using a standardized approach and individual participant data (IPD) from international cohorts in the Stroke and Cognition Consortium (STROKOG) consortium. METHODS: We harmonized data from 13 studies based in 8 countries. Neuropsychological test scores 2 to 6 months after stroke or TIA and appropriate normative data were used to calculate standardized cognitive domain scores. Domain-specific impairment was based on percentile cutoffs from normative groups, and associations between domain scores and risk factors were examined with 1-stage IPD meta-analysis. RESULTS: In a combined sample of 3,146 participants admitted to hospital for stroke (97%) or TIA (3%), 44% were impaired in global cognition and 30% to 35% were impaired in individual domains 2 to 6 months after the index event. Diabetes mellitus and a history of stroke were strongly associated with poorer cognitive function after covariate adjustments; hypertension, smoking, and atrial fibrillation had weaker domain-specific associations. While there were no significant differences in domain impairment among ethnoracial groups, some interethnic differences were found in the effects of risk factors on cognition. CONCLUSIONS: This study confirms the high prevalence of PSCI in diverse populations, highlights common risk factors, in particular diabetes mellitus, and points to ethnoracial differences that warrant attention in the development of prevention strategies.Peer reviewe

Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis

Background. Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results. Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−0.15). Conclusions. The present study identifies novel associations between chronic poststroke sensorimotor impairment and ipsilesional hippocampal volume that are not caused by lesion size and may be stronger in women.S.-L.L. is supported by NIH K01 HD091283; NIH R01 NS115845. A.B. and M.S.K. are supported by National Health and Medical Research Council (NHMRC) GNT1020526, GNT1045617 (A.B.), GNT1094974, and Heart Foundation Future Leader Fellowship 100784 (A.B.). P.M.T. is supported by NIH U54 EB020403. L.A.B. is supported by the Canadian Institutes of Health Research (CIHR). C.M.B. is supported by NIH R21 HD067906. W.D.B. is supported by the Heath Research Council of New Zealand. J.M.C. is supported by NIH R00HD091375. A.B.C. is supported by NIH R01NS076348-01, Hospital Israelita Albert Einstein 2250-14, CNPq/305568/2016-7. A.N.D. is supported by funding provided by the Texas Legislature to the Lone Star Stroke Clinical Trial Network. Its contents are solely the responsibility of the authors and do not necessarily represent the of ficial views of the Government of the United States or the State of Texas. N.E.-B. is supported by Australian Research Council NIH DE180100893. W.F. is sup ported by NIH P20 GM109040. F.G. is supported by Wellcome Trust (093957). B.H. is funded by and NHMRC fellowship (1125054). S.A.K is supported by NIH P20 HD109040. F.B. is supported by Italian Ministry of Health, RC 20, 21. N.S. is supported by NIH R21NS120274. N.J.S. is supported by NIH/National Institute of General Medical Sciences (NIGMS) 2P20GM109040-06, U54-GM104941. S.R.S. is supported by European Research Council (ERC) (NGBMI, 759370). G.S. is supported by Italian Ministry of Health RC 18-19-20-21A. M.T. is sup ported by National Institute of Neurological Disorders and Stroke (NINDS) R01 NS110696. G.T.T. is supported by Temple University sub-award of NIH R24 –NHLBI (Dr Mickey Selzer) Center for Experimental Neurorehabilitation Training. N.J.S. is funded by NIH/National Institute of Child Health and Human Development (NICHD) 1R01HD094731-01A1

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research