Neuroimaging alterations and relapse in early-stage psychosis.

BACKGROUND: Recent reports have indicated that symptom exacerbation after a period of improvement, referred to as relapse, in early-stage psychosis could result in brain changes and poor disease outcomes. We hypothesized that substantial neuroimaging alterations may exist among patients who experience relapse in early-stage psychosis. METHODS: We studied patients with psychosis within 2 years after the first psychotic event and healthy controls. We divided patients into 2 groups, namely those who did not experience relapse between disease onset and the magnetic resonance imaging (MRI) scan (no-relapse group) and those who did experience relapse between these 2 timings (relapse group). We analyzed 3003 functional connectivity estimates between 78 regions of interest (ROIs) derived from resting-state functional MRI data by adjusting for demographic and clinical confounding factors. RESULTS: We studied 85 patients, incuding 54 in the relapse group and 31 in the no-relapse group, along with 94 healthy controls. We observed significant differences in 47 functional connectivity estimates between the relapse and control groups after multiple comparison corrections, whereas no differences were found between the no-relapse and control groups. Most of these pathological signatures (64%) involved the thalamus. The Jonckheere-Terpstra test indicated that all 47 functional connectivity changes had a significant cross-group progression from controls to patients in the no-relapse group to patients in the relapse group. LIMITATIONS: Longitudinal studies are needed to further validate the involvement and pathological importance of the thalamus in relapse. CONCLUSION: We observed pathological differences in neuronal connectivity associated with relapse in early-stage psychosis, which are more specifically associated with the thalamus. Our study implies the importance of considering neurobiological mechanisms associated with relapse in the trajectory of psychotic disorders.

A multimodal study of a first episode psychosis cohort: potential markers of antipsychotic treatment resistance.

Treatment resistant (TR) psychosis is considered to be a significant cause of disability and functional impairment. Numerous efforts have been made to identify the clinical predictors of TR. However, the exploration of molecular and biological markers is still at an early stage. To understand the TR condition and identify potential molecular and biological markers, we analyzed demographic information, clinical data, structural brain imaging data, and molecular brain imaging data in 7 Tesla magnetic resonance spectroscopy from a first episode psychosis cohort that includes 136 patients. Age, gender, race, smoking status, duration of illness, and antipsychotic dosages were controlled in the analyses. We found that TR patients had a younger age at onset, more hospitalizations, more severe negative symptoms, a reduction in the volumes of the hippocampus (HP) and superior frontal gyrus (SFG), and a reduction in glutathione (GSH) levels in the anterior cingulate cortex (ACC), when compared to non-TR patients. The combination of multiple markers provided a better classification between TR and non-TR patients compared to any individual marker. Our study shows that ACC-GSH, HP and SFG volumes, and age at onset, could potentially be biomarkers for TR diagnosis, while hospitalization and negative symptoms could be used to evaluate the progression of the disease. Multimodal cohorts are essential in obtaining a comprehensive understanding of brain disorders.

Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors.

Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheimer's disease outcomes. In this study, we propose an ℓ1 -type regularization for predictors that follow a hierarchical tree structure. Considering a tree as a directed acyclic graph, we interpret the model parameters from a path analysis perspective. Under this concept, the proposed penalty regulates the total effect of each predictor on the outcome. With regularity conditions, it is shown that under the proposed regularization, the estimator of the model coefficient is consistent in ℓ2 -norm and the model selection is also consistent. When applied to a brain sMRI dataset acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the proposed approach identifies brain regions where atrophy in these regions demonstrates the declination in memory. With regularization on the total effects, the findings suggest that the impact of atrophy on memory deficits is localized from small brain regions, but at various levels of brain segmentation. Data used in preparation of this paper were obtained from the ADNI database.

Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup.

Multi-institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure-based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI-rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure-based analysis showed widespread DTI abnormalities in FEP and rs-fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof-of-concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub-groups.

Quantitative Susceptibility Mapping of Brain Iron and ß-Amyloid in MRI and PET Relating to Cognitive Performance in Cognitively Normal Older Adults.

Background For individuals with mild cognitive impairment (MCI) or dementia, elevated brain iron together with ß-amyloid is associated with lower cognitive functioning. But this needs further investigation among cognitively normal older adults. Purpose To investigate via quantitative susceptibility mapping (QSM) in MRI and PET how cerebral iron together with ß-amyloid affects cognition among cognitively normal older adults. Materials and Methods In this secondary analysis of a prospective study, cognitively normal older adults underwent QSM MRI to measure brain iron. A majority underwent PET to measure cerebral ß-amyloid within 30 days of MRI. Multiple linear regression analyses were performed for 12 cortical and subcortical gray matter regions to assess the effect of brain iron on cognitive functions. Voxel-based analyses investigated the associations between tissue iron and ß-amyloid load and their relationship to cognitive performance. Results Evaluated were 150 cognitively normal older adults (mean age, 69 years ± 8 [standard deviation]; 93 women). Of 150, 97 underwent PET; 22 of the 97 (mean age, 71 years ± 6; 13 women) were positive for ß-amyloid. In all participants, brain iron content in the hippocampus negatively correlated with global cognitive composite score (standardized ß = -0.24; 95% CI: -0.40, -0.07; P = .005). In the PET subgroup, brain iron in the hippocampus negatively correlated with episodic memory (ß = -0.24; 95% CI: -0.40, -0.08; P = .004) and visuospatial score (ß = -0.34; 95% CI: -0.56, -0.12; P = .003) independent of ß-amyloid burden. Both negative and positive correlations between brain iron and ß-amyloid were observed in the PET subgroup, revealing clusters where brain iron content negatively correlated with ß-amyloid and global cognitive scores (eg, in the frontal cortex: ß = -0.13; 95% CI: -0.23, -0.02; P = .02). No clusters showed associations between ß-amyloid and global cognition. Conclusion Among cognitively normal older adults, quantitative susceptibility mapping in MRI and PET indicated that elevated cerebral iron load was related to lower cognitive performance independent of ß-amyloid. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Chiang in this issue.

A Fast and Precise Tool for Multi-Layer Planar Coil Self-Inductance Calculation.

An open-source tool that allows for a fast and precise analytical calculation of multi-layer planar coils self-inductance, without any geometry limitation is proposed here. The process of designing and simulating planar coils to achieve reliable results is commonly limited on accuracy and or geometry, or are too time-consuming and expensive, thus a tool to speed up this design process is desired. The model is based on Grover equations, valid for any geometry. The validation of the tool was performed through the comparison with experimental measurements, Finite Element Model (FEM) simulations, and the main analytical methods usually used in literature, with errors registered to be below 2.5%, when compared to standard FEM simulations, and when compared to experimental measurements they are below 10% in the case of the 1-layer coils, and below 5% in the 2-layer coils (without taking into consideration the coil connectors). The proposed model offers a new approach to the calculation of the self-inductance of planar coils of several layers that combines precision, speed, independence of geometry, easy interaction, and no need for extra resources.

Visualising the topography of the acoustic radiation in clinical diffusion tensor imaging scans.

PURPOSE: It has long been thought that the acoustic radiation (AR) white matter fibre tract from the medial geniculate body of the thalamus to the Heschl's gyrus cannot be reconstructed via single-fibre analysis of clinical diffusion tensor imaging (DTI) scans. A recently developed single-fibre probabilistic method suggests otherwise. The method uses dynamic programming (DP) to compute the most probable paths between two regions of interest. This study aims to observe the ability of single-fibre probabilistic analysis via DP to visualise the AR in clinical DTI scans from legacy pilot cohorts of subjects with normal hearing (NH) and profound hearing loss (HL). METHODS: Single-fibre probabilistic analysis via DP was applied to reconstruct 3D models of the AR in the two cohorts. DTI and T1 data at 1.5 T for subjects with NH (n = 11) and HL (n = 5), as well as 3 T for NH (n = 1) and HL (n = 1), were used. RESULTS: The topographical features of AR previously observed in post-mortem and multi-fibre analyses can be visualised in DTI scans of 16 subjects and 2 atlases with a success rate of 100%. Relative to MNI coordinates, there was no significant difference in the varifold distances between the topography of the tracts in the 1.5 T cohort. CONCLUSION: The AR can be visualised in clinical 1.5 T and 3 T DTI scans using single-fibre probabilistic analysis via DP, hence, the potential for DP to visualise the AR in medical and pre-surgical applications in pathologies such as vestibular schwannoma, multiple sclerosis, thalamic tumours and stroke as well as hearing loss.

White Matter Hyperintensities Contribute to Language Deficits in Primary Progressive Aphasia.

OBJECTIVE: To determine the contribution of white matter hyperintensities (WMH) to language deficits while accounting for cortical atrophy in individuals with primary progressive aphasia (PPA). METHOD: Forty-three individuals with PPA completed neuropsychological assessments of nonverbal semantics, naming, and sentence repetition plus T2-weighted and fluid-attenuated inversion recovery scans. Using three visual scales, we rated WMH and cerebral ventricle size for both scan types. We used Spearman correlations to evaluate associations between the scales and scans. To test whether visual ratings-particularly of WMH-are associated with language, we compared a base model (including gray matter component scores obtained via principal component analysis, age, and days between assessment and MRI as independent variables) with full models (ie, the base model plus visual ratings) for each language variable. RESULTS: Visual ratings were significantly associated within and between scans and were significantly correlated with age but not with other vascular risk factors. Only the T2 scan ratings were associated with language abilities. Specifically, controlling for other variables, poorer naming was significantly related to larger ventricles (P = 0.033) and greater global (P = 0.033) and periventricular (P = 0.049) WMH. High global WMH (P = 0.034) were also correlated with worse sentence repetition skills. CONCLUSION: Visual ratings of global brain health were associated with language deficits in PPA independent of cortical atrophy and age. While WMH are not unique to PPA, measuring WMH in conjunction with cortical atrophy may elucidate more accurate brain structure-behavior relationships in PPA than cortical atrophy measures alone.

An Efficient Bedside Measure Yields Prognostic Implications for Language Recovery in Acute Stroke Patients.

BACKGROUND: It is estimated that ∼30% of stroke survivors have aphasia, a language disorder resulting from damage to left-hemisphere language networks. In acute care settings, efficient identification of aphasia is critical, but there is a paucity of efficient bedside assessments. OBJECTIVE: To determine whether objective measures on a picture description task administered within 48 hours post stroke (a) predict language recovery, (b) estimate left-hemisphere lesion volume and location, and (c) correlate with other bedside language assessments. METHOD: Behavioral data were scored at acute and chronic time points. Neuroimaging data were used to determine associations between the picture description task, other language assessments, and lesion volume and location. RESULTS: Acute content units, age, and total lesion volume predicted communication recovery; F3,18 = 3.98, P = 0.024; r = 0.40. Significant correlations were found between the picture description task and lesion volume and location. Picture description outcomes were also associated with other clinical language assessments. DISCUSSION: This picture description task quickly predicted the language performance (communication recovery and outcome) for patients who suffered a left-hemisphere stroke. Picture description task measures correlated with damage in the left hemisphere and with other, more time-consuming and cumbersome language assessments that are typically administered acutely at bedside. CONCLUSION: The predictive value of this picture description task and correlations with existing language assessments substantiate the clinical importance of a reliable yet rapid bedside measure for acute stroke patients that can be administered by a variety of health care professionals.

Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility.

Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ±â€¯0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ±â€¯0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ±â€¯0.08 to manual labels and 0.89 ±â€¯0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

ASL-MRICloud: An online tool for the processing of ASL MRI data.

Arterial spin labeling (ASL) MRI is increasingly used in research and clinical settings. The purpose of this work is to develop a cloud-based tool for ASL data processing, referred to as ASL-MRICloud, which may be useful to the MRI community. In contrast to existing ASL toolboxes, which are based on software installation on the user's local computer, ASL-MRICloud uses a web browser for data upload and results download, and the computation is performed on the remote server. As such, this tool is independent of the user's operating system, software version, and CPU speed. The ASL-MRICloud tool was implemented to be compatible with data acquired by scanners from all major MRI manufacturers, is capable of processing several common forms of ASL, including pseudo-continuous ASL and pulsed ASL, and can process single-delay and multi-delay ASL data. The outputs of ASL-MRICloud include absolute and relative values of cerebral blood flow, arterial transit time, voxel-wise masks indicating regions with potential hyper-perfusion and hypo-perfusion, and an image quality index. The ASL tool is also integrated with a T1 -based brain segmentation and normalization tool in MRICloud to allow generation of parametric maps in standard brain space as well as region-of-interest values. The tool was tested on a large data set containing 309 ASL scans as well as on publicly available ASL data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

Evidence for a subcortical origin of mirror movements after stroke: a longitudinal study.

Following a stroke, mirror movements are unintended movements that appear in the non-paretic hand when the paretic hand voluntarily moves. Mirror movements have previously been linked to overactivation of sensorimotor areas in the non-lesioned hemisphere. In this study, we hypothesized that mirror movements might instead have a subcortical origin, and are the by-product of subcortical motor pathways upregulating their contributions to the paretic hand. To test this idea, we first characterized the time course of mirroring in 53 first-time stroke patients, and compared it to the time course of activities in sensorimotor areas of the lesioned and non-lesioned hemispheres (measured using functional MRI). Mirroring in the non-paretic hand was exaggerated early after stroke (Week 2), but progressively diminished over the year with a time course that parallelled individuation deficits in the paretic hand. We found no evidence of cortical overactivation that could explain the time course changes in behaviour, contrary to the cortical model of mirroring. Consistent with a subcortical origin of mirroring, we predicted that subcortical contributions should broadly recruit fingers in the non-paretic hand, reflecting the limited capacity of subcortical pathways in providing individuated finger control. We therefore characterized finger recruitment patterns in the non-paretic hand during mirroring. During mirroring, non-paretic fingers were broadly recruited, with mirrored forces in homologous fingers being only slightly larger (1.76 times) than those in non-homologous fingers. Throughout recovery, the pattern of finger recruitment during mirroring for patients looked like a scaled version of the corresponding control mirroring pattern, suggesting that the system that is responsible for mirroring in controls is upregulated after stroke. Together, our results suggest that post-stroke mirror movements in the non-paretic hand, like enslaved movements in the paretic hand, are caused by the upregulation of a bilaterally organized subcortical system.

Separable systems for recovery of finger strength and control after stroke.

Impaired hand function after stroke is a major cause of long-term disability. We developed a novel paradigm that quantifies two critical aspects of hand function, strength, and independent control of fingers (individuation), and also removes any obligatory dependence between them. Hand recovery was tracked in 54 patients with hemiparesis over the first year after stroke. Most recovery of strength and individuation occurred within the first 3 mo. A novel time-invariant recovery function was identified: recovery of strength and individuation were tightly correlated up to a strength level of ~60% of estimated premorbid strength; beyond this threshold, strength improvement was not accompanied by further improvement in individuation. Any additional improvement in individuation was attributable instead to a second process that superimposed on the recovery function. We conclude that two separate systems are responsible for poststroke hand recovery: one contributes almost all of strength and some individuation; the other contributes additional individuation.NEW & NOTEWORTHY We tracked recovery of the hand over a 1-yr period after stroke in a large cohort of patients, using a novel paradigm that enabled independent measurement of finger strength and control. Most recovery of strength and control occurs in the first 3 mo after stroke. We found that two separable systems are responsible for motor recovery of hand: one contributes strength and some dexterity, whereas a second contributes additional dexterity.

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc.

Structural signature of classical versus late-onset friedreich's ataxia by Multimodality brain MRI.

INTRODUCTION: Friedreich's ataxia (FRDA) is the most common autosomal-recessive ataxia worldwide. It is characterized by early onset, sensory abnormalities, and slowly progressive ataxia. However, some individuals manifest the disease after the age of 25 years and are classified as late-onset FRDA (LOFA). Therefore, we propose a transversal multimodal MRI-based study to investigate which anatomical substrates are involved in classical (cFRDA) and LOFA. METHODS: We enrolled 36 patients (13 with LOFA) and 29 healthy controls. All subjects underwent magnetic resonance imaging in a 3 T device; three-dimensional high-resolution T1-weighted images and diffusion tensor images were used to assess gray and white matter, respectively. We used T1 multiatlas approach to assess deep gray matter and cortical thickness measures to evaluate cerebral cortex and DTI multiatlas approach to assess white matter. All analyses were corrected for multiple comparisons. RESULTS: Group comparison showed that both groups presented gray matter atrophy mostly in the motor cortex. Regarding white matter, we found abnormalities in the cerebellar peduncles, pyramidal tracts, midbrain, pons, and medulla oblongata for both groups, but the microstructural abnormalities in the cFRDA group were more widespread. In addition, we found that the corticospinal tract presented more severe microstructural damage in the LOFA group. Finally, the midbrain volume of the cFRDA, but not of the LOFA group, correlated with disease duration (R = -0.552, P = 0.012) and severity (R = -0.783, P < 0.001). CONCLUSION: The cFRDA and LOFA groups have similar, but not identical neuroimaging damage pattern. These structural differences might help to explain the phenotypic variability observed in FRDA. Hum Brain Mapp 38:4157-4168, 2017. © 2017 Wiley Periodicals, Inc.

Mitigation of Biofilm Development on Thin-Film Composite Membranes Functionalized with Zwitterionic Polymers and Silver Nanoparticles.

We demonstrate the functionalization of thin-film composite membranes with zwitterionic polymers and silver nanoparticles (AgNPs) for combating biofouling. Combining hydrophilic zwitterionic polymer brushes and biocidal AgNPs endows the membrane with dual functionality: antiadhesion and bacterial inactivation. An atom transfer radical polymerization (ATRP) reaction is used to graft zwitterionic poly(sulfobetaine methacrylate) (PSBMA) brushes to the membrane surface, while AgNPs are synthesized in situ through chemical reduction of silver. Two different membrane architectures (Ag-PSBMA and PSBMA-Ag TFC) are developed according to the sequence AgNPs, and PSBMA brushes are grafted on the membrane surface. A static adhesion assay shows that both modified membranes significantly reduced the adsorption of proteins, which served as a model organic foulant. However, improved antimicrobial activity is observed for PSBMA-Ag TFC (i.e., AgNPs on top of the polymer brush) in comparison to the Ag-PSBMA TFC membrane (i.e., polymer brush on top of AgNPs), indicating that architecture of the antifouling layer is an important factor in the design of zwitterion-silver membranes. Confocal laser scanning microscopy (CLSM) imaging indicated that PSBMA-Ag TFC membranes effectively inhibit biofilm formation under dynamic cross-flow membrane biofouling tests. Finally, we demonstrate the regeneration of AgNPs on the membrane after depletion of silver from the surface of the PSBMA-Ag TFC membrane.

Picturing the Size and Site of Stroke With an Expanded National Institutes of Health Stroke Scale.

BACKGROUND AND PURPOSE: The National Institutes of Health Stroke Scale (NIHSS) includes minimal assessment of cognitive function, particularly in right hemisphere (RH) stroke. Descriptions of the Cookie Theft picture from the NIHSS allow analyses that (1) correlate with aphasia severity and (2) identify communication deficits in RH stroke. We hypothesized that analysis of the picture description contributes valuable information about volume and location of acute stroke. METHODS: We evaluated 67 patients with acute ischemic stroke (34 left hemisphere [LH]; 33 RH) with the NIHSS, analysis of the Cookie Theft picture, and magnetic resonance imaging, compared with 35 sex- and age-matched controls. We evaluated descriptions for total content units (CU), syllables, ratio of left:right CU, CU/minute, and percent interpretive CU, based on previous studies. Lesion volume and percent damage to regions of interest were measured on diffusion-weighted imaging. Multivariable linear regression identified variables associated with infarct volume, independently of NIHSS score, age and sex. RESULTS: Patients with RH and LH stroke differed from controls, but not from each other, on CU, syllables/CU, and CU/minute. Left:right CU was lower in RH compared with LH stroke. CU, syllables/CU, and NIHSS each correlated with lesion volume in LH and RH stroke. Lesion volume was best accounted by a model that included CU, syllables/CU, NIHSS, left:right CU, percent interpretive CU, and age, in LH and RH stroke. Each discourse variable and NIHSS score were associated with percent damage to different regions of interest, independently of lesion volume and age. CONCLUSIONS: Brief picture description analysis complements NIHSS scores in predicting stroke volume and location.

Critical role of the right uncinate fasciculus in emotional empathy.

OBJECTIVE: Common neurological diseases or injuries that can affect the right hemisphere, including stroke, traumatic brain injury, and frontotemporal dementia, disrupt emotional empathy-the ability to share in and make inferences about how other people feel. This impairment negatively impacts social interactions and relationships. Accumulating evidence indicates that emotional empathy depends on coordinated functions of orbitofrontal cortex, anterior insula, anterior cingulate, temporal pole, and amygdala, but few studies have investigated effects of lesions to white matter tracts that connect these structures. We tested the hypothesis that percentage damage to specific white matter tracts connecting these gray matter structures predicts error rate in an emotional empathy task after acute right hemisphere ischemic stroke. METHODS: We used multivariate linear regression with percentage damage to 8 white matter tracts, age, and education as independent variables and error rate on emotional empathy as the dependent variable to test a predictive model of emotional empathy in 30 patients with acute ischemic right hemisphere stroke. RESULTS: Percentage damage to 8 white matter tracts along with age and education predicted the error rate in emotional empathy, but only percentage damage to the uncinate fasciculus was independently associated with error rate. Participants with right uncinate fasciculus lesions were significantly more impaired than right hemisphere stroke patients without uncinate fasciculus lesions in the emotional empathy task. INTERPRETATION: The right uncinate fasciculus plays an important role in the emotional empathy network. Patients with lesions in this network should be evaluated for empathy, so that deficits can be addressed.

White matter tracts critical for recognition of sarcasm.

Failure to recognize sarcasm can lead to important miscommunications. Few previous studies have identified brain lesions associated with impaired recognition of sarcasm. We tested the hypothesis that percent damage to specific white matter tracts, age, and education together predict accuracy in sarcasm recognition. Using multivariable linear regression, with age, education, and percent damage to each of eight white matter tracts as independent variables, and percent accuracy on sarcasm recognition as the dependent variable, we developed a model for predicting sarcasm recognition. Percent damage to the sagittal stratum had the greatest weight and was the only independent predictor of sarcasm recognition.