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The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

The application of ℓ1-regularized machine learning models to high-dimensional connectomes offers a promising methodology to assess clinical-anatomical correlations in humans. Here, we integrate the connectome-based lesion-symptom mapping framework with sparse partial least squares regression (sPLS-R) to isolate elements of the connectome associated with speech repetition deficits. By mapping over 2,500 connections of the structural connectome in a cohort of 71 stroke-induced cases of aphasia presenting with varying left-hemisphere lesions and repetition impairment, sPLS-R was trained on 50 subjects to algorithmically identify connectomic features on the basis of their predictive value. The highest ranking features were subsequently used to generate a parsimonious predictive model for speech repetition whose predictions were evaluated on a held-out set of 21 subjects. A set of 10 short- and long-range parieto-temporal connections were identified, collectively delineating the broader circuitry of the dorsal white matter network of the language system. The strongest contributing feature was a short-range connection in the supramarginal gyrus, approximating the cortical localization of area Spt, with parallel long-range pathways interconnecting posterior nodes in supramarginal and superior temporal cortex with anterior nodes in both ventral and-notably-in dorsal premotor cortex, respectively. The collective disruption of these pathways indexed repetition performance in the held-out set of participants, suggesting that these impairments might be characterized as a parietotemporal disconnection syndrome impacting cortical area Spt and its associated white matter circuits of the frontal lobe as opposed to being purely a disconnection of the arcuate fasciculus., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra-axonal and extra-axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches. However, these particular approaches have yet to be applied in clinical cohorts. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra-axonal and extra-axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra-axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra-axonal diffusivity compared to those with nonrefractory epilepsy. The extra-axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Recent studies have combined multiple neuroimaging modalities to gain further understanding of the neurobiological substrates of aphasia. Following this line of work, the current study uses machine learning approaches to predict aphasia severity and specific language measures based on a multimodal neuroimaging dataset. A total of 116 individuals with chronic left-hemisphere stroke were included in the study. Neuroimaging data included task-based functional magnetic resonance imaging (fMRI), diffusion-based fractional anisotropy (FA)-values, cerebral blood flow (CBF), and lesion-load data. The Western Aphasia Battery was used to measure aphasia severity and specific language functions. As a primary analysis, we constructed support vector regression (SVR) models predicting language measures based on (i) each neuroimaging modality separately, (ii) lesion volume alone, and (iii) a combination of all modalities. Prediction accuracy across models was subsequently statistically compared. Prediction accuracy across modalities and language measures varied substantially (predicted vs. empirical correlation range: r = .00-.67). The multimodal prediction model yielded the most accurate prediction in all cases (r = .53-.67). Statistical superiority in favor of the multimodal model was achieved in 28/30 model comparisons (p-value range: <.001-.046). Our results indicate that different neuroimaging modalities carry complementary information that can be integrated to more accurately depict how brain damage and remaining functionality of intact brain tissue translate into language function in aphasia., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Agrammatism in aphasia is not a homogeneous syndrome, but a characterization of a nonuniform set of language behaviors in which grammatical markers and complex syntactic structures are omitted, simplified, or misinterpreted. In a sample of 71 left-hemisphere stroke survivors, syntactic processing was quantified with the Northwestern Assessment of Verbs and Sentences (NAVS). Classification analyses were used to assess the relation between NAVS performance and morphosyntactically reduced speech in picture descriptions. Voxel-based and connectivity-based lesion-symptom mapping were applied to investigate neural correlates of impaired syntactic processing. Despite a nonrandom correspondence between NAVS performance and morphosyntactic production deficits, there was variation in individual patterns of syntactic processing. Morphosyntactically reduced production was predicted by lesions to left-hemisphere inferior frontal cortex. Impaired verb argument structure production was predicted by damage to left-hemisphere posterior superior temporal and angular gyrus, as well as to a ventral pathway between temporal and frontal cortex. Damage to this pathway was also predictive of impaired sentence comprehension and production, particularly of noncanonical sentences. Although agrammatic speech production is primarily predicted by lesions to inferior frontal cortex, other aspects of syntactic processing rely rather on regional integrity in temporoparietal cortex and the ventral stream., (© 2019 Wiley Periodicals, Inc.)

Advances in neuroimaging have enabled the mapping of white matter connections across the entire brain, allowing for a more thorough examination of the extent of white matter disconnection after stroke. To assess how cortical disconnection contributes to motor impairments, we examined the relationship between structural brain connectivity and upper and lower extremity motor function in individuals with chronic stroke. Forty-three participants [mean age: 59.7 (±11.2) years; time poststroke: 64.4 (±58.8) months] underwent clinical motor assessments and MRI scanning. Nonparametric correlation analyses were performed to examine the relationship between structural connectivity amid a subsection of the motor network and upper/lower extremity motor function. Standard multiple linear regression analyses were performed to examine the relationship between cortical necrosis and disconnection of three main cortical areas of motor control [primary motor cortex (M1), premotor cortex (PMC), and supplementary motor area (SMA)] and motor function. Anatomical connectivity between ipsilesional M1/SMA and the (1) cerebral peduncle, (2) thalamus, and (3) red nucleus were significantly correlated with upper and lower extremity motor performance (P ≤ 0.003). M1-M1 interhemispheric connectivity was also significantly correlated with gross manual dexterity of the affected upper extremity (P = 0.001). Regression models with M1 lesion load and M1 disconnection (adjusted for time poststroke) explained a significant amount of variance in upper extremity motor performance (R 2  = 0.36-0.46) and gait speed (R 2  = 0.46), with M1 disconnection an independent predictor of motor performance. Cortical disconnection, especially of ipsilesional M1, could significantly contribute to variability seen in locomotor and upper extremity motor function and recovery in chronic stroke. Hum Brain Mapp 39:120-132, 2018. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Recent neuroimaging and behavioral studies have revealed that children with new onset epilepsy already exhibit brain structural abnormalities and cognitive impairment. How the organization of large-scale brain structural networks is altered near the time of seizure onset and whether network changes are related to cognitive performances remain unclear. Recent studies also suggest that regional brain volume covariance reflects synchronized brain developmental changes. Here, we test the hypothesis that epilepsy during early-life is associated with abnormalities in brain network organization and cognition. We used graph theory to study structural brain networks based on regional volume covariance in 39 children with new-onset seizures and 28 healthy controls. Children with new-onset epilepsy showed a suboptimal topological structural organization with enhanced network segregation and reduced global integration compared with controls. At the regional level, structural reorganization was evident with redistributed nodes from the posterior to more anterior head regions. The epileptic brain network was more vulnerable to targeted but not random attacks. Finally, a subgroup of children with epilepsy, namely those with lower IQ and poorer executive function, had a reduced balance between network segregation and integration. Taken together, the findings suggest that the neurodevelopmental impact of new onset childhood epilepsies alters large-scale brain networks, resulting in greater vulnerability to network failure and cognitive impairment., (Copyright © 2014 Wiley Periodicals, Inc.)

Memory impairment observed in patients with medial temporal lobe epilepsy (MTLE) is classically attributed to hippocampal atrophy. The contribution of extrahippocampal structures in shaping memory impairment in patients with MTLE is not yet completely understood, even though atrophy in MTLE extends beyond the hippocampus. We aimed to evaluate the neuropsychological profile of patients with MTLE focusing on memory, and to investigate whether gray matter concentration (GMC) distribution within and outside the medial portion of the temporal lobes would be associated with their neuropsychological performance. We performed a voxel based morphometry study of 36 consecutive patients with MTLE and unilateral hippocampal atrophy. We observed a significant simple regression between general and verbal memory performance based on Wechsler Memory Scale-Revised and the GMC of medial temporal and extratemporal structures in patients with left MTLE. We also performed a "regions of interest analysis" of the medial temporal lobe, and we observed that the GMC of the hippocampus, entorhinal, and perirhinal cortices were consistently associated with general and verbal memory performance in patients with MTLE. We also observed that the GMC of the cingulate and orbito-frontal cortex are independently associated with verbal and general memory performances. Our results suggest that general and verbal memory impairments in patients with left MTLE are associated with atrophy of the hippocampus, the entorhinal, and the perirhinal cortex. We also suggest that atrophy and dysfunction of limbic and frontal structures such as the cingulate and the orbito-frontal cortex contribute to memory impairment in MTLE., ((copyright) 2007 Wiley-Liss, Inc.)

Quantitative analysis of brain structures in normal subjects and in different neurological conditions can be carried out in vivo through magnetic resonance imaging (MRI) volumetric studies. The use of high-resolution MRI combined with image post-processing that allows simultaneous multiplanar view may facilitate volumetric segmentation of temporal lobe structures. We define a protocol for volumetric studies of medial temporal lobe structures using high-resolution MR images and we studied 30 healthy subjects (19 women; mean age, 33 years; age range, 21-55 years). Images underwent field non-homogeneity correction and linear stereotaxic transformation into a standard space. Structures of interest comprised temporopolar, entorhinal, perirhinal, parahippocampal cortices, hippocampus, and the amygdala. Segmentation was carried out with multiplanar assessment. There was no statistically significant left/right-sided asymmetry concerning any structure analyzed. Neither gender nor age influenced the volumes obtained. The coefficient of repeatability showed no significant difference of intra- and interobserver measurements. Imaging post-processing and simultaneous multiplanar view of high-resolution MRI facilitates volumetric assessment of the medial portion of the temporal lobe with strict adherence to anatomic landmarks. This protocol shows no significant inter- and intraobserver variations and thus is reliable for longitudinal studies., (Copyright 2004 Wiley-Liss, Inc.)