Gray Matter Integrity Research Articles

117. Brain-Cognition Associations in Late-Life Depression and Mild Cognitive Impairment: A Multivariate Analysis of White and Gray Matter Integrity

117. Brain-Cognition Associations in Late-Life Depression and Mild Cognitive Impairment: A Multivariate Analysis of White and Gray Matter Integrity

Deep learning prediction of motor performance in stroke individuals using neuroimaging data

The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential biomarkers of motor recovery, with limited accuracy up to date. To address this, the present study aimed to develop a deep learning model based on structural brain images obtained from stroke participants and healthy volunteers. The following inputs were used in a multi-channel 3D convolutional neural network (CNN) model: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps obtained from Diffusion Tensor Imaging (DTI) images, white and gray matter intensity values obtained from Magnetic Resonance Imaging, as well as demographic data (e.g., age, gender). Upper limb motor function was classified into “Poor” and “Good” categories. To assess the performance of the DL model, we compared it to more standard machine learning (ML) classifiers including k-nearest neighbor, support vector machines (SVM), Decision Trees, Random Forests, Ada Boosting, and Naïve Bayes, whereby the inputs of these classifiers were the features taken from the fully connected layer of the CNN model. The highest accuracy and area under the curve values were 0.92 and 0.92 for the 3D-CNN and 0.91 and 0.91 for the SVM, respectively. The multi-channel 3D-CNN with residual blocks and SVM supported by DL was more accurate than traditional ML methods to classify upper limb motor impairment in the stroke population. These results suggest that combining volumetric DTI maps and measures of white and gray matter integrity can improve the prediction of the degree of motor impairment after stroke. Identifying the potential of recovery early on after a stroke could promote the allocation of resources to optimize the functional independence of these individuals and their quality of life.

Association of prediabetes with reduced brain volume in a general elderly Japanese population.

Diabetes frequently results in cognitive impairment, but it is less clear if brain health is adversely affected during the prediabetic stage. Our aim is to identify possible changes in brain volume as measured by magnetic resonance imaging (MRI) in a large elderly population stratified according to level of "dysglycemia." This is a cross-sectional study of 2144 participants (median age 69years, 60.9% female) who underwent 3-T brain MRI. Participants were divided into 4 dysglycemia groups based on HbA1c levels (%): normal glucose metabolism (NGM) (< 5.7%), prediabetes (5.7 to < 6.5%), undiagnosed diabetes (6.5% or higher), and known diabetes (defined by self-report). Of the 2144 participants, 982 had NGM, 845 prediabetes, 61 undiagnosed diabetes, and 256 known diabetes. After adjustment for age, sex, education, body weight, cognitive status, smoking, drinking, and disease history, total gray matter volume was significantly lower among participants with prediabetes (0.41% lower, standardized β = - 0.0021 [95% CI - 0.0039, - 0.00039], p = 0.016), undiagnosed diabetes (1.4% lower, standardized β = - 0.0069 [95% CI - 0.012, - 0.002], p = 0.005), and known diabetes (1.1% lower, standardized β = - 0.0055 [95% CI - 0.0081, - 0.0029], p < 0.001) compared to the NGM group. After adjustment, total white matter volume and hippocampal volume did not differ significantly between the NGM group and either the prediabetes group or the diabetes group. Sustained hyperglycemia may have deleterious effects on gray matter integrity even prior to the onset of clinical diabetes. • Sustained hyperglycemia has deleterious effects on gray matter integrity even prior to the onset of clinical diabetes.

Brain-cognition associations in late-life depression or mild cognitive impairment: A multivariate analysis of white and gray matter integrity

Brain-cognition associations in late-life depression or mild cognitive impairment: A multivariate analysis of white and gray matter integrity

Exercise and the Brain in Cardiovascular Disease: A Narrative Review

Patients with cardiovascular diseases (CVDs) (including heart failure) are at increased risk of cognitive impairment and dementia. Vascular risk factors contribute to cognitive decline through cerebral small vessel diseases, pathological brain changes, and hypoperfusion. Habitual exercise and increased cardiorespiratory fitness are associated with higher cognitive function, greater cerebral blood flow, and attenuation of the decline in gray matter volume and white matter integrity. Furthermore, moderate-vigorous exercise training has been shown to improve cognitive function in healthy middle-aged and older adults. Cardiac rehabilitation (CR) is a class 1A recommendation for patients with CVD, which involves exercise training and intensive risk factor modification. This article reviews the current evidence for the effect of exercise-based CR on cognitive function, cerebrovascular function, and brain structure in patients with CVDs. Overall, exercise-based CR appears to improve global cognitive function and attention-psychomotor functions but not language processes. Furthermore, the effect of exercise-based CR on executive function and memory is less clear and there is limited research into the effect of exercise-based CR on cerebrovascular function and brain structure.

ASSOCIATIONS AMONG LATENT FACTORS OF METABOLIC LOAD, BRAIN VOLUME, AND COGNITION IN HEALTHY AGING

Abstract Metabolic syndrome (MetS) refers to risk factors for cardiovascular disease associated with reduced physical fitness, higher disease burden, and impaired cognitive functions. Available evidence indicates that metabolic functioning is related to brain structure at the level of specific indicators, such as hypertension and voxel-based morphometry, respectively. However, attempts to relate metabolic load to brain morphology at the construct level using structural equation modeling are scarce. Here, we used confirmatory factor analysis to: (a) examine level and change associations among latent factors of metabolic risk, regional grey-matter integrity (GMI), and cognition; (b) test whether these associations differ by sex. Analyses were based on a sample of 1,100 healthy adults (52% female) aged 60 to 88 years from the Berlin Aging Study II, and included MRI data for a sub sample of 341 (37 % female) individuals. Metabolic risk was defined by waist circumference, triglycerides, fasting blood glucose, and high-density lipoprotein; regional GMI by mean diffusivity, magnetization ratio transfer ratio, and VBM-based volume estimates; and cognition, represented by the three latent constructs episodic memory, working memory and fluid intelligence. Initial analyses indicate that individuals with lower metabolic risk show greater GMI in prefrontal cortex. Also, we found that greater prefrontal GMI was associated with higher fluid intelligence and working memory in men only. Additionally, we investigated the effects of previous levels of metabolic risk and cognition on subsequent changes in both domains over time. We highlight the benefits of latent factors for establishing brain-behavior relations, and discuss putative physiological substrates of individual differences in GMI.

Present mind in aging brain: Neural associations of dispositional mindfulness in cognitive decline

AbstractBackgroundSubjects at risk of dementia, such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI), present with specific clinical symptoms, as well as functional and structural changes within the brain. Dispositional mindfulness (DM) has been linked to better cognitive performance and is associated with activation and grey matter volume of specific brain regions. It is yet unknown how DM is related to cognitive and neural parameters of those at risk of dementia.ObjectiveTo estimate the association of DM with cognitive functions, brain volumetry, functional connectivity and gray matter integrity in key regions relevant for cognition (hippocampus, anterior cingulate cortex) and self‐awareness (ventromedial prefrontal cortex (vmPFC), posterior cingulate cortex) in SCD and MCI subjects.Methods79 non‐demented older adults with memory complaints ((SCD = 48, MCI = 31) were assessed by neuropsychological tests, MRI volumetry, resting‐state fMRI‐derived connectivity and DTI. Dispositional mindfulness was examined with Breath Counting Task (BCT).ResultsParticipants with MCI showed significantly worse BCT performance in comparison to SCD (p˂0.001). In MCI, BCT performance was positively associated with connectivity (p˂0.001) and negatively related to mean gray matter diffusivity (p˂0.05) in vmPFC. No other significant associations were found between DM, MRI measures and neuropsychological variables in either group.ConclusionWorse cognition in subjects at risk of dementia may be reflected in changes in DM. Lower connectivity and worse gray matter integrity of vmPFC in MCI could play a role in the worsening of DM in this population. Longitudinal studies are needed to further clarify the relatedness of DM and neural changes elicited by neurodegeneration in people at higher risk of dementia.

Executive functioning and attention in amnestic mild cognitive impairment are related to widespread grey matter integrity

AbstractBackgroundMemory problems that are characteristic of amnestic mild cognitive impairment (aMCI) are often accompanied by difficulties in attention and executive functions (EF). Studies have consistently reported atrophy of the hippocampus and its association with memory decline in aMCI. However, it is less clear whether differences in grey matter volume (GMV) also contribute to difficulties in attention and EF. To that end, we investigated whether GMV is related to performance on a series of cognitive tests in people with aMCI.MethodGMV of 29 people with aMCI (mean age = 73.8 ± 7.6 Y, 5 F) was measured with voxel‐based morphometry and regressed against measures of task‐switching (Trail Making B‐A), inhibition (Stroop interference score), working memory (Symbol Digit Modalities), and attention (Vienna Reaction Time S1, S2, S3). Analyses were controlled for age and total intracranial volume. Because of the small sample, we used a lenient significance threshold of p &lt; 0.001 (uncorrected) and cluster size (k) &gt;= 20.ResultBetter task performance was related to higher GMV in widespread cortical regions. Task‐switching was mainly related to GMV in the bilateral insula (k = 924, 456, Z = 4.87, 3.79) and prefrontal areas (k = 846, Z = 4.35). Inhibition was related to volume in left posterior areas (k = 302, 300, Z = 3.93, 3.62), and working memory to volume in left temporal, parietal, and frontal cortices (k = 21‐88, Z = 3.28‐3.67). Attention to visual stimuli was associated with GMV of cerebellar (k = 20‐281, Z = 3.36‐3.59) and parieto‐occipital regions (k = 20‐76, Z = 3.28‐4.17), and attention to auditory stimuli mainly with prefrontal regions (k = 113, 49, Z = 3.96, 3.53). Interestingly, slower reactions to complex stimuli were related to higher GMV in occipital gyri (k = 28, Z = 3.56).ConclusionOur results suggest that EF and attention in people with aMCI are related to integrity of regions beyond those normally implicated in memory decline (e.g. the hippocampus). As investigation into aMCI is crucial for preventing disease progression, our findings should be further investigated by studies with a control group of healthy older adults.

Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy.

Network control theory is increasingly used to profile the brain's energy landscape via simulations of neural dynamics. This approach estimates the control energy required to simulate the activation of brain circuits based on structural connectome measured using diffusion magnetic resonance imaging, thereby quantifying those circuits' energetic efficiency. The biological basis of control energy, however, remains unknown, hampering its further application. To fill this gap, investigating temporal lobe epilepsy as a lesion model, we show that patients require higher control energy to activate the limbic network than healthy volunteers, especially ipsilateral to the seizure focus. The energetic imbalance between ipsilateral and contralateral temporolimbic regions is tracked by asymmetric patterns of glucose metabolism measured using positron emission tomography, which, in turn, may be selectively explained by asymmetric gray matter loss as evidenced in the hippocampus. Our investigation provides the first theoretical framework unifying gray matter integrity, metabolism, and energetic generation of neural dynamics.

Serum unsaturated phosphatidylcholines predict longitudinal basal forebrain degeneration in Alzheimer's disease.

Basal forebrain cholinergic neurons are among the first cell types affected by Alzheimer's disease pathology, but the cause of their early vulnerability is unknown. The lipid phosphatidylcholine is an essential component of the cell membrane, and phosphatidylcholine levels have been shown to be abnormal in the blood and brain of Alzheimer's disease patients. We hypothesized that disease-related changes in phosphatidylcholine metabolism may disproportionately affect basal forebrain cholinergic neurons due to their extremely large size, plasticity in adulthood and unique reliance on phosphatidylcholine for acetylcholine synthesis. To test this hypothesis, we examined whether serum phosphatidylcholine levels predicted longitudinal basal forebrain degeneration in Alzheimer's disease. All data were collected by the Alzheimer's Disease Neuroimaging Initiative. Participants were divided into a normal CSF group (controls; n = 77) and an abnormal CSF group (preclinical and clinical Alzheimer's disease; n = 236) based on their CSF ratios of phosphorylated tau and amyloid beta at baseline. Groups were age-matched (t = 0.89, P > 0.1). Serum lipidomics data collected at baseline were clustered by chemical similarity, and enrichment analyses were used to determine whether serum levels of any lipid clusters differed between the normal and abnormal CSF groups. In a subset of patients with longitudinal structural MRI (normal CSF n = 62, abnormal CSF n = 161), two timepoints of MRI data were used to calculate grey matter annual percent change for each participant. Multivariate partial least squares analyses tested for relationships between neuroimaging and lipidomics data which are moderated by CSF pathology. Our clustering analyses produced 23 serum lipid clusters. Of these clusters, six were altered in the abnormal CSF group, including a cluster of unsaturated phosphatidylcholines. In the subset of participants with longitudinal structural MRI data, a priori nucleus basalis of Meynert partial least squares analyses detected a relationship between unsaturated phosphatidylcholines and degeneration in the nucleus basalis which is moderated by Alzheimer's disease CSF pathology (P = 0.0008). Whole-brain grey matter partial least squares analyses of all 23 lipid clusters revealed that only unsaturated phosphatidylcholines and unsaturated acylcarnitines exhibited an Alzheimer's disease-dependent relationship with longitudinal degeneration (P = 0.0022 and P = 0.0018, respectively). Only the unsaturated phosphatidylcholines predicted basal forebrain degeneration in the whole-brain analyses. Overall, this study provides in vivo evidence for a selective relationship between phosphatidylcholine and basal forebrain degeneration in human Alzheimer's disease, highlighting the importance of phosphatidylcholine to basal forebrain grey matter integrity.

Long-term follow-up of neurodegenerative phenomenon in severe traumatic brain injury using MRI.

Traumatic brain injury (TBI) lesions are known to evolve over time, but the duration and consequences of cerebral remodelling are unclear. Degenerative mechanisms occurring in the chronic phase after TBI could constitute "tertiary" lesions related to the neurological outcome. The objective of this prospective study of severe TBI was to longitudinally evaluate the volume of white and grey matter structures and white matter integrity with 2 time-point multimodal MRI. Longitudinal MRI follow-up was obtained for 11 healthy controls (HCs) and 22 individuals with TBI (mean [SD] 60 [15] months after injury) along with neuropsychological assessments. TBI individuals were classified in the "favourable" recovery group (Glasgow Outcome Scale Extended [GOSE] 6-8) and "unfavourable" recovery group (GOSE 3-5) at 5 years. Variation in brain volumes (3D T1-weighted image) and white matter integrity (diffusion tensor imaging [DTI]) were quantitatively assessed over time and used to predict neurological outcome. TBI individuals showed a marked decrease in volumes of whole white matter (median -11.4% [interquartile range -5.8; -14.6]; p<0.001) and deep grey nuclear structures (-17.1% [-10.6; -20.5]; p<0.001). HCs did not show any significant change over the same time period. Median volumetric loss in several brain regions was higher with GOSE 3-5 than 6-8. These lesions were associated with lower fractional anisotropy and higher mean diffusivity at baseline. Volumetric variations were positively correlated with normalized fractional anisotropy and negatively with normalized mean diffusivity at baseline and follow-up. A computed predictive model with baseline DTI showed good accuracy to predict neurological outcome (area under the receiver operating characteristic curve 0.82 [95% confidence interval 0.81-0.83]) CONCLUSIONS: We characterised the striking atrophy of deep brain structures after severe TBI. DTI imaging in the subacute phase can predict the occurrence and localization of these tertiary lesions as well as long-term neurological outcome. ClinicalTrials.gov: NCT00577954. Registered on October 2006.

Processing speed mediates the relationship between brain structure and semantic fluency in aging

The present study has investigated how brain structure and processing speed contribute to age-related changes in semantic fluency. Groups of younger (N = 37) and older healthy participants (N = 40) completed a semantic fluency test and digit symbol test, and rested while diffusion tensor imaging (DTI) was performed. Group comparisons and correlational analysis revealed that age-related decline in semantic fluency was associated with reduction in gray matter volume in widespread fronto-temporal regions. Age-related decline in semantic fluency was also associated with decline in white matter integrity in brain tracts connecting these brain regions. Critically, hierarchical regression analysis suggested that low processing speed fully mediated the negative effects of lower gray matter volume and white matter integrity on semantic fluency. The present findings provide a support for the processing speed theory in relation to age related decline in semantic fluency, and also provide a reference for improving cognitive decline.

Scene Construction and Spatial Processing in Post-traumatic Stress Disorder.

IntroductionPost-traumatic stress disorder (PTSD) is associated with hippocampal system structural and functional impairments. Neurobiological models of PTSD posit that contextual memory for traumatic events is impaired due to hippocampal system dysfunction whilst memory of sensory details is enhanced due to amygdalar impact on sensory cortices. If hippocampal system dysfunction is a core feature of PTSD, then non-traumatic hippocampal-dependent cognitive functions such as scene construction, spatial processing, and memory should also be impaired in individuals with PTSD.MethodsForty-six trauma survivors, half diagnosed with PTSD, performed two tasks that involved spatial processing. The first was a scene construction task which requires conjuring-up spatially coherent multimodal scenarios, completed by all participants. Twenty-six participants (PTSD: n = 13) also completed a navigation task in a virtual environment, and underwent structural T1, T2 and diffusion-tensor MRI to quantify gray and white matter integrity. We examined the relationship between spatial processing, neural integrity, and symptom severity in a multiple factor analysis.ResultsOverall, patients with PTSD showed impaired performance in both tasks compared to controls. Scenes imagined by patients were less vivid, less detailed, and generated less sense of presence; importantly they had disproportionally reduced spatial coherence between details. Patients also made more errors during virtual navigation. Two components of the multiple factor analysis captured group differences. The first component explained 25% of the shared variance: participants that constructed less spatially coherent scenes also made more navigation errors and had reduced white matter integrity to long association tracts and tracts connecting the hippocampus, thalamus, and cingulate. The second component explained 20% of the variance: participants who generated fewer scene details, with less spatial coherence between them, had smaller hippocampal, parahippocampal and isthmus cingulate volumes. These participants also had increased white matter integrity to the right hippocampal cingulum bundle.ConclusionOur results suggest that patients with PTSD are impaired at imagining even neutral spatially coherent scenes and navigating through a complex spatial environment. Patients that showed reduced spatial processing more broadly had reduced hippocampal systems volumes and abnormal white matter integrity to tracts implicated in multisensory integration.

Diminished Structural Brain Integrity in Long-term Cannabis Users Reflects a History of Polysubstance Use

BackgroundCannabis legalization and use are outpacing our understanding of its long-term effects on brain and behavior, which is fundamental for effective policy and health practices. Existing studies are limited by small samples, cross-sectional measures, failure to separate long-term from recreational use, and inadequate control for other substance use. Here, we address these limitations by determining the structural brain integrity of long-term cannabis users in the Dunedin Study, a longitudinal investigation of a population-representative birth cohort followed to midlife. MethodsWe leveraged prospective measures of cannabis, alcohol, tobacco, and other illicit drug use in addition to structural neuroimaging in 875 study members at age 45 to test for differences in both global and regional gray and white matter integrity between long-term cannabis users and lifelong nonusers. We additionally tested for dose-response associations between continuous measures of cannabis use and brain structure, including careful adjustments for use of other substances. ResultsLong-term cannabis users had a thinner cortex, smaller subcortical gray matter volumes, and higher machine learning–predicted brain age than nonusers. However, these differences in structural brain integrity were explained by the propensity of long-term cannabis users to engage in polysubstance use, especially with alcohol and tobacco. ConclusionsThese findings suggest that diminished midlife structural brain integrity in long-term cannabis users reflects a broader pattern of polysubstance use, underlining the importance of understanding comorbid substance use in efforts to curb the negative effects of cannabis on brain and behavior as well as establish more effective policy and health practices.

Altered grey matter integrity and network vulnerability relate to epilepsy occurrence in patients with multiple sclerosis.

The aim of this study was to investigate the relevance of compartmentalized grey matter (GM) pathology and network reorganization in multiple sclerosis (MS) patients with concomitant epilepsy. From 3-T magnetic resonance imaging scans of 30 MS patients with epilepsy (MSE group; age 41 ± 15 years, 21 females, disease duration 8 ± 6 years, median Expanded Disability Status Scale [EDSS] score 3), 60 MS patients without epilepsy (MS group; age 41 ± 12 years, 35 females, disease duration 6 ± 4 years, EDSS score 2), and 60 healthy subjects (HS group; age 40 ± 13 years, 27 females) the regional volumes of GM lesions and of cortical, subcortical and hippocampal structures were quantified. Network topology and vulnerability were modelled within the graph theoretical framework. Receiver-operating characteristic (ROC) curve analysis was applied to assess the accuracy of GM pathology measures to discriminate between MSE and MS patients. Higher lesion volumes within the hippocampus, mesiotemporal cortex and amygdala were detected in the MSE compared to the MS group (all p &lt; 0.05). The MSE group had lower cortical volumes mainly in temporal and parietal areas compared to the MS and HS groups (all p &lt; 0.05). Lower hippocampal tail and presubiculum volumes were identified in both the MSE and MS groups compared to the HS group (all p &lt; 0.05). Network topology in the MSE group was characterized by higher transitivity and assortativity, and higher vulnerability compared to the MS and HS groups (all p &lt; 0.05). Hippocampal lesion volume yielded the highest accuracy (area under the ROC curve 0.80 [0.67-0.91]) in discriminating between MSE and MS patients. High lesion load, altered integrity of mesiotemporal GM structures, and network reorganization are associated with a greater propensity for epilepsy occurrence in people with MS.

Microstructural Gray Matter Integrity Deteriorates After an Ischemic Stroke and Is Associated with Processing Speed.

Microstructural changes after an ischemic stroke (IS) have mainly been described in white matter. Data evaluating microstructural changes in gray matter (GM) remain scarce. The aim of the present study was to evaluate the integrity of GM on longitudinal data using mean diffusivity (MD), and its influence on post-IS cognitive performances. A prospective study was conducted, including supra-tentorial IS patients without pre-stroke disability. A cognitive assessment was performed at baseline and 1year, including a Montreal Cognitive Assessment, an Isaacs set test, and a Zazzo cancelation task (ZCT): completion time and number of errors. A 3-T brain MRI was performed at the same two time-points, including diffusion tensor imaging for the assessment of GM MD. GM volume was also computed, and changes in GM volume and GM MD were evaluated, followed by the assessment of the relationship between these structural changes and changes in cognitive performances. One hundred and four patients were included (age 68.5 ± 21.5, 38.5% female). While no GM volume loss was observed, GM MD increased between baseline and 1year. The increase of GM MD in left fronto-temporal regions (dorsolateral prefrontal cortex, superior and medial temporal gyrus, p < 0.05, Threshold-Free Cluster Enhancement, 5000 permutations) was associated with an increase time to complete ZCT, regardless of demographic confounders, IS volume and location, GM, and white matter hyperintensity volume. GM integrity deterioration was thus associated with processing speed slowdown, and appears to be a biomarker of cognitive frailty. This broadens the knowledge of post-IS cognitive impairment mechanisms.

Mapping blood traits to structural organization of the brain in rhesus monkeys.

Hematological and biochemical blood traits have been linked to brain structural characteristics in humans. However, the relationship between these two domains has not been systematically explored in nonhuman primates, which are crucial animal models for understanding the mechanisms of brain function and developing therapeutics for various disorders. Here we investigated the associations between hematological/biochemical parameters and the brain's gray matter volume and white matter integrity derived from T1-weighted and diffusion magnetic resonance imaging in 36 healthy macaques. We found that intersubject variations in basophil count and hemoglobin levels correlated with gray matter volumes in the anterior cingulum, prefrontal cortex, and putamen. Through interactions between these key elements, the blood parameters' covariation network was linked with that of the brain structures, forming overarching networks connecting blood traits with structural brain features. These networks exhibited hierarchical small-world architecture, indicating highly effective interactions between their constituent elements. In addition, different subnetworks of the brain areas or fiber tracts tended to correlate with unique groups of blood indices, revealing previously unknown brain structural organization. These results provide a quantitative characterization of the interactions between blood parameters and brain structures in macaques and may increase the understanding of the body-brain relationship and the pathogenesis of relevant disorders.

Maternal deprivation and milk replacement affect the integrity of gray and white matter in the developing lamb brain.

The psychoendocrine evaluation of lamb development has demonstrated that maternal deprivation and milk replacement alters health, behavior, and endocrine profiles. While lambs are able to discriminate familiar and non-familiar conspecifics (mother or lamb), only lambs reared with their mother develop such clear social discrimination or preference. Lambs reared without mother display no preference for a specific lamb from its own group. Differences in exploratory and emotional behaviors between mother-reared and mother-deprived lambs have also been reported. As these behavioural abilities are supported by the brain, we hypothesize that rearing with maternal deprivation and milk replacement leads to altered brain development and maturation. To test this hypothesis, we examined brain morphometric and microstructural variables extracted from in vivo T1-weighted and diffusion-weighted magnetic resonance images acquired longitudinally (1 week, 1.5 months, and 4.5 months of age) in mother-reared and mother-deprived lambs. From the morphometric variables the caudate nuclei volume was found to be smaller for mother-deprived than for mother-reared lambs. T1-weighted signal intensity and radial diffusivity were higher for mother-deprived than for mother-reared lambs in both the white and gray matters. The fractional anisotropy of the white matter was lower for mother-deprived than for mother-reared lambs. Based on these morphometric and microstructural characteristics we conclude that maternal deprivation delays and affects lamb brain growth and maturation.

Brain Morphometry Associated With Response to Levodopa and Deep Brain Stimulation in Parkinson Disease

ObjectivesWhether treatment response in patients with Parkinson disease depends on brain atrophy is insufficiently understood. The goal of this study is to identify specific atrophy patterns associated with response to dopaminergic therapy and deep brain stimulation. Materials and MethodsIn this study, we analyzed the association of gray matter brain atrophy patterns, as identified by voxel-based morphometry, with acute response to levodopa (N = 118) and subthalamic nucleus deep brain stimulation (N = 39). Motor status was measured as a change in points on the Unified Parkinson’s Disease Rating Scale III score. Baseline values were obtained before surgery, after cessation of dopaminergic medication for at least 12 hours; response to medication was assessed after administration of a standardized dose of levodopa. Response to deep brain stimulation was measured three months after surgery in the clinical condition after withdrawal of dopaminergic medication. ResultsAlthough frontoparietal brain gray matter loss was associated with subpar response to deep brain stimulation, there was no significant link between brain atrophy and response to levodopa. ConclusionWe conclude that response to deep brain stimulation relies on gray matter integrity; hence, gray matter loss may present a risk factor for poor response to deep brain stimulation and may be considered when making decision regarding clinical practice.

Sex differences in cortical thickness and diffusion properties in patients with traumatic brain injury: a pilot study

ABSTRACT Objective Cortical thickness and diffusion properties are important measures of gray and white matter integrity in those with traumatic brain injury (TBI). Many studies show that healthy adult females have greater cortical thickness than males across numerous brain sites. In this study, we explored this sex difference in patients with TBI. Method Participants consisted of 32 patients with TBI and 21 neurologically healthy controls. All were scanned by magnetic resonance imaging (MRI). Differences in cortical thickness and diffusion properties were examined between groups (i.e., TBI/control, male/female). Results Patients with TBI had more cortical thinning (both hemispheres) compared to controls. They also showed decreased fractional anisotropy (FA) for several major white matter tracts. Healthy females had significantly greater cortical thickness compared to healthy males. However, this difference was smaller among the patients with TBI. We found no sex differences in diffusion properties. There were moderate correlations between cortical thickness, diffusion properties, and cognitive performance, as measured by the Trail Making Test B. Conclusion These findings contribute to a growing discussion on sex differences in cortical thickness and diffusion properties. Sexual dimorphism could necessitate different clinical profiles, targets, and rehabilitation strategies in patients with TBI.