Enhanced structural connectivity within the motor loop in professional boxers prior to a match.

Professional boxers train to reduce their body mass before a match to refine their body movements. To test the hypothesis that the well-defined movements of boxers are represented within the motor loop (cortico-striatal circuit), we first elucidated the brain structure and functional connectivity specific to boxers and then investigated plasticity in relation to boxing matches. We recruited 21 male boxers 1 month before a match (Time1) and compared them to 22 age-, sex-, and body mass index (BMI)-matched controls. Boxers were longitudinally followed up within 1 week prior to the match (Time2) and 1 month after the match (Time3). The BMIs of boxers significantly decreased at Time2 compared with those at Time1 and Time3. Compared to controls, boxers presented significantly higher gray matter volume in the left putamen, a critical region representing motor skill training. Boxers presented significantly higher functional connectivity than controls between the left primary motor cortex (M1) and left putamen, which is an essential region for establishing well-defined movements. Boxers also showed significantly higher structural connectivity in the same region within the motor loop from Time1 to Time2 than during other periods, which may represent the refined movements of their body induced by training for the match.

Putamen volume predicts real-time fMRI neurofeedback learning success across paradigms and neurofeedback target regions.

Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning this finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback-guided self-regulation.

Influence of genetic variations in IL1B on brain region volumes in bipolar patients and controls.

Involvement of the immune system has been implicated in the etiology and pathophysiology of mood disorders, including bipolar disorder. Neuroimaging studies have reported structural brain pathology in bipolar disorder patients, and both levels of and genetic variants in cytokines have been associated with altered volumes of brain regions. The aim of this study was to investigate associations between single nucleotide polymorphisms in the gene coding for the pro-inflammatory cytokine interleukin-1 beta (IL1B) and whole brain grey matter volume, as well as volumes of several brain regions shown to be of importance in mood disorders. Structural magnetic resonance imaging and vertex-based morphometry were used to obtain volume of different brain regions in subjects with bipolar disorder (n=188) and healthy controls (n=54). Four IL1B polymorphisms were genotyped: rs1143623, rs1143627, and rs16944 in the promoter region together with the synonymous variant rs1143634 in the IL1B gene. The genotype distribution did not differ between bipolar subjects and controls. The T allele at rs16944 and the C allele at rs1143627 were associated with increased volumes of the putamen of the left hemisphere in patients and controls, which lends support to the role of this immune system mediator for brain structure.

Smaller Volume in Left-Lateralized Brain Structures Correlates with Greater Experience of Negative Non-target Emotions in Neurodegenerative Diseases.

Subjective emotional experience that is congruent with a given situation (i.e., target emotions) is critical for human survival (e.g., feeling disgusted in response to contaminated food motivates withdrawal behaviors). Neurodegenerative diseases including frontotemporal dementia and Alzheimer's disease affect brain regions critical for cognitive and emotional functioning, resulting in increased experience of emotions incongruent with the situation (i.e., non-target emotions, such as feeling happy when seeing someone grieving). We examined neuroanatomical correlates of subjective experience of non-target emotions in 147 patients with neurodegenerative diseases and 26 healthy individuals. Participants watched three films intended to elicit particular target emotions and rated their experience of negative and positive target and non-target emotions after watching each film. We found that smaller volume in left hemisphere regions (e.g., caudate, putamen, and dorsal anterior insula) was associated with greater experience of negative non-target emotions. Follow-up analyses confirmed that these effects were left-lateralized. No correlates emerged for positive non-target emotions. These findings suggest that volume loss in left-hemisphere regions produces a more diffuse, incongruent experience of non-target emotions. These findings provide a potential neuroanatomical basis for understanding how subjective emotional experience is constructed in the brain and how this can be disrupted in neurodegenerative disease.

The topology of higher-order complexes associated with brain hubs in human connectomes.

Higher-order connectivity in complex systems described by simplexes of different orders provides a geometry for simplex-based dynamical variables and interactions. Simplicial complexes that constitute a functional geometry of the human connectome can be crucial for the brain complex dynamics. In this context, the best-connected brain areas, designated as hub nodes, play a central role in supporting integrated brain function. Here, we study the structure of simplicial complexes attached to eight global hubs in the female and male connectomes and identify the core networks among the affected brain regions. These eight hubs (Putamen, Caudate, Hippocampus and Thalamus-Proper in the left and right cerebral hemisphere) are the highest-ranking according to their topological dimension, defined as the number of simplexes of all orders in which the node participates. Furthermore, we analyse the weight-dependent heterogeneity of simplexes. We demonstrate changes in the structure of identified core networks and topological entropy when the threshold weight is gradually increased. These results highlight the role of higher-order interactions in human brain networks and provide additional evidence for (dis)similarity between the female and male connectomes.

Neuroanatomy of transgender persons in a Non-Western population and improving reliability in clinical neuroimaging.

Although the neuroanatomy of transgender persons is slowly being charted, findings are presently discrepant. Moreover, the major body of work has focused on Western populations. One important factor is the issue of power and low signal-to-noise (SNR) ratio in neuroimaging studies of rare study populations including endocrine or neurological patient groups. The present study focused on the structural neuroanatomy of a Non-Western (Iranian) sample of 40 transgender men (TM), 40 transgender women (TW), 30 cisgender men (CM), and 30 cisgender women (CW), while assessing whether the reliability of findings across structural anatomical measures including gray matter volume (GMV), cortical surface area (CSA), and cortical thickness (CTh) could be increased by using two back-to-back within-session structural MRI scans. Overall, findings in transgender persons were more consistent with sex assigned at birth in GMV and CSA, while no group differences emerged for CTh. Repeated measures analysis also indicated that having a second scan increased SNR in all regions of interest, most notably bilateral frontal poles, pre- and postcentral gyri and putamina. The results suggest that a simple time and cost-effective measure to improve SNR in rare clinical populations with low prevalence rates is a second anatomical scan when structural MRI is of interest.

Detecting and visualizing differences in brain structures with SPHARM and functional data analysis.

A new procedure for classifying brain structures described by SPHARM is presented. We combine a dimension reduction technique (functional principal component analysis or functional independent component analysis) with stepwise variable selection for linear discriminant classification. This procedure is compared with many well-known methods in a novel classification problem in neuroeducation, where the reversal error (a common error in mathematical problem solving) is analyzed by using the left and right putamens of 33 participants. The comparison shows that our proposal not only provides outstanding performance in terms of predictive power, but it is also valuable in terms of interpretation, since it yields a linear discriminant function for 3D structures.

Gray matter volume differences between lower, average, and higher pain resilience subgroups.

Resilience refers to the capacity to function well despite adversity and facilitates adaptation to various stressors, including pain. Previous studies have operationalized resilience via questionnaires or task performance behaviors that do not always correlate with one another and tested extreme (lower vs. higher) resilience subgroup differences that do not permit the assessment of nonlinear associations between resilience and brain matter volume. To address these limitations, we identified high (HPR, N = 21), moderate (MPR, N = 20), and low (LPR, N = 16) pain resilience subgroups from a trait resilience questionnaire as well as behavioral performance on a laboratory pain task. Subsequently, resilience subgroup differences in gray matter volume (GMV) and behavior responses to a novel numerical interference task (NIT) were assessed. Behavioral results indicated the LPR subgroup was slower in responding to NIT trials accompanied by pain compared to MPR, and especially, HPR subgroups. Voxel-based morphology analyses indicated the LPR subgroup had more GMV in the left postcentral gyrus than did MPR and HPR subgroups. LPR and MPR subgroups displayed larger GMV in the right inferior temporal gyrus than did the HPR subgroup. Nonlinear relations reflecting less regional GMV in the right inferior frontal gyrus (IFG)/putamen, orbitofrontal cortex and left IFG/insula were also observed for the MPR subgroup compared to LPR and HPR subgroups. In sum, lower pain resilience is characterized, in part, by comparatively greater GMV in pain processing regions and reduced GMV in "resilience" regions, though regional GMV also has several nonlinear associations with resilience.

Functionally matched domains in parietal-frontal cortex of monkeys project to overlapping regions of the striatum.

Projections of small regions (domains) of primary motor cortex (M1), premotor cortex (PMC) and posterior parietal cortex (PPC) to the striatum of squirrel monkeys were revealed by restricted injections of anterograde tracers. As many as 8 classes of action-specific domains can be identified in PPC, as well as in PMC and M1, and some have been identified for injections by the action evoked by 0.5 s trains of electrical microstimulation. Injections of domains in all three cortical regions labeled dense patches of terminations in the matrix of the ipsilateral putamen, while providing sparse or no projections to corresponding regions of the contralateral putamen. When two or three of these domains were injected with different tracers, projection fields in the putamen were highly overlapped for injections in functionally matched domains across cortical areas, but were highly segregated for injections placed in functionally mismatched domains. While not all classes of domains were studied, the results suggest that the striatum potentially has separate representations of eight or more classes of actions that receive inputs from domains in three or more cortical regions in sensorimotor cortex. The overlap/segregation of cortico-striatal projections correlates with the strength of cortico-cortical connections between injected motor areas.

Shared genetic etiology between anxiety disorders and psychiatric and related intermediate phenotypes.

BACKGROUND: Psychiatric disorders and related intermediate phenotypes are highly heritable and have a complex, overlapping polygenic architecture. A large-scale genome-wide association study (GWAS) of anxiety disorders identified genetic variants that are significant on a genome-wide. The current study investigated the genetic etiological overlaps between anxiety disorders and frequently cooccurring psychiatric disorders and intermediate phenotypes. METHODS: Using case-control and factor score models, we investigated the genetic correlations of anxiety disorders with eight psychiatric disorders and intermediate phenotypes [the volumes of seven subcortical brain regions, childhood cognition, general cognitive ability and personality traits (subjective well-being, loneliness, neuroticism and extraversion)] from large-scale GWASs (n = 7556-298 420) by linkage disequilibrium score regression. RESULTS: Among psychiatric disorders, the risk of anxiety disorders was positively genetically correlated with the risks of major depressive disorder (MDD) (rg ± standard error = 0.83 ± 0.16, p = 1.97 × 10-7), schizophrenia (SCZ) (0.28 ± 0.09, p = 1.10 × 10-3) and attention-deficit/hyperactivity disorder (ADHD) (0.34 ± 0.13, p = 8.40 × 10-3). Among intermediate phenotypes, significant genetic correlations existed between the risk of anxiety disorders and neuroticism (0.81 ± 0.17, p = 1.30 × 10-6), subjective well-being (-0.73 ± 0.18, p = 4.89 × 10-5), general cognitive ability (-0.23 ± 0.08, p = 4.70 × 10-3) and putamen volume (-0.50 ± 0.18, p = 5.00 × 10-3). No other significant genetic correlations between anxiety disorders and psychiatric or intermediate phenotypes were observed (p > 0.05). The case-control model yielded stronger genetic effect sizes than the factor score model. CONCLUSIONS: Our findings suggest that common genetic variants underlying the risk of anxiety disorders contribute to elevated risks of MDD, SCZ, ADHD and neuroticism and reduced quality of life, putamen volume and cognitive performance. We suggest that the comorbidity of anxiety disorders is partly explained by common genetic variants.

Neural substrates underlying episodic future thinking: A voxel-based morphometry study.

Episodic future thinking (EFT), the mental ability of projecting oneself into the future to pre-experience an event, has strong adaptive value for allowing people to consider potential consequences before taking actions. EFT includes two important components: the ability to construct detailed and vivid scenes of future events to achieve a goal (measured here by the EFT-sensory perceptual qualities scale) and the ability to subjectively experience "mental time travel" in which the person feels oneself to be in the future (measured here by the EFT-Autonoetic consciousness scale). However, little is known about the neuroanatomical structures of EFT. To shed light on this question, we employed voxel-based morphometry (VBM) to investigate the neural substrates underlying EFT. In Sample 1 (135 participants), EFT-sensory perceptual qualities was positively correlated with the gray matter (GM) volume of the hippocampus and putamen. EFT-Autonoetic consciousness was positively correlated with GM volume of the insula and amygdala, and negatively correlated with GM volumes of the medial frontal gyrus. The verification results from Sample 2 (59 participants) found that EFT-sensory perceptual qualities can be predicted by the GM volumes of the hippocampus and putamen, and EFT-Autonoetic consciousness can be predicted by the GM volumes of insula and amygdala. The present findings suggest that the hippocampus, putamen, and amygdala and insula are key regions for scene construction, goal-directed processing, and emotion respectively, and play important roles in the underlying structural neural substrates of EFT.

Microneuroanatomy of the Anterior Frontal Laser Trajectory to the Insula.

BACKGROUND: Magnetic resonance imaging-guided laser interstitial thermal therapy (LITT) is an emerging minimally invasive procedure for the treatment of deep intracranial lesions. Insular lesions are challenging to treat because of the risk of damaging important surrounding structures. The precise knowledge of the neural structures that are at risk along the trajectory and during the ablation is essential to reduce associated complications. This study aims to describe the relevant anatomy of the anterior frontal LITT trajectory to the insular region by using sectional anatomy and fiber dissection technique. METHODS: Three silicone-injected cadaveric heads were used to implant laser catheters bilaterally to the insular region by using a frameless stereotactic technique from a frontal approach. Sections were cut in both the oblique axial plane parallel to the trajectory and in the coronal plane. White matter fiber dissections were used to establish the tracts related to the laser trajectory from lateral to medial and medial to lateral. RESULTS: Supraorbital regions were selected as entry points. After crossing the frontal bone, the track intersected the inferior frontal lobe. The catheter was illustrated reaching the insular region medial to the inferior fronto-occipital fasciculus and insular cortex, and superior to the uncinate fasciculus. The uncinate fasciculus, extreme capsule, claustrum, external capsule, and putamen were traversed, preserving the major vascular structures. CONCLUSIONS: Independent of the insular area treated, an understanding of the neuroanatomy related to the anterior frontal laser trajectory is essential to improve the ability to perform LITT of this challenging region.

The myeloarchitecture of impulsivity: premature responding in youth is associated with decreased myelination of ventral putamen.

Impulsivity has been suggested as a neurocognitive endophenotype conferring risk across a number of neuropsychiatric conditions, including substance and behavioural addictions, eating disorders, and attention deficit/hyperactivity disorder. We used a paradigm with interspecies translation validity (the four-choice serial reaction time task, 4CSRTT) to assess 'waiting' impulsivity in a youth sample (N = 99, aged 16-26 years). We collected magnetization prepared two rapid acquisition gradient echo (MP2RAGE) scans, which enabled us to measure R1, the longitudinal relaxation rate, a parameter closely related to tissue myelin content, as well as quantify grey matter volume. We also assessed inhibitory control (commission errors) on a Go/NoGo task and measured decisional impulsivity (delay discounting) using the Monetary Choice Questionnaire (MCQ). We found R1 of the bilateral ventral putamen was negatively correlated with premature responding, the index of waiting impulsivity on the 4CSRTT. Heightened impulsivity in youth was significantly and specifically associated with lower levels of myelination in the ventral putamen. Impulsivity was not associated with grey matter volume. The association with myelination was specific to waiting impulsivity: R1 was not associated with decisional impulsivity on the MCQ or inhibitory control on the Go/NoGo task. We report that heightened waiting impulsivity, measured as premature responding on the 4CSRTT, is specifically associated with lower levels of ventral putaminal myelination, measured using R1. This may represent a neural signature of vulnerability to diseases associated with excessive impulsivity and demonstrates the added explanatory power of quantifying the mesoscopic organization of the human brain, over and above macroscopic volumetric measurements.

Shape-related characteristics of age-related differences in subcortical structures.

OBJECTIVES: With an increasing aging population, it is important to understand biological markers of aging. Subcortical volume is known to differ with age; additionally considering shape-related characteristics may provide a better index of age-related differences. Fractal dimensionality is more sensitive to age-related differences, but is borne out of mathematical principles, rather than neurobiological relevance. We considered four distinct measures of shape and how they relate to aging and fractal dimensionality: surface-to-volume ratio, sphericity, long-axis curvature, and surface texture. METHODS: Structural MRIs from a combined sample of over 600 healthy adults were used to measure age-related differences in the structure of the thalamus, putamen, caudate, and hippocampus. For each, volume and fractal dimensionality were calculated, as well as four distinct shape measures. These measures were examined for their utility in explaining age-related variability in brain structure. RESULTS: The four shape measures were able to account for 80%-90% of the variance in fractal dimensionality. Of the distinct shape measures, surface-to-volume ratio was the most sensitive biomarker. CONCLUSION: Though volume is often used to characterize inter-individual differences in subcortical structures, our results demonstrate that additional measures can be useful complements. Our results indicate that shape characteristics are useful biological markers of aging.

Volumetric gray matter measures of amygdala and accumbens in childhood overweight/obesity.

OBJECTIVES: Neuroimaging data suggest that pediatric overweight and obesity are associated with morphological alterations in gray matter (GM) brain structures, but previous studies using mainly voxel-based morphometry (VBM) showed inconsistent results. Here, we aimed to examine the relationship between youth obesity and the volume of predefined reward system structures using magnetic resonance (MR) volumetry. We also aimed to complement volumetry with VBM-style analysis. METHODS: Fifty-one Caucasian young subjects (32 females; mean age: 13.8±1.9, range: 10.2-16.5 years) were included. Subjects were selected from a subsample of the I.Family study examined in the Hungarian center. A T1-weighted 1 mm3 isotropic resolution image was acquired. Age- and sex-standardized body mass index (zBMI) was assessed at the day of MRI and ~1.89 years (mean±SD: 689±188 days) before the examination. Obesity related GM alterations were investigated using MR volumetry in five predefined brain structures presumed to play crucial roles in body weight regulation (hippocampus, amygdala, accumbens, caudate, putamen), as well as whole-brain and regional VBM. RESULTS: The volumes of accumbens and amygdala showed significant positive correlations with zBMI, while their GM densities were inversely related to zBMI. Voxel-based GM mass also showed significant negative correlation with zBMI when investigated in the predefined amygdala region, but this relationship was mediated by GM density. CONCLUSIONS: Overweight/obesity related morphometric brain differences already seem to be present in children/adolescents. Our work highlights the disparity between volume and VBM-derived measures and that GM mass (combination of volume and density) is not informative in the context of obesity related volumetric changes. To better characterize the association between childhood obesity and GM morphometry, a combination of volumetric segmentation and VBM methods, as well as future longitudinal studies are necessary. Our results suggest that childhood obesity is associated with enlarged structural volumes, but decreased GM density in the reward system.

Genome-wide association studies of brain imaging phenotypes in UK Biobank.

The genetic architecture of brain structure and function is largely unknown. To investigate this, we carried out genome-wide association studies of 3,144 functional and structural brain imaging phenotypes from UK Biobank (discovery dataset 8,428 subjects). Here we show that many of these phenotypes are heritable. We identify 148 clusters of associations between single nucleotide polymorphisms and imaging phenotypes that replicate at P < 0.05, when we would expect 21 to replicate by chance. Notable significant, interpretable associations include: iron transport and storage genes, related to magnetic susceptibility of subcortical brain tissue; extracellular matrix and epidermal growth factor genes, associated with white matter micro-structure and lesions; genes that regulate mid-line axon development, associated with organization of the pontine crossing tract; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide insights into the genetic architecture of the brain that are relevant to neurological and psychiatric disorders, brain development and ageing.

Neuroanatomical correlates of grit: Growth mindset mediates the association between gray matter structure and trait grit in late adolescence.

There is a long-standing interest in exploring the factors related to student achievement. As a newly explored personality trait, grit is defined as a person's tendency to pursue long-term goals with continual perseverance and passion, and grit plays a critical role in student achievement. Increasing evidence has shown that growth mindset, the belief that one's basic abilities are malleable and can be developed through effort, is a potential factor for cultivating grit. However, less is known about the association between grit and the brain and the role of growth mindset in this association. Here, we utilized voxel-based morphometry to examine the neuroanatomical correlates of grit in 231 healthy adolescent students by performing structural magnetic resonance imaging. The whole-brain regression analyses revealed that the regional gray matter volume (rGMV) in the left dorsolateral prefrontal cortex (DLPFC) negatively predicted grit. In contrast, the rGMV in the right putamen positively predicted grit. Furthermore, mediating analyses suggested that growth mindset served as a mediator in the association between left DLPFC volume and grit. Our results persisted even after controlling for the influences of self-control and delayed gratification. Overall, our study presents novel evidence for the neuroanatomical basis of grit and highlights that growth mindset might play an essential role in cultivating a student's grit level.

The neuromorphological caudate-putaminal clustering of neostriate interneurons: Kohonen self-organizing maps and supervised artificial neural networks with multivariate analysis.

AIMS: The objective of this study is to investigate the possibility of the neuromorphotopological clustering of neostriate interneurons (NSIN) and their consequent classification into caudate (CIN) and putaminal neuron type (PIN), according to the nuclear localization of the neurons. It tends to discover whether these two topological neuron types are morphologically different. MATERIAL AND METHODS: The binary images of adult human NSIN are used for the purposes of the analysis. The total of the 46 neuromorphological parameters is used. They can be divided into the following classes: neuron surface/size, shape, compartmental length, dendritic branching, neuromorphological organization and complexity. The clustering is performed by an algorithm which consists of the steps of predictor extraction, multivariate cluster analysis set and cluster identification. RESULTS: Unifactor analysis extracted as significant the following parameters: neurosoma/perikaryon size (AS), the size of a dendritic tree (ADT), the size of a dendritic field area (ADF), the size of an entire neuron field area (ANF), the size of a perineuronal space (APNS), the fractal dimension of a neuron (DN), the index of perikaryon asymmetry (MS), total dendritic length (L), standardized total dendritic length (Lst), standardized dendritic width (DWDTHst), dendritic centrifugal branching order (DCBO), branching polarization index (MDCBO), dendritic partial surface (DSP), the fractal dimension of a skeletonized neuron image (DS), the index of maximal complex density of a dendritic tree (NMAX) and standardized dendritic branching pattern complexity (CDF/ADFst). The cluster analysis set together with Kohonen self-organizing maps and backpropagation feed-forward artificial neural networks confirmed the classification on both unsupervised and supervised manner, respectively. As a final step, the cluster identification is performed by an assignment of each neuron to a particular cluster. CONCLUSION: NSIN can be classified neuromorphologically into CIN and PIN type. Differences are expected since the two nuclei have different functional roles in processing the information involved in volitional movement control.

Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure.

Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5'UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10-8). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen.

Mis-segmentation in voxel-based morphometry due to a signal intensity change in the putamen.

The aims of this study were to demonstrate an association between changes in the signal intensity of the putamen on three-dimensional T1-weighted magnetic resonance images (3D-T1WI) and mis-segmentation, using the voxel-based morphometry (VBM) 8 toolbox. The sagittal 3D-T1WIs of 22 healthy volunteers were obtained for VBM analysis using the 1.5-T MR scanner. We prepared five levels of 3D-T1WI signal intensity (baseline, same level, background level, low level, and high level) in regions of interest containing the putamen. Groups of smoothed, spatially normalized tissue images were compared to the baseline group using a paired t test. The baseline was compared to the other four levels. In all comparisons, significant volume changes were observed around and outside the area that included the signal intensity change. The present study demonstrated an association between a change in the signal intensity of the putamen on 3D-T1WI and changed volume in segmented tissue images.