Late-Life High Blood Pressure and Enlarged Perivascular Spaces in the Putaminal Regions of Community-Dwelling Japanese Older Persons

BACKGROUND

Enlarged perivascular spaces (EPVS) of the brain may be involved in dementia, such as Alzheimer's disease and cerebral small vessel disease (CSVD). Hypertension has been reported to be a risk factor for dementia and CSVD, but the association between blood pressure (BP) and perivascular spaces is still unclear. The aim of this study was to determine the association between BP and EPVS volumes and to examine the interactions of relevant factors.

METHODS

A total of 9296 community-dwelling subjects aged ≥65 years participated in a brain magnetic resonance imaging and health status screening examination. Perivascular volume was measured using a software package based on deep learning that was developed in-house. The associations between BP and EPVS volumes were examined by analysis of covariance and multiple regression analysis.

RESULTS

Mean EPVS volumes increased significantly with rising systolic and diastolic BP levels (P for trend = .003, P for trend<.001, respectively). In addition, mean EPVS volumes increased significantly for every 1-mmHg-increment in systolic and diastolic BPs (both P values <.001). These significant associations were still observed in the sensitivity analysis after excluding subjects with dementia.

CONCLUSIONS

The present data suggest that higher systolic and diastolic BP levels are associated with greater EPVS volumes in cognitively normal older people.

Association between Gray and White Matter Lesions and Its Involvement in Clinical Symptoms of Alzheimer's-Type Dementia

BACKGROUND

Not only gray matter lesions (GMLs) but also white matter lesions (WMLs) can play important roles in the pathology of Alzheimer's disease (AD). The progression of cognitive impairment (CI) and behavioral and psychological symptoms of dementia (BPSD) might be caused by a concerted effect of both GML and WML.

OBJECTIVE

This study aimed to investigate the association between GML and WML and how they are involved in the symptoms of CI and BPSD in dementia patients by means of imaging technology.

METHODS

Patients in our memory clinic, who were diagnosed with AD-type dementia or amnestic mild cognitive impairment (aMCI) and had undergone both single-photon emission computed tomography (SPECT) and brain MRI, were consecutively enrolled (n = 156; 61 males and 95 females; 79.8 ± 7.4 years old). Symptoms of CI and BPSD were obtained from patients' medical records. For the analysis of GMLs and WMLs, SPECT data and MRI T1-weighted images were used, respectively. This study followed the Declaration of Helsinki, and all procedures were approved by the institutional ethics committee.

RESULTS

According to a multivariate analysis, disorientation and disturbed attention demonstrated a relationship between the precuneus and WMLs in both hemispheres. Hyperactivity in BPSD showed multiple correlations between GMLs on both sides of the frontal cortex and WMLs. Patients with aMCI presented more multiple correlations between GMLs and WMLs compared with those with AD-type dementia regarding dementia symptoms including BPSD.

CONCLUSION

The interaction between GMLs and WMLs may vary depending on the symptoms of CI and BPSD. Hyperactivity in BPSD may be affected by the functional relationship between GMLs and WMLs in the left and right hemispheres. The correlation between GMLs and WMLs may be changing in AD-type dementia and aMCI.

Impact of hs-CRP concentration on brain structure alterations and cognitive trajectory in Alzheimer's disease

Introduction

Present study was to investigate hs-CRP concentration, brain structural alterations, and cognitive function in the context of AD [Subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD].

Methods

We retrospectively included 313 patients (Mean age = 76.40 years, 59 SCD, 101 MCI, 153 AD) in a cross-sectional analysis and 91 patients (Mean age = 75.83 years, 12 SCD, 43 MCI, 36 AD) in a longitudinal analysis. Multivariable linear regression was conducted to investigate the relationship between hs-CRP concentration and brain structural alterations, and cognitive function, respectively.

Results

Hs-CRP was positively associated with gray matter volume in the left fusiform (β = 0.16, pFDR = 0.023) and the left parahippocampal gyrus (β = 0.16, pFDR = 0.029). Post hoc analysis revealed that these associations were mainly driven by patients with MCI and AD. The interaction of diagnosis and CRP was significantly associated with annual cognitive changes (β = 0.43, p = 0.008). Among these patients with AD, lower baseline CRP was correlated with greater future cognitive decline (r = -0.41, p = 0.013).

Conclusion

Our study suggests that increased hs-CRP level may exert protective effect on brain structure alterations and future cognitive changes among patients already with cognitive impairment.

Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study: Rationale, Design, and Background

The Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study (TMM Brain MRI Study) was established to collect multimodal information through neuroimaging and neuropsychological assessments to evaluate the cognitive function and mental health of residents who experienced the Great East Japan Earthquake (GEJE) and associated tsunami. The study also aimed to promote advances in personalized healthcare and medicine related to mental health and cognitive function among the general population. We recruited participants for the first (baseline) survey starting in July 2014, enrolling individuals who were participating in either the TMM Community-Based Cohort Study (TMM CommCohort Study) or the TMM Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). We collected multiple magnetic resonance imaging (MRI) sequences, including 3D T1-weighted sequences, magnetic resonance angiography (MRA), diffusion tensor imaging (DTI), pseudo-continuous arterial spin labeling (pCASL), and three-dimensional fluid-attenuated inversion recovery (FLAIR) sequences. To assess neuropsychological status, we used both questionnaire- and interview-based rating scales. The former assessments included the Tri-axial Coping Scale, Impact of Event Scale in Japanese, Profile of Mood States, and 15-item Depression, Anxiety, and Stress Scale, whereas the latter assessments included the Mini-Mental State Examination, Japanese version. A total of 12,164 individuals were recruited for the first (baseline) survey, including those unable to complete all assessments. In parallel, we returned the MRI results to the participants and subsequently shared the MRI data through the TMM Biobank. At present, the second (first follow-up) survey of the study started in October 2019 is underway. In this study, we established a large and comprehensive database that included robust neuroimaging data as well as psychological and cognitive assessment data. In combination with genomic and omics data already contained in the TMM Biobank database, these data could provide new insights into the relationships of pathological processes with neuropsychological disorders, including age-related cognitive impairment.

Impact of atrial fibrillation on the cognitive decline in Alzheimer's disease

BACKGROUND

Atrial fibrillation (AF) is a strong risk factor for Alzheimer's disease (AD) independent of ischemic stroke. However, the clinicopathological impact of AF on the severity of AD has not been well elucidated. We aimed to investigate the clinical differences between dementia patients with AF and those without AF by means of imaging data.

METHODS

Following approval from the institutional ethics committee, patients with newly diagnosed AD or amnestic mild cognitive impairment (aMCI) were retrospectively screened (n = 170, 79.5 ± 7.4 years old). Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Based on the MRI data, the cerebral volume, cerebral microbleeds (CMBs), periventricular white matter lesions (WMLs), and deep WMLs were evaluated. The regional cerebral blood flow (rCBF) was measured using ¹²³I-IMP SPECT.

RESULTS

Of the patients, 14 (8.2%) and 156 (91.8%) had AF (AF group) and sinus rhythm (SR group), respectively. The AF group had significantly lower MMSE scores than the SR group (average [standard deviation (SD)]: 19.4 [4.4] and 22.0 [4.4], respectively; p = 0.0347). Cerebral volume and CMBs did not differ between the two groups. The periventricular WMLs, but not the deep WMLs, were significantly larger in the AF group than in the SR group (mean [SD] mL: 6.85 [3.78] and 4.37 [3.21], respectively; p = 0.0070). However, there was no significant difference in rCBF in the areas related to AD pathology between the two groups.

CONCLUSION

AD and aMCI patients with AF showed worse cognitive decline along with larger periventricular WMLs compared to those with SR, although the reduction of rCBF was not different between patients with AF and SR. The white matter lesions may be a more important pathology than the impairment of cerebral blood flow in dementia patients with AF. A larger study is needed to confirm our findings in the future.

WOMEN AT RISK: SOCIOECONOMIC STATUS, LIFESTYLE FACTORS, AND BRAIN VULNERABILITY AMONG JAPANESE AND SWEDISH FEMALE

Background

While multiple modifiable lifestyle factors and disease management have been highlighted for preventing dementia and ameliorating neurodegeneration, women and the disadvantaged socioeconomic status (SES) population still bear disproportionate burdens. Objective: Investigate and compare the potential pathways of SES, lifestyle factors, imaging biomarkers, and cognition in two community dwelling cohorts in Japan and Sweden. Subjects: The Kumamoto Cohort included 576 cognitively healthy females (73.66 ± 5.96 years); the Betula Cohort included 195 cognitively healthy females (63.91 ± 13.41 years).

Methods

We constructed structural equational modeling by lifestyle factors including exercise, social activity, sleep, drinking, and smoking status; disease conditions included obesity, diabetes, hypertension, and depressive disorder; brain imaging biomarkers included regional gay matter volume (GMV) and cortical thickness obtained from T1 weighted magnetic resonance imaging scans and global cognition score. We also examined SES-related gray matter volume and cortical thickness map locations at the whole brain level.

Results

SES was positively associated with GMV of limbic lobe (not cortical thickness), Kumamoto Cohort: standardized direct β =0.21 (0.13;0.28); Betula Cohort: standardized direct β =0.27 (0.13; 0.41). This SES-GMV association was mediated by disease conditions and lifestyle in Kumamoto Cohort: indirect β =-0.013 (0.001; 0.054). We also found several regions, including the medial frontal gyrus, superior frontal gyrus, hippocampus, and thalamus, were commonly sensitive to SES status in two cohorts. Conclusions: Although the observational nature of the study precludes proof of causality, our findings suggest that promoting disease management is crucial to tackling the neurodegeneration burden in the female facing SES disparities.

Impact of constipation on progression of Alzheimer's disease: A retrospective study

BACKGROUND AND PURPOSE

In terms of the gut-brain axis, constipation has been considered to be an important factor of neurodegenerative diseases, although the exact mechanism is still controversial. Herein, we aimed to investigate the contribution of constipation to the progression of dementia in a retrospective study.

METHODS

Patients of Alzheimer's disease(AD) and amnestic mild cognitive impairment were consecutively screened between January 2015 and December 2020, and those of whom brain MRI and neuropsychological tests were performed twice were enrolled in this study. Participants were classified into with constipation (Cons[+], n = 20) and without constipation (Cons[-], n = 64) groups. Laboratory data at the first visit were used. Regression analysis was performed in MMSE, ADAS-Cog, and the volumes of hippocampus on MRI-MPRAGE images and deep white matter lesions (DWMLs) on MRI-FLAIR images obtained at two different time points.

RESULTS

The main finding was that the Cons[+] group showed 2.7 times faster decline in cognitive impairment compared with the Cons[-] group, that is, the liner coefficients of ADAS-Cog were 2.3544 points/year in the Cons[+] and 0.8592 points/year in the Cons[-] groups. Ancillary, changes of DWMLs showed significant correlation with the time span (p < 0.01), and the liner coefficients of DWMLs were 24.48 ml/year in the Cons[+] and 14.83 ml/year in the Cons[-] group, although annual rate of hippocampal atrophy was not different between the two groups. Moreover, serum homocysteine level at baseline was significantly higher in the Cons[+] group than Cons[-] group (14.6 ± 6.4 and 11.5 ± 4.2 nmol/ml, respectively: p = 0.03).

CONCLUSION

There is a significant correlation between constipation and faster progression of AD symptoms along with expansion of DWMLs.

Association of the prefrailty with global brain atrophy and white matter lesions among cognitively unimpaired older adults: the Nakajima study

Physical frailty has been associated with adverse outcomes such as dementia. However, the underlying structural brain abnormalities of physical frailty are unclear. We investigated the relationship between physical frailty and structural brain abnormalities in 670 cognitively unimpaired individuals (mean age 70.1 years). Total brain volume (TBV), hippocampal volume (HV), total white matter hypointensities volume (WMHV), and estimated total intracranial volume (eTIV) on the 3D T1-weighted images were automatically computed using FreeSurfer software. Participants were divided into two states of physical frailty (robust vs. prefrail) based on the revised Japanese version of the Cardiovascular Health Study criteria. The multivariable-adjusted mean values of the TBV-to-eTIV ratio was significantly decreased, whereas that of the WMHV-to-eTIV ratio was significantly increased in the prefrail group compared with the robust group. Slowness, one of the components of physical frailty, was significantly associated with reduced TBV-to-eTIV and HV-to-eTIV ratios, and slowness and weakness were significantly associated with an increased WMHV-to-eTIV ratio. Our results suggest that the prefrail state is significantly associated with global brain atrophy and white matter hypointensities. Furthermore, slowness was significantly associated with hippocampal atrophy.

Higher-resolution quantification of white matter hypointensities by large-scale transfer learning from 2D images on the JPSC-AD cohort

White matter lesions (WML) commonly occur in older brains and are quantifiable on MRI, often used as a biomarker in Aging research. Although algorithms are regularly proposed that identify these lesions from T2‐fluid‐attenuated inversion recovery (FLAIR) sequences, none so far can estimate lesions directly from T1‐weighted images with acceptable accuracy. Since 3D T1 is a polyvalent and higher‐resolution sequence, it could be beneficial to obtain the distribution of WML directly from it. However a serious difficulty, both for algorithms and human, can be found in the ambiguities of brain signal intensity in T1 images. This manuscript shows that a cross‐domain ConvNet (Convolutional Neural Network) approach can help solve this problem. Still, this is non‐trivial, as it would appear to require a large and varied dataset (for robustness) labelled at the same high resolution (for spatial accuracy). Instead, our model was taught from two‐dimensional FLAIR images with a loss function designed to handle the super‐resolution need. And crucially, we leveraged a very large training set for this task, the recently assembled, multi‐sites Japan Prospective Studies Collaboration for Aging and Dementia (JPSC‐AD) cohort. We describe the two‐step procedure that we followed to handle such a large number of imperfectly labeled samples. A large‐scale accuracy evaluation conducted against FreeSurfer 7, and a further visual expert rating revealed that WML segmentation from our ConvNet was consistently better. Finally, we made a directly usable software program based on that trained ConvNet model, available at https://github.com/bthyreau/deep-T1-WMH.

Altruistic Social Activity, Depressive Symptoms, and Brain Regional Gray Matter Volume: Voxel-Based Morphometry Analysis from 8695 Old Adults

Altruistic social activity, such as giving support to others, has shown protective benefits on dementia risk and cognitive decline. However, the pathological mechanism is unclear. In the present study, we investigated the association between altruistic social activity and brain regional gray matter. Furthermore, to explore the psychological interplay in altruistic social activity, we tested mediating effect of depressive symptoms on brain regional gray matter. We performed a cross-sectional Voxel-Based Morphology (VBM) analysis including 8695 old adults (72.9±6.1 years) from Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) Cohort. We measured altruistic social activities by self-report questionnaire, depressive symptoms by Geriatric Depression Scale (GDS)-short version. We employed the whole-brain VBM method to detect relevant structural properties related to altruistic social activity. We then performed multiple regression models to detect the mediating effect of depressive symptoms on particular brain regional gray matter volume while adjusting possible physical and social lifestyle covariables. We found that altruistic social activity is associated with larger gray matter volume in posterior insula, middle cingulate gyrus, hippocampus, thalamus, superior temporal gyrus, anterior orbital gyrus, and middle occipital gyrus. Depressive symptoms mediated over 10% on altruistic social activity and hippocampus volume, over 20% on altruistic social activity and cingulate gyrus volume. Our results indicated that altruistic social activity might preserve brain regional gray matter where are sensitive to aging and cognitive decline. Meanwhile, this association may be explained by indirect effect on depressive symptoms, suggesting that altruistic social activity may mitigate the neuropathology of dementia.

Impact of medium-chain triglycerides on gait performance and brain metabolic network in healthy older adults: a double-blind, randomized controlled study

Nutritional supplementation with medium-chain triglycerides (MCTs) has the potential to increase memory function in elderly patients with frailty and dementia. Our aim was to investigate the effects of MCT on cognitive and gait functions and their relationships with focal brain metabolism and functional connectivity even in healthy older adults. Participants were blindly randomized and allocated to two groups: 18 g/day of MCT oil and matching placebo formula (control) administered as a jelly stick (6 g/pack, ingested three times a day). Gait analysis during the 6-m walk test, cognition, brain focal glucose metabolism quantified by ¹⁸F-fluorodeocyglucose positron emission tomography, and magnetic resonance imaging-based functional connectivity were assessed before and after a 3-month intervention. Sixty-three healthy, normal adults (females and males) were included. Compared with the control group, the MCT group showed better balance ability, as represented by the lower Lissajous index (23.1 ± 14.4 vs. 31.3 ± 18.9; P < 0.01), although no time × group interaction was observed in cognitive and other gait parameters. Moreover, MCT led to suppressed glucose metabolism in the right sensorimotor cortex compared with the control (P < 0.001), which was related to improved balance (r = 0.37; P = 0.04) along with increased functional connectivity from the ipsilateral cerebellar hemisphere. In conclusion, a 3-month MCT supplementation improves walking balance by suppressing glucose metabolism, which suggests the involvement of the cerebro-cerebellar network. This may reflect, at least in part, the inverse reaction of the ketogenic switch as a beneficial effect of long-term MCT dietary treatment.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Voxel-Based Morphometry Reveals a Correlation Between Bone Mineral Density Loss and Reduced Cortical Gray Matter Volume in Alzheimer's Disease

Background: Decreased bone mineral density (BMD) was associated with poorer cognitive function and increased risk of Alzheimer's disease (AD). However, objective evidence for the relationship between osteoporosis and AD in humans has not been extensively described. Objectives: We aimed to evaluate the relationships between BMD and the cortical volumes of brain regions vulnerable to AD; hippocampus, parahippocampal gyrus, precuneus, posterior cingulate, and angular gyrus, using voxel-based morphometry (VBM), to investigate the association between bone loss and AD. Methods: A cohort of 149 consecutive elderly participants who complained of memory disturbance underwent high-resolution structural brain magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA). We used SPM12 software to conduct a voxel-based multiple regression analysis to examine the association between femoral neck BMD values and regional gray matter volume (rGMV) on structural T1-weighted MRI. Results: After adjusting for subject age, gender, total brain volume (TBV), and mini-mental state examination (MMSE) scores, the multiple regression analysis showed significant correlations between BMD loss and rGMV decline in the left precuneus, which is an important neural network hub vulnerable to AD. Conclusion: These data suggest that the bone and brain communicate with each other, as in "bone-brain crosstalk," and that control of BMD factors could contribute to cognitive function and help prevent AD.

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.

Phase Difference-Enhanced Magnetic Resonance (MR) Imaging (PADRE) Technique for the Detection of Age-Related Microstructural Changes in Optic Radiation: Comparison with Diffusion Tensor Imaging (DTI)

Background

The optic radiation (OR) is a white-matter bundle connecting the lateral geniculate body and the visual cortex. Phase difference-enhanced imaging (PADRE) is a new MRI technique that is able to achieve precise delineation of the OR. The aim of this study was to investigate the effect of age on the volume and signal intensity of the OR using PADRE, and to establish a volumetric reference of the OR from a healthy population, compared with diffusion tensor imaging (DTI).

Material/Methods

Thirty-nine healthy volunteers underwent MR imaging with PADRE and DTI sequences on a 3.0-T scanner. For the volumetric analysis with PADRE, the OR corresponding to the external sagittal stratum was manually traced, while an automated thresholding method was used for the DTI-based volumetric analysis of the OR.

Results

The mean right and left OR volumes measured from the PADRE images were 1469.0±242.4 mm³ and 1372.6±310.2 mm³, respectively. Although OR volume showed no significant correlation with age, the normalized OR signal intensity showed a linear correlation with increasing age (r²=0.50–0.53; P<0.01). The OR signal intensity on PADRE and DTI-related quantitative parameters for the OR showed significant correlations (r²=0.46–0.49; P<0.01).

Conclusions

The PADRE technique revealed exceptional preservation of OR volume, even in later life. Moreover, PADRE was able to detect age-related changes in signal intensity of the OR and may contribute to future analyses of pathological neurodegeneration in patients with glaucoma and multiple sclerosis.

The neural basis of the imitation drive

Spontaneous imitation is assumed to underlie the acquisition of important skills by infants, including language and social interaction. In this study, functional magnetic resonance imaging (fMRI) was used to examine the neural basis of ‘spontaneously’ driven imitation, which has not yet been fully investigated. Healthy participants were presented with movie clips of meaningless bimanual actions and instructed to observe and imitate them during an fMRI scan. The participants were subsequently shown the movie clips again and asked to evaluate the strength of their ‘urge to imitate’ (Urge) for each action. We searched for cortical areas where the degree of activation positively correlated with Urge scores; significant positive correlations were observed in the right supplementary motor area (SMA) and bilateral midcingulate cortex (MCC) under the imitation condition. These areas were not explained by explicit reasons for imitation or the kinematic characteristics of the actions. Previous studies performed in monkeys and humans have implicated the SMA and MCC/caudal cingulate zone in voluntary actions. This study also confirmed the functional connectivity between Urge and imitation performance using a psychophysiological interaction analysis. Thus, our findings reveal the critical neural components that underlie spontaneous imitation and provide possible reasons why infants imitate spontaneously.

Oxytocin receptor genotype modulates ventral striatal activity to social cues and response to stressful life events

BACKGROUND

Common variants in the oxytocin receptor gene (OXTR) have been shown to influence social and affective behavior and to moderate the effect of adverse experiences on risk for social-affective problems. However, the intermediate neurobiological mechanisms are not fully understood. Although human functional neuroimaging studies have reported that oxytocin effects on social behavior and emotional states are mediated by amygdala function, animal models indicate that oxytocin receptors in the ventral striatum (VS) modulate sensitivity to social reinforcers. This study aimed to comprehensively investigate OXTR-dependent brain mechanisms associated with social-affective problems.

METHODS

In a sample of 1445 adolescents we tested the effect of 23-tagging single nucleotide polymorphisms across the OXTR region and stressful life events (SLEs) on functional magnetic resonance imaging blood oxygen level-dependent activity in the VS and amygdala to animated angry faces. Single nucleotide polymorphisms for which gene-wide significant effects on brain function were found were then carried forward to examine associations with social-affective problems.

RESULTS

A gene-wide significant effect of rs237915 showed that adolescents with minor CC-genotype had significantly lower VS activity than CT/TT-carriers. Significant or nominally significant gene × environment effects on emotional problems (in girls) and peer problems (in boys) revealed a strong increase in clinical symptoms as a function of SLEs in CT/TT-carriers but not CC-homozygotes. However, in low-SLE environments, CC-homozygotes had more emotional problems (girls) and peer problems (boys). Moreover, among CC-homozygotes, reduced VS activity was related to more peer problems.

CONCLUSIONS

These findings suggest that a common OXTR-variant affects brain responsiveness to negative social cues and that in "risk-carriers" reduced sensitivity is simultaneously associated with more social-affective problems in "favorable environments" and greater resilience against stressful experiences.

Developmental changes in brain activation involved in the production of novel speech sounds in children

Older children are more successful at producing unfamiliar, non-native speech sounds than younger children during the initial stages of learning. To reveal the neuronal underpinning of the age-related increase in the accuracy of non-native speech production, we examined the developmental changes in activation involved in the production of novel speech sounds using functional magnetic resonance imaging. Healthy right-handed children (aged 6-18 years) were scanned while performing an overt repetition task and a perceptual task involving aurally presented non-native and native syllables. Productions of non-native speech sounds were recorded and evaluated by native speakers. The mouth regions in the bilateral primary sensorimotor areas were activated more significantly during the repetition task relative to the perceptual task. The hemodynamic response in the left inferior frontal gyrus pars opercularis (IFG pOp) specific to non-native speech sound production (defined by prior hypothesis) increased with age. Additionally, the accuracy of non-native speech sound production increased with age. These results provide the first evidence of developmental changes in the neural processes underlying the production of novel speech sounds. Our data further suggest that the recruitment of the left IFG pOp during the production of novel speech sounds was possibly enhanced due to the maturation of the neuronal circuits needed for speech motor planning. This, in turn, would lead to improvement in the ability to immediately imitate non-native speech.

Regional reliability of quantitative signal targeting with alternating radiofrequency (STAR) labeling of arterial regions (QUASAR)

BACKGROUND AND PURPOSE

Quantitative signal targeting with alternating radiofrequency labeling of arterial regions (QUASAR) is a recent spin labeling technique that could improve the reliability of brain perfusion measurements. Although it is considered reliable for measuring gray matter as a whole, it has never been evaluated regionally. Here we assessed this regional reliability.

METHODS

Using a 3-Tesla Philips Achieva whole-body system, we scanned four times 10 healthy volunteers, in two sessions 2 weeks apart, to obtain QUASAR images. We computed perfusion images and ran a voxel-based analysis within all brain structures. We also calculated mean regional cerebral blood flow (rCBF) within regions of interest configured for each arterial territory distribution.

RESULTS

The mean CBF over whole gray matter was 37.74 with intraclass correlation coefficient (ICC) of .70. In white matter, it was 13.94 with an ICC of .30. Voxel-wise ICC and coefficient-of-variation maps showed relatively lower reliability in watershed areas and white matter especially in deeper white matter. The absolute mean rCBF values were consistent with the ones reported from PET, as was the relatively low variability in different feeding arteries.

CONCLUSIONS

Thus, QUASAR reliability for regional perfusion is high within gray matter, but uncertain within white matter.

Correlations between brain structures and study time at home in healthy children: a longitudinal analysis

INTRODUCTION

Like sleeping and eating habits, the study habits adopted by children when they are at home are important contributors to lifestyle and they affect cognitive ability. It has recently been reported that sleeping and eating habits change the brain structure of children. However, no research on the effect of study habits at home on the brain structure of children has been conducted thus far. We investigated the effects of study habits at home on the brain structures of healthy children by examining correlations between study time at home and changes in brain structure over the course of 3 years.

METHODS

We used the brain magnetic resonance images of 229 healthy children aged 5.6-18.4 years and computed the changes (time 2-time 1) in regional gray matter and white matter volume (rWMV) using voxel-based morphometry. Whole-brain multiple regression analysis revealed a significant positive correlation between study time at home and changes in rWMV in the right superior frontal gyrus (SFG). Behaviorally, we found a significant positive correlation between study time at home and change in the verbal comprehension index (VCI), one of the subscales of the Wechsler Intelligence Scale for Children-third edition (WISC-III).

RESULTS AND CONCLUSIONS

Given that the SFG is involved in memory control and that the VCI measures abilities related to vocabulary, our results indicate that greater SFG involvement in the memorization component of longer study times may result in greater increases in the number of axons and more axon branching and myelination, causing plastic changes in the neural network involved in memory processes.

Neural correlates of deception in social contexts in normally developing children

Deception is related to the ability to inhibit prepotent responses and to engage in mental tasks such as anticipating responses and inferring what another person knows, especially in social contexts. However, the neural correlates of deception processing, which requires mentalizing, remain unclear. Using functional magnetic resonance imaging (fMRI), we examined the neural correlates of deception, including mentalization, in social contexts in normally developing children. Healthy right-handed children (aged 8–9 years) were scanned while performing interactive games involving deception. The games varied along two dimensions: the type of reply (deception and truth) and the type of context (social and less social). Participants were instructed to deceive a witch and to tell the truth to a girl. Under the social-context conditions, participants were asked to consider what they inferred about protagonists' preferences from their facial expressions when responding to questions. Under the less-social-context conditions, participants did not need to consider others' preferences. We found a significantly greater response in the right precuneus under the social-context than under less-social-context conditions. Additionally, we found marginally greater activation in the right inferior parietal lobule (IPL) under the deception than under the truth condition. These results suggest that deception in a social context requires not only inhibition of prepotent responses but also engagement in mentalizing processes. This study provides the first evidence of the neural correlates of the mentalizing processes involved in deception in normally developing children.

White matter structures associated with empathizing and systemizing in young adults

Empathizing is defined as the drive to identify the mental states of others in order to predict their behavior and respond with an appropriate emotion. Systemizing is defined as the drive to analyze a system in terms of the rules that govern it to predict its behavior. We undertook voxel-by-voxel investigations of regional white matter volume (rWMV) and fractional anisotropy (FA) of diffusion tensor imaging to discover the WM structural correlates of empathizing, systemizing, and their difference (D score: systemizing-empathizing). Whole brain analyses of covariance revealed that across both sexes, the D score was negatively correlated with rWMV in the WM area in the bilateral temporal lobe, near the right inferior frontal gyrus, near the ventral medial prefrontal cortex, and near the posterior cingulate cortex and positively correlated with FA in an area involving the superior longitudinal fasciculus. Post-hoc analyses revealed that these associations were generally formed by both the correlation between WM structures and empathizing as well as the opposite correlation between WM structures and systemizing. A significant effect of interaction between sex and the D score on rWMV, which was mainly observed because of a positive correlation between rWMV and empathizing in females and a negative correlation between rWMV and systemizing in females, was found in an area close to the right inferior parietal lobule and temporoparietal junction. Our results suggest that WM structures involving the default mode network and the mirror neuron system support empathizing, and that a WM structure relating to the external attention system supports systemizing. Further, our results revealed an overlap between positive/negative WM structural correlates of empathizing and negative/positive WM structural correlates of systemizing despite little correlation between empathizing and systemizing, which supports the previously held idea that there is a trade-off between empathizing and systemizing in the brain.

Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

Schizophrenia as a network disease: disruption of emergent brain function in patients with auditory hallucinations

Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests.

Adolescent impulsivity phenotypes characterized by distinct brain networks

The impulsive behavior that is often characteristic of adolescence may reflect underlying neurodevelopmental processes. Moreover, impulsivity is a multi-dimensional construct, and it is plausible that distinct brain networks contribute to its different cognitive, clinical and behavioral aspects. As these networks have not yet been described, we identified distinct cortical and subcortical networks underlying successful inhibitions and inhibition failures in a large sample (n = 1,896) of 14-year-old adolescents. Different networks were associated with drug use (n = 1,593) and attention-deficit hyperactivity disorder symptoms (n = 342). Hypofunctioning of a specific orbitofrontal cortical network was associated with likelihood of initiating drug use in early adolescence. Right inferior frontal activity was related to the speed of the inhibition process (n = 826) and use of illegal substances and associated with genetic variation in a norepinephrine transporter gene (n = 819). Our results indicate that both neural endophenotypes and genetic variation give rise to the various manifestations of impulsive behavior.

A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults

To investigate whether personality traits affect the rate of decline of gray matter volume, we analyzed the relationships between personality traits and the annual rate of changes of gray matter volume in 274 healthy community dwelling subjects with a large age range by applying a longitudinal design over 6 years, using brain magnetic resonance images (MRI) and the Revised NEO Personality Inventory (NEO-PI-R) at baseline. Brain MRI data were processed using voxel-based morphometry with a custom template by applying the DARTEL diffeomorphic registration tool. For each subject, we used NEO-PI-R to evaluate the five major personality traits, including neuroticism, extraversion, openness, agreeableness, and conscientiousness. The results show that the annual rate of change in regional gray matter volume in the right inferior parietal lobule was correlated significantly and negatively with a personality of openness, which is known to be related to intellect, intellectual curiosity, and creativity adjusting for age, gender, and intracranial volume. This result indicates that subjects with a personality trait of less openness have an accelerated loss of gray matter volume in the right inferior parietal lobule, compared with subjects with a personality trait of more openness. Because the right inferior parietal lobule is involved in higher cognitive function such as working memory and creativity, a personality trait of openness is thought to be important for preserving gray matter volume and cognitive function of the right inferior parietal lobule in healthy adults.

PyXNAT: XNAT in Python

As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, investigators rely more and more heavily on scripting using high-level languages to automate data management and processing tasks. For this, a structured and programmatic access to the data store is necessary. Web services are a first step toward this goal. They however lack in functionality and ease of use because they provide only low-level interfaces to databases. We introduce here PyXNAT, a Python module that interacts with The Extensible Neuroimaging Archive Toolkit (XNAT) through native Python calls across multiple operating systems. The choice of Python enables PyXNAT to expose the XNAT Web Services and unify their features with a higher level and more expressive language. PyXNAT provides XNAT users direct access to all the scientific packages in Python. Finally PyXNAT aims to be efficient and easy to use, both as a back-end library to build XNAT clients and as an alternative front-end from the command line.

Detecting outliers in high-dimensional neuroimaging datasets with robust covariance estimators

Medical imaging datasets often contain deviant observations, the so-called outliers, due to acquisition or preprocessing artifacts or resulting from large intrinsic inter-subject variability. These can undermine the statistical procedures used in group studies as the latter assume that the cohorts are composed of homogeneous samples with anatomical or functional features clustered around a central mode. The effects of outlying subjects can be mitigated by detecting and removing them with explicit statistical control. With the emergence of large medical imaging databases, exhaustive data screening is no longer possible, and automated outlier detection methods are currently gaining interest. The datasets used in medical imaging are often high-dimensional and strongly correlated. The outlier detection procedure should therefore rely on high-dimensional statistical multivariate models. However, state-of-the-art procedures, based on the Minimum Covariance Determinant (MCD) estimator, are not well-suited for such high-dimensional settings. In this work, we introduce regularization in the MCD framework and investigate different regularization schemes. We carry out extensive simulations to provide backing for practical choices in absence of ground truth knowledge. We demonstrate on functional neuroimaging datasets that outlier detection can be performed with small sample sizes and improves group studies.

Linear and curvilinear correlations of brain gray matter volume and density with age using voxel-based morphometry with the Akaike information criterion in 291 healthy children

We examined linear and curvilinear correlations of gray matter volume and density in cortical and subcortical gray matter with age using magnetic resonance images (MRI) in a large number of healthy children. We applied voxel-based morphometry (VBM) and region-of-interest (ROI) analyses with the Akaike information criterion (AIC), which was used to determine the best-fit model by selecting which predictor terms should be included. We collected data on brain structural MRI in 291 healthy children aged 5-18 years. Structural MRI data were segmented and normalized using a custom template by applying the diffeomorphic anatomical registration using exponentiated lie algebra (DARTEL) procedure. Next, we analyzed the correlations of gray matter volume and density with age in VBM with AIC by estimating linear, quadratic, and cubic polynomial functions. Several regions such as the prefrontal cortex, the precentral gyrus, and cerebellum showed significant linear or curvilinear correlations between gray matter volume and age on an increasing trajectory, and between gray matter density and age on a decreasing trajectory in VBM and ROI analyses with AIC. Because the trajectory of gray matter volume and density with age suggests the progress of brain maturation, our results may contribute to clarifying brain maturation in healthy children from the viewpoint of brain structure.

Linear and curvilinear correlations of brain white matter volume, fractional anisotropy, and mean diffusivity with age using voxel-based and region-of-interest analyses in 246 healthy children

In this study, we examined linear and curvilinear correlations of fractional anisotropy (FA), mean diffusivity (MD), and white matter volume with age by using brain structural and diffusion-tensor magnetic resonance imaging (MRI) in a large number of healthy children and voxel-based morphometry (VBM) and region-of-interest (ROI) analyses. We collected data by brain structural MRI in 246 healthy children, aged 5-18 years. FA and MD images were normalized using the normalization parameter of the corresponding structural MRI. Next, we analyzed the correlations between FA and age and between MD and age by estimating linear and logarithmic functions. We also analyzed the correlation between white matter volume and age by linear, quadratic, and cubic functions. Correlations between FA and age and between MD and age showed exponential trajectories in most ROIs in boys and girls, except for several fibers, such as the corpus callosum connecting the bilateral rectal gyri in boys. The correlation between white matter volume and age showed significant positive linear trajectories in most ROIs in boys and girls, except for a few fibers, such as the bilateral uncinate fasciculus. Additionally, maturational rates differed among major fibers, and in girls, the left superior longitudinal fasciculus, which connects the frontal and temporal lobes, showed a slower rate of maturation than other fibers. Our results may help to clarify the mechanisms of normal brain maturation from the viewpoint of brain white matter.

Correlation between high-sensitivity C-reactive protein and brain gray matter volume in healthy elderly subjects

Although elevated serum high-sensitivity C-reactive protein (hsCRP) is related to atherosclerosis, brain infarction, and cognitive decline, it has not been clarified whether increased hsCRP is associated with the decline in brain gray matter volume. Therefore, the purpose of this study was to determine the relationship between hsCRP levels and brain regional gray matter volume using brain magnetic resonance imaging (MRI) data from 109 community-dwelling healthy elderly subjects. Brain MRIs were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra (DARTEL) procedure. We found a significant negative correlation between regional gray matter volume of the posterior and lateral aspects of the left temporal cortex and hsCRP level after adjusting for age, gender, and intracranial volume. Our results suggest that subjects who have mild inflammation related to arteriosclerosis have decreased regional gray matter volume in the posterior and lateral aspects of the left temporal cortex. Thus, preventing the progression of arteriosclerosis may be important for preventing a decrease in gray matter volume in healthy elderly subjects.

A longitudinal study of age- and gender-related annual rate of volume changes in regional gray matter in healthy adults

The aim of this study was to analyze correlations among the annual rate of gray matter volume change, age, gender, and cerebrovascular risk factors in 381 healthy community-dwelling subjects with a large age range by applying a longitudinal design over 6 years using brain magnetic resonance images (MRIs). Brain MRI data were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra procedure. The annual rate of regional gray matter volume change showed significant positive correlations with age in several regions, including the bilateral temporal pole, caudate nucleus, ventral and dorsolateral prefrontal cortices, insula, hippocampus, and temporoparietal cortex, whereas significant negative correlations with age were observed in several regions including the bilateral cingulate gyri and anterior lobe of the cerebellum. Additionally, a significant age-by-gender interaction was found for the annual rate of regional gray matter volume change in the bilateral hippocampus. No significant correlations were observed between the annual rate of regional gray matter volume change and body mass index or systolic blood pressure. A significant positive correlation between the annual rate of gray matter volume change and age indicates that the region shows not linear but accelerated gray matter loss with age. Therefore, evaluating the annual rate of the gray matter volume change with age in healthy subjects is important in understanding how gray matter volume changes with aging in each brain region and in anticipating what cognitive functions are likely to show accelerated decline with aging.

Apathy is related to cortex morphology in CADASIL. A sulcal-based morphometry study

OBJECTIVES

Apathy is a debilitating symptom in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the pathophysiology of which remains poorly understood. The aim of this study was to evaluate the neuroanatomic correlates of apathy, using new MRI postprocessing methods based on the identification of cortical sulci, in a large cohort of patients with CADASIL.

METHODS

A total of 132 patients with genetically confirmed diagnosis were included in this prospective cohort study. Global cognitive performances were assessed by the Mattis Dementia Rating Scale (MDRS) and disability by the modified Rankin score (mRS). Apathy was defined according to standard criteria. Depth, width, and cortical thickness of 10 large sulci of the frontal lobe in each hemisphere were measured. Logistic regression modeling was used to evaluate the links between apathy and cortical thickness, depth, or width of the different sulci. All models were adjusted for age, gender, level of education, MDRS, mRS, depression, and global brain volume.

RESULTS

Complete MRI datasets of high quality were available in 119 patients. Depth of the posterior cingulate sulcus exhibited the strongest association with apathy in fully adjusted models (right: p value = 0.0006; left: p value = 0.004). Depth and width of cortical sulci in mediofrontal and orbitofrontal areas were independently associated with apathy. By contrast, cortical thickness was not.

CONCLUSIONS

Cortical morphology in mediofrontal and orbitofrontal areas, by contrast to cortical thickness, is strongly and independently associated with apathy. These results suggest that apathy is related to a reduction of cortical surface rather than of cortical thickness secondary to lesion accumulation in CADASIL.

Detecting outlying subjects in high-dimensional neuroimaging datasets with regularized minimum covariance determinant

Medical imaging datasets used in clinical studies or basic research often comprise highly variable multi-subject data. Statistically-controlled inclusion of a subject in a group study, i.e. deciding whether its images should be considered as samples from a given population or whether they should be rejected as outlier data, is a challenging issue. While the informal approaches often used do not provide any statistical assessment that a given dataset is indeed an outlier, traditional statistical procedures are not well-suited to the noisy, high-dimensional, settings encountered in medical imaging, e.g. with functional brain images. In this work, we modify the classical Minimum Covariance Determinant approach by adding a regularization term, that ensures that the estimation is well-posed in high-dimensional settings and in the presence of many outliers. We show on simulated and real data that outliers can be detected satisfactorily, even in situations where the number of dimensions of the data exceeds the number of observations.