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.

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 AND 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.

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.

Spinal fMRI of interoceptive attention/awareness in experts and novices.

Many disciplines/traditions that promote interoceptive (inner sensation of body parts) attention/awareness (IAA) train practitioners to both attend to and be aware of interoceptive sensory experiences in body parts. The effect of such practices has been investigated in previous imaging studies but limited to cerebral neural activity. Here, for the first time, we studied the impact of these practices on the spinal neural activity of experts and novices. We also attempted to clarify the effect of constant and deep breathing, a paradigm utilized in concentration practices to avoid mind wandering, on IAA-related spinal neural activity. Subjects performed IAA tasks with and without a deep and constant breathing pattern in two sessions. Results showed that neural activity in the spinal segment innervating the attended-to body area increased in experts (P = 0.04) when they performed IAA and that this increase was significantly larger for experts versus novices in each of the sessions (P = 0.024). The significant effects of IAA and expertise on spinal neural activity are consistent with and elaborate on previous reports showing similar effects on cerebral neural activity. As the spinal cord directly innervates body parts, the results might indicate that IAA has an instantaneous (possibly beneficial) effect on the physical body after extended training.

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.

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.

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.

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.

Correlation between pulmonary function and brain volume in healthy elderly subjects.

INTRODUCTION: Cigarette smoking decreases brain regional gray matter volume and is related to chronic obstructive lung disease (COPD). COPD leads to decreased pulmonary function, which is represented by forced expiratory volume in one second percentage (FEV1.0 %); however, it is unclear if decreased pulmonary function is directly related to brain gray matter volume decline. Because there is a link between COPD and cognitive decline, revealing a direct relationship between pulmonary function and brain structure is important to better understand how pulmonary function affects brain structure and cognitive function. Therefore, the purpose of this study was to analyze whether there were significant correlations between FEV1.0 % and brain regional gray and white matter volumes using brain magnetic resonance (MR) image data from 109 community-dwelling healthy elderly individuals. METHODS: Brain MR images were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra procedure. RESULTS: We found a significant positive correlation between the regional white matter volume of the cerebellum and FEV1.0 % after adjusting for age, sex, and intracranial volume. CONCLUSION: Our results suggest that elderly individuals who have a lower FEV1.0 % have decreased regional white matter volume in the cerebellum. Therefore, preventing decreased pulmonary function is important for cerebellar white matter volume in the healthy elderly population.

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 (ß = 0.16, pFDR = 0.023) and the left parahippocampal gyrus (ß = 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 (ß = 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.

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.

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.

Very large fMRI study using the IMAGEN database: sensitivity-specificity and population effect modeling in relation to the underlying anatomy.

In this paper we investigate the use of classical fMRI Random Effect (RFX) group statistics when analyzing a very large cohort and the possible improvement brought from anatomical information. Using 1326 subjects from the IMAGEN study, we first give a global picture of the evolution of the group effect t-value from a simple face-watching contrast with increasing cohort size. We obtain a wide activated pattern, far from being limited to the reasonably expected brain areas, illustrating the difference between statistical significance and practical significance. This motivates us to inject tissue-probability information into the group estimation, we model the BOLD contrast using a matter-weighted mixture of Gaussians and compare it to the common, single-Gaussian model. In both cases, the model parameters are estimated per-voxel for one subgroup, and the likelihood of both models is computed on a second, separate subgroup to reflect model generalization capacity. Various group sizes are tested, and significance is asserted using a 10-fold cross-validation scheme. We conclude that adding matter information consistently improves the quantitative analysis of BOLD responses in some areas of the brain, particularly those where accurate inter-subject registration remains challenging.

Sleep duration during weekdays affects hippocampal gray matter volume in healthy children.

Sleep is essential for living beings, and sleep loss has been shown to affect hippocampal structure and function in rats by inhibiting cell proliferation and neurogenesis in this region of the brain. We aimed to analyze the correlation between sleep duration and the hippocampal volume using brain magnetic resonance images of 290 healthy children aged 5-18 years. We examined the volume of gray matter, white matter, and the cerebrospinal fluid (CSF) space in the brain using a fully automated and established neuroimaging technique, voxel-based morphometry, which enabled global analysis of brain structure without bias towards any specific brain region while permitting the identification of potential differences or abnormalities in brain structures. We found that the regional gray matter volume of the bilateral hippocampal body was significantly positively correlated with sleep duration during weekdays after adjusting for age, sex, and intracranial volume. Our results indicated that sleep duration affects the hippocampal regional gray matter volume of healthy children. These findings advance our understanding of the importance of sleep habits in the daily lives of healthy children.

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.

Altruistic Social Activity, Depressive Symptoms, and Brain Regional Gray Matter Volume: Voxel-Based Morphometry Analysis From 8,695 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 8 695 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 questionnaires, 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 which 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.