Regional Gray Matter Density Research Articles

Cholinergic Nucleus 4 Degeneration and Cognitive Impairment in Isolated Rapid Eye Movement Sleep Behavior Disorder.

Cholinergic nucleus 4 (Ch4) degeneration is associated with cognitive impairment in Parkinson's disease and dementia with Lewy bodies, but it is unknown if Ch4 degeneration is also present in isolated rapid eye movement sleep behavior disorder (iRBD). The aim was to determine if there is evidence of Ch4 degeneration in patients with iRBD and if it is associated with cognitive impairment. We analyzed the clinical and neuropsychological data of 35 iRBD patients and 35 age- and sex-matched healthy controls. Regional gray matter density (GMD) was calculated for Ch4 using probabilistic maps applied to brain magnetic resonance imaging (MRI). Ch4 GMD was significantly lower in the iRBD group compared to controls (0.417 vs. 0.441, P= 0.02). Ch4 GMD was also found to be a significant predictor of letter number sequencing (β-coefficient=58.31, P= 0.026, 95% confidence interval [7.47, 109.15]), a measure of working memory. iRBD is associated with Ch4 degeneration, and Ch4 degeneration in iRBD is associated with impairment in working memory. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Longitudinal evolution of neuropathological substrates of Alzheimer’s disease in obese patients

AbstractBackgroundObesity is a metabolic condition with increasing prevalence all over the world. Patients with a body mass index (BMI) higher than 30 are considered obese. Obesity is also a risk factor for chronic morbidities such as type 2 diabetes and may increase the risk of developing Alzheimer's disease (AD). Not much is known about longitudinal changes in Alzheimer’s pathology in these patients. We hypothesised that BMI would predict longitudinal pathological alterations derived from imaging parameters.Method252 participants (n=107 obese non‐diabetic patients with BMI>30) cognitively normal (n=80) and with mild cognitive impairment (n=172) were evaluated from the Alzheimer’s Disease Neuroimaging Initiative (Mean age = 73.6 years, SD = 8.0). All participants had two T1‐weighted MPRAGE MRI scans within two‐years (Mean gap=718 days, SD=107). Regional cortical thickness was measured on T1‐MPRAGE using FreeSurfer v.6.0. Individual gray matter density maps were computed using voxel‐based morphometry (VBM) and regional values were sampled in various cortical regions. Regional cortical thickness and gray matter density are expressed as delta values between baseline and followup (Value followup ‐ Value Baseline). Spearman’s correlation coefficients were calculated to assess the relationship between BMI and imaging biomarkers.ResultIn the whole cohort, we found that BMI is significantly negatively correlated with longitudinal changes in cortical thickness in anterior cingulate (ACC, p=0.0073, r=‐0.17) and posterior cingulate (PCC, p=0.0147, r=‐0.15) cortical thickness. We also found that BMI is significantly negatively correlated with longitudinal changes in frontal (p=0.0184, r=‐0.15), parietal (p=0.0057, r=‐0.18) and temporal (p=0.0141, r=‐0.16) gray matter density. When looking only at MCI participants, we found similar results with even stronger correlations. BMI is significantly negatively correlated with delta anterior cingulate (ACC, p=0.0008, r=‐0.25) and posterior cingulate (PCC, p=0.004, r=‐0.22) cortical thickness.ConclusionIn this cohort of obese and non‐obese participants cognitively normal and with MCI, we found that obesity was associated with a longitudinal 2‐years worsening of macrostructural changes. Higher BMI was associated with a higher reduction of cortical thickness and with a decreased gray matter density in several brain regions.

Sex differences in regional gray matter density in pre-adolescent binge eating disorder: a voxel-based morphometry study.

Binge eating disorder (BED) is a pernicious psychiatric disorder which is linked with broad medical and psychiatric morbidity, and obesity. While BED may be characterized by altered cortical morphometry, no evidence to date examined possible sex-differences in regional gray matter characteristics among those with BED. This is especially important to consider in children, where BED symptoms often emerge coincident with rapid gray matter maturation. Pre-adolescent, 9-10-year old boys (N = 38) and girls (N = 33) with BED were extracted from the 3.0 baseline (Year 0) release of the Adolescent Brain Cognitive Development Study. We investigated sex differences in gray matter density (GMD) via voxel-based morphometry. Control sex differences were also assessed in age and body mass index and developmentally matched control children (boys N = 36; girls N = 38). Among children with BED, we additionally assessed the association between dorsolateral prefrontal (dlPFC) GMD and parent-reported behavioral approach and inhibition tendencies. Girls with BED uniquely demonstrate diffuse clusters of greater GMD (p < 0.05, Threshold Free Cluster Enhancement corrected) in the (i) left dlPFC (p = 0.003), (ii) bilateral dmPFC (p = 0.004), (iii) bilateral primary motor and somatosensory cortex (p = 0.0003) and (iv) bilateral precuneus (p = 0.007). Brain-behavioral associations suggest a unique negative correlation between GMD in the left dlPFC and behavioral approach tendencies among girls with BED. Early-onset BED may be characterized by regional sex differences in terms of its underlying gray matter morphometry.

Convergent lines of evidence supporting involvement of NFKB1 in schizophrenia

ObjectivesNFKB1 was associated with treatment-refractory schizophrenia (SZ) and response to antipsychotics; however, the underlying mechanisms through which NFKB1 confers its risk for SZ are largely unknown. We aimed to investigate the potential role of NFKB1 in SZ. MethodsIn the present study, we investigated the association of the risk SNP rs230529 of NFKB1 with gray matter density and with NFKB1 mRNA levels in various human brain regions. The spatiotemporal expression pattern of NFKB1 in human brains was explored. We constructed a miRNA-NFKB1-target gene regulatory network and analyzed its druggability through targeting NFKB1 for SZ treatment. ResultsNFKB1 showed the highest expression levels in the cerebellum, in which these levels were stratified by genotypes of rs230529. Interestingly, the allelic state of rs230529 was significantly associated with regional gray matter density in multiple brain regions (including the cerebellum), which also differed between patients with schizophrenia and controls. Furthermore, regulatory targets of NFKB1 were enriched among SZ susceptibility genes. A substantial proportion of NFKB1 target genes were subject to combinatorial regulation by NFKB1 and miRNAs, constituting a hybrid NFKB1-miRNA-gene regulatory network. Some components of this network showed expression changes relevant to both the disease and the treatment. Finally, we detected the dynamic changes of NFKB1-miR-155-5p-GSK3B and NFKB1-miR-155-5p/let-7a-5p-IL6 networks in course of the treatment of SZ. ConclusionTaken together, our findings support the involvement of NFKB1-mediated dysregulation in the development of SZ.

Olfaction, cholinergic basal forebrain degeneration, and cognition in early Parkinson disease

IntroductionImpaired olfaction and reduced cholinergic nucleus 4 (Ch4) volume both predict greater cognitive decline in Parkinson's disease (PD). We examined the relationship between olfaction, longitudinal change in cholinergic basal forebrain nuclei and their target regions, and cognition in early PD. MethodsWe analyzed a cohort of 97 PD participants from the Parkinson's Progression Markers Initiative with brain MRIs at baseline, 1 year, 2 years, and 4 years. Using probabilistic maps, regional grey matter density (GMD) was calculated for Ch4, cholinergic nuclei 1, 2, and 3 (Ch123), and their target regions. ResultsBaseline University of Pennsylvania Smell Identification Test score correlated with change in GMD of all regions of interest (all p < 0.05). Rate of change of Ch4 GMD was correlated with rate of change of Ch123 (p = 0.034), cortex (p = 0.001), and amygdala GMD (p < 0.001), but not hippocampus GMD (p = 0.38). Rate of change of Ch123 GMD was correlated with rate of change of cortex (p = 0.001) and hippocampus (p < 0.001), but not amygdala GMD (p = 0.133). In a linear regression model including change in GMD of all regions of interest and age as predictors, change in cortex GMD (βˆslope= 38.2; 95 % CI: [0.47, 75.9]) and change in hippocampus GMD (βˆslope= 24.8; 95 % CI: [0.80, 48.8]) were significant predictors of Montreal Cognitive Assessment score change over time. ConclusionImpaired olfaction is associated with degeneration of the cholinergic basal forebrain and bilateral cortex, amygdala, and hippocampus in PD. The relationship between impaired olfaction and cognitive decline may be mediated by greater atrophy of the cortex and hippocampus.

Brain structural alterations in MDD patients with gastrointestinal symptoms: Evidence from the REST-meta-MDD project

ObjectiveWhile gastrointestinal (GI) symptoms are very common in patients with major depressive disorder (MDD), few studies have investigated the neural basis behind these symptoms. In this study, we sought to elucidate the neural basis of GI symptoms in MDD patients by analyzing the changes in regional gray matter volume (GMV) and gray matter density (GMD) in brain structure. MethodSubjects were recruited from 13 clinical centers and categorized into three groups, each of which is based on the presence or absence of GI symptoms: the GI symptoms group (MDD patients with at least one GI symptom), the non-GI symptoms group (MDD patients without any GI symptoms), and the healthy control group (HCs). Structural magnetic resonance images (MRI) were collected of 335 patients in the GI symptoms group, 149 patients in the non-GI symptoms group, and 446 patients in the healthy control group. The 17-item Hamilton Depression Rating Scale (HAMD-17) was administered to all patients. Correlation analysis and logistic regression analysis were used to determine if there was a correlation between the altered brain regions and the clinical symptoms. ResultsThere were significantly higher HAMD-17 scores in the GI symptoms group than that of the non-GI symptoms group (P < 0.001). Both GMV and GMD were significant different among the three groups for the bilateral superior temporal gyrus, bilateral middle temporal gyrus, left lingual gyrus, bilateral caudate nucleus, right Fusiform gyrus and bilateral Thalamus (GRF correction, cluster-P < 0.01, voxel-P < 0.001). Compared to the HC group, the GI symptoms group demonstrated increased GMV and GMD in the bilateral superior temporal gyrus, and the non-GI symptoms group demonstrated an increased GMV and GMD in the right superior temporal gyrus, right fusiform gyrus and decreased GMV in the right Caudate nucleus (GRF correction, cluster-P < 0.01, voxel-P < 0.001). Compared to the non-GI symptoms group, the GI symptoms group demonstrated significantly increased GMV and GMD in the bilateral thalamus, as well as decreased GMV in the bilateral superior temporal gyrus and bilateral insula lobe (GRF correction, cluster-P < 0.01, voxel-P < 0.001). While these changed brain areas had significantly association with GI symptoms (P < 0.001), they were not correlated with depressive symptoms (P > 0.05). Risk factors for gastrointestinal symptoms in MDD patients (p < 0.05) included age, increased GMD in the right thalamus, and decreased GMV in the bilateral superior temporal gyrus and left Insula lobe. ConclusionMDD patients with GI symptoms have more severe depressive symptoms. MDD patients with GI symptoms exhibited larger GMV and GMD in the bilateral thalamus, and smaller GMV in the bilateral superior temporal gyrus and bilateral insula lobe that were correlated with GI symptoms, and some of them and age may contribute to the presence of GI symptoms in MDD patients.

Tinnitus and Its Central Correlates: A Neuroimaging Study in a Large Aging Population.

To elucidate the association between tinnitus and brain tissue volumes and white matter microstructural integrity. Two thousand six hundred sixteen participants (mean age, 65.7 years [SD: 7.5 years]; 53.9% female) of the population-based Rotterdam Study underwent tinnitus assessment (2011 to 2014) and magnetic resonance imaging of the brain (2011 to 2014). Associations between tinnitus (present versus absent) and total, gray, and white matter volume and global white matter microstructure were assessed using multivariable linear regression models adjusting for demographic factors, cardiovascular risk factors, depressive symptoms, Mini-Mental State Examination score, and hearing loss. Finally, potential regional gray matter density and white matter microstructural volume differences were assessed on a voxel-based level again using multivariable linear regression. Participants with tinnitus (21.8%) had significantly larger brain tissue volumes (difference in SD, 0.09; 95% confidence interval, 0.06 to 0.13), driven by larger white matter volumes (difference, 0.12; 95% confidence interval, 0.04 to 0.21) independent of hearing loss. There was no association between tinnitus and gray matter volumes nor with global white matter microstructure. On a lobar level, tinnitus was associated with larger white matter volumes in each lobe, not with gray matter volume. Voxel-based results did not show regional specificity. We found that tinnitus in older adults was associated with larger brain tissue volumes, driven by larger white matter volumes, independent of age, and hearing loss. Based on these results, it may be hypothesized that tinnitus potentially has a neurodevelopmental origin in earlier life independent of aging processes.

Grey matter alterations in restless legs syndrome: A coordinate-based meta-analysis.

Brain structural abnormalities in idiopathic restless legs syndrome have long been debated. Voxel-based morphometry is an objective structural magnetic resonance imaging technique to investigate regional grey matter volume or density differences between groups. In the last decade, voxel-based morphometry studies have exhibited inconsistent and conflicting findings regarding the presence and localization of brain grey matter alterations in restless legs syndrome. We therefore conducted a coordinate-based meta-analysis to quantitatively examine whether there were consistent grey matter findings in restless legs syndrome using the latest algorithms, seed-based d mapping with permutation of subject images. We included 12 voxel-based morphometry studies (13 datasets, 375 patients and 385 healthy controls). Our coordinate-based meta-analysis did not identify evidence of consistent grey matter alterations in restless legs syndrome. Grey matter alterations via voxel-based morphometry analysis are not therefore recommended to be used as a reliable surrogate neuroimaging marker for restless legs syndrome. This lack of consistency may be attributed to differences in sample size, genetics, gender distribution and age at onset, clinical heterogeneity (clinical course, anatomical distribution of symptoms, disease severity, disease duration, abnormal sensory profiles and comorbidity), and variations in imaging acquisition, data processing and statistical strategies. Longitudinal studies with multimodal neuroimaging techniques are needed to determine whether structural changes are dynamic and secondary to functional abnormalities.

Dissociating regional gray matter density and gray matter volume in autism spectrum condition

BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both. MethodsDifferences in MRI-based GM density and volume were examined in 6–25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47–154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67–155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods. ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions. LimitationsThe method for determining “density” is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences. ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Про COVID-19, психічне здоров’я та медитацію

The art of meditation has attracted vivid attention and considerable interest in contemporary unstable and unpredicted world, especially now when the outbreak of COVID-19 has created mental health concerns among the general population worldwide. Contemporary research on meditation for different conditions shows that meditation helps to control pain, may reduce blood pressure, leads to increases in regional brain gray matter density, may reduce age-related memory loss, enhances self-awareness, reduces feelings of loneliness and increases social contact, cultivates more creative problem-solving skills, promotes emotional health. Its positive impact on stress, anxiety, depression, chronic diseases is well-known. To enhance mental health and stabilize human beings in happiness and harmony, it is now more crucial than ever to turn to the Eastern spiritual practices and integrate them with the Western scientific discoveries. It will expand the functional field of human capabilities to achieve freedom and self-realization.

An analysis of the brain structures underlying the link between pathological Internet use and anxiety

Pathological Internet use (PIU) is associated with various maladaptive problems and is becoming increasingly common among adolescents. Anxiety has been discovered as an important predictor of PIU, with the neural basis underlying the link between these two variables remaining unclear. In this study, PIU variations, individual anxiety levels, and T1-weighted structural magnetic resonance images (MRI) were collected from 95 healthy male adolescents. Voxel-based morphometry (VBM) was then applied to identify the brain regions related to individual variations in PIU, with mediation analyses being conducted to explore the relationship between brain structure, anxiety, and PIU. The results revealed that the PIU tendency is positively correlated with regional grey matter density (rGMD) in the right inferior parietal lobe (IPL), which is known to be involved in inhibitory control. Furthermore, the mediation analysis revealed that the rGMD in the right IPL mediates the association between anxiety and PIU, which is consistent with the mood enhancement theory and the Interaction of Person-Affect-Cognition-Execution (I-PACE) model. This mediation model suggests that individuals with higher anxiety might be more likely to use the Internet, with the rGMD in the right IPL being where the underlying cognitive mechanism of the relationship between these two variables lies. This study’s findings possess implications for society’s understandings of the correlations between anxiety and PIU from a brain structural perspective, which may then help in preventing the progression of PIU among adolescents.

Gray matter alterations in restless legs syndrome: A coordinate-based meta-analysis.

Background:Voxel-based morphometry (VBM) is an objective structural magnetic resonance imaging (MRI) technique which allows researchers to investigate group-level differences in regional gray matter (GM) volume or density over the whole brain. In the last decade, VBM studies in restless leg syndrome (RLS) have exhibited inconsistent and conflicting findings.Methods:Studies will be identified through a computerized literature search of the following databases: PubMed, Web of Science, and Embase until October 1, 2018 and updated on March 1, 2020. This protocol will be performed in accordance with the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P). In addition, we will follow the recent guidelines and recommendations for coordinate-based meta-analysis (CBMA). This CBMA will be performed with the seed-based d mapping with permutation of subject images (SDM-PSI) software.Results:This CBMA will offer the latest evidence of GM alterations in RLS.Conclusions:To our knowledge, this will be the first CBMA that pooled VBM findings in RLS. This quantitative evidence of GM alterations will characterize brain morphometry of RLS.PROSPERO registration number:CRD42018117014.

Regional Gray Matter Density Associated With Fast-Paced Walking in Older Adults: A Voxel-Based Morphometry Study.

Walking speed during fast-paced walking task has been associated with cognitive function. It is unclear what underlying brain structures are related to fast-paced walking. We investigated the association of gray matter (GM) density with fast-paced walking speed and usual-paced walking speed. We collected data from 284 older adults from a subset of the Health, Aging, and Body composition study (mean age = 83 [SD = 2.8], 58% women, 41% black). Voxel-wise analyses on magnetic resonance imaging data identified regions of the brain where GM density was associated with fast-paced walking speed. We then extracted GM density for all identified regions and modeled the association with fast-paced walking speed after adjusting for demographic factors, clinical factors, and cognitive function. Analyses were repeated for usual-paced walking. Regions with beta coefficients ≥0.3 m/s were considered to be meaningfully correlated. GM density of clusters from cortical regions in the right middle and superior frontal gyrus, right postcentral gyrus, and left superior temporal gyrus were positively correlated with fast-paced walking speed in adjusted models. Adjustment for cognitive function had little impact on the findings. Caudate was correlated with usual paced walking speed at coefficient ≥0.3 m/s after adjustment of demographic factors and clinical factors, but not after further adjustment of cognitive function. Fast-paced walking speed was correlated with GM density of right middle and superior frontal gyrus, right postcentral gyrus, and left superior temporal gyrus, and could potentially provide evidence about subclinical structural change of brain related to aging.

Neurostructural correlates of optimism: Gray matter density in the putamen predicts dispositional optimism in late adolescence.

Dispositional optimism reflects one's generalized positive expectancies for future outcomes and plays a crucial role in personal developmental outcomes and health (e.g., counteracting related mental disorders such as depression and anxiety). Increasing evidence has suggested that extraversion is an important personality factor contributing to dispositional optimism. However, less is known about the association between dispositional optimism and brain structure and the role of extraversion in this association. Here, we examined these issues in 231 healthy high school students aged 16 to 20 years (110 males, mean age = 18.48 years, SD = 0.54) by estimating regional gray matter density (rGMD) using a voxel‐based morphometry method via structural magnetic resonance imaging. Whole‐brain regression analyses revealed a significant positive correlation between dispositional optimism and the rGMD of the bilateral putamen after adjusting for age, sex, family socioeconomic status (SES), general intelligence, and total gray matter volume (TGMV). Moreover, prediction analyses using fourfold balanced cross‐validation combined with linear regression confirmed a significant connection between dispositional optimism and putamen density after adjusting for age, sex, and family SES. More importantly, subsequent mediation analysis showed that extraversion may account for the association between putamen density and dispositional optimism after adjusting for age, sex, family SES, general intelligence, TGMV, and the other four Big Five personality traits. Taken together, the current study provides new evidence regarding the neurostructural basis underlying dispositional optimism in adolescents and underscores the importance of extraversion as an essential personality factor for dispositional optimism acquisition.

P2257Self-care abilities and depression symptoms linked to brain injury in heart failure

Abstract Heart failure (HF) patients show brain damage in regions controlling mood, autonomic, and cognitive functions. HF patient's exhibit symptoms related to depression, anxiety, poor sleep quality, daytime sleepiness, impaired cognition, and poor self-care, however, the relationship between brain damage and disease related symptoms is unclear. Therefore, our aim was to correlate gray matter density in prefrontal cortices, hippocampus, and insular lobe with disease symptoms using T1-weight voxel based morphometry procedure and evaluate the measure that predicts the brain damage. Methods Two high-resolution T1-weighted data were collected from each 42 HF subjects (age, 55.65±7.61; 30 male; LVEF 27.74±9.40%; NYHA class II/III) using a 3.0-Tesla MRI scanner. Depression, anxiety, sleep quality, daytime sleepiness, cognition, and self-care issues were examined with Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), Montreal Cognitive Assessment (MoCA), and Self-Care of Heart Failure Inventory (SCHFI) respectively. Both T1-weighted scans were realigned, averaged, and segmented into gray matter (GM), white matter, and cerebrospinal fluid tissue type. GM maps were normalized (unmodulated) to a common space and smoothed to obtain GM density maps. The smoothed GM density maps were used to examine the association of brain damage with disease symptoms (SPM 12; partial correlation; covariates, age and gender; p&lt;0.005). Region of interest analyses were performed in prefrontal cortices, insular lobe and hippocampus to evaluate the correlation using partial correlation (SPSS, covariates, age and gender, p&lt;0.05). Results The average scores for BAI 9.55±9.90, BDI 8.69±7.05, ESS 7.00±3.72, MoCA 24.64±3.48, PSQI 6.62±3.90, maintenance 73.12±13.78, management 70.28±13.98, and confidence 73.77±15.96 were calculated. Significant negative correlations was observed between GM density values and BAI (prefrontal cortices, r=−0.532, p&lt;0.001), BDI (prefrontal cortices, r=−0.60, p&lt;0.001; insula, r=−0.528, p&lt;0.001, hippocampus, r=−0.432, p&lt;0.005), ESS (prefrontal cortices, r=−0.419, p=0.007; insula, r=−0.443, p=0.004), and PSQI (prefrontal cortices, r=−0.517, p=0.001) scores, and positive correlation between GM density values, MoCA (prefrontal cortices, r=0.462, p=0.003) and SCHFI scores (maintenance: prefrontal cortices, r=0.422, p=0.007; insula, r=0.412, p=0.009, hippocampus, r=0.455, p=0.004; management: prefrontal cortices, r=0.728, p=0.001; insula, r=0.707, p=0.001, hippocampus, r=0.775, p&lt;0.001) (Figure 1). Figure 1 Conclusions HF subjects show more wide-spread and significant correlations between regional GM density values and BDI as well as SCHFI management scores compared to the other disease symptom measures. The findings suggest that damage in mood, autonomic, and cognitive functions sites better correlate with BDI and SCHFI over other measures. Acknowledgement/Funding NIH/NINR 1R01 NR014669

The Different Brain Mechanisms of Object and Spatial Working Memory: Voxel-Based Morphometry and Resting-State Functional Connectivity.

In working memory (WM), the ability to concurrently integrate different types of information and to maintain or manipulate them promotes the flow of ongoing tasks. WM is a key component of normal human cognition. In this study, we applied a combined voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) analysis to investigate the relationship between the ability of object and spatial working memory (WM), and regional gray matter density (GMD), as well as intrinsic functional connectivity. The VBM analysis showed a positive correlation between the individual difference of object WM and GMD in the right middle occipital gyrus (MOG) and the left superior temporal gyrus (STG), which are responsible for coding object information and processing the shape of an object. The individual difference of the spatial WM was positively related to GMD in the right middle frontal gyrus (MFG) located in the dorsolateral prefrontal cortex (dlPFC), which confirmed that it is an important region for memory stores and maintains WM spatial representations. Further functional connectivity analysis revealed that the individual difference of object WM was significantly correlated with the rsFC of right intraparietal sulcus (IPS) – left postcentral gyrus (PostCG)/right precentral gyrus (PreCG)/left Supplementary Motor Area (SMA). While the capacity of spatial WM was significantly associated with the FC strength of the left dlPFC – left precuneus, right dlPFC – right MFG, and the left superior frontal sulcus (SFS) – left SMA/ right inferior parietal lobe (IPL). Our findings suggest that object WM is associated with the structure and functional organization of the brain regions involved in the ventral pathway (occipital – temporal regions) and the capacity of spatial WM is related to the dorsal pathway (frontal – parietal regions).

Individual Differences in Brain Structure and Resting Brain Function Underlie Representation-Connection in Scientific Problem Solving

Evidence from a range of fields shows that representation-connection (RC) is the key step towards the solution of a real-world insight problem. However, no study has focused on the inter-individual variability in RC, and little is known about whether structural and resting-state functional signals can account for inter-individual differences in RC. Combining structural (regional grey matter density, rGMD) and functional (fractional amplitude of low-frequency fluctuations (fALFF) and resting-state functional connectivity (RSFC)) analysis approaches was used to examine the neural substrates of RC. The results showed that the RC score was positively correlated with rGMD and fALFF values in the bilateral lingual gyrus (LG), which might be related to relevant visual imagery during the correct matching of a specific prototype with an unsolved technical problem and the retrieval and application of key information from prototypes. In addition, the RC score was negatively correlated with the rGMD in the left dorsolateral prefrontal cortex (DLPFC), and functional connectivity analysis revealed that a higher RC score was inversely correlated with the strength of the RSFC between the right LG and the left inferior parietal lobule (IPL), which indicated that RC might be supported by decreased response inhibition and the automatic association of semantics.

Cannabis use in youth is associated with limited alterations in brain structure.

Frequent cannabis use during adolescence has been associated with alterations in brain structure. However, studies have featured relatively inconsistent results, predominantly from small samples, and few studies have examined less frequent users to shed light on potential brain structure differences across levels of cannabis use. In this study, high-resolution T1-weighted MRIs were obtained from 781 youth aged 14-22 years who were studied as part of the Philadelphia Neurodevelopmental Cohort. This sample included 147 cannabis users (109 occasional [≤1-2 times per week] and 38 frequent [≥3 times per week] users) and 634 cannabis non-users. Several structural neuroimaging measures were examined in whole brain analyses, including gray and white matter volumes, cortical thickness, and gray matter density. Established procedures for stringent quality control were conducted, and two automated neuroimaging software processing packages were used to ensure robustness of results. There were no significant differences by cannabis group in global or regional brain volumes, cortical thickness, or gray matter density, and no significant group by age interactions were found. Follow-up analyses indicated that values of structural neuroimaging measures by cannabis group were similar across regions, and any differences among groups were likely of a small magnitude. In sum, structural brain metrics were largely similar among adolescent and young adult cannabis users and non-users. Our data converge with prior large-scale studies suggesting small or limited associations between cannabis use and structural brain measures in youth. Detailed studies of vulnerability to structural brain alterations and longitudinal studies examining long-term risk are clearly indicated.

Neural correlates of social well-being: gray matter density in the orbitofrontal cortex predicts social well-being in emerging adulthood.

Social well-being reflects the perception of one’s social functioning, which plays an important role in physical and psychological health. However, the exact neuroanatomical substrate for social well-being remains unclear. To address the issue, we employed the voxel-based morphometry method to probe the neuroanatomical basis of individual variation in social well-being in young healthy adults (n = 136). The results revealed a significant negative association between social well-being and regional gray matter density (rGMD) in an anatomical cluster that mainly includes the left orbitofrontal cortex (OFC) that has been involved in emotion regulation and social cognition. Furthermore, a balanced 4-fold cross-validation using the machine learning approach revealed that rGMD in the left OFC could be reliably related to social well-being. More importantly, the multiple mediation analysis revealed that neuroticism and dispositional forgiveness independently mediated the association between rGMD in the left OFC and social well-being. In addition, all these results remained stable when subjective socioeconomic status was controlled. Together, our results provide the initial evidence that the OFC is a neuroanatomical substrate for social well-being and demonstrate that the OFC is a crucial neural site linking neuroticism and dispositional forgiveness to social well-being.

Effect of the SIRT1 gene on regional cortical grey matter density in the Han Chinese population.

Our previous genome-wide association study (CONVERGE sample) identified significant association between single nucleotide polymorphisms (SNPs) near the SIRT1 gene and major depressive disorder (MDD) in Chinese populations. To investigate whether SNPs across the SIRT1 gene locus affect regional grey matter density in the Han Chinese population. T1-weighted structural magnetic resonance imaging was conducted on 92 healthy participants from Eastern China. Grey matter was segmented from the image, which consisted of voxel-wise grey matter density. The effect of SIRT1 SNPs on grey matter density was determined by a multiple linear regression framework. SNP rs4746720 was significantly associated with grey matter density in two brain cortical regions: the orbital part of the right inferior frontal gyrus and the orbital part of the left inferior frontal gyrus (family-wise error-corrected P < 0.05; voxel-wise P < 0.001). Also, rs4746720 exceeded genome-wide significance in association with MDD in our CONVERGE sample (P = 3.32 × 10-08, odds ratio 1.161). Our results provided evidence for a potential role of the SIRT1 gene in the brain, implying a possible pathophysiological mechanism underlying susceptibility to MDD.