Alterations in Brain Morphometric Networks and Their Relationship with Memory Dysfunction in Patients with Type 2 Diabetes Mellitus.

Cognitive dysfunction, a significant complication of type 2 diabetes mellitus (T2DM), can potentially manifest even from the early stages of the disease. Despite evidence of global brain atrophy and related cognitive dysfunction in early-stage T2DM patients, specific regions vulnerable to these changes have not yet been identified. The study enrolled patients with T2DM of less than five years' duration and without chronic complications (T2DM group, n=100) and demographically similar healthy controls (control group, n=50). High-resolution T1-weighted magnetic resonance imaging data were subjected to independent component analysis to identify structurally significant components indicative of morphometric networks. Within these networks, the groups' gray matter volumes were compared, and distinctions in memory performance were assessed. In the T2DM group, the relationship between changes in gray matter volume within these networks and declines in memory performance was examined. Among the identified morphometric networks, the T2DM group exhibited reduced gray matter volumes in both the precuneus (Bonferroni-corrected p=0.003) and insular-opercular (Bonferroni-corrected p=0.024) networks relative to the control group. Patients with T2DM demonstrated significantly lower memory performance than the control group (p=0.001). In the T2DM group, reductions in gray matter volume in both the precuneus (r=0.316, p=0.001) and insular-opercular (r=0.199, p=0.047) networks were correlated with diminished memory performance. Our findings indicate that structural alterations in the precuneus and insular-opercular networks, along with memory dysfunction, can manifest within the first 5 years following a diagnosis of T2DM.

Changes in Structural Covariance among Olfactory-related Brain Regions in Anosmia Patients.

Anosmia, characterized by the loss of smell, is associated not only with dysfunction in the peripheral olfactory system but also with changes in several brain regions involved in olfactory processing. Specifically, the orbitofrontal cortex is recognized for its pivotal role in integrating olfactory information, engaging in bidirectional communication with the primary olfactory regions, including the olfactory cortex, amygdala, and entorhinal cortex. However, little is known about alterations in structural connections among these brain regions in patients with anosmia. In this study, high-resolution T1-weighted images were obtained from participants. Utilizing the volumes of key brain regions implicated in olfactory function, we employed a structural covariance approach to investigate brain reorganization patterns in patients with anosmia (n=22) compared to healthy individuals (n=30). Our structural covariance analysis demonstrated diminished connectivity between the amygdala and entorhinal cortex, components of the primary olfactory network, in patients with anosmia compared to healthy individuals (z=-2.22, FDR-corrected p=0.039). Conversely, connectivity between the orbitofrontal cortex-a major region in the extended olfactory network-and amygdala was found to be enhanced in the anosmia group compared to healthy individuals (z=2.32, FDR-corrected p=0.039). However, the structural connections between the orbitofrontal cortex and entorhinal cortex did not differ significantly between the groups (z=0.04, FDR-corrected p=0.968). These findings suggest a potential structural reorganization, particularly of higher-order cortical regions, possibly as a compensatory effort to interpret the limited olfactory information available in individuals with olfactory loss.

Impact of sleep disturbance in shift workers on hippocampal volume and psychomotor speed.

STUDY OBJECTIVES: Shift work interferes with circadian rhythms, affecting sleep quality and cognitive function. Poor sleep quality in shift workers can impair psychomotor performance due to fatigue and sleepiness, increasing the risk of errors, accidents, and reduced productivity. Given the potential for atrophic changes in the hippocampus due to sleep disturbances, our study investigates how poor sleep quality correlates with hippocampal structural alterations and impacts psychomotor performance among shift workers. METHODS: We recruited 100 shift workers, classifying them based on sleep quality into two groups: good sleep-SW group (n = 59) and poor sleep-SW group (n = 41). Sleep quality was assessed using both 7-day actigraphy for sleep efficiency and the Pittsburgh Sleep Quality Index. A control group of 106 non-shift workers without sleep problems (non-SW group) was also included for comparison. The outcome measures were psychomotor speed and hippocampal volumes, both total and by subfield. RESULTS: The poor sleep-SW group showed significantly smaller hippocampal volumes than both the good sleep-SW group (P<0.001) and the non-SW group (P=0.003). Longer shift work years correlated with greater reductions in hippocampal volume in this group (r=-0.42, P=0.009), unlike in the good sleep-SW group (r=0.08, P=0.541). Furthermore, they demonstrated declines in psychomotor speed relative to the non-SW group (P=0.006), which correlated with smaller hippocampal volumes (r=0.37, P=0.020). CONCLUSIONS: Shift workers with poor sleep quality exhibit significant hippocampal volume reductions and psychomotor speed decline, underscoring the importance of early intervention and support for sleep issues in this population.

Brain Age Prediction Using Multi-Hop Graph Attention Combined with Convolutional Neural Network.

Convolutional neural networks (CNNs) have been used widely to predict biological brain age based on brain magnetic resonance (MR) images. However, CNNs focus mainly on spatially local features and their aggregates and barely on the connective information between distant regions. To overcome this issue, we propose a novel multi-hop graph attention (MGA) module that exploits both the local and global connections of image features when combined with CNNs. After insertion between convolutional layers, MGA first converts the convolution-derived feature map into graph-structured data by using patch embedding and embedding-distance-based scoring. Multi-hop connections between the graph nodes are modeled by using the Markov chain process. After performing multi-hop graph attention, MGA re-converts the graph into an updated feature map and transfers it to the next convolutional layer. We combined the MGA module with sSE (spatial squeeze and excitation)-ResNet18 for our final prediction model (MGA-sSE-ResNet18) and performed various hyperparameter evaluations to identify the optimal parameter combinations. With 2788 three-dimensional T1-weighted MR images of healthy subjects, we verified the effectiveness of MGA-sSE-ResNet18 with comparisons to four established, general-purpose CNNs and two representative brain age prediction models. The proposed model yielded an optimal performance with a mean absolute error of 2.822 years and Pearson's correlation coefficient (PCC) of 0.968, demonstrating the potential of the MGA module to improve the accuracy of brain age prediction.

Brain age prediction using combined deep convolutional neural network and multi-layer perceptron algorithms.

The clinical applications of brain age prediction have expanded, particularly in anticipating the onset and prognosis of various neurodegenerative diseases. In the current study, we proposed a deep learning algorithm that leverages brain structural imaging data and enhances prediction accuracy by integrating biological sex information. Our model for brain age prediction, built on deep neural networks, employed a dataset of 3004 healthy subjects aged 18 and above. The T1-weighted images were minimally preprocessed and analyzed using the convolutional neural network (CNN) algorithm. The categorical sex information was then incorporated using the multi-layer perceptron (MLP) algorithm. We trained and validated both a CNN-only algorithm (utilizing only brain structural imaging data), and a combined CNN-MLP algorithm (using both structural brain imaging data and sex information) for age prediction. By integrating sex information with T1-weighted imaging data, our proposed CNN-MLP algorithm outperformed not only the CNN-only algorithm but also established algorithms, such as brainageR, in prediction accuracy. Notably, this hybrid CNN-MLP algorithm effectively distinguished between mild cognitive impairment and Alzheimer's disease groups by identifying variances in brain age gaps between them, highlighting the algorithm's potential for clinical application. Overall, these results underscore the enhanced precision of the CNN-MLP algorithm in brain age prediction, achieved through the integration of sex information.

Cerebral cortical thinning in brain regions involved in emotional regulation relates to persistent symptoms in subjects with posttraumatic stress disorder.

A considerable proportion of individuals exposed to trauma experience chronic and persistent posttraumatic stress disorder (PTSD). However, the specific brain and clinical features that render trauma-exposed individuals more susceptible to enduring symptoms remain elusive. This study investigated 112 trauma-exposed participants who had been diagnosed with PTSD and 112 demographically-matched healthy controls. Trauma-exposed participants were classified into those with current PTSD (persistent PTSD, n = 78) and those without (remitted PTSD, n = 34). Cortical thickness analysis was performed to discern group-specific brain structural characteristics. Coping strategies and resilience levels, assessed as clinical attributes, were compared across the groups. The persistent PTSD group displayed cortical thinning in the superior frontal cortex (SFC), insula, superior temporal cortex, dorsolateral prefrontal cortex, superior parietal cortex, and precuneus, relative to the remitted PTSD and control groups. Cortical thinning in the SFC was associated with increased utilization of maladaptive coping strategies, while diminished thickness in the insula correlated with lower resilience levels among trauma-exposed individuals. These findings imply that cortical thinning in brain regions related to coping strategy and resilience plays a vital role in the persistence of PTSD symptoms.

Differential alterations in brain structural network organization during addiction between adolescents and adults.

BACKGROUND: The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear. METHODS: Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls). RESULTS: MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents. CONCLUSIONS: Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.

Hippocampal subregional alterations and verbal fluency in the early stage of type 2 diabetes mellitus.

Growing evidence indicates that type 2 diabetes mellitus (T2DM)-related cognitive dysfunction may develop in the early stage of the disease and is often accompanied by hippocampal structural alterations. In the current study, we investigated volume and shape alterations of the hippocampus at a subregional level in patients with T2DM. With the use of high-resolution brain structural images that were obtained from 30 T2DM patients with less than 5 years of disease duration and 30 healthy individuals, volumetric and shape analyses were performed. We also assessed the relationship between T2DM-related hippocampal structural alterations and performance on verbal fluency. In volumetric analysis, total hippocampal volume was smaller in the T2DM group, relative to the control group. At a subregional level, T2DM patients showed significant inward deformation and volume reduction of the right dentate gyrus and cornu ammonis 2/3 subregions as compared with healthy individuals. In particular, T2DM patients with lower performance on verbal fluency had smaller right dentate gyrus volumes relative to those with higher performance. These findings suggest that the hippocampus may undergo atrophy at a subregional level even in the early stage of T2DM, and this subregion-specific atrophy may be associated with reduced performance on verbal fluency.

Severity of post-traumatic stress disorder and childhood abuse in adult crime victims as mediated by low resilience and dysfunctional coping strategies.

BACKGROUND: Experience of childhood abuse has been suggested to increase the severity of post-traumatic stress disorder (PTSD) in adulthood. We hypothesized that resilience and coping strategies, which could be altered by experiencing childhood abuse, may mediate the effects of childhood abuse on PTSD severity in adulthood. METHODS: Crime victims with PTSD (n = 212, 38 men, aged 20-65 years) were recruited from South Korea. PTSD severity, a history of childhood abuse, resilience level, and use of coping strategies were assessed using structured clinical interviews and self-report questionnaires. Upon identifying the key factors that were associated with childhood abuse and PTSD severity, mediating roles of these key factors were examined using structural equation modeling and bootstrapping in simple and multiple mediation analyses. RESULTS: Resilience and dysfunctional coping strategies mediated the association between childhood abuse and lifetime PTSD severity in the adulthood, after covarying for the number of repeated trauma exposure (total effect: ß = 0.44, P = 0.01, 95% CI [0.10, 0.77]; direct effect: ß = 0.02, P = 0.90, 95% CI [-0.34, 0.38]; indirect effect: ß = 0.42, P = 0.003, 95% CI [0.14, 0.69]). LIMITATIONS: Recall of childhood abuse experience and lifetime PTSD severity can be biased in crime victims. CONCLUSIONS: These findings may suggest that resilience and coping strategies mediate the detrimental effects of childhood abuse on lifetime PTSD severity. Targeted treatments that are designed to enhance resilience as well as deter the use of dysfunctional coping strategies may be of help in crime victims with a history of childhood abuse.

Changes in Prefrontal Gamma-Aminobutyric Acid and Perfusion After the Computerized Relaxation Training in Women With Psychological Distress: A Preliminary Report.

Computerized relaxation training has been suggested as an effective and easily accessible intervention for individuals with psychological distress. To better elucidate the neural mechanism that underpins the effects of relaxation training, we investigated whether a 10-session computerized relaxation training program changed prefrontal gamma-aminobutyric acid (GABA) levels and cerebral blood flow (CBF) in women with psychological distress. We specifically focused on women since they were reported to be more vulnerable to develop stress-related disorders than men. Nineteen women with psychological distress but without a diagnosis of psychiatric disorders received the 10-day computerized relaxation training program that consisted of 30-min cognitive-relaxation training and 10-min breathing-relaxation training per day. At baseline and post-intervention, perceived stress levels, anxiety, fatigue, and sleep quality were assessed by self-report questionnaires. Brain magnetic resonance spectroscopy and arterial spin labeling scans were also performed before and after the intervention to evaluate GABA levels and relative CBF in the prefrontal region. Levels of perceived stress (t = 4.02, P < 0.001), anxiety (z = 2.33, P = 0.02), fatigue (t = 3.35, P = 0.004), and sleep quality (t = 4.14, P < 0.001) improved following 10 sessions of computerized relaxation training, resulting in a significant relief in composite scores of stress-related symptoms (t = -5.25, P < 0.001). The prefrontal GABA levels decreased (t = 2.53, P = 0.02), while relative CBF increased (t = -3.32, P = 0.004) after the intervention. In addition, a greater increase in relative prefrontal CBF was associated with better composite scores of stress-related symptoms following the intervention (t = 2.22, P = 0.04). The current findings suggest that computerized relaxation training may improve stress-related symptoms through modulating the prefrontal GABA levels and CBF in women with psychological distress.

Hippocampal cerebral blood flow increased following low-pressure hyperbaric oxygenation in firefighters with mild traumatic brain injury and emotional distress.

BACKGROUND: Recent evidence suggests that hyperbaric oxygenation (HBO), which has been used as an effective treatment for certain types of tissue injury, may change neural activities in the human brain and subsequently improve symptoms of psychiatric disorders. To scrutinize the neural mechanism of HBO in the human brain, we investigated whether 20 sessions of HBO changed regional cerebral blood flow (rCBF) of the limbic system in firefighters with mild traumatic brain injury (mTBI) and subjective emotional distress. METHODS: Twenty firefighters with mTBI and mild emotional distress were treated with HBO at a relatively low pressure of 1.3 atmospheres absolute for 45 min a day for 20 consecutive days (the mild emotional distress group). The rCBF of the limbic system was measured using an arterial spin labeling perfusion magnetic resonance imaging before and after the HBO. Analyses were performed on the data from fourteen individuals who completed the study and 14 age- and sex-matched healthy firefighters (the comparison group). RESULTS: Firefighters in the mild emotional distress group showed increase rCBF following HBO in a cluster encompassing the right hippocampal and parahippocampal regions (peak t = 4.31; cluster size = 248 mm3)(post-hoc analysis, z = 5.92, p < 0.001) that had lower rCBF relative to the comparison group at baseline (post-hoc analysis, t = -2.20, p = 0.04). CONCLUSION: The current study demonstrated that low-pressure HBO might increase rCBF of the hippocampal and parahippocampal regions, suggesting a potential underpinning mechanism of HBO in the human brain.

A double-hit of stress and low-grade inflammation on functional brain network mediates posttraumatic stress symptoms.

Growing evidence indicates a reciprocal relationship between low-grade systemic inflammation and stress exposure towards increased vulnerability to neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, the neural correlates of this reciprocity and their influence on the subsequent development of PTSD are largely unknown. Here we investigated alterations in functional connectivity among brain networks related to low-grade inflammation and stress exposure using two large independent data sets. Functional couplings among the higher-order cognitive network system including the salience, default mode, and central executive networks were reduced in association with low-grade inflammation and stress exposure. This reduced functional coupling may also be related to subsequent posttraumatic stress symptom severity. The current findings propose functional couplings among the higher-order cognitive network system as neural correlates of low-grade inflammation and stress exposure, and suggest that low-grade inflammation, alongside with stress, may render individuals more vulnerable to PTSD.