47,XXX (Triple X syndrome) is a sex chromosome aneuploidy characterized by the presence of a supernumerary X chromosome in affected females, and has been associated with a variable cognitive, behavioral, and psychiatric phenotype. Alterations in brain gray matter structure and function have been reported, but less is known about white matter (WM) organization in 47,XXX. Therefore, we conducted 7 T diffusion tensor imaging and characterized fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of 22 adult women with 47,XXX and 22 age-matched typically developing females using tract-based spatial statistics. Relationships between phenotypic traits and WM organization characteristics in 47,XXX were also investigated. Adults with 47,XXX showed lower axial diffusivity in the body of the corpus callosum and the right superior longitudinal fasciculus. WM organization variability was not associated with IQ and social cognition and social functioning deficits in 47,XXX. Our findings indicate an effect of a supernumerary X chromosome in adult women on axonal integrity of the body of the corpus callosum and the right superior longitudinal fasciculus. These findings provide additional insight into the role of the X chromosome on WM organization. Future research is warranted to explore the clinical significant impact of altered WM organization in 47,XXX.

This study aims to explore the relationship between eye movement characteristics and cognitive function in adolescents with major depressive disorder (MDD).

Negative symptoms are often found in youth at clinical high risk (CHR) for psychosis. The present study explored the feasibility of using tDCS in conjunction with CBT in the treatment of negative symptoms in 5 youths at CHR. We sought to determine whether the protocol was feasible given the requirement for repeated visits over a three-week period, and to determine if measures of neurobiological change could be included, both acutely and following three weeks of stimulation. The results from this study suggest that the protocol is feasible for these youth, and the inclusion of MRI scanning sessions yielded good quality data.

The limbic system and the hippocampus are complex brain structures with key roles in memory, emotions, sexual stimulation and learning, with subregion abnormalities associated with a range of disorders and psychopathologies. Our study aimed to explore the heritability of specific subfield structures within the limbic system and hippocampus first in a Caucasian twin sample with volBrain pipeline.

Obsessive-compulsive disorder (OCD) is characterized by structural alteration within white matter tissues of cortico-striato-thalamo-cortical, temporal and occipital circuits. However, the presence of microstructural changes in the white matter tracts of unaffected first-degree relatives of patients with OCD as a vulnerability marker remains unclear. Therefore, here, diffusion-tensor magnetic resonance imaging (DTI) data were obtained from 29 first-degree relatives of patients with OCD and 59 healthy controls. We investigated the group differences in FA using whole-brain analysis (DTI analysis). For additional regions of interest (ROI) analysis, we focused on the posterior thalamic radiation and sagittal stratum, shown in recent meta-analysis of patients with OCD. In both whole-brain and ROI analyses, using a strict statistical threshold (family-wise error rate [FWE] corrected p<.05 for whole-brain analyses, and p<.0125 (0.05/4) with Bonferroni correction for ROI analyses), we found no significant group differences in FA. Subtle reductions were observed in the anterior corona radiata, forceps minor, cingulum bundle, and corpus callosum only when a lenient statistical was applied (FWE corrected p<.20). These findings suggest that alterations in the white matter microstructure of first-degree relatives, as potential vulnerability markers for OCD, are likely subtle.

Many psychopathologies tied to internalizing symptomatology emerge during adolescence, therefore identifying neural markers of internalizing behavior in childhood may allow for early intervention. We utilized data from the Adolescent Brain and Cognitive Development (ABCD) Study® to evaluate associations between cortico-amygdalar functional connectivity, polygenic risk for depression (PRS), traumatic events experienced, internalizing behavior, and internalizing subscales: withdrawn/depressed behavior, somatic complaints, and anxious/depressed behaviors. Data from 6371 children (ages 9-11) were used to analyze amygdala resting-state fMRI connectivity to Gordon parcellation based whole-brain regions of interest (ROIs). Internalizing behaviors were measured using the parent-reported Child Behavior Checklist. Linear mixed-effects models were used to identify patterns of cortico-amygdalar connectivity associated with internalizing behaviors. Results indicated left amygdala connections to auditory, frontoparietal network (FPN), and dorsal attention network (DAN) ROIs were significantly associated with withdrawn/depressed symptomatology. Connections relevant for withdrawn/depressed behavior were linked to social behaviors. Specifically, amygdala connections to DAN were associated with social anxiety, social impairment, and social problems. Additionally, an amygdala connection to the FPN ROI and the auditory network ROI was associated with social anxiety and social problems, respectively. Therefore, it may be important to account for social behaviors when looking for brain correlates of depression.

Excessive Smartphone Use (ESU) poses a significant challenge in contemporary society, yet its recognition as a distinct disorder remains ambiguous. This study aims to address this gap by leveraging functional magnetic resonance imaging (fMRI) data and machine learning techniques to classify ESU and non-excessive smartphone users (n-ESU) based on their neural Cue-Reactivity (CR) signatures. By conducting a CR task and analyzing brain activation patterns, we identified spatial similarities between addictive smartphone use and established addictive disorders. Our approach involved employing Support Vector Machines (SVM) for classification, enhanced with feature selection methods such as Recursive Feature Elimination (RFE) and Model-based Selection and dimensionality reduction methods such as and Principal Component Analysis (PCA) to mitigate the challenges posed by limited dataset size and high dimensionality of fMRI data. The results demonstrate the effectiveness of our classification model, achieving accuracies of up to 79.9 %. Furthermore, we observed region-specific activations contributing significantly to classification accuracy, highlighting the potential biomarkers associated with ESU. External validation on longitudinal data revealed the necessity for larger training datasets to improve model generalizability. Additionally, feature selection techniques proved crucial for optimizing model performance, particularly in datasets with combined information from multiple sources. Our findings underscore the importance of incorporating more data to enhance model stability and generalizability, with implications for advancing the understanding and treatment of ESU and related disorders. Overall, our study demonstrates the promise of machine learning approaches in elucidating neural correlates of ESU and informing targeted interventions for affected individuals.

Significant evidence links obesity and schizophrenia (SZ), but the brain associations are still largely unclear. 48 people with SZ were divided into two subgroups: patients with lower waist circumference (SZ-LWC: n = 24) and patients with higher waist circumference (SZ-HWC: n = 24). Healthy controls (HC) were included for comparison (HC: n = 27). Using tract-based spatial statistics, we compared fractional anisotropy (FA) of the whole-brain white matter skeleton between these three groups (SZ-LWC, SZ-HWC, HC). Using Free Surfer, we compared whole-brain cortical thickness and the selected subcortical volumes between the three groups. FA of widespread white matter and the mean cortical thickness in the right temporal lobe and insular cortex were significantly lower in the SZ-HWC group than in the HC group. The FA of regional white matter was significantly lower in the SZ-LWC group than in the HC group. There were no significant differences in mean subcortical volumes between the groups. Additionally, the cognitive performances were worse in the SZ-HWC group, who had more severe triglycerides elevation. This study provides evidence for microstructural abnormalities of white matter, cortical thickness and neurocognitive deficits in SZ patients with excessive abdominal obesity.

Our goal is to uncover Electroencephalography (EEG) power spectrum patterns during imagination tasks in individuals who attempted suicide within the past 1-4 weeks, addressing gaps in understanding the neural correlates of future imagination in suicidal behavior.

According to the cortico-striato-thalamo-cortical (CSTC) model of obsessive-compulsive disorder (OCD), the striatum plays a primary role in its neuropathophysiology. Hypothesising that volumetric alterations are more pronounced in subcortical areas of patients within the CSTC circuit compared to healthy controls (HCs), we conducted a coordinate-based meta-analysis of magnetic resonance imaging (MRI) studies. We included 26 whole-brain MRI studies, comprising 3,010 subjects: 1,508 patients (788 men, 720 women; mean age: 30.26 years, SD = 8.16) and 1,502 HCs (801 men, 701 women; mean age: 29.47 years, SD = 7.88). This meta-analysis demonstrated significant grey matter volume increases in the bilateral putamen, lateral globus pallidus, left parietal cortex, right pulvinar, and left cerebellum in adults with OCD, alongside decreases in the right hippocampus/caudate, bilateral medial frontal gyri, and other cortical regions. Volume increases were predominantly observed in subcortical areas, with the exception of the left parietal cortex and cerebellar dentate, while volume decreases were primarily cortical, aside from the right hippocampus/caudate. Further exploration of these neuropathophysiological correlates could inform specific prevention and treatment strategies, advancing precision mental health in clinical applications.

Recent clinical and theoretical frameworks suggest that social skills and theory of mind impairments characteristic of autism spectrum disorder (ASD) are distributed in the general population on a continuum between healthy individuals and patients. The present multimodal study aimed at investigating the amygdala's function, perfusion, and volume in 56 non-clinical subjects from the general population with high (n = 28 High-SOC) or low (n = 28 Low-SOC) autistic-like social skills traits. Participants underwent magnetic resonance imaging to evaluate the amygdala's functional connectivity at rest, blood perfusion by means of arterial spin labelling, its activation during a face evaluation task and lastly grey matter volumes. The High-SOC group was characterised by higher blood perfusion in both amygdalae, lower volume of the left amygdala and higher activations of the right amygdala during processing of human faces with fearful value. Resting state analyses did not reveal any significant difference between the two groups. Overall, our results highlight the presence of overlapping morpho-functional alterations of the amygdala between healthy individuals and ASD patients confirming the importance of the amygdala in this disorder and in social and emotional processing. Our findings may help disentangle the neurobiological facets of ASD elucidating aetiology and the relationship between clinical symptomatology and neurobiology.

Rumination is a common symptom in major depressive disorder (MDD). Previous work has connected individual differences in rumination to structural properties in various brain regions. Some of these, such as the dorsolateral prefrontal cortex (dlPFC), have also been highlighted as being altered in MDD, suggesting a connection between structural changes and ruminative symptoms. Although informative, such localised relations have limitations in the context of a network view of the brain. To further investigate rumination-related structural changes in depression, and to situate these within potential functional networks, we acquired T1-weighted structural MRI data from patients with MDD (n = 32) and controls (n = 69). Rumination was measured with the Rumination Response Scale. Surface-based, whole-brain analysis of cortical grey-matter identified group differences in the dlPFC that were, however, not related to rumination. Instead, rumination was correlated with grey-matter properties in the right precuneus. Using normative functional connectivity analysis on an independent sample (n = 100), we show these two regions to be interconnected. Further developing a network-based perspective, it was shown that the rumination-related precuneus region is connected with networks associated with processes such as executive function, autobiographical memory, and visual perception. Notably, these processes have been connected to rumination. These results suggest that rumination in depression may be linked to focal structural changes. The effects of these focal changes on rumination may then be connected to their influence on distributed functional networks.

Major depressive disorder (MDD) often coexists with anxiety disorders or symptoms, as identified by previous functional magnetic resonance imaging (fMRI) studies. These studies have found abnormal amplitudes of low-frequency fluctuations (ALFF) in the amygdala, which serve as traits and state markers of MDD. This study used standardized weighted low-resolution electromagnetic tomography (swLORETA) technology to explore amygdala markers in patients with comorbid MDD and anxiety. Participants included patients with MDD comorbid with anxiety symptoms (MDD group) and healthy controls (HC group) who completed the Beck Depression Inventory-II (BDI-II) and the Beck Anxiety Inventory (BAI). EEG data collected under resting state, happiness recall, and depressive recall tasks were converted into current-source density (CSD) values using swLORETA to assess amygdala activation. The results indicated higher beta2, beta3, and high beta levels in both the left and right amygdalae during the resting state in the MDD group than in the HC group. Similarly, elevated levels of beta2, beta3, and high beta were observed in the left and right amygdalae of the MDD group during happiness and depressive recall tasks. These findings support the presence of hyperactivity in the amygdala under resting state and emotional tasks in patients with comorbid MDD and anxiety symptoms.

Empirical findings suggest reduced cortico-striatal structural connectivity in patients with major depressive disorder (MDD). However, the relationship between the abnormal structural covariance and one-year outcome of first-episode drug-naive patients has not been evaluated. This longitudinal study aimed to identify specific changes of ventral striatum-related brain structural covariance and grey matter volume in forty-two first-episode patients with major depression disorder compared with thirty-seven healthy controls at the baseline and the one-year follow-up conditions. At the baseline, patients showed decreased structural covariance between the left ventral striatum and the bilateral superior frontal gyrus (SFG), bilateral middle frontal gyrus (MFG), right supplementary motor area (SMA) and left precentral gyrus and increased grey matter volume at the left fusiform and left parahippocampus. At the one-year follow-up, patients showed decreased structural covariance between the left ventral striatum and the right SFG, right MFG, left precentral gyrus and left postcentral gyrus, and increased structural covariance between the right ventral striatum and the right amygdala, right hippocampus, right parahippocampus, right superior temporal pole, right insula and right olfactory bulb and decreased volume at the left SMA compared with controls. These findings suggest that specific ventral striatum connectivity changes contribute to the early brain development of the MDD.

The experience of self-hood in posttraumatic stress disorder (PTSD) is altered cognitively and somatically. Dysfunctional negative cognitions about the self are a central mechanism of PTSD symptomatology and treatment. However, while higher-order brain models of disturbances in self-appraisal (i.e., cognitive processes relating to evaluating the self) have been examined in other psychiatric disorders, it is unclear how normative brain function during self-appraisal is impaired in PTSD.

Substance use is a chronic and recurrent public healthcare concern increasing in the world, causing negative outcomes. Two or more substance use is common among people who have substance use disorders and who receive treatment. For this reason, the present study aimed to measure Retinal Nerve Fiber Layer (RNFL), Mean Macular Thickness (MMT), Central Macular Thickness (CMT) in patients who have Multiple substance use disorder (MSUD) using Optical Coherence Tomography (OCT), considering that it will contribute to the literature. Among the inpatients who were rehabilitated in Elazig Mental Hospital Alcohol and Substance Addiction Treatment Center, 75 people who were diagnosed with MSUD according to DSM-5 and met the criteria, and 51 control groups were included in the study. RNFL, MMT and CMT measurements of both eyes of all participants were made by using the OCT. Total RNFL measurement were significantly thicker than the control group (p < 0.001). MMT and CMT of the eyes of the patient were thinner than the control group (p = 0.009, p < 0.001). The findings provide important contributions to the literature data and in light of these findings, it can be recommended to consider visual findings and possible neurodegeneration when evaluating patients in the addiction group and planning their treatment.

Approximately 7-10% of people experiencing bereavement following a death develop prolonged grief disorder, a psychiatric disorder included in the DSM-5-TR. Prolonged grief disorder encompasses core symptoms of intense yearning/longing for and preoccupation with thoughts or memories of the deceased person experienced to a clinically significant degree for at least the last month, other key associated symptoms (e.g., avoidance, emotional pain), and the death must have occurred at least one year prior to diagnosis. Extant research has shown a relationship between activation in the reward pathway (e.g., nucleus accumbens) and grief severity. To date, functional MRI studies have primarily utilized the Emotional Counting Stroop task (ecStroop) and the Grief Elicitation task to explore these relationships. However, these prior studies are not without limitations, including small sample sizes and absence of a unified task protocol, hindering meaningful comparisons between studies. This protocol paper describes the ecStroop task and the Grief Elicitation task, which will be vital for facilitating multisite studies and enabling comparisons across studies. This will aid to advance the field by identifying neurophysiological measures that may, in the future, serve as potential biomarkers of prolonged grief disorder.

To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features.

Although proven neuronal changes are correlated with anorexia nervosa (AN), where these changes occur and how they change during the course of this disease are often unclear; this is especially true regarding emotion processing, e.g., of anxiety, despite a growing body of literature on its importance for the pathophysiology and clinical course of patients with AN.

Individuals with borderline personality traits are known to have disturbed representations of self and others. Specifically, an unstable self-identity and difficulties distinguishing between self and others can impair their mentalizing abilities in interpersonal situations. However, it is unclear whether these traits are linked to differences in neural representation of self and others.

Emotional dysregulation is a serious and impairing mental health problem. We examined functional activity and connectivity of neural networks involved in emotional dysregulation at baseline and following a pilot neurostimulation-enhanced cognitive restructuring intervention in a transdiagnostic clinical adult sample.

Aging-induced hepatic dysfunction can impair cholesterol metabolism, reducing the availability of cholic acid (CA, bile-acid) in brain. CA is reported to have neuroprotective characteristics in preclinical investigations of Alzheimer's disease (AD). Our aim is to probe the causal-connectivity between the players: amyloid, cholic acid and cerebral-blood-flow, and thereby explore therapeutic applicability in AD. From AD neuroimaging initiative biospecimen platform, we evaluated serum cholic-acid (182 healthy/136 AD individuals). We also assessed 50 healthy/50 Alzheimer's subjects containing MRI-ASL scanning (cerebral blood-flow, CBF) and PET-AV45 scanning (amyloid-load). We performed computational causal connectivity to determine the cause-effect relationship among the parameters. Serum cholic acid in AD subjects substantially decreased to half of controls. Causal-connectivity revealed two novel causative pathways: (i) Decreasing serum CA markedly increased amyloid-load; (ii) Increasing amyloid-load distinctly decreased CBF. We substantiated these two causation pathways respectively with collateral available preclinical observations: (a) increased cholic acid reduces amyloid formation by diminishing gamma-secretase; (b) this decreased amyloid induces capillary-flow enhancement by relaxing vascular pericytes. Indeed, cholic acid can increase amyloid-clearance factor. Neuroimaging-based causal connectivity analysis showed that repositioned pharmacological modulation by cholate derivatives may have appreciable potential as novel window for therapeutic approach to AD. Indicative clinical validation is furnished from available therapeutic trial leads.

Major depressive disorder in old age can cause changes in the cerebral cortex that might lead to postural imbalance and thus increase fall risk. We aim to examine cortical activation during standing balance in depressed older patients compared to healthy controls and to determine how an additional cognitive task affects this activation. Eleven older patients (age ≥65 years) diagnosed with major depressive disorder and sixteen age-matched healthy controls participated in the study. Functional near-infrared spectroscopy (fNIRS) was used to assess cortical activation of the prefrontal (PFC) and motor (MC) cortex during standing balance with eyes closed under single and dual task (counting backwards). The present study generally revealed tendencies in the MC - and partly the PFC too - for more activation whilst balancing compared to baseline. Also, in the MC, patients tended to show more cortical activation compared to controls and dual task tended to elicit more activation. The results suggest that depressed older patients, to compensate for their illness, may require increased cortical activation to perform motor and cognitive tasks than healthy controls. The absence of PFC activation in the main analyses may be related to the small participant number and possibly to too simple task conditions.

The hypothalamus is an important component of the hypothalamic-pituitary-adrenal axis and an important brain region of the limbic system. Twenty-four first depressive episode(FDE) patients and 25 healthy controls were recruited for this study. The hypothalamus was used as a seed to observe the characteristics of resting state and dynamic functional connectivity (FC) changes in FDE patients, and further observed the correlation between the different brain regions and clinical symptoms. The results found that compared with the HC group, the FDE group showed sFC was increased of the left hypothalamus with right superior parietal gyrus and right middle temporal gyrus, and dFC was increased of the left hypothalamus with left inferior occipital gyrus. And sFC was increased of the right hypothalamus with right orbital part of inferior frontal gyrus, right supplementary motor area, and right middle temporal gyrus, and the dFC was also increased of right hypothalamus with right superior parietal gyrus and left middle temporal gyrus. In addition,there was a negative correlation between dFC values of the right hypothalamus with the right superior parietal gyrus and clinical symptoms in the FDE group. This study provides new insights into understanding the altered neuropathological mechanisms of the hypothalamic circuit in FDE.

Mood disorders, particularly bipolar disorder (BD) and major depressive disorder (MDD), manifest changes in brain structure that can be detected using structural magnetic resonance imaging (MRI). Although structural MRI is a promising diagnostic tool, prevailing diagnostic criteria for BD and MDD are predominantly subjective, sometimes leading to misdiagnosis. This challenge is compounded by a limited understanding of the underlying causes of these disorders. In response, we present SE-ResNet, a Residual Network (ResNet)-based framework designed to discriminate between BD, MDD, and healthy controls (HC) using structural MRI data. Our approach extends the traditional Squeeze-and-Excitation (SE) layer by incorporating a dedicated branch for spatial attention map generation, equipped with soft-pooling, a 7 × 7 convolution, and a sigmoid function, intended to detect complex spatial patterns. The fusion of channel and spatial attention maps through element-wise addition aims to enhance the model's ability to discriminate features. Unlike conventional methods that use max-pooling for downsampling, our methodology employs soft-pooling, which aims to preserve a richer representation of input features and reduce data loss. When evaluated on a proprietary dataset comprising 303 subjects, the SE-ResNet achieved an accuracy of 85.8 %, a recall of 85.7 %, a precision of 85.9 %, and an F1 score of 85.8 %. These performance metrics suggest that the SE-ResNet framework has potential as a tool for detecting psychiatric disorders using structural MRI data.

Schizophrenia patients frequently present with structural and functional abnormalities of the ventral striatum (VS).

Recent fMRI resting-state findings show aberrant functional connectivity within somatomotor network (SMN) in schizophrenia. Moreover, functional connectivity aberrations of the motor system are often reported to be related to the severity of psychotic symptoms. Thus, it is important to validate those findings and confirm their relationship with psychopathology. Therefore, we decided to take an entirely data-driven approach in our fMRI resting-state study of 30 chronic schizophrenia outpatients and 30 matched control subjects. We used independent component analysis (ICA), dual regression, and seed-based connectivity analysis. We found reduced functional connectivity within SMN in schizophrenia patients compared to controls and SMN hypoconnectivity with the cerebellum in schizophrenia patients. The latter was strongly correlated with the severity of alogia, one of the main psychotic symptoms, i.e. poverty of speech and reduction in spontaneous speech,. Our results are consistent with the recent knowledge about the role of the cerebellum in cognitive functioning and its abnormalities in psychiatric disorders, e.g. schizophrenia. In conclusion, the presented results, for the first time clearly showed the involvement of the cerebellum hypoconnectivity with SMN in the persistence and severity of alogia symptoms in schizophrenia.

A large body of literature exists on white matter (WM) abnormalities in individuals with anorexia nervosa (AN). However, these studies have primarily relied on the diffusion tensor imaging (DTI), a technique known for its limited ability to resolve complex WM fibre arrangements. To overcome limitations of DTI, this study employed fixel-based analysis (FBA) to investigate fibre-specific WM abnormalities in AN. FBA, which incorporates information on connectivity and crossing-fibres, offers greater anatomical specificity and interpretability than DTI. Twenty-six acute AN patients and thirty-one healthy controls underwent diffusion-weighted imaging scanning, and FBA and DTI metrics were compared between groups. Results revealed significant reductions in fibre-bundle cross-section within the anterior corona radiata and genu of corpus callosum, indicating morphological atrophy in AN patients. These specific tracts, identified by FBA, connect brain regions involved in the symptomatology of AN. DTI showed increased axial diffusivity in the cerebellar peduncles of AN patients but did not show significant differences in other metrics. Notably, there was no overlap between findings of FBA and DTI analyses. Overall, this study highlights the potential of FBA to detect WM abnormalities not accounted for by DTI and suggests that myelin loss contributes to the observed clinical picture in AN patients.

The current study compared the reliability of manual collateral sulcus depth and entorhinal and transentorhinal cortical volume measurements between native oriented MRI scans versus MRI scans realigned to the hippocampal long axis. Data included 10 participants with two serial 3.0T MRI scans from the Alzheimer's Disease Neuroimaging Initiative. Both collateral sulcus depth and entorhinal and transentorhinal cortical volume measurement reliability improved from the native to the hippocampal oriented scans. Standardizing scan orientation is important to optimize reliability of MRI-derived manual measurements of the entorhinal and transentorhinal cortices. In quantitative MRI studies, aligning scans to a common, normalized orientation is recommended.

Sleep disruptions associated with neurodegenerative diseases (NDDs) damage the brain's sleep-regulating regions. Advanced magnetic resonance imaging (MRI) techniques can characterize the signature of each neurodegenerative pathology. We performed an evaluation of sleep-related regions in NDDs using MRI to localize the central nervous system (CNS). In the initial search, 61 related papers were discovered using predetermined inclusion and exclusion criteria. Finally, 30 articles were included in this study. The study included patients with Parkinson's disease (PD), Alzheimer's disease (AD), multiple sclerosis (MS), rapid eye movement (REM) sleep behavior disorder (RBD), idiopathic RBD (iRBD), amyotrophic lateral sclerosis (ALS), and mild cognitive impairment (MCI). Sleep-related regions recognized by CNS localization in NDDs can be linked to important regions. MRI also revealed cortical thinning, GM atrophy, WM, and tract loss, changes in diffusion tensor imaging (DTI) biomarkers (fractional anisotropy (FA), axial diffusivity (Da), and radial diffusivity (Dr)), a decrease in DMN connectivity, a reduction in functional connectivity (FC), and amplitude of low-frequency fluctuation (ALFF) alterations. Sleep plays an important role in predicting future risks for the development of NDDs. Other neuroimaging, cognitive-behavioral, and clinical research can use the information found in this research about the brain regions, MRI biomarker changes, and their relationships.