Keywords: Psychiatric Disorders, Adolescents, depression, emotional regulation, PFC

Motivation: The neural correlation between emotional regulation and  adolescent depressive symptoms has not yet been elucidated.

Goal(s): Our goal was to identify the neural substrates of emotional regulation ability (ERA) and its association with depressive symptoms in adolescents.

Approach: We conducted whole-brain correlation, prediction and mediate analyses with resting-state fMRI and behavioral measurements data.

Results: The results indicated that ERA was associated with brain activity in right ventromedial prefrontal cortex (VMPFC) and cuneus. Additionally, ERA mediated the link between spontaneous activity of VMPFC and depressive symptoms.

Impact: Emotional regulation ability may indirectly modulate depressive symptoms in adolescents through affecting neural activity in the VMPFC, which may provide some neurobiological implications for early intervention of adolescent depression.

Keywords: Psychiatric Disorders, Psychiatric Disorders

Motivation: Compared to cortical regions, the involvement of  functional connectivity of subcortical regions in bipolar disorder (BD) are less well known.

Goal(s): The potential involvement of subcortical and subregions of thalamus are explored in BD.

Approach: Seed-based subcortical and thalamic subregional functional connectivity was compared between the BD patients and HCs, as well as between patients with BD type I (BD-I) subgroup and HCs as a sub-group analysis.

Results: BD patients showed increased functional connectivity between left thalamus and right lingual gyrus, between right anterior thalamus and superior frontal gyrus, and between right ventral anterior thalamus and precuneus.

Impact: These findings provide evidence of disorganized thalamo-cortical functional connectivity in BD, suggesting that the thalamus and its subregions may play important and specific roles in the neural circuitry of BD.

Keywords: Psychiatric Disorders, Diffusion/other diffusion imaging techniques, schizophrenia

Motivation: Schizophrenia is a complex psychiatric disorder with cognitive and behavioral disruptions. Previous studies have reported the abnormalities of white matter, but elucidating the biological mechanisms remains a challenge.

Goal(s): To investigate the changes of white matter in schizophrenia patients and correlate with changes of neuropsychological function.

Approach: NODDI was adopted to quantify the changes of neurite orientation and extracellular free water in white matter among schizophrenia patients. The correlation analyses between image indices and neuropsychological scale scores were performed.

Results: Significant changes of brain microstructure, particularly in the fornix with schizophrenia, was observed. Those changes were correlated with global function and cognition decline.

Impact: This study demonstrated abnormalities of white matter microstructure, especially in the fornix, among individuals with schizophrenia. NODDI could become a potential technique for finding biomarker in revealing the pathophysiological process of the disorder.

Keywords: Psychiatric Disorders, Psychiatric Disorders

Motivation: Impaired global cerebrovascular reactivity (CVR) has been reported in major depressive disorder (MDD). However, regional CVR has not been evaluated in MDD patients due to experimental difficulties. 

Goal(s): The goal is to use a recently developed resting-state technique to map regional CVR in MDD patients. 

Approach: Resting-state images was filtered and relative CVR index was calculated by regressing the voxel-wise BOLD signal against the reference signal. 

Results: CVR was significantly reduced in occipital lobe in MDD. Temporal CVR was negatively correlated with illness duration, while psychomotor retardation was associated with elevated CVR in several emotion-related areas, including amygdala. 

Impact: Current study indicated a region-specific relationship between cerebrovascular dysfunction and depression.

Keywords: Psychiatric Disorders, Spectroscopy

Motivation: There is limited information on anterior cingulate cortex (ACC) myo-inositol (m)I level in medication-free bipolar disorder (BD) patients in depressed state, which can explore role of neuro-inflammation in BD.

Goal(s): Investigate modulation of ACC mI level during Li monotherapy.

Approach: Patients with BD (depressed state) and healthy controls were scanned at 7-tesla MRI with a semi-LASER sequence at baseline and 2, 8 and 26 weeks from onset of Li monotherapy, and ACC mI level was measured at each time point.

Results: mI level decreased in 1st 2 weeks of onset of therapy but the reduction was not observed after 8 weeks.

Impact: The preliminary results suggest that decrease in neuro-inflammatory/microglial marker mI during Li monotherapy of depressed BD may be a short term effect. Future studies can investigate if this is specific to depressed state by investigating during manic state also.

Keywords: Psychiatric Disorders, Psychiatric Disorders, Schizophrenia, Subtypes, MRI, fMRI, Machine Learning

Motivation: The heterogeneity in schizophrenia remains poorly understood which contributes to the limited success of existing treatments and the observed variability in treatment responses.

Goal(s): Our goal was to classify schizophrenia and its subtypes by using machine learning (ML) and MRI to improve understanding of the neurological basis of this schizophrenia.

Approach: We applied conventional ML and feature selection methods on MRI to reach our goal.

Results: We were able to distinguish schizophrenia and healthy and subtypes of schizophrenia using the combination of MRI and ML. we also showed evidences of brain dysfunctions in schizophrenia and its correlation with behaviors related to the disorder

Impact: The outcomes of this study reinforce the notion that the fusion of machine learning methodologies with structural and functional neuroimaging holds the potential to unearth novel biomarkers, consequently contributing to the enhancement of diagnosis and treatment strategies for psychiatric disorders.

Keywords: Psychiatric Disorders, Metabolism

Motivation: To better understand the neurochemical correlates of cognitive impairment in subjects with schizophrenia and healthy control subjects. 

Goal(s): Are regional brain metabolite levels and peripheral markers correlated with cognition in subjects with schizophrenia?

Approach: Regional brain metabolism using 7T MRS, detailed neuropsychological testing, and peripheral markers from venipuncture were obtained in 12 subjects with schizophrenia and 9 healthy control subjects. 

Results: In all subjects, significant positive correlations were found between regional glutamine (Gln) levels and blood ammonia levels, and, in subjects with schizophrenia, regional brain Gln levels were negatively correlated with measures of cognition. 

Impact: These preliminary data support the hypothesized role of aberrant Gln metabolism as one of the factors associated with CI in schizophrenia, possibly by perturbation of the glutamate/GABA-glutamine neurotransmitter cycle.

Keywords: Psychiatric Disorders, Psychiatric Disorders

Motivation: Assessing the Gray matter volume changes in the hippocampal subfield and amygdala nuclei will help to understand the underlying mechanisms of the disease. 

Goal(s): To assess hippocampal subfield and amygdala nuclei volume changes in patients with early-onset schizophrenia (EOS).

Approach: High-resolution 3D T1 images were acquired in both the control (34) and the EOS (31). Hippocampal subfield and amygdala nuclei segmentation was performed using FreeSurfer.

Results: Volume reduction in the bilateral basal, para-laminar, and right lateral amygdala nuclei, as well as molecular layer, subiculum, para-subiculum, CA4 hippocampal subfield.

Impact: The gray matter volume reduction of the hippocampus subfield and amygdala nuclei maybe associated with poor clinical outcomes in EOS.

Keywords: Psychiatric Disorders, Psychiatric Disorders, fMRI (resting state)

Motivation: Given that suicidal ideation (SI) is closely related to social development, it is important to understand the associations between network function and SI (or the non-suicidal ideation, NS) in patients with depression.

Goal(s): We aim to investigate brain function changes in depressed patients with SI and NS between baseline (Time 1, TP1) and follow-up (Time 2, TP2; after one year of therapy).

Approach: Paired t-tests, repeated-measure ANCOVA, and network-based statistical analysis were used.

Results: We found differences in functional activity after treatment, the results surrounded the DMN region in each group. NBS revealed significantly increased functional interconnections of subnetworks after treatment.

Impact: Our findings provide more information about potential neural biomarkers of various depressive disorders.

Keywords: Psychiatric Disorders, Psychiatric Disorders

Motivation: To investigate the specific changes of volumetric differences in Major Depressive Disorder (MDD) and healthy controls (HC) including their relationships with clinically related behavioral phenomena.
 

Goal(s): To investigate volumetric differences in the thalamic subnuclei of untreated MDD patients and HC groups.

Approach: We collected high-resolution 3D T1-weighted images from untreated MDD patients and age- and sex-matched healthy controls.

Results: No significant volume differences of the bilateral thalamus as a subnuclei between MDD patients and healthy controls. Found age-by-diagnosis interactions for specific thalamic subnuclei. Partial correlation analyses show several left thalamic subnuclei showed positive correlations with HAMD-17 scores and cognitive disturbance scores.

Impact: The study offers valuable insights into thalamic subnuclei changes and their impact on MDD. These findings underscore the significance of examining specific thalamic subnuclei and their potential impact on MDD's development.

Keywords: Psychiatric Disorders, fMRI (resting state), anxiety disorders

Motivation: It is necessary to clarify the neurobiological mechanisms of anxiety disorders (ADs) to provide a unique biomarker for diagnosing ADs, facilitating accurate clinical diagnosis and targeted therapeutic interventions.

Goal(s): The primary objective is to elucidate the specific abnormalities in individuals with ADs' amygdala-based whole-brain connectivity.

Approach: The coordinate-based meta-analysis was conducted to find amygdala resting-state functional connectivity in patients with ADs. Furthermore, subgroup analysis was performed to explore potential functional lateralization.

Results: Distinct functional connectivity abnormalities were found in ADs, which provides a reference for diagnosing ADs.
 

Impact: These findings not only enhance our understanding of the underlying pathophysiological mechanisms in ADs but also may be valuable for the prevention, diagnosis and intervention of ADs.

Keywords: Psychiatric Disorders, Psychiatric Disorders

Motivation: It is currently unknown which hippocampal substructure or composite based on the different is the most effective in evaluating treatment outcomes.

Goal(s): To explore which hippocampal organization might predict an early antidepressant response to in patients with major depressive disorder.

Approach: We used Freesurfer software to segment the hippocampus automatically, and created the hippocampal composites by summing component substructures early antidepressants response were evaluated from many dimensions of hippocampal organization.

Results: We found hippocampal substructures segmented along its transverse axis exhibit best classification performance, and the most relevant region for treatments efficacy maybe located in the CA1 and ML. 

Impact: We found hippocampal substructures segmented along its transverse axis exhibit best classification performance, and the most relevant region for treatments efficacy maybe located in the CA1 and ML. 

Keywords: Psychiatric Disorders, Psychiatric Disorders, Schizophrenia, Glymphatic, Perivascular Space, water clearance

Motivation: Perivascular spaces(PVS) are fluid-filled spaces that surround blood vessels in the brain. While dilated PVS(dPVS) play an important role, investigations into dPVS in schizophrenia are poorly understood.

Goal(s): In this study, we aim to explore the potential of dPVS quantification as a biomarker for schizophrenia.

Approach: For volumetric assessment, we segmented the dPVS in the white matter(WM) and basal ganglia(BG), and calculated the volumes and numbers of dPVS for each subject.

Results: Our findings reveal differences in dPVS numbers and volumes among schizophrenia subgroups, especially in treatment-resistant schizophrenia(TRS) which showed smaller dPVS volumes compared to other groups in both WM and BG.

Impact: Our study offers insights into the potential of dPVS quantification as a biomarker for schizophrenia. We observed differences in total dPVS volumes and number of dPVS components between different schizophrenia subgroups and found significant results especially in TRS.

Keywords: Psychiatric Disorders, Psychiatric Disorders, Schizophrenia, Dynamic Functional Connectivity, Cerebellum

Motivation: The complex nature of schizophrenia and its unclear pathophysiology drive our research. We aim to delve into altered brain communication, especially the cerebellum, during transitions between mental states for deeper insights. 

Goal(s): Our goal was to investigate cerebellar communication dynamics in schizophrenia to better understand its pathophysiology.

Approach: We used dynamic ICA analysis to study resting-state cerebello-cortical temporal dynamics.

Results: We observed implications in the dynamics of the cerebello-frontal and cerebello-occipital connections potentially indicative of higher social sensitivity and deficits in cognitive inhibition, and highlighting the role of the cerebellum as modulator between different brain circuits.

Impact: The identification of resting state temporal dynamic changes in cerebello-frontal and cerebello-occipital circuits in schizophrenia provides crucial pathophysiological insights, inspiring further research on the role of the cerebellum as a brain circuit modulator, promising advancements in treatment strategies and outcomes.

Keywords: Psychiatric Disorders, Psychiatric Disorders, schizophrenia, multilayer network analysis, switching rate, antipsychotics, dynamic functional connectivity

Motivation: Although aberrant static functional connectome in schizophrenia has been reported, little is known about how the neural dynamics change in first-episode schizophrenia and are modulated by antipsychotic treatment.

Goal(s): We aim to characterize dynamic topological reconfiguration of brain connectome in schizophrenia.

Approach: Multilayer network analysis was applied to calculate the network switching rates between brain states. We compared switching rates of patients and controls at baseline, and tested for changes after one-year of treatment.

Results: Significantly increased network switching rates were found in patients at baseline, mainly in the sensorimotor and dorsal attention networks. Switching rates were reduced after treatment.

Impact: The findings of excessive neural flexibility in patients extend our understanding for the disease-related brain dynamics aberrance in schizophrenia, and the normalization of network switching rates further illustrate the biological mechanism underlying antipsychotic treatment from a perspective of neural dynamics.