Opposite effects of dopamine and serotonin on resting-state networks: review and implications for psychiatric disorders

Abnormally slow dynamics in occipital cortex of depression

AIM

Major depressive disorder (MDD) is characterized by altered activity in various higher-order regions like the anterior cingulate and prefrontal cortex. While some findings also show changes in lower-order sensory regions like the occipital cortex in MDD, the latter's exact neural and temporal, e.g., dynamic characterization and symptom severity remains yet unclear.

METHODS

We conducted resting state fMRI in MDD (N = 49) and healthy controls to investigate the global activity representation of the brain's spontaneous activity in occipital cortex including lower-order (V1) and higher-order (hMT+) regions in the hierarchy of the visual cortex. We further explored (i) these regions' functional connectivity to higher-order prefrontal and subcortical regions, (ii) global signal correlation differences between MDD and controls in different frequency bands, and (iii) their power spectrum's correlation (using median frequency/MF) with symptom severity.

RESULTS

Our findings in MDD show: (i) abnormally high functional connectivity of the occipital cortex to both subcortical and higher-order cortical regions; (ii) occipital global signal correlation is reduced mainly in the faster infraslow frequency range (slow 3: 0.073 to 0.198 Hz) as distinguished from the slower ones (slow 5 and 4: 0.01 to 0.027 Hz, and 0.027 to 0.073 Hz); (iii) the reduced neural dynamics in occipital cortex (MF) correlate with the severity of both overall depressive symptoms and psychomotor retardation scores.

CONCLUSIONS

MDD shows reduced global activity with abnormally slow neural dynamics in occipital cortex that is functionally connected with higher-order regions like the anterior cingulate cortex. The slow dynamics in occipital cortex relates to overall symptom severity and psychomotor retardation.

High-order network degree revealed shared and distinct features among adult schizophrenia, bipolar disorder and ADHD

Schizophrenia (SCHZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD) share clinical symptoms and risk genes, but the shared and distinct neural dynamic mechanisms at adults remain inadequately understood. Degree is a fundamental and important graph measure in network neuroscience, and we here used eigenmodes to extend the degree to hierarchical levels and compared the resting-state brain networks of three disorders and healthy controls (HC) at adults (age: 21-50 years old). First, compared to HC, SCHZ and BD patients exhibited substantially overlapped abnormalities in brain networks, wherein BD patients displayed more significant alterations. In contrast, ADHD patients exhibited few alterations. Second, compared to the graph theory measure, hierarchical degree better predicted the clinical symptoms of three disorders, and distinguished them from HC. Furthermore, three disorders shared associations of brain network abnormalities with dopamine receptors/transporters. Finally, the alterations in SCHZ and BD patients were associated with cellular localization and transport, as well as abnormal social behavior and communication, while ADHD patients were associated with energy production and transport. These findings provided a deep understanding of the shared and distinct neuropathology of three disorders and facilitated a more precise differentiation for them.

Connecting brain and mind through temporo-spatial dynamics: Towards a theory of common currency

Despite major progress in our understanding of the brain, the connection of neural and mental features, that is, brain and mind, remains yet elusive. In our 2020 target paper ("Is temporospatial dynamics the 'common currency' of brain and mind? Spatiotemporal Neuroscience") we proposed the "Common currency hypothesis": temporo-spatial dynamics are shared by neural and mental features, providing their connection. The current paper aims to further support and extend the original description of such common currency into a first outline of a "Common currency theory" (CCT) of neuro-mental relationship. First, we extend the range of examples to thoughts, meditation, depression and attention all lending support that temporal characteristics, (i.e. dynamics) are shared by both neural and mental features. Second, we now also show empirical examples of how spatial characteristics, i.e., topography, are shared by neural and mental features; this is illustrated by topographic reorganization of both neural and mental states in depression and meditation. Third, considering the neuro-mental connection in theoretical terms, we specify their relationship by distinct forms of temporospatial correspondences, ranging on a continuum from simple to complex. In conclusion, we extend our initial hypothesis about the key role of temporo-spatial dynamics in neuro-mental relationship into a first outline of an integrated mind-brain theory, the "Common currency theory" (CCT).

Quantification of three neurotransmitters in cerebrospinal fluid, serum and random urine using a robust and simplified liquid chromatography-tandem mass spectrometry method

Imbalance in the monoamine neurotransmitters has been implicated in a variety of neurological disorders, making it necessary to quantify neurotransmitters accurately. Thus, the study aims to develop a robust and validated method for simultaneously quantifying serotonin, 5-Hydroxyindole Acetic Acid (5-HIAA), and homovanillic acid (HVA) using liquid chromatography-tandem mass spectrometry (LC-MS/MS). One-step precipitation with methanol containing 0.2 % formic acid was used for pretreating serum and cerebrospinal fluid samples, while dilution with deionized water was used for pretreating urine samples. Neurotransmitters were detected using an Exion AD liquid chromatography-tandem Qtrap 6500 Plus mass spectrometer, with a total run time of 6.5 mins. The linearity range was 0.5-500.0, 0.2-100.0, 2.0-1000.0 ng/mL for serotonin, 5-HIAA, and HVA in serum and cerebrospinal fluid, and 2.0-500.0, 40.0-10,000.0, 100.0-10,000.0 ng/mL in urine (R2≥0.997). Recovery rate was 81.5-114.4 %, 80.3-114.6 %, and 85.0-115.6 % for serotonin, 5-HIAA, and HVA in three matrices. The matrix effect was compensated by using internal standards. Acceptable intra-assay and inter-assay precision were achieved for all analytes and the total coefficients of variation were 4.9-14.4 %, 6.1-11.2 %, and 4.5-10.5 % for serotonin, 5-HIAA, and HVA. Additionally, we also explored the distribution of neurotransmitters. Patients with motor impairment had higher HVA levels than those without symptoms (P < 0.05), while serotonin and 5-HIAA concentrations were insignificant. Accordingly, a robust LC-MS/MS method combined with easy sample preprocessing was established and systematically validated for quantifying three important neurotransmitters in multiple matrices in a single run, allowing for accurate identification of motor impairment.

Neurobiological influences on event perception: the role of catecholamines

BACKGROUND

Event segmentation, the cognitive process of parsing continuous experiences into discrete events, plays a fundamental role in how humans perceive and interact with their environment. Guided by Event Segmentation Theory, this study investigates the modulation of event segmentation by the catecholaminergic system by methylphenidate (MPH).

METHODS

Healthy adult participants (N = 52) engaged in a double-blind, counter-balanced, placebo-controlled experiment in which they watched a movie and identified event boundaries under placebo and MPH conditions.

RESULTS

With the same information given, MPH increased the likelihood that the information was considered meaningful. Crucially, the number of situational changes and participant's prior experience had an interactive effect on the probability of event segmentation. There was a stronger relationship between environmental information and segmentation probability when catecholaminergic levels were elevated by MPH in addition to previous experience.

CONCLUSIONS

The catecholaminergic system modulates how incoming information is segmented to build meaningful episodes. Prior experience supports the effects of MPH to unfold. These findings underscore the complex interplay between neurochemical modulation and cognitive processes involved in event perception.

Comparison of attention and brain functional connectivity between patient groups with schizophrenia and attention deficit hyperactivity disorder

Schizophrenia and attention deficit hyperactivity disorder (ADHD) have many contradicting features, but both these disorders share inattention as a core symptom. This study explored how the characteristics of inattention differ between the two disorders. 20 patients with schizophrenia, 20 patients with adult ADHD and 20 healthy controls participated in this study. Comprehensive attention test, Korean Wechsler adult intelligence scale-IV and resting-state functional magnetic resonance imaging (fMRI) were collected, among other things. The schizophrenia and ADHD groups showed low and high levels of functional connectivity in the default mode network (DMN), respectively. Functional connectivity level within the DMN was also positively correlated with processing speed index in the schizophrenia group and positively correlated with the number of divided-attention commission errors in the ADHD group. These results show that schizophrenia and adult ADHD have similarities in the characteristics of attention deficit, in that both may arise from dysregulation within the DMN. However, the differences in the levels of functional connectivity in the DMN between these groups affect how inattention manifests in each group.

Reduced resting-state functional connectivity of default mode network subsystems in patients with obsessive-compulsive disorder

OBJECTIVES

Neuroimaging studies have reported extensive resting-state functional connectivity (rsFC) abnormalities in the default mode network (DMN) in patients with obsessive-compulsive disorder (OCD), but findings are inconsistent. DMN can be divided into three subsystems: core, dorsal medial prefrontal cortex (dMPFC), and medial temporal lobe (MTL). This study aimed to explore abnormalities in rsFC strength within and between DMN subsystems in OCD patients, and their relationship with clinical symptoms.

METHODS

This study recruited 39 OCD patients and 45 healthy controls (HCs). OCD symptoms were assessed using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). The seed-to-seed method was used to construct rsFC matrix. The rsFC strength within and between the three DMN subsystems were calculated.

RESULTS

Compared to the HC group, the OCD group exhibited reduced rsFC strength within core subsystem (F = 7.799, p = 0.007, Bonferroni corrected p = 0.042). Further, this reduction was also observed in the unmedicated OCD group (n = 19), but not in the medicated OCD group (n = 18). In addition, rsFC strength within core subsystem was negatively correlated with the obsession subscale of YBOCS in the OCD group (r = -0.512, p = 0.004, Bonferroni corrected p = 0.008). Further, this correlation was also significant in the unmedicated OCD group, but not in the medicated OCD group.

CONCLUSIONS

Our findings suggest that reduced rsFC strength within core subsystem is a feature of OCD patients and may serve as a potential biomarker of obsession severity. Moreover, pharmacological treatments may affect rsFC strength in DMN.

Temporal changes of neurobehavior in rats following varied blast magnitudes and screening of serum biomarkers in early stage of brain injury

Blast neurotrauma has been linked to impairments in higher-order cognitive functions, including memory, attention, and mood. Current literature is limited to a single overpressure exposure or repeated exposures at the same level of overpressure. In this study, a rodent model of primary blast neurotrauma was employed to determine the pressure at which acute and chronic neurological alterations occurred. Three pressure magnitudes (low, moderate and high) were used to evaluate injury thresholds. A biology shock tube (BST) was used to simulate shock waves with overpressures of 60 kPa, 90 kPa and 120 kPa respectively. Neurological behavior of the rats was assessed by the Multi-Conditioning System (MCS) at 1 d, 7 d, 28 d and 90 d after shock wave exposure. Serum dopamine (DA), 5-hydroxytryptamine (5-HT), brain-derived neurotrophic factor (BDNF) and gamma-aminobutyric acid (GABA) were measured at the same time points. The proteomic analysis was conducted to identify potentially vulnerable cellular and molecule targets of serum in the immediate post-exposure period. Results revealed that: (1) Anxiety-like behavior increased significantly at 1 d post-exposure in the medium and high overpressure (90 kPa, 120 kPa) groups, returned to baseline at 7 days, and anxiety-like behavior in the high overpressure groups re-emerged at 28 d and 90 d. (2) High overpressure (120 kPa) impaired learning and memory in the immediate post-exposure period. (3) The serum DA levels decreased significantly at 1 d post-exposure in the medium and high overpressure groups; The 5-HT levels decreased significantly at 1 d and 90 d in the high overpressure groups; The BDNF levels decreased significantly at 90 d in the high overpressure groups. (4) Proteomic analysis identified 38, 306, and 57 differentially expressed proteins in serum following low, medium and high overpressure exposures, respectively. Two co-expressed proteins were validated. Functional analysis revealed significant enrichment of 1121, 2096, and 1121 Gene Ontology (GO) items and 33, 47, and 26 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating extensive molecular responses to overpressure in the early phase. These findings suggest that exposure, even at moderate levels, can induce persistent neurobehavioral and molecular alterations, highlighting the need for further research into the long-term consequences of blast neurotrauma.

Temporal dysregulation of the somatomotor network in agitated depression

Agitated depression (A-MDD) is a severe subtype of major depressive disorder, with an increased risk of suicidality and the potential to evolve into bipolar disorder. Despite its clinical significance, the neural basis remains unclear. We hypothesize that psychomotor agitation, marked by pressured speech and racing thoughts, is linked to disruptions in brain dynamics. To test this hypothesis, we examined brain dynamics using time delay estimation and edge-centre time series, as well as dynamic connections between the somatomotor network (SMN) and the default mode network in 44 patients with A-MDD, 75 with non-agitated MDD (NA-MDD), and 94 healthy controls. Our results revealed that the neural co-activity duration was shorter in the A-MDD group compared with both the NA-MDD and controls (A-MDD versus NA-MDD: t = 2.295; A-MDD versus controls: t = 2.192, all P < 0.05). In addition, the dynamic of neural fluctuation in SMN altered in the A-MDD group than in the NA-MDD group (t = -2.616, P = 0.011) and was correlated with agitation severity (β = -0.228, P = 0.011). The inter-network connection was reduced in the A-MDD group compared with the control group (t = 2.102, P = 0.037), especially at low-amplitude time points (t = 2.139, P = 0.034). These findings indicate rapid neural fluctuations and disrupted dynamic coupling between the SMN and default mode network in A-MDD, potentially underlying the psychomotor agitation characteristic of this subtype. These insights contribute to a more nuanced understanding of the heterogeneity of depression and have implications for differential diagnosis and treatment strategies.

Functional gradient dysfunction in drug-naïve first-episode schizophrenia and its correlation with specific transcriptional patterns and treatment predictions

BACKGROUND

First-episode schizophrenia (FES) is a progressive psychiatric disorder influenced by genetics, environmental factors, and brain function. The functional gradient deficits of drug-naïve FES and its relationship to gene expression profiles and treatment outcomes are unknown.

METHODS

In this study, we engaged a cohort of 116 FES and 100 healthy controls (HC), aged 7 to 30 years, including 15 FES over an 8-week antipsychotic medication regimen. Our examination focused on primary-to-transmodal alterations in voxel-based connection gradients in FES. Then, we employed network topology, Neurosynth, postmortem gene expression, and support vector regression to evaluate integration and segregation functions, meta-analytic cognitive terms, transcriptional patterns, and treatment predictions.

RESULTS

FES displayed diminished global connectome gradients (Cohen's d = 0.32-0.57) correlated with compensatory integration and segregation functions (Cohen's d = 0.31-0.36). Predominant alterations were observed in the default (67.6%) and sensorimotor (21.9%) network, related to high-order cognitive functions. Furthermore, we identified notable overlaps between partial least squares (PLS1) weighted genes and dysregulated genes in other psychiatric conditions. Genes linked with gradient alterations were enriched in synaptic signaling, neurodevelopment process, specific astrocytes, cortical layers (layer II and IV), and developmental phases from late/mid fetal to young adulthood. Additionally, the onset age influenced the severity of FES, with discernible differences in connection gradients between minor- and adult-FES. Moreover, the connectivity gradients of FES at baseline significantly predicted treatment outcomes.

CONCLUSIONS

These results offer significant theoretical foundations for elucidating the intricate interplay between macroscopic functional connection gradient changes and microscopic transcriptional patterns during the onset and progression of FES.

Integration patterns of functional brain networks can predict the response to abdominal acupuncture in patients with major depressive disorder

Abdominal acupuncture has definite efficacy for major depressive disorder (MDD). Our study examined how abdominal acupuncture regulates the integration within and between brain networks of MDD patients by neuroimaging and whether this functional integration can predict the efficacy. Forty-six female MDD patients were randomly divided into a fluoxetine + real acupuncture group (n = 22) and a fluoxetine + sham acupuncture group (n = 24). The differences in functional magnetic resonance imaging data in the intra- and inter-network functional connectivity (FC) of the default mode network (DMN), affective network (AN), salience network (SN), and cognitive control network (CCN) between the two groups were analyzed. The FCs in brain regions with the inter-group differences and support vector regression were used to predict the efficacy of abdominal acupuncture. Our results showed: that the intra- and inter-network FCs of DMN, AN, SN, and CCN could be changed by abdominal acupuncture. Using the baseline FCs within AN and DMN or AN-DMN as characteristics, combined with support vector regression, could better predict the efficacy of acupuncture. Our study suggests that abdominal acupuncture could treat MDD by regulating the integration of the functional networks DMN, AN, SN, and CCN. The baseline FCs within the DMN and AN or between them could be used as neural markers for predicting the efficacy of abdominal acupuncture.

Associations between phenols, parabens, and phthalates and depressive symptoms: The role of inflammatory markers and bioinformatic insights

Phenols, parabens, and phthalates are commonly found in consumer products, yet there is limited research on their individual and combined effects on depressive symptoms, particularly regarding the role of inflammation in these associations. This study aimed to evaluate these effects and explore potential molecular mechanisms, with a focus on inflammation as a mediator. We conducted a cross-sectional analysis involving 2766 adult participants from the National Health and Nutrition Examination Survey (NHANES) 2013-2016. Urine samples were analyzed for 15 chemicals, including 3 phenols, 2 parabens, and 10 phthalates. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Statistical analyses included linear regression, restricted cubic splines, Bayesian Kernel Machine Regression and quantile g-computation models to investigate the relationships between chemical exposures and depressive symptoms. Additionally, mediation analysis was employed to explore the potential role of inflammation (immune cells, CRP, NLR) in these associations. The underlying molecular mechanisms were analyzed using bioinformatic approaches. Notably, BPA, MECPP, MEHHP, MiBP and MBP were found to be positively associated with depressive symptoms among females. Besides, BPA was the most significant positive contributor to the effect in the context of the chemical mixture, while the overall mixture effect was relatively weak. Furthermore, WBC were found to mediate a marginal portion (4 %) of the potential effects of MBP on depressive symptoms. The 15 genes identified are primarily involved in neurotransmission, mood regulation, and stress response. Further research is needed to elucidate the mechanisms underlying the observed associations.

Controlling Alzheimer's disease by deep brain stimulation based on a data-driven cortical network model

This work aims to explore the control effect of DBS on Alzheimer's disease (AD) from a neurocomputational perspective. Firstly, a data-driven cortical network model is constructed using the Diffusion Tensor Imaging data. Then, a typical electrophysiological feature of EEG slowing in AD is reproduced by reducing the synaptic connectivity parameters. The corresponding changes in kinetic behavior mainly include an oscillation decrease in the amplitude and frequency of the pyramidal neuron population. Subsequently, DBS current with specific parameters is introduced into three potential targets of the hippocampus, the nucleus accumbens and the olfactory tubercle, respectively. The results indicate that applying DBS to simulated mild AD patients induces an increase in relative alpha power, a decrease in relative theta power, and a significant rightward shift of the dominant frequency. This is consistent with the EEG reversal in pharmacological treatments for AD. Further, the optimal stimulation strategy of DBS is investigated through spectral and statistical analyses. Specifically, the pathological symptoms of AD could be alleviated by adjusting the critical parameters of DBS, and the control effect of DBS on various targets is that the hippocampus is superior to the olfactory tubercle and nucleus accumbens. Finally, using correlation analysis between the power increments and the nodal degrees, it is concluded that the control effect of DBS is related to the importance of the nodes in the brain network. This study provides a theoretical guidance for determining DBS targets and parameters, which may have a substantial impact on the development of DBS treatment for AD.

The emerging neuroimmune hypothesis of bipolar disorder: An updated overview of neuroimmune and microglial findings

Bipolar disorder (BD) is a severe and multifactorial disease, with onset usually in young adulthood, which follows a progressive course throughout life. Replicated epidemiological studies have suggested inflammatory mechanisms and neuroimmune risk factors as primary contributors to the onset and development of BD. While not all patients display overt markers of inflammation, significant evidence suggests that aberrant immune signaling contributes to all stages of the disease and seems to be mood phase dependent, likely explaining the heterogeneity of findings observed in this population. As the brain's immune cells, microglia orchestrate the brain's immune response and play a critical role in maintaining the brain's health across the lifespan. Microglia are also highly sensitive to environmental changes and respond to physiological and pathological events by adapting their functions, structure, and molecular expression. Recently, it has been highlighted that instead of a single population of cells, microglia comprise a heterogeneous community with specialized states adjusted according to the local molecular cues and intercellular interactions. Early evidence has highlighted the contribution of microglia to BD neuropathology, notably for severe outcomes, such as suicidality. However, the roles and diversity of microglial states in this disease are still largely undermined. This review brings an updated overview of current literature on the contribution of neuroimmune risk factors for the onset and progression of BD, the most prominent neuroimmune abnormalities (including biomarker, neuroimaging, ex vivo studies) and the most recent findings of microglial involvement in BD neuropathology. Combining these different shreds of evidence, we aim to propose a unifying hypothesis for BD pathophysiology centered on neuroimmune abnormalities and microglia. Also, we highlight the urgent need to apply novel multi-system biology approaches to characterize the diversity of microglial states and functions involved in this enigmatic disorder, which can open bright perspectives for novel biomarkers and therapeutic discoveries.

A connectome-based model of delusion in schizophrenia using functional connectivity under working memory task

Delusion is an important feature of schizophrenia, which may stem from cognitive biases. Working memory (WM) is the core foundation of cognition, closely related to delusion. However, the knowledge of neural mechanisms underlying the relationship between WM and delusion in schizophrenia is poorly investigated. Two hundred and thirty patients with schizophrenia (dataset 1: n = 130; dataset 2: n = 100) were enrolled and scanned for an N-back WM task. We constructed the WM-related whole-brain functional connectome and conducted Connectome-based Predictive Modelling (CPM) to detect the delusion-related networks and built the correlation model in dataset 1. The correlation between identified networks and delusion severity was tested in a separate, heterogeneous sample of dataset 2 that mainly includes early-onset schizophrenia. The identified delusion-related network has a strong correlation with delusion severity measured by the NO.20 item of SAPS in dataset 1 (r = 0.433, p = 2.7 × 10-7, permutation-p = 0.035), and can be validated in the same dataset by using another delusion measurement, that is, the P1 item of PANSS (r = 0.362, p = 0.0005). It can be validated in another independent dataset 2 (NO.20 item of SAPS for r = 0.31, p = 0.0024, P1 item of PANSS for r = 0.27, p = 0.0074). The delusion-related network comprises the connections between the default mode network (DMN), cingulo-opercular network (CON), salience network (SN), subcortical, sensory-somatomotor network (SMN), and visual networks. We successfully established correlation models of individualized delusion based on the WM-related functional connectome and showed a strong correlation between delusion severity and connections within the DMN, CON, SMN, and subcortical network.

Schizophrenia and Neurodevelopment: Insights From Connectome Perspective

BACKGROUND

Schizophrenia is conceptualized as a brain connectome disorder that can emerge as early as late childhood and adolescence. However, the underlying neurodevelopmental basis remains unclear. Recent interest has grown in children and adolescent patients who experience symptom onset during critical brain development periods. Inspired by advanced methodological theories and large patient cohorts, Chinese researchers have made significant original contributions to understanding altered brain connectome development in early-onset schizophrenia (EOS).

STUDY DESIGN

We conducted a search of PubMed and Web of Science for studies on brain connectomes in schizophrenia and neurodevelopment. In this selective review, we first address the latest theories of brain structural and functional development. Subsequently, we synthesize Chinese findings regarding mechanisms of brain structural and functional abnormalities in EOS. Finally, we highlight several pivotal challenges and issues in this field.

STUDY RESULTS

Typical neurodevelopment follows a trajectory characterized by gray matter volume pruning, enhanced structural and functional connectivity, improved structural connectome efficiency, and differentiated modules in the functional connectome during late childhood and adolescence. Conversely, EOS deviates with excessive gray matter volume decline, cortical thinning, reduced information processing efficiency in the structural brain network, and dysregulated maturation of the functional brain network. Additionally, common functional connectome disruptions of default mode regions were found in early- and adult-onset patients.

CONCLUSIONS

Chinese research on brain connectomes of EOS provides crucial evidence for understanding pathological mechanisms. Further studies, utilizing standardized analyses based on large-sample multicenter datasets, have the potential to offer objective markers for early intervention and disease treatment.

Risk stratification of new-onset psychiatric disorders using clinically distinct traumatic brain injury phenotypes

BACKGROUND

Patients with traumatic brain injury (TBI) constitute a highly heterogeneous population, with varying risks for New-onset Psychiatric Disorders (NPDs). The objectives of this study were to identify TBI phenotypes and determine how NPDs differ among these phenotypes.

METHODS

Hospitalized TBI patients from 2003 to 2019 were obtained from the provincial trauma registry. Propensity score matching was conducted to balance covariates among patients with TBI and controls. To uncover heterogeneity in TBI, latent class analysis (LCA)-based clustering was applied. LCA was conducted separately for two TBI cohorts: those with and without pre-injury psychiatric conditions The effect of classes on NPDs was assessed using log binomial regression models.

RESULTS

A total of 3,453 patients with TBI and 13,112 controls were included in the analysis. In a conditional regression involving propensity matched patients with TBI and controls, TBI was significantly associated with the development of NPD-A (OR: 2.78; 95% CI: 2.49-3.09), as well as NPD-P (OR: 2.36; 95% CI: 2.07-2.70). Eight distinct latent classes were identified which differed in the incidence of NPDs. Four classes displayed a 53% (RR:1.53; 95% CI: 1.31-1.78), 48% (RR:1.48; 95% CI: 1.26-1.74), 28% (RR:1.28; 95% CI: 1.08-1.54), and 20% (RR: 1.20, 95%CI: 1.03-1.39), increased NPD risk.

CONCLUSION

TBI is a significant predictor of NPDs. There are clinically distinguishable phenotypes with different patterns of NPD risk among patients with TBI. Identifying individuals with respect to their phenotype may improve risk stratification of patients with TBI and promote early intervention for psychiatric care in this vulnerable population.

Brain Networks, Neurotransmitters and Psychedelics: Towards a Neurochemistry of Self-Awareness

PURPOSE OF REVIEW

Self-awareness can be defined as the capacity of becoming the object of one's own awareness and, increasingly, it has been the target of scientific inquiry. Self-awareness has important clinical implications, and a better understanding of the neurochemical basis of self-awareness may help clarifying causes and developing interventions for different psychopathological conditions. The current article explores the relationship between neurochemistry and self-awareness, with special attention to the effects of psychedelics.

RECENT FINDINGS

The functioning of self-related networks, such as the default-mode network and the salience network, and how these are influenced by different neurotransmitters is discussed. The impact of psychedelics on self-awareness is reviewed in relation to specific processes, such as interoception, body ownership, agency, metacognition, emotional regulation and autobiographical memory, within a framework based on predictive coding. Improved outcomes in emotional regulation and autobiographical memory have been observed in association with the use of psychedelics, suggesting higher-order self-awareness changes, which can be modulated by relaxation of priors and improved coping mechanisms linked to cognitive flexibility. Alterations in bodily self-awareness are less consistent, being potentially impacted by doses employed, differences in acute/long-term effects and the presence of clinical conditions. Future studies investigating the effects of different molecules in rebalancing connectivity between resting-state networks may lead to novel therapeutic approaches and the refinement of existing treatments.

Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders

BACKGROUND

Patients with psychosis and patients with depression exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC) allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders.

METHODS

We report the analysis of dFC in a large sample including 127 patients at clinical high risk for psychosis, 142 patients with recent-onset psychosis, 134 patients with recent-onset depression, and 256 healthy control participants. A sliding window-based technique was used to calculate the time-dependent FC in resting-state magnetic resonance imaging data, followed by clustering to reveal recurrent FC states in each diagnostic group.

RESULTS

We identified 5 unique FC states, which could be identified in all groups with high consistency (mean r = 0.889 [SD = 0.116]). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly connected FC state in patients with recent-onset depression (p < .0005) compared with the other groups and a common increase in the lifetime of an FC state characterized by high sensorimotor and cingulo-opercular connectivities in all patient groups compared with the healthy control group (p < .0002). Canonical correlation analysis revealed a mode that exhibited significant correlations between dFC parameters and clinical variables (r = 0.617, p < .0029), which was associated with positive psychosis symptom severity and several dFC parameters.

CONCLUSIONS

Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression and psychosis and clinical risk states.

Striatal GABA levels correlate with risk sensitivity in monetary loss

Background

Decision-making under risk is a common challenge. It is known that risk-taking behavior varies between contexts of reward and punishment, yet the mechanisms underlying this asymmetry in risk sensitivity remain unclear.

Methods

This study used a monetary task to investigate neurochemical mechanisms and brain dynamics underpinning risk sensitivity. Twenty-eight participants engaged in a task requiring selection of visual stimuli to maximize monetary gains and minimize monetary losses. We modeled participant trial-and-error processes using reinforcement learning.

Results

Participants with higher subjective utility parameters showed risk preference in the gain domain (r = -0.59) and risk avoidance in the loss domain (r = -0.77). Magnetic resonance spectroscopy (MRS) revealed that risk avoidance in the loss domain was associated with γ-aminobutyric acid (GABA) levels in the ventral striatum (r = -0.42), but not in the insula (r = -0.15). Using functional magnetic resonance imaging (fMRI), we tested whether risk-sensitive brain dynamics contribute to participant risky choices. Energy landscape analyses demonstrated that higher switching rates between brain states, including the striatum and insula, were correlated with risk avoidance in the loss domain (r = -0.59), a relationship not observed in the gain domain (r = -0.02).

Conclusions

These findings from MRS and fMRI suggest that distinct mechanisms are involved in gain/loss decision making, mediated by subcortical neurometabolite levels and brain dynamic transitions.

Is depression a global brain disorder with topographic dynamic reorganization?

Major depressive disorder (MDD) is characterized by a multitude of psychopathological symptoms including affective, cognitive, perceptual, sensorimotor, and social. The neuronal mechanisms underlying such co-occurrence of psychopathological symptoms remain yet unclear. Rather than linking and localizing single psychopathological symptoms to specific regions or networks, this perspective proposes a more global and dynamic topographic approach. We first review recent findings on global brain activity changes during both rest and task states in MDD showing topographic reorganization with a shift from unimodal to transmodal regions. Next, we single out two candidate mechanisms that may underlie and mediate such abnormal uni-/transmodal topography, namely dynamic shifts from shorter to longer timescales and abnormalities in the excitation-inhibition balance. Finally, we show how such topographic shift from unimodal to transmodal regions relates to the various psychopathological symptoms in MDD including their co-occurrence. This amounts to what we describe as 'Topographic dynamic reorganization' which extends our earlier 'Resting state hypothesis of depression' and complements other models of MDD.

Dynamic aberrances of substantia nigra-relevant coactivation patterns in first-episode treatment-naïve patients with schizophrenia

BACKGROUND

Although dopaminergic disturbances are well-known in schizophrenia, the understanding of dopamine-related brain dynamics remains limited. This study investigates the dynamic coactivation patterns (CAPs) associated with the substantia nigra (SN), a key dopaminergic nucleus, in first-episode treatment-naïve patients with schizophrenia (FES).

METHODS

Resting-state fMRI data were collected from 84 FES and 94 healthy controls (HCs). Frame-wise clustering was implemented to generate CAPs related to SN activation or deactivation. Connectome features of each CAP were derived using an edge-centric method. The occurrence for each CAP and the balance ratio for antagonistic CAPs were calculated and compared between two groups, and correlations between temporal dynamic metrics and symptom burdens were explored.

RESULTS

Functional reconfigurations in CAPs exhibited significant differences between the activation and deactivation states of SN. During SN activation, FES more frequently recruited a CAP characterized by activated default network, language network, control network, and the caudate, compared to HCs (F = 8.54, FDR-p = 0.030). Moreover, FES displayed a tilted balance towards a CAP featuring SN-coactivation with the control network, caudate, and thalamus, as opposed to its antagonistic CAP (F = 7.48, FDR-p = 0.030). During SN deactivation, FES exhibited increased recruitment of a CAP with activated visual and dorsal attention networks but decreased recruitment of its opposing CAP (F = 6.58, FDR-p = 0.034).

CONCLUSION

Our results suggest that neuroregulatory dysfunction in dopaminergic pathways involving SN potentially mediates aberrant time-varying functional reorganizations in schizophrenia. This finding enriches the dopamine hypothesis of schizophrenia from the perspective of brain dynamics.

Cognitive impairment in schizophrenia is associated with prefrontal-striatal functional hypoconnectivity and striatal dopaminergic abnormalities

BACKGROUND

A better understanding of the mechanisms underlying cognitive impairment in schizophrenia is imperative, as it causes poor functional outcomes and a lack of effective treatments.

AIMS

This study aimed to investigate the relationships of two proposed main pathophysiology of schizophrenia, altered prefrontal-striatal connectivity and the dopamine system, with cognitive impairment and their interactions.

METHODS

Thirty-three patients with schizophrenia and 27 healthy controls (HCs) who are right-handed and matched for age and sex were recruited. We evaluated their cognition, functional connectivity (FC) between the dorsolateral prefrontal cortex (DLPFC)/middle frontal gyrus (MiFG) and striatum, and the availability of striatal dopamine transporter (DAT) using a cognitive battery investigating attention, memory, and executive function, resting-state functional magnetic resonance imaging with group independent component analysis and single-photon emission computed tomography with 99mTc-TRODAT.

RESULTS

Patients with schizophrenia exhibited poorer cognitive performance, reduced FC between DLPFC/MiFG and the caudate nucleus (CN) or putamen, decreased DAT availability in the left CN, and decreased right-left DAT asymmetry in the CN compared to HCs. In patients with schizophrenia, altered imaging markers are associated with cognitive impairments, especially the relationship between DLPFC/MiFG-putamen FC and attention and between DAT asymmetry in the CN and executive function.

CONCLUSIONS

This study is the first to demonstrate how prefrontal-striatal hypoconnectivity and altered striatal DAT markers are associated with different domains of cognitive impairment in schizophrenia. More research is needed to evaluate their complex relationships and potential therapeutic implications.

Effects of Catecholaminergic and Transcranial Direct Current Stimulation on Response Inhibition

BACKGROUND

The principle of gain control determines the efficiency of neuronal processing and can be enhanced with pharmacological or brain stimulation methods. It is a key factor for cognitive control, but the degree of how much gain control may be enhanced underlies a physical limit.

METHODS

To investigate whether methylphenidate (MPH) and transcranial direct current stimulation (tDCS) share common underlying mechanisms and cognitive effects, we administered MPH and anodal tDCS (atDCS) over the right inferior frontal gyrus both separately and combined, while healthy adult participants (n = 104) performed a response selection and inhibition task. The recorded EEG data were analyzed with a focus on theta band activity, and source estimation analyses were conducted.

RESULTS

The behavioral data show that MPH and atDCS revealed interactive effects on the ability to inhibit responses. Both MPH and atDCS modulated task-related theta oscillations in the supplementary motor area when applied separately, making a common underlying mechanism likely. When both stimulation methods were combined, there was no doubling of effects in the supplementary motor area but a shift to inferior frontal areas in the cortical network responsible for theta-driven processing.

CONCLUSIONS

The results indicate that both MPH and atDCS likely share a common underlying neuronal mechanism, and interestingly, they demonstrate interactive effects when combined, which are most likely due to the physical limitations of gain control increases. The current study provides critical groundwork for future combined applications of MPH and non-invasive brain stimulation.

Alterations in the brain serotonin system and serotonin-regulated behavior during aging in zebrafish males and females

The brain serotonin (5-HT) system performs a neurotrophic function and supports the plasticity of the nervous system, while its age-related changes can increase the risk of senile neurodegeneration. Zebrafish brain is highly resistant to damage and neurodegeneration due to its high regeneration potential and it is a promising model object in searching for molecular factors preventing age-related neurodegeneration. In the present study alterations in 5-HT-related behavior in the home tank and the novel tank diving test, as well as 5-HT, 5-HIAA levels, tryptophan hydroxylase (TPH), monoamine oxidase (MAO) activity and the expression of genes encoding TPH, MAO, 5-HT transporter and 5-HT receptors in the brain of 6, 12, 24 and 36 month old zebrafish males and females are investigated. Marked sexual dimorphism in the locomotor activity in the novel tank test is revealed: females of all ages move slower than males. No sexual dimorphism in 5-HT-related traits is observed. No changes in 5-HT and 5-HIAA levels in zebrafish brain during aging is observed. At the same time, the aging is accompanied by a decrease in the locomotor activity, TPH activity, tph2 and htr1aa genes expression as well as an increase in the MAO activity and slc6a4a gene expression in their brain. These results indicate that the brain 5-HT system in zebrafish is resistant to age-related alterations.

Affective dysfunction mediates the link between neuroimmune markers and the default mode network functional connectivity, and the somatic symptoms in somatic symptom disorder

OBJECTIVE

Somatic symptom disorder (SSD) is characterized by physical symptoms and associated functional impairments that are often comorbid with depression and anxiety disorders. In this study, we explored relationships between affective symptoms and the functional connectivity of the default mode network (DMN) in SSD patients, as well as the impact of peripheral inflammation. We employed mediation analyses to investigate the potential pathways between these factors.

METHODS

We recruited a total of 119 individuals (74 unmedicated SSD patients and 45 healthy controls), who were subjected to comprehensive psychiatric and clinical evaluations, blood tests, and resting-state functional magnetic resonance imaging scanning. We assessed neuroimmune markers (interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α), tryptophan, serotonin, and 5-hydroxyindoleacetic acid (5-HIAA)), clinical indicators of somatic symptoms, depression, anxiety, anger, alexithymia, and functional connectivity (FC) within the DMN regions. Data were analyzed using correlation and mediation analysis, with a focus on exploring potential relations between clinical symptoms, blood indices, and DMN FCs.

RESULTS

Patients with SSD had higher clinical scores as well as IL-6 and TNF-α levels compared with those in the control group (P < 0.05). The SSD group exhibited lower FC strength between the left inferior parietal lobule and left prefrontal cortex (Pfalse discovery rate (FDR) < 0.05). Exploratory correlation analysis revealed that somatic symptom scores were positively correlated with affective symptom scores, negatively correlated with the FC strength between the intra prefrontal cortex regions, and correlated with levels of IL-6, TNF- α, and tryptophan (uncorrected P < 0.01). Mediation analysis showed that levels of anxiety and trait anger significantly mediated the relations between DMN FC strength and somatic symptoms. In addition, the DMN FC mediated the level of trait anger with respect to somatic symptoms (all PFDR < 0.05). The levels of depression and trait anger exhibited significant mediating effects as suppressors of the relations between the level of 5-HIAA and somatic symptom score (all PFDR < 0.05). Further, the level of 5-HIAA had a mediating effect as a suppressor on the relation between DMN FC and state anger. Meanwhile, the levels of hs-CRP and IL-6 had full mediating effects as suppressors when explaining the relations of DMN FC strengths with the level of depression (all PFDR < 0.05). The patterns of valid mediation pathways were different in the control group.

CONCLUSIONS

Affective symptoms may indirectly mediate the associations between DMN connectivity, somatic symptoms, and neuroimmune markers. Inflammatory markers may also mediate the impact of DMN connectivity on affective symptoms. These results emphasize the importance of affective dysregulation in understanding the mechanisms of SSD and have potential implications for the development of tailored therapeutic approaches for SSD patients with affective symptoms. Furthermore, in SSD research using DMN FC or neuroimmune markers, considering and incorporating such mediating effects of affective symptoms suggests the possibility of more accurate prediction and explanation.

Corticostriatal causality analysis in children and adolescents with attention-deficit/hyperactivity disorder

AIM

The effective connectivity between the striatum and cerebral cortex has not been fully investigated in attention-deficit/hyperactivity disorder (ADHD). Our objective was to explore the interaction effects between diagnosis and age on disrupted corticostriatal effective connectivity and to represent the modulation function of altered connectivity pathways in children and adolescents with ADHD.

METHODS

We performed Granger causality analysis on 300 participants from a publicly available Attention-Deficit/Hyperactivity Disorder-200 dataset. By computing the correlation coefficients between causal connections between striatal subregions and other cortical regions, we estimated the striatal inflow and outflow connection to represent intermodulation mechanisms in corticostriatal pathways.

RESULTS

Interactions between diagnosis and age were detected in the superior occipital gyrus within the visual network, medial prefrontal cortex, posterior cingulate gyrus, and inferior parietal lobule within the default mode network, which is positively correlated with hyperactivity/impulsivity severity in ADHD. Main effect of diagnosis exhibited a general higher cortico-striatal causal connectivity involving default mode network, frontoparietal network and somatomotor network in ADHD compared with comparisons. Results from high-order effective connectivity exhibited a disrupted information pathway involving the default mode-striatum-somatomotor-striatum-frontoparietal networks in ADHD.

CONCLUSION

The interactions detected in the visual-striatum-default mode networks pathway appears to be related to the potential distraction caused by long-term abnormal information input from the retina in ADHD. Higher causal connectivity and weakened intermodulation may indicate the pathophysiological process that distractions lead to the impairment of motion planning function and the inhibition/control of this unplanned motion signals in ADHD.

Motor performance and functional connectivity between the posterior cingulate cortex and supplementary motor cortex in bipolar and unipolar depression

Although implicated in unsuccessful treatment, psychomotor deficits and their neurobiological underpinnings in bipolar (BD) and unipolar (UD) depression remain poorly investigated. Here, we hypothesized that motor performance deficits in depressed patients would relate to basal functional coupling of the hand primary motor cortex (M1) and the posterior cingulate cortex (PCC) with the supplementary motor area (SMA). We performed a longitudinal, naturalistic study in BD, UD and matched healthy controls comprising of two resting-state functional MRI measurements five weeks apart and accompanying assessments of motor performance using a finger tapping task (FTT). A subject-specific seed-based analysis describing functional connectivity between PCC-SMA as well as M1-SMA was conducted. The basal relationships with motor performance were investigated using linear regression models and all measures were compared across groups. Performance in FTT was impaired in BD in comparison to HC in both sessions. Behavioral performance across groups correlated significantly with resting state functional coupling of PCC-SMA, but not of M1-SMA regions. This relationship was partially reflected in a reduced PCC-SMA connectivity in BD vs HC in the second session. Exploratory evaluation of large-scale networks coupling (SMN-DMN) exhibited no correlation to motor performance. Our results shed new light on the association between the degree of disruption in the SMA-PCC anticorrelation and the level of motor impairment in BD.

Progress in the study of intestinal microbiota involved in morphine tolerance

Morphine is a widely used opioid for treatment of pain. The attendant problems including morphine tolerance and morphine dependence pose a major public health challenge. In recent years, there has been increasing interest in the gastrointestinal microbiota in many physiological and pathophysiological processes. The connectivity network between the gut microbiota and the brain is involved in multiple biological systems, and bidirectional communication between them is critical in gastrointestinal tract homeostasis, the central nervous system, and the microbial system. Many research have previously shown that morphine has a variety of effects on the gastrointestinal tract, but none have determined the function of intestinal microbiota in morphine tolerance. This study reviewed the mechanisms of morphine tolerance from the perspective of dysregulation of microbiota-gut-brain axis homeostasis, by summarizing the possible mechanisms originating from the gut that may affect morphine tolerance and the improvement of morphine tolerance through the gut microbiota.

Where do the symptoms come from in depression? Topography and dynamics matter

This scientific commentary refers to 'Brain dynamics predictive of response to psilocybin for treatment-resistant depression', by Vohryzek et al. (https://doi.org/10.1093/braincomms/fcae049).

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Brain dynamics predictive of response to psilocybin for treatment-resistant depression

Psilocybin therapy for depression has started to show promise, yet the underlying causal mechanisms are not currently known. Here, we leveraged the differential outcome in responders and non-responders to psilocybin (10 and 25 mg, 7 days apart) therapy for depression-to gain new insights into regions and networks implicated in the restoration of healthy brain dynamics. We used large-scale brain modelling to fit the spatiotemporal brain dynamics at rest in both responders and non-responders before treatment. Dynamic sensitivity analysis of systematic perturbation of these models enabled us to identify specific brain regions implicated in a transition from a depressive brain state to a healthy one. Binarizing the sample into treatment responders (>50% reduction in depressive symptoms) versus non-responders enabled us to identify a subset of regions implicated in this change. Interestingly, these regions correlate with in vivo density maps of serotonin receptors 5-hydroxytryptamine 2a and 5-hydroxytryptamine 1a, which psilocin, the active metabolite of psilocybin, has an appreciable affinity for, and where it acts as a full-to-partial agonist. Serotonergic transmission has long been associated with depression, and our findings provide causal mechanistic evidence for the role of brain regions in the recovery from depression via psilocybin.

Using normative modeling to assess pharmacological treatment effect on brain state in patients with schizophrenia

Quantifying individual differences in neuroimaging metrics is attracting interest in clinical studies with mental disorders. Schizophrenia is diagnosed exclusively based on symptoms, and the biological heterogeneity makes it difficult to accurately assess pharmacological treatment effects on the brain state. Using the Cambridge Centre for Ageing and Neuroscience data set, we built normative models of brain states and mapped the deviations of the brain characteristics of each patient, to test whether deviations were related to symptoms, and further investigated the pharmacological treatment effect on deviation distributions. Specifically, we found that the patients can be divided into 2 groups: the normalized group had a normalization trend and milder symptoms at baseline, and the other group showed a more severe deviation trend. The baseline severity of the depression as well as the overall symptoms could predict the deviation of the static characteristics for the dorsal and ventral attention networks after treatment. In contrast, the positive symptoms could predict the deviations of the dynamic fluctuations for the default mode and dorsal attention networks after treatment. This work evaluates the effect of pharmacological treatment on static and dynamic brain states using an individualized approach, which may assist in understanding the heterogeneity of the illness pathology as well as the treatment response.

Manifold alteration between major depressive disorder and healthy control subjects using dynamic mode decomposition in resting-state fMRI data

Background

The World Health Organization has reported that approximately 300 million individuals suffer from the mood disorder known as MDD. Non-invasive measurement techniques have been utilized to reveal the mechanism of MDD, with rsfMRI being the predominant method. The previous functional connectivity and energy landscape studies have shown the difference in the coactivation patterns between MDD and HCs. However, these studies did not consider oscillatory temporal dynamics.

Methods

In this study, the dynamic mode decomposition, a method to compute a set of coherent spatial patterns associated with the oscillation frequency and temporal decay rate, was employed to investigate the alteration of the occurrence of dynamic modes between MDD and HCs. Specifically, The BOLD signals of each subject were transformed into dynamic modes representing coherent spatial patterns and discrete-time eigenvalues to capture temporal variations using dynamic mode decomposition. All the dynamic modes were disentangled into a two-dimensional manifold using t-SNE. Density estimation and density ratio estimation were applied to the two-dimensional manifolds after the two-dimensional manifold was split based on HCs and MDD.

Results

The dynamic modes that uniquely emerged in the MDD were not observed. Instead, we have found some dynamic modes that have shown increased or reduced occurrence in MDD compared with HCs. The reduced dynamic modes were associated with the visual and saliency networks while the increased dynamic modes were associated with the default mode and sensory-motor networks.

Conclusion

To the best of our knowledge, this study showed initial evidence of the alteration of occurrence of the dynamic modes between MDD and HCs. To deepen understanding of how the alteration of the dynamic modes emerges from the structure, it is vital to investigate the relationship between the dynamic modes, cortical thickness, and surface areas.

TAAR1 as an emerging target for the treatment of psychiatric disorders

Trace amines, a group of amines expressed at the nanomolar level in the mammalian brain, can modulate monoamine transmission. The discovery of and the functional research on the trace amine-associated receptors (TAARs), especially the most well-characterized TAAR1, have largely facilitated our understanding of the function of the trace amine system in the brain. TAAR1 is expressed in the mammalian brain at a low level and widely distributed in the monoaminergic system, including the ventral tegmental area and substantial nigra, where the dopamine neurons reside in the mammalian brain. Growing in vitro and in vivo evidence has demonstrated that TAAR1 could negatively modulate monoamine transmission and play a crucial role in many psychiatric disorders, including schizophrenia, substance use disorders, sleep disorders, depression, and anxiety. Notably, in the last two decades, many studies have repeatedly confirmed the pharmacological effects of the selective TAAR1 ligands in various preclinical models of psychiatric disorders. Recent clinical trials of the dual TAAR1 and serotonin receptor agonist ulotaront also revealed a potential efficacy for treating schizophrenia. Here, we review the current understanding of the TAAR1 system and the recent advances in the elucidation of behavioral and physiological properties of TAAR1 agonists evaluated both in preclinical animal models and clinical trials. We also discuss the potential TAAR1-dependent signaling pathways and the cellular mechanisms underlying the inhibitory effects of TAAR1 activation on drug addiction. We conclude that TAAR1 is an emerging target for the treatment of psychiatric disorders.

The origins of catatonia - Systematic review of historical texts between 1800 and 1900

Since January 1st 2022, catatonia is (again) recognized as an independent diagnostic entity in the 11th revision of the International Classification of Diseases (ICD-11). This is a relevant time to systematically review how the concept of catatonia has evolved within the 19th century and how this concept changed under the influence of a wide variety of events in the history of psychiatry. Here, we systematically reviewed historical and modern German and English texts focusing on catatonic phenomena, published from 1800 to 1900. We searched five different electronical databases (https://archive.org, www.hathitrust.org, www.books.google.de, https://link.springer.com and PubMed) and closely reviewed 60 historical texts on catatonic symptoms. Three main findings emerged: First, catatonic phenomena and their underlying mechanisms were studied decades before Karl Ludwig Kahlbaum's catatonia concept of 1874. Second, Kahlbaum not only introduced catatonia, but, more generally, also called for a new classification of psychiatric disorders based on a comprehensive analysis of the entire clinical picture, including the dynamic course and cross-sectional symptomatology. Third, the literature review shows that between 1800 and 1900 catatonic phenomena were viewed to be 'located' right at the interface of motor and psychological symptoms with the respective pathophysiological mechanisms being discussed. In conclusion, catatonia can truly be considered one of the most exciting and controversial entity in both past and present psychiatry and neurology, as it occupies a unique position in the border territory between organic, psychotic and psychogenic illnesses.

Motor cortex repetitive transcranial magnetic stimulation in major depressive disorder - A preliminary randomized controlled clinical trial

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) at left dorsolateral prefrontal cortex (lDLPFC) is commonly used in major depressive disorder (MDD), even though its therapeutic efficacy is limited. Given that many MDD patients show psychomotor retardation, we aim to examine whether the left motor cortex (lMC) as a novel rTMS target would provide effective and well-tolerated treatment as being comparable to lDLPFC-rTMS.

METHODS

In this prospective double-blind randomized single-center study, 131 MDD patients were randomly assigned to the lDLPFC or lMC group and were treated with 10 Hz rTMS (90 % motor threshold) applied twice daily for 4000 pulses continuously over five days. The primary endpoint was the Hamilton Depression Scale (HAMD) total score change after treatment.

RESULTS

After the five-day rTMS treatment, there was no significant difference in both HAMD reduction rate (lDLPFC 59.3 % ± 20.4 %, lMC 51.3 % ± 26.3 %, P = 0.10) and adverse effects (P = 0.79) between 48 (73.8 %) lMC subjects and 51 (77.3 %) lDLPFC subjects. Furthermore, the lMC study group showed stable HAMD scores at follow-up compared to their endpoint scores (P = 0.08).

LIMITATIONS

Sham-control group was not included and the sample size was small. Therefore, our results should be seen as exploratory and preliminary.

CONCLUSIONS

The preliminary good therapeutic response, comparability, and tolerability of lMC-rTMS suggest lMC a potential and more easily accessible rTMS target. Together, our findings raise the possibility of symptom-specific rTMS in motor cortex (psychomotor retardation) or lDLPFC (cognitive deficits). This warrants larger clinical trials of rTMS in MDD with symptom-specific stimulation targets.

Altered interhemispheric functional connectivity in patients with obsessive-compulsive disorder and its potential in therapeutic response prediction

The trajectory of voxel-mirrored homotopic connectivity (VMHC) after medical treatment in obsessive-compulsive disorder (OCD) and its value in prediction of treatment response remains unclear. This study aimed to investigate the pathophysiological mechanism of OCD, as well as biomarkers for prediction of pharmacological efficacy. Medication-free patients with OCD and healthy controls (HCs) underwent magnetic resonance imaging. The patients were scanned again after a 4-week treatment with paroxetine. The acquired data were subjected to VMHC, support vector regression (SVR), and correlation analyses. Compared with HCs (36 subjects), patients with OCD (34 subjects after excluding two subjects with excessive head movement) exhibited significantly lower VMHC in the bilateral superior parietal lobule (SPL), postcentral gyrus, and calcarine cortex, and VMHC in the postcentral gyrus was positively correlated with cognitive function. After treatment, the patients showed increased VMHC in the bilateral posterior cingulate cortex/precuneus (PCC/PCu) with the improvement of symptoms. SVR results showed that VMHC in the postcentral gyrus at baseline could aid to predict a change in the scores of OCD scales. This study revealed that SPL, postcentral gyrus, and calcarine cortex participate in the pathophysiological mechanism of OCD while PCC/PCu participate in the pharmacological mechanism. VMHC in the postcentral gyrus is a potential predictive biomarker of the treatment effects in OCD.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders

Background

Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders (SUD).

Aims

This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling (CPM).

Methods

One hundred and eight inpatients with OUD underwent structural and functional magnetic resonance imaging (fMRI) scans at baseline. The Heroin Craving Questionnaire (HCQ) was used to assess craving levels at baseline and at the 8-month follow-up of abstinence. CPM with leave-one-out cross-validation was used to identify baseline networks that could predict follow-up HCQ scores and changes in HCQ (HCQfollow-up-HCQbaseline). Then, the predictive ability of identified networks was tested in a separate, heterogeneous sample of methamphetamine individuals who underwent MRI scanning before abstinence for SUD.

Results

CPM could predict craving changes induced by long-term abstinence, as shown by a significant correlation between predicted and actual HCQfollow-up (r=0.417, p<0.001) and changes in HCQ (negative: r=0.334, p=0.002；positive: r=0.233, p=0.038). Identified craving-related prediction networks included the somato-motor network (SMN), salience network (SALN), default mode network (DMN), medial frontal network, visual network and auditory network. In addition, decreased connectivity of frontal-parietal network (FPN)-SMN, FPN-DMN and FPN-SALN and increased connectivity of subcortical network (SCN)-DMN, SCN-SALN and SCN-SMN were positively correlated with craving levels.

Conclusions

These findings highlight the potential applications of CPM to predict the craving level of individuals after protracted abstinence, as well as the generalisation ability; the identified brain networks might be the focus of innovative therapies in the future.

Compressed primary-to-transmodal gradient is accompanied with subcortical alterations and linked to neurotransmitters and cellular signatures in major depressive disorder

Major depressive disorder (MDD) has been shown to involve widespread changes in low-level sensorimotor and higher-level cognitive functions. Recent research found that a primary-to-transmodal gradient could capture a cortical hierarchical organization ranging from perception and action to cognition in healthy subjects, but a prominent gradient dysfunction in MDD patients. However, whether and how this cortical gradient is linked to subcortical impairments and whether it is reflected in the microscale neurotransmitter systems and cell type-specific transcriptional signatures remain largely unknown. Data were acquired from 323 MDD patients and 328 sex- and age-matched healthy controls derived from the REST-meta-MDD project, and the human brain neurotransmitter systems density maps and gene expression data were drawn from two publicly available datasets. We investigated alterations of the primary-to-transmodal gradient in MDD patients and their correlations with clinical symptoms of depression and anxiety, as well as  their paralleled subcortical impairments. The correlations between MDD-related gradient alterations and densities of the neurotransmitter systems and gene expression information were assessed, respectively. The results demonstrated that MDD patients had a compressed primary-to-transmodal gradient accompanied by paralleled alterations in subcortical regions including the caudate, amygdala, and thalamus. The case-control gradient differences were spatially correlated with the densities of the neurotransmitter systems including the serotonin and dopamine receptors, and meanwhile with gene expression enriched in astrocytes, excitatory and inhibitory neuronal cells. These findings mapped the paralleled subcortical impairments in cortical hierarchical organization and also helped us understand the possible molecular and cellular substrates of the co-occurrence of high-level cognitive impairments with low-level sensorimotor abnormalities in MDD.

Emotion in action: When emotions meet motor circuits

The brain is a remarkably complex organ responsible for a wide range of functions, including the modulation of emotional states and movement. Neuronal circuits are believed to play a crucial role in integrating sensory, cognitive, and emotional information to ultimately guide motor behavior. Over the years, numerous studies employing diverse techniques such as electrophysiology, imaging, and optogenetics have revealed a complex network of neural circuits involved in the regulation of emotional or motor processes. Emotions can exert a substantial influence on motor performance, encompassing both everyday activities and pathological conditions. The aim of this review is to explore how emotional states can shape movements by connecting the neural circuits for emotional processing to motor neural circuits. We first provide a comprehensive overview of the impact of different emotional states on motor control in humans and rodents. In line with behavioral studies, we set out to identify emotion-related structures capable of modulating motor output, behaviorally and anatomically. Neuronal circuits involved in emotional processing are extensively connected to the motor system. These circuits can drive emotional behavior, essential for survival, but can also continuously shape ongoing movement. In summary, the investigation of the intricate relationship between emotion and movement offers valuable insights into human behavior, including opportunities to enhance performance, and holds promise for improving mental and physical health. This review integrates findings from multiple scientific approaches, including anatomical tracing, circuit-based dissection, and behavioral studies, conducted in both animal and human subjects. By incorporating these different methodologies, we aim to present a comprehensive overview of the current understanding of the emotional modulation of movement in both physiological and pathological conditions.

Revisiting Functional Dysconnectivity: a Review of Three Model Frameworks in Schizophrenia

PURPOSE OF REVIEW

Over the last decade, evidence suggests that a combination of behavioral and neuroimaging findings can help illuminate changes in functional dysconnectivity in schizophrenia. We review the recent connectivity literature considering several vital models, considering connectivity findings, and relationships with clinical symptoms. We reviewed resting state fMRI studies from 2017 to 2023. We summarized the role of two sets of brain networks (cerebello-thalamo-cortical (CTCC) and the triple network set) across three hypothesized models of schizophrenia etiology (neurodevelopmental, vulnerability-stress, and neurotransmitter hypotheses).

RECENT FINDINGS

The neurotransmitter and neurodevelopmental models best explained CTCC-subcortical dysfunction, which was consistently connected to symptom severity and motor symptoms. Triple network dysconnectivity was linked to deficits in executive functioning, and the salience network (SN)-default mode network dysconnectivity was tied to disordered thought and attentional deficits. This paper links behavioral symptoms of schizophrenia (symptom severity, motor, executive functioning, and attentional deficits) to various hypothesized mechanisms.

The functional connectome of 3,4-methyldioxymethamphetamine-related declarative memory impairments

The chronic intake of 3,4-methylenedioxymethamphetamine (MDMA, "ecstasy") bears a strong risk for sustained declarative memory impairments. Although such memory deficits have been repeatedly reported, their neurofunctional origin remains elusive. Therefore, we here investigate the neuronal basis of altered declarative memory in recurrent MDMA users at the level of brain connectivity. We examined a group of 44 chronic MDMA users and 41 demographically matched controls. Declarative memory performance was assessed by the Rey Auditory Verbal Learning Test and a visual associative learning test. To uncover alterations in the whole brain connectome between groups, we employed a data-driven multi-voxel pattern analysis (MVPA) approach on participants' resting-state functional magnetic resonance imaging data. Recent MDMA use was confirmed by hair analyses. MDMA users showed lower performance in delayed recall across tasks compared to well-matched controls with moderate-to-strong effect sizes. MVPA revealed a large cluster located in the left postcentral gyrus of global connectivity differences between groups. Post hoc seed-based connectivity analyses with this cluster unraveled hypoconnectivity to temporal areas belonging to the auditory network and hyperconnectivity to dorsal parietal regions belonging to the dorsal attention network in MDMA users. Seed-based connectivity strength was associated with verbal memory performance in the whole sample as well as with MDMA intake patterns in the user group. Our findings suggest that functional underpinnings of MDMA-related memory impairments encompass altered patterns of multimodal sensory integration within auditory processing regions to a functional heteromodal connector hub, the left postcentral gyrus. In addition, hyperconnectivity in regions of a cognitive control network might indicate compensation for degraded sensory processing.

Resting-state EEG dynamics help explain differences in response control in ADHD: Insight into electrophysiological mechanisms and sex differences

Reductions in response control (greater reaction time variability and commission error rate) are consistently observed in those diagnosed with attention-deficit/hyperactivity disorder (ADHD). Previous research suggests these reductions arise from a dysregulation of large-scale cortical networks. Here, we extended our understanding of this cortical-network/response-control pathway important to the neurobiology of ADHD. First, we assessed how dynamic changes in three resting-state EEG network properties thought to be relevant to ADHD (phase-synchronization, modularity, oscillatory power) related with response control during a simple perceptual decision-making task in 112 children/adolescents (aged 8-16) with and without ADHD. Second, we tested whether these associations differed in males and females who were matched in age, ADHD-status and ADHD- subtype. We found that changes in oscillatory power (as opposed to phase-synchrony and modularity) are most related with response control, and that this relationship is stronger in ADHD compared to controls. Specifically, a tendency to dwell in an electrophysiological state characterized by high alpha/beta power (8-12/13-30Hz) and low delta/theta power (1-3/4-7Hz) supported response control, particularly in those with ADHD. Time in this state might reflect an increased initiation of alpha-suppression mechanisms, recruited by those with ADHD to suppress processing unfavourable to response control. We also found marginally significant evidence that this relationship is stronger in males compared to females, suggesting a distinct etiology for response control in the female presentation of ADHD.

High-amplitude network co-fluctuations linked to variation in hormone concentrations over the menstrual cycle

Many studies have shown that the human endocrine system modulates brain function, reporting associations between fluctuations in hormone concentrations and brain connectivity. However, how hormonal fluctuations impact fast changes in brain network organization over short timescales remains unknown. Here, we leverage a recently proposed framework for modeling co-fluctuations between the activity of pairs of brain regions at a framewise timescale. In previous studies we showed that time points corresponding to high-amplitude co-fluctuations disproportionately contributed to the time-averaged functional connectivity pattern and that these co-fluctuation patterns could be clustered into a low-dimensional set of recurring "states." Here, we assessed the relationship between these network states and quotidian variation in hormone concentrations. Specifically, we were interested in whether the frequency with which network states occurred was related to hormone concentration. We addressed this question using a dense-sampling dataset (N = 1 brain). In this dataset, a single individual was sampled over the course of two endocrine states: a natural menstrual cycle and while the subject underwent selective progesterone suppression via oral hormonal contraceptives. During each cycle, the subject underwent 30 daily resting-state fMRI scans and blood draws. Our analysis of the imaging data revealed two repeating network states. We found that the frequency with which state 1 occurred in scan sessions was significantly correlated with follicle-stimulating and luteinizing hormone concentrations. We also constructed representative networks for each scan session using only "event frames"-those time points when an event was determined to have occurred. We found that the weights of specific subsets of functional connections were robustly correlated with fluctuations in the concentration of not only luteinizing and follicle-stimulating hormones, but also progesterone and estradiol.

Drug-induced delusion: A comprehensive overview of the WHO pharmacovigilance database

INTRODUCTION

A number of prescribed medicines have been reported in cases of drug-induced delusion, such as dopaminergic agents or psychostimulants. But to this day, most studies are based on a limited number of cases and focus on a few drug classes, so a clear overview of this topic remains difficult. To address this issue, we provide in this article a comprehensive analysis of drug-induced delusion, based on the World Health Organization (WHO) pharmacovigilance database.

METHODS

We performed a disproportionality analysis of this database using the information component (IC). The IC compares observed and expected values to find associations between drugs and delusion, using disproportionate Bayesian reporting. An IC0.25 (lower end of the IC 95% credibility interval) > 0 is considered statistically significant.

RESULTS

Here we present an analysis of 4559 suspected drug-induced delusion reports in the WHO pharmacovigilance database. These results identified 66 molecules statistically associated with delusion and an extensive analysis of confounding factors and coprescriptions was performed, using full database as background with an IC0.25 > 0. The main drug classes involved were antidepressants, antiepileptics, dopaminergic agents, opioids, antiinfective agents, benzodiazepines, anti-dementia drugs and psychostimulants.

CONCLUSION

These results will help clinicians identify potential suspected drugs associated with delusion and decide which drug to discontinue and eventually lead to a re-evaluation of drug labels for some molecules.

Which Severe Mental Illnesses Most Increase the Risk of Developing Dementia? Comparing the Risk of Dementia in Patients with Schizophrenia, Major Depressive Disorder and Bipolar Disorder

Objective

Previous studies have shown that certain severe mental illnesses (SMIs) increase the risk of dementia, but those that increase the risk to a greater degree in comparison with other SMIs are unknown. Furthermore, physical illnesses may alter the risk of developing dementia, but these cannot be well-controlled.

Methods

Using the Taiwan National Health Insurance Research Database, patients with schizophrenia, bipolar disorder and major depressive disorder (MDD) were recruited. We also recruited normal healthy subjects as the control group. All subjects were aged over 60 years, and the duration of follow-up was from 2008 to 2015. Multiple confounders were adjusted, including physical illnesses and other variables. Use of medications, especially benzodiazepines, was analyzed in a sensitivity analysis.

Results

36,029 subjects (MDD: 23,371, bipolar disorder: 4,883, schizophrenia: 7,775) and 108,084 control subjects were recruited after matching according to age and sex. The results showed that bipolar disorder had the highest hazard ratio (HR) (HR: 2.14, 95% confidence interval [CI]: 1.99-2.30), followed by schizophrenia (HR: 2.06, 95% CI: 1.93-2.19) and MDD (HR: 1.60, 95% CI: 1.51-1.69). The results remained robust after adjusting for covariates, and sensitivity analysis showed similar results. Anxiolytics use did not increase the risk of dementia in any of the three groups of SMI patients.

Conclusion

SMIs increase the risk of dementia, and among them, bipolar disorder confers the greatest risk of developing dementia. Anxiolytics may not increase the risk of developing dementia in patients with an SMI, but still need to be used with caution in clinical practices.