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

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.

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.

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.

Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia

Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.

Distinct Cognitive Function Profiles Are Associated With a Higher Presurgery Symptom Burden in Patients With Breast Cancer

BACKGROUND

Cancer-related cognitive impairment (CRCI) is a common symptom in patients with breast cancer. In our previous study of 397 women with breast cancer, we identified 3 groups of patients with distinct CRCI profiles (ie, high, moderate, and low-moderate attentional function). Compared with the other 2 classes, the low-moderate class was younger, had more comorbidities, and with lower functional status.

OBJECTIVES

In this study, we expand on this work and evaluate for differences among these latent classes in the severity of psychological (depression and anxiety) and physical (fatigue, decrements in energy, sleep disturbance, and pain) symptoms before surgery.

METHODS

Cancer-related cognitive impairment was assessed using the Attentional Functional Index from before through 6 months after surgery. Lower Attentional Functional Index scores indicate higher levels of CRCI. Psychological and physical symptoms were assessed with valid instruments. Parametric and nonparametric tests were used to evaluate for differences in symptom severity scores among the latent classes.

RESULTS

Approximately 60% of patients experienced CRCI (ie, moderate and low-moderate classes). Significant differences were found among the 3 classes in the severity of trait and state anxiety, depressive symptoms, fatigue, and sleep disturbance (ie, high < moderate < low-moderate). In addition, compared with the other 2 classes, the low-moderate class reported higher pain interference scores.

CONCLUSIONS

These findings suggest that women with clinically meaningful levels of persistent CRCI have a relatively high symptom burden before surgery.

IMPLICATIONS FOR PRACTICE

Clinicians need to routinely perform preoperative assessments of CRCI and associated symptoms and initiate therapeutic interventions.

From neurotransmitters to networks: Transcending organisational hierarchies with molecular-informed functional imaging

The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain's function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research - spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses - to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.

Serotonin sensing by microglia conditions the proper development of neuronal circuits and of social and adaptive skills

The proper maturation of emotional and sensory circuits requires fine-tuning of serotonin (5-HT) level during early postnatal development. Consistently, dysfunctions of the serotonergic system have been associated with neurodevelopmental psychiatric diseases, including autism spectrum disorders (ASD). However, the mechanisms underlying the developmental effects of 5-HT remain partially unknown, one obstacle being the action of 5-HT on different cell types. Here, we focused on microglia, which play a role in brain wiring refinement, and we investigated whether the control of these cells by 5-HT is relevant for neurodevelopment and spontaneous behaviors in mice. Since the main 5-HT sensor in microglia is the 5-HT2B receptor subtype, we prevented 5-HT signaling specifically in microglia by conditional invalidation of the Htr2b gene in these cells. We observed that abrogating the serotonergic control of microglia during early postnatal development affects the phagolysosomal compartment of these cells and their proximity to dendritic spines and perturbs neuronal circuits maturation. Furthermore, this early ablation of microglial 5-HT2B receptors leads to adult hyperactivity in a novel environment and behavioral defects in sociability and flexibility. Importantly, we show that these behavioral alterations result from a developmental effect, since they are not observed when microglial Htr2b invalidation is induced later, at P30 onward. Thus, a primary alteration of 5-HT sensing in microglia, during a critical time window between birth and P30, is sufficient to impair social and flexibility skills. This link between 5-HT and microglia may explain the association between serotonergic dysfunctions and behavioral traits like impaired sociability and inadaptability to novelty, which are prominent in psychiatric disorders such as ASD.

Spatiotemporal dynamics of functional connectivity and association with molecular architecture in schizophrenia

Schizophrenia is a self-disorder characterized by disrupted brain dynamics and architectures of multiple molecules. This study aims to explore spatiotemporal dynamics and its association with psychiatric symptoms. Resting-state functional magnetic resonance imaging data were collected from 98 patients with schizophrenia. Brain dynamics included the temporal and spatial variations in functional connectivity density and association with symptom scores were evaluated. Moreover, the spatial association between dynamics and receptors/transporters according to prior molecular imaging in healthy subjects was examined. Patients demonstrated decreased temporal variation and increased spatial variation in perceptual and attentional systems. However, increased temporal variation and decreased spatial variation were revealed in higher order networks and subcortical networks in patients. Specifically, spatial variation in perceptual and attentional systems was associated with symptom severity. Moreover, case-control differences were associated with dopamine, serotonin and mu-opioid receptor densities, serotonin reuptake transporter density, dopamine transporter density, and dopamine synthesis capacity. Therefore, this study implicates the abnormal dynamic interactions between the perceptual system and cortical core networks; in addition, the subcortical regions play a role in the dynamic interaction among the cortical regions in schizophrenia. These convergent findings support the importance of brain dynamics and emphasize the contribution of primary information processing to the pathological mechanism underlying schizophrenia.

Connecting Circuits with Networks in Addiction Neuroscience: A Salience Network Perspective

Human neuroimaging has demonstrated the existence of large-scale functional networks in the cerebral cortex consisting of topographically distant brain regions with functionally correlated activity. The salience network (SN), which is involved in detecting salient stimuli and mediating inter-network communication, is a crucial functional network that is disrupted in addiction. Individuals with addiction display dysfunctional structural and functional connectivity of the SN. Furthermore, while there is a growing body of evidence regarding the SN, addiction, and the relationship between the two, there are still many unknowns, and there are fundamental limitations to human neuroimaging studies. At the same time, advances in molecular and systems neuroscience techniques allow researchers to manipulate neural circuits in nonhuman animals with increasing precision. Here, we describe attempts to translate human functional networks to nonhuman animals to uncover circuit-level mechanisms. To do this, we review the structural and functional connections of the salience network and its homology across species. We then describe the existing literature in which circuit-specific perturbation of the SN sheds light on how functional cortical networks operate, both within and outside the context of addiction. Finally, we highlight key outstanding opportunities for mechanistic studies of the SN.

Neuropharmacological computational analysis of longitudinal electroencephalograms in clozapine-treated patients with schizophrenia using hierarchical dynamic causal modeling

The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN. The medication duration mainly affects the intrinsic connectivity and NMDA time constant in DMN. Virtual perturbation analysis specified the contribution of each parameter to the cross-spectral density (CSD) of the EEG, particularly intrinsic connectivity and membrane capacitances for CSD frequency shifts and progression. It further reveals that excitatory and inhibitory connectivity complements frequency-specific CSD changes, notably the alpha frequency band in DMN. Positive and negative synergistic interactions exist between neurobiological properties primarily within the same region in patients treated with clozapine. The current study shows how computational neuropharmacology helps explore the multiscale link between neurobiological properties and clinical observations and understand the long-term mechanism of neuropharmacological intervention reflected in clinical EEG.

The comorbidity of depression and neurocognitive disorder in persons with HIV infection: call for investigation and treatment

Depression and neurocognitive disorder continue to be the major neuropsychiatric disorders affecting persons with HIV (PWH). The prevalence of major depressive disorder is two to fourfold higher among PWH than the general population (∼6.7%). Prevalence estimates of neurocognitive disorder among PWH range from 25 to over 47% - depending upon the definition used (which is currently evolving), the size of the test battery employed, and the demographic and HIV disease characteristics of the participants included, such as age range and sex distribution. Both major depressive disorder and neurocognitive disorder also result in substantial morbidity and premature mortality. However, though anticipated to be relatively common, the comorbidity of these two disorders in PWH has not been formally studied. This is partly due to the clinical overlap of the neurocognitive symptoms of these two disorders. Both also share neurobehavioral aspects - particularly apathy - as well as an increased risk for non-adherence to antiretroviral therapy. Shared pathophysiological mechanisms potentially explain these intersecting phenotypes, including neuroinflammatory, vascular, and microbiomic, as well as neuroendocrine/neurotransmitter dynamic mechanisms. Treatment of either disorder affects the other with respect to symptom reduction as well as medication toxicity. We present a unified model for the comorbidity based upon deficits in dopaminergic transmission that occur in both major depressive disorder and HIV-associated neurocognitive disorder. Specific treatments for the comorbidity that decrease neuroinflammation and/or restore associated deficits in dopaminergic transmission may be indicated and merit study.

Topography of the Anxious Self: Abnormal Rest-Task Modulation in Social Anxiety Disorder

Social anxiety disorder (SAD) is characterized by social anxiety/fear, self-attention, and interoception. Functional magnetic resonance imaging studies demonstrate increased activity during symptom-sensitive tasks in regions of the default-mode network (DMN), amygdala (AMG), and salience network (SN). What is the source of this task-unspecific symptom-sensitive hyperactivity in DMN? We address this question by probing SAD resting state (rs) changes in DMN including their relation to other regions as possible source of task-unspecific hyperactivity in the same regions. Our findings show the following: (1) rs-hypoconnectivity within-DMN regions; (2) rs-hyperconnectivity between DMN and AMG/SN; (3) task-evoked hyperactivity in the abnormal rs-regions of DMN and AMG/SN during different symptom-sensitive tasks; (4) negative relationship of rest and task changes in especially anterior DMN regions as their rs-hypoconnectivity is accompanied by task-unspecific hyperactivity; (5) abnormal top-down/bottom-up modulation between anterior DMN regions and AMG during rest and task. Findings demonstrate that rs-hypoconnectivity among DMN regions is negatively related to task-unspecific hyperactivity in DMN and AMG/SN. We propose a model of "Topography of the Anxious Self" in SAD (TAS-SAD). Abnormal DMN-AMG/SN topography during rest, as trait feature of an "unstable social self", is abnormally aggravated during SAD-sensitive situations resulting in task-related hyperactivity in the same regions with an "anxious self" as state feature.

Alcohol-induced changes in mesostriatal resting-state functional connectivity are linked to sensation seeking in young adults

BACKGROUND

Studies in animals and humans suggest that greater levels of sensation seeking and alcohol use are related to individual differences in drug-induced dopamine release. However, it remains unclear whether drug-induced alterations in the functional synchrony between mesostriatal regions are related to sensation seeking and alcohol use.

METHODS

In this within-subject masked-design study, 21-year-old participants (n = 34) underwent functional magnetic resonance imaging to measure ventral tegmental area (VTA) resting-state functional connectivity to the striatum after receiving alcohol (target blood alcohol concentration 0.08 g/dL) or placebo. Participants also completed the UPPS-P Impulsive Behavior Scale to assess sensation seeking, the Young Adult Alcohol Consequences Questionnaire, and self-reported patterns of alcohol and drug use.

RESULTS

Voxel-wise analyses within the striatum demonstrated that during the alcohol condition (compared with placebo) young adults had less connectivity between the VTA and bilateral caudate (p < 0.05 corrected). However, young adults exhibiting smaller alcohol-induced decreases or increases in VTA-left caudate connectivity reported greater sensation seeking.

CONCLUSION

These findings provide novel information about how acute alcohol impacts resting-state connectivity, an effect that may be driven by the complex pre and postsynaptic effects of alcohol on various neurotransmitters including dopamine. Further, alcohol-induced differences in VTA connectivity represent a plausible mechanistic substrate underlying sensation seeking.