Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies.

The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.

Brain morphometry and connectivity differs between adolescent- and adult-onset major depressive disorder.

BACKGROUND: Early-onset (EO) major depressive disorder (MDD) patients experience more depressive episodes and an increased risk of relapse. Thus, on a neurobiological level, adult EO patients might display brain structure and function different from adult-onset (AO) patients. METHODS: A total of 103 patients (66 females) underwent magnetic resonance imaging. Structural measures of gray matter volume (GMV) and functional connectivity networks during resting state were compared between EO (≤19 years) and AO groups. Four residual major depression symptoms, mood, anxiety, insomnia, and somatic symptoms, were correlated with GMV between groups. RESULTS: We found comparatively increased GMV in the EO group, namely the medial prefrontal and insular cortex, as well as the anterior hippocampus. Functional networks in EO patients showed a comparatively weaker synchronization of the left hippocampus with the adjacent amygdala, and a stronger integration with nodes in the contralateral prefrontal cortex and supramarginal gyrus. Volumetric analysis of depression symptoms associated the caudate nuclei with symptoms of insomnia, and persisting mood symptoms with the right amygdala, while finding no significant clusters for somatic and anxiety symptoms. CONCLUSIONS: The study highlights the important role of the hippocampus and the prefrontal cortex in EO patients as part of emotion-regulation networks. Results in EO patients demonstrated subcortical volume changes irrespective of sleep and mood symptom recovery, which substantiates adolescence as a pivotal developmental phase for MDD. Longitudinal studies are needed to differentiate neural recovery trajectories while accounting for age of onset.

Neurobiological predictors for clinical trajectories in fully remitted depressed patients.

BACKGROUND: Serious long term health and economic detriment accompany residual depressive symptoms even in fully remitted depressed patients (rMDD). Neurobiological predictors for rMDD patients' illness trajectory are absent. METHODS: rMDD patients (n = 39, female = 26) underwent magnetic resonance imaging. Baseline analyses of brain structure via voxel-based morphometry and brain function via functional connectivity (FC) at rest were correlated with changes in the Hamilton Depression Rating Scale between baseline and follow-up, and incidence of a recurrent major depressive episode (MDE) within a 2-year period. RESULTS: Gray matter increases in default mode (DN) regions in the posterior cingulate cortex (PCC) and increased resting-state FC within the DN both predicted change of depressive symptoms. Patients with recurrent MDE had larger bilateral nucleus accumbens and left insula volumes. Post hoc exploratory analysis of nucleus accumbens and insula conceptualized as part of the brain's reward circuit demonstrated reduced connectivity in patients with recurrent MDE. CONCLUSIONS: Higher DN connectivity and PCC volume coinciding with a more favorable course of symptoms suggest neural mechanisms of self-recovery beyond the phase of active medical treatment. Alterations in the brain's reward circuit might be a starting point for designing maintenance treatments that prevent recurrent MDEs in rMDD patients.

Additive gene-environment effects on hippocampal structure in healthy humans.

Hippocampal volume loss has been related to chronic stress as well as genetic factors. Although genetic and environmental variables affecting hippocampal volume have extensively been studied and related to mental illness, limited evidence is available with respect to G × E interactions on hippocampal volume. The present MRI study investigated interaction effects on hippocampal volume between three well-studied functional genetic variants (COMT Val158Met, BDNF Val66Met, 5-HTTLPR) associated with hippocampal volume and a measure of environmental adversity (life events questionnaire) in a large sample of healthy humans (n = 153). All three variants showed significant interactions with environmental adversity with respect to hippocampal volume. Observed effects were additive by nature and driven by both recent as well as early life events. A consecutive analysis of hippocampal subfields revealed a spatially distinct profile for each genetic variant suggesting a specific role of 5-HTTLPR for the subiculum, BDNF Val66Met for CA4/dentate gyrus, and COMT Val158Met for CA2/3 volume changes. The present study underscores the importance of G × E interactions as determinants of hippocampal volume, which is crucial for the neurobiological understanding of stress-related conditions, such as mood disorders or post-traumatic stress disorder (PTSD).

Physical exercise counteracts genetic susceptibility to depression.

BACKGROUND/AIMS: Depression is a highly prevalent disorder in elderly individuals. A genetic variant (rs6265) of the brain-derived neurotrophic factor (BDNF) impacting on emotion processing is known to increase the risk for depression. We aim to investigate whether intensive endurance sports might attenuate this genetic susceptibility in a cohort of elderly marathon athletes. METHODS: Fifty-five athletes and 58 controls were included. rs6265 of the BDNF gene was genotyped by the TaqMan method. Depressive symptoms were assessed by standardized self-rating tests (BDI = Beck Depression Inventory, GDS = Geriatric Depression Scale). RESULTS: In multivariable analysis of BDI and GDS scores, the interaction between group (athletes vs. controls) and genotypes ([C];[C] vs. [C];[T] + [T];[T]) was found to be statistically significant (BDI: p = 0.027, GDS: p = 0.013). Among [C];[C] carriers, merely controls had an increased relative risk of 3.537 (95% CI = 1.276-9.802) of achieving a subclinical depression score ≥10 on the BDI. There was no such effect in carriers of the [T] allele. In a multivariable binary logistic regression, genetic information, group (athletes/controls), but no information on rs6265 allele carrier status presented as a significant predictor of BDI scores ≥10. CONCLUSION: Physical exercise positively affects BDNF effects on mood. Since 66Met BDNF secretion is impaired, this effect seems to be much stronger in [C];[C] homozygous individuals expressing the 66Val variant. This confirms that genetic susceptibility to depressive symptoms can indeed be influenced by endurance sports in elderly people.

rs6295 [C]-Allele Protects Against Depressive Mood in Elderly Endurance Athletes.

A single nucleotide variant within the promoter of the 5-hydroxytryptamine1A (5HT1A) receptor, rs6295, is part of a binding site for the transcription factor. We aimed to ascertain whether the rs6295 mediates the effect of exercise on depressive mood in elderly endurance athletes. We prospectively enrolled 55 elderly athletes (marathon runners/bicyclists) and 58 controls. In a controlled, univariate model, an interaction between the [C]-allele and physical activity indicated that only among athletes, the variant resulting in an imperfect NUDR binding site was associated with a lower depression score. Hence, athletes presented with a significantly lower relative risk of achieving a suspicious depression score among carriers of at least one [C]-allele. Our results suggest that the positive effect of physical exercise on depressive mood might be mediated by the 5HT1A receptor and the extent of this protective effect seems to be enhanced by the [C]-allele of the rs6295 variant.

Affective and inflammatory responses among orchestra musicians in performance situation.

A number of studies have shown that mental challenge under controlled experimental conditions is associated with elevations in inflammatory markers such as interleukin-6 (IL-6) and C-reactive protein (CRP). However, relatively little work has been done on the effects of 'naturalistic' stressors on acute changes in inflammatory markers. The present study examined whether perceived arousal, valence and dominance in musicians are associated with pro-inflammatory and oxidative responses to a concert situation. Blood and salivary samples obtained from 48 members of a symphony orchestra on the day of rehearsal (i.e., control situation) and on the following day of premiere concert (i.e., test situation) were used to determine changes in salivary cortisol, pro-inflammatory markers (plasma myeloperoxidase, serum CRP, plasma IL-6), oxidative stress markers (paraoxonase1 activity and malondialdehyde), and homocysteine, a risk factor for vascular disease. Results of regression analyses showed a significant trend to increased myeloperoxidase (MPO) response in individuals with low valence score. Both affective states, valence and arousal, were identified as significant predictors of cortisol response during concert. In addition, control levels of plasma malondialdehyde were positively correlated with differences in IL-6 levels between premiere and rehearsal (r=.38, p=.012), pointing to higher oxidative stress in individuals with pronounced IL-6 response. Our results indicate that stress of public performance leads to increased concentrations of plasma MPO (20%), IL-6 (27%) and salivary cortisol (44%) in musicians. The decreasing effect of pleasantness on the MPO response was highly pronounced in non-smokers (r=-.60, p<.001), suggesting a significant role of emotional valence in stress-induced secretion of MPO. Additional studies are needed to assess the generalizability of these findings to other 'naturalistic' stress situations.

A highly parallelized framework for computationally intensive MR data analysis.

OBJECT: The goal of this study was to develop a comprehensive magnetic resonance (MR) data analysis framework for handling very large datasets with user-friendly tools for parallelization and to provide an example implementation. MATERIALS AND METHODS: Commonly used software packages (AFNI, FSL, SPM) were connected via a framework based on the free software environment R, with the possibility of using Nvidia CUDA GPU processing integrated for high-speed linear algebra operations in R. Three hundred single-subject datasets from the 1,000 Functional Connectomes project were used to demonstrate the capabilities of the framework. RESULTS: A framework for easy implementation of processing pipelines was developed and an R package for the example implementation of Fully Exploratory Network ICA was compiled. Test runs on data from 300 subjects demonstrated the computational advantages of a processing pipeline developed using the framework compared to non-parallelized processing, reducing computation time by a factor of 15. CONCLUSION: The feasibility of computationally intensive exploratory analyses allows broader access to the tools for discovery science.

Altered resting-state functional connectome in major depressive disorder: a mega-analysis from the PsyMRI consortium.

Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.

Imaging genetics of mood disorders.

Mood disorders are highly heritable and have been linked to brain regions of emotion processing. Over the past few years, an enormous amount of imaging genetics studies has demonstrated the impact of risk genes on brain regions and systems of emotion processing in vivo in healthy subjects as well as in mood disorder patients. While sufficient evidence already exists for several monaminergic genes as well as for a few non-monoaminergic genes, such as brain-derived neurotrophic factor (BDNF) in healthy subjects, many others only have been investigated in single studies so far. Apart from these studies, the present review also covers imaging genetics studies applying more complex genetic disease models of mood disorders, such as epistasis and gene-environment interactions, and their impact on brain systems of emotion processing. This review attempts to provide a comprehensive overview of the rapidly growing field of imaging genetics studies in mood disorder research.

Multi-subject analyses with dynamic causal modeling.

Currently, most studies that employ dynamic causal modeling (DCM) use random-effects (RFX) analysis to make group inferences, applying a second-level frequentist test to subjects' parameter estimates. In some instances, however, fixed-effects (FFX) analysis can be more appropriate. Such analyses can be implemented by combining the subjects' posterior densities according to Bayes' theorem either on a multivariate (Bayesian parameter averaging or BPA) or univariate basis (posterior variance weighted averaging or PVWA), or by applying DCM to time-series averaged across subjects beforehand (temporal averaging or TA). While all these FFX approaches have the advantage of allowing for Bayesian inferences on parameters a systematic comparison of their statistical properties has been lacking so far. Based on simulated data generated from a two-region network we examined the effects of signal-to-noise ratio (SNR) and population heterogeneity on group-level parameter estimates. Data sets were simulated assuming either a homogeneous large population (N=60) with constant connectivities across subjects or a heterogeneous population with varying parameters. TA showed advantages at lower SNR but is limited in its applicability. Because BPA and PVWA take into account posterior (co)variance structure, they can yield non-intuitive results when only considering posterior means. This problem is relevant for high SNR data, pronounced parameter interdependencies and when FFX assumptions are violated (i.e. inhomogeneous groups). It diminishes with decreasing SNR and is absent for models with independent parameters or when FFX assumptions are appropriate. Group results obtained with these FFX approaches should therefore be interpreted carefully by considering estimates of dependencies among model parameters.

Is there a personalized medicine for mood disorders?

Major Depressive Disorder (MDD) and antidepressant therapy response are largely based on behavioral criteria, which are known to correlate at best modestly with biological measures. Therefore, it is not surprising that the search for peripheral biological markers (biomarkers) being assessed in distant biological systems such as body fluids has not yet resulted in clinically convincing measures for MDD diagnostics or treatment evaluation. Imaging genetics studies, however, have been successful in the search for intermediate imaging phenotypes of MDD and treatment response that are directly related to the neurobiological underpinnings of MDD, but are not suitable for a broad clinical use today. Hence, we argue that intermediate phenotypes derived from imaging genetics studies should be utilized as substitutes of behaviorally assessed psychiatric diagnoses or therapy response in the search for easily accessible peripheral biomarkers. This article will further cover the current state of peripheral and neural biomarker research.

On the relationship of first-episode psychosis to the amphetamine-sensitized state: a dopamine D2/3 receptor agonist radioligand study.

Schizophrenia is characterized by increased behavioral and neurochemical responses to dopamine-releasing drugs. This prompted the hypothesis of psychosis as a state of "endogenous" sensitization of the dopamine system although the exact basis of dopaminergic disturbances and the possible role of prefrontal cortical regulation have remained uncertain. To show that patients with first-episode psychosis release more dopamine upon amphetamine-stimulation than healthy volunteers, and to reveal for the first time that prospective sensitization induced by repeated amphetamine exposure increases dopamine-release in stimulant-naïve healthy volunteers to levels observed in patients, we collected data on amphetamine-induced dopamine release using the dopamine D2/3 receptor agonist radioligand [11C]-(+)-PHNO and positron emission tomography. Healthy volunteers (n = 28, 14 female) underwent a baseline and then a post-amphetamine scan before and after a mildly sensitizing regimen of repeated oral amphetamine. Unmedicated patients with first-episode psychosis (n = 21; 6 female) underwent a single pair of baseline and then post-amphetamine scans. Furthermore, T1 weighted magnetic resonance imaging of the prefrontal cortex was performed. Patients with first-episode psychosis showed larger release of dopamine compared to healthy volunteers. After sensitization of healthy volunteers their dopamine release was significantly amplified and no longer different from that seen in patients. Healthy volunteers showed a negative correlation between prefrontal cortical volume and dopamine release. There was no such relationship after sensitization or in patients. Our data in patients with untreated first-episode psychosis confirm the "endogenous sensitization" hypothesis and support the notion of impaired prefrontal control of the dopamine system in schizophrenia.

Impact of interacting functional variants in COMT on regional gray matter volume in human brain.

BACKGROUND: Functional variants in the catechol-O-methyltransferase (COMT) gene have been shown to impact cognitive function, cortical physiology and risk for schizophrenia. A recent study showed that previously reported effects of the functional val158met SNP (rs4680) on brain function are modified by other functional SNPs and haplotypes in the gene, though it was unknown if these effects are also seen in brain structure. METHODS: We used voxel-based morphometry to investigate the impact of multiple functional variants in COMT on gray matter volume in a large group of 151 healthy volunteers from the CBDB/NIMH Genetic Study of Schizophrenia. RESULTS: We found that the previously described rs4680 val risk variant affects hippocampal and dorsolateral prefrontal (DLPFC) gray matter volume. In addition, we found that this SNP interacts with a variant in the P2 promoter region (rs2097603) in predicting changes in hippocampal gray matter volume consistent with a nonlinear effect of extracellular dopamine. CONCLUSIONS: We report evidence that interacting functional variants in COMT affect gray matter regional volume in hippocampus and DLPFC, providing further in vivo validation of the biological impact of complex genetic variation in COMT on neural systems relevant for the pathophysiology of schizophrenia and extending observations of nonlinear dependence of prefrontal neurons on extracellular dopamine to the domain of human brain structure.

5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression.

Carriers of the short allele of a functional 5' promoter polymorphism of the serotonin transporter gene have increased anxiety-related temperamental traits, increased amygdala reactivity and elevated risk of depression. Here, we used multimodal neuroimaging in a large sample of healthy human subjects to elucidate neural mechanisms underlying this complex genetic association. Morphometrical analyses showed reduced gray matter volume in short-allele carriers in limbic regions critical for processing of negative emotion, particularly perigenual cingulate and amygdala. Functional analysis of those regions during perceptual processing of fearful stimuli demonstrated tight coupling as a feedback circuit implicated in the extinction of negative affect. Short-allele carriers showed relative uncoupling of this circuit. Furthermore, the magnitude of coupling inversely predicted almost 30% of variation in temperamental anxiety. These genotype-related alterations in anatomy and function of an amygdala-cingulate feedback circuit critical for emotion regulation implicate a developmental, systems-level mechanism underlying normal emotional reactivity and genetic susceptibility for depression.

Prefrontal networks dynamically related to recovery from major depressive disorder: a longitudinal pharmacological fMRI study.

Due to lacking predictors of depression recovery, successful treatment of major depressive disorder (MDD) is frequently only achieved after therapeutic optimization leading to a prolonged suffering of patients. This study aimed to determine neural prognostic predictors identifying non-remitters prior or early after treatment initiation. Moreover, it intended to detect time-sensitive neural mediators indicating depression recovery. This longitudinal, interventional, single-arm, open-label, phase IV, pharmacological functional magnetic resonance imaging (fMRI) study comprised four scans at important stages prior (day 0) and after escitalopram treatment initiation (day 1, 28, and 56). Totally, 22 treatment-free MDD patients (age mean ± SD: 31.5 ± 7.7; females: 50%) suffering from a concurrent major depressive episode without any comorbid DSM-IV axis I diagnosis completed the study protocol. Primary outcome were neural prognostic predictors of depression recovery. Enhanced de-activation of anterior medial prefrontal cortex (amPFC, single neural mediator) indicated depression recovery correlating with MADRS score and working memory improvements. Strong dorsolateral PFC (dlPFC) activation and weak dlPFC-amPFC, dlPFC-posterior cingulate cortex (PCC), dlPFC-parietal lobe (PL) coupling (three prognostic predictors) hinted at depression recovery at day 0 and 1. Preresponse prediction of continuous (dlPFC-PL: R2day1 = 55.9%, 95% CI: 22.6-79%, P < 0.005) and dichotomous (specificity/sensitivity: SP/SNday1 = 0.91/0.82) recovery definitions remained significant after leave-one-out cross-validation. Identified prefrontal neural predictors might propel the future development of fMRI markers for clinical decision making, which could lead to increased response rates and adherence during acute phase treatment periods. Moreover, this study underscores the importance of the amPFC in depression recovery.

Allelic variation in RGS4 impacts functional and structural connectivity in the human brain.

Regulator of G-protein signaling 4 (RGS4) modulates postsynaptic signal transduction by affecting the kinetics of G alpha-GTP binding. Linkage, association, and postmortem studies have implicated the gene encoding RGS4 (RGS4) as a schizophrenia susceptibility factor. Using a multimodal neuroimaging approach, we demonstrate that genetic variation in RGS4 is associated with functional activation and connectivity during working memory in the absence of overt behavioral differences, with regional gray and white matter volume and with gray matter structural connectivity in healthy human subjects. Specifically, variation at one RGS4 single nucleotide polymorphism that has been associated previously with psychosis (rs951436) impacts frontoparietal and frontotemporal blood oxygenation level-dependent response and network coupling during working memory and results in regionally specific reductions in gray and white matter structural volume in individuals carrying the A allele. These findings suggest mechanisms in brain for the association of RGS4 with risk for psychiatric illness.

New perspectives on techniques for the clinical psychiatrist: Brain stimulation, chronobiology and psychiatric brain imaging.

This review summarizes a scientific dialogue between representatives in non-pharmacological treatment options of affective disorders. Among the recently introduced somatic treatments for depression those with most evidenced efficacy will be discussed. The first part of this article presents current opinions about the clinical applications of transcranial magnetic stimulation in the treatment of depression. The second part explains the most relevant uses of chronobiology in mood disorders, while the last part deals with the main perspectives on brain imaging techniques in psychiatry. The aim was to bridge gaps between the research evidence and clinical decisions, and reach an agreement on several key points of chronobiological and brain stimulation techniques, as well as on relevant objectives for future research.

Midday and nadir salivary cortisol appear superior to cortisol awakening response in burnout assessment and monitoring.

Burnout and work-related stress symptoms of anxiety disorder and depression cause prolonged work absenteeism and early retirement. Hence, reliable identification of patients under risk and monitoring of treatment success is highly warranted. We aimed to evaluate stress-specific biomarkers in a population-based, "real-world" cohort (burnouts: n = 40, healthy controls: n = 26), recruited at a preventive care ward, at baseline and after a four-month follow up, during which patients received medical and psychological treatment. At baseline, significantly higher levels of salivary cortisol were observed in the burnout group compared to the control group. This was even more pronounced in midday- (p < 0.001) and nadir samples (p < 0.001) than for total morning cortisol secretion (p < 0.01). The treatment program resulted in a significant reduction of stress, anxiety, and depression scores (all p < 0.001), with 60% of patients showing a clinically relevant improvement. This was accompanied by a ~30% drop in midday cortisol levels (p < 0.001), as well as a ~25% decrease in cortisol nadir (p < 0.05), although not directly correlating with score declines. Our data emphasize the potential usefulness of midday and nadir salivary cortisol as markers in the assessment and biomonitoring of burnout.

Oppositional COMT Val158Met effects on resting state functional connectivity in adolescents and adults.

Prefrontal dopamine levels are relatively increased in adolescence compared to adulthood. Genetic variation of COMT (COMT Val158Met) results in lower enzymatic activity and higher dopamine availability in Met carriers. Given the dramatic changes of synaptic dopamine during adolescence, it has been suggested that effects of COMT Val158Met genotypes might have oppositional effects in adolescents and adults. The present study aims to identify such oppositional COMT Val158Met effects in adolescents and adults in prefrontal brain networks at rest. Resting state functional connectivity data were collected from cross-sectional and multicenter study sites involving 106 healthy young adults (mean age 24 ± 2.6 years), gender matched to 106 randomly chosen 14-year-olds. We selected the anterior medial prefrontal cortex (amPFC) as seed due to its important role as nexus of the executive control and default mode network. We observed a significant age-dependent reversal of COMT Val158Met effects on resting state functional connectivity between amPFC and ventrolateral as well as dorsolateral prefrontal cortex, and parahippocampal gyrus. Val homozygous adults exhibited increased and adolescents decreased connectivity compared to Met homozygotes for all reported regions. Network analyses underscored the importance of the parahippocampal gyrus as mediator of observed effects. Results of this study demonstrate that adolescent and adult resting state networks are dose-dependently and diametrically affected by COMT genotypes following a hypothetical model of dopamine function that follows an inverted U-shaped curve. This study might provide cues for the understanding of disease onset or dopaminergic treatment mechanisms in major neuropsychiatric disorders such as schizophrenia and attention deficit hyperactivity disorder.