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.

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.

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.

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.

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.

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.

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.

fMRI measurements of amygdala activation are confounded by stimulus correlated signal fluctuation in nearby veins draining distant brain regions.

Imaging the amygdala with functional MRI is confounded by multiple averse factors, notably signal dropouts due to magnetic inhomogeneity and low signal-to-noise ratio, making it difficult to obtain consistent activation patterns in this region. However, even when consistent signal changes are identified, they are likely to be due to nearby vessels, most notably the basal vein of rosenthal (BVR). Using an accelerated fMRI sequence with a high temporal resolution (TR = 333 ms) combined with susceptibility-weighted imaging, we show how signal changes in the amygdala region can be related to a venous origin. This finding is confirmed here in both a conventional fMRI dataset (TR = 2000 ms) as well as in information of meta-analyses, implying that "amygdala activations" reported in typical fMRI studies are likely confounded by signals originating in the BVR rather than in the amygdala itself, thus raising concerns about many conclusions on the functioning of the amygdala that rely on fMRI evidence alone.

Reduced default mode network suppression during a working memory task in remitted major depression.

Insufficient default mode network (DMN) suppression was linked to increased rumination in symptomatic Major Depressive Disorder (MDD). Since rumination is known to predict relapse and a more severe course of MDD, we hypothesized that similar DMN alterations might also exist during full remission of MDD (rMDD), a condition known to be associated with increased relapse rates specifically in patients with adolescent onset. Within a cross-sectional functional magnetic resonance imaging study activation and functional connectivity (FC) were investigated in 120 adults comprising 78 drug-free rMDD patients with adolescent- (n = 42) and adult-onset (n = 36) as well as 42 healthy controls (HC), while performing the n-back task. Compared to HC, rMDD patients showed diminished DMN deactivation with strongest differences in the anterior-medial prefrontal cortex (amPFC), which was further linked to increased rumination response style. On a brain systems level, rMDD patients showed an increased FC between the amPFC and the dorsolateral prefrontal cortex, which constitutes a key region of the antagonistic working-memory network. Both whole-brain analyses revealed significant differences between adolescent-onset rMDD patients and HC, while adult-onset rMDD patients showed no significant effects. Results of this study demonstrate that reduced DMN suppression exists even after full recovery of depressive symptoms, which appears to be specifically pronounced in adolescent-onset MDD patients. Our results encourage the investigation of DMN suppression as a putative predictor of relapse in clinical trials, which might eventually lead to important implications for antidepressant maintenance treatment.

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.

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).

A multivariate approach linking reported side effects of clinical antidepressant and antipsychotic trials to in vitro binding affinities.

The vast majority of approved antidepressants and antipsychotics exhibit a complex pharmacology. The mechanistic understanding of how these psychotropic medications are related to adverse drug reactions (ADRs) is crucial for the development of novel drug candidates and patient adherence. This study aims to associate in vitro assessed binding affinity profiles (39 compounds, 24 molecular drug targets) and ADRs (n=22) reported in clinical trials of antidepressants and antipsychotics (n>59.000 patients) by the use of robust multivariate statistics. Orthogonal projection to latent structures (O-PLS) regression models with reasonable predictability were found for several frequent ADRs such as nausea, diarrhea, hypotension, dizziness, headache, insomnia, sedation, sleepiness, increased sweating, and weight gain. Results of the present study support many well-known pharmacological principles such as the association of hypotension and dizziness with α1-receptor or sedation with H1-receptor antagonism. Moreover, the analyses revealed novel or hardly investigated mechanisms for common ADRs including the potential involvement of 5-HT6-antagonism in weight gain, muscarinic receptor antagonism in dizziness, or 5-HT7-antagonism in sedation. To summarize, the presented study underlines the feasibility and value of a multivariate data mining approach in psychopharmacological development of antidepressants and antipsychotics.

The spectral diversity of resting-state fluctuations in the human brain.

In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1-0.25 Hz; 0.25-0.75 Hz; 0.75-1.4 Hz) was computed for both the low-TR and (for the two lower-frequency ranges) the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low-TR EPI sequences for resting-state and potentially also task-related fMRI experiments.

Platelet serotonin transporter function predicts default-mode network activity.

BACKGROUND: The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. METHODS: A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet Vmax. RESULTS: The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity. CONCLUSION: This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.

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.

Neuroplasticity and memory formation in major depressive disorder: an imaging genetics perspective on serotonin and BDNF.

A vast number of imaging studies have demonstrated the impact of serotonin (5-HT) and brain-derived neurotrophic factor (BDNF) on emotion and memory-related networks in the context of Major Depressive Disorder (MDD). Underlying molecular mechanisms that affect the functionality of these networks have been examined in detail in animals and corroborate imaging findings. The crucial role of 5-HT and BDNF signaling in the context of MDD is reflected in the etiologic models of MDD such as the monoamine or neuroplasticity hypothesis as well as in pharmacological models of antidepressant response. While antidepressant drug treatment has been primarily linked to the modulation of emotion-related networks, cognitive behavioral therapy has been implicated in a top-down control of limbic structures. Initially, a simple lack of monoamines or BDNF has been proposed as causal factor of MDD etiology. However, recent findings suggest a much more complex neurobiology emphasizing epistatic and epigenetic mechanisms responsible for structural and functional changes observed in emotion and memory-related brain regions of healthy subjects and MDD patients. In this review, which focuses on neuroimaging studies in the context of MDD, the authors will provide a comprehensive overview of these networks as well as on the specific role of 5-HT and BDNF in their development and function.

Fully exploratory network independent component analysis of the 1000 functional connectomes database.

The 1000 Functional Connectomes Project is a collection of resting-state fMRI datasets from more than 1000 subjects acquired in more than 30 independent studies from around the globe. This large, heterogeneous sample of resting-state data offers the unique opportunity to study the consistencies of resting-state networks at both subject and study level. In extension to the seminal paper by Biswal et al. (2010), where a repeated temporal concatenation group independent component analysis (ICA) approach on reduced subsets (using 20 as a pre-specified number of components) was used due to computational resource limitations, we herein apply Fully Exploratory Network ICA (FENICA) to 1000 single-subject independent component analyses. This, along with the possibility of using datasets of different lengths without truncation, enabled us to benefit from the full dataset available, thereby obtaining 16 networks consistent over the whole group of 1000 subjects. Furthermore, we demonstrated that the most consistent among these networks at both subject and study level matched networks most often reported in the literature, and found additional components emerging in prefrontal and parietal areas. Finally, we identified the influence of scan duration on the number of components as a source of heterogeneity between studies.