Neural Circuitry and Therapeutic Targeting of Depressive Symptoms in Schizophrenia Spectrum Disorders.

OBJECTIVE: Conceptual similarities between depressive and negative symptoms complicate biomarker and intervention development. This study employed a data-driven approach to delineate the neural circuitry underlying depressive and negative symptoms in schizophrenia spectrum disorders (SSDs). METHODS: Data from three studies were analyzed (157 participants with SSDs) to assess brain-behavior relationships: two neuroimaging studies and a randomized trial of repetitive transcranial magnetic stimulation (rTMS). Partial least squares correlation (PLSC) was used to investigate associations between resting-state functional connectivity and depressive and negative symptoms. Secondary analyses of rTMS trial data (active, N=37; sham, N=33) were used to assess relationships between PLSC-derived symptom profiles and treatment outcomes. RESULTS: PLSC identified three latent variables (LVs) relating functional brain circuitry with symptom profiles. LV1 related a general depressive symptom factor with positive associations between and within the default mode network (DMN), the frontoparietal network (FPN), and the cingulo-opercular network (CON). LV2 related negative symptoms (no depressive symptoms) via negative associations, especially between the FPN and the CON, but also between the DMN and the FPN and the CON. LV3 related a guilt and early wakening depression factor via negative rather than positive associations with the DMN, FPN, and CON. The secondary visual network had a positive association with general depressive symptoms and negative associations with guilt and negative symptoms. Active (but not sham) rTMS applied bilaterally to the dorsolateral prefrontal cortex (DLPFC) reduced general depressive but not guilt-related or negative symptoms. CONCLUSIONS: The results clearly differentiate the neural circuitry underlying depressive and negative symptoms, and segregated across the two-factor structure of depression in SSDs. These findings support divergent neurobiological pathways of depressive symptoms and negative symptoms in people with SSDs. As treatment options are currently limited, bilateral rTMS to the DLPFC is worth exploring further for general depressive symptoms in people with SSDs.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression.

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Acute Stress Increases Striatal Connectivity With Cortical Regions Enriched for µ and κ Opioid Receptors.

BACKGROUND: Understanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps. METHODS: Across 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task. Using partial least squares regression, we investigated genes whose expression in the Allen Human Brain Atlas was associated with anatomical patterns of stress-related FC change. Finally, we correlated stress-related FC change maps with opioid and GABAA (gamma-aminobutyric acid A) receptor distribution maps derived from positron emission tomography. RESULTS: Results revealed robust effects of stress on global cortical connectivity, with increased global FC in frontoparietal and attentional networks and decreased global FC in the medial default mode network. Moreover, robust increases emerged in FC of the caudate, putamen, and amygdala with regions from the ventral attention/salience network, frontoparietal network, and motor networks. Such regions showed preferential expression of genes involved in cell-to-cell signaling (OPRM1, OPRK1, SST, GABRA3, GABRA5), similar to previous genetic MDD studies. CONCLUSIONS: Acute stress altered global cortical connectivity and increased striatal connectivity with cortical regions that express genes that have previously been associated with imaging abnormalities in MDD and are rich in µ and κ opioid receptors. These findings point to overlapping circuitry underlying stress response, reward, and MDD.

Heterogeneity of Cognition in Older Adults with Remitted Major Depressive Disorder: A Latent Profile Analysis.

OBJECTIVES: To identify data-driven cognitive profiles in older adults with remitted major depressive disorder (rMDD) with or without mild cognitive impairment (MCI) and examine how the profiles differ regarding demographic, clinical, and neuroimaging measures. DESIGN: Secondary cross-sectional analysis using latent profile analysis. SETTING: Multisite clinical trial in Toronto, Canada. PARTICIPANTS: One hundred seventy-eight participants who met DSM-5 criteria for rMDD without MCI (rMDD-MCI; n = 60) or with MCI (rMDD + MCI; n = 118). MEASUREMENTS: Demographic, clinical, neuroimaging measures, and domain scores from a neuropsychological battery assessing verbal memory, visuospatial memory, processing speed, working memory, language, and executive function. RESULTS: We identified three latent profiles: Profile 1 (poor cognition; n = 75, 42.1%), Profile 2 (intermediate cognition; n = 75, 42.1%), and Profile 3 (normal cognition; n = 28, 15.7%). Compared to participants with Profile 3, those with Profile 1 or 2 were older, had lower education, experienced a greater burden of medical comorbidities, and were more likely to have MCI. The profiles did not differ on the severity of residual symptoms, age of onset of rMDD, number of depressive episodes, psychotropic medication, cerebrovascular risk, ApoE4 carrier status, or family history of depression, dementia, or Alzheimer's disease. The profiles differed in cortical thickness of 15 regions, with the most prominent effects for left precentral and pars opercularis, and right inferior parietal and supramarginal. CONCLUSION: Older patients with rMDD can be grouped cross-sectionally based on data-driven cognitive profiles that differ from the absence or presence of a diagnosis of MCI. Future research should determine the differential risk for dementia of these data-driven subgroups.

Age-Related Alterations in Gray Matter Microstructure in Older People With Remitted Major Depression at Risk for Dementia.

Background: Major depressive disorder (MDD) in late life is a risk factor for mild cognitive impairment (MCI) and Alzheimer's disease. However, studies of gray matter changes have produced varied estimates of which structures are implicated in MDD and dementia. Changes in gray matter volume and cortical thickness are macrostructural measures for the microstructural processes of free water accumulation and dendritic spine loss. Methods: We conducted multishell diffusion imaging to assess gray matter microstructure in 244 older adults with remitted MDD (n = 44), MCI (n = 115), remitted MDD+MCI (n = 61), or without psychiatric disorders or cognitive impairment (healthy control participants; n = 24). We estimated measures related to neurite density, orientation dispersion, and free water (isotropic volume fraction) using a biophysically plausible model (neurite orientation dispersion and density imaging). Results: Results showed that increasing age was correlated with an increase in isotropic volume fraction and a decrease in orientation dispersion index, which is consistent with neuropathology dendritic loss. In addition, this relationship between age and increased isotropic volume fraction was more disrupted in the MCI group than in the remitted MDD or healthy control groups. However, the association between age and orientation dispersion index was similar for all 3 groups. Conclusions: The findings suggest that the neurite orientation dispersion and density imaging measures could be used to identify biological risk factors for Alzheimer's disease, signifying both conventional neurodegeneration observed with MCI and dendritic loss seen in MDD.

Neurobehavioral Precursors of Compulsive Cocaine Seeking in Dual Frontostriatal Circuits.

Background: Only some individuals who use drugs recreationally eventually develop a substance use disorder, characterized in part by the rigid engagement in drug foraging behavior (drug seeking), which is often maintained in the face of adverse consequences (i.e., is compulsive). The neurobehavioral determinants of this individual vulnerability have not been fully elucidated. Methods: Using a prospective longitudinal study involving 39 male rats, we combined multidimensional characterization of behavioral traits of vulnerability to stimulant use disorder (impulsivity and stickiness) and resilience (sign tracking and sensation seeking/locomotor reactivity to novelty) with magnetic resonance imaging to identify the structural and functional brain correlates of the later emergence of compulsive drug seeking in drug-naïve subjects. We developed a novel behavioral procedure to investigate the individual tendency to persist in drug-seeking behavior in the face of punishment in a drug-free state in subjects with a prolonged history of cocaine seeking under the control of the conditioned reinforcing properties of a drug-paired Pavlovian conditioned stimulus. Results: In drug-naïve rats, the tendency to develop compulsive cocaine seeking was characterized by behavioral stickiness-related functional hypoconnectivity between the prefrontal cortex and posterior dorsomedial striatum in combination with impulsivity-related structural alterations in the infralimbic cortex, anterior insula, and nucleus accumbens. Conclusions: These findings show that the vulnerability to developing compulsive cocaine-seeking behavior stems from preexisting structural or functional changes in two distinct corticostriatal systems that underlie deficits in impulse control and goal-directed behavior.

Opposing brain signatures of sleep in task-based and resting-state conditions.

Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project. Neural signatures of insomnia and depression are negatively correlated with those of sleep duration measured by accelerometer in the task condition but positively correlated in the resting-state condition. Our results show that resting-state neural signatures of insomnia and depression resemble that of rested wakefulness. This is further supported by our finding of hypoconnectivity in task but hyperconnectivity in resting-state data in association with insomnia and depression. These observations dispute conventional assumptions about the neurofunctional manifestations of hyper- and hypo-somnia, and may explain inconsistent findings in the literature.

Protocol for a systematic review and meta-analysis of coordinate-based network mapping of brain structure in bipolar disorder across the lifespan.

BACKGROUND: Studies about brain structure in bipolar disorder have reported conflicting findings. These findings may be explained by the high degree of heterogeneity within bipolar disorder, especially if structural differences are mapped to single brain regions rather than networks. AIMS: We aim to complete a systematic review and meta-analysis to identify brain networks underlying structural abnormalities observed on T1-weighted magnetic resonance imaging scans in bipolar disorder across the lifespan. We also aim to explore how these brain networks are affected by sociodemographic and clinical heterogeneity in bipolar disorder. METHOD: We will include case-control studies that focus on whole-brain analyses of structural differences between participants of any age with a standardised diagnosis of bipolar disorder and controls. The electronic databases Medline, PsycINFO and Web of Science will be searched. We will complete an activation likelihood estimation analysis and a novel coordinate-based network mapping approach to identify specific brain regions and brain circuits affected in bipolar disorder or relevant subgroups. Meta-regressions will examine the effect of sociodemographic and clinical variables on identified brain circuits. CONCLUSIONS: Findings from this systematic review and meta-analysis will enhance understanding of the pathophysiology of bipolar disorder. The results will identify brain circuitry implicated in bipolar disorder, and how they may relate to relevant sociodemographic and clinical variables across the lifespan.

Brain-cognition relationships in late-life depression: a systematic review of structural magnetic resonance imaging studies.

BACKGROUND: Most patients with late-life depression (LLD) have cognitive impairment, and at least one-third meet diagnostic criteria for mild cognitive impairment (MCI), a prodrome to Alzheimer's dementia (AD) and other neurodegenerative diseases. However, the mechanisms linking LLD and MCI, and brain alterations underlying impaired cognition in LLD and LLD + MCI remain poorly understood. METHODS: To address this knowledge gap, we conducted a systematic review of studies of brain-cognition relationships in LLD or LLD + MCI to identify circuits underlying impaired cognition in LLD or LLD + MCI. We searched MEDLINE, PsycINFO, EMBASE, and Web of Science databases from inception through February 13, 2023. We included studies that assessed cognition in patients with LLD or LLD + MCI and acquired: (1) T1-weighted imaging (T1) measuring gray matter volumes or thickness; or (2) diffusion-weighted imaging (DWI) assessing white matter integrity. Due to the heterogeneity in studies, we only conducted a descriptive synthesis. RESULTS: Our search identified 51 articles, resulting in 33 T1 studies, 17 DWI studies, and 1 study analyzing both T1 and DWI. Despite limitations, reviewed studies suggest that lower thickness or volume in the frontal and temporal regions and widespread lower white matter integrity are associated with impaired cognition in LLD. Lower white matter integrity in the posterior cingulate region (precuneus and corpus callosum sub-regions) was more associated with impairment executive function and processing speed than with memory. CONCLUSION: Future studies should analyze larger samples of participants with various degrees of cognitive impairment and go beyond univariate statistical models to assess reliable brain-cognition relationships in LLD.

Spatial cognition is associated with levels of phosphorylated-tau and ß-amyloid in clinically normal older adults.

Spatial cognition is associated with Alzheimer's disease (AD) biomarkers in the symptomatic stages of the disease. We investigated whether cerebrospinal fluid (CSF) biomarkers (phosphorylated-tau [p-tau] and ß-amyloid) are associated with poorer spatial cognition in clinically normal older adults. Participants were 1875 clinically normal adults (age 67.8 [8.5] years) from the European Prevention of Alzheimer's Dementia Consortium. Mixed effect models assessed the cross-sectional association between p-tau181, ß-amyloid1-42 (Aß1-42) and p-tau181/Aß1-42 ratio and spatial cognition measured using semi-automated Supermarket Task and the 4 Mountains Task. Levels of p-tau181, Aß1-42, and p-tau181/Aß1-42 ratio were significantly associated with spatial cognition scores on both tasks. The p-tau181/Aß1-42 ratio showed the largest effect sizes (ß = -0.04/0.05, p < 0.001). Lower entorhinal cortical volume was associated with poorer outcomes on both tasks (ß = 0.06, p < 0.002) and accounted for 18%-22% of the direct association between p-tau181 and spatial cognition scores. In conclusion, degeneration of the entorhinal cortex mediates a significant proportion of the association between p-tau181 and spatial assessments in cognitively normal adults. Future studies should focus on increasing the sensitivity of digital spatial assessments.

Brain-Cognition Associations in Older Patients With Remitted Major Depressive Disorder or Mild Cognitive Impairment: A Multivariate Analysis of Gray and White Matter Integrity.

BACKGROUND: Almost half of older patients with major depressive disorder (MDD) present with cognitive impairment, and one-third meet diagnostic criteria for mild cognitive impairment (MCI). However, mechanisms linking MDD and MCI remain unclear. We investigated multivariate associations between brain structural alterations and cognition in 3 groups of older patients at risk for dementia, remitted MDD (rMDD), MCI, and rMDD+MCI, as well as cognitively healthy nondepressed control participants. METHODS: We analyzed magnetic resonance imaging data and cognitive domain scores in participants from the PACt-MD (Prevention of Alzheimer's Disease With Cognitive Remediation Plus Transcranial Direct Current Stimulation in Mild Cognitive Impairment and Depression) study. Following quality control, we measured cortical thickness and subcortical volumes of selected regions from 283 T1-weighted scans and fractional anisotropy of white matter tracts from 226 diffusion-weighted scans. We assessed brain-cognition associations using partial least squares regressions in the whole sample and in each subgroup. RESULTS: In the entire sample, atrophy in the medial temporal lobe and subregions of the motor and prefrontal cortex was associated with deficits in verbal and visuospatial memory, language skills, and, to a lesser extent, processing speed (p < .0001; multivariate r = 0.30, 0.34, 0.26, and 0.18, respectively). Widespread reduced white matter integrity was associated with deficits in executive functioning, working memory, and processing speed (p = .008; multivariate r = 0.21, 0.26, 0.35, respectively). Overall, associations remained significant in the MCI and rMDD+MCI groups, but not the rMDD or healthy control groups. CONCLUSIONS: We confirm findings of brain-cognition associations previously reported in MCI and extend them to rMDD+MCI, but similar associations in rMDD are not supported. Early-onset and treated MDD might not contribute to structural alterations associated with cognitive impairment.

Case-control virtual histology elucidates cell types associated with cortical thickness differences in Alzheimer's disease.

Many neuropsychiatric disorders are characterised by altered cortical thickness, but the cell types underlying these changes remain largely unknown. Virtual histology (VH) approaches map regional patterns of gene expression with regional patterns of MRI-derived phenotypes, such as cortical thickness, to identify cell types associated with case-control differences in those MRI measures. However, this method does not incorporate valuable information of case-control differences in cell type abundance. We developed a novel method, termed case-control virtual histology (CCVH), and applied it to Alzheimer's disease (AD) and dementia cohorts. Leveraging a multi-region gene expression dataset of AD cases (n = 40) and controls (n = 20), we quantified AD case-control differential expression of cell type-specific markers across 13 brain regions. We then correlated these expression effects with MRI-derived AD case-control cortical thickness differences across the same regions. Cell types with spatially concordant AD-related effects were identified through resampling marker correlation coefficients. Among regions thinner in AD, gene expression patterns identified by CCVH suggested fewer excitatory and inhibitory neurons, and greater proportions of astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, and endothelial cells in AD cases vs. controls. In contrast, original VH identified expression patterns suggesting that excitatory but not inhibitory neuron abundance was associated with thinner cortex in AD, despite the fact that both types of neurons are known to be lost in the disorder. Compared to original VH, cell types identified through CCVH are more likely to directly underlie cortical thickness differences in AD. Sensitivity analyses suggest our results are largely robust to specific analysis choices, like numbers of cell type-specific marker genes used and background gene sets used to construct null models. As more multi-region brain expression datasets become available, CCVH will be useful for identifying the cellular correlates of cortical thickness across neuropsychiatric illnesses.

Vestibular contribution to path integration deficits in 'at-genetic-risk' for Alzheimer's disease.

Path integration changes may precede a clinical presentation of Alzheimer's disease by several years. Studies to date have focused on how spatial cell changes affect path integration in preclinical AD. However, vestibular input is also critical for intact path integration. Here, we developed the vestibular rotation task that requires individuals to manually point an iPad device in the direction of their starting point following rotational movement, without any visual cues. Vestibular features were derived from the sensor data using feature selection. Machine learning models illustrate that the vestibular features accurately classified Apolipoprotein E ε3ε4 carriers and ε3ε3 carrier controls (mean age 62.7 years), with 65% to 79% accuracy depending on task trial. All machine learning models produced a similar classification accuracy. Our results demonstrate the cross-sectional role of the vestibular system in Alzheimer's disease risk carriers. Future investigations should examine if vestibular functions explain individual phenotypic heterogeneity in path integration among Alzheimer's disease risk carriers.

Connectivity between default mode and frontoparietal networks mediates the association between global amyloid-ß and episodic memory.

Βeta-amyloid (Aß) is a neurotoxic protein that deposits early in the pathogenesis of preclinical Alzheimer's disease. We aimed to identify network connectivity that may alter the negative effect of Aß on cognition. Following assessment of memory performance, resting-state fMRI, and mean cortical PET-Aß, a total of 364 older adults (286 with clinical dementia rating [CDR-0], 59 with CDR-0.5 and 19 with CDR-1, mean age: 74.0 ± 6.4 years) from the OASIS-3 sample were included in the analysis. Across all participants, a partial least squares regression showed that lower connectivity between posterior medial default mode and frontoparietal networks, higher within-default mode, and higher visual-motor connectivity predict better episodic memory. These connectivities partially mediate the effect of Aß on episodic memory. These results suggest that connectivity strength between the precuneus cortex and the superior frontal gyri may alter the negative effect of Aß on episodic memory. In contrast, education was associated with different functional connectivity patterns. In conclusion, functional characteristics of specific brain networks may help identify amyloid-positive individuals with a higher likelihood of memory decline, with implications for AD clinical trials.

Symptom dimensions of major depression in a large community-based cohort.

BACKGROUND: Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community. METHODS: This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or 'symptom dimensions' via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records. RESULTS: Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations. CONCLUSIONS: An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

Unravelling the relationship between amyloid accumulation and brain network function in normal aging and very mild cognitive decline: a longitudinal analysis.

Pathological changes in the brain begin accumulating decades before the appearance of cognitive symptoms in Alzheimer's disease. The deposition of amyloid beta proteins and other neurotoxic changes occur, leading to disruption in functional connections between brain networks. Discrete characterization of the changes that take place in preclinical Alzheimer's disease has the potential to help treatment development by targeting the neuropathological mechanisms to prevent cognitive decline and dementia from occurring entirely. Previous research has focused on the cross-sectional differences in the brains of patients with mild cognitive impairment or Alzheimer's disease and healthy controls or has concentrated on the stages immediately preceding cognitive symptoms. The present study emphasizes the early preclinical phases of neurodegeneration. We use a longitudinal approach to examine the brain changes that take place during the early stages of cognitive decline in the Open Access Series of Imaging Studies-3 data set. Among 1098 participants, 274 passed the inclusion criteria (i.e. had at least two cognitive assessments and two amyloid scans). Over 90% of participants were healthy at baseline. Over 8-10 years, some participants progressed to very mild cognitive impairment (n = 48), while others stayed healthy (n = 226). Participants with cognitive decline show faster amyloid accumulation in the lateral temporal, motor and parts of the lateral prefrontal cortex. These changes in amyloid levels were linked to longitudinal increases in the functional connectivity of select networks, including default mode, frontoparietal and motor components. Our findings advance the understanding of amyloid staging and the corresponding changes in functional organization of large-scale brain networks during the progression of early preclinical Alzheimer's disease.

Morphometric similarity deviations in stimulant use disorder point towards abnormal brain ageing.

Chronic drug use negatively impacts ageing, resulting in diminished health and quality of life. However, little is known about biomarkers of abnormal ageing in stimulant drug users. Using morphometric similarity network mapping, a novel approach to structural connectomics, we first mapped cross-sectional morphometric similarity trajectories of ageing in the publicly available Rockland Sample (20-80 years of age, n = 665). We then compared morphometric similarity and neuropsychological function between non-treatment-seeking, actively using patients with stimulant use disorder (n = 183, mean age: 35.6 years) and healthy control participants (n = 148, mean age: 36.0 years). The significantly altered mean regional morphometric similarity was found in 43 cortical regions including the inferior and orbital frontal gyri, pre/postcentral gyri and anterior temporal, superior parietal and occipital areas. Deviations from normative morphometric similarity trajectories in patients with stimulant use disorder suggested abnormal brain ageing. Furthermore, deficits in paired associates learning were consistent with neuropathology associated with both ageing and stimulant use disorder. Morphometric similarity mapping provides a promising biomarker for ageing in health and disease and may complement existing neuropsychological markers of age-related cognitive decline. Neuropathological ageing mechanisms in stimulant use disorder warrant further investigation to develop more age-appropriate treatments for older people addicted to stimulant drugs.

Multiscale neural signatures of major depressive, anxiety, and stress-related disorders.

The extent of shared and distinct neural mechanisms underlying major depressive disorder (MDD), anxiety, and stress-related disorders is still unclear. We compared the neural signatures of these disorders in 5,405 UK Biobank patients and 21,727 healthy controls. We found the greatest case­control differences in resting-state functional connectivity and cortical thickness in MDD, followed by anxiety and stress-related disorders. Neural signatures for MDD and anxiety disorders were highly concordant, whereas stress-related disorders showed a distinct pattern. Controlling for cross-disorder genetic risk somewhat decreased the similarity between functional neural signatures of stress-related disorders and both MDD and anxiety disorders. Among cases and healthy controls, reduced within-network and increased between-network frontoparietal and default mode connectivity were associated with poorer cognitive performance (processing speed, attention, associative learning, and fluid intelligence). These results provide evidence for distinct neural circuit function impairments in MDD and anxiety disorders compared to stress disorders, yet cognitive impairment appears unrelated to diagnosis and varies with circuit function.

Alternative labeling tool: a minimal algorithm for denoising single-subject resting-state fMRI data with ICA-MELODIC.

Subject-level independent component analysis (ICA) is a well-established and widely used approach in denoising of resting-state functional magnetic resonance imaging (fMRI) data. However, approaches such as ICA-FIX and ICA-AROMA require advanced setups and can be computationally intensive. Here, we aim to introduce a user-friendly, computationally lightweight toolbox for labeling independent signal and noise components, termed Alternative Labeling Tool (ALT). ALT uses two features that require manual tuning: proportion of an independent component's spatial map located inside gray matter and positive skew of the power spectrum. ALT is tightly integrated with the commonly used FMRIB's statistical library (FSL). Using the Open Access Series of Imaging Studies (OASIS-3) ageing dataset (n = 275), we found that ALT shows a high degree of inter-rater agreement with manual labeling (over 86% of true positives for both signal and noise components on average). In conclusion, ALT can be extended to small and large-scale datasets when the use of more complex tools such as ICA-FIX is not possible. ALT will thus allow for more widespread adoption of ICA-based denoising of resting-state fMRI data.

Prefrontal Cortex Activation and Stopping Performance Underlie the Beneficial Effects of Atomoxetine on Response Inhibition in Healthy Volunteers and Those With Cocaine Use Disorder.

BACKGROUND: Impaired response inhibition in individuals with cocaine use disorder (CUD) is hypothesized to depend on deficient noradrenergic signaling in corticostriatal networks. Remediation of noradrenergic neurotransmission with selective norepinephrine reuptake inhibitors such as atomoxetine may therefore have clinical utility to improve response inhibitory control in CUD. METHODS: We carried out a randomized, double-blind, placebo-controlled, crossover study with 26 participants with CUD and 28 control volunteers investigating the neural substrates of stop-signal inhibitory control. The effects of a single dose of atomoxetine (40 mg) were compared with placebo on stop-signal reaction time performance and functional network connectivity using dynamic causal modeling. RESULTS: We found that atomoxetine speeded Go response times in both control participants and those with CUD. Improvements in stopping efficiency on atomoxetine were conditional on baseline (placebo) stopping performance and were directly associated with increased inferior frontal gyrus activation. Further, stopping performance, task-based brain activation, and effective connectivity were similar in the 2 groups. Dynamic causal modeling of effective connectivity of multiple prefrontal and basal ganglia regions replicated and extended previous models of network function underlying inhibitory control to CUD and control volunteers and showed subtle effects of atomoxetine on prefrontal-basal ganglia interactions. CONCLUSIONS: These findings demonstrate that atomoxetine improves response inhibition in a baseline-dependent manner in control participants and in those with CUD. Our results emphasize inferior frontal cortex function as a future treatment target owing to its key role in improving response inhibition in CUD.