Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis

BACKGROUND

Individuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD.

METHODS

Neuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global 'variability score'. Pairwise correlational distance was calculated as 1 - the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability.

RESULTS

Group comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01).

CONCLUSIONS

Diagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.

Digital Disconnection: A Qualitative Study of Youth and Young Adult Perspectives on Cyberbullying and the Adoption of Auto-Detection or Software Tools

PURPOSE

The purpose of this study was to understand the needs of youth and young adults, current gaps around safeguarding social media, and factors affecting adoption of data-driven auto-detection or software tools.

METHODS

This qualitative study is the first step of a larger initiative that aims to use participatory action research and co-design principles to develop a digital tool that targets cyberbullying. Youth and young adults aged 16-21 years were recruited to participate in semistructured focus groups between March 2020 and November 2021. Thematic analysis was used to develop themes, with a member-checking process to validate the findings.

RESULTS

Six focus groups were completed with 39 participants and five themes were generated from the analysis. Participants described the mental health impacts of cyberbullying on young people, the stigma associated with it, and the need for more mental health resources. They felt that additional efforts are needed to improve the school environment, school-based interventions, and training protocols to ensure that youth feel safe reporting cyberbullying. Most participants were open to using a digital solution but raised concerns around the trustworthiness of artificial intelligence and wanted it to be co-designed with young people, integrated across platforms, informed by data-driven decisions, and transparent with users.

DISCUSSION

Youth and young adults are accepting of a low-risk digital cyberbullying solution as current interventions are not meeting their needs.

Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning

BACKGROUND

Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.

METHOD

One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.

RESULTS

Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.

CONCLUSIONS

Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Bayesian Optimization of Neurostimulation (BOONStim)

BACKGROUND

Transcranial magnetic stimulation (TMS) treatment response is influenced by individual variability in brain structure and function. Sophisticated, user-friendly approaches, incorporating both established functional magnetic resonance imaging (fMRI) and TMS simulation tools, to identify TMS targets are needed.

OBJECTIVE

The current study presents the development and validation of the Bayesian Optimization of Neuro-Stimulation (BOONStim) pipeline.

METHODS

BOONStim uses Bayesian optimization for individualized TMS targeting, automating interoperability between surface-based fMRI analytic tools and TMS electric field modeling. Bayesian optimization performance was evaluated in a sample dataset (N=10) using standard circular and functional connectivity-defined targets, and compared to grid optimization.

RESULTS

Bayesian optimization converged to similar levels of total electric field stimulation across targets in under 30 iterations, converging within a 5% error of the maxima detected by grid optimization, and requiring less time.

CONCLUSIONS

BOONStim is a scalable and configurable user-friendly pipeline for individualized TMS targeting with quick turnaround.

Cognitive function based on theta-gamma coupling vs. clinical diagnosis in older adults with mild cognitive impairment with or without major depressive disorder

Whether individuals with mild cognitive impairment (MCI) and a history of major depressive disorder (MDD) are at a higher risk for cognitive decline than those with MCI alone is still not clear. Previous work suggests that a reduction in prefrontal cortical theta phase-gamma amplitude coupling (TGC) is an early marker of cognitive impairment. This study aimed to determine whether using a TGC cutoff is better at separating individuals with MCI or MCI with remitted MDD (MCI+rMDD) on cognitive performance than their clinical diagnosis. Our hypothesis was that global cognition would differ more between TGC-based groups than diagnostic groups. We analyzed data from 128 MCI (mean age: 71.8, SD: 7.3) and 85 MCI+rMDD (mean age: 70.9, SD: 4.7) participants. Participants completed a comprehensive neuropsychological battery; TGC was measured during the N-back task. An optimal TGC cutoff was determined during the performance of the 2-back. This TGC cutoff was used to classify participants into low vs. high-TGC groups. We then compared Cohen's d of the difference in global cognition between the high and low TGC groups to Cohen's d between the MCI and MCI+rMDD groups. We used bootstrapping to determine 95% confidence intervals for Cohen's d values using the whole sample. As hypothesized, Cohen's d for the difference in global cognition between the TGC groups was larger (0.64 [0.32, 0.88]) than between the diagnostic groups (0.10 [0.004, 0.37]) with a difference between these two Cohen's d's of 0.54 [0.10, 0.80]. Our findings suggest that TGC is a useful marker to identify individuals at high risk for cognitive decline, beyond clinical diagnosis. This could be due to TGC being a sensitive marker of prefrontal cortical dysfunction that would lead to an accelerated cognitive decline.

Effect of olanzapine exposure on relapse and brain structure in patients with major depressive disorder with psychotic features

Some data suggest that antipsychotics may adversely affect brain structure. We examined the relationship among olanzapine exposure, relapse, and changes in brain structure in patients with major depressive disorder with psychotic features. We analyzed data from the Study of the Pharmacotherapy of Psychotic Depression II trial (STOP-PD II), a randomized, placebo-controlled trial in patients with psychotic depression who attained remission on sertraline and olanzapine and were randomized to continue sertraline plus olanzapine or placebo for 36 weeks. Olanzapine steady state concentration (SSC) were calculated based on sparsely-sampled levels. Rates of relapse and changes in brain structure were assessed as outcomes. There were significant associations between dosage and relapse rates (N = 118; HR = 0.94, 95% CI [0.897, 0.977], p = 0.002) or changes in left cortical thickness (N = 44; B = -2.0 × 10-3, 95% CI [-3.1 × 10-3, -9.6 × 10-4], p < 0.001) and between SSC and changes in left cortical thickness (N = 44; B = -8.7 × 10-4, 95% CI [-1.4 × 10-3, -3.6 × 10-4], p = 0.001). Similar results were found for the right cortex. These associations were no longer significant when the analysis was restricted to participants treated with olanzapine. Our findings suggest that, within its therapeutic range, the effect of olanzapine on relapse or cortical thickness does not depend on its dosage or SSC. Further research is needed on the effect of olanzapine and other antipsychotics on mood symptoms and brain structure.

SAN: mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites

In neuroimaging studies, combining data collected from multiple study sites or scanners is becoming common to increase the reproducibility of scientific discoveries. At the same time, unwanted variations arise by using different scanners (inter-scanner biases), which need to be corrected before downstream analyses to facilitate replicable research and prevent spurious findings. While statistical harmonization methods such as ComBat have become popular in mitigating inter-scanner biases in neuroimaging, recent methodological advances have shown that harmonizing heterogeneous covariances results in higher data quality. In vertex-level cortical thickness data, heterogeneity in spatial autocorrelation is a critical factor that affects covariance heterogeneity. Our work proposes a new statistical harmonization method called SAN (Spatial Autocorrelation Normalization) that preserves homogeneous covariance vertex-level cortical thickness data across different scanners. We use an explicit Gaussian process to characterize scanner-invariant and scanner-specific variations to reconstruct spatially homogeneous data across scanners. SAN is computationally feasible, and it easily allows the integration of existing harmonization methods. We demonstrate the utility of the proposed method using cortical thickness data from the Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) study. SAN is publicly available as an R package.

Cognition and Educational Achievement in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data

BACKGROUND

Both cognition and educational achievement in youths are linked to psychosis risk. One major aim of the Toronto Adolescent and Youth (TAY) Cohort Study is to characterize how cognitive and educational achievement trajectories inform the course of psychosis spectrum symptoms (PSSs), functioning, and suicidality. Here, we describe the protocol for the cognitive and educational data and early baseline data.

METHODS

The cognitive assessment design is consistent with youth population cohort studies, including the NIH Toolbox, Rey Auditory Verbal Learning Test, Wechsler Matrix Reasoning Task, and Little Man Task. Participants complete an educational achievement questionnaire, and report cards are requested. Completion rates, descriptive data, and differences across PSS status are reported for the first participants (N = 417) ages 11 to 24 years, who were recruited between May 4, 2021, and February 2, 2023.

RESULTS

Nearly 84% of the sample completed cognitive testing, and 88.2% completed the educational questionnaire, whereas report cards were collected for only 40.3%. Modifications to workflows were implemented to improve data collection. Participants who met criteria for PSSs demonstrated lower performance than those who did not on numerous key cognitive indices (p < .05) and also had more academic/educational problems.

CONCLUSIONS

Following youths longitudinally enabled trajectory mapping and prediction based on cognitive and educational performance in relation to PSSs in treatment-seeking youths. Youths with PSSs had lower cognitive performance and worse educational outcomes than youths without PSSs. Results show the feasibility of collecting data on cognitive and educational outcomes in a cohort of youths seeking treatment related to mental illness and substance use.

The Toronto Adolescent and Youth Cohort Study: Study Design and Early Data Related to Psychosis Spectrum Symptoms, Functioning, and Suicidality

BACKGROUND

Psychosis spectrum symptoms (PSSs) occur in a sizable percentage of youth and are associated with poorer cognitive performance, poorer functioning, and suicidality (i.e., suicidal thoughts and behaviors). PSSs may occur more frequently in youths already experiencing another mental illness, but the antecedents are not well known. The Toronto Adolescent and Youth (TAY) Cohort Study aims to characterize developmental trajectories in youths with mental illness and understand associations with PSSs, functioning, and suicidality.

METHODS

The TAY Cohort Study is a longitudinal cohort study that aims to assess 1500 youths (age 11-24 years) presenting to tertiary care. In this article, we describe the extensive diagnostic and clinical characterization of psychopathology, substance use, functioning, suicidality, and health service utilization in these youths, with follow-up every 6 months over 5 years, including early baseline data.

RESULTS

A total of 417 participants were enrolled between May 4, 2021, and February 2, 2023. Participants met diagnostic criteria for an average of 3.5 psychiatric diagnoses, most frequently anxiety and depressive disorders. Forty-nine percent of participants met a pre-established threshold for PSSs and exhibited higher rates of functional impairment, internalizing and externalizing symptoms, and suicidality than participants without PSSs.

CONCLUSIONS

Initial findings from the TAY Cohort Study demonstrate the feasibility of extensive clinical phenotyping in youths who are seeking help for mental health problems. PSS prevalence is much higher than in community-based studies. Our early data support the critical need to better understand longitudinal trajectories of clinical youth cohorts in relation to psychosis risk, functioning, and suicidality.

Neuroimaging and Biosample Collection in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data

BACKGROUND

The Toronto Adolescent and Youth (TAY) Cohort Study will characterize the neurobiological trajectories of psychosis spectrum symptoms, functioning, and suicidality (i.e., suicidal thoughts and behaviors) in youth seeking mental health care. Here, we present the neuroimaging and biosample component of the protocol. We also present feasibility and quality control metrics for the baseline sample collected thus far.

METHODS

The current study includes youths (ages 11-24 years) who were referred to child and youth mental health services within a large tertiary care center in Toronto, Ontario, Canada, with target recruitment of 1500 participants. Participants were offered the opportunity to provide any or all of the following: 1) 1-hour magnetic resonance imaging (MRI) scan (electroencephalography if ineligible for or declined MRI), 2) blood sample for genomic and proteomic data (or saliva if blood collection was declined or not feasible) and urine sample, and 3) heart rate recording to assess respiratory sinus arrhythmia.

RESULTS

Of the first 417 participants who consented to participate between May 4, 2021, and February 2, 2023, 412 agreed to participate in the imaging and biosample protocol. Of these, 334 completed imaging, 341 provided a biosample, 338 completed respiratory sinus arrhythmia, and 316 completed all 3. Following quality control, data usability was high (MRI: T1-weighted 99%, diffusion-weighted imaging 99%, arterial spin labeling 90%, resting-state functional MRI 95%, task functional MRI 90%; electroencephalography: 83%; respiratory sinus arrhythmia: 99%).

CONCLUSIONS

The high consent rates, good completion rates, and high data usability reported here demonstrate the feasibility of collecting and using brain imaging and biosamples in a large clinical cohort of youths seeking mental health care.

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.

An SMS text messaging intervention to improve clinical engagement in early psychosis: A pilot randomized-controlled trial

Disengagement of youth with psychosis from Early Psychosis Intervention (EPI) services continues to be a significant barrier to recovery, with approximately one-third prematurely discontinuing treatment despite the ongoing need. The current pilot trial sought to evaluate the preliminary efficacy and feasibility of a weekly short message service (SMS) intervention to improve engagement in EPI services. This was a longitudinal single-blinded randomized control trial in which participants were assigned to receive either an active or sham SMS intervention over nine months. Sixty-one participants with early psychosis between the ages of 16 and 29 were enrolled, randomized, and received at least part of the intervention. Primary outcomes consisted of participant clinic attendance rates over the course of the intervention and clinician-rated engagement. Secondary measures included patient-rated therapeutic rapport, attitude toward medication, psychopathology, cognition, functioning, and intervention feedback from participants. Compared to the sham group, participants receiving the active intervention did not show improved appointment attendance rates; however, did exhibit some improvements in aspects of engagement, including improved clinician-rated availability, attitude toward medication, positive symptoms, avolition-apathy and social functioning. Thus, contrary to our hypotheses, digitally augmented care did not result in enhanced engagement in EPI services, as measured by clinic attendance, although with some indication that it may contribute to improved attitude toward medication and, potentially, medication adherence. Weekly SMS text messaging appeared to result in a pattern of engagement whereby individuals who were improving clinically attended appointments less often, possibly due to inadvertent use of the intervention to check in with clinicians. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04379349).

Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.

Brain metabolite levels in remitted psychotic depression with consideration of effects of antipsychotic medication

BACKGROUND

The neurobiology of psychotic depression is not well understood and can be confounded by antipsychotics. Magnetic resonance spectroscopy (MRS) is an ideal tool to measure brain metabolites non-invasively. We cross-sectionally assessed brain metabolites in patients with remitted psychotic depression and controls. We also longitudinally assessed the effects of olanzapine versus placebo on brain metabolites.

METHODS

Following remission, patients with psychotic depression were randomized to continue sertraline + olanzapine (n = 15) or switched to sertraline + placebo (n = 18), at which point they completed an MRS scan. Patients completed a second scan either 36 weeks later, relapse, or discontinuation. Where water-scaled metabolite levels were obtained and a Point-RESolved Spectroscopy sequence was utilized, choline, myo-inositol, glutamate + glutamine (Glx), N-acetylaspartate, and creatine were measured in the left dorsolateral prefrontal cortex (L-DLPFC) and dorsal anterior cingulate cortex (dACC). An ANCOVA was used to compare metabolites between patients (n = 40) and controls (n = 46). A linear mixed-model was used to compare olanzapine versus placebo groups.

RESULTS

Cross-sectionally, patients (compared to controls) had higher myo-inositol (standardized mean difference [SMD] = 0.84; 95%CI = 0.25-1.44; p = 0.005) in the dACC but not different Glx, choline, N-acetylaspartate, and creatine. Longitudinally, patients randomized to placebo (compared to olanzapine) showed a significantly greater change with a reduction of creatine (SMD = 1.51; 95%CI = 0.71-2.31; p = 0.0002) in the dACC but not glutamate + glutamine, choline, myo-inositol, and N-acetylaspartate.

CONCLUSIONS

Patients with remitted psychotic depression have higher myo-inositol than controls. Olanzapine may maintain creatine levels. Future studies are needed to further disentangle the mechanisms of action of olanzapine.

Experiences of Sexual and Reproductive Health Care Access for Women and Nonbinary People With Early Psychosis: Towards an Integrated Perspective of Service Users and Clinicians

OBJECTIVE

Individuals with psychosis are at elevated risk of adverse sexual and reproductive health (SRH) outcomes, and not receiving adequate SRH care. SRH is important for youth, yet little is known about SRH care access and experiences among those with early psychosis. This study explored SRH care experiences among women and nonbinary individuals with early psychosis.

METHOD

We conducted semistructured qualitative interviews with 19 service users (cisgender and transgender women, nonbinary individuals) receiving care in 2 early psychosis programs in Ontario, Canada. We also conducted semistructured interviews and focus groups with 36 clinicians providing SRH or mental health care to this population. Participants were asked about SRH care access/provision experiences and the interplay with psychosis. Using a social interactionist orientation, a thematic analysis described and explained service user and clinician perspectives regarding SRH care.

RESULTS

Amongst both service users and clinician groups, common themes developed: (a) diversity of settings: SRH services are accessed in a large range of spaces across the health care system, (b) barriers in nonpsychiatric SRH care settings: psychosis impacts the ability to engage with existing SRH services, (c) invisibility of SRH in psychiatric settings: SRH is rarely addressed in psychiatric care, (d) variability of informal SRH-related conversations and supports, and cutting across all of the above themes, (e) intersecting social and cultural factors impacted SRH services access.

CONCLUSIONS

SRH is important for health and wellbeing; improvements are urgently needed across the healthcare system and within early psychosis programs to meet this population's multifaceted SRH needs.

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.

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.

Neuroimaging features of depression-frailty phenotype in older adults: a pilot study

OBJECTIVE

Frailty and late-life depression (LLD) often coexist and share several structural brain changes. We aimed to study the joint effect LLD and frailty have on brain structure.

DESIGN

Cross-sectional study.

SETTING

Academic Health Center.

PARTICIPANTS

Thirty-one participants (14 LLD+Frail and 17 Never-depressed+Robust).

MEASUREMENT

LLD was diagnosed by a geriatric psychiatrist according to the Diagnostic and Statistical Manual of Mental Disorders 5th edition for single episode or recurrent major depressive disorder without psychotic features. Frailty was assessed using the FRAIL scale (0-5), classifying subjects as robust (0), prefrail (1-2), and frail (3-5). Participants underwent T1-weighted magnetic resonance imaging in which covariance analysis of subcortical volumes and vertex-wise analysis of cortical thickness values were performed to access changes in grey matter. Participants also underwent diffusion tensor imaging in which tract-based spatial statistics was used with voxel-wise statistical analysis on fractional anisotropy and mean diffusion values to assess changes in white matter (WM).

RESULTS

We found a significant difference in mean diffusion values (48,225 voxels; peak voxel: pFWER=0.005, MINI coord. (X,Y,Z) = -26,-11,27) between the LLD-Frail group and comparison group. The corresponding effect size (f=0.808) was large.

CONCLUSION

We showed the LLD+Frailty group is associated with significant microstructural changes within WM tracts compared to Never-depressed+Robust individuals. Our findings indicate the possibility of a heightened neuroinflammatory burden as a potential mechanism underlying the co-occurrence of both conditions and the possibility of a depression-frailty phenotype in older adults.

Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls

BACKGROUND AND HYPOTHESIS

Neurocognitive and social cognitive abilities are important contributors to functional outcomes in schizophrenia spectrum disorders (SSDs). An unanswered question of considerable interest is whether neurocognitive and social cognitive deficits arise from overlapping or distinct white matter impairment(s).

STUDY DESIGN

We sought to fill this gap, by harnessing a large sample of individuals from the multi-center Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) dataset, unique in its collection of advanced diffusion imaging and an extensive battery of cognitive assessments. We applied canonical correlation analysis to estimates of white matter microstructure, and cognitive performance, across people with and without an SSD.

STUDY RESULTS

Our results established that white matter circuitry is dimensionally and strongly related to both neurocognition and social cognition, and that microstructure of the uncinate fasciculus and the rostral body of the corpus callosum may assume a "privileged role" subserving both. Further, we found that participant-wise estimates of white matter microstructure, weighted by cognitive performance, were largely consistent with participants' categorical diagnosis, and predictive of (cross-sectional) functional outcomes.

CONCLUSIONS

The demonstrated strength of the relationship between white matter circuitry and neurocognition and social cognition underscores the potential for using relationships among these variables to identify biomarkers of functioning, with potential prognostic and therapeutic implications.

Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after personalized intrinsic network topography

BACKGROUND

Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls (HC) using individualized connectivity profiles.

METHODS

We utilized resting-state and anatomical MRI data from n = 406 participants (n = 203 SSD, n = 203 HC) from four cohorts. Functional timeseries were extracted from previously defined intrinsic network subregions of the striatum, thalamus, and cerebellum as well as 80 cortical regions of interest, representing six intrinsic networks using (1) volume-based approaches, (2) a surface-based group atlas approaches, and (3) Personalized Intrinsic Network Topography (PINT).

RESULTS

The correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs. surface 0.27-1.00, all p < 10-6 ) and further increased after PINT (Cohen's D surface vs. PINT 0.18-0.96, all p < 10-4 ). In SSD versus HC comparisons, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 404, surface: 570, PINT: 628, FDR corrected).

CONCLUSION

Surface-based and individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models.

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.

Spatial-extent inference for testing variance components in reliability and heritability studies

Clusterwise inference is a popular approach in neuroimaging to increase sensitivity, but most existing methods are currently restricted to the General Linear Model (GLM) for testing mean parameters. Statistical methods for testing variance components, which are critical in neuroimaging studies that involve estimation of narrow-sense heritability or test-retest reliability, are underdeveloped due to methodological and computational challenges, which would potentially lead to low power. We propose a fast and powerful test for variance components called CLEAN-V (CLEAN for testing Variance components). CLEAN-V models the global spatial dependence structure of imaging data and computes a locally powerful variance component test statistic by data-adaptively pooling neighborhood information. Correction for multiple comparisons is achieved by permutations to control family-wise error rate (FWER). Through analysis of task-fMRI data from the Human Connectome Project across five tasks and comprehensive data-driven simulations, we show that CLEAN-V outperforms existing methods in detecting test-retest reliability and narrow-sense heritability with significantly improved power, with the detected areas aligning with activation maps. The computational efficiency of CLEAN-V also speaks of its practical utility, and it is available as an R package.

Care Pathways and Initial Engagement in Early Psychosis Intervention Services Among Youths and Young Adults

Importance

Broad efforts to improve access to early psychosis intervention (EPI) services may not address health disparities in pathways to care and initial engagement in treatment.

Objective

To understand factors associated with referral from acute hospital-based settings and initial engagement in EPI services.

Design, Setting, and Participants

This retrospective cohort study used electronic medical record data from all patients aged 16 to 29 years who were referred to a large EPI program between January 2018 and December 2019. Statistical analysis was performed from March 2022 to February 2023.

Exposures

Patients self-reported demographic information in a structured questionnaire. The main outcome for the first research question (referral source) was an exposure for the second research question (initial attendance).

Main Outcomes and Measures

Rate of EPI referral from acute pathways compared with other referral sources, and rate of attendance at the consultation appointment.

Results

The final study population included 999 unique patient referrals. At referral, patients were a mean (SD) age of 22.5 (3.5) years; 654 (65.5%) identified as male, 323 (32.3%) female, and 22 (2.2%) transgender, 2-spirit, nonbinary, do not know, or prefer not to answer; 199 (19.9%) identified as Asian, 176 (17.6%) Black, 384 (38.4%) White, and 167 (16.7%) other racial or ethnic groups, do not know, or prefer not to answer. Participants more likely to be referred to EPI services from inpatient units included those who were older (relative risk ratio [RRR], 1.10; 95% CI, 1.05-1.15) and those who identified as Black (RRR, 2.11; 95% CI, 1.38-3.22) or belonging to other minoritized racial or ethnic groups (RRR, 1.79; 95% CI, 1.14-2.79) compared with White participants. Older patients (RRR, 1.16; 95% CI, 1.11-1.22) and those who identified as Black (RRR, 1.67; 95% CI, 1.04-2.70) or belonging to other minoritized racial or ethnic groups (RRR, 2.11; 95% CI, 1.33-3.36) were more likely to be referred from the emergency department (ED) compared with White participants, whereas participants who identified as female (RRR, 0.51 95% CI, 0.34-.74) had a lower risk of ED referral compared with male participants. Being older (odds ratio [OR], 0.95; 95% CI, 0.90-1.00) and referred from the ED (OR, 0.40; 95% CI, 0.27-0.58) were associated with decreased odds of attendance at the consultation appointment.

Conclusions and relevance

In this cohort study of patients referred to EPI services, disparities existed in referral pathways and initial engagement in services. Improving entry into EPI services may help facilitate a key step on the path to recovery among youths and young adults with psychosis.

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.

RELIEF: A structured multivariate approach for removal of latent inter-scanner effects

Combining data collected from multiple study sites is becoming common and is advantageous to researchers to increase the generalizability and replicability of scientific discoveries. However, at the same time, unwanted inter-scanner biases are commonly observed across neuroimaging data collected from multiple study sites or scanners, rendering difficulties in integrating such data to obtain reliable findings. While several methods for handling such unwanted variations have been proposed, most of them use univariate approaches that could be too simple to capture all sources of scanner-specific variations. To address these challenges, we propose a novel multivariate harmonization method called RELIEF (REmoval of Latent Inter-scanner Effects through Factorization) for estimating and removing both explicit and latent scanner effects. Our method is the first approach to introduce the simultaneous dimension reduction and factorization of interlinked matrices to a data harmonization context, which provides a new direction in methodological research for correcting inter-scanner biases. Analyzing diffusion tensor imaging (DTI) data from the Social Processes Initiative in Neurobiology of the Schizophrenia (SPINS) study and conducting extensive simulation studies, we show that RELIEF outperforms existing harmonization methods in mitigating inter-scanner biases and retaining biological associations of interest to increase statistical power. RELIEF is publicly available as an R package.

Effects of antipsychotic medication on functional connectivity in major depressive disorder with psychotic features

The effect of antipsychotic medication on resting state functional connectivity in major depressive disorder (MDD) is currently unknown. To address this gap, we examined patients with MDD with psychotic features (MDDPsy) participating in the Study of the Pharmacotherapy of Psychotic Depression II. All participants were treated with sertraline plus olanzapine and were subsequently randomized to continue sertraline plus olanzapine or be switched to sertraline plus placebo. Participants completed an MRI at randomization and at study endpoint (study completion at Week 36, relapse, or early termination). The primary outcome was change in functional connectivity measured within and between specified networks and the rest of the brain. The secondary outcome was change in network topology measured by graph metrics. Eighty-eight participants completed a baseline scan; 73 completed a follow-up scan, of which 58 were usable for analyses. There was a significant treatment X time interaction for functional connectivity between the secondary visual network and rest of the brain (t = -3.684; p = 0.0004; pFDR = 0.0111). There was no significant treatment X time interaction for graph metrics. Overall, functional connectivity between the secondary visual network and the rest of the brain did not change in participants who stayed on olanzapine but decreased in those switched to placebo. There were no differences in changes in network topology measures when patients stayed on olanzapine or switched to placebo. This suggests that olanzapine may stabilize functional connectivity, particularly between the secondary visual network and the rest of the brain.

The relationship of white matter microstructure with psychomotor disturbance and relapse in remitted psychotic depression

BACKGROUND

Psychomotor disturbance is common in psychotic depression and is associated with relapse. In this analysis, we examined whether white matter microstructure is associated with relapse probability in psychotic depression and, if so, whether white matter microstructure accounts for the association between psychomotor disturbance and relapse.

METHODS

We used tractography to characterize diffusion-weighted MRI data in 80 participants enrolled in a randomized clinical trial that compared efficacy and tolerability of sertraline plus olanzapine with sertraline plus placebo in the continuation treatment of remitted psychotic depression. Cox proportional hazard models tested the relationships between psychomotor disturbance (processing speed and CORE score) at baseline, white matter microstructure (fractional anisotropy [FA] and mean diffusivity [MD]) in 15 selected tracts at baseline, and relapse probability.

RESULTS

CORE was significantly associated with relapse. Higher mean MD was significantly associated with relapse in the each of the following tracts: corpus callosum, left striato-frontal, left thalamo-frontal, and right thalamo-frontal. CORE and MD were each associated with relapse in the final models.

LIMITATIONS

As a secondary analysis with a small sample size, this study was not powered for its aims, and is vulnerable to types I and II statistical errors. Further, the sample size was not sufficient to test the interaction of the independent variables and randomized treatment group with relapse probability.

CONCLUSIONS

While both psychomotor disturbance and MD were associated with psychotic depression relapse, MD did not account for the relationship between psychomotor disturbance and relapse. The mechanism by which of psychomotor disturbance increases the risk of relapse requires further investigation.

CLINICAL TRIAL REGISTRATION

Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II); NCT01427608. URL: https://clinicaltrials.gov/ct2/show/NCT01427608.

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Genomic Investigation of Remission and Relapse of Psychotic Depression Treated with Sertraline plus Olanzapine: The STOP-PD II Study

INTRODUCTION

Little is known regarding genetic factors associated with treatment outcome of psychotic depression. We explored genomic associations of remission and relapse of psychotic depression treated with pharmacotherapy.

METHODS

Genomic analyses were performed in 171 men and women aged 18-85 years with an episode of psychotic depression who participated in the Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II). Participants were treated with open-label sertraline plus olanzapine for up to 12 weeks; those who achieved remission or near-remission and maintained it following 8 weeks of stabilization were eligible to participate in a 36-week randomized controlled trial that compared sertraline plus olanzapine with sertraline plus placebo in preventing relapse.

RESULTS

There were no genome-wide significant associations with either remission or relapse. However, at a suggestive threshold, SNP rs1026501 (31 kb from SYNPO2) in the whole sample and rs6844137 (within the intronic region of SYNPO2) in the European ancestry subsample were associated with a decreased likelihood of remission. In polygenic risk analyses, participants who had greater improvement after antidepressant treatments showed a higher likelihood of reaching remission. Those who achieved remission and had a higher polygenic risk for Alzheimer's disease had a significantly decreased likelihood of relapse.

CONCLUSION

Our analyses provide preliminary insights into the genetic architecture of remission and relapse in a well-characterized group of patients with psychotic depression.

Residual or re-emergent impaired insight into delusions following remission is unrelated to later relapse during a randomized clinical trial of continuation pharmacotherapy for psychotic depression - The STOP-PD II Study

BACKGROUND

Impaired insight into delusions is associated with a lower probability of remission of psychotic depression, independent of illness severity. The relationship between participant characteristics and impaired insight into delusions in remitted psychotic depression, and whether impaired insight is associated with risk of relapse of psychotic depression during continuation pharmacotherapy were examined.

METHODS

Data were analyzed from 126 participants in the STOP-PD II study who experienced sustained remission of psychotic depression during 8-week stabilization treatment with sertraline plus olanzapine and were then randomized to 36 weeks of continuation treatment with sertraline plus either olanzapine or placebo. Insight into delusions was assessed with the Resolution of Delusions Scale (RODS). Linear regression analyses examined the associations between participant characteristics and insight into delusions. Cox proportional-hazards models examined whether i) change in RODS during stabilization treatment; or ii) RODS at the end of stabilization treatment predicted risk of relapse during 36 weeks of continuation treatment.

RESULTS

Severity of psychosis before initiation of treatment was the only participant characteristic associated with the change in insight during stabilization treatment. Neither change in insight during stabilization treatment nor insight at the end of stabilization treatment was associated with risk of relapse.

LIMITATIONS

Insufficient statistical power and the lack of variability in RODS scores at the time of randomization may have contributed to the absence of a relationship between RODS and risk of relapse.

CONCLUSION

Residual or reemergent insight impairment following acute treatment does not preclude patients from sustaining remission of psychotic depression in a randomized placebo-controlled trial.

Association of functional connectivity of the executive control network or default mode network with cognitive impairment in older adults with remitted major depressive disorder or mild cognitive impairment

Major depressive disorder (MDD) is associated with an increased risk of developing dementia. The present study aimed to better understand this risk by comparing resting state functional connectivity (rsFC) in the executive control network (ECN) and the default mode network (DMN) in older adults with MDD or mild cognitive impairment (MCI). Additionally, we examined the association between rsFC in the ECN or DMN and cognitive impairment transdiagnostically. We assessed rsFC alterations in ECN and DMN in 383 participants from five groups at-risk for dementia-remitted MDD with normal cognition (MDD-NC), non-amnestic mild cognitive impairment (naMCI), remitted MDD + naMCI, amnestic MCI (aMCI), and remitted MDD + aMCI-and from healthy controls (HC) or individuals with Alzheimer's dementia (AD). Subject-specific whole-brain functional connectivity maps were generated for each network and group differences in rsFC were calculated. We hypothesized that alteration of rsFC in the ECN and DMN would be progressively larger among our seven groups, ranked from low to high according to their risk for dementia as HC, MDD-NC, naMCI, MDD + naMCI, aMCI, MDD + aMCI, and AD. We also regressed scores of six cognitive domains (executive functioning, processing speed, language, visuospatial memory, verbal memory, and working memory) on the ECN and DMN connectivity maps. We found a significant alteration in the rsFC of the ECN, with post hoc testing showing differences between the AD group and the HC, MDD-NC, or naMCI groups, but no significant alterations in rsFC of the DMN. Alterations in rsFC of the ECN and DMN were significantly associated with several cognitive domain scores transdiagnostically. Our findings suggest that a diagnosis of remitted MDD may not confer functional brain risk for dementia. However, given the association of rs-FC with cognitive performance (i.e., transdiagnostically), rs-FC may help in stratifying this risk among people with MDD and varying degrees of cognitive impairment.

Within-subject reliability of concurrent TMS-fMRI during a single session

Concurrent transcranial magnetic stimulation with functional MRI (concurrent TMS-fMRI) allows real-time causative probing of brain connectivity. However, technical challenges, safety, and tolerability may limit the number of trials employed during a concurrent TMS-fMRI experiment. We leveraged an existing data set with 100 trials of active TMS compared to a sub-threshold control condition to assess the reliability of the evoked BOLD response during concurrent TMS-fMRI. This data will permit an analysis of the minimum number of trials that should be employed in a concurrent TMS-fMRI protocol in order to achieve reliable spatial changes in activity. Single-subject maps of brain activity were created by splitting the trials within the same experimental session into groups of 50, 40, 30, 25, 20, 15, or 10 trials, correlations (R) between t-maps derived from paired subsets of trials within the same individual were calculated as reliability. R was moderate-high for 50 trials (mean R = .695) and decreased as the number of trials decreased. Consistent with previous findings of high individual variability in the spatial patterns of evoked neuronal changes following a TMS pulse, the spatial pattern of Rs differed across participants, but regional R was correlated with the magnitude of TMS-evoked activity. These results demonstrate concurrent TMS-fMRI produces a reliable pattern of activity at the individual level at higher trial numbers, particularly within localized regions. The spatial pattern of reliability is individually idiosyncratic and related to the individual pattern of evoked changes.

Predictors of relapse of psychotic depression: Findings from the STOP-PD II randomized clinical trial

Psychotic depression has a high rate of relapse. The study aims were to identify a prediction model of risk of relapse of psychotic depression and examine whether predictors moderated the effect of treatment on relapse. One hundred and twenty-six men and women aged 18-85 years, who experienced sustained remission or near-remission of psychotic depression with sertraline plus olanzapine, participated in a 36-week randomized controlled trial that compared sertraline plus olanzapine with sertraline plus placebo in preventing relapse (NCT01427608). Cox regression analyses were performed to identify significant predictors of relapse and to model the combined role of significant predictors. Concordance statistic was calculated to determine the accuracy of the best fit multivariable models in predicting relapse. Finally, interaction terms were tested for each significant predictor to examine whether they moderated the effect of treatment on risk of relapse. Lifetime number of depressive episodes, severity of residual depressive symptoms at the time of randomization, and psychomotor disturbance both at acute enrollment when participants were depressed and at the time of randomization predicted risk of relapse. Multivariable models had 69-70% accuracy in predicting relapse. Psychomotor disturbance was associated with increased risk of relapse in the sertraline plus olanzapine group compared with sertraline plus placebo, whereas the other predictors did not moderate the effect of treatment on relapse. Future research is needed to determine whether a combination of clinical and biological variables can further increase the accuracy of prediction of relapse of psychotic depression.

Preliminary Observations of Resting-State Magnetoencephalography in Nonmedicated Children with Obsessive-Compulsive Disorder

Background: Cortico-striato-thalamo-cortical (CSTC) network alterations are hypothesized to contribute to symptoms of obsessive-compulsive disorder (OCD). To date, very few studies have examined whether CSTC network alterations are present in children with OCD, who are medication naive. Medication-naive pediatric imaging samples may be optimal to study neural correlates of illness and identify brain-based markers, given the proximity to illness onset. Methods: Magnetoencephalography (MEG) data were analyzed at rest, in 18 medication-naive children with OCD (M = 12.1 years ±2.0 standard deviation [SD]; 10 M/8 F) and 13 typically developing children (M = 12.3 years ±2.2 SD; 6 M/7 F). Whole-brain MEG-derived resting-state functional connectivity (rs-fc), for alpha- and gamma-band frequencies were compared between OCD and typically developing (control) groups. Results: Increased MEG-derived rs-fc across alpha- and gamma-band frequencies was found in the OCD group compared to the control group. Increased MEG-derived rs-fc at alpha-band frequencies was evident across a number of regions within the CSTC circuitry and beyond, including the cerebellum and limbic regions. Increased MEG-derived rs-fc at gamma-band frequencies was restricted to the frontal and temporal cortices. Conclusions: This MEG study provides preliminary evidence of altered alpha and gamma networks, at rest, in medication-naive children with OCD. These results support prior findings pointing to the relevance of CSTC circuitry in pediatric OCD and further support accumulating evidence of altered connectivity between regions that extend beyond this network, including the cerebellum and limbic regions. Given the substantial portion of children and youth whose OCD symptoms do not respond to conventional treatments, our findings have implications for future treatment innovation research aiming to target and track whether brain patterns associated with having OCD may change with treatment and/or predict treatment response.

The Longitudinal Youth in Transition Study (LYiTS) Cohort Profile: Exploration by Hospital- Versus Community-Based Mental Health Services

OBJECTIVES

Youth face numerous challenges in receiving coordinated and continuous mental health services, particularly as they reach the age of transition from child and adolescent mental health services (CAMHS) to adult mental health services (AMHS). The Longitudinal Youth in Transition Study (LYiTS) follows youth prospectively as they cross this transition boundary to better understand their transition pathways and resulting symptoms and health service use outcomes. The current paper presents the baseline profile description for the LYiTS cohort and additionally examines differences in symptoms and functioning and health service utilization between youth receiving services at hospital- versus community-based CAMHS.

METHODS

A cross-sectional design was used. A sample of 237 16-18-year-old youth recruited from outpatient CAMHS at two hospitals and two community sites completed self-report measures at their first of four annual assessments. A latent profile analysis was conducted to identify symptomology profiles, and youth were compared on symptoms and health service use between hospital- and community-based sites.

RESULTS

Four distinct symptomology profiles were identified (subclinical, moderate internalizing, moderate externalizing, and high symptomology). Symptom profiles and functioning levels reported by youth were no different across both types of organization, although there were differences detected in health service utilization, such as type of provider seen and use of medications.

CONCLUSIONS

These findings suggest that there is little difference in symptomology between youth accessing hospital versus community-based CAMHS. With growing interest in understanding the effectiveness and cost-effectiveness of different models of mental health care, these findings provide a new understanding of the clinical and service use profiles of transition-aged youth that will be explored further as this cohort is followed across the CAMHS to AMHS transition boundary.

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

Βeta-amyloid (Aβ) 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 Aβ on cognition. Following assessment of memory performance, resting-state fMRI, and mean cortical PET-Aβ, 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 Aβ on episodic memory. These results suggest that connectivity strength between the precuneus cortex and the superior frontal gyri may alter the negative effect of Aβ 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.

Longer illness duration is associated with greater individual variability in functional brain activity in Schizophrenia, but not bipolar disorder

BACKGROUND

Individuals with schizophrenia exhibit greater inter-patient variability in functional brain activity during neurocognitive task performance. Some studies have shown associations of age and illness duration with brain function; however, the association of these variables with variability in brain function activity is not known. In order to better understand the progressive effects of age and illness duration across disorders, we examined the relationship with individual variability in brain activity.

METHODS

Neuroimaging and behavioural data were extracted from harmonized datasets collectively including 212 control participants, 107 individuals with bipolar disorder, and 232 individuals with schizophrenia (total n = 551). Functional activity in response to an N-back working memory task (2-back vs 1-back) was examined. Individual variability was quantified via the correlational distance of fMRI activity between participants; mean correlational distance of one participant in relation to all others was defined as a 'variability score'.

RESULTS

Greater individual variability was found in the schizophrenia group compared to the bipolar disorder and control groups (p = 1.52e-09). Individual variability was significantly associated with aging (p = 0.027), however, this relationship was not different across diagnostic groups. In contrast, in the schizophrenia sample only, a longer illness duration was associated with increased variability (p = 0.027).

CONCLUSION

An increase in variability was observed in the schizophrenia group related to illness duration, beyond the effects of normal aging, implying illness-related deterioration of cognitive networks. This has clinical implications for considering long-term trajectories in schizophrenia and progressive neural and cognitive decline which may be amiable to novel treatments.

Disengagement from early psychosis intervention services: an observational study informed by a survey of patient and family perspectives

Approximately one-third of patients with early psychosis disengage from services before the end of treatment. We sought to understand patient and family perspectives on early psychosis intervention (EPI) service engagement and use these findings to elucidate factors associated with early disengagement, defined as dropout from EPI in the first 9 months. Patients aged 16-29 referred to a large EPI program between July 2018-February 2020 and their family members were invited to complete a survey exploring facilitators and barriers to service engagement. A prospective chart review was conducted for 225 patients consecutively enrolled in the same EPI program, receiving the NAVIGATE model of coordinated specialty care, between July 2018-May 2019. We conducted a survival analysis, generating Kaplan-Meier curves depicting time to disengagement and Cox proportional hazards models to determine rate of disengagement controlling for demographic, clinical, and program factors. The survey was completed by 167 patients and 79 family members. The top endorsed engagement facilitator was related to the therapeutic relationship in both patients (36.5%) and families (43.0%). The top endorsed barrier to engagement was medication side effects in both patients (28.7%) and families (39.2%). In Cox proportional hazards models, medication nonadherence (HR = 2.37, 95% CI = 1.17-4.80) and use of individual psychotherapy (HR = .460, 95% CI = 0.220-0.962) were associated with early disengagement, but some of the health equity factors expected to affect engagement were not. Findings suggest that delivery of standardized treatment may buffer the effects of health disparities on service disengagement in early psychosis.

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 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 early preclinical phases of neurodegeneration. We use a longitudinal approach to examine the brain changes that take place during early stages of cognitive decline in the Open Access Series of Imaging Studies-3 dataset. 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 lateral temporal, motor, and parts of the lateral prefrontal cortex. These changes in amyloid levels were linked to longitudinal increases in 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.

Brain Structure in Acutely Underweight and Partially Weight-Restored Individuals With Anorexia Nervosa: A Coordinated Analysis by the ENIGMA Eating Disorders Working Group

BACKGROUND

The pattern of structural brain abnormalities in anorexia nervosa (AN) is still not well understood. While several studies report substantial deficits in gray matter volume and cortical thickness in acutely underweight patients, others find no differences, or even increases in patients compared with healthy control subjects. Recent weight regain before scanning may explain some of this heterogeneity. To clarify the extent, magnitude, and dependencies of gray matter changes in AN, we conducted a prospective, coordinated meta-analysis of multicenter neuroimaging data.

METHODS

We analyzed T1-weighted structural magnetic resonance imaging scans assessed with standardized methods from 685 female patients with AN and 963 female healthy control subjects across 22 sites worldwide. In addition to a case-control comparison, we conducted a 3-group analysis comparing healthy control subjects with acutely underweight AN patients (n = 466) and partially weight-restored patients in treatment (n = 251).

RESULTS

In AN, reductions in cortical thickness, subcortical volumes, and, to a lesser extent, cortical surface area were sizable (Cohen's d up to 0.95), widespread, and colocalized with hub regions. Highlighting the effects of undernutrition, these deficits were associated with lower body mass index in the AN sample and were less pronounced in partially weight-restored patients.

CONCLUSIONS

The effect sizes observed for cortical thickness deficits in acute AN are the largest of any psychiatric disorder investigated in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium to date. These results confirm the importance of considering weight loss and renutrition in biomedical research on AN and underscore the importance of treatment engagement to prevent potentially long-lasting structural brain changes in this population.

Behavioural phenotypes of intrinsic motivation in schizophrenia determined by cluster analysis of objectively quantified real-world performance

Intrinsic motivation deficits are a prominent feature of schizophrenia that substantially impacts functional outcome. This study used cluster analysis of innate real-world behaviours captured during two open-field tasks to dimensionally examine heterogeneity in intrinsic motivation in schizophrenia patients (SZ) and healthy controls (HC). Wireless motion capture quantified participants' behaviours aligning with distinct aspects of intrinsic motivation: exploratory behaviour and effortful activity in the absence of external incentive. Cluster analysis of task-derived measures identified behaviourally differentiable subgroups, which were compared across standard clinical measures of general amotivation, cognition, and community functioning. Among 45 SZ and 47 HC participants, three clusters with characteristically different behavioural phenotypes emerged: low exploration (20 SZ, 19 HC), low activity (15 SZ, 8 HC), and high exploration/activity (10 SZ, 20 HC). Low performance in either dimension corresponded with similar increased amotivation. Within-cluster discrepancies emerged for amotivation (SZ > HC) within the low exploration and high performance clusters, and for functioning (SZ < HC) within all clusters, increasing from high performance to low activity to low exploration. Objective multidimensional characterization thus revealed divergent behavioural expression of intrinsic motivation deficits that may be conflated by summary clinical measures of motivation and overlooked by unidimensional evaluation. Deficits in either aspect may hinder general motivation and functioning particularly in SZ. Multidimensional phenotyping may help guide personalized remediation by discriminating between intrinsic motivation impairments that require amelioration versus unimpaired tendencies that may facilitate remediation.

Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD)

Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a 'variability score'. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more 'idiosyncratic' activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.

Associations between locus coeruleus integrity and diagnosis, age, and cognitive performance in older adults with and without late-life depression: An exploratory study

Late-life depression (LLD) is a risk factor for age-dependent cognitive deterioration. Norepinephrine-related degeneration in the locus coeruleus (LC) may explain this link. To examine the LC norepinephrine system in vivo, we acquired neuromelanin-sensitive MRI (NM-MRI) in a sample of 48 participants, including 25 with LLD (18 women, age 68.08 ± 5.41) and 23 never-depressed comparison participants (ND, 12 women, age 70 ± 8.02), matched on age and cognitive status. We employed a semi-automated procedure to segment the LC into three bilateral sections along its rostro-caudal extent, and calculated relative contrast as a proxy of integrity. Then, we examined associations between integrity and LLD diagnosis, age, and cognition, as measured via the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Delis-Kaplan Executive Function System (D-KEFS). We did not identify an effect of LLD diagnosis nor age on LC integrity, but exploratory canonical correlation analysis across the combined participant sample revealed a strong (Rc = 0.853) and significant multivariate relationship between integrity and cognition (Wilks' λ = 0.03, F(84, 162.44) = 1.66, p = <.01). The first and only significant variate explained 72.83% model variance, and linked better attention and delayed memory performance, faster processing speed, and lower verbal fluency performance with higher integrity in the right rostral but lower integrity in the left caudal LC. Our results complement prior evidence of LC involvement in cognition in healthy older adults, and extend this association to individuals with LLD.

Factor analysis of the CORE measure of psychomotor disturbance in psychotic depression: Findings from the STOP-PD II study

The CORE instrument is commonly used to measure psychomotor disturbance. We examined the factor structure of the CORE in 266 adults with an acute episode psychotic depression, a disorder with a high rate of psychomotor disturbance. Exploratory factor analysis identified a two-factor solution: Factor 1 corresponded to the CORE's retardation and non-interactiveness items and Factor 2 corresponded to its agitation items. Internal consistency was excellent for Factor 1 but questionable for Factor 2. These findings suggest that the CORE's retardation and non-interactiveness items should be combined in one subscale when assessing patients with an acute episode of psychotic depression.

A longitudinal multi-scanner multimodal human neuroimaging dataset

Human neuroimaging has led to an overwhelming amount of research into brain function in healthy and clinical populations. However, a better appreciation of the limitations of small sample studies has led to an increased number of multi-site, multi-scanner protocols to understand human brain function. As part of a multi-site project examining social cognition in schizophrenia, a group of "travelling human phantoms" had structural T1, diffusion, and resting-state functional MRIs obtained annually at each of three sites. Scan protocols were carefully harmonized across sites prior to the study. Due to scanner upgrades at each site (all sites acquired PRISMA MRIs during the study) and one participant being replaced, the end result was 30 MRI scans across 4 people, 6 MRIs, and 4 years. This dataset includes multiple neuroimaging modalities and repeated scans across six MRIs. It can be used to evaluate differences across scanners, consistency of pipeline outputs, or test multi-scanner harmonization approaches.

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 case–control 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.

Neurobiological, familial and genetic risk factors for dimensional psychopathology in the Adolescent Brain Cognitive Development study

BACKGROUND

Adolescence is a key period for brain development and the emergence of psychopathology. The Adolescent Brain Cognitive Development (ABCD) study was created to study the biopsychosocial factors underlying healthy and pathological brain development during this period, and comprises the world's largest youth cohort with neuroimaging, family history and genetic data.

METHODS

We examined 9856 unrelated 9-to-10-year-old participants in the ABCD study drawn from 21 sites across the United States, of which 7662 had multimodal magnetic resonance imaging scans passing quality control, and 4447 were non-Hispanic white and used for polygenic risk score analyses. Using data available at baseline, we associated eight 'syndrome scale scores' from the Child Behavior Checklist-summarizing anxious/depressed symptoms, withdrawn/depressed symptoms, somatic complaints, social problems, thought problems, attention problems, rule-breaking behavior, and aggressive behavior-with resting-state functional and structural brain magnetic resonance imaging measures; eight indicators of family history of psychopathology; and polygenic risk scores for major depression, bipolar disorder, schizophrenia, attention deficit hyperactivity disorder (ADHD) and anorexia nervosa. As a sensitivity analysis, we excluded participants with clinically significant (>97th percentile) or borderline (93rd-97th percentile) scores for each dimension.

RESULTS

Most Child Behavior Checklist dimensions were associated with reduced functional connectivity within one or more of four large-scale brain networks-default mode, cingulo-parietal, dorsal attention, and retrosplenial-temporal. Several dimensions were also associated with increased functional connectivity between the default mode, dorsal attention, ventral attention and cingulo-opercular networks. Conversely, almost no global or regional brain structural measures were associated with any of the dimensions. Every family history indicator was associated with every dimension. Major depression polygenic risk was associated with six of the eight dimensions, whereas ADHD polygenic risk was exclusively associated with attention problems and externalizing behavior (rule-breaking and aggressive behavior). Bipolar disorder, schizophrenia and anorexia nervosa polygenic risk were not associated with any of the dimensions. Many associations remained statistically significant even after excluding participants with clinically significant or borderline psychopathology, suggesting that the same risk factors that contribute to clinically significant psychopathology also contribute to continuous variation within the clinically normal range.

CONCLUSIONS

This study codifies neurobiological, familial and genetic risk factors for dimensional psychopathology across a population-scale cohort of community-dwelling preadolescents. Future efforts are needed to understand how these multiple modalities of risk intersect to influence trajectories of psychopathology into late adolescence and adulthood.

Cortico-amygdalar connectivity and externalizing/internalizing behavior in children with neurodevelopmental disorders

Background

Externalizing and internalizing behaviors contribute to clinical impairment in children with neurodevelopmental disorders (NDDs). Although associations between externalizing or internalizing behaviors and cortico-amygdalar connectivity have been found in clinical and non-clinical pediatric samples, no previous study has examined whether similar shared associations are present across children with different NDDs.

Methods

Multi-modal neuroimaging and behavioral data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used. POND participants aged 6–18 years with a primary diagnosis of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or obsessive–compulsive disorder (OCD), as well as typically developing children (TDC) with T1-weighted, resting-state fMRI or diffusion weighted imaging (DWI) and parent-report Child Behavioral Checklist (CBCL) data available, were analyzed (total n = 346). Associations between externalizing or internalizing behavior and cortico-amygdalar structural and functional connectivity indices were examined using linear regressions, controlling for age, gender, and image-modality specific covariates. Behavior-by-diagnosis interaction effects were also examined.

Results

No significant linear associations (or diagnosis-by-behavior interaction effects) were found between CBCL-measured externalizing or internalizing behaviors and any of the connectivity indices examined. Post-hoc bootstrapping analyses indicated stability and reliability of these null results.

Conclusions

The current study provides evidence towards an absence of a shared linear relationship between internalizing or externalizing behaviors and cortico-amygdalar connectivity properties across a transdiagnostic sample of children with different primary NDD diagnoses and TDC. Different methodological approaches, including incorporation of multi-dimensional behavioral data (e.g., task-based fMRI) or clustering approaches may be needed to clarify complex brain-behavior relationships relevant to externalizing/internalizing behaviors in heterogeneous clinical NDD populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00429-022-02483-0.

From the Group to the Individual in Schizophrenia Spectrum Disorders: Biomarkers of Social Cognitive Impairments and Therapeutic Translation

People with schizophrenia spectrum disorders (SSDs) often experience persistent social cognitive impairments, associated with poor functional outcome. There are currently no approved treatment options for these debilitating symptoms, highlighting the need for novel therapeutic strategies. Work to date has elucidated differential social processes and underlying neural circuitry affected in SSDs, which may be amenable to modulation using neurostimulation. Further, advances in functional connectivity mapping and electric field modeling may be used to identify individualized treatment targets to maximize the impact of brain stimulation on social cognitive networks. Here, we review literature supporting a roadmap for translating functional connectivity biomarker discovery to individualized treatment development for social cognitive impairments in SSDs. First, we outline the relevance of social cognitive impairments in SSDs. We review machine learning approaches for dimensional brain-behavior biomarker discovery, emphasizing the importance of individual differences. We synthesize research showing that brain stimulation techniques, such as repetitive transcranial magnetic stimulation, can be used to target relevant networks. Further, functional connectivity-based individualized targeting may enhance treatment response. We then outline recent approaches to account for neuroanatomical variability and optimize coil positioning to individually maximize target engagement. Overall, the synthesized literature provides support for the utility and feasibility of this translational approach to precision treatment. The proposed roadmap to translate biomarkers of social cognitive impairments to individualized treatment is currently under evaluation in precision-guided trials. Such a translational approach may also be applicable across conditions and generalizable for the development of individualized neurostimulation targeting other behavioral deficits.