The quandary of covarying: A brief review and empirical examination of covariate use in structural neuroimaging studies on psychological variables

Assessing the association between ADHD and brain maturation in late childhood and emotion regulation in early adolescence

A delay in brain maturation is a hypothesized pathomechanism of attention-deficit/hyperactivity disorder (ADHD). Differences in emotion regulation are associated with phenotypic and prognostic heterogeneity in ADHD. The development of emotion regulation is driven, in part, by brain maturation. Whether the difference between an individual's brain age predicted by machine-learning algorithms trained on neuroimaging data and that individual's chronological age, i.e. brain-predicted age difference (brain-PAD) predicts differences in emotion regulation, and whether ADHD problems add to this prediction is unknown. Using data from the Adolescent Brain Cognitive Development Study, we examined, in 2711 children (Mage = 120.09 months, SD = 7.61; 54.15% female; 61.23% white), whether adjusting for action cancellation (inhibition), age, sex assigned at birth, psychotropic treatment, and pubertal status, brain-PAD in late childhood predicts self-reported emotion regulation in early adolescence (at 3-year follow-up), and whether parent-reported ADHD problems predict self-reported emotion regulation above and beyond brain-PAD. Greater brain-PAD predicted greater expressive suppression (b = 0.172, SE = 0.051, pFDR = 0.004), whereas ADHD problems did not (b = 0.041, SE = 0.022, pFDR = 0.124), model marginal R2 = 0.020. This pattern of results was replicated across sensitivity tests. Neither brain-PAD, nor ADHD problems predicted cognitive reappraisal, pFDRs = 0.734. Clinically, consistent with earlier findings linking greater brain-PAD to psychopathology, we observed that greater brain-PAD in childhood-but not ADHD problems-predicted expressive suppression in early adolescence. Expressive suppression is implicated in the etiology, maintenance, and treatment of numerous psychopathologies, highlighting the relevance of brain-PAD in understanding developmental risk mechanisms. Conceptually, these findings further validate brain-PAD as a valuable tool for advancing developmental neuroscience.

Neural Electrical Correlates of Subjective Happiness

Happiness is a subjective experience that can serve as the ultimate goal for humans. A recent study that employed resting-state functional magnetic resonance imaging (fMRI) reported that spontaneous fluctuation (fractional amplitude of low-frequency fluctuation: fALFF) in the precuneus is negatively associated with subjective happiness. However, little is known about the neural electrical correlates of subjective happiness, which can provide direct evidence of neural activity and insights regarding the underlying psychological, cellular, and neurotransmitter mechanisms. Therefore, we measured 400-channel whole-head magnetoencephalography (MEG) during resting state in participants whose subjective happiness was evaluated using questionnaires. We conducted source reconstruction analysis utilizing bandpass-filtered MEG data and analyzed the fALFF of the band-limited power time series as an index of spontaneous neural fluctuation. Gamma-band fALFF values in the right precuneus were negatively associated with subjective happiness scores (partial correlation coefficient = -0.56). These findings indicate that subjective happiness has a neural electrical correlate of reduced spontaneous fluctuation of gamma-band neuronal oscillations in the right precuneus, and that it could be mediated by a reduction in wandering, clinging self-consciousness through heightened N-methyl-d-aspartate-dependent gamma-aminobutyric acid-ergic parvalbumin inhibitory interneuron activity.

Neural network disruptions between default mode network and salience network in mild cognitive impairment with neuropsychiatric symptoms

BACKGROUND

Neuropsychiatric symptoms (NPS) in mild cognitive impairment (MCI) are associated with accelerated Alzheimer's disease (AD) progression. Identifying multimodal brain imaging patterns associated with NPS in MCI may help understand pathophysiology correlates AD.

METHODS

This cross-sectional resting-state functional magnetic resonance imaging study included 376 participants: 130 MCI with neuropsychiatric symptoms (MCI+NPS), 154 MCI without neuropsychiatric symptoms (MCI-NPS), 92 cognitively normal (CN). NPS were assessed by the Neuropsychiatric Inventory Questionnaire (NPI-Q). Functional connectivity between default mode network (DMN) and salience network (SN) was compared among MCI+NPS, MCI-NPS and CN. Then, the morphometric measurements of abnormal node in default mode and salience networks was explored. Furthermore, correlation analysis was performed to investigate the relationship between NPS and functional and structural alterations in DMN and SN in MCI.

RESULTS

In the MCI+NPS group, the most frequently endorsed NPS was anxiety (46.2 %), the less prevalent NPS was euphoria/elation (1.44 %). Compared with the MCI-NPS group, there was abnormal FC between medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) (P < 0.05) in the MCI+NPS group, which was significantly associated with total NPI-Q score (r = 0.244, p = 0.000), affective symptoms (r = 0.212, p = 0.000), and hyperactivity symptoms (r = 0.196 p = 0.000). The mPFC area of MCI-NPS group was smaller than that of CN group (p < 0.05), and the area of mPFC was significantly associated with hyperactivity symptoms in MCI group.

CONCLUSIONS

Dysfunction of DMN and SN may partly contribute to the NPS in MCI patients, especially affective symptoms and hyperactivity symptoms. Our results complement the evidence linking NPS with Alzheimer's disease biomarkers.

Longitudinal clinical outcomes based on cognitive and hippocampal clusters of first episode psychosis

BACKGROUND

In first episode psychosis (FEP), cognitive impairments are core features contributing to clinical and functional heterogeneity. Significant impairment indicates greater clinical severity throughout the course of the illness, particularly for negative symptoms. Hippocampal volume is smaller in FEP than in healthy controls (notably subfields like Cornu Ammonis 1-3 and subiculum), and is related to cognitive impairments and negative symptoms. The aim of this study was to compare the clinical and functional trajectories of FEP subgroups as a function of cognitive performance and hippocampal volumes.

METHODS

One hundred FEP patients and sixty healthy controls initially assessed using the CogState research battery, underwent 3 T MRI to extract hippocampal subfields and adjacent structures using the MAGeT brain algorithm. Clinical assessments were carried out for negative (Motivational and Pleasure - MAP, and diminished expression - EXP) and depressive symptoms, and global functioning. Measurements were taken at 4 time points (3, 9, 15, 21 months following program entry). Based on available first timepoint standardized cognitive and hippocampal features, using healthy controls as reference, clusters were determined by a hierarchical ascending classification. Their clinical and functional longitudinal trajectories were analyzed using linear mixed-effects models.

RESULTS

Three baseline clusters were revealed: normal-range hippocampal volume with low attention, working and verbal memory (FEP 0), small hippocampus with low verbal memory and social cognition (FEP 1), and large hippocampus with low verbal memory (FEP 2). At baseline, the clusters did not differ on symptoms severity and global functioning. Longitudinally, MAP, EXP and depressive symptoms decreased over time in FEP 0. Global functioning improved in FEP 0 and FEP 1, while FEP 2 was clinically and functionally stable over time. Longitudinal inter-group comparisons did not yield any significant differences.

CONCLUSION

The clusters were dissociated between hippocampus and cognition, but their trajectories suggest the importance of hippocampal integrity in the clinical and/or functional outcome. Future studies are needed to understand intervention efficiency depending on hippocampal integrity.

Prenatal alcohol exposure alters brain structure and neurocognitive outcomes for 6- to 7-year-old children in a South African birth cohort

BACKGROUND

Several studies have demonstrated an association between prenatal alcohol exposure (PAE) and altered brain structure. However, more research is needed to understand how structural brain changes may influence neurocognitive performance in children with PAE at the age of school entry. We investigated the associations between PAE and cortical and subcortical gray matter morphology and whether PAE-related structural brain changes mediate the associations between PAE and neurocognitive outcomes in 6- to 7-year-old children.

METHODS

One hundred fifty-eight children (49 PAE, 109 unexposed controls; 46% female; mean age 76 ± 5 months) who participated in a brain imaging substudy of the population-based Drakenstein Child Health Study were included. The children had moderate-to-high PAE without other substance exposure, except prenatal tobacco exposure. T1-weighted brain structural scans were acquired using a 3T MRI scanner. General linear models and mediation analyses tested the associations of PAE with cortical and subcortical metrics and associated neurocognitive outcomes.

RESULTS

PAE was associated with a smaller total cortical surface area and had multivariate effects on regional cortical volume and surface area in the temporal lobe. The smaller volume and surface area of the left middle temporal gyrus mediated associations between PAE and neurocognitive outcomes for numeracy and mathematics and/or cognition and executive functioning. Findings persisted when adjusting for age, sex, maternal education, prenatal tobacco exposure, and, in volumetric and surface area models, intracranial volume.

CONCLUSION

This study suggests that there is persistent altered brain structural development in children with PAE, consistent with previous findings in this cohort at infancy and age 2-3 years. Cortical changes in regions known to play a role in numeracy and semantic memory mediated associations between PAE and neurocognitive deficits, highlighting clinical relevance. Efforts to prevent PAE and improve neurocognitive development in children with PAE should be implemented as early as possible after birth.

Modeling recurrent heart failure risk in type 2 diabetes: impact of flexible HbA1c trajectories using nonhomogeneous Poisson processes

Background

Many clinical trials yielded inconsistent results regarding the effect of intensive glycated hemoglobin control on cardiovascular diseases in type 2 diabetes. We identified distinct HbA1c trajectories and their association with the recurrent hospitalization of heart failures (HHF) for patients with type 2 diabetes starting from the date of diabetes diagnosis.

Methods

In this study, we included 194,258 patients who entered the SingHealth Diabetes Registry from 2013 to 2020. Their diagnoses of type 2 diabetes spanned the years 1960-2020, encompassing HbA1c measurements, records of HHF, and other cardiovascular complications. Latent class growth models (LCGM) with splines were used to extract the subgroups with distinct HbA1c trajectories. The association between HbA1c trajectories and the recurrent risk of HHF was investigated by nonhomogeneous Poisson processes (NHPP).

Results

Eight distinct HbA1c trajectories were identified as follows: low stable (LowS, 22.2%), moderate low ascending (ModLowA, 12.7%), moderate high ascending (ModHighA, 11.5%), moderate low descending (ModLowD, 17.2%), moderate high descending (ModHighD, 10.1%), moderate high volatility (ModHighV, 10.1%), high with a sharp decline (HighSD, 8.0%), and high volatility (HighV, 10.2%). Using the Class LowS as a reference, the hazard ratios for recurrent HHF for the other classes are as follows: 0.79 for ModLowA, 1.30 for ModHighA, 1.17 for ModLowD, 1.89 for ModHighD, 1.94 for ModHighV, 1.25 for HighSD, and 2.88 for HighV. Considering recurrent HHFs, our NHPP model demonstrated predictive capability for type 2 diabetes patients' future HHF events.

Conclusions

Low baseline HbA1c levels are associated with a lower risk of recurrent HHF, while poor glycemic control significantly increases this risk. Our application of LCGM with splines effectively captures flexible, long-term HbA1c trajectories, while the innovative use of the NHPP model allows for precise modeling of HHF recurrence risk. This approach provides a foundation for personalized risk predictions and future HF management by incorporating dynamically updated risk factors.

Perils of Partialing: Can Scholars Predict Residualized Variables' Nomological Nets?

OBJECTIVE

Partialing is a statistical procedure in which the variance shared among two or more constructs is removed, allowing researchers to examine the unique properties of the residualized, partialed, or unique portions of each construct. Although this technique is common, its use has been criticized due to the difficulty faced in interpreting residualized variables, especially when the original constructs were highly correlated. The aim of this study is to test the degree to which psychological researchers from the fields of clinical, social, and personality psychology are able to estimate the nomological network of partialed variables accurately when provided with information on the zero-order relations between the variables and with general personality traits.

METHODS

Variables with intercorrelations of varying magnitudes (i.e., anxiety, depression, antisocial personality disorder, and borderline personality disorder) will be used to test whether experts can estimate partialed variables' nomological networks vis-à-vis basic trait profiles. Experts' estimates will be compared to obtained partialed trait profiles via macro (overall profile similarity) and more micro (individual trait comparisons) approaches.

Preliminary results of the EPIDIA4Kids study on brain function in children: multidimensional ADHD-related symptomatology screening using multimodality biometry

Attention-deficit hyperactivity disorder (ADHD) occurs in 5.9% of youth, impacting their health and social conditions often across their lifespan. Currently, early diagnosis is constrained by clinical complexity and limited resources of professionals to conduct evaluations. Scalable methods for ADHD screening are thus needed. Recently, digital epidemiology and biometry, such as the visual, emotional, or digit pathway, have examined brain dysfunction in ADHD individuals. However, whether biometry can support screening for ADHD symptoms using a multimodal tech system is still unknown. The EPIDIA4Kids study aims to create objective measures, i.e., biometrics, that will provide a comprehensive transdiagnostic picture of individuals with ADHD, aligning with current evidence for comorbid presentations. Twenty-four children aged 7 to 12 years performed gamified tasks on an unmodified tablet using the XAI4Kids® multimodal system, which allows extraction of biometrics (eye-, digit-, and emotion-tracking) from video and touch events using machine learning. Neuropsychological assessments and questionnaires were administered to provide ADHD-related measures. Each ADHD-related measure was evaluated with each biometric using linear mixed-effects models. In contrast to neuro-assessments, only two digit-tracking features had age and sex effects (p < 0.001) among the biometrics. Biometric constructs were predictors of working memory (p < 0.0001) and processing speed (p < 0.0001) and, to a lower extent, visuo-spatial skills (p = 0.003), inattention (p = 0.04), or achievement (p = 0.04), where multimodalities are crucial to capture several symptomatology dimensions. These results illustrate the potential of multimodality biometry gathered from a tablet as a viable and scalable transdiagnostic approach for screening ADHD symptomatology and improving accessibility to specialized professionals. Larger populations including clinically diagnosed ADHD will be needed for further validation.

For Myself or for Others? The Influence of Family Communication Patterns on Family Health History Communication and Online Health Information Seeking

With innovations in health information technology, there are increasing opportunities to search for health information online, with the potential to reduce health care costs and improve health outcomes for the family. This study aims to investigate how family communication processes influence online health information seeking for oneself (self OHIS) and for another person (surrogate OHIS). An online survey was conducted among 325 adults in China. The results showed that family conversation orientation was positively related to family health history (FHH) communication intentions, whereas family conformity orientation was negatively related to FHH communication intentions. Family conversation orientation was positively related to self and surrogate OHIS through the partial and masking mediation effects of FHH communication intentions, respectively. Family conformity orientation was negatively related to self OHIS through the full mediating effect of FHH communication intentions, while FHH communication intentions played a masking mediating role between conformity orientation and surrogate OHIS. Implications for extending family communication patterns research to health communication and cultural forces on OHIS are discussed.

Prediction by Young Autistic Children from Visual and Spoken Input

Recent theoretical accounts suggest that differences in the processing of probabilistic events underlie the core and associated traits of autism spectrum disorder (ASD). These theories hypothesize that autistic individuals are differentially impacted by disruptions in probabilistic input relative to neurotypical peers. According to this view, autistic individuals assign disproportionate weight to prediction errors such that novel input is overweighted relative to the aggregation of prior input; this is referred to as 'hyperplasticity' of learning. Prediction among autistic individuals has primarily been examined in nonverbal, visual contexts with older children and adults. The present study examined 32 autistic and 32 cognitively-matched neurotypical (NT) children's ability to generate predictions and adjust to changes in predictive relationships in auditory stimuli using two eye gaze tasks. In both studies, children were trained and tested on an auditory-visual cue which predicted the location of a reward stimulus. In Experiment 1 the cue was non-linguistic (instrumental sound) whereas in Experiment 2 the cue was linguistically-relevant (speaker gender). In both experiments, the cue-reward contingency was switched after the first block of trials, and predictive behavior was evaluated across a second block of trials. Analyses of children's looking behavior revealed similar performance in both groups on the non-linguistic task (Exp. 1). In the linguistically-relevant task (Exp. 2), predictive looking was less disrupted by the contingency switch for autistic children than NT children. Results suggest that autistic children may demonstrate hyperplastic learning in linguistically-relevant contexts, relative to NT peers.

Multi-dimensional predictors of first drinking initiation and regular drinking onset in adolescence: A prospective longitudinal study

Early adolescent drinking onset is linked to myriad negative consequences. Using the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) baseline to year 8 data, this study (1) leveraged best subsets selection and Cox Proportional Hazards regressions to identify the most robust predictors of adolescent first and regular drinking onset, and (2) examined the clinical utility of drinking onset in forecasting later binge drinking and withdrawal effects. Baseline predictors included youth psychodevelopmental characteristics, cognition, brain structure, family, peer, and neighborhood domains. Participants (N=538) were alcohol-naïve at baseline. The strongest predictors of first and regular drinking onset were positive alcohol expectancies (Hazard Ratios [HRs]=1.67-1.87), easy home alcohol access (HRs=1.62-1.67), more parental solicitation (e.g., inquiring about activities; HRs=1.72-1.76), and less parental control and knowledge (HRs=.72-.73). Robust linear regressions showed earlier first and regular drinking onset predicted earlier transition into binge and regular binge drinking (βs=0.57-0.95). Zero-inflated Poisson regressions revealed that delayed first and regular drinking increased the likelihood (Incidence Rate Ratios [IRR]=1.62 and IRR=1.29, respectively) of never experiencing withdrawal. Findings identified behavioral and environmental factors predicting temporal paths to youthful drinking, dissociated first from regular drinking initiation, and revealed adverse sequelae of younger drinking initiation, supporting efforts to delay drinking onset.

Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.

Age-related differences in functional connectivity associated with pain modulation

Growing evidence suggests that aging is associated with impaired endogenous pain modulation, and that this likely underlies the increased transition from acute to chronic pain in older individuals. Resting-state functional connectivity (rsFC) offers a valuable tool to examine the neural mechanisms behind these age-related changes in pain modulation. RsFC studies generally observe decreased within-network connectivity due to aging, but its relevance for pain modulation remains unknown. We compared rsFC within a set of brain regions involved in pain modulation between young and older adults and explored the relationship with the efficacy of distraction from pain. This revealed several age-related increases and decreases in connectivity strength. Importantly, we found a significant association between lower pain relief and decreased strength of three connections in older adults, namely between the periaqueductal gray and right insula, between the anterior cingulate cortex (ACC) and right insula, and between the ACC and left amygdala. These findings suggest that the functional integrity of the pain control system is critical for effective pain modulation, and that its function is compromised by aging.

Larger putamen in individuals at risk and with manifest bipolar disorder

BACKGROUND

Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

METHODS

In 410 male and female participants aged 17-35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

RESULTS

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

CONCLUSIONS

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

From the U.S. to Denmark and Beyond: It's Time to Reimagine the Use of Control Variables in Observational Research

Methodologists from a variety of social and behavioral sciences have called attention to misunderstandings, misclassifications, and misapplications of third variable "controls" in observational research. We are unaware, however, of a comprehensive discussion of these issues in the sexological literature. In this article, we attempt to detail several of the more important potential pitfalls within the context of a case study commentary on a recent Journal of Sex Research inquiry into Danish persons' pornography use, sexual satisfaction, and sexual behavior. We emphasize that our own (still limited) edification came only through personal error and chart an optimistic path forward wherein the current state of practice can be transformed into theoretical progress and innovation.

Increasing the representation of minoritized youth for inclusive and reproducible brain-behavior associations

Population neuroscience datasets allow researchers to estimate reliable effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals. We employ motion-ordering and motion-ordering+resampling (bagging) to test if these methods preserve functional MRI (fMRI) data in the Adolescent Brain Cognitive Development Study ( N = 5,733 ). Black and Hispanic youth exhibited excess head motion relative to data collected from White youth, and were discarded disproportionately when using conventional approaches. Both methods retained more than 99% of Black and Hispanic youth. They produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data. The motion-ordering and bagging methods are two feasible approaches that can enhance sample representation for testing brain-behavior associations and fulfill the promise of consortia datasets to produce generalizable effect sizes across diverse populations.

Alcohol attention bias modulates neural engagement during moral processing

The neurobiology of typical moral cognition involves the interaction of frontal, limbic, and temporoparietal networks. There is still much to be understood mechanistically about how moral processing is disrupted; such understanding is key to combating antisociality. Neuroscientific models suggest a key role for attention mechanisms in atypical moral processing. We hypothesized that attention-bias toward alcohol cues in alcohol use disorder (AUD) leads to a failure to properly engage with morally relevant stimuli, reducing moral processing. We recruited patients with AUD (n = 30) and controls (n = 30). During functional magnetic resonance imaging, participants viewed pairs of images consisting of a moral or neutral cue and an alcohol or neutral distractor. When viewing moral cues paired with alcohol distractors, individuals with AUD had lower medial prefrontal cortex engagement; this pattern was also seen for left amygdala in younger iAUDs. Across groups, individuals had less engagement of middle/superior temporal gyri. These findings provide initial support for AUD-related attention bias interference in sociomoral processing. If supported in future longitudinal and causal study designs, this finding carries potential societal and clinical benefits by suggesting a novel, leverageable mechanism and in providing a cognitive explanation that may help combat persistent stigma.

Reconfiguration of Structural and Functional Connectivity Coupling in Patient Subgroups With Adolescent Depression

IMPORTANCE

Adolescent major depressive disorder (MDD) is associated with serious adverse implications for brain development and higher rates of self-injury and suicide, raising concerns about its neurobiological mechanisms in clinical neuroscience. However, most previous studies regarding the brain alterations in adolescent MDD focused on single-modal images or analyzed images of different modalities separately, ignoring the potential role of aberrant interactions between brain structure and function in the psychopathology.

OBJECTIVE

To examine alterations of structural and functional connectivity (SC-FC) coupling in adolescent MDD by integrating both diffusion magnetic resonance imaging (MRI) and resting-state functional MRI data.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study recruited participants aged 10 to 18 years from January 2, 2020, to December 28, 2021. Patients with first-episode MDD were recruited from the outpatient psychiatry clinics at The First Affiliated Hospital of Chongqing Medical University. Healthy controls were recruited by local media advertisement from the general population in Chongqing, China. The sample was divided into 5 subgroup pairs according to different environmental stressors and clinical characteristics. Data were analyzed from January 10, 2022, to February 20, 2023.

MAIN OUTCOMES AND MEASURES

The SC-FC coupling was calculated for each brain region of each participant using whole-brain SC and FC. Primary analyses included the group differences in SC-FC coupling and clinical symptom associations between SC-FC coupling and participants with adolescent MDD and healthy controls. Secondary analyses included differences among 5 types of MDD subgroups: with or without suicide attempt, with or without nonsuicidal self-injury behavior, with or without major life events, with or without childhood trauma, and with or without school bullying.

RESULTS

Final analyses examined SC-FC coupling of 168 participants with adolescent MDD (mean [mean absolute deviation (MAD)] age, 16.0 [1.7] years; 124 females [73.8%]) and 101 healthy controls (mean [MAD] age, 15.1 [2.4] years; 61 females [60.4%]). Adolescent MDD showed increased SC-FC coupling in the visual network, default mode network, and insula (Cohen d ranged from 0.365 to 0.581; false discovery rate [FDR]-corrected P < .05). Some subgroup-specific alterations were identified via subgroup analyses, particularly involving parahippocampal coupling decrease in participants with suicide attempt (partial η2 = 0.069; 90% CI, 0.025-0.121; FDR-corrected P = .007) and frontal-limbic coupling increase in participants with major life events (partial η2 ranged from 0.046 to 0.068; FDR-corrected P < .05).

CONCLUSIONS AND RELEVANCE

Results of this cross-sectional study suggest increased SC-FC coupling in adolescent MDD, especially involving hub regions of the default mode network, visual network, and insula. The findings enrich knowledge of the aberrant brain SC-FC coupling in the psychopathology of adolescent MDD, underscoring the vulnerability of frontal-limbic SC-FC coupling to external stressors and the parahippocampal coupling in shaping future-minded behavior.

Sex-dependent differences in connectivity patterns are related to episodic memory recall

Previous studies have shown that females typically outperform males on episodic memory tasks. In this study, we investigated if (1) there are differences between males and females in their connectome characteristics, (2) if these connectivity patterns are associated with memory performance, and (3) if these brain connectome characteristics contribute to the differences in episodic memory performance between sexes. In a sample of 655 healthy young subjects (n = 391 females; n = 264 males), we derived brain network characteristics from diffusion-weighted imaging (DWI) data using models of crossing fibers within each voxel of the brain and probabilistic tractography (graph strength, shortest path length, global efficiency, and weighted transitivity). Group differences were analysed with linear models and mediation analyses were used to explore how connectivity patterns might relate to sex-dependent differences in memory performance. Our results show significant sex-dependent differences in weighted transitivity (d = 0.42), with males showing higher values. Further, we observed a negative association between weighted transitivity and memory performance (r = -0.12). Finally, these distinct connectome characteristics partially mediated the observed differences in memory performance (effect size of the indirect effect r = 0.02). Our findings indicate a higher interconnectedness in females compared to males. Additionally, we demonstrate that the sex-dependent differences in episodic memory performance can be partially explained by the differences in this connectome measure. These results further underscore the importance of sex-dependent differences in brain connectivity and their impact on cognitive function.

Resting-state network analysis of suicide attempt history in the UK Biobank

BACKGROUND

Prior research has identified altered brain structure and function in individuals at risk for self-directed violence thoughts and behaviors. However, these studies have largely utilized healthy controls and findings have been inconsistent. Thus, this study examined differences in resting-state functional network connectivity among individuals with lifetime suicide attempt(s) v. lifetime self-directed violence thoughts alone.

METHODS

Using data from the UK Biobank, this study utilized a series of linear regressions to compare individuals with lifetime suicide attempt(s) (n = 566) v. lifetime self-directed violence thoughts alone (n = 3447) on within- and between- network resting-state functional connectivity subnetworks.

RESULTS

There were no significant between-group differences for between-network, within-network, or whole-brain functional connectivity after adjusting for age, sex, ethnicity, and body mass index and performing statistical corrections for multiple comparisons. Resting-state network measures may not differentiate between individuals with lifetime suicide attempt(s) and lifetime self-directed violence thoughts alone.

CONCLUSIONS

Null findings diverge from results reported in smaller neuroimaging studies of suicide risk, but are consistent with null findings in other large-scale studies and meta-analyses. Strengths of the study include its large sample size and stringent control group. Future research on a wider array of imaging, genetic, and psychosocial risk factors can clarify relative contributions of individual and combined variables to suicide risk and inform scientific understanding of ideation-to-action framework.

The alteration of cortical microstructure similarity in drug-resistant epilepsy correlated with mTOR pathway genes

BACKGROUND

Drug-resistant epilepsy (DRE) is associated with distributed laminar disruptions due to cytoarchitectonic pathologies, which may be characterized by multimodal MRI approaches such as morphometric similarity networks (MSNs). However, the genetic and histological underpinning of MSN alterations in DRE remains poorly understood, hampering its clinical application.

METHODS

We enrolled 60 patients with DRE and 23 controls, acquiring T1 and diffusion spectrum imaging data with a 3.0T GE SIGNA Premier scanner. Morphometric similarity networks (MSNs) were constructed and analyzed to identify microstructure similarity differences between patients and controls. Subsequently, patient-specific MSN alteration patterns were associated with gene expression using the GAMBA tool, and layer-specific neuronal signature mapping were also applied. During these analyses, sex and age were adjusted as covariates and multiple comparisons corrections were applied when appropriate.

FINDINGS

We observed widespread MSN changes in patients with DRE and identified five distinct MSN alteration patterns. Major patterns presented pattern-specific associations with expressions of epilepsy-related genes, particularly involving the mTOR pathway. Histological analysis confirmed the presence of cortical microstructure changes in areas with MSN alterations and revealed cellular abnormalities matching the aforementioned genetic risks.

INTERPRETATION

Our findings highlight the potential of quantifying laminar-related microstructure integrity using MSN to uncover the cytoarchitectonic changes in the pathophysiology of DRE. This approach may facilitate the identification of genetic and histological underpinnings of MSN alterations in DRE, ultimately aiding in the development of targeted therapeutic strategies.

FUNDINGS

The National Natural Science Foundation of China, the Ministry of Science and Technology of the People's Republic of China, and the Beijing Municipal Health Commission.

Cortical structural differences following repeated ayahuasca use hold molecular signatures

Introduction

Serotonergic psychedelics such as ayahuasca are reported to promote both structural and functional neural plasticity via partial 5-HT2A agonism. However, little is known about how these molecular mechanisms may extend to repeated psychedelic administration in humans, let alone neuroanatomy. While early evidence suggests localised changes to cortical thickness in long-term ayahuasca users, it is unknown how such findings may be reflected by large-scale anatomical brain networks comprising cytoarchitecturally complex regions.

Methods

Here, we examined the relationship between cortical gene expression markers of psychedelic action and brain morphometric change following repeated ayahuasca usage, using high-field 7 Tesla neuroimaging data derived from 24 members of an ayahuasca-using church (Santo Daime) and case-matched controls.

Results

Using a morphometric similarity network (MSN) analysis, repeated ayahuasca use was associated with a spatially distributed cortical patterning of both structural differentiation in sensorimotor areas and de-differentiation in transmodal areas. Cortical MSN remodelling was found to be spatially correlated with dysregulation of 5-HT2A gene expression as well as a broader set of genes encoding target receptors pertinent to ayahuasca's effects. Furthermore, these associations were similarly interrelated with altered gene expression of specific transcriptional factors and immediate early genes previously identified in preclinical assays as relevant to psychedelic-induced neuroplasticity.

Conclusion

Taken together, these findings provide preliminary evidence that the molecular mechanisms of psychedelic action may scale up to a macroscale level of brain organisation in vivo. Closer attention to the role of cortical transcriptomics in structural-functional coupling may help account for the behavioural differences observed in experienced psychedelic users.

Brain structure, phenotypic and genetic correlates of reading performance

Reading is an evolutionarily recent development that recruits and tunes brain circuitry connecting primary- and language-processing regions. We investigated whether metrics of the brain's physical structure correlate with reading performance and whether genetic variants affect this relationship. To this aim, we used the Adolescent Brain Cognitive Development dataset (n = 9,013) of 9-10-year-olds and focused on 150 measures of cortical surface area (CSA) and thickness. Our results reveal that reading performance is associated with nine measures of brain structure including relevant regions of the reading network. Furthermore, we show that this relationship is partially mediated by genetic factors for two of these measures: the CSA of the entire left hemisphere and, specifically, of the left superior temporal gyrus CSA. These effects emphasize the complex and subtle interplay between genes, brain and reading, which is a partly heritable polygenic skill that relies on a distributed network.

Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models

We present generalized additive latent and mixed models (GALAMMs) for analysis of clustered data with responses and latent variables depending smoothly on observed variables. A scalable maximum likelihood estimation algorithm is proposed, utilizing the Laplace approximation, sparse matrix computation, and automatic differentiation. Mixed response types, heteroscedasticity, and crossed random effects are naturally incorporated into the framework. The models developed were motivated by applications in cognitive neuroscience, and two case studies are presented. First, we show how GALAMMs can jointly model the complex lifespan trajectories of episodic memory, working memory, and speed/executive function, measured by the California Verbal Learning Test (CVLT), digit span tests, and Stroop tests, respectively. Next, we study the effect of socioeconomic status on brain structure, using data on education and income together with hippocampal volumes estimated by magnetic resonance imaging. By combining semiparametric estimation with latent variable modeling, GALAMMs allow a more realistic representation of how brain and cognition vary across the lifespan, while simultaneously estimating latent traits from measured items. Simulation experiments suggest that model estimates are accurate even with moderate sample sizes.

Education differentiates cognitive performance and resting state fMRI connectivity in healthy aging

Objectives

In healthy aging, the way people cope differently with cognitive and neural decline is influenced by exposure to cognitively enriching life-experiences. Education is one of them, so that in general, the higher the education, the better the expected cognitive performance in aging. At the neural level, it is not clear yet how education can differentiate resting state functional connectivity profiles and their cognitive underpinnings. Thus, with this study, we aimed to investigate whether the variable education allowed for a finer description of age-related differences in cognition and resting state FC.

Methods

We analyzed in 197 healthy individuals (137 young adults aged 20-35 and 60 older adults aged 55-80 from the publicly available LEMON database), a pool of cognitive and neural variables, derived from magnetic resonance imaging, in relation to education. Firstly, we assessed age-related differences, by comparing young and older adults. Then, we investigated the possible role of education in outlining such differences, by splitting the group of older adults based on their education.

Results

In terms of cognitive performance, older adults with higher education and young adults were comparable in language and executive functions. Interestingly, they had a wider vocabulary compared to young adults and older adults with lower education. Concerning functional connectivity, the results showed significant age- and education-related differences within three networks: the Visual-Medial, the Dorsal Attentional, and the Default Mode network (DMN). For the DMN, we also found a relationship with memory performance, which strengthen the evidence that this network has a specific role in linking cognitive maintenance and FC at rest in healthy aging.

Discussion

Our study revealed that education contributes to differentiating cognitive and neural profiles in healthy older adults. Also, the DMN could be a key network in this context, as it may reflect some compensatory mechanisms relative to memory capacities in older adults with higher education.

Combining exercise with cognitive training and vitamin D3 to improve functional brain connectivity (FBC) in older adults with mild cognitive impairment (MCI). Results from the SYNERGIC trial

Changes in functional brain connectivity (FBC) may indicate how lifestyle modifications can prevent the progression to dementia; FBC identifies areas that are spatially separate but temporally synchronized in their activation and is altered in those with mild cognitive impairment (MCI), a prodromal state between healthy cognitive aging and dementia. Participants with MCI were randomly assigned to one of five study arms. Three times per week for 20-weeks, participants performed 30-min of (control) cognitive training, followed by 60-min of (control) physical exercise. Additionally, a vitamin D₃ (10,000 IU/pill) or a placebo capsule was ingested three times per week for 20-weeks. Using the CONN toolbox, we measured FBC change (Post-Pre) across four statistical models that collapsed for and/or included some or all study arms. We conducted Pearson correlations between FBC change and changes in physical and cognitive functioning. Our sample included 120 participants (mean age: 73.89 ± 6.50). Compared to the pure control, physical exercise (model one; p-False Discovery Rate (FDR) < 0.01 & < 0.05) with cognitive training (model two; p-FDR =  < 0.001), and all three interventions combined (model four; p-FDR =  < 0.01) demonstrated an increase in FBC between regions of the Default-Mode Network (i.e., hippocampus and angular gyrus). After controlling for false discovery rate, there were no significant correlations between change in connectivity and change in cognitive or physical function. Physical exercise alone appears to be as efficacious as combined interventional strategies in altering FBC, but implications for behavioral outcomes remain unclear.

Task fMRI paradigms may capture more behaviorally relevant information than resting-state functional connectivity

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design. We decomposed the task fMRI time course of each task into the task model fit (the fitted time course of the task condition regressors from the single-subject general linear model) and the task model residuals, calculated their respective FC, and compared the behavioral prediction performance of these FC estimates to resting-state FC and the original task-based FC. The FC of the task model fit was better than the FC of the task model residual and resting-state FC at predicting a measure of general cognitive ability or two measures of performance on the fMRI tasks. The superior behavioral prediction performance of the FC of the task model fit was content-specific insofar as it was only observed for fMRI tasks that probed similar cognitive constructs to the predicted behavior of interest. To our surprise, the task model parameters, the beta estimates of the task condition regressors, were equally if not more predictive of behavioral differences than all FC measures. These results showed that the observed improvement of behavioral prediction afforded by task-based FC was largely driven by the FC patterns associated with the task design. Together with previous studies, our findings highlighted the importance of task design in eliciting behaviorally meaningful brain activation and FC patterns.

Decreased cortical gyrification and surface area in the left medial parietal cortex in patients with treatment-resistant and ultratreatment-resistant schizophrenia

AIM

Validating the vulnerabilities and pathologies underlying treatment-resistant schizophrenia (TRS) is an important challenge in optimizing treatment. Gyrification and surface area (SA), reflecting neurodevelopmental features, have been linked to genetic vulnerability to schizophrenia. The aim of this study was to identify gyrification and SA abnormalities specific to TRS.

METHODS

We analyzed 3T magnetic resonance imaging findings of 24 healthy controls (HCs), 20 responders to first-line antipsychotics (FL-Resp), and 41 patients with TRS, including 19 clozapine responders (CLZ-Resp) and 22 FL- and clozapine-resistant patients (patients with ultratreatment-resistant schizophrenia [URS]). The local gyrification index (LGI) and associated SA were analyzed across groups. Diagnostic accuracy was verified by receiver operating characteristic curve analysis.

RESULTS

Both CLZ-Resp and URS had lower LGI values than HCs (P = 0.041, Hedges g [g_H ] = 0.75; P = 0.013, g_H  = 0.96) and FL-Resp (P = 0.007, g_H  = 1.00; P = 0.002, g_H  = 1.31) in the left medial parietal cortex (Lt-MPC). In addition, both CLZ-Resp and URS had lower SA in the Lt-MPC than FL-Resp (P < 0.001, g_H  = 1.22; P < 0.001, g_H  = 1.75). LGI and SA were positively correlated in non-TRS (FL-Resp) (ρ = 0.64, P = 0.008) and TRS (CLZ-Resp + URS) (ρ = 0.60, P < 0.001). The areas under the receiver operating characteristic curve for non-TRS versus TRS with LGI and SA in the Lt-MPC were 0.79 and 0.85, respectively. SA in the Lt-MPC was inversely correlated with negative symptoms (ρ = -0.40, P = 0.018) and clozapine plasma levels (ρ = -0.35, P = 0.042) in TRS.

CONCLUSION

LGI and SA in the Lt-MPC, a functional hub in the default-mode network, were abnormally reduced in TRS compared with non-TRS. Thus, altered LGI and SA in the Lt-MPC might be structural features associated with genetic vulnerability to TRS.

Association of Maternal and Child Anemia With Brain Structure in Early Life in South Africa

Importance

Anemia affects millions of pregnant women and their children worldwide, particularly in low- and middle-income countries. Although anemia in pregnancy is a well-described risk factor for cognitive development, the association with child brain structure is poorly understood.

Objective

To explore the association of anemia during pregnancy and postnatal child anemia with brain structure in early life.

Design, Setting, and Participants

This neuroimaging nested cohort study was embedded within the Drakenstein Child Health Study (DCHS), a population-based birth cohort in South Africa. Pregnant individuals were enrolled into the DCHS between 2012 and 2015 from 2 clinics in a periurban setting. Mother-child pairs were assessed prospectively; follow-up is ongoing. A subgroup of children had brain magnetic resonance imaging (MRI) at age 2 to 3 years from 2015 to 2018. This study focused on the 147 pairs with structural neuroimaging and available hemoglobin data. Data analyses were conducted in 2021 and 2022.

Exposures

Mothers had hemoglobin measurements during pregnancy, and a subgroup of children had hemoglobin measurements during early life. Anemia was classified as hemoglobin levels less than 11 g/dL based on World Health Organization guidelines; children younger than 6 months were classified using local guidelines.

Main Outcomes and Measures

Child brain volumes of global, subcortical, and corpus callosum structures were quantified using T1-weighted MRI. Linear regression models were used to analyze the associations between maternal and child anemia with child brain volumes, accounting for potential confounders.

Results

Of 147 children (mean [SD] age at MRI, 34 [2] months; 83 [56.5%] male) with high-resolution MRI scans, prevalence of maternal anemia in pregnancy was 31.3% (46 of 147; median [IQR] gestation of measurement: 13 [9-20] weeks). Maternal anemia during pregnancy was significantly associated with smaller volumes of the child caudate bilaterally (adjusted percentage difference, -5.30% [95% CI, -7.01 to -3.59]), putamen (left hemisphere: -4.33% [95% CI, -5.74 to -2.92]), and corpus callosum (-7.75% [95% CI, -11.24 to -4.26]). Furthermore, antenatal maternal hemoglobin levels were also associated with brain volumes in the caudate (left hemisphere: standardized β = 0.15 [95% CI, 0.02 to 0.28]; right hemisphere: β = 0.15 [95% CI, 0.02 to 0.27]), putamen left hemisphere (β = 0.21 [95% CI, 0.07 to 0.35]), and corpus callosum (β = 0.24 [95% CI, 0.09 to 0.39]). Prevalence of child anemia was 52.5% (42 of 80; median [IQR] age of measurement: 8.0 [2.7 to 14.8] months). Child anemia was not associated with brain volumes, nor did it mediate the association of maternal anemia during pregnancy with brain volumes.

Conclusions and Relevance

In this cohort study, anemia in pregnancy was associated with altered child brain structural development. Given the high prevalence of antenatal maternal anemia worldwide, these findings suggest that optimizing interventions during pregnancy may improve child brain outcomes.

Comparison of brain microstructure alterations on diffusion kurtosis imaging among Alzheimer’s disease, mild cognitive impairment, and cognitively normal individuals

Objective

Our study aimed to explore the differences in brain microstructure in patients with Alzheimer’s disease (AD) and with mild cognitive impairment (MCI) and in individuals with normal cognition using diffusion kurtosis imaging (DKI) to identify a potential non-invasive biomarker of AD.

Materials and methods

A total of 61 subjects were included in our study, including 20 subjects diagnosed with AD, 21 patients diagnosed with amnestic MCI, and 20 cognitively normal individuals. We acquired magnetic resonance imaging (MRI) scans, and DKI images were processed. Twelve regions of interest were drawn, and various parameters were measured and analyzed using SPSS version 11.0 software.

Results

Comparative analysis showed that differences in brain regions in terms of mean diffusion (MD) and mean kurtosis (MK) between groups were the most marked. Precuneus MD, temporal MK, precuneus MK, and hippocampal MK were significantly correlated with neuropsychological test scores. Hippocampal MK showed the strongest correlation with the medial temporal lobe atrophy score (r = −0.510), and precuneus MD had the strongest correlation with the Koedam score (r = 0.463). The receiver operating curve analysis revealed that hippocampal MK exhibited better diagnostic efficacy than precuneus MD for comparisons between any group pair.

Conclusion

DKI is capable of detecting differences in brain microstructure between patients with AD, patients with MCI, and cognitively normal individuals. Moreover, it compensates for the deficiencies of conventional MRI in detecting pathological changes in microstructure before the appearance of macroscopic atrophy. Hippocampus MK was the most sensitive single parameter map for differentiating patients with AD, patients with MCI, and cognitively normal individuals.

"Nothing to see here": No structural brain differences as a function of the Big Five personality traits from a systematic review and meta-analysis

Personality reflects social, affective, and cognitive predispositions that emerge from genetic and environmental influences. Contemporary personality theories conceptualize a Big Five Model of personality based on the traits of neuroticism, extraversion, agreeableness, conscientiousness, and openness to experience. Starting around the turn of the millennium, neuroimaging studies began to investigate functional and structural brain features associated with these traits. Here, we present the first study to systematically evaluate the entire published literature of the association between the Big Five traits and three different measures of brain structure. Qualitative results were highly heterogeneous, and a quantitative meta-analysis did not produce any replicable results. The present study provides a comprehensive evaluation of the literature and its limitations, including sample heterogeneity, Big Five personality instruments, structural image data acquisition, processing, and analytic strategies, and the heterogeneous nature of personality and brain structures. We propose to rethink the biological basis of personality traits and identify ways in which the field of personality neuroscience can be strengthened in its methodological rigor and replicability.

Disorganized attachment behaviors in infancy as predictors of brain morphology and peer rejection in late childhood

Studies show robust links between disorganized attachment in infancy and socioemotional maladjustment in childhood. Little is known, however, about the links between disorganized attachment and brain development, and whether attachment-related differences in brain morphology translate into meaningful variations in child socioemotional functioning. This study examined the links between infants' disorganized attachment behaviors toward their mothers, whole-brain regional grey matter volume and thickness, and peer rejection in late childhood. Thirty-three children and their mothers took part in this study. The Strange Situation Procedure was used to assess mother-infant attachment when infants were 18 months old. Magnetic resonance imaging was performed when they were 10 years old to assess cortical thickness and grey matter volumes. Children and teachers reported on peer rejection 1 year later, as an indicator of socioemotional maladjustment. Results indicated that disorganized attachment was not associated with grey matter volumes. However, children who exhibited more disorganized attachment behaviors in infancy had significantly thicker cortices in bilateral middle and superior frontal gyri, and extending to the inferior frontal gyrus, as well as the orbitofrontal and insular cortices in the right hemisphere in late childhood. Moreover, children with thicker cortices in these regions experienced greater peer rejection, as rated by themselves and their teachers. Although preliminary, these results are the first to indicate that disorganized attachment may play a role in cortical thickness development and that changes in cortical thickness are associated with differences in child socioemotional functioning.

Altered Surface Area Covariance in the Mentalizing Network in Schizophrenia: Insight Into Theory of Mind Processing

BACKGROUND

Theory of mind (ToM), the cognitive capacity to attribute mental states to self and others, is robustly affected in schizophrenia. The neural substrates of ToM impairment have been largely studied with functional imaging, but little is known about structural abnormalities. We compared structural covariance (between-subjects correlations of brain regional measures) of magnetic resonance imaging-based cortical surface area between patients with schizophrenia and healthy control subjects and between schizophrenia subgroups based on the patients' ToM ability to examine ToM-specific effects on structural covariance in schizophrenia.

METHODS

T1-weighted structural images were acquired on a 3T magnetic resonance imaging scanner, and ToM was assessed with the Hinting Task for 104 patients with schizophrenia and 69 healthy control subjects. The sum of surface area was computed for 12 regions of interest selected and compared between groups to examine structural covariance within the often reported mentalizing network: rostral and caudal middle frontal gyrus, inferior parietal lobule, precuneus, and middle and superior temporal gyrus. High and low ToM groups were defined using a median split on the Hinting Task.

RESULTS

Cortical surface contraction was observed in the schizophrenia group, predominantly in temporoparietal regions. Patients with schizophrenia also exhibited significantly stronger covariance between the right rostral middle frontal gyrus and the right superior temporal gyrus than control subjects (r = 4.015; p < .001). Direct comparisons between high and low ToM subgroups revealed stronger contralateral frontotemporal covariances in the low ToM group.

CONCLUSIONS

Our results provide evidence for structural changes underlying ToM impairments in schizophrenia that need to be confirmed to develop new therapeutic perspectives.

The impact of prenatal alcohol exposure on gray matter volume and cortical surface area of 2 to 3-year-old children in a South African birth cohort

BACKGROUND

There is a growing literature that demonstrates the effects of prenatal alcohol exposure (PAE) on brain development in school-aged children. Less is known, however, on how PAE impacts the brain early in life. We investigated the effects of PAE and child sex on subcortical gray matter volume, cortical surface area (CSA), cortical volume (CV), and cortical thickness (CT) in children aged 2 to 3 years.

METHODS

The sample was recruited as a nested cross-sectional substudy of the Drakenstein Child Health Study. Images from T1-weighted magnetic resonance imaging were acquired on 47 alcohol-exposed and 124 control children (i.e., with no or minimal alcohol exposure), aged 2 to 3 years, some of whom were scanned as neonates. Brain images were processed through automated processing pipelines using FreeSurfer version 6.0. Subcortical and a priori selected cortical regions of interest were compared.

RESULTS

Subcortical volume analyses revealed a PAE by child sex interaction for bilateral putamen volumes (Left: p = 0.02; Right: p = 0.01). There was no PAE by child sex interaction effect on CSA, CV, and CT. Analyses revealed an impact of PAE on CSA (p = 0.04) and CV (p = 0.04), but not CT in this age group. Of note, the inferior parietal gyrus CSA was significantly smaller in children with PAE compared to control children.

CONCLUSIONS

Findings from this subgroup scanned at age 2 to 3 years build on previously described subcortical volume differences in neonates from this cohort. Findings suggest that PAE persistently affects gray matter development through the critical early years of life. The detectable influence of PAE on brain structure at this early age further highlights the importance of brain imaging studies on the impact of PAE on the young developing brain.

Neural and behavioral correlates of sexual stimuli anticipation point to addiction-like mechanisms in compulsive sexual behavior disorder

BACKGROUND AND AIMS

Compulsive sexual behavior disorder (CSBD) is characterized by persistent patterns of failure to control sexual impulses resulting in repetitive sexual behavior, pursued despite adverse consequences. Despite previous indications of addiction-like mechanisms and the recent impulse-control disorder classification in the International Classification of Diseases (ICD-11), the neurobiological processes underlying CSBD are unknown.

METHODS

We designed and applied a behavioral paradigm aimed at disentangling processes related to anticipation and viewing of erotic stimuli. In 22 male CSBD patients (age: M = 38.7, SD = 11.7) and 20 healthy male controls (HC, age: M = 37.6, SD = 8.5), we measured behavioral responses and neural activity during functional magnetic resonance imaging (fMRI). The main outcomes were response time differences between erotic and non-erotic trials and ventral striatum (VS) activity during anticipation of visual stimuli. We related these outcomes with each other, to CSBD diagnosis, and symptom severity.

RESULTS

We found robust case-control differences on behavioral level, where CSBD patients showed larger response time differences between erotic and non-erotic trials than HC. The task induced reliable main activations within each group. While we did not observe significant group differences in VS activity, VS activity during anticipation correlated with response time differences and self-ratings for anticipation of erotic stimuli.

DISCUSSION AND CONCLUSIONS

Our results support the validity and applicability of the developed task and suggest that CSBD is associated with altered behavioral correlates of anticipation, which were associated with ventral striatum activity during anticipation of erotic stimuli. This supports the idea that addiction-like mechanisms play a role in CSBD.

An analysis of neuroscience and psychiatry papers published from 2009 and 2019 outlines opportunities for increasing discovery of sex differences

Sex differences exist in many neurological and psychiatric diseases, but these have not always been addressed adequately in research. In order to address this, it is necessary to consider how sex is incorporated into the design (e.g. using a balanced design) and into the analyses (e.g. using sex as a covariate) in the published literature. We surveyed papers published in 2009 and 2019 across six journals in neuroscience and psychiatry. In this sample, we find a 30% increase in the percentage of papers reporting studies that included both sexes in 2019 compared with 2009. Despite this increase, in 2019 only 19% of papers in the sample reported using an optimal design for discovery of possible sex differences, and only 5% of the papers reported studies that analysed sex as a discovery variable. We conclude that progress to date has not been sufficient to address the importance of sex differences in research for discovery and therapeutic potential for neurological and psychiatric disease.

Sex differences occur in many neurological and psychiatric diseases, and yet research is not always designed optimally to identify these. Here the authors perform a study of how sex was incorporated into the design and analyses of papers published six journals in neuroscience and psychiatry in 2009 compared with 2019.

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers

Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

The impacts of HIV infection, age, and education on functional brain networks in adults with HIV

HIV-associated neurocognitive disorders (HAND) remain highly prevalent in people with HIV (PWH). Studies suggested that certain sociodemographic factors are associated with the risk of HAND in PWH. Here we investigated the impact of HIV infection and demographics on functional brain networks. One run of 8.5 min resting state functional MRI (fMRI) data was collected from 101 PWH (41-70 years old) and 40 demographically comparable controls. Functional connectivity (FC) was calculated using average wavelet coherence. The impact of demographic factors on FCs was investigated using canonical correlation analysis (CCA). Wavelet coherence analysis revealed a reduced within-network connectivity in the dorsal somatomotor network (dSMN), along with a reduced between-network connectivity between dSMN and medial temporal lobe (MTL) in PWH (compared to controls). Across all participants, CCA revealed that older age and HIV infection had negative impacts on network connectivity measures (mainly reduced within- and between-network FCs), whereas education had an opposite effect. In addition, being female at birth or a member of a minority ethnic/racial group was also associated with network disruptions. Our data suggested that advanced age and HIV infection are risk factors for functional brain network disruptions, whereas higher educational attainment was linked to better preserved functional network connectivity.

Structural brain differences do not mediate the relations between sex and personality or psychopathology

INTRODUCTION

Males and females tend to exhibit small but reliable differences in personality traits and indices of psychopathology that are relatively stable over time and across cultures. Previous work suggests that sex differences in brain structure account for differences in domains of cognition.

METHODS

We used data from the Human Connectome Project (N = 1098) to test whether sex differences in brain morphometry account for observed differences in the personality traits neuroticism and agreeableness, as well as symptoms of internalizing and externalizing psychopathology. We operationalized brain morphometry in three ways: omnibus measures (e.g., total gray matter volume), Glasser regions defined through a multi-modal parcellation approach, and Desikan regions defined by structural features of the brain.

RESULTS

Most expected sex differences in personality, psychopathology, and brain morphometry were observed, but the statistical mediation analyses were null: sex differences in brain morphometry did not account for sex differences in personality or psychopathology.

CONCLUSIONS

Men and women tend to exhibit meaningful differences in personality and psychopathology, as well as in omnibus morphometry and regional morphometric differences as defined by the Glasser and Desikan atlases, but these morphometric differences appear unrelated to the psychological differences.

The Use of Neuroimaging for Predicting Sumatriptan Treatment Response in Patients With Migraine

Objectives

To identify the neuroimaging predictors for the responsiveness of patients to sumatriptan and use an independent cohort for external validation.

Methods

Structuralized headache questionnaire and 3-Tesla brain magnetic resonance imaging were performed in migraine patients. Regional brain volumes were automatically calculated using FreeSurfer version 6.0, including bilateral amygdala, anterior cingulated cortex, caudate, putamen, precuneus, orbitofrontal cortex, superior frontal gyri, middle frontal gyri, hippocampus, and parahippocampus. A sumatriptan-responder was defined as headache relief within 2 h after the intake of sumatriptan in at least two out of three treated attacks. We constructed a prediction model for sumatriptan response using the regional brain volume and validated it with an independent cohort of migraine patients.

Results

A total of 105 migraine patients were recruited, including 73 sumatriptan responders (69.5%) and 32 (30.5%) non-responders. We divided the migraine patients into derivation (n = 73) and validation cohorts (n = 32). In the derivation cohort, left hippocampal volume was larger in sumatriptan responders (responders vs. non-responders: 3,929.5 ± 403.1 vs. 3,611.0 ± 389.9 mm³, p = 0.002), and patients with a larger left hippocampal volume had a higher response rate to sumatriptan (>4,036.2 vs. ≤4,036.2 mm³: 92.0 vs. 56.3%, p = 0.001). Based on the findings, we constructed a prediction model using the cutoff value of 4,036.2 mm³, and we found that patients with a left hippocampal volume >4,032.6 mm³ had a higher response rate to sumatriptan than those with a left hippocampal volume ≤4,032.6 mm³ (84.6 vs. 42.1%, odds ratio [OR] = 7.6 [95% confidence interval = 1.3–44.0], p = 0.013) in the validation cohort.

Conclusion

Our study showed that left hippocampal volume is helpful to identify sumatriptan non-responders. This proof-of-concept study shows that left hippocampal volume could be used to predict the treatment response to sumatriptan in migraine patients.

Cortical thickness across the cingulate gyrus in schizophrenia and its association to illness duration and memory performance

Schizophrenia has been associated with structural brain abnormalities and cognitive deficits that partly change during the course of illness. In the present study, cortical thickness in five subregions of the cingulate gyrus was assessed in 44 patients with schizophrenia-spectrum disorder and 47 control persons and related to illness duration and memory capacities. In the patients group, cortical thickness was increased in the posterior part of the cingulate gyrus and related to illness duration whereas cortical thickness was decreased in anterior parts unrelated to illness duration. In contrast, cortical thickness was related to episodic and working memory performance only in the anterior but not posterior parts of the cingulate gyrus. Our finding of a posterior cingulate increase may point to either increased parietal communication that is accompanied by augmented neural plasticity or to effects of altered neurodegenerative processes in schizophrenia.

How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses

COVID-19 research has relied heavily on convenience-based samples, which-though often necessary-are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study ( www.icarestudy.com ). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended.

The Relationship Between Grey Matter Volume and Clinical and Functional Outcomes in People at Clinical High Risk for Psychosis

Objective

To examine the association between baseline alterations in grey matter volume (GMV) and clinical and functional outcomes in people at clinical high risk (CHR) for psychosis.

Methods

265 CHR individuals and 92 healthy controls were recruited as part of a prospective multi-center study. After a baseline assessment using magnetic resonance imaging (MRI), participants were followed for at least two years to determine clinical and functional outcomes, including transition to psychosis (according to the Comprehensive Assessment of an At Risk Mental State, CAARMS), level of functioning (according to the Global Assessment of Functioning), and symptomatic remission (according to the CAARMS). GMV was measured in selected cortical and subcortical regions of interest (ROI) based on previous studies (ie orbitofrontal gyrus, cingulate gyrus, gyrus rectus, inferior temporal gyrus, parahippocampal gyrus, striatum, and hippocampus). Using voxel-based morphometry, we analysed the relationship between GMV and clinical and functional outcomes.

Results

Within the CHR sample, a poor functional outcome (GAF < 65) was associated with relatively lower GMV in the right striatum at baseline (P < .047 after Family Wise Error correction). There were no significant associations between baseline GMV and either subsequent remission or transition to psychosis.

Conclusions

In CHR individuals, lower striatal GMV was associated with a poor level of overall functioning at follow-up. This finding was not related to effects of antipsychotic or antidepressant medication. The failure to replicate previous associations between GMV and later psychosis onset, despite studying a relatively large sample, is consistent with the findings of recent large-scale multi-center studies.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.

Intrinsic neural network dynamics in catatonia

Catatonia is a transnosologic psychomotor syndrome with high prevalence in schizophrenia spectrum disorders (SSD). There is mounting neuroimaging evidence that catatonia is associated with aberrant frontoparietal, thalamic and cerebellar regions. Large-scale brain network dynamics in catatonia have not been investigated so far. In this study, resting-state fMRI data from 58 right-handed SSD patients were considered. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). Group spatial independent component analysis was carried out with a multiple analysis of covariance (MANCOVA) approach to estimate and test the underlying intrinsic components (ICs) in SSD patients with (NCRS total score ≥ 3; n = 30) and without (NCRS total score = 0; n = 28) catatonia. Functional network connectivity (FNC) during rest was calculated between pairs of ICs and transient changes in connectivity were estimated using sliding windowing and clustering (to capture both static and dynamic FNC). Catatonic patients showed increased static FNC in cerebellar networks along with decreased low frequency oscillations in basal ganglia (BG) networks. Catatonic patients had reduced state changes and dwelled more in a state characterized by high within-network correlation of the sensorimotor, visual, and default-mode network with respect to noncatatonic patients. Finally, in catatonic patients according to DSM-IV-TR (n = 44), there was a significant correlation between increased within FNC in cortico-striatal state and NCRS motor scores. The data support a neuromechanistic model of catatonia that emphasizes a key role of disrupted sensorimotor network control during distinct functional states.

Meaningful associations in the adolescent brain cognitive development study

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and children's health in the United States. A cohort of n = 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

Caudate nucleus volume mediates the link between glutamatergic neurotransmission and problematic smartphone use in youth

BACKGROUND AND AIMS

Problematic smartphone use (PSU) is growing rapidly among teens. It has similar presentations as other behavioral addictions in terms of excessive use, impulse control problems, and negative consequences. However, the underlying neurobiological mechanisms remain undiscovered. We hypothesized that structural changes in the striatum might serve as an important link between alteration in glutamate signaling and development of PSU.

METHODS

Among 88 participants, twenty (F:M, 12:8; age 16.2 ± 1.1) reported high scores in the smartphone addiction proneness scale (SAPS) with a cut-off score of 42; the other 68 (F:M, 19:49; age 15.3 ± 1.7) comprised the control group. Sociodemographic data and depression, anxiety, and impulsivity traits were measured. Striatal volumes (caudate, putamen, and nucleus accumbens) were estimated from T1 imaging data. Serum glutamate levels were estimated from peripheral blood samples. Group comparisons of each data were performed after controlling for age and gender. Mediation analyses were conducted to test the indirect effects of glutamate level alteration on PSU through striatal volumetric alteration.

RESULTS

The PSU group showed a decrease in both caudate volumes than the control group. Left caudate volume was positively correlated with serum glutamate level, and negatively with impulsivity traits and SAPS scores. The mediation model revealed a significant indirect effect of serum glutamate on SAS scores through the reduced left caudate volume.

DISCUSSION AND CONCLUSIONS

This study suggests that altered glutamatergic neurotransmission may be associated with PSU among teens, possibly through reduced left caudate volume. Current findings might support neural mechanisms of smartphone addiction.