Association of Neural Connectome With Early Experiences of Abuse in Adults

Shedding Light on the Aftermath: Childhood Maltreatment's Role in Modifying the Association Between Recent Life Stress and Resting-State Network Connectivity

Childhood maltreatment has been demonstrated to impact brain development. However, whether childhood maltreatment can influence the effects of recent stress on brain networks remains unclear. This study aimed to investigate whether childhood maltreatment moderates the longitudinal relationship between recent life stress and within- and between-network connectivity in key brain networks, including the anterior salience (ASN), central executive (CEN), default mode (DMN), and emotional regulation network (ERN). A cohort of 172 individuals from the Neuroscience in Psychiatry Network (NSPN) underwent MRI scans at two specific time points and undertook evaluations of childhood maltreatment and recent life stress. The results showed that childhood abuse moderated the association of recent life stress with the within-network connectivity of ASN and ERN but not DMN and CEN. Furthermore, recent life stress significantly interacted with childhood abuse to be associated with the between-network connectivity of ASN-DMN, ASN-CEN, ASN-ERN, DMN-ERN and CEN-ERN. Overall, among youth exposed to higher degrees of childhood abuse, greater recent life stress was longitudinally associated with increased network connectivity. Understanding these interactions can provide valuable insights for developing prevention strategies and interventions aimed at mitigating the lasting impact of childhood maltreatment on brain development and overall well-being.

The neural connectome of suicidality in adults with mood and anxiety disorders

Although suicide risk is a major public health issue, attempts to understand the neural basis of suicidality have been limited by small sample sizes and a focus on specific psychiatric disorders. This sample comprised 579 participants, of whom 428 had a psychiatric disorder (depression, anxiety or stress-related disorder) and 151 were non-psychiatric controls. All participants underwent structured clinical interviews, including an assessment of suicidality in the past month, and completed a functional magnetic resonance imaging scan. There were 238 (41.1%) participants who met criteria for suicidality and 341 (58.9%) were non-suicidal. Task-derived functional connectivity was calculated for 436 brain regions, comprising 8 intrinsic connectivity networks. Participants who were suicidal had decreased connectivity in a network of 143 connections across 86 brain regions. This pattern was characterized primarily by decreased connectivity within the visual, somatomotor and salience networks, between these networks, and also with the default mode and limbic networks. By adopting a transdiagnostic approach with a very large sample of individuals with mood disorders, anxiety and stress and non-psychiatric participants, this study highlights the hypoconnectivity that characterizes suicidality and points to altered connectivity within and between key networks involved in emotional, sensory and cognitive processes that are implicated in suicidal risk.

Neuroimaging signatures and a deep learning modeling for early diagnosing and predicting non-pharmacological therapy success for subclinical depression comorbid sleep disorders in college students

Objective

College students with subclinical depression often experience sleep disturbances and are at high risk of developing major depressive disorder without early intervention. Clinical guidelines recommend non-pharmacotherapy as the primary option for subclinical depression with comorbid sleep disorders (sDSDs). However, the neuroimaging mechanisms and therapeutic responses associated with these treatments are poorly understood. Additionally, the lack of an early diagnosis and therapeutic effectiveness prediction model hampers the clinical promotion and acceptance of non-pharmacological interventions for subclinical depression.

Methods

This study involved pre- and post-treatment resting-state functional Magnetic Resonance Imaging (rs-fMRI) and clinical data from a multicenter, single-blind, randomized clinical trial. The trial included 114 first-episode, drug-naïve university students with subclinical depression and comorbid sleep disorders (sDSDs; Mean age=22.8±2.3 years; 73.7% female) and 93 healthy controls (HCs; Mean age=22.2±1.7 years; 63.4% female). We examined altered functional connectivity (FC) and brain network connective mode related to subregions of Default Mode Network (sub-DMN) using seed-to-voxel analysis before and after six weeks of non-pharmacological antidepressant treatment. Additionally, we developed an individualized diagnosing and therapeutic effect predicting model to realize early recognition of subclinical depression and provide objective suggestions to select non-pharmacological therapy by using the newly proposed Hierarchical Functional Brain Network (HFBN) with advanced deep learning algorithms within the transformer framework.

Results

Neuroimaging responses to non-pharmacologic treatments are characterized by alterations in functional connectivity (FC) and shifts in brain network connectivity patterns, particularly within the sub-DMN. At baseline, significantly increased FC was observed between the sub-DMN and both Executive Control Network (ECN) and Dorsal Attention Network (DAN). Following six weeks of non-pharmacologic intervention, connectivity patterns primarily shifted within the sub-DMN and ECN, with a predominant decrease in FCs. The HFBN model demonstrated superior performance over traditional deep learning models, accurately predicting therapeutic outcomes and diagnosing subclinical depression, achieving cumulative scores of 80.47% for sleep quality prediction and 84.67% for depression prediction, along with an overall diagnostic accuracy of 82.34%.

Conclusions

Two-scale neuroimaging signatures related to the sub-DMN underlying the antidepressant mechanisms of non-pharmacological treatments for subclinical depression. The HFBN model exhibited supreme capability in early diagnosing and predicting non-pharmacological treatment outcomes for subclinical depression, thereby promoting objective clinical psychological treatment decision-making.

The impact of psychosocial adversity on brain and behaviour: an overview of existing knowledge and directions for future research

Environmental experiences play a critical role in shaping the structure and function of the brain. Its plasticity in response to different external stimuli has been the focus of research efforts for decades. In this review, we explore the effects of adversity on brain's structure and function and its implications for brain development, adaptation, and the emergence of mental health disorders. We are focusing on adverse events that emerge from the immediate surroundings of an individual, i.e., microenvironment. They include childhood maltreatment, peer victimisation, social isolation, affective loss, domestic conflict, and poverty. We also take into consideration exposure to environmental toxins. Converging evidence suggests that different types of adversity may share common underlying mechanisms while also exhibiting unique pathways. However, they are often studied in isolation, limiting our understanding of their combined effects and the interconnected nature of their impact. The integration of large, deep-phenotyping datasets and collaborative efforts can provide sufficient power to analyse high dimensional environmental profiles and advance the systematic mapping of neuronal mechanisms. This review provides a background for future research, highlighting the importance of understanding the cumulative impact of various adversities, through data-driven approaches and integrative multimodal analysis techniques.

Do aversive well-being comparisons mediate the effects of childhood adversity on anxiety and depression?

BACKGROUND

Childhood adversity (CA) is strongly associated with depression and anxiety in later life. Many adults with a history of CA may have internalized an insecure self-concept, which may contribute to negative evaluations of one's current well-being relative to different standards. Yet, there is lack of research on well-being comparisons in adults with a history of CA.

OBJECTIVE

We examined aversive well-being comparisons (i.e., comparisons threatening the comparer's motives) in the context of CA and their predictive value in depression and anxiety beyond self-esteem, emotion regulation, and external control beliefs. Further, we investigated whether well-being comparison processes mediate the relationship between CA and depression and anxiety.

PARTICIPANTS AND SETTING

We conducted a two-wave longitudinal study with 942 adult participants (mean age: 31.56 years, SD = 10.49, 18-75 years).

METHODS

Participants completed measures of CA, aversive well-being comparisons (social, temporal, counterfactual, and criteria-based comparisons), self-esteem, emotion regulation, and locus of control at two time points, three months apart.

RESULTS

CA was significantly linked to more frequent aversive well-being comparisons. These comparisons were associated with greater discrepancies relative to the comparison standard and a more negative affective impact, ultimately contributing to higher levels of subsequent anxiety and depression symptoms. Comparison frequency emerged as key mediator, highlighting potential pathways through which CA affects adult mental health. These associations emerged despite controlling for established variables in this context, namely self-esteem, emotion regulation, and external locus of control.

CONCLUSION

Our findings underscore the unique importance of aversive well-being comparisons in individuals with a history of CA.

Global topology of human connectome is insensitive to early life environments - A prospective longitudinal study of the general population

The widely acknowledged detrimental impact of early adversity on child development has driven efforts to understand the underlying mechanisms that may mediate these effects within the developing brain. Recent efforts have begun to move beyond associating adversity with the morphology of individual brain regions towards determining if and how adversity might shape their interconnectivity. However, whether adversity effects a global shift in the organisation of whole-brain networks remains unclear. In this study, we assessed this possibility using parental questionnaire and diffusion imaging data from The Avon Longitudinal Study of Parents and Children (ALSPAC, N = 913), a prospective longitudinal study spanning more than 20 years. We tested whether a wide range of adversities-including experiences of abuse, domestic violence, physical and emotional cruelty, poverty, neglect, and parental separation-measured by questionnaire within the first seven years of life were significantly associated with the tractography-derived connectome in young adulthood. We tested this across multiple measures of organisation and using a computational model that simulated the wiring economy of the brain. We found no significant relationships between early exposure to any form of adversity and the global organisation of the structural connectome in young adulthood. We did detect local differences in the medial prefrontal cortex, as well as an association between weaker brain wiring constraints and greater externalising behaviour in adolescence. Our results indicate that further efforts are necessary to delimit the magnitude and functional implications of adversity-related differences in connectomic organization. RESEARCH HIGHLIGHTS: Diverse prospective measures of the early-life environment do not predict the organisation of the DTI tractography-derived connectome in young adulthood Wiring economy of the connectome is weakly associated with externalising in adolescence, but not internalising or cognitive ability Further work is needed to establish the scope and significance of global adversity-related differences in the structural connectome.