Temperament & Character account for brain functional connectivity at rest: A diathesis-stress model of functional dysregulation in psychosis

The human brain’s resting-state functional connectivity (rsFC) provides stable trait-like measures of differences in the perceptual, cognitive, emotional, and social functioning of individuals. The rsFC of the prefrontal cortex is hypothesized to mediate a person’s rational self-government, as is also measured by personality, so we tested whether its connectivity networks account for vulnerability to psychosis and related personality configurations. Young adults were recruited as outpatients or controls from the same communities around psychiatric clinics. Healthy controls (n = 30) and clinically stable outpatients with bipolar disorder (n = 35) or schizophrenia (n = 27) were diagnosed by structured interviews, and then were assessed with standardized protocols of the Human Connectome Project. Data-driven clustering identified five groups of patients with distinct patterns of rsFC regardless of diagnosis. These groups were distinguished by rsFC networks that regulate specific biopsychosocial aspects of psychosis: sensory hypersensitivity, negative emotional balance, impaired attentional control, avolition, and social mistrust. The rsFc group differences were validated by independent measures of white matter microstructure, personality, and clinical features not used to identify the subjects. We confirmed that each connectivity group was organized by differential collaborative interactions among six prefrontal and eight other automatically-coactivated networks. The temperament and character traits of the members of these groups strongly accounted for the differences in rsFC between groups, indicating that configurations of rsFC are internal representations of personality organization. These representations involve weakly self-regulated emotional drives of fear, irrational desire, and mistrust, which predispose to psychopathology. However, stable outpatients with different diagnoses (bipolar or schizophrenic psychoses) were highly similar in rsFC and personality. This supports a diathesis-stress model in which different complex adaptive systems regulate predisposition (which is similar in stable outpatients despite diagnosis) and stress-induced clinical dysfunction (which differs by diagnosis)

Temperament & Character account for brain functional connectivity at rest: A diathesis-stress model of functional dysregulation in psychosis

The online version contains supplementary material available at https://doi.org/10.1038/s41380-023-02039-6The human brain’s resting-state functional connectivity (rsFC) provides stable trait-like measures of differences in the perceptual, cognitive, emotional, and social functioning of individuals. The rsFC of the prefrontal cortex is hypothesized to mediate a person’s rational self-government, as is also measured by personality, so we tested whether its connectivity networks account for vulnerability to psychosis and related personality configurations. Young adults were recruited as outpatients or controls from the same communities around psychiatric clinics. Healthy controls (n = 30) and clinically stable outpatients with bipolar disorder (n = 35) or schizophrenia (n = 27) were diagnosed by structured interviews, and then were assessed with standardized protocols of the Human Connectome Project. Data-driven clustering identified five groups of patients with distinct patterns of rsFC regardless of diagnosis. These groups were distinguished by rsFC networks that regulate specific biopsychosocial aspects of psychosis: sensory hypersensitivity, negative emotional balance, impaired attentional control, avolition, and social mistrust. The rsFc group differences were validated by independent measures of white matter microstructure, personality, and clinical features not used to identify the subjects. We confirmed that each connectivity group was organized by differential collaborative interactions among six prefrontal and eight other automatically-coactivated networks. The temperament and character traits of the members of these groups strongly accounted for the differences in rsFC between groups, indicating that configurations of rsFC are internal representations of personality organization. These representations involve weakly self-regulated emotional drives of fear, irrational desire, and mistrust, which predispose to psychopathology. However, stable outpatients with different diagnoses (bipolar or schizophrenic psychoses) were highly similar in rsFC and personality. This supports a diathesis-stress model in which different complex adaptive systems regulate predisposition (which is similar in stable outpatients despite diagnosis) and stress-induced clinical dysfunction (which differs by diagnosis).EU FEDER grants through the Spanish Ministry of Science and Technology PID2021-125017OB-I00, RTI2018-098983-B-I00, D43 TW011793-06A1, PID2021-125017OB-I00, RTI2018-098983-B-I00, D43 TW011793-06A1United States Department of Health & Human Services National Institutes of Health (NIH) - USA R01-MH124060Psychosis-Risk Outcomes Network U01 MH12463

Brainstem glucose metabolism predicts reward dependence scores in treatment-resistant major depression

BACKGROUND: It has been suggested that individual differences in temperament could be involved in the (non-)response to antidepressant (AD) treatment. However, how neurobiological processes such as brain glucose metabolism may relate to personality features in the treatment-resistant depressed (TRD) state remains largely unclear. METHODS: To examine how brainstem metabolism in the TRD state may predict Cloninger's temperament dimensions Harm Avoidance (HA), Novelty Seeking (NS), and Reward Dependence (RD), we collected (18)fluorodeoxyglucose positron emission tomography ((18)FDG PET) scans in 40 AD-free TRD patients. All participants were assessed with the Temperament and Character Inventory (TCI). We applied a multiple kernel learning (MKL) regression to predict the HA, NS, and RD from brainstem metabolic activity, the origin of respectively serotonergic, dopaminergic, and noradrenergic neurotransmitter (NT) systems. RESULTS: The MKL model was able to significantly predict RD but not HA and NS from the brainstem metabolic activity. The MKL pattern regression model identified increased metabolic activity in the pontine nuclei and locus coeruleus, the medial reticular formation, the dorsal/median raphe, and the ventral tegmental area that contributed to the predictions of RD. CONCLUSIONS: The MKL algorithm identified a likely metabolic marker in the brainstem for RD in major depression. Although (18)FDG PET does not investigate specific NT systems, the predictive value of brainstem glucose metabolism on RD scores however indicates that this temperament dimension in the TRD state could be mediated by different monoaminergic systems, all involved in higher order reward-related behavior

AN INTEGRATIVE MODEL OF PERSONALITY DISORDER: PART 3: MECHANISM-BASED APPROACH TO THE PHARMACOTHERAPY OF PERSONALITY DISORDER: AN EMERGING CONCEPT

Temperament traits of Novelty Seeking, Harm Avoidance, Reward Dependence, and Persistence, are well defined in terms of their neural circuitry, neurochemical modulators, and patterns of associative learning. When heritably excessive, each of these traits may become a mechanistically fundamental biogenetic trait vulnerability for personality disorder. The other main risk factor for personality disorder is environmental, notably abuse, neglect, and psychological trauma. The emerging concept of mechanism-based pharmacotherapy aims to activate the brain’s homeostasis as the only available delivery system to re-calibrate complex neurophysiological participants in each of the temperament traits. In a positive feedback, a homeostasis-driven improvement of excessive temperament is expected to facilitate maturation of neocortical networks of cognition, most reliably in expert psychotherapy (Part I of this paper) and, ultimately, thereby improve top-down cortical control of subcortical affect reactivity. As an emerging concept informed by neuroscience and clinical research, mechanism based pharmacotherapy has the potential to be superior to traditional symptom-based treatments. Such mechanism-based approach illustrates what the pharmacological treatment of Research Domain Criteria (RDoC) might look like

Cross-paradigm connectivity: reliability, stability, and utility

While functional neuroimaging studies typically focus on a particular paradigm to investigate network connectivity, the human brain appears to possess an intrinsic “trait” architecture that is independent of any given paradigm. We have previously proposed the use of “cross-paradigm connectivity (CPC)” to quantify shared connectivity patterns across multiple paradigms and have demonstrated the utility of such measures in clinical studies. Here, using generalizability theory and connectome fingerprinting, we examined the reliability, stability, and individual identifiability of CPC in a group of highly-sampled healthy traveling subjects who received fMRI scans with a battery of five paradigms across multiple sites and days. Compared with single-paradigm connectivity matrices, the CPC matrices showed higher reliability in connectivity diversity, lower reliability in connectivity strength, higher stability, and higher individual identification accuracy. All of these assessments increased as a function of number of paradigms included in the CPC analysis. In comparisons involving different paradigm combinations and different brain atlases, we observed significantly higher reliability, stability, and identifiability for CPC matrices constructed from task-only data (versus those from both task and rest data), and higher identifiability but lower stability for CPC matrices constructed from the Power atlas (versus those from the AAL atlas). Moreover, we showed that multi-paradigm CPC matrices likely reflect the brain’s “trait” structure that cannot be fully achieved from single-paradigm data, even with multiple runs. The present results provide evidence for the feasibility and utility of CPC in the study of functional “trait” networks and offer some methodological implications for future CPC studies

Investigation of brain networks for personalized rTMS in healthy subjects and patients with major depressive disorder: A translational study

Depression is a complex psychiatric disorder with emotional dysregulation at its core. The first line of treatment includes cognitive behaviour therapy and pharmacological antidepressants. However, up to one third of patients with depression fail to respond to these treatment interventions. The past decades have seen an increasing use of repetitive Transcranial Magnetic Stimulation (rTMS) in clinical studies, as an alternative treatment for depression. Several large-scale, multicentre randomized controlled trials have led the Food and Drugs Administration (FDA), USA to approve two rTMS protocols for clinical application in the treatment of depression - 10 Hz rTMS and intermittent Theta Burst Stimulation (iTBS). However, only 30-50% of patients receiving rTMS respond to the treatment. The large variability in response to rTMS likely stems from multiple reasons, one being the targeting method currently employed for delivering rTMS at the left dorsolateral prefrontal cortex (DLPFC). Previous functional connectivity studies have shown that stimulation at left DLPFC targets with larger negative correlation to the subgenual anterior cingulate cortex (sgACC) may result in greater therapeutic response than those with lower negative correlation. However, current use of rTMS ignores functional connectivity in choosing the left DLPFC target, thus largely discarding functional architectural differences of the brain across subjects. Furthermore, despite widespread clinical use of rTMS, the basic network mechanisms behind these rTMS protocols remain elusive. This work presents a novel personalization method of left DLPFC target selection based on their negative functional connectivity to the sgACC. The default mode network (DMN) is a large-scale brain network commonly involved in self-referential thought processing and plays an essential role in the pathophysiology of depression. I use the novel personalization method and identical study designs to delineate DMN mechanisms from a single session of 10 Hz rTMS and iTBS in healthy subjects. Arguably, an understanding of basic mechanisms of clinically relevant rTMS protocols in healthy subjects will help improve the current therapeutic effect of rTMS, and possibly expand the therapeutic role of rTMS. My work shows, for the first time, strong but different modulations of DMN connectivity by single personalized sessions of 10 Hz rTMS and iTBS. Such modulations can be predicted using the personality trait harm avoidance (HA). Given that initial results show that the method is robust and reproducible, its adaptation to patient cohorts is likely to result in improved therapeutic benefits. Therefore, the novel method of personalization is translated to clinical setting by using accelerated iTBS (aiTBS) in patients with depression. Additionally, a comparison is made between effects resulting from personalized and nonpersonalized (10-20 EEG system F3 position) aiTBS in patients with depression. By evaluating the DMN, and heart rate variability, I show precise modulatory effects of personalized aiTBS, which is not seen in the standard aiTBS group. The work presented here introduces an important method to reduce variability and increase precision in rTMS modulation by personalizing the left DLPFC target selection. Even though DMN and cardiac effects already point towards the advantage of personalization, the still preliminary analysis fails to show significant differences in treatment response. Lack of greater therapeutic benefits viii from personalized aiTBS in this ongoing study probably stems from a still limited sample size. In case personalization proves clinically advantageous to standard iTBS by the final sample size, this work can sediment the first step towards systems medicine in the field of psychiatry.2022-02-0

Dissociation and interpersonal autonomic physiology in psychotherapy research: an integrative view encompassing psychodynamic and neuroscience theoretical frameworks

Interpersonal autonomic physiology is an interdisciplinary research field, assessing the relational interdependence of two (or more) interacting individual both at the behavioral and psychophysiological levels. Despite its quite long tradition, only eight studies since 1955 have focused on the interaction of psychotherapy dyads, and none of them have focused on the shared processual level, assessing dynamic phenomena such as dissociation. We longitudinally observed two brief psychodynamic psychotherapies, entirely audio and video-recorded (16 sessions, weekly frequency, 45 min.). Autonomic nervous system measures were continuously collected during each session. Personality, empathy, dissociative features and clinical progress measures were collected prior and post therapy, and after each clinical session. Two-independent judges, trained psychotherapist, codified the interactions\u2019 micro-processes. Time-series based analyses were performed to assess interpersonal synchronization and de-synchronization in patient\u2019s and therapist\u2019s physiological activity. Psychophysiological synchrony revealed a clear association with empathic attunement, while desynchronization phases (range of length 30-150 sec.) showed a linkage with dissociative processes, usually associated to the patient\u2019s narrative core relational trauma. Our findings are discussed under the perspective of psychodynamic models of Stern (\u201cpresent moment\u201d), Sander, Beebe and Lachmann (dyad system model of interaction), Lanius (Trauma model), and the neuroscientific frameworks proposed by Thayer (neurovisceral integration model), and Porges (polyvagal theory). The collected data allows to attempt an integration of these theoretical approaches under the light of Complex Dynamic Systems. The rich theoretical work and the encouraging clinical results might represents a new fascinating frontier of research in psychotherapy

Characterizing the Association Between Material Hardship Across Development and Connectome-Wide Brain Connectivity in Adolescents

Experiencing poverty during childhood may prompt experience-dependent neural adaptations. These manifest through functional connectivity patterns across networks thought to support cognitive and socio-emotional processing. Interrelated network connectivity disruptions have been associated with the development of internalizing disorders. Connectome-wide network characterizations of functional connectivity in adolescents who grew up in poverty are lacking. To this end, this dissertation aimed to characterize the association between family material hardship, connectome-wide network connectivity and internalizing symptoms in adolescence. The introductory chapter proposes material hardship, which directly measures a family's experiences with unmet basic needs (e.g., no access to food) as a better alternative to income-based measures used in research. Subsequently, in Chapters Two and Three, network contingency analyses were conducted to characterize connectome-wide connectivity associated with lifetime family material hardship for adolescents drawn from a national longitudinal study. Correlational analyses evaluating the association between network connectivity and current adolescent internalizing symptoms were done. Notably, the mixed findings across the two studies suggest that connectome-wide adaptations confer both cost and benefits to youth who experienced material hardship. Data suggests that altered network connectivity may be protective and that not everyone who experiences material hardship develops internalizing symptoms. In the final chapter, the limitations and implications of the present findings are discussed. Recommendations for more multi-method research to better characterize the association between brain function and poverty are made.PHDPsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/167916/1/jaimemv_1.pd

The bed nucleus of the Stria Terminalis:Connections, genetics, & trait associations

This thesis examines the functional and structural connections of the Bed Nucleus of the Stria Terminalis (BNST). The principal motivation in doing so stems from the documented gap in our knowledge between the prolific pre-clinical animal BNST research, and that of human BNST research (Lebow & Chen, 2016). Understanding the human BNST may prove to be clinically important, as animal models often implicate this structure as being key in processes underlying the stress-response, disorders of negative affect, and in substance misuse- particularly related to alcohol (Herman et al., 2020; Maita et al., 2021). Therefore I further set out to test BNST connectivity relationships with related psychological phenotypes and examine any genetic associations. Chapter 1 provides an overview of the relevant BNST literature and a brief summary of the methods used in this thesis. In Chapter 2 I use the Human Connectome Project young human adults sample (n = ~1000) to map the intrinsic connectivity network of the BNST. In addition, I compare this network to that of the central nucleus of the amygdala, an area anatomically and functionally associated with the BNST (Alheid, 2009). Next, I test for associations across this network with self-report traits relating to dispositional negativity and alcohol use. Finally, I examine the heritability of specific BNST- amygdala sub-region functional connectivity, and co-heritability with the selfreport traits. In Chapter 3 I use the large UK biobank sample (n = ~ 19,000) to run a genome-wide association analysis, aiming to uncover specific common genetic variants that may be linked with BNST – amygdala sub-region functional connectivity. In Chapter 4, I focus on structural connectivity and use a mixture of macaque tracttracing analysis, and human and macaque diffusion MRI probabilistic tractography to examine the evidence for a connection between the subiculum and the BNST. As well, I test for associations between measures of white-matter microstructure and self-report dispositional negativity and alcohol-use phenotypes. Finally, in the Discussion, I bring together the findings of the research, noting their implications within the wider BNST literature and making several suggestions for improving similar analysis in future