How reliable are amygdala findings in psychopathy? A systematic review of MRI studies

Manifold learning uncovers nonlinear interactions between the adolescent brain and environment that predict emotional and behavioral problems

BACKGROUND

To progress adolescent mental health research beyond our present achievements - a complex account of brain and environmental risk factors without understanding neurobiological embedding in the environment - we need methods to unveil relationships between the developing brain and real-world environmental experiences.

METHODS

We investigated associations among brain function, environments, and emotional and behavioral problems using participants from the Adolescent Brain and Cognitive Development Study (N=2,401 female). We applied manifold learning, a promising technique for uncovering latent structure from high-dimensional biomedical data like functional magnetic resonance imaging (fMRI). Specifically, we developed exogenous PHATE (E-PHATE) to model brain-environment interactions. We used E-PHATE embeddings of participants' brain activation during emotional and cognitive processing to predict individual differences in cognition and emotional and behavioral problems, both cross-sectionally and longitudinally.

RESULTS

E-PHATE embeddings of participants' brain activation and environments at baseline show moderate-to-large associations with total, externalizing, and internalizing problems at baseline, across several subcortical regions and large-scale cortical networks, relative to the zero-to-small effects achieved by voxel or PHATE methods. E-PHATE embeddings of the brain and environment at baseline also relate to emotional and behavioral problems two years later. These longitudinal predictions show a consistent, moderate effect in the frontoparietal and attention networks.

CONCLUSIONS

Adolescent brain's embedding in the environment yields enriched insight into emotional and behavioral problems. Using E-PHATE, we demonstrate how the harmonization of cutting-edge computational methods with longstanding developmental theories advances detection and prediction of adolescent emotional and behavioral problems.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

Meanness and affective processing: A meta-analysis of EEG findings on emotional face processing in individuals with psychopathic traits

BACKGROUND

The triarchic model (Patrick et al., 2009) conceptualizes psychopathy as a multidimensional construct encompassing three biobehavioral dimensions: meanness, boldness, and disinhibition. Meanness entails low empathy, shallow affect, and lack of remorse, and is associated with poor facial emotion recognition; however, the mechanistic processes contributing to these deficits are unclear. Emotional face processing can be examined on a neurophysiological level using event-related potentials (ERPs) such as N170, P200, and LPP. No quantitative review to date has examined the extent to which amplitude of these ERP components may be modulated by psychopathic traits.

METHOD

The current study performed random-effects model meta-analyses of nine studies (N = 1131) which examined affective face processing ERPs in individuals with psychopathic traits to provide an overall effect size for the association between meanness, boldness, and disinhibition and N170, P200, and LPP amplitudes across studies. Analyses were also conducted examining potential moderators and publication bias.

RESULTS

N170 amplitudes were significantly smaller (r =.18) among individuals high in meanness when processing fearful faces. Significant effects were not found for N170 amplitude when processing angry or happy faces, nor for LPP and P200 amplitudes across stimulus types. Additionally, significant effects were not found for the association between N170 amplitude and other dimensions of psychopathy. Meta-regression analyses indicated the manipulation of facial stimuli was significant in explaining some between-study heterogeneity of the meanness N170-fear model. No evidence of publication bias was found.

CONCLUSIONS

Diminished amplitude of the N170 when viewing fear faces appears to be a neurophysiological marker of psychopathic meanness. Deficits in early encoding of faces may account for empathy deficits characteristic of psychopathy.

Newborn Brain Function and Early Emerging Callous-Unemotional Traits

Importance

Children with high callous-unemotional traits are more likely to develop severe and persistent conduct problems; however, the newborn neurobiology underlying early callous-unemotional traits remains unknown. Understanding the neural mechanisms that precede the development of callous-unemotional traits could help identify at-risk children and encourage development of novel treatments.

Objective

To determine whether newborn brain function is associated with early-emerging empathy, prosociality, and callous-unemotional traits.

Design, Setting, and Participants

In this prospective, longitudinal cohort study, pregnant women were recruited from obstetric clinics in St Louis, Missouri, from September 1, 2017, to February 28, 2020, with longitudinal data collected until March 20, 2023. Mothers were recruited during pregnancy. Newborns underwent brain magnetic resonance imaging shortly after birth. Mothers completed longitudinal follow-up when the children were aged 1, 2, and 3 years.

Exposures

The sample was enriched for exposure to socioeconomic disadvantage.

Main Outcome and Measure

Functional connectivity between hypothesized brain regions was assessed using newborn-specific networks and voxel-based connectivity analyses. Children's callous-unemotional traits were measured using the Inventory of Callous-Unemotional Traits. Empathy and prosociality were assessed using the Infant and Toddler Socio-Emotional Assessment.

Results

A total of 283 children (mean [SD] gestational age, 38 [2] weeks; 159 male [56.2%]; 2 Asian [0.7%], 171 Black [60%], 7 Hispanic or Latino [2.5%], 106 White [38%], 4 other racial or ethnic group [1.4%]) were included in the analysis. Stronger newborn functional connectivity between the cingulo-opercular network (CO) and medial prefrontal cortex (mPFC) was associated with higher callous-unemotional traits at age 3 years (β = 0.31; 95% CI, 0.17-0.41; P < .001). Results persisted when accounting for parental callous-unemotional traits and child externalizing symptoms. Stronger newborn CO-mPFC connectivity was also associated with lower empathy and lower prosociality at ages 1, 2, and 3 years using multilevel models (β = -0.12; 95% CI, -0.21 to -0.04; P = .004 and β = -0.20; 95% CI, -0.30 to -0.10; P < .001, respectively).

Conclusions and Relevance

Newborn functional connectivity was associated with early-emerging empathy, prosociality, and callous-unemotional traits, even when accounting for parental callous-unemotional traits and child externalizing symptoms. Understanding the neurobiological underpinnings of empathy, prosociality, and callous-unemotional traits at the earliest developmental point may help early risk stratification and novel intervention development.

Brain structural correlates of psychopathic traits in elite female combat-sports athletes

Psychopathy is characterized by glibness and superficial charm, as well as a lack of empathy, guilt and remorse, and is often accompanied by antisocial behaviour. The cerebral bases of this syndrome have been mostly studied in violent subjects or those with a criminal history. However, the antisocial component of psychopathy is not central to its conceptualization, and in fact, psychopathic traits are present in well-adjusted, non-criminal individuals within the general population. Interestingly, certain psychopathy characteristics appear to be particularly pronounced in some groups or professions. Importantly, as these so-called adaptive or successful psychopaths do not show antisocial tendencies or have significant psychiatric comorbidities, they may represent an ideal population to study this trait. Here, we investigated such a group, specifically elite female judo athletes, and compared them with matched non-athletes. Participants completed psychopathy, anger, perspective-taking and empathic concern questionnaires and underwent structural magnetic resonance imaging (MRI). Grey matter volume (GMV) was computed using voxel-based morphometry from the T1-weighted images. Athletes scored significantly higher in primary psychopathy and anger and lower in empathy and perspective taking. They also exhibited smaller GMV in the right temporal pole, left occipital cortex and left amygdala/hippocampus. GMV values for the latter cluster significantly correlated with primary psychopathy scores across both groups. These results confirm and extend previous findings to a little-studied population and provide support for the conceptualization of psychopathy as a dimensional personality trait which not only is not necessarily associated with antisocial behaviour but may potentially have adaptive value.

Impaired salience network switching in psychopathy

Growing evidence suggests that psychopathy is related to altered connectivity within and between three large-scale brain networks that support core cognitive functions, including allocation of attention. In healthy individuals, default mode network (DMN) is involved in internally-focused attention and cognition such as self-reference. Frontoparietal network (FPN) is anticorrelated with DMN and is involved in externally-focused attention to cognitively demanding tasks. A third network, salience network (SN), is involved in detecting salient cues and, crucially, appears to play a role in switching between the two anticorrelated networks, DMN and FPN, to efficiently allocate attentional resources. Psychopathy has been related to reduced anticorrelation between DMN and FPN, suggesting SN's role in switching between these two networks may be diminished in the disorder. To test this hypothesis, we used independent component analysis to derive DMN, FPN, and SN activity in resting-state fMRI data in a sample of incarcerated men (N = 148). We entered the activity of the three networks into dynamic causal modeling to test SN's switching role. The previously established switching effect of SN among young, healthy adults was replicated in a group of low psychopathy participants (posterior model probability = 0.38). As predicted, SN's switching role was significantly diminished in high psychopathy participants (t(145) = 26.39, p < .001). These findings corroborate a novel theory of brain function in psychopathy. Future studies may use this model to test whether disrupted SN switching is related to high psychopathy individuals' abnormal allocation of attention.

A neurocognitive model of early onset persistent and desistant antisocial behavior in early adulthood

It remains unclear which functional and neurobiological mechanisms are associated with persistent and desistant antisocial behavior in early adulthood. We reviewed the empirical literature and propose a neurocognitive social information processing model for early onset persistent and desistant antisocial behavior in early adulthood, focusing on how young adults evaluate, act upon, monitor, and learn about their goals and self traits. Based on the reviewed literature, we propose that persistent antisocial behavior is characterized by domain-general impairments in self-relevant and goal-related information processing, regulation, and learning, which is accompanied by altered activity in fronto-limbic brain areas. We propose that desistant antisocial development is associated with more effortful information processing, regulation and learning, that possibly balances self-relevant goals and specific situational characteristics. The proposed framework advances insights by considering individual differences such as psychopathic personality traits, and specific emotional characteristics (e.g., valence of social cues), to further illuminate functional and neural mechanisms underlying heterogenous developmental pathways. Finally, we address important open questions and offer suggestions for future research to improve scientific knowledge on general and context-specific expression and development of antisocial behavior in early adulthood.

Altered functional connectivity of the amygdala across variants of callous-unemotional traits: A resting-state fMRI study in children and adolescents

Over the past years, research has shown that primary (high callousness and low anxiety) and secondary (high callousness and anxiety) variants of CU traits may be associated with opposite amygdala activity (hypo- and hyper-reactivity, respectively). However, their differences in amygdala functional connectivity remains largely unexplored. We conducted a Latent Profile Analysis on a large sample of adolescents (n = 1416) to identify homogeneous subgroups with different levels of callousness and anxiety. We then performed a seed-to-voxel connectivity analysis on resting-state fMRI data to compare subgroups on connectivity patterns of the amygdala. We examined the results in relation to conduct problems to identify potential neural risk factors. The Latent Profile Analysis revealed four subgroups, including the primary and secondary variants, anxious, and typically developing adolescents. The seed-to-voxel analyses showed that the primary variant was mainly characterized by increased connectivity between the left amygdala and left thalamus. The secondary variant exhibited deficient connectivity between the amygdala and the dorsomedial prefrontal cortex, temporo-parietal junction, premotor, and postcentral gyrus. Both variants showed increased connectivity between the left amygdala and the right thalamus but exhibited opposite functional connectivity between the left amygdala and the parahippocampal gyrus. Dimensional analyses indicated that conduct problems may play a mediating role between callousness and amygdala-dmPFC functional connectivity across youths with already high levels of callousness. Our study highlights that both variants differ in the functional connectivity of the amygdala. Our results support the importance of disentangling the heterogeneity of adolescents at risk for conduct problems in neuroimaging.

The computational psychiatry of antisocial behaviour and psychopathy

Antisocial behaviours such as disobedience, lying, stealing, destruction of property, and aggression towards others are common to multiple disorders of childhood and adulthood, including conduct disorder, oppositional defiant disorder, psychopathy, and antisocial personality disorder. These disorders have a significant negative impact for individuals and for society, but whether they represent clinically different phenomena, or simply different approaches to diagnosing the same underlying psychopathology is highly debated. Computational psychiatry, with its dual focus on identifying different classes of disorder and health (data-driven) and latent cognitive and neurobiological mechanisms (theory-driven), is well placed to address these questions. The elucidation of mechanisms that might characterise latent processes across different disorders of antisocial behaviour can also provide important advances. In this review, we critically discuss the contribution of computational research to our understanding of various antisocial behaviour disorders, and highlight suggestions for how computational psychiatry can address important clinical and scientific questions about these disorders in the future.