Amygdala Nuclei Volumes Are Selectively Associated With Social Network Size in Homeless and Precariously Housed Persons

Challenges in replication: Does amygdala gray matter volume relate to social network size?

In this work, we tried to replicate and extend prior research on the relationship between social network size and the volume of the amygdala. We focused on the earliest evidence for this relationship (Bickart et al., Nature Neuroscience 14(2), 163-164, 2011) and another methodologically unique study that often is cited as a replication (Kanai et al., Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012). Despite their tight link in the literature, we argue that Kanai et al. (Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012) is not a replication of Bickart et al. Nature Neuroscience 14(2), 163-164 (2011), because it uses different morphometric measurements. We collected data from 128 participants on a 7-Tesla MRI and examined variations in gray matter volume (GMV) in the amygdala and its nuclei. We found inconclusive support for a correlation between measures of real-world social network and amygdala GMV, with small effect sizes and only anecdotal evidence for a positive relationship. We found support for the absence of a correlation between measures of online social network and amygdala GMV. We discuss different challenges faced in replication attempts for small effects, as initially reported in these two studies, and suggest that the results would be most helpful in the context of estimation and future meta-analytical efforts. Our findings underscore the value of a narrow approach in replication of brain-behavior relationships, one that is focused enough to investigate the specifics of what is measured. This approach can provide a complementary perspective to the more popular "thematic" alternative, in which conclusions are often broader but where conclusions may become disconnected from the evidence.

Relationship between drug-induced movement disorders and psychosis in adults living in precarious housing or homelessness

BACKGROUND

Studies have reported positive associations between drug-induced movement disorders (DIMDs) and symptoms of psychosis in patients with schizophrenia. However, it is not clear which subtypes of symptoms are related to each other, and whether one symptom precedes another. The current report assessed both concurrent and temporal associations between DIMDs and symptoms of psychosis in a community-based sample of homeless individuals.

METHODS

Participants were recruited in Vancouver, Canada. Severity of DIMDs and psychosis was rated annually, allowing for the analysis of concurrent associations between DIMDs and Positive and Negative Syndrome Scale (PANSS) five factors. A brief version of the PANSS was rated monthly using five psychotic symptoms, allowing for the analysis of their temporal associations with DIMDs. Mixed-effects linear and logistic regression models were used to assess the associations.

RESULTS

401 participants were included, mean age of 40.7 years (SD = 11.2) and 77.4% male. DIMDs and symptoms of psychosis were differentially associated with each other, in which the presence of parkinsonism was associated with greater negative symptoms, dyskinesia with disorganized symptoms, and akathisia with excited symptoms. The presence of DIMDs of any type was not associated with depressive symptoms. Regarding temporal associations, preceding delusions and unusual thought content were associated with parkinsonism, whereas dyskinesia was associated with subsequent conceptual disorganization.

CONCLUSIONS

The current study found significant associations between DIMDs and symptoms of psychosis in individuals living in precarious housing or homelessness. Moreover, there were temporal associations between parkinsonism and psychotic symptoms (delusions or unusual thought content), and the presence of dyskinesia was temporally associated with higher odds of clinically relevant conceptual disorganization.

Neurobiological Bases of Social Networks

A social network is a web that integrates multiple levels of interindividual social relationships and has direct associations with an individual’s health and well-being. Previous research has mainly focused on how brain and social network structures (structural properties) act on each other and on how the brain supports the spread of ideas and behaviors within social networks (functional properties). The structure of the social network is correlated with activity in the amygdala, which links decoding and interpreting social signals and social values. The structure also relies on the mentalizing network, which is central to an individual’s ability to infer the mental states of others. Network functional properties depend on multilayer brain-social networks, indicating that information transmission is supported by the default mode system, the valuation system, and the mentalizing system. From the perspective of neuroendocrinology, overwhelming evidence shows that variations in oxytocin, β-endorphin and dopamine receptor genes, including oxytocin receptor (OXTR), mu opioid receptor 1 (OPRM1) and dopamine receptor 2 (DRD2), predict an individual’s social network structure, whereas oxytocin also contributes to improved transmission of emotional and behavioral information from person to person. Overall, previous studies have comprehensively revealed the effects of the brain, endocrine system, and genes on social networks. Future studies are required to determine the effects of cognitive abilities, such as memory, on social networks, the characteristics and neural mechanism of social networks in mental illness and how social networks change over time through the use of longitudinal methods.

Cognitive Dysfunction, Brain Volumes, and Traumatic Brain Injury in Homeless Persons

Although homeless persons experience traumatic brain injury (TBI) frequently, little is known about the structural and functional brain changes in this group. We aimed to describe brain volume changes and related cognitive/motor deficits in homeless persons with or without TBI versus controls. Participants underwent T1-weighted magnetic resonance imaging (MRI), neuropsychological (NP) tests (the Grooved Pegboard Test [GPT]/Finger Tapping Test [FTT]), alcohol/drug use screens (the Alcohol Use Disorders Identification Test [AUDIT]/Drug Abuse Screening Test [DAST]), and questionnaires (the Brain Injury Screening Questionnaire [BISQ]/General Information Questionnaire [GIQ]) to determine TBI. Normalized volumes of brain substructures from MRI were derived from FreeSurfer. Comparisons were tested by Mann-Whitney U and Kruskal-Wallis rank sum tests. Leave-one-out cross-validation using random forest classifier was applied to determine the ability of predicting TBI. Diagnostic ability of this classifier was assessed using area under the receiver operating characteristic curve (AUC). Fifty-one participants—25 homeless persons (9 with TBI) and 26 controls—were included. The homeless group had higher AUDIT scores and smaller thalamus and brainstem volumes (p < 0.001) than controls. Within homeless participants, the TBI group had reduced normalized volumes of nucleus accumbens, thalamus, ventral diencephalon, and brainstem compared with the non-TBI group (p < 0.001). Homeless participants took more time on the GPT compared with controls using both hands (p < 0.0001); but the observed effects were more pronounced in the homeless group with TBI in the non-dominant hand. Homeless persons with TBI had fewer dominant hand finger taps than controls (p = 0.0096), and homeless participants with (p = 0.0148) or without TBI (p = 0.0093) tapped less than controls with their non-dominant hand. In all participants, TBI was predicted with an AUC of 0.95 (95% confidence interval [CI]: 0.89-1.00) by the classifier modeled on MRI, NP tests, and screening data combined. The MRI-data-based classifier was the best predictor of TBI within the homeless group (AUC: 0.76, 95% CI: 0.53-0.99). Normalized volumes of specific brain substructures were important indicators of TBI in homeless participants and they are important indicators of TBI in the state of homelessness itself. They may improve predictive ability of NP and screening tests in determining these outcomes.