Psychoticism and salience network morphology

Identifying neural network structures explained by personality traits: combining unsupervised and supervised machine learning techniques in translational validity assessment

There have been studies previously the neurobiological underpinnings of personality traits in various paradigms such as psychobiological theory and Eysenck’s model as well as five-factor model. However, there are limited results in terms of co-clustering of the functional connectivity as measured by functional MRI, and personality profiles. In the present study, we have analyzed resting-state connectivity networks and character type with the Lowen bioenergetic test in 66 healthy subjects. There have been identified direct correspondences between network metrics such as eigenvector centrality (EC), clustering coefficient (CC), node strength (NS) and specific personality characteristics. Specifically, N Acc L and OFCmed were associated with oral and masochistic traits in terms of EC and CC, while Insula R is associated with oral traits in terms of NS and EC. It is noteworthy that we observed significant correlations between individual items and node measures in specific regions, suggesting a more targeted relationship. However, the more relevant finding is the correlation between metrics (NS, CC, and EC) and overall traits. A hierarchical clustering algorithm (agglomerative clustering, an unsupervised machine learning technique) and principal component analysis were applied, where we identified three prominent principal components that cumulatively explain 76% of the psychometric data. Furthermore, we managed to cluster the network metrics (by unsupervised clustering) to explore whether neural connectivity patterns could be grouped based on combined average network metrics and psychometric data (global and local efficiencies, node strength, eigenvector centrality, and node strength). We identified three principal components, where the cumulative amount of explained data reaches 99%. The correspondence between network measures (CC and NS) and predictors (responses to Lowen’s items) is 62% predicted with a precision of 90%.

The role of the salience network in cognitive and affective deficits

Analysis and interpretation of studies on cognitive and affective dysregulation often draw upon the network paradigm, especially the Triple Network Model, which consists of the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). DMN activity is primarily dominant during cognitive leisure and self-monitoring processes. The FPN peaks during task involvement and cognitive exertion. Meanwhile, the SN serves as a dynamic "switch" between the DMN and FPN, in line with salience and cognitive demand. In the cognitive and affective domains, dysfunctions involving SN activity are connected to a broad spectrum of deficits and maladaptive behavioral patterns in a variety of clinical disorders, such as depression, insomnia, narcissism, PTSD (in the case of SN hyperactivity), chronic pain, and anxiety, high degrees of neuroticism, schizophrenia, epilepsy, autism, and neurodegenerative illnesses, bipolar disorder (in the case of SN hypoactivity). We discuss behavioral and neurological data from various research domains and present an integrated perspective indicating that these conditions can be associated with a widespread disruption in predictive coding at multiple hierarchical levels. We delineate the fundamental ideas of the brain network paradigm and contrast them with the conventional modular method in the first section of this article. Following this, we outline the interaction model of the key functional brain networks and highlight recent studies coupling SN-related dysfunctions with cognitive and affective impairments.

Sex differences in the association between symptom profiles and cognitive functioning in patients with depressive disorder

OBJECTIVE

Depressive disorder (DD) is a heterogeneous disease with sex differences in symptom profiles and cognitive performance. However, sex differences in cognitive dysfunction associated with different symptom profiles have received little systematic study. This study aimed to explore the association between clinical symptoms and cognitive deficits in patients with DD.

METHODS

A cohort of 222 hospitalized patients with DD (males/females = 114/108) and 173 healthy controls (males/females = 80/93) were enrolled. Cognitive function was measured using a comprehensive neuropsychological battery. Depression was assessed using the 17-item Hamilton Rating Scale for Depression (HAMD-17). According to different genders, the relationship between symptom profiles and cognitive deficits was identified using partial correlation analysis and multiple regression analysis.

RESULTS

Patients with DD performed significantly worse than healthy controls in all cognitive domains investigated (all p < 0.05). Remarkably, female patients scored better than male patients on information processing speed (p < 0.05). Multivariate regression analyses showed that the retardation factor score was independently associated with attention and cognitive flexibility, and the sleep disturbance factor score was independently associated with information processing speed in male patients. Furthermore, the anxiety/somatization factor score was independently associated with working memory in female patients.

CONCLUSION

In the present study, we showed that significant sex differences in the association between symptom profiles and cognitive impairment are present in DD patients. Understanding how DD patients' clinical features and cognitive performance are linked from a sex perspective may have clinical implications for predicting and interfering with the outcome of depression.

Insula functional connectivity in schizophrenia

The insula is structurally abnormal in schizophrenia, demonstrating reductions in volume, cortical thickness, and altered gyrification during prodromal, early and chronic stages of the illness. Despite compelling structural alterations, less is known about its functional connectivity, limited by studies considering the insula as a whole or only within the context of resting-state networks. There is evidence, however, from healthy subjects that the insula is comprised of sub-regions with distinct functional profiles, with dorsal anterior insula (dAI) involved in cognitive processing, ventral anterior insula (vAI) involved in affective processing, and posterior insula (PI) involved in somatosensory processing. The current study builds on this prior work and characterizes insula resting-state functional connectivity sub-region profiles in a large cohort of schizophrenia (N = 191) and healthy (N = 196) participants and hypothesizes specific associations between insula sub-region connectivity abnormalities and clinical characteristics related to their functional profiles. Functional dysconnectivity of the insula in schizophrenia is broadly characterized by reduced connectivity within insula sub-networks and greater connectivity with regions not normally connected with that sub-region, reflected in significantly greater similarity of dAI and PI connectivity profiles and significantly lower similarity of dAI and vAI connectivity profiles (p < .05). In schizophrenia, reduced connectivity of dAI correlates with cognitive function (r = 0.18, p = .014), whereas stronger connectivity between vAI and superior temporal sulcus correlates with negative symptoms (r = 0.27, p < .001). These findings reveal altered insula connectivity in all three sub-regions and converge with recent evidence of reduced differentiation of insula connectivity in schizophrenia, implicating functional dysconnectivity of the insula in cognitive and clinical symptoms.

Techniques of Neutralization: A Brain Network Perspective

Sykes and Matza introduced neutralization theory in 1957 to explain how juvenile delinquents retain a positive self-image when engaging in delinquent acts. Since then, aspects of neutralization theory have been incorporated into sociological and criminological theories to explain socially deviant behavior. Functional brain mapping research utilizing advanced magnetic resonance imaging techniques has identified complex, intrinsically organized, large-scale brain networks. Higher order operations commonly attributed to three brain networks (default mode network [DMN], central executive network [CEN], salience network [SN]) align closely with neutralization theory. This article briefly discusses brain networks in general and the DMN, CEN, and SN specifically. It also discusses how these networks are involved when engaging in the use of techniques of neutralization and offers implications for future research.

Motivation but not valence modulates neuroticism-dependent cingulate cortex and insula activity

Neuroticism has been found to specifically modulate amygdala activations during differential processing of valence and motivation while other brain networks yet are unexplored for associated effects. The main purpose of this study was to investigate whether neural mechanisms processing valence or motivation are prone to neuroticism in the salience network (SN), a network that is anchored in the anterior cingulate cortex (ACC) and the anterior insula. This study used functional magnetic resonance imaging (fMRI) and an approach/avoid emotional pictures task to investigate brain activations modulated by pictures' valence or motivational status between high and low neurotic individuals. We found that neuroticism-dependent SN and the parahippocampal-fusiform area activations were modulated by motivation but not valence. Valence in contrast interacted with neuroticism in the lateral orbitofrontal cortex. We suggested that neuroticism modulated valence and motivation processing, however, under the influence of the two distinct networks. Neuroticism modulated the motivation through the SN while it modulated the valence through the orbitofrontal networks.

Novelty seeking and reward dependence-related large-scale brain networks functional connectivity variation during salience expectancy

A salience network (SN) anchored in the anterior insula (AI) and dorsal anterior cingulate cortex (dACC) plays a key role in switching between brain networks during salience detection and attention regulation. Previous fMRI studies have associated expectancy behaviors and SN activation with novelty seeking (NS) and reward dependence (RD) personality traits. To address the question of how functional connectivity (FC) in the SN is modulated by internal (expectancy-related) salience assignment and different personality traits, 68 healthy participants performed a salience expectancy task using functional magnetic resonance imaging, and psychophysiological interaction analysis (PPI) was conducted to determine salience-related connectivity changes during these anticipation periods. Correlation was then evaluated between PPI and personality traits, assessed using the temperament and character inventory of 32 male participants. During high salience expectancy, SN-seed regions showed reduced FC to visual areas and parts of the default mode network, but increased FC to the central executive network. With increasing NS, participants showed significantly increasing disconnection between right AI and middle cingulate cortex when expecting high-salience pictures as compared to low-salience pictures, while increased RD also predicted decreased right dACC and caudate FC for high salience expectancy. Our findings suggest a direct link between personality traits and internal salience processing mediated by differential network integration of the SN. SN activity and coordination may therefore be moderated by novelty seeking and reward dependency personality traits, which are associated with risk of addiction. Hum Brain Mapp 38:4064-4077, 2017. © 2017 Wiley Periodicals, Inc.

Effects of early life stress on depression, cognitive performance and brain morphology

BACKGROUND

Childhood early life stress (ELS) increases risk of adulthood major depressive disorder (MDD) and is associated with altered brain structure and function. It is unclear whether specific ELSs affect depression risk, cognitive function and brain structure.

METHOD

This cross-sectional study included 64 antidepressant-free depressed and 65 never-depressed individuals. Both groups reported a range of ELSs on the Early Life Stress Questionnaire, completed neuropsychological testing and 3T magnetic resonance imaging (MRI). Neuropsychological testing assessed domains of episodic memory, working memory, processing speed and executive function. MRI measures included cortical thickness and regional gray matter volumes, with a priori focus on the cingulate cortex, orbitofrontal cortex (OFC), amygdala, caudate and hippocampus.

RESULTS

Of 19 ELSs, only emotional abuse, sexual abuse and severe family conflict independently predicted adulthood MDD diagnosis. The effect of total ELS score differed between groups. Greater ELS exposure was associated with slower processing speed and smaller OFC volumes in depressed subjects, but faster speed and larger volumes in non-depressed subjects. In contrast, exposure to ELSs predictive of depression had similar effects in both diagnostic groups. Individuals reporting predictive ELSs exhibited poorer processing speed and working memory performance, smaller volumes of the lateral OFC and caudate, and decreased cortical thickness in multiple areas including the insula bilaterally. Predictive ELS exposure was also associated with smaller left hippocampal volume in depressed subjects.

CONCLUSIONS

Findings suggest an association between childhood trauma exposure and adulthood cognitive function and brain structure. These relationships appear to differ between individuals who do and do not develop depression.