scholarly journals Connectome-based model predicts individual psychopathic traits in college students

2021 ◽  
Author(s):  
Shuer Ye ◽  
Bing Zhu ◽  
Lei Zhao ◽  
Xuehong Tian ◽  
Qun Yang ◽  
...  
Keyword(s):  
College Students ◽  
Prefrontal Cortex ◽  
General Population ◽  
Limbic System ◽  
Psychopathic Traits ◽  
Anterior Cingulate ◽  
Self Report ◽  
Special Role ◽  
Whole Brain ◽  
Secondary Psychopathy

Background: Psychopathic traits have been suggested to increase the risk of violations of socio-moral norms. Previous studies revealed that abnormal neural signatures are associated with elevated psychopathic traits; however, whether the intrinsic network architecture can predict psychopathic traits at the individual level remains unclear. Methods: The present study utilized connectome-based predictive modeling (CPM) to investigate whether whole-brain resting-state functional connectivity (RSFC) can predict psychopathic traits in the general population. RS functional magnetic resonance imaging data were collected from 84 college students with varying psychopathic traits measured by the Levenson Self-Report Psychopathy Scale (LSRP). Results: We found that RSFC of the negative networks predicted individual differences in total LSRP and secondary psychopathy scores but not primary psychopathy score. Particularly, nodes with the most connections in the predictive connectome anchored in the prefrontal cortex (e.g., anterior prefrontal cortex and orbitofrontal cortex) and limbic system (e.g., anterior cingulate cortex and insula). In addition, the connections between the occipital network (OCCN) and cingulo-opercular network (CON) served as a significant predictive connectome for total LSRP and secondary psychopathy score. Conclusion: CPM constituted by whole-brain RSFC significantly predicted psychopathic traits individually in the general population. The prefrontal cortex and limbic system at the anatomic level and the CON and OCCN at the functional network level plays a special role in the predictive model-reflecting atypical executive control and affective processing for individuals with elevated psychopathic traits. These findings may provide some implications for early detection and potential intervention of psychopathic tendency.

Affective startle potentiation differentiates primary and secondary variants of juvenile psychopathy

2016 ◽  
Vol 29 (4) ◽  
pp. 1149-1160 ◽  
Author(s):  
Eva R. Kimonis ◽  
Kostas A. Fanti ◽  
Natalie Goulter ◽  
Jason Hall
Keyword(s):  
Childhood Maltreatment ◽  
Latent Profile Analysis ◽  
Emotional Reactivity ◽  
Psychopathic Traits ◽  
Self Report ◽  
Cu Traits ◽  
Secondary Psychopathy ◽  
High Aggression ◽  
Secondary Variants ◽  
Startle Potentiation

AbstractIndividuals with psychopathic traits show an attenuated emotional response to aversive stimuli. However, recent evidence suggests heterogeneity in emotional reactivity among individuals with psychopathic or callous–unemotional (CU) traits in the identification of primary and secondary subtypes, or variants. We hypothesized that primary CU variants will respond with blunted affect to negatively valenced stimuli, whereas individuals with a history of childhood maltreatment, fitting with theoretical conceptualizations of secondary psychopathy, will display heightened emotional reactivity. To test this hypothesis, we examined fear-potentiated startle between CU variants while viewing aversive, pleasant, and neutral scenes. Two hundred thirty-eight incarcerated adolescent (M age = 16.8 years, SD = 1.11 years) boys completed a picture-startle paradigm and self-report questionnaires assessing CU traits, aggressive behavior, and maltreatment. Latent profile analysis of CU trait, aggression, and maltreatment scores identified four classes: primary psychopathy variants (high CU traits, high aggression, low maltreatment; n = 46), secondary psychopathy variants (high CU traits, high aggression, high maltreatment; n = 42), and two nonpsychopathic groups differentiated on maltreatment experience (n = 148). Primary CU variants displayed reduced startle potentiation to aversive images relative to control, maltreated, and also secondary variants that exhibited greater startle modulation. Findings add to a rapidly growing body of literature supporting the possibility of multiple developmental pathways to psychopathic traits (i.e., equifinality), and extend it by finding support for divergent potential biomarkers between primary and secondary CU variants.

scholarly journals Depression-related anterior cingulate prefrontal resting state connectivity normalizes following cognitive behavioral therapy

2020 ◽  
Vol 63 (1) ◽  
Author(s):  
Spiro P. Pantazatos ◽  
Ashley Yttredahl ◽  
Harry Rubin-Falcone ◽  
Ronit Kishon ◽  
Maria A. Oquendo ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Cognitive Behavioral Therapy ◽  
Resting State ◽  
Behavioral Therapy ◽  
Post Treatment ◽  
Anterior Cingulate ◽  
Cognitive Behavioral ◽  
Symptom Improvement ◽  
Whole Brain ◽  
Before And After

Abstract Background. Aberrant activity of the subcallosal cingulate (SCC) is a common theme across pharmacologic treatment efficacy prediction studies. The functioning of the SCC in psychotherapeutic interventions is relatively understudied, as are functional differences among SCC subdivisions. We conducted functional connectivity analyses (rsFC) on resting-state functional magnetic resonance imaging (fMRI) data, collected before and after a course of cognitive behavioral therapy (CBT) in patients with major depressive disorder (MDD), using seeds from three SCC subdivisions. Methods. Resting-state data were collected from unmedicated patients with current MDD (Hamilton Depression Rating Scale-17 > 16) before and after 14-sessions of CBT monotherapy. Treatment outcome was assessed using the Beck Depression Inventory (BDI). Rostral anterior cingulate (rACC), anterior subcallosal cingulate (aSCC), and Brodmann’s area 25 (BA25) masks were used as seeds in connectivity analyses that assessed baseline rsFC and symptom severity, changes in connectivity related to symptom improvement after CBT, and prediction of treatment outcomes using whole-brain baseline connectivity. Results. Pretreatment BDI negatively correlated with pretreatment rACC ~ dorsolateral prefrontal cortex and aSCC ~ lateral prefrontal cortex rsFC. In a region-of-interest longitudinal analysis, rsFC between these regions increased post-treatment (p < 0.05FDR). In whole-brain analyses, BA25 ~ paracentral lobule and rACC ~ paracentral lobule connectivities decreased post-treatment. Whole-brain baseline rsFC with SCC did not predict clinical improvement. Conclusions. rsFC features of rACC and aSCC, but not BA25, correlated inversely with baseline depression severity, and increased following CBT. Subdivisions of SCC involved in top-down emotion regulation may be more involved in cognitive interventions, while BA25 may be more informative for interventions targeting bottom-up processing. Results emphasize the importance of subdividing the SCC in connectivity analyses.

scholarly journals Connectome-based predictive modeling of individual anxiety

2020 ◽  
Author(s):  
Zhihao Wang ◽  
Katharina S. Goerlich ◽  
Hui Ai ◽  
André Aleman ◽  
Yuejia Luo ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Predictive Modeling ◽  
Limbic System ◽  
Human Society ◽  
Resting State Functional Connectivity ◽  
Whole Brain ◽  
Personality Differences ◽  
Individual Personality ◽  
High Trait Anxiety

AbstractAnxiety-related illnesses are highly prevalent in human society. Being able to identify neurobiological markers signaling high trait anxiety could aid the assessment of individuals with high risk for mental illness. Here, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity (rsFC) data to predict the degree of anxiety in 76 healthy participants. Using a computational “lesion” method in CPM, we then examined the weights of the identified main brain areas as well as their connectivity. Results showed that the CPM could predict individual anxiety from whole-brain rsFC, especially from limbic areas-whole brain and prefrontal cortex-whole brain. The prediction power of the model significantly decreased from (simulated) lesions of limbic areas, lesions of the connectivity within the limbic system, and lesions of the connectivity between limbic regions and the prefrontal cortex.Although the same model also predicted depression, anxiety-specific networks could be identified independently, centered at the prefrontal cortex. These findings highlight the important role of the limbic system and the prefrontal cortex in the prediction of anxiety. Our work provides evidence for the usefulness of connectome-based modeling of rsFC in predicting individual personality differences and indicates its potential for identifying personality structures at risk of developing psychopathology.

scholarly journals Model brain based learning (BBL) and whole brain teaching (WBT) in learning

2017 ◽  
Vol 1 (2) ◽  
pp. 153
Author(s):  
Baiq Sri Handayani ◽  
A. D. Corebima
Keyword(s):  
Prefrontal Cortex ◽  
Limbic System ◽  
Learning Process ◽  
Learning Model ◽  
The Body ◽  
Learning System ◽  
Whole Brain ◽  
Whole Brain Teaching ◽  
Brain Based Learning ◽  
The Brain

<p class="Abstract">The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL) and the model of Whole Brain Teaching (WBT). The purposes of this article are to obtain information related to (1) the brain’s natural learning system, (2) analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3) explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1) the brain’s natural learning system are: (a) the nerves in each hemisphere do not work independently, (b) doing more activities can connect more brain nerves, (c) the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2) the characteristics of BBL and WBT are: (a) BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b) the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c) the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3) the typical attribute of them compared to other models are that in BBL there are classical music and gestures in the form of easy exercises, while on the WBT model there are fast instructions and movements as instructions or code of every spoken word.</p>

scholarly journals Gray Matter Correlates of Impulsivity in Psychopathy and in the General Population Differ by Kind, Not by Degree: A Comparison of Systematic Reviews

2020 ◽  
Author(s):  
Cole Korponay ◽  
Michael Koenigs
Keyword(s):  
Prefrontal Cortex ◽  
General Population ◽  
Systematic Reviews ◽  
Gray Matter ◽  
Ventral Striatum ◽  
Psychopathic Traits ◽  
Fundamental Question ◽  
Pathophysiological Mechanism ◽  
The Relationship ◽  
Ventral Prefrontal Cortex

A fundamental question in neuropsychiatry is whether a neurobiological continuum accompanies the behavioral continuum between subclinical and clinical traits. Impulsivity is a trait that varies in the general population and manifests severely in disorders like psychopathy. Is the neural profile of severe impulsivity in psychopathy an extreme but continuous manifestation of that associated with impulsivity in the general population (different by degree)? Or is it discontinuous and unique (different by kind)? Here, we compare systematic reviews of the relationship between impulsivity and gray matter in psychopathy and in the general population. The findings suggest that the neural profile associated with extreme impulsivity in psychopathy (increased gray matter in rostral and ventral striatum and prefrontal cortex) is distinct from that associated with impulsivity in the general population (decreased gray matter in rostral and ventral prefrontal cortex). Severe impulsivity in psychopathy may therefore arise from a pathophysiological mechanism that is unique to the disorder. The results caution against the use of community samples to examine impulsive psychopathic traits in relation to neurobiology.

scholarly journals The Limbic System Conception and Its Historical Evolution

2011 ◽  
Vol 11 ◽  
pp. 2427-2440 ◽  
Author(s):  
Marcelo R. Roxo ◽  
Paulo R. Franceschini ◽  
Carlos Zubaran ◽  
Fabrício D. Kleber ◽  
Josemir W. Sander
Keyword(s):  
Prefrontal Cortex ◽  
Molecular Biology ◽  
Human Brain ◽  
Limbic System ◽  
Anterior Cingulate ◽  
Regulatory Control ◽  
Historical Evolution ◽  
Affective Neuroscience ◽  
Emotional Processes ◽  
The Brain

Throughout the centuries, scientific observers have endeavoured to extend their knowledge of the interrelationships between the brain and its regulatory control of human emotions and behaviour. Since the time of physicians such as Aristotle and Galen and the more recent observations of clinicians and neuropathologists such as Broca, Papez, and McLean, the field of affective neuroscience has matured to become the province of neuroscientists, neuropsychologists, neurologists, and psychiatrists. It is accepted that the prefrontal cortex, amygdala, anterior cingulate cortex, hippocampus, and insula participate in the majority of emotional processes. New imaging technologies and molecular biology discoveries are expanding further the frontiers of knowledge in this arena. The advancements of knowledge on the interplay between the human brain and emotions came about as the legacy of the pioneers mentioned in this field. The aim of this paper is to describe the historical evolution of the scientific understanding of interconnections between the human brain, behaviour, and emotions.

scholarly journals People that score high on psychopathic traits are less likely to yawn contagiously

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrew C. Gallup ◽  
Mariska E. Kret ◽  
Omar Tonsi Eldakar ◽  
Julia Folz ◽  
Jorg J. M. Massen
Keyword(s):  
Negative Relationship ◽  
Psychopathic Traits ◽  
Self Report ◽  
Psychopathic Personality ◽  
Community Members ◽  
Contagious Yawning ◽  
Online Study ◽  
Secondary Psychopathy ◽  
Dirty Dozen ◽  
Video Stimulus

AbstractConsiderable variation exists in the contagiousness of yawning, and numerous studies have been conducted to investigate the proximate mechanisms involved in this response. Yet, findings within the psychological literature are mixed, with many studies conducted on relatively small and homogeneous samples. Here, we aimed to replicate and extend upon research suggesting a negative relationship between psychopathic traits and yawn contagion in community samples. In the largest study of contagious yawning to date (N = 458), which included both university students and community members from across 50 nationalities, participants completed an online study in which they self-reported on their yawn contagion to a video stimulus and completed four measures of psychopathy: the primary and secondary psychopathy scales from the Levenson Self-Report Psychopathy Scale (LSRPS), the psychopathy construct from the Dirty Dozen, and the Psychopathic Personality Traits Scale (PPTS). Results support previous findings in that participants that yawned contagiously tended to score lower on the combined and primary measures of psychopathy. That said, tiredness was the strongest predictor across all models. These findings align with functional accounts of spontaneous and contagious yawning and a generalized impairment in overall patterns of behavioral contagion and biobehavioral synchrony among people high in psychopathic traits.

Psychometric Properties of the Social Phobia and Anxiety Inventory for Children (SPAI-C)

2012 ◽  
Vol 28 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Anna Ogliari ◽  
Simona Scaini ◽  
Michael J. Kofler ◽  
Valentina Lampis ◽  
Annalisa Zanoni ◽  
...  
Keyword(s):  
General Population ◽  
Social Phobia ◽  
Psychometric Properties ◽  
Emotional Disorders ◽  
Child Anxiety ◽  
Self Report ◽  
Public Performance ◽  
Confirmatory Factor Analyses ◽  
The Social ◽  
General Populations

Reliable and valid self-report questionnaires could be useful as initial screening instruments for social phobia in both clinical settings and general populations. The present study investigates the factor structure and psychometric properties of the Social Phobia and Anxiety Inventory for Children (SPAI-C) in a sample of 228 children from the Italian general population aged 8 to 11. The children were asked to complete the Italian version of the SPAI-C and the Screen for Child Anxiety Related Emotional Disorders (SCARED) questionnaire. Confirmatory factor analyses revealed that social phobia can be conceptualized as a unitary construct consisting of five distinct but interrelated symptom clusters named Assertiveness, General Conversation, Physical/Cognitive Symptoms, Avoidance, and Public Performance. Internal consistency of the SPAI-C total scores and two subscales was good; correlations between SPAI-C total scores and SCARED total scores/subscales ranged from moderate to high (Generalized Anxiety Disorder, for social phobia), with the SCARED Social Phobia subscale as the best predictor of SPAI-C total scores. The results indicate that the SPAI-C is a reliable and sensitive instrument suitable for identifying Social Phobia in the young Italian general population.

Factor Structure and Measurement Invariance of the Obsessive-Compulsive Inventory – Child Version (OCI-CV) in General Population

2017 ◽  
Vol 33 (2) ◽  
pp. 97-103 ◽  
Author(s):  
Tíscar Rodríguez-Jiménez ◽  
Antonio Godoy ◽  
José A. Piqueras ◽  
Aurora Gavino ◽  
Agustín E. Martínez-González ◽  
...  
Keyword(s):  
General Population ◽  
Children And Adolescents ◽  
Factor Structure ◽  
Self Report ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Good Consistency ◽  
Order Factor ◽  
General Populations ◽  
Report Measure

Abstract. Evidence-based assessment is necessary as a first step for developing psychopathological studies and assessing the effectiveness of empirically validated treatments. There are several measures of obsessive-compulsive disorder (OCD) and/or symptomatology in children and adolescents, but all of them present some limitations. The Obsessive-Compulsive Inventory-Revised (OCI-R) by Foa and her colleagues has showed to be a good self-report measure to capture the dimensionality of OCD in adults and adolescents. The child version of the OCI (OCI-CV) was validated for clinical children and adolescents in 2010, showing excellent psychometric properties. The objective of this study was to examine the factor structure and invariance of the OCI-CV in the general population. Results showed a six-factor structure with one second-order factor, good consistency values, and invariance across region, age, and sex. The OCI-CV is an excellent inventory for assessing the dimensions of OCD symptomatology in general populations of children and adolescents. The invariance across sex and age warrants its utilization for research purposes.

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