Identification of psychopathic individuals using pattern classification of MRI images

Sato, João Ricardo; Oliveira‐Souza, Ricardo de; Thomaz, Carlos Eduardo; Basílio, Rodrigo; Amaro, Edson; Tovar‐Moll, Fernanda; Hare, Robert D.; Moll, Jorge

doi:10.1080/17470919.2011.562687

Cited by 39 publications

(36 citation statements)

References 68 publications

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“…Psychopaths are characterized by a general lack of empathy and shallow affect, traits associated with callous disregard for the wellbeing of others, guiltlessness, and little appreciation of moral wrongdoing. However, the precise nature of their emotional, moral and empathetic deficits remains unclear [Carré et al, ; Sato et al, ; Seara‐Cardoso and Viding, ]. While most behavioral and neuroimaging studies report that psychopaths are impaired in their capacity to experience empathic concern [Decety et al, ], resonate with the affective states of others [Decety et al, ; Marsh, ], or process stimuli depicting moral violations in a typical way [Harenski et al, ], some work also suggests that they may have difficulties in correctly identifying the emotional states of others [Brook and Kosson, ].…”

Section: Discussionmentioning

confidence: 99%

Socioemotional processing of morally‐laden behavior and their consequences on others in forensic psychopaths

Decety

Chen

Harenski

et al. 2015

Human Brain Mapping

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A large body of evidence supports the view that psychopathy is associated with anomalous emotional processing, reduced guilt and empathy, which are important risk factors for criminal behaviors. However, the precise nature and specificity of this atypical emotional processing is not well understood, including its relation to moral judgment. To further our understanding of the pattern of neural response to perceiving and evaluating morally-laden behavior, this study included 155 criminal male offenders with various level of psychopathy, as assessed with the Psychopathy Check List-Revised. Participants were scanned while viewing short clips depicting interactions between two individuals resulting in either interpersonal harm or interpersonal assistance. After viewing each clip, they were asked to identify the emotions of the protagonists. Inmates with high levels of psychopathy were more accurate than controls in successfully identifying the emotion of the recipient of both helpful and harmful actions. Significant hemodynamic differences were detected in the posterior superior temporal sulcus, amygdala, insula, ventral striatum, and prefrontal cortex when individuals with high psychopathy viewed negative versus positive scenarios moral scenarios and when they evaluated the emotional responses of the protagonists. These findings suggest that socioemotional processing abnormalities in psychopathy may be somewhat more complicated than merely a general or specific emotional deficit. Rather, situation-specific evaluations of the mental states of others, in conjunction with sensitivity to the nature of the other (victim vs. perpetrator), modulate attention to emotion-related cues. Such atypical processing likely impacts moral decision-making and behavior in psychopaths.

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Section: Discussionmentioning

confidence: 99%

Socioemotional processing of morally‐laden behavior and their consequences on others in forensic psychopaths

Decety

Chen

Harenski

et al. 2015

Human Brain Mapping

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“…Much of the literature concerning the neuroimaging of youth AB has focused on single brain areas to a single contrast. Resting state fMRI can help identify circuits that may differ systematically in these youth (Shannon et al, 2011) and novel approaches to neuroimaging analysis (e.g, pattern classification) can uncover novel brain areas linked to AB (Sato et al, 2011). Moreover, novel integration of genes, brain and behavior studies may provide the richest understanding of the interaction of biology and experience (Sameroff, 1995, 2010) at multiple levels of analysis (e.g., neighborhoods to families to children to neural function) in the development of youth AB through probing the interaction of genes and environment as they predict neural differences (i.e., Imaging Gene by Environment (IGxE) interaction studies) associated with AB (Bronfenbrenner & Ceci, 1994; Hyde, Bogdan, et al, 2011), especially if they are applied in experimental or treatment settings (Brody et al, 2009; Jaffee et al, 2012).…”

Section: Future Directionsmentioning

confidence: 99%

Understanding youth antisocial behavior using neuroscience through a developmental psychopathology lens: Review, integration, and directions for research

Hyde

Shaw

Hariri

2013

Developmental Review

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Youth antisocial behavior (AB) is an important public health concern impacting perpetrators, victims, and society. Functional neuroimaging is becoming a more common and useful modality for understanding neural correlates of youth AB. Although there has been a recent increase in neuroimaging studies of youth AB and corresponding theoretical articles on the neurobiology of AB, there has been little work critically examining the strengths and weaknesses of individual studies and using this knowledge to inform the design of future studies. Additionally, research on neuroimaging and youth AB has not been integrated within the broader framework of developmental psychopathology. Thus, this paper provides an in-depth review of the youth AB functional neuroimaging literature with the following goals: 1. to evaluate how this literature has informed our understanding of youth AB, 2. to evaluate current neuroimaging studies of youth AB from a developmental psychopathology perspective with a focus on integrating research from neuroscience and developmental psychopathology, as well as placing this research in the context of other related areas (e.g., psychopathy, molecular genetics), and 3. to examine strengths and weaknesses of neuroimaging and behavioral studies of youth AB to suggest how future studies can develop a more informed and integrated understanding of youth AB.

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“…Ecker et al (2010) have shown that Support Vector Machines (SVM) combined with computational neuroanatomy can be useful in autism diagnosis support, achieving a discrimination accuracy of 90%. Sato et al (2011) investigated the potential of structural MRI as a clinical tool to identify individuals with psychopathy. These methods have the potential to translate objective biological information extracted from neuroimaging data to clinical practice (Marquand et al, 2008; Zhu et al, 2008; Dosenbach et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Pattern Recognition and Feature Extraction Methods in ADHD Prediction

Sato¹,

Hoexter²,

Fujita³

et al. 2012

Front. Syst. Neurosci.

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Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, being one of the most prevalent psychiatric disorders in childhood. The neural substrates associated with this condition, both from structural and functional perspectives, are not yet well established. Recent studies have highlighted the relevance of neuroimaging not only to provide a more solid understanding about the disorder but also for possible clinical support. The ADHD-200 Consortium organized the ADHD-200 global competition making publicly available, hundreds of structural magnetic resonance imaging (MRI) and functional MRI (fMRI) datasets of both ADHD patients and typically developing (TD) controls for research use. In the current study, we evaluate the predictive power of a set of three different feature extraction methods and 10 different pattern recognition methods. The features tested were regional homogeneity (ReHo), amplitude of low frequency fluctuations (ALFF), and independent components analysis maps (resting state networks; RSN). Our findings suggest that the combination ALFF+ReHo maps contain relevant information to discriminate ADHD patients from TD controls, but with limited accuracy. All classifiers provided almost the same performance in this case. In addition, the combination ALFF+ReHo+RSN was relevant in combined vs. inattentive ADHD classification, achieving a score accuracy of 67%. In this latter case, the performances of the classifiers were not equivalent and L2-regularized logistic regression (both in primal and dual space) provided the most accurate predictions. The analysis of brain regions containing most discriminative information suggested that in both classifications (ADHD vs. TD controls and combined vs. inattentive), the relevant information is not confined only to a small set of regions but it is spatially distributed across the whole brain.

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Identification of psychopathic individuals using pattern classification of MRI images

Cited by 39 publications

References 68 publications

Socioemotional processing of morally‐laden behavior and their consequences on others in forensic psychopaths

Socioemotional processing of morally‐laden behavior and their consequences on others in forensic psychopaths

Understanding youth antisocial behavior using neuroscience through a developmental psychopathology lens: Review, integration, and directions for research

Evaluation of Pattern Recognition and Feature Extraction Methods in ADHD Prediction

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