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Background: Psychopathy is a disorder characterized by antisocial and affective traits and moral violations. It has developed over time from a general sense of moral insanity to a scientifically investigated personality disorder. Prior studies of psychopathy have found abnormal brain activity during moral processing in the amygdala, posterior cingulate, and basal ganglia; however, these studies only examined negatively valenced moral stimuli. Here we aim to replicate prior moral decision-making research in a forensic population and the differences between moral verdict and moral deliberation by psychopathy. We also aim to replicate prior psychopathy research on negative moral judgment and to extend this work by investigating positive and controversial moral stimuli and to investigate whether psychopaths can determine right from wrong. Methods: Incarcerated adult males (N = 245) completed a functional magnetic resonance imaging protocol on the Mind Research Networks mobile imaging system. Psychopathy was assessed using the Hare Psychopathy Checklist-Revised (PCL-R). Participants were shown words describing three types of moral stimuli: negative (e.g., stealing), positive (e.g., giving to charity), and controversial (e.g., abortion). Participants rated each stimulus as 'wrong' or 'not wrong'. Results were modeled time-locked to stimulus presentation and separately to participant response. Results: PCL-R Total scores were correlated with 'not wrong' responses to negative moral stimuli. PCL-R Total scores were also inversely related to hemodynamic activity in the middle temporal gyrus, basal ganglia, anterior cingulate, and temporal pole and positively related to greater activity in the anterior insula in the contrast of negative > positive. In the controversial > noncontroversial comparison, psychopathy was inversely associated with activity in the temporal parietal junction and dorsolateral prefrontal cortex. Stimulus-locked and response-locked models had few differen

BACKGROUND: Craving is implicated the maintenance of alcohol abuse and dependence as well as relapse during attempts at recovery. An early investigation by Boggio et al. (2008b) demonstrated that transcranial direct current stimulation (tDCS) applied over dorsolateral prefrontal cortex (DLPFC) was effective in reducing craving among individuals with alcohol dependence. The present study is the first to continue to explore the potential of tDCS to manipulate craving in the context of alcohol use and abuse. METHODS: 18 adult participants completed assessments of alcohol abuse severity, and of alcohol craving and mood before and after transcranial stimulation. Active and sham tDCS of DLPFC was utilized in two separate experimental sessions. The protocol was revised midway through the study to include potential induction of craving through the visual presentation of alcohol cues. RESULTS: Within the revised protocol, a comparison of pre- to post-stimulation difference scores for active versus sham stimulation produced a reduction in craving that approached significance (p = .06). A comparison of pre- to post-stimulation scores for active stimulation produced a significant reduction in craving (p = .03), whereas a comparison of pre- to post-stimulation scores for sham stimulation was nonsignificant(p = .42). A significant linear relationship existed between response to active stimulation and both alcohol abuse severity and retrospective accounts of alcohol craving. CONCLUSIONS: The findings showed that tDCS applied to the DLPFC may be effective in reducing alcohol craving among individuals with alcohol use disorders who experience frequent or intense cravings. The use of minimum cutoff scores on assessments of alcohol abuse severity and alcohol craving may aid in identifying individuals who would benefit from tDCS treatment. Additional research may demonstrate the utility of noninvasive brain stimulation in clinical alcohol abuse treatment settings.

Mental disorders are diagnosed on the basis of reported symptoms and externally observed clinical signs. Nonetheless, these cannot be evaluated by means of clinical tests. This is the case for schizophrenia, a complex disease characterized by perturbations in language, perception, thinking, social relationships and will that affects about 1% of the U.S. population. Besides the absence of an objective assessment of symptoms to diagnose schizophrenia, not even a set of symptoms that uniquely characterize this disorder have been found. Given the absence of a biologically-based diagnosis of schizophrenia, several studies have used different brain imaging techniques in an attempt to characterize the biological abnormalities found on patients. One of those techniques is functional magnetic resonance imaging (fMRI), a non-invasive technique that captures brain images that reflect neuronal activity. While fMRI studies have been able to provide significant information about schizophrenia, the acquired data present some technical challenges. FMRI characterizes the dynamics of brain activity in time for several brain volumetric elements (voxels), thus generating massive amounts of data. On the other hand, fMRI studies acquire images from tens or hundreds of subjects, the rate between the data dimensionality and the sample size being very high. One way of dealing with this issue is to use univariate approaches to analyze the data, i.e., analyze each voxel individually. However, such approaches neglect the spatial correlation in the data. Machine learning algorithms can be used to do a multivariate analysis of fMRI data and predict a condition of interest. In addition, the contribution of the analyzed features (in this case voxels) to the learning task can be estimated. Nonetheless, these algorithms' performance is also precluded by the high dimensionality of fMRI data, making whole-brain approaches prone to poorly fit the data. For this reason, some studies restricted their ana

Psychopathy is a personality disorder that is exemplified by affective and interpersonal characteristics such as grandiosity, pathological lying, manipulative use of others, and a profound lack of empathy, guilt, and remorse. Psychopaths also typically demonstrate a constellation of problematic and dangerous behavioral characteristics including sensation seeking, impulsivity, and both instrumental and reactive aggression. Psychopathy and substance use disorders (i.e., abuse and dependence) are significant sources of financial and emotional burden in the United States, as both are strongly linked to severe and repetitive criminal activity. They are also highly comorbid, with psychopaths being about two to three times more likely to have a drug use disorder than nonpsychopaths. Using structural and functional neuroimaging and cluster analysis, this comorbidity was investigated in a series of studies involving incarcerated adult males and females, incarcerated adolescent males and females, and nonincarcerated adult males and females. Across samples, structural differences related to psychopathic traits were largely consistent, lending support to the idea that a network of regions across the paralimbic system is abnormal, at least structurally. Several of the regions identified in the structural studies were also hypoactive during the viewing of drug cues in a functional magnetic resonance imaging study of craving, suggesting a close link between structural and functional abnormalities. Finally, cluster analysis was used to identify typologies of substance users, and differential correlations with personality and individual differences variables were found. These results suggest that substance users are actually a heterogeneous group in terms of severity, drugs of choice, and personality correlates. This heterogeneity also suggests that individual differences should be taken into account when designing substance use treatment strategies. Analogous to the notion of perso

Studies in adult mild traumatic brain injury (mTBI) have shown that two key measures of attention, spatial reorienting and inhibition of return (IOR), are impaired during the first few weeks of injury. However, it is currently unknown whether similar deficits exist following pediatric mTBI. The current study used fMRI to investigate the effects of semi-acute mTBI (< 3 weeks post-injury) on auditory orienting in 14 pediatric mTBI patients (age 13.50 ± 1.83; education: 6.86 ± 1.88) and 14 healthy controls (age 13.29 ± 2.09; education: 7.21 ± 2.08) matched for age and years of education. Results indicated that patients with mTBI showed subtle (i.e., moderate effect sizes) but non-significant deficits on formal neuropsychological testing and during inhibition of return. In contrast, functional imaging results indicated that patients with mTBI demonstrated significantly decreased activation within the bilateral posterior cingulate gyrus, thalamus, basal ganglia, midbrain nuclei, and cerebellum. The spatial topography of hypoactivation was very similar to our previous study in adults, suggesting that subcortical structures may be particularly affected by the initial biomechanical forces in mTBI. Current results also suggest that fMRI may be a more sensitive tool for identifying semi-acute effects of mTBI than the procedures currently used in clinical practice such as neuropsychological testing and structural scans. fMRI findings could potentially serve as a biomarker for measuring the subtle injury caused by mTBI and documenting the course of recovery.

Medical image analysis techniques are becoming ever useful in allowing us to better understand the complexities and constructs of the brain and its functions. These analysis methods have proven to be integral in revealing trends in brain activity within individuals with mental disorders that are distinguishable from what would be considered normal' activity within healthy populations. This has led us to gaining a better understanding of functional connectivity within the brain, especially within populations suffering from mental disorders. Functional magnetic resonance imaging (fMRI) is one of the leading techniques currently being implemented to explore cognitive function and aberrant brain activity resulting from mental illness. Functional connectivity has investigated the associations of spatially-remote neuronal activations in the brain. Independent component analysis (ICA) is the leading analytical method in functional connectivity research and has been extensively implemented in the analysis of fMRI data, allowing us to draw group inferences from that data. However, there is mounting interest in the functional network connectivity (FNC) among components estimated through group ICA. This type of analysis allows us to delve further into the temporal dependencies among components or 'regions' within the brain. In this thesis, we investigate the implementation of group ICA and FNC analysis on two large-scale psychopathology studies -— the first from a multi-site study involving the comparison of schizophrenia patients with healthy controls using a sensorimotor task paradigm, and the second from an investigation in psychopathy in prisoners performing an auditory oddball task. In both studies, we analyzed the fMRI data with group ICA and implemented FNC analysis on the resulting ICA output. The purpose of these studies was to investigate differences in modulation of task-related and default mode networks, identifying any potential temporal dependencies among s

Previous functional neuroimaging studies of psychopathy have demonstrated abnormal functioning in several brain regions associated with emotion and decision-making, including amygdala, orbital frontal cortex, insula, cingulate, anterior superior temporal gyrus, and parahippocampal gyrus. However, investigations of structural differences in these regions are sparse. The relation between structural abnormalities and psychopathy was investigated using Voxel-Based Morphometry (VBM) and the Psychopathy Checklist-Revised (PCL-R). Factor analysis of the PCL-R has revealed a two factor model that was utilized here. Seventy-seven participants from a community sample of substance users were scanned using high-resolution structural magnetic resonance imaging and assessed for psychopathy using the PCL-R. VBM was used to investigate morphometric differences correlated with PCL-R total score, factor one (interpersonal/affective), and factor two (behavioral/antisocial). Results showed a negative correlation between gray matter concentration and total PCL-R score in middle and superior temporal areas, inferior parietal cortex, middle occipital gyrus, caudate, and posterior cingulate. A similar result was found for factor two. There was a negative correlation between gray matter concentration and factor one score in several regions, including bilateral insula, bilateral middle temporal gyri, bilateral superior temporal gyri, right temporal pole, bilateral amygdala/parahippocampal gyri, right orbital frontal cortex, bilateral anterior and posterior cingulate, and thalamus. These results are consistent with functional studies showing abnormal functioning in paralimbic regions.

While mo re sophisticated and constructively aligned assessment is encouraged to promote higher level learning, it is easier to assess knowledge and comprehension than critical thinking and making judgements (Bryan & Clegg 2006). Managing the logistics and resource s required for assessing large numbers of students challenges the ethos of placing students at the heart of the learning process and helping them take responsibility for their own learning. The introduction of innovative technology enhanced assessment stra tegies contests our understanding of the purposes of assessment and affords opportunities for more integrated and personalised approa ches to learning and assessment across disciplines. This paper will examine the design, implementation and impacts of inno vative assessment strategies forming an integral part of a collaborative lifeworld - led transprofessional curriculum delivered to cohorts of 600 students in health and social work using technology to connect learners to wide - ranging, humanising perspectives on evidence for guiding practice. Innovative assessment technologies included group blogs, multiple choice electronic or computer assisted assessment (CAA), and an audience response system (ARS) affording combinations of assessment for learning and assess ment of learning. We will explore, through analys es of student assessment experie nces and student and staff evaluations, how these innovative assessment approaches contribute to effective and efficient blended education enabling students to enhance their practice through promoting and developing critical thinking and reflection for judgement - based practice (Polkinghorne 2004) . Secondly, we will debate the yin and yang of contrasting and connecting values associated with the controlled, systematic measurem ent and objectivity of multiple choice assessments, compared with the formative, iterative and subjective nature of reflective blog ging. We will consider relationships between teaching a