Rosalind Baker

Neuroimaging findings in disruptive behavior disorders

Decades of research have shown that youths with disruptive behavior disorders (DBD) are a heterogeneous population. Over the past 20 years, researchers have distinguished youths with DBD as those displaying high (DBD/HCU) versus low (DBD/LCU) callous-unemotional (CU) traits. These traits include flat affect and reduced empathy and remorse, and are associated with more severe, varied, and persistent patterns of antisocial behavior and aggression. Conduct problems in youths with HCU and LCU are thought to reflect distinct causal vulnerabilities, with antisocial behavior in youths with DBD/HCU reflecting a predominantly genetic etiology, while antisocial behavior in youths with DBD/LCU is associated primarily with environmental influences. Here we selectively review recent functional (fMRI) and structural (sMRI) magnetic resonance imaging research on DBD, focusing particularly on the role of CU traits. First, fMRI studies examining the neural correlates of affective stimuli, emotional face processing, empathy, theory of mind, morality, and decision-making in DBD are discussed. This is followed by a review of the studies investigating brain structure and structural connectivity in DBD. Next, we highlight the need to further investigate females and the role of sex differences in this population. We conclude the review by identifying potential clinical implications of this research.

Learning to predict: Exposure to temporal sequences facilitates prediction of future events

Highlights • Exposure to temporal sequences improves prediction of future events.• Learning to predict from temporal sequences generalizes to untrained stimuli.• Learning to predict is sensitive to the global structure of the trained sequence.• Learning to predict is compromised by increased attentional load.

Community Violence Exposure and Conduct Problems in Children and Adolescents with Conduct Disorder and Healthy Controls

Exposure to community violence through witnessing or being directly victimized has been associated with conduct problems in a range of studies. However, the relationship between community violence exposure (CVE) and conduct problems has never been studied separately in healthy individuals and individuals with conduct disorder (CD). Therefore, it is not clear whether the association between CVE and conduct problems is due to confounding factors, because those with high conduct problems also tend to live in more violent neighborhoods, i.e., an ecological fallacy. Hence, the aim of the present study was: (1) to investigate whether the association between recent CVE and current conduct problems holds true for healthy controls as well as adolescents with a diagnosis of CD; (2) to examine whether the association is stable in both groups when including effects of aggression subtypes (proactive/reactive aggression), age, gender, site and socioeconomic status (SES); and (3) to test whether proactive or reactive aggression mediate the link between CVE and conduct problems. Data from 1178 children and adolescents (62% female; 44% CD) aged between 9 years and 18 years from seven European countries were analyzed. Conduct problems were assessed using the Kiddie-Schedule of Affective Disorders and Schizophrenia diagnostic interview. Information about CVE and aggression subtypes was obtained using self-report questionnaires (Social and Health Assessment and Reactive-Proactive aggression Questionnaire (RPQ), respectively). The association between witnessing community violence and conduct problems was significant in both groups (adolescents with CD and healthy controls). The association was also stable after examining the mediating effects of aggression subtypes while including moderating effects of age, gender and SES and controlling for effects of site in both groups. There were no clear differences between the groups in the strength of the association between witnessing violence and conduct problems. However, we found evidence for a ceiling effect, i.e., individuals with very high levels of conduct problems could not show a further increase if exposed to CVE and vice versa. Results indicate that there was no evidence for an ecological fallacy being the primary cause of the association, i.e., CVE must be considered a valid risk factor in the etiology of CD.

Sex Differences in the Relationship Between Conduct Disorder and Cortical Structure in Adolescents

OBJECTIVE Previous studies have reported reduced cortical thickness and surface area and altered gyrification in frontal and temporal regions in adolescents with conduct disorder (CD). Although there is evidence that the clinical phenotype of CD differs between males and females, no studies have examined whether such sex differences extend to cortical and subcortical structure. METHOD As part of a European multisite study (FemNAT-CD), structural magnetic resonance imaging (MRI) data were collected from 48 female and 48 male participants with CD and from 104 sex-, age-, and pubertal-status-matched controls (14-18 years of age). Data were analyzed using surface-based morphometry, testing for effects of sex, diagnosis, and sex-by-diagnosis interactions, while controlling for age, IQ, scan site, and total gray matter volume. RESULTS CD was associated with cortical thinning and higher gyrification in ventromedial prefrontal cortex in both sexes. Males with CD showed lower, and females with CD showed higher, supramarginal gyrus cortical thickness compared with controls. Relative to controls, males with CD showed higher gyrification and surface area in superior frontal gyrus, whereas the opposite pattern was seen in females. There were no effects of diagnosis or sex-by-diagnosis interactions on subcortical volumes. Results are discussed with regard to attention-deficit/hyperactivity disorder, depression, and substance abuse comorbidity, medication use, handedness, and CD age of onset. CONCLUSION We found both similarities and differences between males and females in CD-cortical structure associations. This initial evidence that the pathophysiological basis of CD may be partly sex-specific highlights the need to consider sex in future neuroimaging studies and suggests that males and females may require different treatments.

Learning to predict is spared in mild cognitive impairment due to Alzheimer’s disease

Learning the statistics of the environment is critical for predicting upcoming events. However, little is known about how we translate previous knowledge about scene regularities to sensory predictions. Here, we ask whether patients with mild cognitive impairment due to Alzheimer’s disease (MCI–AD) that are known to have spared implicit but impaired explicit recognition memory are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI–AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards oriented gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI–AD patients and controls. Further, we show that executive cognitive control may account for individual variability in predictive learning. That is, we observed significant positive correlations of performance in attentional and working memory tasks with post-training performance in the prediction task. Taken together, these results suggest a mediating role of circuits involved in cognitive control (i.e. frontal circuits) that may support the ability for predictive learning in MCI–AD.

Learning temporal statistics for sensory predictions in aging

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

Learning temporal statistics for sensory predictions in mild cognitive impairment

Training is known to improve performance in a variety of perceptual and cognitive skills. However, there is accumulating evidence that mere exposure (i.e. without supervised training) to regularities (i.e. patterns that co-occur in the environment) facilitates our ability to learn contingencies that allow us to interpret the current scene and make predictions about future events. Recent neuroimaging studies have implicated fronto-striatal and medial temporal lobe brain regions in the learning of spatial and temporal statistics. Here, we ask whether patients with mild cognitive impairment due to Alzheimers disease (MCI-AD) that are characterized by hippocampal dysfunction are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards orientated gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. However, our fMRI results demonstrate that MCI-AD patients recruit an alternate circuit to hippocampus to succeed in learning of predictive structures. In particular, we observed stronger learning-dependent activations for structured sequences in frontal, subcortical and cerebellar regions for patients compared to age-matched controls. Thus, our findings suggest a cortico-striatal-cerebellar network that may mediate the ability for predictive learning despite hippocampal dysfunction in MCI-AD.