Faculty Bibliography

Despite the high prevalence and consequences associated with externalizing psychopathologies, little is known about their underlying neurobiological mechanisms. Studying multiple externalizing disorders, each characterized by compromised inhibition, could reveal both common and distinct mechanisms of impairment. The present study therefore compared individuals with intermittent explosive disorder (IED) (N = 11), individuals with cocaine use disorder (CUD) (N = 21), and healthy controls (N = 17) on task performance and functional magnetic resonance imaging (fMRI) activity during an event-related color-word Stroop task; self-reported trait anger expression was also collected in all participants. Results revealed higher error-related activity in the two externalizing psychopathologies as compared with controls in two subregions of the dorsolateral prefrontal cortex (DLPFC) (a region known to be involved in exerting cognitive control during this task), suggesting a neural signature of inhibitory-related error processing common to these psychopathologies. Interestingly, in one DLPFC subregion, error-related activity was especially high in IED, possibly indicating a specific neural correlate of clinically high anger expression. Supporting this interpretation, error-related DLPFC activity in this same subregion positively correlated with trait anger expression across all participants. These collective results help to illuminate common and distinct neural signatures of impaired self-control, and could suggest novel therapeutic targets for increasing self-control in clinical aggression specifically and/or in various externalizing psychopathologies more generally.

BACKGROUND:Gene polymorphisms that affect serotonin signaling modulate reactivity to salient stimuli and risk for emotional disturbances. Here, we hypothesized that these serotonin genes, which have been primarily explored in depressive disorders, could also have important implications for drug addiction, with the potential to reveal important insights into drug symptomatology, severity, and/or possible sequelae such as dysphoria. METHODS:Using an imaging genetics approach, the current study tested in 62 cocaine abusers and 57 healthy controls the separate and combined effects of variations in the serotonin transporter (5-HTTLPR) and monoamine oxidase A (MAOA) genes on processing of aversive information. Reactivity to standardized unpleasant images was indexed by a psychophysiological marker of stimulus salience (i.e., the late positive potential (LPP) component of the event-related potential) during passive picture viewing. Depressive symptomatology was assessed with the Beck Depression Inventory (BDI). RESULTS:Results showed that, independent of diagnosis, the highest unpleasant LPPs emerged in individuals with MAOA-Low and at least one 'Short' allele of 5-HTTLPR. Uniquely in the cocaine participants with these two risk variants, higher unpleasant LPPs correlated with higher BDI scores. CONCLUSIONS:Taken together, these results suggest that a multilocus genetic composite of monoamine signaling relates to depression symptomatology through brain function associated with the experience of negative emotions. This research lays the groundwork for future studies that can investigate clinical outcomes and/or pharmacogenetic therapies in drug addiction and potentially other psychopathologies of emotion dysregulation.

Management of blood pressure (BP) abnormalities in patients with autonomic failure is usually based on office BP readings. It is uncertain, whether office readings reflect actual BP's [corrected] during a typical day. Therefore, in 45 patients with autonomic failure, we compared office BP values during a tilt test with those captured on a 24-h BP [corrected] ambulatory monitor. Office BP values while supine predicted well the level of nighttime hypertension. However, in only 33% of patients, office values during tilt test accurately reflected hypotension during a typical day. Therefore, BP [corrected] ambulatory monitoring is useful to gauge the true severity of hypotension in patients with autonomic failure.

The formation and maintenance of neuromuscular synapses requires a complex exchange of signals between motor neurons and skeletal muscle fibers leading to the formation of a highly specialized postsynaptic membrane and a highly differentiated nerve terminal. As a consequence, acetylcholine receptors (AChRs) become highly concentrated in the postsynaptic membrane and arranged in perfect register with active zones in the presynaptic nerve terminal, insuring for rapid, robust and reliable synaptic transmission. During development, motor axons approach and recognize muscle that is primed, or prepatterned in the prospective synaptic region. Muscle prepatterning is established by MuSK, a receptor tyrosine kinase, and Lrp4, a member of the LDLR family. Lrp4 associates with MuSK and stimulates MuSK kinase activity, increasing Lrp4 and MuSK expression and causing the clustering of Lrp4 and MuSK. Once clustered, Lrp4 functions as a direct retrograde signal for presynaptic differentiation, causing motor axons to stop growing and develop specializations required for neurotransmitter release. Nascent synapses are stabilized by neuronal Agrin, which is released by motor nerve terminals and binds to Lrp4, stimulating further association between Lrp4 and MuSK and increasing MuSK kinase activity. Lrp4 thus has a central role in coordinating synaptic differentiation, as Lrp4 not only binds Agrin and stimulates postsynaptic differentiation but also acts in turn as a direct retrograde signal for presynaptic differentiation. Mutations in Agrin, Lrp4 and MuSK, as well as additional genes that function in this signaling pathway, cause congenital myasthenia, and auto-antibodies to Lrp4, MuSK, or AChRs are responsible for myasthenia gravis. I will summarize experiments that have contributed to this model of neuromuscular synapse formation, indicate how this knowledge has provided insight into causes for neuromuscular disease, and describe a therapeutic approach for preserving synapses and treating neuromuscular diseases

Over the course of the last century, economists and ethologists have built detailed models from first principles of how humans and animals should make decisions. Over the course of the last few decades, psychologists and behavioral economists have gathered a wealth of data at variance with the predictions of these economic models. This has led to the development of highly descriptive models that can often predict what choices people or animals will make but without offering any insight into why people make the choices that they do--especially when those choices reduce a decision-maker's well-being. Over the course of the last two decades, neurobiologists working with economists and psychologists have begun to use our growing understanding of how the nervous system works to develop new models of how the nervous system makes decisions. The result, a growing revolution at the interdisciplinary border of neuroscience, psychology, and economics, is a new field called Neuroeconomics. Emerging neuroeconomic models stand to revolutionize our understanding of human and animal choice behavior by combining fundamental properties of neurobiological representation with decision-theoretic analyses. In this overview, one class of these models, based on the widely observed neural computation known as divisive normalization, is presented in detail. The work demonstrates not only that a discrete class of computation widely observed in the nervous system is fundamentally ubiquitous, but how that computation shapes behaviors ranging from visual perception to financial decision-making. It also offers the hope of reconciling economic analysis of what choices we should make with psychological observations of the choices we actually do make.

Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers.