Jeremy R. Reynolds

Anorexia Nervosa and Obesity are Associated with Opposite Brain Reward Response

Anorexia nervosa (AN) is a severe psychiatric disorder associated with food avoidance and malnutrition. In this study, we wanted to test whether we would find brain reward alterations in AN, compared with individuals with normal or increased body weight. We studied 21 underweight, restricting-type AN (age M 22.5, SD 5.8 years), 19 obese (age M 27.1, SD 6.7 years), and 23 healthy control women (age M 24.8, SD 5.6 years), using blood oxygen level-dependent functional magnetic resonance brain imaging together with a reward-conditioning task. This paradigm involves learning the association between conditioned visual stimuli and unconditioned taste stimuli, as well as the unexpected violation of those learned associations. The task has been associated with activation of brain dopamine reward circuits, and it allows the comparison of actual brain response with expected brain activation based on established neuronal models. A group-by-task condition analysis (family-wise-error-corrected P<0.05) indicated that the orbitofrontal cortex differentiated all three groups. The dopamine model reward-learning signal distinguished groups in the anteroventral striatum, insula, and prefrontal cortex (P<0.001, 25 voxel cluster threshold), with brain responses that were greater in the AN group, but lesser in the obese group, compared with controls. These results suggest that brain reward circuits are more responsive to food stimuli in AN, but less responsive in obese women. The mechanism for this association is uncertain, but these brain reward response patterns could be biomarkers for the respective weight state.

Altered temporal difference learning in bulimia nervosa.

BACKGROUNDnThe neurobiology of bulimia nervosa (BN) is poorly understood. Recent animal literature suggests that binge eating is associated with altered brain dopamine (DA) reward function. In this study, we wanted to investigate DA-related brain reward learning in BN.nnnMETHODSnIll BN (n = 20, age: mean = 25.2, SD = 5.3 years) and healthy control women (CW) (n = 23, age: mean = 27.2, SD = 6.4 years) underwent functional magnetic resonance brain imaging together with application of a DA-related reward learning paradigm, the temporal difference (TD) model. That task involves association learning between conditioned visual and unconditioned taste stimuli, as well as unexpected violation of those learned associations. Study participants also completed the Sensitivity to Reward and Punishment Questionnaire.nnnRESULTSnBulimia nervosa individuals showed reduced brain response compared with CW for unexpected receipt and omission of taste stimuli, as well as reduced brain regression response to the TD computer model generated reward values, in insula, ventral putamen, amygdala, and orbitofrontal cortex. Those results were qualitatively similar in BN individuals who were nondepressed and unmedicated. Binge/purge frequency in BN inversely predicted reduced TD model response. Bulimia nervosa individuals showed significantly higher Sensitivity to Reward and Punishment compared with CW.nnnCONCLUSIONSnThis is the first study that relates reduced brain DA responses in BN to the altered learning of associations between arbitrary visual stimuli and taste rewards. This attenuated response is related to frequency of binge/purge episodes in BN. The brain DA neurotransmitter system could be an important treatment target for BN.

The Function and Organization of Lateral Prefrontal Cortex: A Test of Competing Hypotheses

The present experiment tested three hypotheses regarding the function and organization of lateral prefrontal cortex (PFC). The first account (the information cascade hypothesis) suggests that the anterior-posterior organization of lateral PFC is based on the timing with which cue stimuli reduce uncertainty in the action selection process. The second account (the levels-of-abstraction hypothesis) suggests that the anterior-posterior organization of lateral PFC is based on the degree of abstraction of the task goals. The current study began by investigating these two hypotheses, and identified several areas of lateral PFC that were predicted to be active by both the information cascade and levels-of-abstraction accounts. However, the pattern of activation across experimental conditions was inconsistent with both theoretical accounts. Specifically, an anterior area of mid-dorsolateral PFC exhibited sensitivity to experimental conditions that, according to both accounts, should have selectively engaged only posterior areas of PFC. We therefore investigated a third possible account (the adaptive context maintenance hypothesis) that postulates that both posterior and anterior regions of PFC are reliably engaged in task conditions requiring active maintenance of contextual information, with the temporal dynamics of activity in these regions flexibly tracking the duration of maintenance demands. Activity patterns in lateral PFC were consistent with this third hypothesis: regions across lateral PFC exhibited transient activation when contextual information had to be updated and maintained in a trial-by-trial manner, but sustained activation when contextual information had to be maintained over a series of trials. These findings prompt a reconceptualization of current views regarding the anterior-posterior organization of lateral PFC, but do support other findings regarding the active maintenance role of lateral PFC in sequential working memory paradigms.

Developing PFC representations using reinforcement learning.

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically [Fuster (1991); Koechlin, E., Ody, C., & Kouneiher, F. (2003). Neuroscience: The architecture of cognitive control in the human prefrontal cortex. Science, 424, 1181-1184; Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt]. However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data.

Reduced Neural Tracking of Prediction Error in Substance-Dependent Individuals

OBJECTIVEnSubstance-dependent individuals make poor decisions on the Iowa Gambling Task, a reward-related decision-making task that involves risk and uncertainty. Task performance depends on several factors, including how sensitive individuals are to feedback and how well they learn based on such feedback. A physiological signal that guides decision making based on feedback is prediction error. The authors investigated whether disruptions in the neural systems underlying prediction error processing in substance-dependent individuals could account for decision-making performance on a modified Iowa Gambling Task.nnnMETHODSnThirty-two substance-dependent individuals and 30 healthy comparison subjects played a modified version of the Iowa Gambling Task during MR scanning. Trial-to-trial behavior and functional MRI (fMRI) blood-oxygen-level-dependent (BOLD) signal were analyzed using a computational model of prediction error based on internal expectancies. The authors investigated how well BOLD signal tracked prediction error in the striatum and the orbitofrontal cortex as well as over the whole brain in patients relative to comparison subjects.nnnRESULTSnCompared with healthy subjects, substance-dependent patients were less sensitive to loss compared with gain, made less consistent choices, and performed worse on the modified Iowa Gambling Task. The ventral striatum and medial orbitofrontal cortex did not track prediction error as strongly in patients as in healthy subjects.nnnCONCLUSIONSnWeaker tracking of prediction error in substance-dependent relative to healthy individuals suggests that altered frontal-striatal error learning signals may underlie decision-making impairments in drug abusers. Computational fMRI may help bridge the knowledge gap between physiology and behavior to inform research aimed at substance abuse treatment.

Application of a cognitive neuroscience perspective of cognitive control to late-life anxiety

Recent evidence supports a negative association between anxiety and cognitive control. Given age-related reductions in some cognitive abilities and the relation of late life anxiety to cognitive impairment, this negative association may be particularly relevant to older adults. This critical review conceptualizes anxiety and cognitive control from cognitive neuroscience and cognitive aging theoretical perspectives and evaluates the methodological approaches and measures used to assess cognitive control. Consistent with behavioral investigations of young adults, the studies reviewed implicate specific and potentially negative effects of anxiety on cognitive control processes in older adults. Hypotheses regarding the role of both aging and anxiety on cognitive control, the bi-directionality between anxiety and cognitive control, and the potential for specific symptoms of anxiety (particularly worry) to mediate this association, are specified and discussed.

Temporal profile of fronto-striatal-limbic activity during implicit decisions in drug dependence.

BACKGROUNDnSubstance dependence is associated with impaired decision-making and altered fronto-striatal-limbic activity. Both greater and lesser brain activity have been reported in drug users compared to controls during decision-making. Inconsistent results might be explained by group differences in the temporal profile of the functional magnetic resonance imaging (fMRI) response. While most previous studies model a canonical hemodynamic response, a finite impulse response (FIR) model measures fMRI signal at discrete time points without assuming a temporal profile. We compared brain activity during decision-making and feedback in substance users and controls using two models: a canonical hemodynamic response function (HRF) and a FIR model.nnnMETHODSn37 substance-dependent individuals (SDI) and 43 controls performed event-related decision-making during fMRI scanning. Brain activity was compared across group using canonical HRF and FIR models.nnnRESULTSnCompared to controls, SDI were impaired at decision-making. The canonical HRF model showed that SDI had significantly greater fronto-striatal-limbic activity during decisions and less activity during feedback than controls. The FIR model confirmed greater activity in SDI during decisions. However, lower activity in SDI during feedback corresponded to a lower post-stimulus undershoot of the hemodynamic response.nnnCONCLUSIONSnGreater activity in fronto-striatal-limbic pathways in SDI compared to controls is consistent with prior work, further supporting the hypothesis that abnormalities in these circuits underlie impaired decision-making. We demonstrate for the first time using FIR analysis that lower activity during feedback may simply reflect the tail end of the hemodynamic response to decision, the post-stimulus undershoot, rather than an actual difference in feedback response.