Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

http://www.princeton.edu/~ashenhav/Publications_Presentations_files/Neuron%202013%20Shenhav.pdf

The Expected Value of Control: An Integrative Theory of Anterior Cingulate Cortex Function

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk- neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk- seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices, and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision-making.

The Neural Basis of Financial Risk Taking

Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries an opportunity cost-that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished.

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An opportunity cost model of subjective effort and task performance.

Various brain regions have been implicated in emotion regulation, although this process remains poorly understood. In this Opinion article, Etkin and colleagues bring together neuroimaging findings and ideas from value-based decision-making and reinforcement learning to propose a conceptual framework for emotion regulation. Emotions are powerful determinants of behaviour, thought and experience, and they may be regulated in various ways. Neuroimaging studies have implicated several brain regions in emotion regulation, including the ventral anterior cingulate and ventromedial prefrontal cortices, as well as the lateral prefrontal and parietal cortices. Drawing on computational approaches to value-based decision-making and reinforcement learning, we propose a unifying conceptual framework for understanding the neural bases of diverse forms of emotion regulation.

The neural bases of emotion regulation

https://www.sas.upenn.edu/psych/kable_lab/Joes_Homepage/Publications_files/Bartra_McGuire_Kable_2013.pdf

The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value.

References 1. Kable, J.W., & Glimcher, P.W. (2009). Neuron, 63, 733–745. 2. Kable, J.W., & Glimcher, P.W. (2007). Nat Neurosci, 10, 1625–1633. 3. Litt, A., Plassmann, H., Shiv, B., & Rangel, A. (2011). Cereb Cortex, 21, 95–102. 4. Peters, J., & Buchel, C. (2010). Behav Brain Res, 213, 135–141. 5. Liu, X., Hairston, J., Schrier, M., & Fan, J. (2011). Neurosci and Biobehav Reviews, 35, 1219–1236. 6. Wager, T.D., Lindquist, M.A., Nichols, T.E., Kober, H., & Van Snellenberg, J.X. (2009). NeuroImage, 45, 210–221. 7. Denny, B.T., Kober, H., Wager, T.D., & Ochsner, K.N. (2012). J Cog Neurosci, 24, 1742–1752. 8. Laird, A.R., Eickhoff, S.B., Li, K., Robin, D.A, Glahn, D.C., & Fox, P.T. (2009). J Neurosci, 29, 14496–14505.

/pdf/the-valuation-system-a-coordinate-based-meta-analysis-2yahk90e4m.pdf

Oscar Bartra

Papers

The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value.

The valuation system: a coordinate-based meta-analysis examining BOLD correlates of subjective value