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      Neural Mechanisms of the Transformation from Objective Value to Subjective Utility: Converting from Count to Worth

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          Abstract

          When deciding, we aim to choose the “best” possible outcome. This is not just selection of the option that is the most numerous or physically largest, as options are translated from objective value (count) to subjective value (worth or utility). We localized the neural instantiation of the value-to-utility transformation to the dorsal anterior midcingulate cortex (daMCC), with independent replication. The daMCC encodes the context-specific information necessary to convert from count to worth. This encoding is not simply a representation of utility or preference, but the interaction of the two. Specifically, the relationship of brain activation to value is dependent on individual preference, with both positive and negative slopes across the population depending on whether each individual's preference results in enhancement or diminishment of the valuation. For a given value, across participants, enhanced daMCC activation corresponds to diminished subjective valuation, deactivation to enhanced subjective valuation, and non-modulated activation with non-modulated subjective valuation. Further, functional connectivity analyses identified brain regions (positive connectivity with the inferior frontal gyrus and negative connectivity with the nucleus accumbens) through which contextual information may be integrated into the daMCC and allow for outputs to modulate valuation signals. All analyses were replicated through an independent within-study replication, with initial testing in the gains domain and replication in the intermixed and mirrored losses trials. We also present and discuss an ancillary finding: we were unable to identify parametric value signals for losses through whole-brain analyses, and ROI analyses of the vmPFC presented non-modulation across loss value levels. These results identify the neural locus of the value-to-utility transformation, and provide a specific computational function for the daMCC in the production of subjective valuation through the integration of value, context, and preferences.

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          Most cited references21

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          Pain and emotion interactions in subregions of the cingulate gyrus.

          Brent Vogt (2005)
          Acute pain and emotion are processed in two forebrain networks, and the cingulate cortex is involved in both. Although Brodmann's cingulate gyrus had two divisions and was not based on any functional criteria, functional imaging studies still use this model. However, recent cytoarchitectural studies of the cingulate gyrus support a four-region model, with subregions, that is based on connections and qualitatively unique functions. Although the activity evoked by pain and emotion has been widely reported, some view them as emergent products of the brain rather than of small aggregates of neurons. Here, we assess pain and emotion in each cingulate subregion, and assess whether pain is co-localized with negative affect. Amazingly, these activation patterns do not simply overlap.
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            The neural basis of loss aversion in decision-making under risk.

            People typically exhibit greater sensitivity to losses than to equivalent gains when making decisions. We investigated neural correlates of loss aversion while individuals decided whether to accept or reject gambles that offered a 50/50 chance of gaining or losing money. A broad set of areas (including midbrain dopaminergic regions and their targets) showed increasing activity as potential gains increased. Potential losses were represented by decreasing activity in several of these same gain-sensitive areas. Finally, individual differences in behavioral loss aversion were predicted by a measure of neural loss aversion in several regions, including the ventral striatum and prefrontal cortex.
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              Common regions of the human frontal lobe recruited by diverse cognitive demands.

              Though many neuroscientific methods have been brought to bear in the search for functional specializations within prefrontal cortex, little consensus has emerged. To assess the contribution of functional neuroimaging, this article reviews patterns of frontal-lobe activation associated with a broad range of different cognitive demands, including aspects of perception, response selection, executive control, working memory, episodic memory and problem solving. The results show a striking regularity: for many demands, there is a similar recruitment of mid-dorsolateral, mid-ventrolateral and dorsal anterior cingulate cortex. Much of the remainder of frontal cortex, including most of the medial and orbital surfaces, is largely insensitive to these demands. Undoubtedly, these results provide strong evidence for regional specialization of function within prefrontal cortex. This specialization, however, takes an unexpected form: a specific frontal-lobe network that is consistently recruited for solution of diverse cognitive problems.
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                Author and article information

                Contributors
                URI : http://loop.frontiersin.org/people/137329/overview
                URI : http://loop.frontiersin.org/people/4050/overview
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                09 November 2016
                2016
                : 10
                : 507
                Affiliations
                [1] 1Department of Psychology, National University of Singapore Singapore, Singapore
                [2] 2Neuroscience and Behavioral Disorders Program, Duke-NUS Medical School Singapore, Singapore
                [3] 3Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore Singapore, Singapore
                Author notes

                Edited by: Paul E. M. Phillips, University of Washington, USA

                Reviewed by: G. Elliott Wimmer, Stanford University, USA; Armin Lak, University College London (UCL), UK; Shunsuke Kobayashi, Fukushima Medical University, Japan

                *Correspondence: O'Dhaniel A. Mullette-Gillman odubik@ 123456gmail.com

                This article was submitted to Decision Neuroscience, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2016.00507
                5101215
                27881949
                bfd3a70c-4455-492b-bc40-4ee66a1ab4c5
                Copyright © 2016 Kurnianingsih and Mullette-Gillman.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 June 2016
                : 24 October 2016
                Page count
                Figures: 7, Tables: 1, Equations: 2, References: 36, Pages: 15, Words: 10753
                Categories
                Neuroscience
                Original Research

                Neurosciences
                value,utility,gains,losses,risk,preferences,decision-making,executive function
                Neurosciences
                value, utility, gains, losses, risk, preferences, decision-making, executive function

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