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• W2017759897 abstract "In this issue of Neuron, Nicolle et al., 2012Nicolle A. Klein Flugge M.C. Hunt L.T. Vlaev I. Dolan R.J. Behrens T. Neuron. 2012; 75 (this issue): 1114-1121Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar suggest that choice-related value signals in ventromedial and anterior dorsomedial prefrontal cortex can be distinguished by their relevance to the current choice, as opposed to their reflection of preferences ascribed to the self versus another. In this issue of Neuron, Nicolle et al., 2012Nicolle A. Klein Flugge M.C. Hunt L.T. Vlaev I. Dolan R.J. Behrens T. Neuron. 2012; 75 (this issue): 1114-1121Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar suggest that choice-related value signals in ventromedial and anterior dorsomedial prefrontal cortex can be distinguished by their relevance to the current choice, as opposed to their reflection of preferences ascribed to the self versus another. Our understanding of the neural mechanisms of value-based decision making has increased dramatically in the last decade. Much of this progress has been achieved with the adoption of formal mathematical models that can be used to explain the process by which we compute values for stimuli in the world and use those values to guide our choices (Montague et al., 1996Montague P.R. Dayan P. Sejnowski T.J. J. Neurosci. 1996; 16: 1936-1947PubMed Google Scholar; Glimcher and Rustichini, 2004Glimcher P.W. Rustichini A. Science. 2004; 306: 447-452Crossref PubMed Scopus (484) Google Scholar; Daw et al., 2005Daw N.D. Niv Y. Dayan P. Nat. Neurosci. 2005; 8: 1704-1711Crossref PubMed Scopus (1519) Google Scholar). By mapping components of these mathematical models to neural activity (a technique called computational fMRI; O’Doherty et al., 2007O’Doherty J.P. Hampton A. Kim H. Ann. N Y Acad. Sci. 2007; 1104: 35-53Crossref PubMed Scopus (339) Google Scholar), it has been possible not only to determine whether a region is engaged under a condition of interest, but also to make inferences about the nature of the computations being implemented. More recently, efforts have been made to expand the application of this method to choice problems with a social component (Hampton et al., 2008Hampton A.N. Bossaerts P. O’Doherty J.P. Proc. Natl. Acad. Sci. USA. 2008; 105: 6741-6746Crossref PubMed Scopus (342) Google Scholar; Suzuki et al., 2012Suzuki S. Harasawa N. Ueno K. Gardner J.L. Ichinohe N. Haruno M. Cheng K. Nakahara H. Neuron. 2012; 74: 1125-1137Abstract Full Text Full Text PDF PubMed Scopus (141) Google Scholar) These studies have reaffirmed the roles of key areas of prefrontal cortex such as dorsomedial prefrontal cortex (dmPFC), known previously to be engaged in tasks requiring social cognition (Amodio and Frith, 2006Amodio D.M. Frith C.D. Nat. Rev. Neurosci. 2006; 7: 268-277Crossref PubMed Scopus (2829) Google Scholar), and ventromedial prefrontal cortex (vmPFC), known to be involved in value-based choice (Hare et al., 2008Hare T.A. O’Doherty J. Camerer C.F. Schultz W. Rangel A. J. Neurosci. 2008; 28: 5623-5630Crossref PubMed Scopus (604) Google Scholar). But, more importantly, such studies are beginning to yield insights into the specific components of the choice processes in which these areas are implicated. In a new study published in the current issue of Neuron, Nicolle et al., 2012Nicolle A. Klein Flugge M.C. Hunt L.T. Vlaev I. Dolan R.J. Behrens T. Neuron. 2012; 75 (this issue): 1114-1121Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar used computational fMRI to investigate whether the neural substrates of value are sensitive to the distinction between actions evaluated based on their direct value to the self and those evaluated based on their value to others. In the task design in Nicolle et al., 2012Nicolle A. Klein Flugge M.C. Hunt L.T. Vlaev I. Dolan R.J. Behrens T. Neuron. 2012; 75 (this issue): 1114-1121Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar, subjects made a choice on each trial between receiving a small monetary prize that would be delivered following a short delay or a larger prize that would be received following a longer delay, with the magnitudes and delays varying across trials. Crucially, trials differed in that on some, the subject chose between the prizes based on their own preferences, while on others they made choices on behalf of a partner, whose preferences they had learned in a training session before beginning the task. Subjects were paired with partners whose preferences for the balance between prize magnitude and delay were dissimilar to their own, which enabled the authors to determine that subjects were truly making choices for their partner based on the partner’s preferences. The authors used the choices made by each of the subjects during the task to fit a temporal discounting model, which allowed them to estimate for each trial both the valuations subjects held for the prizes (“self values”) and the valuations for the prizes the subject ascribed to their partner (“partner values”). The sets of choices presented to the subjects were constructed such that the correlation between the self and partner values of the available prizes were minimized, allowing the authors to separately examine the neural correlates of each. The time series of the self and partner values were regressed against fMRI data that were acquired while the subjects made their choices in order to test for regions with corresponding response profiles. Accumulating evidence suggests that the vmPFC plays a key role in “model-based” reinforcement learning, in which the value of decision options is computed with reference to a rich internal model of the states of the decision problem and the reward values of these states (or “state space”) (Hampton et al., 2006Hampton A.N. Bossaerts P. O’Doherty J.P. J. Neurosci. 2006; 26: 8360-8367Crossref PubMed Scopus (373) Google Scholar; Daw et al., 2011Daw N.D. Gershman S.J. Seymour B. Dayan P. Dolan R.J. Neuron. 2011; 69: 1204-1215Abstract Full Text Full Text PDF PubMed Scopus (967) Google Scholar). Accordingly, the value of options can be updated instantaneously in a model-based framework based on knowledge about changes in the structure of the world, such as, for example, a change in the subjective value of the goal state (Valentin et al., 2007Valentin V.V. Dickinson A. O’Doherty J.P. J. Neurosci. 2007; 27: 4019-4026Crossref PubMed Scopus (404) Google Scholar), or a change in the transitions between states reached following specific actions (Hampton et al., 2006Hampton A.N. Bossaerts P. O’Doherty J.P. J. Neurosci. 2006; 26: 8360-8367Crossref PubMed Scopus (373) Google Scholar). Here, Nicolle et al., 2012Nicolle A. Klein Flugge M.C. Hunt L.T. Vlaev I. Dolan R.J. Behrens T. Neuron. 2012; 75 (this issue): 1114-1121Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar found that, when participants were asked to choose for themselves, activity in vmPFC reflected valuation signals corresponding to the relative values assigned to the options based on their own subjective preferences, consistent with the findings of a number of previous studies (Boorman et al., 2009Boorman E.D. Behrens T.E.J. Woolrich M.W. Rushworth M.F.S. Neuron. 2009; 62: 733-743Abstract Full Text Full Text PDF PubMed Scopus (470) Google Scholar; FitzGerald et al., 2009FitzGerald T.H.B. Seymour B. Dolan R.J. J. Neurosci. 2009; 29: 8388-8395Crossref PubMed Scopus (219) Google Scholar). However, much more intriguing was the finding that, in trials in which the subjects made choices on behalf of their partners, vmPFC no longer responded to the self values, but instead responded to the partner values; that is, activity in vmPFC reflected not their own preferences, but rather those of their partner. Within the context of a role for this region in model-based computations, the findings by Nicolle et al. starkly demonstrate just how flexible the value computations in this region are: not only does vmPFC reflect valuation based on one's own preferences when those are needed to guide choice, but the same region can also reflect the preferences of another person when those preferences are relevant to the choice process. In addition to the valuation signals noted in vmPFC, Nicolle et al. also report a striking pattern of value-related BOLD activation in dmPFC. Specifically, on trials in which the subjects made choices on behalf of their partners, dmPFC responded to the difference in the self value for the two available prizes, while in trials in which subjects chose for themselves, dmPFC responded to the difference in their partner values. It is interesting to note that the self- versus other-oriented distinction was not reflected in the neural activations in either dmPFC or vmPFC. That is, although one value signal reflected the subjects’ own preferences for discounting and the other, arguably more social, value signal reflected the preferences subjects attributed to their partners, each was encoded in vmPFC when relevant for choice and in dmPFC when it was not. The pattern of dmPFC activations is particularly surprising in this regard, given the role commonly attributed to the region in supporting social cognition (Amodio and Frith, 2006Amodio D.M. Frith C.D. Nat. Rev. Neurosci. 2006; 7: 268-277Crossref PubMed Scopus (2829) Google Scholar). In particular, the ability to “mentalize,” or to attribute intentions, beliefs, and other mental states to other agents is consistently associated with activation of this region across fMRI and PET studies (Frith and Frith, 2003Frith U. Frith C.D. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2003; 358: 459-473Crossref PubMed Scopus (1653) Google Scholar). However, the present results suggest that anterior dmPFC in the present task may not necessarily be “social” at all, but instead might facilitate the simulation of signals that are currently not relevant for choice, regardless of whether those signals correspond to representations about the self or another person. Such an interpretation conforms to theories of dmPFC function that claim that its critical role lies in the creation of representations of the world that are decoupled from the sensory environment (Frith and Frith, 2003Frith U. Frith C.D. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2003; 358: 459-473Crossref PubMed Scopus (1653) Google Scholar). Such a computational process could still underlie social inferences by allowing for the simulation of other agents, but importantly, its functional remit is not limited to social contexts, but rather to any situation in which simulation of events divorced from the sensory environment is required. The above-mentioned interpretation of the dmPFC findings raises an interesting question: Why are these value signals in dmPFC being computed in the first place? The presence of these activations is somewhat surprising in the task used by Nicolle et al., because the respective variables they represent are, at least superficially, irrelevant to the choice at hand. One possibility is that the representation of the valuations according to the alternative preference set in dmPFC corresponds to their storage in a temporary buffer. In the event of a change of decision context, those signals can be immediately transferred into vmPFC, permitting rapid deployment of the now behaviorally relevant preference set. Another possibility is that (although not applicable in the specific task used by Nicolle et al., 2012Nicolle A. Klein Flugge M.C. Hunt L.T. Vlaev I. Dolan R.J. Behrens T. Neuron. 2012; 75 (this issue): 1114-1121Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar), the representation of the alternative valuations in dmPFC may allow for the ongoing updating of those model-based value signals on the basis of new information about the sensory environment as it is received. The study by Nicolle et al. invites several important directions for further research going forward. First of all, if “other” versus “self” is not the relevant dimension for differentiating ventromedial versus anterior dorsomedial prefrontal function, but instead the distinction is between the choice relevance of alternative state-space models, one might expect a similar pattern of results in a task involving switching between two state-space models, even in a completely nonsocial context. Second, if it is the case that the dmPFC is acting as a buffer to store alternative models of the decision problem at hand to enable rapid transferring of choice-relevant models into vmPFC, what happens in the dmPFC if more than two such frameworks are to be used for a given task, such as, for example, if participants had to make choices on behalf of two other people as well as themselves? Regardless of the outcome of such future research, the study by Nicolle et al. illustrates how, through the use of quantitative computational approaches married to dynamic measurements of brain function, it is possible to gain insight into the specific computational functions of brain regions involved in even the most complex social-cognitive processes. An Agent Independent Axis for Executed and Modeled Choice in Medial Prefrontal CortexNicolle et al.NeuronSeptember 20, 2012In BriefNicolle et al. show that valuation and choice for self and other exhibit parallel computations, where gradients exist within both medial prefrontal and temporoparietal cortices. Ventral regions compute choices that will be executed, while dorsal regions compute choices that are merely modeled. Full-Text PDF Open Access" @default.
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• W2017759897 title "Choosing for Me or Choosing for You: Value in Medial Prefrontal Cortex" @default.
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