Distributed neural representation of expected value

Department of Psychology, Stanford University, Stanford, California 94305, USA.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 06/2005; 25(19):4806-12. DOI: 10.1523/JNEUROSCI.0642-05.2005
Source: PubMed


Anticipated reward magnitude and probability comprise dual components of expected value (EV), a cornerstone of economic and psychological theory. However, the neural mechanisms that compute EV have not been characterized. Using event-related functional magnetic resonance imaging, we examined neural activation as subjects anticipated monetary gains and losses that varied in magnitude and probability. Group analyses indicated that, although the subcortical nucleus accumbens (NAcc) activated proportional to anticipated gain magnitude, the cortical mesial prefrontal cortex (MPFC) additionally activated according to anticipated gain probability. Individual difference analyses indicated that, although NAcc activation correlated with self-reported positive arousal, MPFC activation correlated with probability estimates. These findings suggest that mesolimbic brain regions support the computation of EV in an ascending and distributed manner: whereas subcortical regions represent an affective component, cortical regions also represent a probabilistic component, and, furthermore, may integrate the two.

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    • "The representation of value in the brain—like most representations and processes in the brain—is likely to be distributed across multiple nodes (Knutson et al. 2005). A growing scientific literature has, in fact, supported the idea that value representations reside in fronto-striatal circuits, centered on ventral striatum (VS) and the ventral and medial aspects of prefrontal cortex (PFC), in particular (Kahnt et al. 2010, 2014; Smith et al. 2014; Takahashi et al. 2009). "
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    ABSTRACT: Motivational deficits (avolition and anhedonia ) have historically been considered important negative symptoms of schizophrenia (SZ). Numerous studies have attempted to identify the neural substrates of avolition and anhedonia in schizophrenia , but these studies have not produced much agreement. Deficits in various aspects of reinforcement processing have been observed in individuals with schizophrenia, but it is not exactly clear which of these deficits actually engender motivational impairments in SZ. The purpose of this chapter is to examine how various reinforcement-related behavioral and neural signals could contribute to motivational impairments in both schizophrenia and psychiatric illness, in general. In particular, we describe different aspects of the concept of expected value (EV) , such as the distinction between the EV of stimuli and the expected value of actions, the acquisition of value versus the estimation of value, and the discounting of value as a consequence of time or effort required. We conclude that avolition and anhedonia in SZ are most commonly tied to aberrant signals for expected value, in the context of learning. We discuss implications for further research on the neural substrates of motivational impairments in psychiatric illness.
    Current Topics in Behavioral Neurosciences 09/2015; DOI:10.1007/7854_2015_385
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    • "During the anticipation period of the task, activation in the nucleus accumbens increased linearly with the probability of a given reward. Similarly, Knutson et al. (2005) found that activity of the mesial prefrontal cortex increased proportionally to gain probability. However, brain areas identified with reinforcement learning may rather mediate processes such as stimulus-independent value expectations. "
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    ABSTRACT: Bayesian models are currently a dominant framework for describing human information processing. However, it is not clear yet how major tenets of this framework can be translated to brain processes. In this study, we addressed the neural underpinning of prior probability and its effect on anticipatory activity in category-specific areas. Before fMRI scanning, participants were trained in two behavioral sessions to learn the prior probability and correct order of visual events within a sequence. The events of each sequence included two different presentations of a geometric shape and one picture of either a house or a face, which appeared with either a high or a low likelihood. Each sequence was preceded by a cue that gave participants probabilistic information about which items to expect next. This allowed examining cue-related anticipatory modulation of activity as a function of prior probability in category-specific areas (fusiform face area and parahippocampal place area). Our findings show that activity in the fusiform face area was higher when faces had a higher prior probability. The finding of a difference between levels of expectations is consistent with graded, probabilistically modulated activity, but the data do not rule out the alternative explanation of a categorical neural response. Importantly, these differences were only visible during anticipation, and vanished at the time of stimulus presentation, calling for a functional distinction when considering the effects of prior probability. Finally, there were no anticipatory effects for houses in the parahippocampal place area, suggesting sensitivity to stimulus material when looking at effects of prediction.
    Cognitive Affective & Behavioral Neuroscience 09/2015; DOI:10.3758/s13415-015-0373-4 · 3.29 Impact Factor
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    • "In this regard, the intense dopaminergic projection from the ventral tegmental area (VTA) to the prelimbic cortex is particularly noteworthy (Naneix et al., 2009), given that dopamine-producing cells have been shown to compute the difference between the expected and the actual value of an outcome, often called reward prediction error (Cohen et al., 2012). It is noteworthy that the anterior cingulate cortex, another mPFC region, has also been shown to encode the expected value of an outcome , factoring the real magnitude of the reward and its cost (including its risk, its delay, and the effort necessary to retrieve it; Knutson et al., 2005; Kable and Glimcher, 2007; Rushworth and Behrens, 2008); its activation increases as a function of cognitive control demanded by the task (Brown and Braver, 2005). Chronic stress response induces an overall atrophy and hypofunction of this network that correlates with a facilitated shift from goal-directed to habit-based decisions (Dias-Ferreira et al., 2009, for rodents; Soares et al., 2012, for humans). "
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    ABSTRACT: For a number of decades, different fields of knowledge, including psychology, economics, and neurosciences, have focused their research efforts on a better understanding of the decision-making process. Making decisions based on the probability of future events is routine in everyday life; it occurs whenever individuals select an option from several alternatives, each one associated with a specific value. Sometimes subjects decide knowing the precise outcomes of each option, but commonly they have to decide without knowing the consequences (because either ambiguity or risk is involved). Stress has a broad impact on animal behaviors, affects brain regions involved in decision-making processes, and, when maladaptive, is a trigger for neuropsychiatric disorders. This Mini-Review provides a comprehensive overview on how stress impacts decision-making processes, particularly under uncertain conditions. Understanding this can prove to be useful for intervention related to impairments to decision-making processes that present in several stress-triggered neuropsychiatric disorders. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.
    Journal of Neuroscience Research 12/2014; 93(6). DOI:10.1002/jnr.23521 · 2.59 Impact Factor
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