Medial prefrontal cell activity signaling prediction errors of action values

Matsumoto, Madoka; Matsumoto, Kenji; Abe, Hiroshi; Tanaka, Keiji

doi:10.1038/nn1890

Cited by 403 publications

(375 citation statements)

References 44 publications

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“…The pMFC was previously implicated into conflict detection (Botvinick et al, 2001), cognitive dissonance (van Veen et al, 2009;Izuma et al, 2010), volatility monitoring (Behrens et al, 2007), "goal-based action selection" (Matsumoto and Tanaka, 2004a,b), error likelihood prediction (Brown and Braver, 2005), and error processing (Holroyd and Coles, 2002;Ridderinkhof et al, 2004;Matsumoto et al, 2007). One possible explanation of our results is that TMS of the pMFC could be reducing cognitive/emotional dissonance evoked by conflicts with social norms.…”

Section: Discussionmentioning

confidence: 54%

“…In humans, the pMFC is particularly responsive to performance errors in various tasks von Cramon, 2001, 2003;Gehring and Willoughby, 2002;Kerns et al, 2004). Neurons in the pMFC are probably involved in generating a "history of action" (Kennerley et al, 2006;Jocham et al, 2009b); distinct neuronal populations of the pMFC encode positive and negative prediction errors of action values (Matsumoto et al, 2007). Activity of the pMFC represents the direction of error in action-value prediction and varies as a function of the environmental context (Jocham et al, 2009a) to allow optimal adaptation to reversing reward contingencies.…”

Section: Discussionmentioning

confidence: 99%

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Downregulation of the Posterior Medial Frontal Cortex Prevents Social Conformity

Klucharev¹,

Munneke²,

Smidts³

et al. 2011

J. Neurosci.

128

133

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We often change our behavior to conform to real or imagined group pressure. Social influence on our behavior has been extensively studied in social psychology, but its neural mechanisms have remained largely unknown. Here we demonstrate that the transient downregulation of the posterior medial frontal cortex by theta-burst transcranial magnetic stimulation reduces conformity, as indicated by reduced conformal adjustments in line with group opinion. Both the extent and probability of conformal behavioral adjustments decreased significantly relative to a sham and a control stimulation over another brain area. The posterior part of the medial frontal cortex has previously been implicated in behavioral and attitudinal adjustments. Here, we provide the first interventional evidence of its critical role in social influence on human behavior.

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Section: Discussionmentioning

confidence: 54%

Section: Discussionmentioning

confidence: 99%

Downregulation of the Posterior Medial Frontal Cortex Prevents Social Conformity

Klucharev¹,

Munneke²,

Smidts³

et al. 2011

J. Neurosci.

128

133

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show abstract

“…Finally, we sought to identify human brain regions resembling the ACC region in which neurons have been recorded that encode reward prediction errors (51,52) (Fig. 4C).…”

Section: Resultsmentioning

confidence: 99%

Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex

Neubert

Mars

Sallet

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

357

388

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Reward-guided decision-making depends on a network of brain regions. Among these are the orbitofrontal and the anterior cingulate cortex. However, it is difficult to ascertain if these areas constitute anatomical and functional unities, and how these areas correspond between monkeys and humans. To address these questions we looked at connectivity profiles of these areas using resting-state functional MRI in 38 humans and 25 macaque monkeys. We sought brain regions in the macaque that resembled 10 human areas identified with decision making and brain regions in the human that resembled six macaque areas identified with decision making. We also used diffusion-weighted MRI to delineate key human orbital and medial frontal brain regions. We identified 21 different regions, many of which could be linked to particular aspects of reward-guided learning, valuation, and decision making, and in many cases we identified areas in the macaque with similar coupling profiles.orbitofrontal cortex | anterior cingulate cortex | decision making | resting state functional connectivity | comparative anatomy A s humans we make decisions by taking into account different types of information, weighing our options carefully, and eventually coming to a conclusion. We then learn from witnessing the outcome of our decisions. Human functional MRI (fMRI) has had a major impact on elucidating the neural networks mediating decision making and learning, but key insights can only be obtained in neural recording, stimulation, and focal lesion studies conducted in animal models, such as the macaque. Combining insights from human fMRI and animal studies is, however, not straightforward because there is uncertainty about basic issues, such as anatomical and functional correspondences between species (1). For example, although there are many reports of decision value-related activity in the human ventromedial prefrontal cortex (vmPFC) (2, 3), it is unclear whether they can be related to reports of reward-related activity either on the ventromedial surface of the frontal lobe (4, 5), in the adjacent medial orbitofrontal sulcus (6), or indeed to any macaque brain area. It is claimed that some areas implicated in rewardguided decision making and learning, such as parts of anterior cingulate cortex (ACC), are not found in macaques (7), but such theories have never been formally tested.In addition, there is uncertainty about the basic constituent components of decision-making and learning circuits. To return to the example of the vmPFC, although this region is often contrasted with similarly large subdivisions of the frontal cortex, such as the lateral orbitofrontal cortex (lOFC) and ACC (8), it is unclear whether, and if so how, it should be decomposed into further subdivisions. Moreover, there are sometimes fundamental disagreements about how brain areas contribute to decision making and learning. For example, it has been claimed both that the ACC does (9-11) and does not (12) contribute to reward-based decision making and that it is concerned with dist...

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“…ACC plays a pivotal role in RL (Botvinick, 2007;Rushworth, 2008). It is thought to be implicated in the computation of reward expectations linked to actions or environmental stimuli, and calculate the difference between such expectations and the actual environmental outcomes (prediction error) (Amiez, Joseph, & Procyk, 2005;Jessup, Busemeyer, & Brown, 2010;Kennerley, Behrens, & Wallis, 2011;Matsumoto, Matsumoto, Abe, & Tanaka, 2007;Oliveira, McDonald, & Goodman, 2007). In ADHD patients, EEG studies have a diminished error related negativity (ERN) and error positivity (Pe) (Groen, et al, 2008;Herrmann, et al, 2010;Wiersema, van der Meere, & Roeyers, 2009).…”

Section: Acc Dysfunction In Adhdmentioning

confidence: 99%

“…The second module simulates ACC itself. This module contains distinct neural units estimating reward expectations (V unit) (Amiez, et al, 2006;Kennerley, et al, 2011), and neural units coding for the difference between these expectations and actual environmental outcomes (prediction errors,  units) (Kennerley, et al, 2011;Matsumoto, et al, 2007). The ACC module estimates the reward expectations linked to each external event (stimulus or action), so that the activation of each of the two neurons coding for cues (C1, C2) is followed by the response of the V neuron.…”

Section: Model Structure and Dynamicsmentioning

confidence: 99%

Deficient reinforcement learning in medial frontal cortex as a model of dopamine-related motivational deficits in ADHD

et al. 2013

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Attention Deficit/Hyperactivity Disorder (ADHD) is a pathophysiologically complex and heterogeneous condition with both cognitive and motivational components. We propose a novel computational hypothesis of motivational deficits in ADHD, drawing together recent evidence on the role of anterior cingulate cortex (ACC) and associated meso-limbic dopamine circuits in both reinforcement learning and ADHD. Based on findings of dopamine dysregulation and ACC involvement in ADHD we simulated a lesion in a previously validated computational model of ACC (Reward Value and Prediction Model, RVPM). We explored the effects of the lesion on the processing of reinforcement signals. We tested specific behavioural predictions about the profile of reinforcement-related deficits in ADHD in three experimental contexts; probability tracking task, partial and continuous reward schedules, and immediate versus delayed rewards. In addition, predictions were made at the neurophysiological level.Behavioural and neurophysiological predictions from the RVPM-based lesion-model of motivational dysfunction in ADHD were confirmed by data from previously published studies. RVPM represents a promising model of ADHD reinforcement learning suggesting that ACC dysregulation might play a role in the pathogenesis of motivational deficits in ADHD. However, more behavioral and neurophysiological studies are required to test core predictions of the model. In addition, the interaction with different brain networks underpinning other aspects of ADHD neuropathology (i.e., executive function) needs to be better understood.

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Medial prefrontal cell activity signaling prediction errors of action values

Cited by 403 publications

References 44 publications

Downregulation of the Posterior Medial Frontal Cortex Prevents Social Conformity

Downregulation of the Posterior Medial Frontal Cortex Prevents Social Conformity

Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex

Deficient reinforcement learning in medial frontal cortex as a model of dopamine-related motivational deficits in ADHD

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