+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Learning-Induced Plasticity in Medial Prefrontal Cortex Predicts Preference Malleability

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          Learning induces plasticity in neuronal networks. As neuronal populations contribute to multiple representations, we reasoned plasticity in one representation might influence others. We used human fMRI repetition suppression to show that plasticity induced by learning another individual’s values impacts upon a value representation for oneself in medial prefrontal cortex (mPFC), a plasticity also evident behaviorally in a preference shift. We show this plasticity is driven by a striatal “prediction error,” signaling the discrepancy between the other’s choice and a subject’s own preferences. Thus, our data highlight that mPFC encodes agent-independent representations of subjective value, such that prediction errors simultaneously update multiple agents’ value representations. As the resulting change in representational similarity predicts interindividual differences in the malleability of subjective preferences, our findings shed mechanistic light on complex human processes such as the powerful influence of social interaction on beliefs and preferences.


          • Learning the values of another causes plasticity in a mPFC value representation

          • This plasticity predicts how much subjects’ own preferences change

          • Plasticity is explained by a striatal surprise signal

          • Value coding in mPFC occurs independently of the agent for whom a decision is made


          Garvert et al. demonstrate that learning the preferences of another person increases the similarity between neural value representations for self and other. This plasticity in medial prefrontal cortex predicts how much one’s own preferences shift toward those of the other.

          Related collections

          Most cited references 54

          • Record: found
          • Abstract: found
          • Article: not found

          Repetition and the brain: neural models of stimulus-specific effects.

          One of the most robust experience-related cortical dynamics is reduced neural activity when stimuli are repeated. This reduction has been linked to performance improvements due to repetition and also used to probe functional characteristics of neural populations. However, the underlying neural mechanisms are as yet unknown. Here, we consider three models that have been proposed to account for repetition-related reductions in neural activity, and evaluate them in terms of their ability to account for the main properties of this phenomenon as measured with single-cell recordings and neuroimaging techniques. We also discuss future directions for distinguishing between these models, which will be important for understanding the neural consequences of repetition and for interpreting repetition-related effects in neuroimaging data.
            • Record: found
            • Abstract: found
            • Article: not found

            Varieties of impulsivity.

             J Evenden (1999)
            The concept of impulsivity covers a wide range of "actions that are poorly conceived, prematurely expressed, unduly risky, or inappropriate to the situation and that often result in undesirable outcomes". As such it plays an important role in normal behaviour, as well as, in a pathological form, in many kinds of mental illness such as mania, personality disorders, substance abuse disorders and attention deficit/hyperactivity disorder. Although evidence from psychological studies of human personality suggests that impulsivity may be made up of several independent factors, this has not made a major impact on biological studies of impulsivity. This may be because there is little unanimity as to which these factors are. The present review summarises evidence for varieties of impulsivity from several different areas of research: human psychology, psychiatry and animal behaviour. Recently, a series of psychopharmacological studies has been carried out by the present author and colleagues using methods proposed to measure selectively different aspects of impulsivity. The results of these studies suggest that several neurochemical mechanisms can influence impulsivity, and that impulsive behaviour has no unique neurobiological basis. Consideration of impulsivity as the result of several different, independent factors which interact to modulate behaviour may provide better insight into the pathology than current hypotheses based on serotonergic underactivity.
              • Record: found
              • Abstract: found
              • Article: not found

              Reward representations and reward-related learning in the human brain: insights from neuroimaging.

              This review outlines recent findings from human neuroimaging concerning the role of a highly interconnected network of brain areas including orbital and medial prefrontal cortex, amygdala, striatum and dopaminergic mid-brain in reward processing. Distinct reward-related functions can be attributed to different components of this network. Orbitofrontal cortex is involved in coding stimulus reward value and in concert with the amygdala and ventral striatum is implicated in representing predicted future reward. Such representations can be used to guide action selection for reward, a process that depends, at least in part, on orbital and medial prefrontal cortex as well as dorsal striatum.

                Author and article information

                Cell Press
                21 January 2015
                21 January 2015
                : 85
                : 2
                : 418-428
                [1 ]Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, UK
                [2 ]Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Russell Square House, 10-12 Russell Square, London WC1B 5EH, UK
                [3 ]Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9D, UK
                Author notes
                []Corresponding author mona.garvert.11@
                © 2015 The Authors

                This is an open access article under the CC BY license (




                Comment on this article