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Selective alteration of human value decisions with medial frontal tDCS is predicted by changes in attractor dynamics

Hämmerer, D; Bonaiuto, J; Klein-Flügge, M; Bikson, M; Bestmann, S; (2016) Selective alteration of human value decisions with medial frontal tDCS is predicted by changes in attractor dynamics. Scientific Reports , 6 , Article 25160. 10.1038/srep25160. Green open access

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Abstract

During value-based decision making, ventromedial prefrontal cortex (vmPFC) is thought to support choices by tracking the expected gain from different outcomes via a competition-based process. Using a computational neurostimulation approach we asked how perturbing this region might alter this competition and resulting value decisions. We simulated a perturbation of neural dynamics in a biophysically informed model of decision-making through in silico depolarization at the level of neuronal ensembles. Simulated depolarization increased baseline firing rates of pyramidal neurons, which altered their susceptibility to background noise, and thereby increased choice stochasticity. These behavioural predictions were compared to choice behaviour in healthy participants performing similar value decisions during transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique. We placed the soma depolarizing electrode over medial frontal PFC. In line with model predictions, this intervention resulted in more random choices. By contrast, no such effect was observed when placing the depolarizing electrode over lateral PFC. Using a causal manipulation of ventromedial and lateral prefrontal function, these results provide support for competition-based choice dynamics in human vmPFC, and introduce computational neurostimulation as a mechanistic assay for neurostimulation studies of cognition.

Type: Article
Title: Selective alteration of human value decisions with medial frontal tDCS is predicted by changes in attractor dynamics
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/srep25160
Publisher version: http://dx.doi.org/10.1038/srep25160
Language: English
Additional information: Copyright © This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Human behaviour; Network models; Operant learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Institute of Cognitive Neuroscience
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
URI: https://discovery.ucl.ac.uk/id/eprint/1494156
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