Neurodynamic Evidence Supports a Forced-Excursion Model of Decision-Making under Speed/Accuracy Instructions

Spieser, L., Kohl, C., Forster, B., Bestmann, S. & Yarrow, K. (2018). Neurodynamic Evidence Supports a Forced-Excursion Model of Decision-Making under Speed/Accuracy Instructions. eNeuro, doi: 10.1523/ENEURO.0159-18.2018

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Abstract

Evolutionary pressures suggest that choices should be optimised to maximise rewards, by appropriately trading speed for accuracy. This speed-accuracy tradeoff (SAT) is commonly explained by variation in just the baseline-to-boundary distance, i.e. excursion, of accumulation-to-bound models of perceptual decision making. However, neural evidence is not consistent with this explanation. A compelling account of speeded choice should explain both overt behaviour and the full range of associated brain signatures. Here, we reconcile seemingly contradictory behavioural and neural findings. In two variants of the same experiment, we triangulated upon the neural underpinnings of the SAT in the human brain using both EEG and TMS. We found that distinct neural signals, namely the ERP centroparietal positivity (CPP) and a smoothed motor-evoked potential (MEP) signal, which have both previously been shown to relate to decision-related accumulation, revealed qualitatively similar average neurodynamic profiles with only subtle differences between SAT conditions. These signals were then modelled from behaviour by either incorporating traditional boundary variation or utilising a forced excursion. These model variants are mathematically equivalent, in terms of their behavioural predictions, hence providing identical fits to correct and erroneous reaction time distributions. However, the forced-excursion version instantiates SAT via a more global change in parameters and implied neural activity, a process conceptually akin to, but mathematically distinct from, urgency. This variant better captured both ERP and MEP neural profiles, suggesting that the SAT may be implemented via neural gain modulation, and reconciling standard modelling approaches with human neural data.

Publication Type: Article
Subjects: B Philosophy. Psychology. Religion > BF Psychology
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Departments: School of Social Sciences > Department of Psychology
URI: http://openaccess.city.ac.uk/id/eprint/19866

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