Neurocomputational account of how the human brain decides when to have a break
ABSTRACT No pain, no gain: cost-benefit trade-off has been formalized in classical decision theory to account for how we choose whether to engage effort. However, how the brain decides when to have breaks in the course of effort production remains poorly understood. We propose that decisions to cease and resume work are triggered by a cost evidence accumulation signal reaching upper and lower bounds, respectively. We developed a task in which participants are free to exert a physical effort knowing that their payoff would be proportional to their effort duration. Functional MRI and magnetoencephalography recordings conjointly revealed that the theoretical cost evidence accumulation signal was expressed in proprioceptive regions (bilateral posterior insula). Furthermore, the slopes and bounds of the accumulation process were adapted to the difficulty of the task and the money at stake. Cost evidence accumulation might therefore provide a dynamical mechanistic account of how the human brain maximizes benefits while preventing exhaustion.
SourceAvailable from: Jeanick Brisswalter[Show abstract] [Hide abstract]
ABSTRACT: This study aimed at investigating concurrent changes in cognitive control and cerebral oxygenation (Cox) during steady intense exercise to volitional exhaustion. Fifteen participants were monitored using prefrontal near-infrared spectroscopy and electromyography of the thumb muscles during the completion of an Eriksen flanker task completed either at rest (control condition) or while cycling at a strenuous intensity until exhaustion (exercise condition). Two time windows were matched between the conditions to distinguish a potential exercise-induced evolutive cognitive effect: an initial period and a terminal period. In the initial period, Cox remained unaltered and, contrary to theoretical predictions, exercise did not induce any deficit in selective response inhibition. Rather, the drop-off of the delta curve as reaction time lengthened suggested enhanced efficiency of cognitive processes in the first part of the exercise bout. Shortly before exhaustion, Cox values were severely reduced – though not characteristic of a hypofrontality state – while no sign of deficit in selective response inhibition was observed. Despite this, individual’s susceptibility to making fast impulsive errors increased and less efficient online correction of incorrect activation was observed near exhaustion. A negative correlation between Cox values and error rate was observed and is discussed in terms of cerebral resources redistribution.Neuropsychologia 01/2015; 68. DOI:10.1016/j.neuropsychologia.2015.01.006 · 3.45 Impact Factor
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ABSTRACT: Recent years have seen a rejuvenation of interest in studies of motivation-cognition interactions arising from many different areas of psychology and neuroscience. The present issue of Cognitive, Affective, & Behavioral Neuroscience provides a sampling of some of the latest research from a number of these different areas. In this introductory article, we provide an overview of the current state of the field, in terms of key research developments and candidate neural mechanisms receiving focused investigation as potential sources of motivation-cognition interaction. However, our primary goal is conceptual: to highlight the distinct perspectives taken by different research areas, in terms of how motivation is defined, the relevant dimensions and dissociations that are emphasized, and the theoretical questions being targeted. Together, these distinctions present both challenges and opportunities for efforts aiming toward a more unified and cross-disciplinary approach. We identify a set of pressing research questions calling for this sort of cross-disciplinary approach, with the explicit goal of encouraging integrative and collaborative investigations directed toward them.Cognitive Affective & Behavioral Neuroscience 06/2014; 14(2). DOI:10.3758/s13415-014-0300-0 · 3.87 Impact Factor
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ABSTRACT: Given the option, humans and other animals elect to distribute their time between work and leisure, rather than choosing all of one and none of the other. Traditional accounts of partial allocation have characterised behavior on a macroscopic timescale, reporting and studying the mean times spent in work or leisure. However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved. We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity. We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.PLoS Computational Biology 12/2014; 10(12):e1003894. DOI:10.1371/journal.pcbi.1003894 · 4.87 Impact Factor