Executive Functions and Performance Variability Measured by Event-Related Potentials to Understand the Neural Bases of Perceptual Decision-Making

摘要

Deciding between different choices: neurocognitive factors of decision-making and response variability Perceptual decision-making tasks usually require subjects to recognize stimulus categories and select between different response alternatives. For example, in Go/No-go tasks, one has to respond to target stimuli and withhold responding to non-target stimuli. Accomplishing even just a single trial of such a task needs a complex sequence of functions (most of them executive) consisting, for example, in motor readiness, sustained attention, sensory processing, inhibitory control, conflict monitoring, stimulus-response mapping, context updating and, if any, error detection and awareness. In this context, the motor response reflects the behavioral outcome of the fast and proper interaction of the above-mentioned processes, and the response consistency (or variability) is often adopted as index of executive functioning.Nowadays, one challenge of the cognitive neuroscience is to understand how executive functions allow to make decisions. In fact, understanding decisional processes, and reasons of decision failure, would be helpful to clarify the executive dysfunctions of clinical conditions such as obsessive compulsive disorders, impulsivity, and addictions (typically intended as a failure of inhibition; Chamberlain et al., 2005 ; Crews and Boettiger, 2009 ; álvarez-Moya et al., 2011 ), as well as success in real-life tasks (e.g., car driving; Bunce et al., 2012 ) and goal-directed behaviors (e.g., complying with diet schedules; Jahanshahi et al., 2015 ). In this context, the response variability reflects a behavioral index of efficiency of frontal cognitive control (Bellgrove et al., 2004 ), and this association was suggested since the first half of the twentieth century, when Head ( 1926 , p. 145) reported that “ an inconsistent response is one of the most striking consequences of lesions to the cerebral cortex.” More recently, consistent literature indicated response variability as an indirect index of top down control (Tamm et al., 2012 ), executive functioning (Swick et al., 2013 ), neurological (Segalowitz et al., 1997 ; Hultsch et al., 2000 ), and psychiatric conditions (Barkley et al., 1992 ; Vinogradov et al., 1998 ; Leth-Steensen et al., 2000 ), and frontal lobes integrity (Bunce et al., 2007 ; Walhovd and Fjell, 2007 ; L?vdén et al., 2013 ). The frontal cortex is in fact considered as the main region supporting the executive functions and behavioral variability (Stuss et al., 2003 ), as revealed by the poor response consistency and accuracy of frontal patients performing a decision-making task (Arnot, 1952 ; Stuss et al., 1999 , 2003 ; Picton et al., 2007 ).Even though it is evident the relationship between executive functioning and performance variability at group level (e.g., in the comparison between high- and low-level athletes in sport; Vestberg et al., 2012 ), it is less known the mediating role of response variability at intra-individual level. Also, it is still not clear the mediating role of PFC activity in the intra-individual variability because of contrasting results of neuroimaging studies: in fact, two studies reported a greater dorsolateral PFC (DLPFC) activation associated with high intra-individual variability (Bellgrove et al., 2004 ; Simmonds et al., 2007 ), while Weissman et al. ( 2006 ) reported reduced pre-stimulus activity of the right DLPFC in the less consistent trials. In other words, depending on the main findings, neuroimaging literature interpreted the high individual variability as the consequence of the greater need of top-down executive control (enhanced PFC activation), or in terms of lapses in attention (reduced PFC activation). ERPs and executive functions: state of the art and main limitations Identification of neurophysiological correlates of executive functioning requires to investigate different cognitive abilities, which in part depend on the experimental paradigm: for example, in Stroop or sustained attention tasks (Demeter and Woldorff, 2016 ), voluntary selective attention would be more stressed than Go/No-go tasks in which accumulation of sensory evidence would be determinant, or oddball tasks where decision making in effected by expectancy, or stop-signal tasks in which the so-called “reactive inhibition” is often required (for a review see Jahanshahi et al., 2015 ). It is also relevant to note that decisional processes work in a narrow temporal window, such as the time needed to perform a single trial in a speeded decision-making task. This constraint requires the researchers to adopt a technique with adequate temporal resolution to carry out their own investigations: this means that neuroimaging studies may not be the most suitable to investigate the fast temporal succession of the decisional processes. Moreover, as also suggested by Bogacz et al. ( 2010 ), the duration of the decision processes can affect the amplitude of the BOLD signal, therefore funct