To Head or to Heed? Beyond the Surface of Selective Action Inhibition: A Review

To head rather than heed to temptations is easier said than done. Since tempting actions are often contextually inappropriate, selective suppression is invoked to inhibit such actions. Thus far, laboratory tasks have not been very successful in highlighting these processes. We suggest that this is for three reasons. First, it is important to dissociate between an early susceptibility to making stimulus-driven impulsive but erroneous actions, and the subsequent selective suppression of these impulses that facilitates the selection of the correct action. Second, studies have focused on mean or median reaction times (RT), which conceals the temporal dynamics of action control. Third, studies have focused on group means, while considering individual differences as a source of error variance. Here, we present an overview of recent behavioral and imaging studies that overcame these limitations by analyzing RT distributions. As will become clear, this approach has revealed variations in inhibitory control over impulsive actions as a function of task instructions, conflict probability, and between-trial adjustments (following conflict or following an error trial) that are hidden if mean RTs are analyzed. Next, we discuss a selection of behavioral as well as imaging studies to illustrate that individual differences are meaningful and help understand selective suppression during action selection within samples of young and healthy individuals, but also within clinical samples of patients diagnosed with attention deficit/hyperactivity disorder or Parkinson's disease

Time–Frequency and ERP Analyses of EEG to Characterize Anticipatory Postural Adjustments in a Bimanual Load-Lifting Task

Anticipatory postural adjustments (APAs) compensate in advance for the destabilizing effect of a movement. This study investigated the specific involvement of each primary motor cortex (M1) during a bimanual load-lifting task in which subjects were required to maintain a stable forearm position during voluntary unloading. Kinematics, electromyographic, and electroencephalographic (EEG) data were recorded in eight right-handed healthy subjects lifting a load placed on their left forearm. Two EEG analyses were performed: a time–frequency (TF) analysis and an event-related potential (ERP) analysis. The TF analysis revealed a mean power decrease in the mu rhythm over the left and right M1 concomitant with lifting onset. Each decrease showed specific features: over the right M1, contralateral to the postural forearm, there was a steeper slope and a greater amplitude than over the left M1. Although a mu rhythm desynchronization has until now been the signature of cortical activity related to a motor component, we show that it can also be related to postural stabilization. We discuss the involvement of the mu rhythm desynchronization over the postural M1 in the high temporal precision enabling efficient APAs. ERP analysis showed a negative wave over the left M1 and a concomitant positive wave over the right M1. While the negative wave classically reflects M1 recruitment related to the forthcoming lifting, the novelty here is that the positive wave reflects the transmission of inhibitory commands toward the postural forearm

Basics for sensorimotor information processing: some implications for learning.

AbstractIn sensorimotor activities, learning requires efficient information processing; whether in car driving, sport activities or human-machine interactions. Several factors may affect the efficiency of such processing: they may be extrinsic (i.e. task-related) on intrinsic (i.e. subjects-related). The effects of these factors are intimately related to the structure of human information processing. In the present article we will focus on some of them, which are poorly taken into account, even when minimizing errors or their consequences is an essential issue at stake. Among the extrinsic factors, we will discuss, first, the effects of the quantity and quality of information, secondly, the effects of instruction and thirdly motor program learning. Among the intrinsic factors, we will discuss first the influence of prior information, secondly how individual strategies affect performance and, thirdly, we will stress the fact that although the human brain is not structured to function errorless (which is not a new) humans are able to detect their errors very quickly and (in most of the cases), fast enough to correct them before they result in an overt failure