Implicit visual cues tune oscillatory motor activity during decision-making.

Motor decisions entails a buildup of choice-selective activity in the motor cortex. The rate of this buildup crucially depends on the amount of evidence favoring the selection of each action choice in the visual environment. Though numerous studies have characterized how sensory evidence drives motor activity when processed consciously, very little is known about the neural mechanisms that underlie the integration of implicit sources of information. Here, we used electroencephalography to investigate the impact of implicit visual cues on response-locked potentials and oscillatory activity in the motor cortex during decision-making. Subjects were required to select between left and right index finger responses according to the motion direction of a cloud of dots presented in one of three possible colors. Unbeknown to the participants, the color cue could bring evidence either in favor of or against the selection of the correct response. Implicit color cues tuned choice-selective oscillatory activity in the low beta range (16-25 Hz), boosting the buildup of contralateral activity when evidence favored the selection of the correct action, while weakening it when evidence biased against the correct response. This modulation of oscillatory activity influenced the speed at which the correct action was eventually chosen. Implicit cues also altered oscillatory activity in a non-selective way in the low frequency oscillation (1-7 Hz) and high beta ranges (25-35 Hz), impacting both contralateral and ipsilateral activity. The current findings yield a critical extension of prior observations by indicating that the integration of both explicit and implicit sources of evidence tunes oscillatory motor activity during decision-making.

Region-Specific Summation Patterns Inform the Role of Cortical Areas in Selecting Motor Plans.

Given an instruction regarding which effector to move and what location to move to, simply adding the effector and spatial signals together will not lead to movement selection. For this, a nonlinearity is required. Thresholds, for example, can be used to select a particular response and reject others. Here we consider another useful nonlinearity, a supralinear multiplicative interaction. To help select a motor plan, spatial and effector signals could multiply and thereby amplify each other. Such an amplification could constitute one step within a distributed network involved in response selection, effectively boosting one response while suppressing others. We therefore asked whether effector and spatial signals sum supralinearly for planning eye versus arm movements from the parietal reach region (PRR), the lateral intraparietal area (LIP), the frontal eye field (FEF), and a portion of area 5 (A5) lying just anterior to PRR. Unlike LIP neurons, PRR, FEF, and, to a lesser extent, A5 neurons show a supralinear interaction. Our results suggest that selecting visually guided eye versus arm movements is likely to be mediated by PRR and FEF but not LIP.

Systematic bias in representation of reaction time distribution.

A correct perception of one's own abilities is essential for making appropriate decisions. A well-known bias in probability perception is that rare events are overestimated. Here, we examined whether such a bias also exists for action outcomes using a simple reaction task. In Experiment 1, after completing a set of 30 trials of the simple reaction task, participants were required to judge the probability that they would be able to respond before a given reference time when performing the task next. We assessed the difference between the actual reaction times and the probability judgement and found that the represented probability distribution was more widely distributed than the actual one, suggesting that low-probability events were overestimated and high-probability events were underestimated. Experiment 2 confirmed the presence of such a bias in the representation of both one's own and another's reaction times. In addition, Experiment 3 showed the presence of such a bias regardless of the difference between the representation of another's reaction times and the mere numerical representation. Furthermore, Experiment 4 found the presence of such a bias even when the information regarding actual reaction times was visually shown before the representation. The present results reveal the existence of a highly robust bias in the representation of motor performance, which reflects the ubiquitous bias in probability perception and is difficult to eliminate.

Motor Decision-Making as a Common Denominator in Motor Pathology and a Possible Rehabilitation Target.

Despite the substantial progress in motor rehabilitation, patient involvement and motivation remain major challenges. They are typically addressed with communicational and environmental strategies, as well as with improved goal-setting procedures. Here we suggest a new research direction and framework involving Neuroeconomics principles to investigate the role of Motor Decision-Making (MDM) parameters in motivational component and motor performance in rehabilitation. We argue that investigating NE principles could bring new approaches aimed at increasing active patient engagement in the rehabilitation process by introducing more movement choice, and adapting existing goal-setting procedures. We discuss possible MDM implementation strategies and illustrate possible research directions using examples of stroke and psychiatric disorders.

Action Selection and Motor Decision Making: Insights from Transcranial Magnetic Stimulation.

In everyday life, goal-oriented motor behaviour relies on the estimation of the rewards/costs associated with alternative actions and on the appropriate selection of movements. Motor decision making is defined as the process by which a motor plan is chosen among a set of competing actions based on the expected value. In the present literature review we discuss evidence from transcranial magnetic stimulation (TMS) studies of motor control. We focus primarily on studies of action selection for instructed movements and motor decision making. In the first section, we delve into the usefulness of various TMS paradigms to characterise the contribution of motor areas and distributed brain networks to cued action selection. Then, we address the influence of motivational information (e.g., reward and biomechanical cost) in guiding action choices based on TMS findings. Finally, we conclude that TMS represents a powerful tool for elucidating the neurophysiological mechanisms underlying action choices in humans.

Competition Rather Than Observation and Cooperation Facilitates Optimal Motor Planning.

Humans tend to select motor planning with a high reward and low success compared with motor planning, which has a small reward and high success rate. Previous studies have shown such a risk-seeking property in motor decision tasks. However, it is unclear how to facilitate a shift from risk-seeking to optimal motor planning that maximizes the expected reward. Here, we investigate the effect of interacting with virtual partners/opponents on motor plans since interpersonal interaction has a powerful influence on human perception, action, and cognition. This study compared three types of interactions (competition, cooperation, and observation) and two types of virtual partners/opponents (those engaged in optimal motor planning and those engaged in risk-averse motor planning). As reported in previous studies, the participants took a risky aim point when they performed a motor decision task alone. However, we found that the participant's aim point was significantly modulated when they performed the same task while competing with a risk-averse opponent (p = 0.018) and that there was no significant difference from the optimal aim point (p = 0.63). No significant modulation in the aim points was observed during the cooperation and observation tasks. These results highlight the importance of competition for modulating suboptimal decision-making and optimizing motor performance.