Motivational context for response inhibition influences proactive involvement of attention

Motoric inhibition is ingrained in human cognition and implicated in pervasive neurological diseases and disorders. The present electroencephalographic (EEG) study investigated proactive motivational adjustments in attention during response inhibition. We compared go-trial data from a stop-signal task, in which infrequently presented stop-signals required response cancellation without extrinsic incentives ("standard-stop"), to data where a monetary reward was posted on some stop-signals ("rewarded-stop"). A novel EEG analysis was used to directly model the covariation between response time and the attention-related N1 component. A positive relationship between response time and N1 amplitudes was found in the standard-stop context, but not in the rewarded-stop context. Simultaneously, average go-trial N1 amplitudes were larger in the rewarded-stop context. This suggests that down-regulation of go-signal-directed attention is dynamically adjusted in the standard-stop trials, but is overridden by a more generalized increase in attention in reward-motivated trials. Further, a diffusion process model indicated that behavior between contexts was the result of partially opposing evidence accumulation processes. Together these analyses suggest that response inhibition relies on dynamic and flexible proactive adjustments of low-level processes and that contextual changes can alter their interplay. This could prove to have ramifications for clinical disorders involving deficient response inhibition and impulsivity

A meta-analytic investigation of the role of reward on inhibitory control

Contemporary theories predict that Inhibitory Control (IC) can be improved when rewards are available for successfully inhibiting. In non-clinical samples empirical research has demonstrated some support, however 'null' findings have also been published. The aim of this meta-analysis was to clarify the magnitude of the effect of reward on IC, and identify potential moderators. Seventy-three articles (contributing k = 80 studies) were identified from Pubmed, PsychInfo and Scopus, published between 1997 - 2020, using a systematic search strategy. A random effects meta-analysis was performed on effect sizes generated from IC tasks which included rewarded and non-rewarded inhibition trials. Moderator analyses were conducted on clinical samples (vs 'healthy controls'), task type (Go/No-Go vs Stop Signal vs Flanker vs Simon vs Stroop vs Anti-Saccade), reward type (monetary vs points vs other), and age (adults vs children). The prospect of reward for successful inhibition significantly improved IC (SMD=0.429 (95% CI= 0.288, 0.570), I2=96.7%), compared to no reward conditions/groups. This finding was robust against influential cases and outliers. The significant effect was present across all IC tasks. There was no evidence the effect was moderated by type of reward, age or clinical samples. Moderator analyses did not resolve considerable heterogeneity. Findings suggest that IC is a transient state that fluctuates in response to motivations driven by reward. Future research might examine the potential of improving inhibitory control through rewards as a behavioural intervention

Proactive inhibitory control: a general biasing account

Flexible behavior requires a control system that can inhibit actions in response to changes in the environment. Recent studies suggest that people proactively adjust response parameters in anticipation of a stop signal. In three experiments, we tested the hypothesis that proactive inhibitory control involves adjusting both attentional and response settings, and we explored the relationship with other forms of proactive and anticipatory control. Subjects responded to the color of a stimulus. On some trials, an extra signal occurred. The response to this signal depended on the task context subjects were in: in the ‘ignore’ context, they ignored it; in the ‘stop’ context, they had to withhold their response; and in the ‘double-response’ context, they had to execute a secondary response. An analysis of event-related brain potentials for no-signal trials in the stop context revealed that proactive inhibitory control works by biasing the settings of lower-level systems that are involved in stimulus detection, action selection, and action execution. Furthermore, subjects made similar adjustments in the double-response and stop-signal contexts, indicating an overlap between various forms of proactive action control. The results of Experiment 1 also suggest an overlap between proactive inhibitory control and preparatory control in task-switching studies: both require reconfiguration of task-set parameters to bias or alter subordinate processes. We conclude that much of the top-down control in response inhibition tasks takes place before the inhibition signal is presente

The Effects of Reward and Risk Level Associated with Speeded Actions: Evidence from Behavior and Electroencephalography

Choosing a course of action in our daily lives requires an accurate assessment of the associated risks as well as the potential rewards. The present two studies investigated the mechanism of how reward and risk level influence the motor decisions of speeded actions (Chapter 2) and its neural dynamics (Chapter 3) by focusing on the beta band (15-30 Hz) oscillation patterns reflected in the EEG signals. Participants performed a modified version of the Go-NoGo task, in which they earned reward points based on the speed and accuracy of response. On each trial, the reward points at stake (120 vs. 6) and the probability that a Go signal would follow (Go-probability) were presented prior to a Go/NoGo signal (Trial Information Period). The behavioral results (from both Chapters 2 and 3) showed that larger amount of rewards can motivate people to respond faster, and this effect was modulated by the assessed risk, suggesting that decisions for actions are based on a systematic trade-off between rewards and risks. The EEG data showed that motor beta oscillations from the two studied brain regions reflected different levels of motivation towards a motor response across different reward and risk levels. Specifically, the lower beta power associated with higher reward and lower risk level. Collectively, the results provide a mechanistic understanding of how motivational cues are translated into action outcomes via modulating patterns of brain oscillations

Action control in uncertain environments

A long-standing dichotomy in neuroscience pits automatic or reflexive drivers of behaviour against deliberate or reflective processes. In this thesis I explore how this concept applies to two stages of action control: decision-making and response inhibition. The first part of this thesis examines the decision-making process itself during which actions need to be selected that maximise rewards. Decisions arise through influences from model-free stimulus-response associations as well as model-based, goal-directed thought. Using a task that quantifies their respective contributions, I describe three studies that manipulate the balance of control between these two systems. I find that a pharmacological manipulation with levodopa increases model-based control without affecting model-free function; disruption of dorsolateral prefrontal cortex via magnetic stimulation disrupts model-based control; and direct current stimulation to the same prefrontal region has no effect on decision-making. I then examine how the intricate anatomy of frontostriatal circuits subserves reinforcement learning using functional, structural and diffusion magnetic resonance imaging (MRI). A second stage of action control discussed in this thesis is post-decision monitoring and adjustment of action. Specifically, I develop a response inhibition task that dissociates reactive, bottom-up inhibitory control from proactive, top-down forms of inhibition. Using functional MRI I show that, unlike the strong neural segregation in decision-making systems, neural mechanisms of reactive and proactive response inhibition overlap to a great extent in their frontostriatal circuitry. This leads to the hypothesis that neural decline, for 4 example in the context of ageing, might affect reactive and proactive control similarly. I test this in a large population study administered through a smartphone app. This shows that, against my prediction, reactive control reliably declines with age but proactive control shows no such decline. Furthermore, in line with data on gender differences in age-related neural degradation, reactive control in men declines faster with age than that of women