A key aim of psychology is to explain the causes of human actions. However, mechanisms of intention, motivation, and agency have remained difficult to study experimentally, and their underlying psychological organisation remains unclear. This data gives measures of cognitive-motor performance of 94 healthy adult volunteers in a test battery designed to study intention and agency in humans. We used factor analysis to identify common action processes across a battery of five laboratory tasks measuring sense of agency, value-based decision-making, choice reactions, reactive inhibition and intentional inhibition. A three-factor solution was identified. The first factor, labelled ideomotor action control, involved unbiased experience of one’s own action consequences, together with good performance in risky monetary decision-making. Interestingly, low scores on this factor would suggest a distortion in the ability to represent and exploit one’s own instrumental effect on external events. The second factor, labelled psychomotor regulation, combined motor efficiency with a biased experience of one’s own actions. The third factor loaded exclusively on inhibitory control of pre-potent actions. Interestingly, it was unrelated to both decision-making variables and agency variables. Our results suggest clear linkage between decision-making processes and the phenomenology of action, even though these areas have historically been studied quite independently. Further, we show that cognitive control and experience of agency has a rich and reliable internal structure. Specifically, our results suggest two distinct and independent components of sense of agency: a bias in action awareness linked to psychomotor efficiency, and a bias in outcome awareness linked to poor decision-making.Most people recognise the experience of stopping themselves 'just in time' before committing an unwise action. We call this process 'intentional inhibition'. The capacity for intentional inhibition is as important for human volition as the capacity for initiating actions, and is essential for successful social interaction. However, it has been largely ignored, perhaps because it produces no measurable behavioural output. Yet our preliminary studies successfully identified processes of intentional inhibition distinct from external inhibition previously studied with 'stop' signals. We therefore propose the first systematic research programme on intentional inhibition of human action. Experimental paradigms for eliciting intentional inhibition are developed and implemented across four complementary laboratories. These are used to investigate psychological (CC1: London) and neural (CC2: Gent) mechanisms of intentional inhibition, and interactions of these mechanisms with reward, emotion and social context. The emergence of intentional inhibition in normal child development (CC3: Leiden) is contrasted with striking pathologies of the action/inhibition balance in Tourette's Syndrome (CC4: Hamburg). Specific research collaborations transfer knowledge and skills between partners, and integrate the various studies. We aim for a rigorous, scientific approach to a crucial but under-investigated aspect of human nature and individual behaviour.
Battery of five tasks - 1. Temporal binding (an implicit measure of sense of agency): Participants judged the time of their own voluntary action (pressing a key at a time of their choice) or of a computer-generated tone (100 ms 800 Hz), based on the position of a rotating clock hand. In two baseline conditions the voluntary keypress or the tone occurred in isolation, and participants judged the onset of each. In operant conditions, participants’ keypress triggered the tone after a delay of 250 ms. A temporal judgement error was calculated for each trial. Mean temporal judgement errors in the baseline conditions were subtracted from errors in the operant conditions to calculate the shift of the perceived time of an action towards its outcome (action binding) and the shift in perceived time of an outcome towards its action cause (outcome binding). 2. Reactive stopping (assesses stimulus-driven response inhibition): Participants pressed a key as quickly and accurately as possible in response to a visual Go-signal (a circle or a square), whose shape instructed a left or right hand response. In 25% of trials, an auditory Stop-signal was presented at a variable delay following the Go-signal. This delay was adjusted continuously using a 1up/1down staircase procedure (with a decrease upon errors of commission and an increase following successful inhibition). Stop-signal reaction time (SSRT) was calculated using the quantile method (18). For this, Go trial reaction times were listed in descending order. The mean Stop-signal delay was subtracted from the reaction time whose ordered position corresponded to the percentage of successful Stop-signal trials for that participant. Post-error slowing was calculated as the mean reaction time following an error of commission minus the mean reaction time across all other Go trials. The SSRT reflects the time needed to reactively inhibit an ongoing motor response, while post-error slowing reflects a behavioural adjustment following an error of commission. 3. Intentional stopping (tests subjects’ capacity to voluntary inhibit a pre-potent action): On each trial, participants saw a marble on a horizontal surface on the screen which started rolling to the right after a variable delay. As it began to roll, the marble turned either green or remained white. Participants had to press a key to prevent all green marbles from rolling off the screen (imperative Go trials). However, if the marble remained white, participants were instructed to press a key to stop the marble on approximately half of all trials and to withhold the action on the remainder (free choice trials). White marbles followed a sequence of 1, 2, 3 or 4 green marbles. The marbles’ speed was set by a staircase procedure prior to the main experiment, such that participants were able to stop green marbles on only ~50% of trials, ensuring a genuine time pressure to act. We measured the proportion of white marbles that were stopped as an index of overall bias towards action. We also regressed the percentage of stopped white marbles on the number of preceding green marbles to obtain an index of the tendency to act after a “Go” sequence as a function of sequence length. 4. Choice reaction (probes activation and inhibition of alternative motor plans during action selection): Participants made speeded key presses with their left or right hand in response to a left- or right pointing target arrow. A briefly presented subliminal prime, pointing in the same or in the opposite direction, preceded the target by 200 ms (compatible or incompatible priming, respectively). The prime was backward-masked to prevent conscious identification, as confirmed by a forced-choice post-test of prime recognition. Crucially, priming at this latency results in a negative compatibility effect, such that motor performance is slower and less accurate following compatible compared to incompatible primes. This effect is thought to reflect auto-inhibition of a motor plan initially activated but not immediately executed. Reaction time and error rate were combined in a single measure of inverse efficiency, and averaged across all trials. The difference between compatible and incompatible trials served as an index of auto-inhibitory regulation of action control. 5. Risk taking (monetary rewards are earner at an increasing cost of potential monetary losses): Participants repeatedly pressed a key to inflate a balloon on the screen. Each keypress could inflate the balloon a little further, adding 6p to participants’ earnings. However, repeated inflations were associated with an increasing risk of the balloon exploding, in which case earnings for that balloon were lost. After each inflation, participants could decide to inflate the balloon further or to collect the money earned for inflating the balloon so far by pressing another key. Two balloon colours indicated different risk levels (blue and yellow, counterbalanced across subjects). The risk of explosion at a given level of inflation was equal to 1/(n-k), with n equal to the maximum possible number of inflations (16 or 8, depending on the balloon colour) and k equal to the number of previous inflations for a given balloon. The meaning of the balloon colour was not made explicit. Post-test questioning showed that 68% of participants were aware that it signalled current risk level. Earnings were added to the basic hourly reimbursement. Two dependent variables were extracted. The mean number of inflations across balloons that did not explode, irrespective of balloon colour, served as an overall tendency for choosing risky. The difference between the mean number of inflations for low- vs. high-risk balloons that did not explode was taken as a measure of behavioural adjustment to risk.
