An object-tracking model that combines position and speed explains spatial and temporal responses in a timing task

Many tasks require synchronizing our actions withparticular moments along the path of moving targets.However, it is controversial whether we base theseactions on spatial or temporal information, and whetherusing either can enhance our performance. Weaddressed these questions with a coincidence timingtask. A target varying in speed and motion durationapproached a goal. Participants stopped the target andwere rewarded according to its proximity to the goal.Results showed larger reward for responses temporally(rather than spatially) equidistant to the goal acrossspeeds, and this pattern was promoted by longer motiondurations. We used a Kalman filter to simulate time andspace-based responses, where modeled speeduncertainty depended on motion duration and positionaluncertainty on target speed. The comparison betweensimulated and observed responses revealed that a singleposition-tracking mechanism could account for bothspatial and temporal patterns, providing a unifiedcomputational explanation

Number line estimation in highly math-anxious individuals

In the present study we aimed to investigate the difficulties highly math-anxious individuals (HMA) may face when having to estimate a number's position in a number line task. Twenty-four HMA and 24 low math-anxiety (LMA) individuals were presented with four lines with endpoints 0-100, 0-1000, 0-100000 and 267-367 on a computer monitor on which they had to mark the correct position of target numbers using the mouse. Although no differences were found between groups in the frequency of their best-fit model, which was linear for all lines, the analysis of slopes and intercepts for the linear model showed that the two groups differed in performance on the less familiar lines (267-367 and 0-100000). Lower values for the slope and higher values for the intercept were found in the HMA group, suggesting that they tended to overestimate small numbers and underestimate large numbers on these non-familiar lines. Percentage absolute error analyses confirmed that HMA individuals were less accurate than their LMA counterparts on these lines, although no group differences were found in response time. These results indicate that math anxiety is related to worse performance only in the less familiar and more difficult number line tasks. Therefore, our data challenge the idea that HMAs individuals might have less precise numerical representations and support the anxiety-complexity effect posited by Ashcraft and colleagues

Decoupling sensory from decisional choice biases in perceptual decision making

The contribution of sensory and decisional processes to perceptual decision making is still unclear, even in simple perceptual tasks. When decision makers need to select an action from a set of balanced alternatives, any tendency to choose one alternative more often choice bias is consistent with a bias in the sensory evidence, but also with a preference to select that alternative independently of the sensory evidence. To decouple sensory from decisional biases, here we asked humans to perform a simple perceptual discrimination task with two symmetric alternatives under two different task instructions. The instructions varied the response mapping between perception and the category of the alternatives. We found that from 32 participants, 30 exhibited sensory biases and 15 decisional biases. The decisional biases were consistent with a criterion change in a simple signal detection theory model. Perceptual decision making, thus, even in simple scenarios, is affected by sensory and decisional choice biases

The Confidence Database

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects

Sensorimotor decision-making with moving objects

[eng] Moving is essential for us to survive, and in countless occasions we move in response to visual information. However, this process is characterized as uncertain, given the variability present both at the sensory and motor stages. A crucial question, then, is how to deal with this uncertainty in order for our actions to lead to the best possible outcomes. Statistical decision theory (SDT) is a normative framework that establishes how people should make decisions in the presence of uncertainty. This theory identifies the optimal action as that which maximizes the expected reward (outcome) of the situation. Movement planning can be reformulated in terms of SDT, so that the focus is placed on the decisional component. Some experimental work making use of this theoretical approach has concluded that humans are optimal movement planners, while other has identified situations where suboptimality arises. However, sensorimotor decision-making within SDT has commonly eluded scenarios of interaction with moving objects. At the same time, the work devoted to moving objects has not focused on the decisional aspect. The present thesis aims at bridging both fields, with each of our three studies trying to answer different questions. Given the spatiotemporal nature of situations with moving objects, we can plan our actions by relying on both temporal and spatial cues provided by the object. In Study I we investigated whether exploiting more one type of these visual cues led to a better performance, as defined by the reward given after each action. In our task we presented a target, which could vary in speed and motion time, approaching a line. Participants responded to stop the target and were rewarded according to its proximity to the line. Responding after the target crossed the line was penalized. We discovered that those participants planning their responses based on time-based motion cues had a better performance than those monitoring the target’s changing spatial position. This was due to the former approach circumventing a limitation imposed by the resolution of the visual system. We also found that viewing the object for longer favored time-based responses, as mediated by longer integration time. Finally, we used existing SDT models to obtain a reference of optimality, but we defend that these models are limited to interpret our data. Study II built on our previous findings to explore whether the use of temporal cues could be learnt. We took our previous paradigm and adapted it so that reward was manipulated after each task in order to foster exploiting temporal information. There was no evidence for learning taking place, since participants using temporal cues did so from the start of the experiment. Whether other methods reward can shape the use of certain cues, and why some people naturally tend to make more use of temporal information, still remain elusive. Study III deepened our knowledge on which variability people consider when planning their responses. We hypothesized that the reason why people are suboptimal (as defined by SDT) in many situations is because they represent only their measurement variability, roughly equivalent to the execution noise, while excluding the variability created by sudden changes in their planning. We took previous data and used a Kalman filter to extract each participant’s measurement variability. We then used it to compute SDT-derived optimal responses, and discovered that they explained well our data, giving support to our hypothesis. We also found evidence for participants using the information provided by reward both to avoid being penalized and to choose the point at which to stabilize their responses. Taken together, our experimental work presents interaction with moving objects as a complex set of situations where different information guides our response planning. Firstly, visual cues of different origin. Secondly, our variability, coming from many sources, some of which may not be considered. Finally, the outcomes related to each action.[cat] Moure’s és essencial per a la nostra supervivència, i en incomptables ocasions ens movem en resposta a informació visual. Tanmateix, aquest procés és incert, donada la variabilitat present tant a l'estadi sensorial com en el motor. Una pregunta crucial, doncs, és com gestionar aquesta incertesa perquè les nostres accions portin a les millors conseqüències possibles. La teoria de la decisió estadística (Statistical decision theory, SDT) és un marc teòric normatiu que estableix com la gent hauria de fer decisions en presència d'incertesa. Aquesta teoria identifica l'acció òptima amb aquella que maximitza la recompensa (entesa com a conseqüència) esperada de la situació. La planificació del moviment pot ser reformulada en termes de SDT, de tal manera que s’emfatitza el component decisional. Diferents treballs experimentals que han fet servir aquesta aproximació teòrica han conclòs que els humans som planificadors de moviment òptims, mentre que altres han identificat situacions on la suboptimalitat sorgeix. No obstant això, la presa de decisions sensoriomotora des de SDT normalment ha ignorat escenaris que requereixen d'interacció com objectes en moviment. Alhora, els treballs dedicats als objectes en moviment no s'han centrat en l'aspecte de decisió. La present tesi es proposa acostar els dos camps, amb cada un dels nostres tres estudis intentant respondre diferents preguntes. L’Estudi I descobrí que, per planificar les nostres decisions, fer servir informació temporal portà a un millor rendiment que fer servir informació espacial, i això fou facilitat per veure l'objecte durant més temps. També vam criticar la limitació de certs models d’SDT per interpretar els nostres dades. L'Estudi II intentà promoure l'ús d'informació temporal, tot i que no s’aconseguí fomentar l’aprenentatge. Finalment, l’'Estudi III trobà que la raó per la qual la gent és subòptima en moltes situacions es deu al fet que representa només la seva variabilitat de mesura, més o menys equivalent al soroll d'execució, mentre que s'exclou la variabilitat creada per sobtats canvis en la planificació de la resposta. També trobàrem que els participants van usar la informació donada per la recompensa tant per evitar ser penalitzats com per escollir el punt on estabilitzar les seves respostes

Confidence guides priority between forthcoming tasks

International audienceAbstract Humans can estimate confidence in their decisions, and there is increasing interest on how this feeling of confidence regulates future behavior. Here, we investigate whether confidence in a perceptual task affects prioritizing future trials of that task, independently of task performance. To do so, we experimentally dissociated confidence from performance. Participants judged whether an array of differently colored circles was closer to blue or red, and we manipulated the mean and variability of the circles’ colors across the array. We first familiarized participants with a low mean low variability condition and a high mean high variability condition, which were matched in performance despite participants being more confident in the former. Then we made participants decide in which order to complete forthcoming trials for both conditions. Crucially, prioritizing one condition was associated with being more confident in that condition compared to the other. This relationship was observed both across participants, by correlating inter-individual heterogeneity in prioritization and in confidence, and within participants, by assessing how changes in confidence with accuracy, condition and response times could predict prioritization choices. Our results suggest that confidence, above and beyond performance, guides prioritization between forthcoming tasks, strengthening the evidence for its role in regulating behavior

Confidence as a Priority Signal

International audienceWhen dealing with multiple tasks, we must establish the order in which to tackle them. In multiple experiments, including a preregistered replication (Ns = 16–105), we found that confidence, or the subjective accuracy of decisions, acts as a priority signal, both when ordering responses about tasks already completed or ordering tasks yet to be completed. Specifically, when participants categorized perceptual stimuli along two dimensions, they tended to first give the decision associated with higher confidence. When participants selected which of two tasks they wanted to perform first, they were slightly biased toward the task associated with higher confidence. This finding extends to nonperceptual decisions (mental calculation) and cannot be reduced to effects of task difficulty, response accuracy, response availability, or implicit demands. Our results thus support the role of confidence as a priority signal, thereby suggesting a new way in which it may regulate human behavior