The timing database: An open-access, live repository for interval timing studies.

Interval timing refers to the ability to perceive and remember intervals in the seconds to minutes range. Our contemporary understanding of interval timing is derived from relatively small-scale, isolated studies that investigate a limited range of intervals with a small sample size, usually based on a single task. Consequently, the conclusions drawn from individual studies are not readily generalizable to other tasks, conditions, and task parameters. The current paper presents a live database that presents raw data from interval timing studies (currently composed of 68 datasets from eight different tasks incorporating various interval and temporal order judgments) with an online graphical user interface to easily select, compile, and download the data organized in a standard format. The Timing Database aims to promote and cultivate key and novel analyses of our timing ability by making published and future datasets accessible as open-source resources for the entire research community. In the current paper, we showcase the use of the database by testing various core ideas based on data compiled across studies (i.e., temporal accuracy, scalar property, location of the point of subjective equality, malleability of timing precision). The Timing Database will serve as the repository for interval timing studies through the submission of new datasets.

Temporal encoding: Relative and absolute representations of time guide behavior.

Temporal information-processing is critical for adaptive behavior and goal-directed action. It is thus crucial to understand how the temporal distance between behaviorally relevant events is encoded to guide behavior. However, research on temporal representations has yielded mixed findings as to whether organisms utilize relative versus absolute judgments of time intervals. To address this fundamental question about the timing mechanism, we tested mice in a duration discrimination procedure in which they learned to correctly categorize tones of different durations as short or long. After being trained on a pair of target intervals, the mice were transferred to conditions in which cue durations and corresponding response locations were systematically manipulated so that either the relative or absolute mapping remained constant. The findings indicate that transfer occurred most readily when relative relationships of durations and response locations were preserved. In contrast, when subjects had to re-map these relative relations, even when positive transfer initially occurred based on absolute mappings, their temporal discrimination performance was impaired, and they required extensive training to re-establish temporal control. These results demonstrate that mice can represent experienced durations both as having a certain magnitude (absolute representation) and as being shorter or longer of the two durations (an ordinal relation to other cue durations), with relational control having a more enduring influence in temporal discriminations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Temporal scaling and computing time in neural circuits: Should we stop watching the clock and look for its gears?

Timing underlies a variety of functions, from walking to perceiving causality. Neural timing models typically fall into one of two categories-"ramping" and "population-clock" theories. According to ramping models, individual neurons track time by gradually increasing or decreasing their activity as an event approaches. To time different intervals, ramping neurons adjust their slopes, ramping steeply for short intervals and vice versa. In contrast, according to "population-clock" models, multiple neurons track time as a group, and each neuron can fire nonlinearly. As each neuron changes its rate at each point in time, a distinct pattern of activity emerges across the population. To time different intervals, the brain learns the population patterns that coincide with key events. Both model categories have empirical support. However, they often differ in plausibility when applied to certain behavioral effects. Specifically, behavioral data indicate that the timing system has a rich computational capacity, allowing observers to spontaneously compute novel intervals from previously learned ones. In population-clock theories, population patterns map to time arbitrarily, making it difficult to explain how different patterns can be computationally combined. Ramping models are viewed as more plausible, assuming upstream circuits can set the slope of ramping neurons according to a given computation. Critically, recent studies suggest that neurons with nonlinear firing profiles often scale to time different intervals-compressing for shorter intervals and stretching for longer ones. This "temporal scaling" effect has led to a hybrid-theory where, like a population-clock model, population patterns encode time, yet like a ramping neuron adjusting its slope, the speed of each neuron's firing adapts to different intervals. Here, we argue that these "relative" population-clock models are as computationally plausible as ramping theories, viewing population-speed and ramp-slope adjustments as equivalent. Therefore, we view identifying these "speed-control" circuits as a key direction for evaluating how the timing system performs computations. Furthermore, temporal scaling highlights that a key distinction between different neural models is whether they propose an absolute or relative time-representation. However, we note that several behavioral studies suggest the brain processes both scales, cautioning against a dichotomy.

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.

Are you early or late?: Temporal error monitoring.

Temporal judgments regarding a target interval typically produce a nearly normally distributed reproduction times centered on the target with substantial variance. This phenomenon indicates that the majority of our temporal judgments are deviations from the target times, which are assumed to originate from the underlying timing uncertainty. Although humans were found to adapt their decisions in response to timing uncertainty, we do not know if they can accurately judge the direction and degree of their temporal errors. In this study, we asked participants to reproduce durations as accurately as possible. After each reproduction, participants were asked to retrospectively rate their confidence in their temporal estimates and to judge if their response time was earlier or later than the target interval. The results revealed that human participants are aware of both the direction and magnitude of their timing errors, pointing at an informationally rich temporal error monitoring ability. We further show that a sequential diffusion process can account for the detection of direction of errors as well as the qualitative features of the relationship of objective temporal errors with subjective confidence ratings and associated response times. (PsycINFO Database Record

The effects of payoff manipulations on temporal bisection performance.

There is growing evidence that alterations in reward rates modify timing behavior demonstrating the role of motivational factors in interval timing behavior. This study aimed to investigate the effects of manipulations of rewards and penalties on temporal bisection performance in humans. Participants were trained to classify experienced time intervals as short or long based on the reference durations. Two groups of participants were tested under three different bias conditions in which either the relative reward magnitude or penalty associated with correct or incorrect categorizations of short and long reference durations was manipulated. Participants adapted their choice behavior (i.e., psychometric functions shifted) based on these payoff manipulations in directions predicted by reward maximization. The signal detection theory-based analysis of the data revealed that payoff contingencies affected the response bias parameter (B″) without altering participants' sensitivity (A') to temporal distances. Finally, the response time (RT) analysis showed that short categorization RTs increased, whereas long categorization RTs decreased as a function of stimulus durations. However, overall RTs did not exhibit any modulation in response to payoff manipulations. Taken together, this study provides additional support for the effects of motivational variables on temporal decision-making.

Stimulus probability effects on temporal bisection performance of mice (Mus musculus).

In the temporal bisection task, participants classify experienced stimulus durations as short or long based on their temporal similarity to previously learned reference durations. Temporal decision making in this task should be influenced by the experienced probabilities of the reference durations for adaptiveness. In this study, we tested the temporal bisection performance of mice (Mus musculus) under different short and long reference duration probability conditions implemented across two experimental phases. In Phase 1, the proportion of reference durations (compared to probe durations) was 0.5, whereas in Phase 2 it was increased to 0.8 to further examine the adjustment of choice behavior with more frequent reference duration presentations (under higher reinforcement rate). Our findings suggest that mice developed adaptive biases in their choice behaviors. These adjustments in choice behavior were nearly optimal as the mice maximized their gain to a great extent which required them to monitor stimulus probabilities as well as the level of variability in their temporal judgments. We further found that short but not long categorization response times were sensitive to stimulus probability manipulations, which in turn suggests an asymmetry between short and long categorizations. Finally, we investigated the latent decision processes underlying the bias manifested in subjects' choice behavior within the diffusion model framework. Our results revealed that probabilistic information influenced the starting point and the rate of evidence accumulation process. Overall, the stimulus probability effects on choice behavior were modulated by the reinforcement rate. Our findings illustrate that mice can adapt their temporal behaviors with respect to the probabilistic contingencies in the environment.