Converging evidence that common timing processes underlie temporal-order and simultaneity judgments: a model-based analysis

Abstract

Perception of simultaneity and temporal order is studied with simultaneity judgment (SJ) and temporal-order judgment (TOJ) tasks. In the former, observers report whether presentation of two stimuli was subjectively simultaneous; in the latter, they report which stimulus was subjectively presented first. SJ and TOJ tasks typically give discrepant results, which has prompted the view that performance is mediated by different processes in each task. We looked at these discrepancies from a model that yields psychometric functions whose parameters characterize the timing, decisional, and response processes involved in SJ and TOJ tasks. We analyzed 12 data sets from published studies in which both tasks had been used in within-subjects designs, all of which had reported differences in performance across tasks. Fitting the model jointly to data from both tasks, we tested the hypothesis that common timing processes sustain simultaneity and temporalorder judgments, with differences in performance arising from task-dependent decisional and response processes. The results supported this hypothesis, also showing that model psychometric functions account for aspects of SJ and TOJ data that classical analyses overlook. Implications for research on perception of simultaneity and temporal order are discussed.Keywords Simultaneity . Temporal order . Timing processes . Decisional processesThe timing processes sustaining perception of simultaneity and temporal order are respectively inferred from observers' performance in simultaneity judgment (SJ) and temporalorder judgment (TOJ) tasks. In both cases, each trial presents a pair of stimuli whose onsets (or offsets) occur at arbitrary times, resulting in a temporal delay regarded as positive when the stimulus designated "test" lags the stimulus designated "reference" and negative when the test stimulus leads the reference stimulus. In SJ tasks, observers report whether presentation (or extinction) of the two stimuli was subjectively simultaneous. Because observers directly report perception of simultaneity, the temporal delay at which simultaneous responses are maximally prevalent is interpreted as the point of subjective simultaneity (PSS). In contrast, in TOJ tasks observers report which stimulus was subjectively presented (or extinguished) first (or second), with no option to report subjective simultaneity. The temporal delay at which observers give equal numbers of "test first" and "reference first" (alternatively, "test second" and "reference second") responses is taken as the PSS, but this is only an indirect measure because the TOJ task avoids collecting evidence of perceived simultaneity. Strictly speaking, such analysis of TOJ data only identifies the temporal delay at which "test first" and "reference first" responses are equally prevalent, which is synonymous with the PSS only under the strong additional assumption that observers give "test first" and "reference first" responses equally often when they perceive simultaneity. Unfortunately, the validity of such a...

A single mechanism account of duration and rate processing via the pacemaker–accumulator and beat frequency models

“…Moreover, any model will need to account for how information from different modalities is timed. Recent work directly comparing tasks, such as temporal order and simultaneity judgements, has shown that different patterns of data arise depending on what participants are asked to do [51], [52]. Multisensory studies of both rate and duration can, in tandem with a broad range of other tasks, help probe the plausibility of different models of temporal perception.…”

Perceived Temporal Order and Simultaneity: Beyond Psychometric Functions

“…This type of data have been reported in a number of independent studies (e.g., Capa et al, 2014;Fujisaki & Nishida, 2009;Li & Cai, 2014;Linares & Holcombe, 2014;Matthews & Welch, 2015;Sanders et al, 2011;Schneider & Bavelier, 2003;van Eijk et al, 2008). An analysis of the 455 data sets from those studies supported the expectation of common timing parameters across tasks: The model including common timing parameters for all tasks was rejected in 24 (5.27%) of the occasions at the 5% significance level (see García-Pérez & Alcalá-Quintana, 2012b, 2015a, 2015b.…”

“…1 is simple and easily tractable mathematically, and it has often been used to model arrival latencies and peripheral processing times (e.g., Colonius & Diederich, 2011;Heath, 1984). In addition, this distribution has proven empirically adequate to account for observed performance in timing tasks (see García-Pérez & Alcalá-Quintana, 2012a, 2012b, 2015a, 2015b, 2015c. Thus, and without loss of generality, these are the distributions that will be used here.…”

“…These errors may be caused by carelessness, by an unnatural arrangement of the response interface, or by insufficient practice to use it properly. The probability of a response error is generally small, but errors seem to affect some responses more often than others (for empirical examples, see García-Pérez & Alcalá-Quintana, 2012a, 2012b, 2015a, 2015b, 2015c. The response component thus comprises the mapping of judgments onto one of the responses allowed by the task, with a potential for misreporting such judgments due to errors.…”

Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation

“…On one hand, plausible models are expected to give a good fit to observations with a relatively small $-qopnamelog(\hat{L})$. One can perform a likelihood-ratio-based test to evaluate goodness of fit to measurements, see e.g., García-Pérez and Alcalá-Quintana (2015a,b). The idea is to compare the purposed HM model and the saturated model (which contains parameters just being detection probabilities based on binomial fit at each amplitude) by the ratio of likelihood denoted by G 2 .…”