Conditions for motion flow in dynamic visual noise

doi:10.1016/0042-6989(80)90033-4

Vision Research

Volume 20, Issue 5, 1980, Pages 431-435

https://doi.org/10.1016/0042-6989(80)90033-4 Get rights and content

Abstract

Dynamic visual noise was constrained to produce perceptually continuous unidirectional flow by plotting dots in pairs the members of which were consistently separated in time and in space. Flow was observed only when the spatial separation was less than 0.2–0.3 degrees of visual angle: the upper temporal limit varied with the state of retinal adaptation between 60 msec (under dim light) and 100 msec (under normal artificial light). In contrast with traditional phi motion, flow was observed with delays as short as 2–4 msec.

Reference (15)

Biederman-ThorsonM. et al.
Apparent movement due to closely spaced sequentially flashed dots in the human peripheral field of vision
Vision Res.
(1971)
BraddickO.
The masking of apparent motion in random-dot patterns
Vision Res.
(1973)
BraddickO.
A short range process in apparent motion
Vision Res.
(1974)
PetersikJ.T. et al.
Factors controlling the competing sensations produced by a bistable stroboscopic display
Vision Res.
(1979)
WestheimerG. et al.
Perception of temporal order in adjacent visual stimuli
Vision Res.
(1977)
ZeemanW.P.C. et al.
Some aspects of apparent motion
Acta psychol.
(1953)
AubertH.
Die Bewegungsempfindung
Arch. ges. Physiol.
(1886)

There are more references available in the full text version of this article.

Cited by (101)

Speeded response tasks with unpredictable deadlines
2023, Journal of Mathematical Psychology
In response time (RT) research, it is common to instruct participants to respond as fast and as accurately as possible, which is easily conceived as a contradiction. Participants may overcome this dilemma using a two-fold strategy, with (A) delaying their response until they feel confident that enough information has been sampled, and (B) scheduling the response right before the end of the response window to avoid omissions. The purpose of this strategy is to satisfy the contradictory requirements of the task instructions, but both (A) and (B) may yield a distorted picture of the processing times under investigation. We asked participants to discriminate random dot motion with fixed and variable deadlines for responding. With the exponentially distributed variable deadline, strategic responding is useless because it is impossible to schedule an optimal time point for the response. We present two analyses, a model-free approach that investigates the effect of an unpredictable deadline on standard RT measures, and the fit of an RT model testing for effects of the deadline on specific parameters. Compared to the fixed deadline, faster responses that were less variable across participants were observed under the variable deadline, suggesting that the new paradigm can reduce strategic responding. We demonstrate how to deal with omitted responses and conclude that variable deadlines are a promising tool to exert time pressure in RT experiments and potentially yield better estimates of the underlying processing times.
Decision-time statistics of nonlinear diffusion models: Characterizing long sequences of subsequent trials
2020, Journal of Mathematical Psychology
Citation Excerpt :
Here we present an efficient numerical procedure to calculate first-passage-time densities for general nonlinear DDMs that is based on the method of threshold integration by Richardson (2007, 2008) for white-noise-driven integrate-and-fire neurons. Experiments related to binary decision times often measure response-time distributions by performing sequential trials with randomly varying setups (see e.g. Green, Smith, & Gierke, 1983; Morgan & Ward, 1980; Ratcliff, 2002; Roitman & Shadlen, 2002). In such a procedure, slow transients that may occur due to the loss of the subject’s attention and also possible correlations between trials are neglected.
Cognitive models of decision making are an important tool in studies of cognitive psychology and have been successfully used to fit experimental data and to relate them to neurophysiological mechanisms in the brain. One of the most important models for binary decision making is the diffusion-decision model (DDM) in which a diffusion process that models the accumulation of perceived evidence yields the decisions upon reaching one of two thresholds. Due to its simplicity, the model is analytically tractable and has been used to bridge the gap between implementations of decision making in neurobiologically plausible neural networks and experiments. However, biologically realistic network models exhibit nonlinear dynamics that yield via mean-field-reduction techniques a nonlinear DDM for which analytical solutions and proper numerical tools in general are not known. Furthermore, although often agents have to make a number of subsequent decisions, the statistics of such sequences of decisions (containing information on whether the decisions are correct or incorrect and on their timing) are so far poorly understood. Here we introduce the decision trains, sequences of negative or positive spikes at the decision times with the sign corresponding to the correctness of the decision. The decision trains enable a proper characterization of experiments in which many trials are performed consecutively. For the principal reference case of independent decisions (renewal statistics), we derive relations between the second-order statistics of the decision trains (i.e. their power spectra) and the response-time densities. Most importantly, we extend an efficient numerical procedure for spiking neuron models, the threshold-integration method, to determine the temporal statistics of nonlinear DDMs. The threshold-integration method provides the temporal statistics, i.e. decision rates, decision-time densities and the decision-train power spectra. Moreover, the procedure is used for the calculation of the linear response to a sinusoidal modulation. We compare all results with direct simulations of the stochastic model.
Causal actions enhance perception of continuous body movements
2020, Cognition
Citation Excerpt :
For example, previous studies have demonstrated that it is only within certain ranges of displacements and temporal sampling measured as stimulus-onset-asynchrony (SOA) between frames that a two-frame stimulus evokes a percept of smooth movement. Apparent motion is lost when the spatial and temporal parameters exceed those limits (Baker & Braddick, 1985a, 1985b; Bours, Stuur, & Lankheet, 2007; Lappin & Bell, 1976; Morgan & Ward, 1980). Further, response profiles of neurons in early visual areas (such as V1 and MT) demonstrate similar spatial and temporal limits in giving rise to the perception of apparent motion (Baker & Cynader, 1986; Churchland, Priebe, & Lisberger, 2005; Mikami, Newsome, & Wurtz, 1986; Newsome, Mikami, & Wurtz, 1986).
Our experience of motion depends not only on spatiotemporal features of stimuli, but also on our recognition of seemingly higher-level properties, as when we see an actor's body movements as goal-directed. Here, we examined how the perception of social causation in human actions guides the perceptual interpolation of motion in the observation of body movements. Natural human-object interactions were recorded for videos in which a person prepared to catch a ball thrown by another person. We manipulated the number of image frames between key postures to yield a short clip with different frame rates, and asked participants to judge whether the catcher's action showed smooth movements or sudden changes. In the causal condition, the catcher faced toward the ball and the thrower to preserve an intention-based causal relation between the ball's movement and the catcher's action in which the former causes the catcher's intention to act. In the non-causal condition, the catcher performed the same movements to raise their hands to catch a ball, except that they faced away from the ball, creating the impression of either a psychic reaction or coincidental non-goal-directed behavior, which makes movements of the ball appear to be an implausible cause of the catcher's intention to act. Across four experiments, we found that humans were more likely to judge the catcher's body movements to be continuous in the causal condition than in the non-causal condition. The effect was maintained as long as the intention-based causal relation was present, even when only part of the chain of causal events was observed. These findings indicate that intention-based cause-effect relations in human actions guide perceptual interpolation of body movements.
Comparing fixed and collapsing boundary versions of the diffusion model
2016, Journal of Mathematical Psychology
Citation Excerpt :
The fifth and sixth experiments used a dot motion discrimination task with various difficulty levels and a speed/accuracy manipulation. This task has been used extensively in both the neurophysiological and behavioral literature (e.g. Cain, Barreiro, Shadlen, & Shea-Brown, 2013; Churchland et al., 2008; Ditterich, 2006a; Forstmann et al., 2010, 2008; Gold & Shadlen, 2007; Hanks, Kiani, & Shadlen, 2014; Mazurek, Roitman, Ditterich, & Shadlen, 2003; Morgan & Ward, 1980; Mulder, Boekel, Ratcliff, & Forstmann, 2014; Niwa & Ditterich, 2008; Palmer et al., 2005; Ratcliff & McKoon, 2008; Ratcliff & Starns, 2013; Roitman & Shadlen, 2002; Shadlen & Newsome, 1996; van Ravenzwaaij, Mulder, Tuerlinckx, & Wagenmakers, 2012). We present the fits of the two models to all of the experiments followed by the PBCM results and interpretation.
Optimality studies and studies of decision-making in monkeys have been used to support a model in which the decision boundaries used to evaluate evidence collapse over time. This article investigates whether a diffusion model with collapsing boundaries provides a better account of human data than a model with fixed boundaries. We compared the models using data from four new numerosity discrimination experiments and two previously published motion discrimination experiments. When model selection was based on BIC values, the fixed boundary model was preferred over the collapsing boundary model for all of the experiments. When model selection was carried out using a parametric bootstrap cross-fitting method (PBCM), which takes into account the flexibility of the alternative models and the ability of one model to account for data from another model, data from 5 of 6 experiments favored either fixed boundaries or boundaries with only negligible collapse. We found that the collapsing boundary model produces response times distributions with the same shape as those produced by the fixed boundary model and that its parameters were not well-identified and were difficult to recover from data. Furthermore, the estimated boundaries of the best-fitting collapsing boundary model were relatively flat and very similar to those of the fixed-boundary model. Overall, a diffusion model with decision boundaries that converge over time does not provide an improvement over the standard diffusion model for our tasks with human data.
Two tales of how expectation of reward modulates behavior
2014, Current Opinion in Neurobiology
Citation Excerpt :
Finally, we put forth some open questions for future studies, guided by a comparison of existing knowledge between the two lines of research. To illustrate some key properties of reward-modulated perceptual decision behavior, we focus on examples of adding explicit reward expectation manipulations to a well-known perceptual decision task, the visual motion direction discrimination task [1,2]. On a basic motion discrimination task, a subject sees a field of moving dots on a screen and needs to report the global motion of these dots.
Expectation of reward modulates many types of behaviors. Here we highlight two lines of research on reward-modulated perceptual decision making in primates and social context-modulated singing in songbirds, respectively. These two seemingly distinct behaviors are both known to involve cortico-basal ganglia-thalamic circuits. The underlying computations may be conceptualized using a simple, common framework. We summarize and compare our current knowledge of the two fields to motivate new experiments for each field, with the goal of finding general principles for how the brain implements reward-modulated behavior.
Animal models and measures of perceptual processing in schizophrenia
2013, Neuroscience and Biobehavioral Reviews
This paper summarizes the discussions regarding animal paradigms for assessing perception at the seventh meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS). A breakout group at the meeting addressed candidate tests in animals that might best parallel the human paradigms selected previously in the CNTRICS program to assess two constructs in the domain of perception: gain control and visual integration. The perception breakout group evaluated the degree to which each of the nominated tasks met pre-specified criteria: comparability of tasks across multiple species; construct validity; neuroanatomical homology between species; and dynamic range across parametric variation.

View all citing articles on Scopus

^†: Universitédu Québec a Trois Rivières.

View full text

Conditions for motion flow in dynamic visual noise

Abstract

Vision Res.

Vision Res.

Vision Res.

Vision Res.

Vision Res.

Acta psychol.

Die Bewegungsempfindung

Arch. ges. Physiol.