Temporal thresholds and reaction time to changes in velocity of visual motion

Mateeff, S; Dimitrov, Georgi; Hohnsbein, J.

doi:10.1016/0042-6989(94)00130-e

Cited by 26 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The human RT to the onset of our visual motion stimulus changed with speed, which is in agreement with the results of previous psychophysical studies [Ball and Sekuler, 1980;Dzhafarov et al, 1993;Hohnsbein and Mateeff, 1992;Mateeff et al, 1995Mateeff et al, , 1999Smeets and Brenner, 1994], that is, the marked similarity in the value of ␥ (about 0.5) of equation (1) (see Results), considering that different visual motion stimuli were used in these studies. Although in two other studies, higher values (approximately 1.0) of ␥ were reported [Burr et al, 1998;Troscianko and Fahle, 1988], the reason could be due to the use of lower speeds as discussed by the authors [Burr et al, 1998] and of a speed range (0.3-2°/sec) narrower than ours (0.4 -500°/sec).…”

Section: Relation Of Meg Response To Human Reaction Timesupporting

confidence: 89%

Visual detection of motion speed in humans: spatiotemporal analysis by fMRI and MEG

Kawakami

Kaneoke

Maruyama

et al. 2002

Human Brain Mapping

View full text Add to dashboard Cite

Humans take a long time to respond to the slow visual motion of an object. It is not known what neural mechanism causes this delay. We measured magnetoencephalographic neural responses to light spot motion onset within a wide speed range (0.4-500 degrees /sec) and compared these with human reaction times (RTs). The mean response latency was inversely related to the speed of motion up to 100 degrees /sec, whereas the amplitude increased with the speed. The response property at the speed of 500 degrees /sec was different from that at the other speeds. The speed-related latency change was observed when the motion duration was 10 msec or longer in the speed range between 5 and 500 degrees /sec, indicating that the response is directly related to the speed itself. The source of the response was estimated to be around the human MT+ and was validated by functional magnetic imaging study using the same stimuli. The results indicate that the speed of motion is encoded in the neural activity of MT+ and that it can be detected within 10 msec of motion observation. RT to the same motion onset was also inversely related to the speed of motion but the delay could not be explained by the magnetic response latency change. Instead, the reciprocal of RT was linearly related to the reciprocal of the magnetic response latency, suggesting that the visual process interacts with other neural processes for decision and motor preparation.

show abstract

Section: Relation Of Meg Response To Human Reaction Timesupporting

confidence: 89%

Visual detection of motion speed in humans: spatiotemporal analysis by fMRI and MEG

Kawakami

Kaneoke

Maruyama

et al. 2002

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…The duration thresholds probably reflect both neural and stimulus limitations (Borghuis, 2003). Duration thresholds have been used in previous work on surround suppression (e.g., Betts, Taylor, Sekuler, & Bennett, 2005;Tadin & Lappin, 2005b;Tadin et al, 2003), on other aspects of motion perception (Mateeff, Dimitrov, & Hohnsbein, 1995;Tayama, 2000), color perception (Pokorny, Bowen, Williams, & Smith, 1979), and symmetry perception (Tyler, 2001). In the present study, the same method also measured spatial displacement thresholds.…”

Section: General Commentsmentioning

confidence: 89%

Spatial and temporal limits of motion perception across variations in speed, eccentricity, and low vision

Lappin¹,

Tadin²,

Nyquist³

et al. 2009

Journal of Vision

View full text Add to dashboard Cite

We evaluated spatial displacement and temporal duration thresholds for discriminating the motion direction of gratings for a broad range of speeds (0.06 degrees/s to 30 degrees/s) in fovea and at +/-30 degrees eccentricity. In general, increased speed yielded lower duration thresholds but higher displacement thresholds. In most conditions, these effects of speed were comparable in fovea and periphery, yielding relatively similar thresholds not correlated with decreased peripheral acuity. The noteworthy exceptions were interactive effects at slow speeds: (1) Displacement thresholds for peripheral motion were affected by acuity limits for speeds below 0.5 degrees/s. (2) Low-vision observers with congenital nystagmus had elevated thresholds for peripheral motion and slow foveal motion but resembled typically sighted observers for foveal motions at speeds above 1 degree/s. (3) Suppressive center-surround interactions were absent below 0.5 degrees/s and their strength increased with speed. Overall, these results indicate qualitatively different sensitivities to slow and fast motions. Thresholds for very slow motion are limited by spatial resolution, while thresholds for fast motion are probably limited by temporal resolution.

show abstract

“…Effective use of colour, motion, etc., can effectively capture human attention, which is especially needed in the case of monitoring tasks. Related research areas where human reaction time in response to dynamic data [MDH95] has been studied can be utilized for addressing the problem of inattentional blindness.…”

Section: Research Directions For Addressing Gapsmentioning

confidence: 99%

Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization

Dasgupta

Arendt

Franklin

et al. 2017

Computer Graphics Forum

View full text Add to dashboard Cite

Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems. In this paper, our goal is to fill this gap by studying how the state of the art in streaming data visualization handles the challenges and reflect on the gaps and opportunities. To this end, we have three contributions in this paper: (i) problem characterization for identifying domain‐specific goals and challenges for handling streaming data, (ii) a survey and analysis of the state of the art in streaming data visualization research with a focus on how visualization design meets challenges specific to change perception and (iii) reflections on the design trade‐offs, and an outline of potential research directions for addressing the gaps in the state of the art.

show abstract

Temporal thresholds and reaction time to changes in velocity of visual motion

Cited by 26 publications

References 25 publications

Visual detection of motion speed in humans: spatiotemporal analysis by fMRI and MEG

Visual detection of motion speed in humans: spatiotemporal analysis by fMRI and MEG

Spatial and temporal limits of motion perception across variations in speed, eccentricity, and low vision

Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization

Contact Info

Product

Resources

About