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Testing a simplified method for measuring velocity integration in saccades using a manipulation of target contrast.

Etchells PJ, Benton CP, Ludwig CJ, Gilchrist ID - Front Psychol (2011)

Bottom Line: Observers generated saccades to one of two moving targets which were presented at high (80%) or low (7.5%) contrast.The extent to which the saccade endpoint can be accounted for as a weighted combination of the pre- or post-step velocities allows for identification of the temporal velocity integration window.Our results show that the temporal integration window takes longer to peak in the low when compared to high contrast condition.

View Article: PubMed Central - PubMed

Affiliation: School of Experimental Psychology, University of Bristol Bristol, UK.

ABSTRACT
A growing number of studies in vision research employ analyses of how perturbations in visual stimuli influence behavior on single trials. Recently, we have developed a method along such lines to assess the time course over which object velocity information is extracted on a trial-by-trial basis in order to produce an accurate intercepting saccade to a moving target. Here, we present a simplified version of this methodology, and use it to investigate how changes in stimulus contrast affect the temporal velocity integration window used when generating saccades to moving targets. Observers generated saccades to one of two moving targets which were presented at high (80%) or low (7.5%) contrast. In 50% of trials, target velocity stepped up or down after a variable interval after the saccadic go signal. The extent to which the saccade endpoint can be accounted for as a weighted combination of the pre- or post-step velocities allows for identification of the temporal velocity integration window. Our results show that the temporal integration window takes longer to peak in the low when compared to high contrast condition. By enabling the assessment of how information such as changes in velocity can be used in the programming of a saccadic eye movement on single trials, this study describes and tests a novel methodology with which to look at the internal processing mechanisms that transform sensory visual inputs into oculomotor outputs.

No MeSH data available.


Related in: MedlinePlus

ρn (the relative weight attributed to the post-step velocity) as a function of D (time between velocity change and saccade onset) for a single observer. Dark blue solid line in the top panel denotes the fit of a cumulative Gamma function to the high contrast condition data. Light blue dashed line in the lower panel denotes a Gamma function fit to the low-contrast data. Error bars denote the SD. The dash–dot line in both plots denotes the time at which σn = 0.5, i.e., when both velocities are being weighted equally. Note that while the data are presented here in approximately 15 equal bins, the actual Gamma fit was conducted on the full data set.
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Figure 4: ρn (the relative weight attributed to the post-step velocity) as a function of D (time between velocity change and saccade onset) for a single observer. Dark blue solid line in the top panel denotes the fit of a cumulative Gamma function to the high contrast condition data. Light blue dashed line in the lower panel denotes a Gamma function fit to the low-contrast data. Error bars denote the SD. The dash–dot line in both plots denotes the time at which σn = 0.5, i.e., when both velocities are being weighted equally. Note that while the data are presented here in approximately 15 equal bins, the actual Gamma fit was conducted on the full data set.

Mentions: Values of ρn range between 0 and 1, with ρn = 0 equivalent to the saccadic system solely basing its response on the pre-step speed, and ρn = 1 equivalent to the system solely utilizing the post-step speed. Figure 4 illustrates (in 15 roughly equal bins) how these weights vary as a function of D. As expected, just before saccade onset, the system has not had time to include the new velocity in its movement program, corresponding to a post-step velocity weight of 0. As time to saccade onset increases, more emphasis is placed on the post-step velocity, eventually reaching values close to 1. It is clear that the transition is gradual, which may be attributed to the varying portions of the pre- and post-step velocities falling under the temporal filter.


Testing a simplified method for measuring velocity integration in saccades using a manipulation of target contrast.

Etchells PJ, Benton CP, Ludwig CJ, Gilchrist ID - Front Psychol (2011)

ρn (the relative weight attributed to the post-step velocity) as a function of D (time between velocity change and saccade onset) for a single observer. Dark blue solid line in the top panel denotes the fit of a cumulative Gamma function to the high contrast condition data. Light blue dashed line in the lower panel denotes a Gamma function fit to the low-contrast data. Error bars denote the SD. The dash–dot line in both plots denotes the time at which σn = 0.5, i.e., when both velocities are being weighted equally. Note that while the data are presented here in approximately 15 equal bins, the actual Gamma fit was conducted on the full data set.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3108583&req=5

Figure 4: ρn (the relative weight attributed to the post-step velocity) as a function of D (time between velocity change and saccade onset) for a single observer. Dark blue solid line in the top panel denotes the fit of a cumulative Gamma function to the high contrast condition data. Light blue dashed line in the lower panel denotes a Gamma function fit to the low-contrast data. Error bars denote the SD. The dash–dot line in both plots denotes the time at which σn = 0.5, i.e., when both velocities are being weighted equally. Note that while the data are presented here in approximately 15 equal bins, the actual Gamma fit was conducted on the full data set.
Mentions: Values of ρn range between 0 and 1, with ρn = 0 equivalent to the saccadic system solely basing its response on the pre-step speed, and ρn = 1 equivalent to the system solely utilizing the post-step speed. Figure 4 illustrates (in 15 roughly equal bins) how these weights vary as a function of D. As expected, just before saccade onset, the system has not had time to include the new velocity in its movement program, corresponding to a post-step velocity weight of 0. As time to saccade onset increases, more emphasis is placed on the post-step velocity, eventually reaching values close to 1. It is clear that the transition is gradual, which may be attributed to the varying portions of the pre- and post-step velocities falling under the temporal filter.

Bottom Line: Observers generated saccades to one of two moving targets which were presented at high (80%) or low (7.5%) contrast.The extent to which the saccade endpoint can be accounted for as a weighted combination of the pre- or post-step velocities allows for identification of the temporal velocity integration window.Our results show that the temporal integration window takes longer to peak in the low when compared to high contrast condition.

View Article: PubMed Central - PubMed

Affiliation: School of Experimental Psychology, University of Bristol Bristol, UK.

ABSTRACT
A growing number of studies in vision research employ analyses of how perturbations in visual stimuli influence behavior on single trials. Recently, we have developed a method along such lines to assess the time course over which object velocity information is extracted on a trial-by-trial basis in order to produce an accurate intercepting saccade to a moving target. Here, we present a simplified version of this methodology, and use it to investigate how changes in stimulus contrast affect the temporal velocity integration window used when generating saccades to moving targets. Observers generated saccades to one of two moving targets which were presented at high (80%) or low (7.5%) contrast. In 50% of trials, target velocity stepped up or down after a variable interval after the saccadic go signal. The extent to which the saccade endpoint can be accounted for as a weighted combination of the pre- or post-step velocities allows for identification of the temporal velocity integration window. Our results show that the temporal integration window takes longer to peak in the low when compared to high contrast condition. By enabling the assessment of how information such as changes in velocity can be used in the programming of a saccadic eye movement on single trials, this study describes and tests a novel methodology with which to look at the internal processing mechanisms that transform sensory visual inputs into oculomotor outputs.

No MeSH data available.


Related in: MedlinePlus