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Alex Holcombe
Sarah McIntyre
Fahed Jbarah
• Shih-Yu Lo
• Patrick Goodbourn
Lizzy Nguyen

action precision
Tactile Motion
Tactile Receptors
Binding, grouping


Skills Checklist
Python Programming
Psychopy/VisionEgg Installation Notes
R analysis,plot,stats
Buttonbox with photocell
Programming Cheat Sheets

  • [1]22 ms- participants have to hit a virtual disk into a goal by moving a stylus along a trackpad. Also quantify other sources of error. Argue that visual resolution limits performance. Seem to argue for use of position information causing this, saying 'Moreover the prediction of the disk’s position at the expected moment of the hit must have been updated throughout the movement, because considering the resolution of visual velocity judgments, and that the influ- ence of misjudging the velocity on the prediction is proportional to the duration for which motion is extrapo- lated, misjudging the disk’s velocity would otherwise have overshadowed all other effects (unless interception uses velocity information that was not accessible for the velocity discrimination judgments of de Bruyn and Orban 1988). Thus in many sports situations visual resolution is likely to limit performance.'. Are they saying there was a long integration time for position estimate?
  • cricket:[2] They explored the shot called "back leg glance" in which the trajectory of the ball is perpendicular to the trajectory of the bat. In that way, they can calculate precision just by considering the width of the bat. The temporal resolution of best cricket players is 2 ms. For normal subjects is about 5-10 ms. They think that the precision is not qualitatively different. How can this temporal resolution be achieved? Review paper, see [3] for more detail.
  • Hopkins and Kristofferson[4] required subjects to generate a time interval by trying to press a button at a precise time after a light went on. After 70000 trials the standard deviation was only 7 ms!
  • ping-pong [5] "managed to get 75% of the balls, on average, into the target area. Because the target had a diameter of 55 cm and was located some 2.5 m away from the point of contact (near the leading edge of the table), this implies that at least 75% of the balls have been contacted with the direction of travel of the bat not varying more than 6° around the line through the center of the target. Assuming a normal distribution, the standard deviation of the direction of travel of the bat at the moment of contact must have been therefore 5.2°. As seen later, angular bat velocities at contact of 800°/s are quite common, which means that the players have to time their moment of contact with a precision of, at maximum, 5.2/0.800 = 6.5 ms"
  • ball falling from ceiling [3] ball dropped down vertical chute. Subject had to swing bat horizontally through line of flight of ball. Plotting successful hit rate against bat width. Showed that ordinary people without any particular practice executed the action within +/- 10msec 90% of the time
  • [6] Showed that expert batsmen need 190-240ms to react to an unforseen change in ball direction (this may include time for a noticeable change to become apparent, and time to overcome inertia and reverse the bat swing already in motion). In Expt 1, expert batsmen had to bat balls that bounced on an uneven patch of ground. Graphs did not include spatial scale or error bars, nor were stats given. In Expt 2, experts were compared with novice cricketers. Both were shown videos of different bowls and were asked to judge if they were short, of good length, or long. The videos were blanked at 0, 80, 160 or 240ms after the ball left the bowler’s hand. Experts and amateurs had very similar performance. They performed at chance for 0ms and showed a monotonic increase as they were shown more footage. They were performing better than chance at 80ms, and perfectly at 240ms. Again no stats, this just from eyeballing the data. McLeod concludes that expert performance in cricket is not due to differences in visual processing but in visual response strategies.
  • infants can reach for moving objects with 50 ms precision! [7]
  • less-ecological using mouse to move cursor to intercept object moving in circular trajectory [8]Target (small disc) following a circular path with constant velocity. Design: 2 (real vs apparent motion) x 5 (velocity) within Ss. Ss had to move a mouse cursor to intercept the disc at the 12 o'clock position. For all conditions, Ss intercepted late. Error increased for faster speeds, with a sharp increase for fastest speed (540 deg/s). Precision (SD in deg) was overall worse for apparent motion than for real motion. Precision worsened as a linear function of speed, which means it is more or less constant in time. From their linear regression equations, for real motion it was around 38-47ms, for apparent motion it was 73-91ms. I don't think Ss had to fixate. They got online feedback about the mouse cursor – it would be a pretty meaningless task if they didn't since you can't assume any pre-existing knowledge about how much kinaesthetic motion corresponds to cursor motion on the screen.
  • [9]
  • [10]
  • Flash-lag in depth [11]: Using different types of motion in depth they found mean precisions about 55-71 ms. The individual differences, however, are very big.
  • Visuomotor control shown to change conscious perception[12]. Participants saw a moving dot that disappeared unexpectedly. They judged its vanishing point to be further along its trajectory than it actually was. After a session of controlling the dot by “braking” it with keyboard presses, participants would then observe passively and show more of an error than when they had not previously controlled it.
  • [13]

Rapid motor response to visual stimuli

  • [14] 152 ms RT reflex vs 324 ms RT for voluntary movements
  • [15]
  • [16]point to a briefly presented target (110 ms). the impact of visual information on endpoint precision by using a shutter to close off view of the hand 50, 110 and 250 ms into the reach. precision was degraded if the view of the hand was restricted at any time during the reach, despite the fact that the target disappeared long before the reach was completed. We therefore conclude that vision keeps the hand on the planned trajectory. We then investigated the effects of a perturbation of target position during the reach. For these experiments, the target remained visible until the reach was completed. The target position was shifted at 110, 180 or 250 ms into the reach. Early shifts in target position were easily compensated for, but late shifts led to a shift in the mean position of the endpoints; observers pointed to the center of the two locations, as a kind of best bet on the position of the target. Visual information is used to guide the hand throughout a reach and has a significant impact on endpoint precision.
  • review by Gomi[17]


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  1. Error fetching PMID 19283369: [BrennerSmeets09]
  2. McLeod P and Jenkins S. Timing accuracy and decision time in high-speed ball games. International Journal of Sport Psychology 1991; 22 279-295.


  3. McLeod, P., McLaughlin, C. and Nimmo-Smith, I., 1985. Information encapsulation and automaticity evidence from the visual control of finely timed actions. In: Posner, M.I. and Marin, O.S., Editors, 1985. Attention and performance XI, Erlbaum, Hillsdale, NJ.


  4. Hopkins and Kristofferson. Ultrastable stimulus-response latencies: acquisition and stimulus control. Perception and psychophysics, 27, 241-250.


  5. Bootsma RJ, van Wieringen PCW. Timing an attacking forehand drive in table tennis. Journal of Experimental Psychology: Human Perception and Performance. 1990;16:21


  6. McLeod P. Visual reaction time and high-speed ball games" Perception 1987; 16(1) 49 – 59


  7. von Hofsten, C. (1987). Catching. In H. Heuer & A. F. Sanders (Eds.), Perspectives on perception and action (pp. 33-46). Hillsdale,NJ Erlbaum


  8. Port NL, Pellizzer G, Georgopoulos AP. Intercepting real and path-guided apparent motion targets. Exp Brain Res. 1996;110:298-307.


  9. Error fetching PMID 9486434: [Ripoll-Latiri-1997]
  10. Error fetching PMID 16120661: [Senot-2005]
  11. Harris, LR, Duke, AP, Kopinska, A. Flash-lag in depth. Vision Research, 46, 2735-2742.


  12. Jordan and Hunsinger (2008). Learned Patterns of Action-Effect Anticipation Contribute to the Spatial Displacement of Continuously Moving Stimuli. Journal of Experimental Psychology: Human Perception and Performance, 34(1), 113-124.


  13. Error fetching PMID 11991570: [BrennerDS02]
  14. Error fetching PMID 19109499: [FranklinWolpert08]
  15. Error fetching PMID 16707782: [Gomi06]
  16. Error fetching PMID 17109109: [MaWyatt07]
  17. Error fetching PMID 19095435: [Gomi08]
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