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Alex Holcombe
• Jiahao "Aaron" Wu


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

Phenomenon interval before transient interval after transient Spatial Bias Temporal Bias- increase w/speed, or temporal freq tuned Spatial Variab Temporal Variab Foveo attn effect vector sum /IOC, hi-level motion land - marks monotonic inc w/ motion dur awareness necess feature space affects eyemove retinal motn sufficnt
Flash-lag yes some substantial in some participants and negative in some, but always linear, implicating latency?[1] 0 80ms petal[2],[3] ? yes[4] less spatial σ? yes? yes[5]
Cai[6] .5deg 0[7, 8] ? 0 fugal[7]
Hazelhoff,[9] yes[10] 0 large ?? discrepant Ss[7] ?? ?? ??
Motion on nearby flash (flash-drag)[11] ~80ms before matters, dunno greater[12] 80-200ms later matters [12],[11],[13] signif ~0[14],[11] ?? betting0 ?? large not early[15]
Flash attracted toward position of motion[16] yes[17][18] 0[17],not much[18]
Twinkle goes
Offset localization lags (when transient not reduced) small flash-terminated saturated at slow[3], offset of blurred peaked at slow in [19], but high-speed LINEAR (or log?) to 70degpersec,implying 24ms[20] lag
Offset localization (when transient reduced Nijhawan, twinkle-goes) small LINEAR in [21] implying 13 ms with 100ms fading time. LINEAR in NakayamaHolcombe(2021) implying 50 ms, but saturation over 1.2rps
Shrinkage of motion paths (related to offset localization) linear but they test only 3 speeds, max 6.5 deg/sec or .74 rev/sec [22]
Flash-grab[23](partly a way to measure the shrinkage effect) 200ms[23] 200ms[23] Linear (really, decelerating?) up to .75rps[23] (could continue faster if faster monitor?), suggesting 50ms. To be explained by temporal averaging, 100ms large, based on cloud test[23] mostly component, partly global motion[24]
Frohlich N/A .5deg fugal:1.5deg,petal:0[25] 0[7],<27ms[26] fugal:10ms,petal:15ms[25],0-5ms[27],2-8ms[28],79ms[14]

39ms[29],100ms[30],18ms but nonlinear[20]

? 0 fugal[25, 31],0[7] large no[32]
onset-repuls <=15ms[33],[34]
repr momentum illusion only happens with eye move?[35] 33ms[34]
deValois large[36][37] Tuned to temporal freq [38][39] miniscule miniscule fugal[2] yes[37],[40] NO No[41]
kinetic edge[42] read[43] [43] [43] petal[43]
bg motion->IC[44] not much? only 2 speeds tested[44]
Motion capture[45]
Motion adapt saturat at 5degpersec/Hz[46] ~0[21] ~0[21] fugal Yes[21] No[47]
binding 0[48]
induced motion 0? Yes[49]
10Hz jitter[50] yes
Floating square[51] no
Eyeblink extrapolation yes no [52]
timed buttonpress


motion-defined motion contours also are perceived shifted[53]


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  54. [Moradi]
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All Medline abstracts: PubMed | HubMed

Biphasic Neuron Extrap
A-V flash lag
foveo fugal/petal biases

Temporal variability might arise from:

  1. Position shifting that increases with velocity, with constant noise added to velocity
  2. Uncertainty in *when* the judgment was supposed to be made
  3. For any effects caused by afferent latency (Hazelhoff?), variability in latency

deValois stands out as only temporal bias with spatial variability. Then why doesn't Cai and Frohlich have temporal bias? Only easy explanation would be the possibly-greater blur of the deValois stimuli, so we have to check that. Increasing eccentricity would also increase the spatial uncertainty[55] perhaps allowing temporal to manifest

  • The idea of separate position representations (e.g. for first- and second-order motion as suggested by Pavan & Mather 2008) is really fascinating
  • Nicolls,Mattingley,Berberovic,Smith,&Bradshaw(2004) review horiz/vert asymmetries we should check out for ideas
  • To explain the Cai & Schlag smooth pursuit flash mislocalisation effect, Rotman, Brenner , Smeets (2005) suggest that efference copy motion signal is combined with (absent) retinal motion of flash to yield extrapolation. They present their whack-a-mole targets for variable duration and find the longer the exposure duration, the less mislocalization in the direction of the eye movement. They theorize that the reason is that the longer targets have more retinal motion opposite the pursuit, so this cancels the efference copy to eliminate the extrapolation. An alternative account is that longer exposure improves the integration with spatiotopically stationary landmarks, reducing the reliance on the retinotopic code. Since this does not help for targets moving with the eyes, would have to posit that stabilization thanks to landmarks doesn't happen with moving targets. But this seems unlikely. I would like to see 1) Mislocalization when target moves in orthogonal direction 2) Whether variability (presumably spatial in both cases, since we find spatial for Cai&Schlag), which might implicate growth of a spatial code.