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SUMMARY:Attention filters for features - Professor George Sperling\, Unive
 rsity of California at Irvine
DTSTART:20160718T120000Z
DTEND:20160718T130000Z
UID:TALK66748@talks.cam.ac.uk
CONTACT:John Mollon
DESCRIPTION:An attention filter is a brain process\, initiated by a partic
 ipant in the context of a task requiring feature based selective attention
 \, that operates broadly across space to modulate the relative effectivene
 ss with which different features in the retinal input influence performanc
 e. The method for quantitatively measuring attention filters uses a ``stat
 istical summary representation" (SSR) task in which the participant strive
 s to mouse-click the centroid of a briefly flashed cloud composed of items
  of different types (e.g.\, dots of different luminances or sizes)\, weigh
 ting some types of items more strongly than others. In different attention
  conditions\, the target weights for different item-types in the centroid 
 task are varied. The actual weights exerted on the participant's responses
  by different item-types in any given attention condition are derived by s
 imple linear regression. Because\, on each trial\, the centroid paradigm o
 btains information about the relative effectiveness of all the features in
  the display\, both target and distractor features\, and because the parti
 cipant's response is a continuous variable in each of two dimensions (vers
 us a\nsimple binary choice as in most previous paradigms)\, it is an order
  of magnitude quicker and more efficient than previous measurements of hum
 an selective attention. To be described: (1) Three useful statistics to de
 scribe attention filters: efficiency\, fidelity\, and data driveness\, (2)
  some important procedural improvements: singleton trials\, constant dispe
 rsion\, and (3) illustrative examples as time permits: Attention filters f
 or light versus dark dots\, the speed with which attention filters are for
 med\, filters with equal item weights for targets of all contrasts versus 
 proportional weights and other transformations\, 32 attention\nfilters for
  single colors\, confirmations of the differences between filters for hue 
 versus filters for saturation and lightness\, a simple dimension for which
  humans cannot form a SSR attention filters\, and more (or fewer) examples
  as time permits.\n\nReference: Sun\, R.\, Chubb\, C.\, Wright\, C. E.\, S
 perling\, G. (2016). The centroid paradigm: Quantifying feature-based atte
 ntion in terms of attention filters. Attention\, Perception\, and Psychoph
 ysics\, 78(2) 474-515. DOI 10.3758/s13414-015-0978-2
LOCATION:Kenneth Craik Room\, Craik-Marshall Building\, Downing Site
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