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Modelling the formation of attentional episodes: It’s about time

Modelling the formation of attentional episodes: It’s about time. Brad Wyble Molly Potter and Howard Bowman Mark Nieuwenstein Jenn Olejarczyk. 25/08/08 Utrecht. Bridge. Dogs. ?. 3. ..DTTD. T1. B. A. 5. 6. 9. 4. T2|T1. T2. 0. 300. 600. 100 msec. Time(ms).

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Modelling the formation of attentional episodes: It’s about time

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  1. Modelling the formation of attentional episodes: It’s about time Brad Wyble Molly Potter and Howard Bowman Mark Nieuwenstein Jenn Olejarczyk 25/08/08 Utrecht

  2. Bridge

  3. Dogs ? 3

  4. ..DTTD.. T1 B A 5 6 9 4 T2|T1 T2 0 300 600 100 msec Time(ms) Attentional Blink

  5. …D T1 T2 D D… Sparing 90 ms Spreading of Sparing 100 % Accuracy 70 40 …D T1 D T2 D… …D T1 T2 T3 D… Olivers, Van Der Stighchel & Hulleman (2007) Kawahara, Kumada, & DiLollo (2007)

  6. T T D D D D D D T T T T One Window Two Windows Sparing and Blinking: A temporal attention strategy

  7. * Competitive Regulation Of Temporal Attention Working Memory Encoding Attention Targets

  8. T1 Encoding Sparing Blink Competitive Attention In RSVP: Attention D D T1 D D D

  9. Spreading the Sparing D D T1 D D D D D D T1 T2 D D D D D T1 T2 T3 D D

  10. T1 A Target Gap Produces a blink D D T1 D T2 D Sparing Blink

  11. * 1 Task Demand Targets 2 3 4 … Attention Blaster Working Memory Encoding Types Transient Attention Tokens Encoding Input Binding Pool … Input T1 T2 Tn D Simultaneous-TypeSerial -Token Episodic

  12. T2 T1 Type Working Memory Attention T1 500 ms Two targets Lag-5 No Blink T1 T2 Lag-3 Blink! T1 T2

  13. Simulating the blink T1 Accuracy T2|T1 Lag Lag Data from: Chun & Potter (1995)

  14. Spreading of Sparing Accuracy Same Parameters Data from Olivers, Van Der Stigchel, & Hulleman (2007)

  15. 107 ms SOA 53 ms SOA Prediction: ~200 ms temporal Interval between targets initiate an Attentional Blink One RSVP Experiment 4 conditions all mixed together ...D T D T D T D T D... ...D T T T T D D D D... ...DDTDTDTDTDD... ...DDTTTTDDDDD...

  16. Letters 3 D 3 4 2 5 9 5 6 N B K 4

  17. Letters 3 D 3 4 2 5 9 5 6 N B K 4

  18. Std Err 400ms 700ms 52% 62% Slow Trials: Predictions and Data Accuracy two-tailed t, p < .001

  19. Std Err Fast Trials

  20. Std Err DTDTDTDTD (100 ms SOA) 400ms 400ms (50ms SOA) D T T T T D Time course of attention unaltered by distractors

  21. Why care about episodes? Blinking: Episodic Distinctiveness Sparing: More Items Measure temporal order as an index of episodic information

  22. 86% 91% 79% p < .015 std err ~4% 100% Temporal Order for Targets 200ms apart TTTTDDD Correctly Ordered Spared 200ms TDTDTDT Blinked

  23. Encoding Temporal order Sparing/Blinking Sparing T1 T2 T3 Blinking T1 D T2

  24. eSTST Model The Attentional Blink provides Episodic Distinctiveness: Sparing at a Cost Wyble, Bowman,Nieuwenstein (In Press) JEP: HPP http://www.bradwyble.com/research/models/eSTST/ CONCLUSION • Attention structures perception into episodes • This strategy manifests as sparing and blinking • Temporal intervals between target onsets, not distractors, trigger the end of an episode

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