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UNCLASSIFIED UNCLASSIFIED UNCLASSIFIED / APPROVED FOR PUBLIC RELEASE Evoked Response Potential Latency Modeling and Production Time Prediction Da Daniel iel Ca Casse ssenti, ti, U.S .S. . Ar Army my Rese search Laborato tory ACT


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The Nation’s Premier Laboratory for Land Forces

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The Nation’s Premier Laboratory for Land Forces

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Da Daniel iel Ca Casse ssenti, ti, U.S .S. . Ar Army my Rese search Laborato tory ACT CT-R Post

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Grad adua uate te Summer Summer Sc Scho hool

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Evoked Response Potential Latency Modeling and Production Time Prediction

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Neuroscience in Psychology

TIME SCALE OF HUMAN ACTION (Newell, 1990) Scale (sec) Time Units System World (theory) 107 Months Social Band 106 Weeks 105 Days 104 Hours Task Rational Band 103 10 min Task 102 Minutes Task 101 10 sec Unit task Cognitive Band 100 1 sec Operations 10-1 100 ms Deliberate act 10-2 10 ms Neural circuit Biological Band 10-3 1 ms Neuron 10-4 100 ms Organelle

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ACT-R Neuro Integration

  • The neuro-ACT-R integration settles into the cross-
  • ver between the biological and cognitive bands at

the ACT-R sub-symbolic layer

  • Spatial: BOLD models
  • Temporal: EEG models

– Phase and power analysis (e.g., van Rugt, 2012) – ERPs (e.g., Cassenti et al., 2011)

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Event Related Potentials

  • Amplitude
  • Latency
  • N1, P2, P3…
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ERP-Production Links

  • N1 – Perceptual Recognition
  • P3 – Context Updating
  • Production chain maps out initial to goal state
  • Equate ERP latency with timing of cognitive step
  • Timing of ACT-R productions
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Iterative Test-Model

Higher-level strategy

  • Experiment  Model
  • Model gives production times for one cog process
  • Experiment  Model
  • More production times
  • (Experiment-Model)*N
  • N cognitive processes
  • Get to point where production times are based on

empirical data more than guesswork

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Visual Perception EEG Test McDowell, Jeka, Schoner, & Hatfield (2002)

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Visual Test Results

50 100 150 200 250 300 350 400 Freq Rare Freq Rare Freq Rare Freq Rare Narrow Wide Narrow Wide Pressing Pointing Time (ms) Task and Condition N100 P300 RT

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Visual Model

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Visual Model Results

0.5 0.6 0.7 0.8 0.9 1.0 Freq Rare Freq Rare Freq Rare Freq Rare Narrow Wide Narrow Wide Pressing Pointing Correlation with Test Results Condition N1 P3 RT

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Auditory Test Kerick, Oie, & McDowell (2009) High Pitch (20%) Low Pitch (80%) Press Button Don’t Press

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Auditory Results Mean Time in ms (St.Dev) Low High N100 165 (16) 155 (21) P300 352 (36) 384 (40) RT 600 (177)

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Auditory Model

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Auditory Model Results Correlation Low High N100 0.97 0.89 P300 0.97 0.95 RT 0.95

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Decision Making Test Rule Yes, No Negative

  • 9,-8,-7,-6,-5,-4,-3,-2,-1,1,2,3,4,5,6,7,8,9

Odd

  • 9,-8,-7,-6,-5,-4,-3,-2,-1,1,2,3,4,5,6,7,8,9

Complex

  • 9,-8,-7,-6,-5,-4,-3,-2,-1,1,2,3,4,5,6,7,8,9
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D-M Test Results 100 200 300 400 500 600 700 800 900 Neg Odd Complex Time (ms) Rule N100 P300 RT

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D-M Model

N100 P300 Onset Response P300

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DM Model Results

0.5 0.6 0.7 0.8 0.9 1.0 Neg Odd Complex Correlation with Test Results Rule N1 P3 RT

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Production Duration

  • No longer restricted to response time
  • N1 – Perceptual encoding completed
  • P3 – Context updating completed
  • RT – Response made
  • Now segmenting is possible and production times are

less guesswork

  • More?

– P2 (Anderson et al, in press) – lexical access? – P600 (Osterhaut & Holcomb, 1992) – grammatical errors

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Applied Aspects

  • ERP latency  Length of time to complete stage
  • Long N1 – Improve visual saliency?
  • Long P3 – Disambiguate stimuli?
  • Long RT – Improve response requirements?
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A Program of Research

  • Potential for future studies is vast
  • Existing databases with ERP latencies
  • New experiments with ERP latencies
  • Spread over multiple cognitive phenomena
  • Share results with others
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Question? Comments?

  • Cassenti, D.N., Kerick, S.E., & McDowell, K. (2011).

Observing and modeling cognitive events through event related potentials and ACT-R. Cognitive Systems Research, 12, 56-65.

  • Cassenti, D.N. (in press). Opening the Black Box: A Test

and Computational Model of the Relationship between ERPs and Cognition. In Event-Related Potential (ERP): Methods, Outcomes and Research Insights