SlideShare uma empresa Scribd logo
1 de 6
Human Learning
             Topic 12 - 2: Special Issues: Timing




CEDP324   Ryan Sain, Ph.D.    1                     3/30/2012
What is timing?
 Effects of stimuli are determined by durations or
  distributions in time

 Identifying that time has passed – and responding in a
  different manner

 Habituation, sensitization, spontaneous recovery

 Classical conditioning

 Operant conditioning


CEDP324   Ryan Sain, Ph.D.   2                        3/30/2012
Studying timing
 Timing as a biological process

 Environmental clues must be ruled out
     Clocks ticking
     Sun rising




CEDP324   Ryan Sain, Ph.D.   3            3/30/2012
Timing techniques
 Duration estimation
     Discrimination task
     Sd is the duration of an event
     Match to sample procedure
 Peak procedure
     Sd presented
     After specified time passes a response will produce Sr
     Responding follows a generalization gradient

CEDP324   Ryan Sain, Ph.D.     4                        3/30/2012
Time out!
 Using a peak
  procedure
                                     20 second peak   10 second delay
     20 second                      No delay

 Introduce a break in
  the Sd
     10 seconds
     Sd only presented for
      20 seconds total
                                      10       20       30           40
 The peak shifts by that
  amount of break
CEDP324   Ryan Sain, Ph.D.       5                           3/30/2012
Theories
 Cognitive – Scalar Expectancy Theory
     Pacemaker  Switch  accumulator (sums)
     Send that info to working memory
     Then compare that to the stimulus and decide if you should
      respond
 Behavioral
     Adjunctive behavior (waiting behaviors)
              Finger tapping, etc
     Those occur in a particular pattern
     After the pattern is complete the interval should be over

CEDP324       Ryan Sain, Ph.D.       6                            3/30/2012

Mais conteúdo relacionado

Mais de Ryan Sain

324 12 3 special topics tool use language
324 12 3 special topics tool use language324 12 3 special topics tool use language
324 12 3 special topics tool use language
Ryan Sain
 
324 12 part 1 special topics food caching
324 12 part 1 special topics food caching324 12 part 1 special topics food caching
324 12 part 1 special topics food caching
Ryan Sain
 
324 10 observational learning
324 10 observational learning324 10 observational learning
324 10 observational learning
Ryan Sain
 
324 09 avoidance
324 09 avoidance324 09 avoidance
324 09 avoidance
Ryan Sain
 
324 7 part 2 extinction
324 7 part 2 extinction 324 7 part 2 extinction
324 7 part 2 extinction
Ryan Sain
 
324 06 stimulus control
324 06 stimulus control324 06 stimulus control
324 06 stimulus control
Ryan Sain
 
324 05.5 motivational mechanisms
324 05.5 motivational mechanisms324 05.5 motivational mechanisms
324 05.5 motivational mechanisms
Ryan Sain
 

Mais de Ryan Sain (20)

Psyc 321_14 surveys
Psyc 321_14 surveysPsyc 321_14 surveys
Psyc 321_14 surveys
 
Psyc 321_13 ethics
Psyc 321_13 ethicsPsyc 321_13 ethics
Psyc 321_13 ethics
 
Psyc 321_12 small n research
Psyc 321_12 small n researchPsyc 321_12 small n research
Psyc 321_12 small n research
 
Psyc 321_11 quasi experimentation
Psyc 321_11 quasi experimentationPsyc 321_11 quasi experimentation
Psyc 321_11 quasi experimentation
 
psyc 321_10 experimental ecology
psyc 321_10 experimental ecologypsyc 321_10 experimental ecology
psyc 321_10 experimental ecology
 
Psyc 321_09 within groups
Psyc 321_09 within groupsPsyc 321_09 within groups
Psyc 321_09 within groups
 
Psyc 321_07 control
Psyc 321_07 controlPsyc 321_07 control
Psyc 321_07 control
 
psyc 321_06 threats to validity and control
psyc 321_06 threats to validity and controlpsyc 321_06 threats to validity and control
psyc 321_06 threats to validity and control
 
Psyc 321_05 introduction to stats
Psyc 321_05 introduction to statsPsyc 321_05 introduction to stats
Psyc 321_05 introduction to stats
 
Psyc 321_04 numerical description
Psyc 321_04 numerical descriptionPsyc 321_04 numerical description
Psyc 321_04 numerical description
 
Psyc 321_03 hypotheses
Psyc 321_03 hypothesesPsyc 321_03 hypotheses
Psyc 321_03 hypotheses
 
Psyc 321_02 methods of_science
Psyc 321_02 methods of_sciencePsyc 321_02 methods of_science
Psyc 321_02 methods of_science
 
Psyc 321_01 what is science
Psyc 321_01 what is sciencePsyc 321_01 what is science
Psyc 321_01 what is science
 
324 12 3 special topics tool use language
324 12 3 special topics tool use language324 12 3 special topics tool use language
324 12 3 special topics tool use language
 
324 12 part 1 special topics food caching
324 12 part 1 special topics food caching324 12 part 1 special topics food caching
324 12 part 1 special topics food caching
 
324 10 observational learning
324 10 observational learning324 10 observational learning
324 10 observational learning
 
324 09 avoidance
324 09 avoidance324 09 avoidance
324 09 avoidance
 
324 7 part 2 extinction
324 7 part 2 extinction 324 7 part 2 extinction
324 7 part 2 extinction
 
324 06 stimulus control
324 06 stimulus control324 06 stimulus control
324 06 stimulus control
 
324 05.5 motivational mechanisms
324 05.5 motivational mechanisms324 05.5 motivational mechanisms
324 05.5 motivational mechanisms
 

Último

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Último (20)

Cyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdfCyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdf
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUKSpring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 

324 12 2 special topics timing

  • 1. Human Learning Topic 12 - 2: Special Issues: Timing CEDP324 Ryan Sain, Ph.D. 1 3/30/2012
  • 2. What is timing?  Effects of stimuli are determined by durations or distributions in time  Identifying that time has passed – and responding in a different manner  Habituation, sensitization, spontaneous recovery  Classical conditioning  Operant conditioning CEDP324 Ryan Sain, Ph.D. 2 3/30/2012
  • 3. Studying timing  Timing as a biological process  Environmental clues must be ruled out  Clocks ticking  Sun rising CEDP324 Ryan Sain, Ph.D. 3 3/30/2012
  • 4. Timing techniques  Duration estimation  Discrimination task  Sd is the duration of an event  Match to sample procedure  Peak procedure  Sd presented  After specified time passes a response will produce Sr  Responding follows a generalization gradient CEDP324 Ryan Sain, Ph.D. 4 3/30/2012
  • 5. Time out!  Using a peak procedure 20 second peak 10 second delay  20 second No delay  Introduce a break in the Sd  10 seconds  Sd only presented for 20 seconds total 10 20 30 40  The peak shifts by that amount of break CEDP324 Ryan Sain, Ph.D. 5 3/30/2012
  • 6. Theories  Cognitive – Scalar Expectancy Theory  Pacemaker  Switch  accumulator (sums)  Send that info to working memory  Then compare that to the stimulus and decide if you should respond  Behavioral  Adjunctive behavior (waiting behaviors)  Finger tapping, etc  Those occur in a particular pattern  After the pattern is complete the interval should be over CEDP324 Ryan Sain, Ph.D. 6 3/30/2012