Piéron’s Law holds in conditions of response conflict Tom Stafford, Kevin N. Gurney & Leanne Ingram Department of Psychology, University of Sheffield

Slides:



Advertisements
Similar presentations
A formal model of new reinforcement sensitivity theory (RST) Alan Pickering Department of Psychology
Advertisements

Communication Theory Lecture 1: Introduction to Communication Theory and Novel Technology Dr. Danaë Stanton Fraser.
Emmanuel A Stamatakis Centre for Speech, Language and the Brain, Department of Experimental Psychology, University of Cambridge School of Psychological.
Detecting Conflict-Related Changes in the ACC Judy Savitskaya 1, Jack Grinband 1,3, Tor Wager 2, Vincent P. Ferrera 3, Joy Hirsch 1,3 1.Program for Imaging.
Chapter Thirteen Conclusion: Where We Go From Here.
Modality-specific interaction between phonology and semantics Gail Moroschan & Chris Westbury Department of Psychology, University of Alberta, Edmonton,
Quasi-Continuous Decision States in the Leaky Competing Accumulator Model Jay McClelland Stanford University With Joel Lachter, Greg Corrado, and Jim Johnston.
Decision Dynamics and Decision States: the Leaky Competing Accumulator Model Psychology 209 March 4, 2013.
SPREADSHEETS IN EDUCATION OF LOGISTICS MANAGERS AT FACULTY OF ORGANIZATIONAL SCIENCES: AN EXAMPLE OF INVENTORY DYNAMICS SIMULATION L. Djordjevic, D. Vasiljevic.
Psycholinguistic methodology Psycholinguistics: Questions and methods.
Midterm 1 Wednesday next week!. Synthesize the Big Picture Understanding Brain-wide neural circuits Extracranial electrophysiology EEG/MEG Metabolic Imaging.
Sensation Perception = gathering information from the environment 2 stages: –Sensation = simple sensory experiences and translating physical energy from.
I. Face Perception II. Visual Imagery. Is Face Recognition Special? Arguments have been made for both functional and neuroanatomical specialization for.
Organizational Notes no study guide no review session not sufficient to just read book and glance at lecture material midterm/final is considered hard.
Copyright 2008 by User Interface Lab Industrial Engineering Dept. of Industrial Systems & Information Engineering Korea University Serial Modules in Parallel.
Stochastic Neural Networks, Optimal Perceptual Interpretation, and the Stochastic Interactive Activation Model PDP Class January 15, 2010.
Pattern Recognition Pattern - complex composition of sensory stimuli that the human observer may recognize as being a member of a class of objects Issue.
Visual Cognition II Object Perception. Theories of Object Recognition Template matching models Feature matching Models Recognition-by-components Configural.
What is Cognitive Science? … is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience,
Models of Human Performance Dr. Chris Baber. 2 Objectives Introduce theory-based models for predicting human performance Introduce competence-based models.
Baysian Approaches Kun Guo, PhD Reader in Cognitive Neuroscience School of Psychology University of Lincoln Quantitative Methods 2011.
What is Cognitive Science? … is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience,
From T. McMillen & P. Holmes, J. Math. Psych. 50: 30-57, MURI Center for Human and Robot Decision Dynamics, Sept 13, Phil Holmes, Jonathan.
Theory of Decision Time Dynamics, with Applications to Memory.
An Integrated Model of Decision Making and Visual Attention Philip L. Smith University of Melbourne Collaborators: Roger Ratcliff, Bradley Wolfgang.
Information Processing Approach Define cognition and differentiate among the stage, levels-of-processing, parallel distributed processing, and connectionist.
Studying Visual Attention with the Visual Search Paradigm Marc Pomplun Department of Computer Science University of Massachusetts at Boston
Understanding Movement Preparation
SLA Seminar, NSYSU 11/17/2006 Ch. 9 Cognitive accounts of SLA OUTLINE Cognitive theory of language acquisition Models of cognitive accounts Implicit vs.
1 Computational Vision CSCI 363, Fall 2012 Lecture 31 Heading Models.
Results Attentional Focus Presence of others restricted the attentional focus: Participants showed a smaller flanker compatibility effect for the error.
Xiao-Jing Wang Department of Neurobiology Yale University School of Medicine The Concept of a Decision Threshold in Sensory-Motor Processes.
Information Processing Assumptions Measuring the real-time stages General theory –structures –control processes Representation –definition –content vs.
Lecture 4 – Attention 1 Three questions: What is attention? Are there different types of attention? What can we do with attention that we cannot do without.
Cognitive Modeling / University of Groningen / / Artificial Intelligence |RENSSELAER| Cognitive Science CogWorks Laboratories › Christian P. Janssen ›
Comp 15 - Usability and Human Factors
Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms Annual Workshop Introduction August, 2008.
Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms Progress and Future Directions November 17, 2009.
Method: Reaction Time (RT)
The effects of working memory load on negative priming in an N-back task Ewald Neumann Brain-Inspired Cognitive Systems (BICS) July, 2010.
A View from the Bottom Peter Dayan Gatsby Computational Neuroscience Unit.
Experimental Psychology PSY 433
Pattern Classification of Attentional Control States S. G. Robison, D. N. Osherson, K. A. Norman, & J. D. Cohen Dept. of Psychology, Princeton University,
Sensation Perception = gathering information from the environment 2 stages: –Sensation = simple sensory experiences and translating physical energy from.
Modeling interactions between visually responsive and movement related neurons in frontal eye field during saccade visual search Braden A. Purcell 1, Richard.
Understanding Movement Preparation Chapter 2. Perception: the process by which meaning is attached to information (interpretation) Theory 1: Indirect.
Principled Probabilistic Inference and Interactive Activation Psych209 January 25, 2013.
What’s optimal about N choices? Tyler McMillen & Phil Holmes, PACM/CSBMB/Conte Center, Princeton University. Banbury, Bunbury, May 2005 at CSH. Thanks.
Grounded cognition. Barsalou, L. W. (2008). Annual Review of Psychology, 59, Grounded theories versus amodal representations. – Recapitulation.
Artificial Intelligence: Research and Collaborative Possibilities a presentation by: Dr. Ernest L. McDuffie, Assistant Professor Department of Computer.
Eye Movements – Target Selection & Control READING Schall JD (2002) The neural selection and control of saccades by frontal eye field. Philosophical Transactions.
Disrupting face biases in visual attention Anna S. Law, Liverpool John Moores University Stephen R. H. Langton, University of Stirling Introduction Method.
Response dynamics and phase oscillators in the brainstem
Signal detection Psychophysics.
How to investigate Perception & Cognition n Ask your subjects (Introspectionism) n Look at S-R patterns (Behaviorism) n Infer mental processes (Cognitive.
1 Computational Vision CSCI 363, Fall 2012 Lecture 32 Biological Heading, Color.
Methods Identifying the Costs of Auditory Dominance on Visual Processing: An Eye Tracking Study Wesley R. Barnhart, Samuel Rivera, & Christopher W. Robinson.
© F. Anceau, Page 1 Sept , Models of Consciousness Exploration Workshop A Model for Consciousness Based on the Sequential Behavior of the Conscious.
Adapted from by E.Day THE COGNITIVE APPROACH TYPES OF PROCESSING.
Hallucination as a Response to the Ecological Approach to Perception
David Marchant, Evelyn Carnegie, Paul Ellison
1 University of Hamburg 2 University of Applied Sciences Heidelberg
A Bayesian account of context-induced orientation illusions
Neural Basis of the Perception and Estimation of Time
King Saud University College of Engineering IE – 341: “Human Factors Engineering” Fall – 2017 (1st Sem H) Chapter 3. Information Input and Processing.
Oliver Sawi1,2, Hunter Johnson1, Kenneth Paap1;
Dynamical Models of Decision Making Optimality, human performance, and principles of neural information processing Jay McClelland Department of Psychology.
Tom Stafford, University of Sheffield
On the unconscious context-specific proportion congruency effect:
Dynamical Models of Decision Making Optimality, human performance, and principles of neural information processing Jay McClelland Department of Psychology.
Presentation transcript:

Piéron’s Law holds in conditions of response conflict Tom Stafford, Kevin N. Gurney & Leanne Ingram Department of Psychology, University of Sheffield CogSci 2009, Amsterdam, 2 nd of August

Image thanks to Roger Carpenter

Stages to decision making? (1)‏ ‘‘Most research on AFM shows consistent and robust evidence in favor of seven successive processing stages in traditional choice reactions” (Sanders, 1990)‏ “information is transmitted discretely between perceptual and response stages of processing” (Woodman et al, 2008)‏ 30/07/09© The University of Sheffield 3 Sanders, A. F. (1990). Issues and trends in the debate on discrete vs continuous processing of information. Acta Psychologica, 74 (2-3), Woodman, G. F., Kang, M. S., Thompson, K., & Schall, J. D. (2008). The effect of visual search efficiency on response preparation: neurophysiological evidence for discrete flow. Psychological Science, 19(2),

Stages to decision making? (2)‏ PDP framework (Rumelhart et al, 1986) explicitly rejects stage models, in favour of continuous processing (McClelland, 1979)‏ Most successful model of RTs is single stage, Ratcliff's diffusion model‏ 30/07/09© The University of Sheffield 4 Rumelhart, D., McClelland, J. & the PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition. Cambridge, MA: MIT Press. McClelland, J. (1979). On the time-relations of mental processes: An examination of systems of processes in cascade. Psychological Review, 86,

30/07/09© The University of Sheffield 5 The diffusion model of decision making Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85(2), Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: Theory and data for two- choice decision tasks. Neural computation, 20(4),

30/07/09© The University of Sheffield 6 Decision making ‘decision making’ research has focused on perceptual decisions (e.g. Gold & Shadlen, 2007)‏ Diffusion model has been shown to be optimal (Bogacz et al, 2006)‏ Optimal processing seems to require integration of factors influencing a decision into a single variable (e.g. Ratcliff, 2001?)‏ Bogacz, R., Brown, E., Moehlis, J., Holmes, P., & Cohen, J. D. (2006). The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. Psychological Review, 113 (4), Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annual Review of Neuroscience, 30, Ratcliff, R. (2001). Putting noise into neurophysiological models of simple decision making. Nature Neuroscience, 4 (4),

Task: to inspect RTs in a more complex‏ choice task, something that is not just a perceptual decision...a decision which involves two factors, which provide evidence that (we might assume) is represented at different stages Are reaction times affected additively by these two factors? Can existing single stage models account for the pattern of results?

The Stroop Task Name the colour ControlSHOE 30/07/09© The University of Sheffield 8

The Stroop Task Name the colour ControlSHOE CongruentGREEN 30/07/09© The University of Sheffield 9

The Stroop Task Name the colour ControlSHOE CongruentGREEN ConflictBLUE 30/07/09© The University of Sheffield 10

30/07/09© The University of Sheffield 11 The stimulus intensity – reaction time function aka ‘Piéron’s Law’ RT = R 0 + kI -β Pieron, H. (1952). The sensations; their functions, processes and mechanisms: Their Functions, Processes, and Mechanisms. Yale University Press.

Pieron's Law found for white light, pure tones, taste...(Luce, 1986)‏...and in simple choice decisions (Pins & Bonnet, 1996)‏ “luminance processing and any further processing due to the specific requirements of the psychophysical task combine additively” Rumelhart, D., McClelland, J. & the PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition. Cambridge, MA: MIT Press. Luce, R. D. (1986). Response times: Their role in inferring elementary mental organization. Oxford University Press. Pins, D., & Bonnet, C. (1996). On the relation between stimulus intensity and processing time: Piéron's law and choice reaction time. Perception and Psychophysics, 58(3),

30/07/09© The University of Sheffield 13 Piéron’s Law inherent in any rise-to- threshold decision process Stafford, T., & Gurney, K. N. (2004). The role of response mechanisms in determining reaction time performance: Pieron’s law revisited. Psychonomic Bulletin & Review, 11(6),

30/07/09© The University of Sheffield 14 Expt 1: A Stroop task with varying levels of colour saturation

30/07/09© The University of Sheffield 15 If saturation and response conflict information are integrated then the different Stroop conditions should differ by different amounts at each level of saturation

Interactive

Additive Interactive

Expt 1 Results, i 30/07/09© The University of Sheffield 18 Colour saturation (%)‏ Reaction Time (ms)‏

Expt 1 Results, ii 30/07/09© The University of Sheffield 19

30/07/09© The University of Sheffield 20 Expt 2: A Stroop task with varying levels of colour saturation, with word and colour elements of the stimulus separated in space

Expt 2 Results, i 30/07/09© The University of Sheffield 21 Colour saturation (%)‏ Reaction Time (ms)‏

Expt 2 Results, ii 30/07/09© The University of Sheffield 22

30/07/09© The University of Sheffield 23 Cohen et al’s (1990) model of Stroop processing Cohen, J. D., Dunbar, K., & McClelland, J. L. (1990). On the control of automatic processes - a parallel distributed-processing account of the stroop effect. Psychological Review, 97 (3),

30/07/09© The University of Sheffield 24 S S Stimulus Stimulus-Response Translation RT

30/07/09© The University of Sheffield 25 Stimulus Stimulus-Response Translation RT S S

30/07/09© The University of Sheffield 26 S Stimulus Stimulus-Response Translation RT S

30/07/09© The University of Sheffield 27 Simulation Results, i

30/07/09© The University of Sheffield 28 Simulation Results, ii

Conclusions (1/2)‏ Stimulus intensity and response conflict appear additive in a colour-saturation variant of the Stroop task...but existing continuous-processing single-stage models of the Stroop task are adequate to account for this result We must be careful before inferring discrete stages from additive RT data 30/07/09© The University of Sheffield 29

Conclusions (2/2)‏ Also, Piéron’s Law holds for colour saturation… ….in a complex choice task 30/07/09© The University of Sheffield 30

Stafford, T., Gurney, K.N. & Ingram, L. (2009). Piéron’s Law holds in conditions of response conflict. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31th Annual Conference of the Cognitive Science Society. Cognitive Science Society. We thank Sarah Fox for help running the experiments, David Lawrence & David Yates for reading drafts and Marius Usher and Eddy Davelaar for useful discussion of the material. CogSci 2009, Amsterdam, 2 nd of August

Locked S S

independent S 1

Single stage, independent inputs

Two stage, locked 1 S 1 S

Two stages, locked inputs

Two stage, independent 1 S 1 1

Two stages, independent inputs

Expt 2, Separated stroop