SlideShare a Scribd company logo
The vanishing central executive

Distributed neural mechanisms of decision-making



                     Paul Cisek
        Summer School in Cognitive Sciences
       Evolution and Function of Consciousness
                    July 4, 2012
Our question:

• When, where, how and why — since the origin of life on Earth
  about 4 billion years ago — did organisms' input/output
  functions become conscious input/output functions?




            But first, another question:

• Why “input/output” functions?
What is behavior?

sensory                                                                     motor
             Perception           Cognition              Action
  input                                                                     output

                      representation      representation
                        of the world     of the motor plan


   “The whole neural organism, it will be remembered, is,
   physiologically considered, but a machine for converting
   stimuli into reactions” (James, 1890, p. 372).


   Behavior: An analysis of the world,
             followed by deliberation and planning,
             followed by execution of the plan.                   William James

               “sense, think, act”
Psychological architecture for behavior

sensory                                                                     motor
                Perception            Cognition                Action
  input                                                                     output

                          representation        representation
                            of the world       of the motor plan



     •   University courses
     •   Textbooks                         Q: From where does this view originate?
     •   Journals
     •   Conferences
     •   Academic departments
     •   Grant review committees
     •   Scientists
     •   Questions we ask
     •   Theories we propose
“Dualism”

sensory                                                                 motor
                Perception               Mind            Action
  input                                                                 output



                                                                  Socrates

                                                                       Descartes
   •   Philosophy: The mind is non-physical
          – This forces interfaces between non-
            physical mind and physical world



   •   Psychology: Study of the psyche
          – Structuralism: The mind is studied
            through introspection                 John Locke


                                                  Wilhelm Wundt
Behaviorism

sensory                                                 motor
               Perception          Mind        Action
  input                                                 output




          – Stop this metaphysical nonsense…




     John Watson
Behaviorism

sensory                                                                   motor
                Perception                             Action
  input                                                                   output




    – Stop this metaphysical nonsense…
    – Perception and Action are directly linked
    – Subject matter: Learning laws which establish the linkage




  John Watson       Ivan Pavlov     Edward Thorndike       B.F. Skinner
Cognitivism

sensory                                               motor
             Perception                      Action
  input                                               output



    – Internal processes are indispensable            Tolman
Cognitivism

sensory                                                                 motor
               Perception               Cognition       Action
  input                                                                 output



          – Internal processes are indispensable                     Tolman
                                                                        Shannon
          – Cognition takes the mind’s place
          – A fully physical process – but what
            kind?
          – “Information processing”
              • Definition of “information”
              • Definition of “processing”
          – Cognition is a computational process
                                                    Turing
              • Linguistics
                                                      Chomsky
              • Language of thought
                                                             Fodor
Computational view of the brain
•   The “computer metaphor”
    – Cognition is like computation:
      Rule-based manipulation of
      representations
      (Newell & Simon, Pylyshyn)
    – The mind is the software (Block)

                                                   Newell & Simon



    – Studies of mental phenomena may be conducted independently of
      studies of brain physiology
        •   Less to worry about
        •   Not so much known (yet) about the brain
        •   Historical separation between psychology and biology
What kinds of representations?

•   “Descriptive” representations
     –   Capture knowledge about the world
         and the organism
     –   Explicit
     –   Objective, accurate to external            Descriptive representations
         reality, uncontaminated by internal        delineate the conceptual borders
         states                                           input/output
     –   Examples:                                  between the processes that
           •
                                                               ^
               Reconstructed visual image
           •
                                                    construct them and the
               3-D map of the world
                                                 input/output
           •   Labeled objects                          processes   that use them.
           •   Desired path of the hand in space      ^




               David Marr
Can we use this to understand the brain?

•   Cognitive Neuroscience
     – How are psychological /
       cognitive functions produced by
       the brain?
     – Ex: Decision-making
     – Based on the concepts of
       cognitivism
         • Computation, descriptive
           representations, working
           memory, attentional filters,   Michael Gazzaniga
           motor programs, etc.
Where is the central representation?

•   The visual system
    – Two visual processing streams:
        •   ventral “what”
        •                                 where
            dorsal “where”
    – Separate regions analyze color,
      motion, form, etc.
    – Separate regions for near and
      far space
                                           what
•   Binding problem
    – How to create the unified
      representation of the world that
      is needed as input for cognition?
Perception, Cognition, & Action Systems?

•   Primary sensory and motor regions
•   “Association” regions
    – Appear to first encode sensory,
      then motor representations          Cognition?
                                                       Cognition
    – Even true at the level of
                                                       Cognition
      individual neurons

    Example: Lateral intraparietal area
    – is it “attention”?
      (input to cognition)
    – or “intention”?
      (output of cognition)
    – How could it be both?
    – Could it be cognition?
Where is the central executive?

•   Decision-making
    – Neural correlates in prefrontal
      and orbitofrontal cortex
    – also in parietal cortex
    – Premotor cortex
    – Supplemental motor area
    – Frontal eye fields
    – Basal ganglia
    – Even the superior colliculus

    – Activity reflects decision everywhere at
      about the same time (~150ms)
Conceptual challenges

• The binding problem
   – How to create the unified representation of the world that is needed
     as input for cognition?

• The problem of meaning
   – How does a computational process know the meaning of the
     representations that it manipulates?
   – “Chinese Room” (Searle)
   – The “symbol grounding problem” (Harnad)
   – Representations are purely syntactic, they have no intrinsic
                             input/output
     semantics, no meaning to the system that uses them
                                  ^
Psychological architecture for behavior

sensory                                                               motor
                Perception         Cognition            Action
  input                                                               output



   •      Some observations:
          1. This model inherits its structure from
             mind-body dualism
          2. Was designed to explain the abstract
             problem-solving behavior of adult humans
          3. Its concepts were developed under the
             explicit assumption that the substrate
             doesn’t matter

   •      Perhaps it should not be surprising that this model has difficulty
          explaining neural data…
Evolution

         •   Two key concepts:

             – Natural selection
                 • What is the selective advantage of X?


Darwin
             – Descent with modification
                 • What are the phylogenetic origins of X?
The long history of behavior
Are brains input/output devices?

• What else could they be?
What kinds of devices are living systems?

• Control systems:
   – Ex: Biochemistry
       • Suppose there is some substance A necessary               A



         for survival
       • Suppose there’s a catalyst for creating A whose
         action is regulated inversely by the concentration of A
       • Feedback control system
       • Exploits consistencies in the laws of chemistry
       • Control loop within the organism: “Physiology”
What kinds of devices are living systems?

• Control systems can extend beyond the skin
   – Ex: Kinesis
                                                                   B

       • Suppose substance B cannot be produced                                A



         within the body, must be absorbed from the world
       • If the local concentration of substance B falls
         below desired levels, move randomly
       • Exploits statistics of nutrient distributions
         (assumes that there is more elsewhere)                   Concentration of [B]
       • Control loop that extends outside the skin: “Behavior”
   – Reliable motor-sensory contingencies exist
       • Statistics of food distributions (move → find food)
       • Laws of optics and mechanics (contract muscle → arm moves)
       • Laws of interaction (you show teeth → I back off)

• Animals are constantly doing whatever brings them to the most
  desirable situation (full stomach, safety, etc.)
       • “Behavior: The control of perception” (Powers, 1973)
Different ways of looking at behavior

1. Given a perception, produce the best action
   “The whole neural organism, it will be
   remembered, is, physiologically considered,
   but a machine for converting stimuli into
   reactions” (James, 1890).
                                                 William James



2. Of the possible actions, produce that which
   results in the best perception
   “What we have is a circuit… the motor
   response determines the stimulus, just as
   truly as sensory stimulus determines
   movement” (Dewey, 1896).
                                                 John Dewey
Ethology

•   Studies of animal behavior in                      Von Uexküll

    the wild


•   Species-specific behavioral
    niches


•   “Closed-loop” sensorimotor
    control


•   Key stimuli



                            Lorenz & Von Holst


                                           Tinbergen
What kinds of representations?

•   “Descriptive” representations                  •   “Pragmatic” representations
     –   Capture knowledge about the world              –   Used to guide interaction between
         and the organism                                   the world and the organism
     –   Explicit                                       –   Implicit
     –   Objective, accurate to external                –   Subjective, mix external reality and
         reality, uncontaminated by internal                internal state, often correlate with
                                                            many variables at once
         states
                                                        –   Examples:
     –   Examples:
                                                              •   Salience map
           •   Reconstructed visual image                     •   Motor signals to the limb
           •   3-D map of the world                           •   Subject-dependent opportunities for
           •   Labeled objects                                    action (“affordances”)
           •   Desired path of the hand in space




               David Marr                                             J.J. Gibson
Example: Decision-making

What to do?
 Move the queen?
 Protect the pawn?
 Threaten the
  knight?
                                                                    How to do it?
                                                                     Which grasp point?
“Selection”                                                          What trajectory?
                                                                     How to avoid
                                                                      obstacles?


                                                                    “Specification”


     • Classical model:
           – First decide what to do (select) then plan the movement (specify)
           – Sense, think, act
Decision-making in the wild




•   The world presents animals with multiple opportunities for action (“affordances”)
•   Cannot perform all actions at the same time
•   Real-time activity is constantly modifying affordances, introducing new ones, etc.
Paul Cisek Model - No "Decision" "Decision-Making"
Paul Cisek Model - No "Decision" "Decision-Making"
Action specification and selection
must occur in parallel
Paul Cisek Model - No "Decision" "Decision-Making"
Sensorimotor contingencies influence
how selection should be done
Specification and selection in parallel

                                               A population of tuned neurons




                                    Distance




                                                                               Cell activity
                                                       Direction


•   Action Specification: Activation of parameter regions corresponding
    to potential actions
•   Action Selection: Competition between distinct regions of activity
What are the neural substrates?
attention   Specification in the dorsal visual stream
             –   Cells sensitive to spatial visual information
                 (Ungerleider & Mishkin …)
             –   Involved in action guidance (Milner & Goodale)
             –   Divergence into separate sub-streams, each
                 specialized toward different kinds of actions
                 (Stein; Andersen; Colby & Goldberg; Matelli &
                 Luppino ...)
             –   An increasing influence of attentional effects,
                 enhancing information from particular regions of
                 interest (Duncan & Desimone; Posner & Gilbert;
                 Treue; Boynton ...)
             –   Parietal representation of external world is
                 “sparse” (Goldberg)
potential actions




attention




                       Fronto-parietal system
                         –      Activity related to potential motor
                                actions (Andersen; Georgopoulos;
                                Kalaska; Wise; Hoshi & Tanji)
                         –      Competition between potential actions
                         –      Various biasing factors
                                 • attention (Goldberg; Steinmetz)
                                 • behavioral relevance
                                     (Mountcastle; Seal & Gross)
                                 • probability (Glimcher; Shadlen)
                                 • reward (Glimcher; Olson)
potential actions




attention




                 behavioral
                 biasing



                       Basal ganglia
                         –      Cortico-striatal-pallido-thalamo-cortical
                                loops (Alexander; Middleton & Strick)
                         –      Selection of actions from among
                                alternatives (Mink; Redgrave et al.)
                         –      Reward (Hikosaka; Schultz)
potential actions




attention
                                          cognitive
                                         decision-making




                 behavioral
                 biasing


                                    Prefrontal cortex
                                     –    High-level decisions
                                          based on knowledge
                         object           about object identity
                         identity         (Fuster; Miller; Tanji…)
                                     –    Receives ventral stream
                                          information on object
                                          identity (Sakata…)
potential actions




attention
                                                                  cognitive
                                                                 decision-making




                   predicted        behavioral
                   feedback         biasing


                                                                   Execution
                                                                     –   Fast visual feedback
                                                                         (Prablanc; Desmurget)
                                            object                   –   Forward models
                                            identity
                                                                         (Ito; Wolpert; Miall)




 visual feedback                                       motor
                                                       command
potential actions




attention
                                                                  cognitive
                                                                 decision-making




                   predicted        behavioral
                   feedback         biasing




                                            object
                                            identity




 visual feedback                                       motor
                                                       command
“Affordance competition hypothesis”
                                       potential actions

   Cisek (2007) Phil.Trans.Royal Soc. B.

•attention
     Continuous specification of currently available potential actions
                                                                            cognitive
                                                                           decision-making
• Competition between potential action representations in fronto-
  parietal regions
• Biasing from frontal and subcortical areas
               predicted       behavioral
                     feedback               biasing
• Decision is made through a “distributed consensus”


                                                      object
                                                      identity




 visual feedback                                                 motor
                                                                 command
Behavior



          Perception                                     Cognition                                    Action

                                audition   attention                     propositional
proprioception         vision                                                logic                              forward
                                                                                                     inverse
                                                       decision   planning                                      models
                                                                                                   kinematics
                                                       making

           object                vision
                                                                   trajectory      action
         recognition            of space         reinforcement
                                                                  generation     sequencing
                                                    learning



                                                        Behavior

                       Action                                                             Action
                    specification                                                        selection

                                                                                              decision
         grasping           reaching       running                          attention         making             affect

                                                                                                            reinforcement
           forward    vision proprio- inverse arm                                   key stimulus
                                                                                                     action    learning
                                       kinematics                                    detection
         arm models of nearby ception                                                              sequencing
                      space
                                                                                  object
                                                                                                      propositional
                                                                                recognition
                                                                                                          logic
Predictions


• Multiple potential actions can be specified simultaneously


• Biased competition between potential actions


• Everything occurs in parallel
Neural activity specifies multiple actions

                                      Classic model:
                                       – Store information, decide,
                                         then plan one action

                                      Affordance competition:
                                       – Specify both actions,
                                         then select one
                               Time
      Ce
      Ce




Primary
        llll P
             PD




 Motor
               D




Cortex

            Caudal
             PMd


                     Rostral
                      PMd

                                Cisek & Kalaska (2005) Neuron
Predictions


• Multiple potential actions can be specified simultaneously


• Biased competition between potential actions


• Everything occurs in parallel
Biased choice task

1-TARGET                                       1 drop       Alexandre
   CHT                                         2 drops      Pastor-Bernier
           DELAY
                                               3 drops
                   GO

                            THT



                                   Reward: 1




                              GO
2-TARGET
                     FREE              THT
   CHT
                                                Reward: 3
           DELAY   67%



                              GO

                                       THT

                   33%


                   FORCED                       Reward: 1
Neural activity in premotor cortex
•   No effect of value
    in 1T task
•   However, if another
    target is present, then
    activity increases with
    value of preferred
    target
•   If value of preferred
    target is constant,
    activity decreases with
    value of other target
•   Activity decreases with
    distance between
    targets


                              Pastor-Bernier & Cisek (2011) J. Neurosci.
Distance-dependent interactions

                •   More activity when targets are
                    closer
                •   Compare the strength of the
                    competition as a function of
                    target distance
                     – As distance increases, slope is
                       increasingly negative



                •   The competition is strongest
                    between cells with the largest
                    difference in preferred directions
Why should it matter that distance matters?

• The distance effect suggests that the decision is made
  within the sensorimotor system
   – If decisions were purely cognitive (“I prefer to get 3 drops of juice
     over 1 drop”), then they should be determined in an abstract space
   – The dynamics of the competition which determines choice depend
     on the spatial relationship between the movements themselves
Predictions


• Multiple potential actions can be specified simultaneously


• Biased competition between potential actions


• Everything occurs in parallel
potential actions




attention
                                                                  cognitive
                                                                 decision-making




                   predicted        behavioral
                   feedback         biasing




                                            object
                                            identity




 visual feedback                                       motor
                                                       command
Timing
                                       potential actions




• An animal is constantly interacting with the world
attention
     –      Continuous sensorimotor control of ongoing actions cognitive
                                                              decision-making
     –      Continuous specification of alternative actions
     –      Continuous evaluation of value
     –      Continuous tradeoffs between persisting in a given activity or
            switching to a different, currently available one
                       predicted           behavioral
                       feedback             biasing
• Specification and selection must normally occur in parallel
• However, if we put the animal in the lab
     – Time is broken into discrete “trials”object of which begins with a
                                             each
       stimulus and ends with a responseidentity
     – The stimulus is deliberately made independent from the response

• What should we see?                                      motor
 visual feedback
                                                           command
potential actions




attention
                                                                  cognitive
                                                                 decision-making




                   predicted        behavioral
                   feedback         biasing




                                            object
                                            identity




 visual feedback                                       motor
                                                       command
potential actions




Wave 1. Fast feedforward sweep
potential actions




attention
                                               cognitive
                                              decision-making




                           behavioral
                           biasing




                                   object
                                   identity




     Wave 2. Attentional/Decisional modulation
Two waves of activity
Ledberg et al. (2007) Cerebral Cortex




 •   Measured LFPs from various regions of cerebral cortex
 •   Monkeys performed a conditional GO / NOGO task
Two waves of activity




1. Fast feedforward sweep
    •   Activation in ~50ms
        throughout dorsal
        stream and frontal
        cortex

2. Attentional/Decisional
    •   About 150ms post-
        stimulus,
        discrimination of
        Go/Nogo throughout
        the cortex
Summary 1: Experimental data

• Simultaneous specification of multiple potential actions
    – Arm reaching system (PMd, PRR, M1)
    – Grasping system (AIP, PMv)
    – Saccade system (LIP, FEF, Superior colliculus)
• Biased competition
    – Potential actions compete against each other within sensorimotor
      maps, influenced by a variety of biasing factors (e.g. reward)
    – NOTE: Similar mechanism as attention (Duncan & Desimone)
        • “Attention” is selection near sensors, “decision” is selection near
          effectors
    – Influences depend on geometry – decisions are not simply abstract
        • These are “pragmatic” representations, not “descriptive”
    – Decision is made through a “distributed consensus”
• Parallel specification and selection systems
Summary 2: Theoretical concepts

•   “Affordance competition hypothesis”
     – Instead of serial Perception, Cognition, & Action modules, we have parallel
       specification and selection systems
     – Better match to neural data
     – Better suited to the kinds of tasks that dominated animal behavior

•   “Pragmatic representations”
     – Neural activity aimed not at describing the world, but at mediating
       interaction with the world
     – Correlation with external and internal variables is necessary, but mixtures
       are useful (e.g. spatial direction mixed with reward values)
     – Conjecture: Most, but not all, neural activity is of this kind
          • “Descriptive” representations (e.g. in the ventral stream) emerged in evolution as
            specializations of pragmatic representations for advanced selection

•   Cognitive advances evolved through hierarchical elaboration
     – Diversification of fronto-parietal loops, cortico-striatal circuits, cortico-
       cerebellar circuits, into progressively anterior/abstract systems
     – Interaction lays the foundation for cognition (Piaget)
Summary 3: Philosophical implications

•   There is no central executive
     – Decisions emerge through a distributed consensus

•   Classic problems in a different context
     – Binding problem:
         • Activity of separate streams is coherent by virtue of dealing with the same world
     – Symbol grounding problem:
         • Interaction has meaning by virtue of influencing the variables critical for life
         • Symbols are specializations (“shorthand notation”) that emerged late in evolution,
           already within the context of grounded interaction
     – The “Hard” problem
         • Feeling is different than doing
              – Being inside the loop is different than observing it from the outside
              – Private language, beetle in box, squirrel in head, 1 st person perspective, the “Umwelt”

•   The computer metaphor
     – With all due respect to Alan Turing, the computer metaphor is misleading as
       a model for the brain
     – What matters is control (Wiener, Ashby, Powers, Gibson, Dewey, etc.)
“The great end of life is not
 knowledge but action”
                  – T. H. Huxley
                    (1825-1895)




“Your head is there to move
 you around”
            – R.E.M. (1980-2011)
THANK YOU

•   Lab members
    –   Marie-Claude Labonté
    –   Alexandre Pastor-Bernier
    –   David Thura
    –   Ignasi Cos
    –   Matthew Carland
    –   Jessica Trung

•   Alumni
    – Jean-Philippe Thivierge
    – Thomas Michelet
    – Valeriya Gritsenko


                                       EJLB
                                     THE
                                     FOUNDATION

        paul.cisek@gmail.com

More Related Content

PPTX
深層強化学習による自動運転車両の追い越し行動の実現に関する研究
PDF
【DL輪読会】GradMax: Growing Neural Networks using Gradient Information
PPTX
[DL輪読会]機械学習におけるカオス現象について
PDF
Jubatus Casual Talks #2 異常検知入門
PPT
Artificial intelligence and knowledge representation
PDF
Dynamic Routing Between Capsules
PDF
[DL輪読会]Control as Inferenceと発展
PPTX
ベイズ深層学習5章 ニューラルネットワークのベイズ推論 Bayesian deep learning
深層強化学習による自動運転車両の追い越し行動の実現に関する研究
【DL輪読会】GradMax: Growing Neural Networks using Gradient Information
[DL輪読会]機械学習におけるカオス現象について
Jubatus Casual Talks #2 異常検知入門
Artificial intelligence and knowledge representation
Dynamic Routing Between Capsules
[DL輪読会]Control as Inferenceと発展
ベイズ深層学習5章 ニューラルネットワークのベイズ推論 Bayesian deep learning

What's hot (20)

PPTX
[DL輪読会]World Models
PPTX
[DL輪読会]モデルベース強化学習とEnergy Based Model
PDF
Learning to forget continual prediction with lstm
PDF
Deep Learning技術の今
PDF
Meta-Learning with Memory Augmented Neural Network
PPTX
[授業]洞察問題解決プロセスの分析(眼編)
PDF
能動学習セミナー
PDF
PPTX
[DL輪読会]Meta-Learning Probabilistic Inference for Prediction
PDF
心理学/認知科学者のための人工知能概論
PPTX
[DL輪読会]representation learning via invariant causal mechanisms
PDF
[DL輪読会]Feature Interaction Interpretability: A Case for Explanining Ad-Recomm...
PDF
애자일 머신러닝
PDF
Matlantisに込められた 技術・思想_高本_Matlantis User Conference
PDF
(DL hacks輪読) Variational Dropout and the Local Reparameterization Trick
PDF
Ant Colony Optimization: Routing
PPTX
[DL輪読会]物理学による帰納バイアスを組み込んだダイナミクスモデル作成に関する論文まとめ
PPTX
論文紹介: "MolGAN: An implicit generative model for small molecular graphs"
PPTX
Knowledge representation and reasoning
PPT
Or seminar2011final
[DL輪読会]World Models
[DL輪読会]モデルベース強化学習とEnergy Based Model
Learning to forget continual prediction with lstm
Deep Learning技術の今
Meta-Learning with Memory Augmented Neural Network
[授業]洞察問題解決プロセスの分析(眼編)
能動学習セミナー
[DL輪読会]Meta-Learning Probabilistic Inference for Prediction
心理学/認知科学者のための人工知能概論
[DL輪読会]representation learning via invariant causal mechanisms
[DL輪読会]Feature Interaction Interpretability: A Case for Explanining Ad-Recomm...
애자일 머신러닝
Matlantisに込められた 技術・思想_高本_Matlantis User Conference
(DL hacks輪読) Variational Dropout and the Local Reparameterization Trick
Ant Colony Optimization: Routing
[DL輪読会]物理学による帰納バイアスを組み込んだダイナミクスモデル作成に関する論文まとめ
論文紹介: "MolGAN: An implicit generative model for small molecular graphs"
Knowledge representation and reasoning
Or seminar2011final
Ad

Similar to Paul Cisek Model - No "Decision" "Decision-Making" (20)

PPT
introduction to cognition
PDF
Mind Models (Minsky, Pinker, Hawkins)
PDF
Hpai class 25 - emotions in ai and self -051820
PDF
Cognetics
PPTX
Computational Imagination
PPTX
Psychology Presentation final.pptx
PPTX
Cognitive processes
PPTX
Lec1 introduction
PDF
Vass2012 fisher
PPTX
Artificial intelligence
PPTX
Creating Consciousness
PPT
Artificial_Intelligence.ppt
PPTX
Visual Thinking
PDF
Expoiting Cognitive Biais - Creating UX for the Irrational Human Mind
PPT
Cognitive Science and AI
PPT
Artificialintelligence 131226011156-phpapp02
PPTX
Abhinav
PPTX
Artificial intelligence
PPTX
Mind and language: Ontology and neuroscience
PPTX
FOUNDATIONS OF ARTIFICIAL INTELIGENCE BASICS
introduction to cognition
Mind Models (Minsky, Pinker, Hawkins)
Hpai class 25 - emotions in ai and self -051820
Cognetics
Computational Imagination
Psychology Presentation final.pptx
Cognitive processes
Lec1 introduction
Vass2012 fisher
Artificial intelligence
Creating Consciousness
Artificial_Intelligence.ppt
Visual Thinking
Expoiting Cognitive Biais - Creating UX for the Irrational Human Mind
Cognitive Science and AI
Artificialintelligence 131226011156-phpapp02
Abhinav
Artificial intelligence
Mind and language: Ontology and neuroscience
FOUNDATIONS OF ARTIFICIAL INTELIGENCE BASICS
Ad

Recently uploaded (20)

PDF
Nante Industrial Plug Factory: Engineering Quality for Modern Power Applications
PDF
Keppel_Proposed Divestment of M1 Limited
PDF
pdfcoffee.com-opt-b1plus-sb-answers.pdfvi
PDF
Building a Smart Pet Ecosystem: A Full Introduction to Zhejiang Beijing Techn...
PDF
Comments on Crystal Cloud and Energy Star.pdf
PDF
Technical Architecture - Chainsys dataZap
PPTX
Astra-Investor- business Presentation (1).pptx
PPTX
Slide gioi thieu VietinBank Quy 2 - 2025
PDF
kom-180-proposal-for-a-directive-amending-directive-2014-45-eu-and-directive-...
PPTX
3. HISTORICAL PERSPECTIVE UNIIT 3^..pptx
PDF
Charisse Litchman: A Maverick Making Neurological Care More Accessible
PDF
Introduction to Generative Engine Optimization (GEO)
PDF
ANALYZING THE OPPORTUNITIES OF DIGITAL MARKETING IN BANGLADESH TO PROVIDE AN ...
PDF
1911 Gold Corporate Presentation Aug 2025.pdf
PDF
Digital Marketing & E-commerce Certificate Glossary.pdf.................
PDF
How to Get Funding for Your Trucking Business
PDF
Module 2 - Modern Supervison Challenges - Student Resource.pdf
PDF
Booking.com The Global AI Sentiment Report 2025
PDF
TyAnn Osborn: A Visionary Leader Shaping Corporate Workforce Dynamics
PDF
Daniels 2024 Inclusive, Sustainable Development
Nante Industrial Plug Factory: Engineering Quality for Modern Power Applications
Keppel_Proposed Divestment of M1 Limited
pdfcoffee.com-opt-b1plus-sb-answers.pdfvi
Building a Smart Pet Ecosystem: A Full Introduction to Zhejiang Beijing Techn...
Comments on Crystal Cloud and Energy Star.pdf
Technical Architecture - Chainsys dataZap
Astra-Investor- business Presentation (1).pptx
Slide gioi thieu VietinBank Quy 2 - 2025
kom-180-proposal-for-a-directive-amending-directive-2014-45-eu-and-directive-...
3. HISTORICAL PERSPECTIVE UNIIT 3^..pptx
Charisse Litchman: A Maverick Making Neurological Care More Accessible
Introduction to Generative Engine Optimization (GEO)
ANALYZING THE OPPORTUNITIES OF DIGITAL MARKETING IN BANGLADESH TO PROVIDE AN ...
1911 Gold Corporate Presentation Aug 2025.pdf
Digital Marketing & E-commerce Certificate Glossary.pdf.................
How to Get Funding for Your Trucking Business
Module 2 - Modern Supervison Challenges - Student Resource.pdf
Booking.com The Global AI Sentiment Report 2025
TyAnn Osborn: A Visionary Leader Shaping Corporate Workforce Dynamics
Daniels 2024 Inclusive, Sustainable Development

Paul Cisek Model - No "Decision" "Decision-Making"

  • 1. The vanishing central executive Distributed neural mechanisms of decision-making Paul Cisek Summer School in Cognitive Sciences Evolution and Function of Consciousness July 4, 2012
  • 2. Our question: • When, where, how and why — since the origin of life on Earth about 4 billion years ago — did organisms' input/output functions become conscious input/output functions? But first, another question: • Why “input/output” functions?
  • 3. What is behavior? sensory motor Perception Cognition Action input output representation representation of the world of the motor plan “The whole neural organism, it will be remembered, is, physiologically considered, but a machine for converting stimuli into reactions” (James, 1890, p. 372). Behavior: An analysis of the world, followed by deliberation and planning, followed by execution of the plan. William James “sense, think, act”
  • 4. Psychological architecture for behavior sensory motor Perception Cognition Action input output representation representation of the world of the motor plan • University courses • Textbooks Q: From where does this view originate? • Journals • Conferences • Academic departments • Grant review committees • Scientists • Questions we ask • Theories we propose
  • 5. “Dualism” sensory motor Perception Mind Action input output Socrates Descartes • Philosophy: The mind is non-physical – This forces interfaces between non- physical mind and physical world • Psychology: Study of the psyche – Structuralism: The mind is studied through introspection John Locke Wilhelm Wundt
  • 6. Behaviorism sensory motor Perception Mind Action input output – Stop this metaphysical nonsense… John Watson
  • 7. Behaviorism sensory motor Perception Action input output – Stop this metaphysical nonsense… – Perception and Action are directly linked – Subject matter: Learning laws which establish the linkage John Watson Ivan Pavlov Edward Thorndike B.F. Skinner
  • 8. Cognitivism sensory motor Perception Action input output – Internal processes are indispensable Tolman
  • 9. Cognitivism sensory motor Perception Cognition Action input output – Internal processes are indispensable Tolman Shannon – Cognition takes the mind’s place – A fully physical process – but what kind? – “Information processing” • Definition of “information” • Definition of “processing” – Cognition is a computational process Turing • Linguistics Chomsky • Language of thought Fodor
  • 10. Computational view of the brain • The “computer metaphor” – Cognition is like computation: Rule-based manipulation of representations (Newell & Simon, Pylyshyn) – The mind is the software (Block) Newell & Simon – Studies of mental phenomena may be conducted independently of studies of brain physiology • Less to worry about • Not so much known (yet) about the brain • Historical separation between psychology and biology
  • 11. What kinds of representations? • “Descriptive” representations – Capture knowledge about the world and the organism – Explicit – Objective, accurate to external Descriptive representations reality, uncontaminated by internal delineate the conceptual borders states input/output – Examples: between the processes that • ^ Reconstructed visual image • construct them and the 3-D map of the world input/output • Labeled objects processes that use them. • Desired path of the hand in space ^ David Marr
  • 12. Can we use this to understand the brain? • Cognitive Neuroscience – How are psychological / cognitive functions produced by the brain? – Ex: Decision-making – Based on the concepts of cognitivism • Computation, descriptive representations, working memory, attentional filters, Michael Gazzaniga motor programs, etc.
  • 13. Where is the central representation? • The visual system – Two visual processing streams: • ventral “what” • where dorsal “where” – Separate regions analyze color, motion, form, etc. – Separate regions for near and far space what • Binding problem – How to create the unified representation of the world that is needed as input for cognition?
  • 14. Perception, Cognition, & Action Systems? • Primary sensory and motor regions • “Association” regions – Appear to first encode sensory, then motor representations Cognition? Cognition – Even true at the level of Cognition individual neurons Example: Lateral intraparietal area – is it “attention”? (input to cognition) – or “intention”? (output of cognition) – How could it be both? – Could it be cognition?
  • 15. Where is the central executive? • Decision-making – Neural correlates in prefrontal and orbitofrontal cortex – also in parietal cortex – Premotor cortex – Supplemental motor area – Frontal eye fields – Basal ganglia – Even the superior colliculus – Activity reflects decision everywhere at about the same time (~150ms)
  • 16. Conceptual challenges • The binding problem – How to create the unified representation of the world that is needed as input for cognition? • The problem of meaning – How does a computational process know the meaning of the representations that it manipulates? – “Chinese Room” (Searle) – The “symbol grounding problem” (Harnad) – Representations are purely syntactic, they have no intrinsic input/output semantics, no meaning to the system that uses them ^
  • 17. Psychological architecture for behavior sensory motor Perception Cognition Action input output • Some observations: 1. This model inherits its structure from mind-body dualism 2. Was designed to explain the abstract problem-solving behavior of adult humans 3. Its concepts were developed under the explicit assumption that the substrate doesn’t matter • Perhaps it should not be surprising that this model has difficulty explaining neural data…
  • 18. Evolution • Two key concepts: – Natural selection • What is the selective advantage of X? Darwin – Descent with modification • What are the phylogenetic origins of X?
  • 19. The long history of behavior
  • 20. Are brains input/output devices? • What else could they be?
  • 21. What kinds of devices are living systems? • Control systems: – Ex: Biochemistry • Suppose there is some substance A necessary A for survival • Suppose there’s a catalyst for creating A whose action is regulated inversely by the concentration of A • Feedback control system • Exploits consistencies in the laws of chemistry • Control loop within the organism: “Physiology”
  • 22. What kinds of devices are living systems? • Control systems can extend beyond the skin – Ex: Kinesis B • Suppose substance B cannot be produced A within the body, must be absorbed from the world • If the local concentration of substance B falls below desired levels, move randomly • Exploits statistics of nutrient distributions (assumes that there is more elsewhere) Concentration of [B] • Control loop that extends outside the skin: “Behavior” – Reliable motor-sensory contingencies exist • Statistics of food distributions (move → find food) • Laws of optics and mechanics (contract muscle → arm moves) • Laws of interaction (you show teeth → I back off) • Animals are constantly doing whatever brings them to the most desirable situation (full stomach, safety, etc.) • “Behavior: The control of perception” (Powers, 1973)
  • 23. Different ways of looking at behavior 1. Given a perception, produce the best action “The whole neural organism, it will be remembered, is, physiologically considered, but a machine for converting stimuli into reactions” (James, 1890). William James 2. Of the possible actions, produce that which results in the best perception “What we have is a circuit… the motor response determines the stimulus, just as truly as sensory stimulus determines movement” (Dewey, 1896). John Dewey
  • 24. Ethology • Studies of animal behavior in Von Uexküll the wild • Species-specific behavioral niches • “Closed-loop” sensorimotor control • Key stimuli Lorenz & Von Holst Tinbergen
  • 25. What kinds of representations? • “Descriptive” representations • “Pragmatic” representations – Capture knowledge about the world – Used to guide interaction between and the organism the world and the organism – Explicit – Implicit – Objective, accurate to external – Subjective, mix external reality and reality, uncontaminated by internal internal state, often correlate with many variables at once states – Examples: – Examples: • Salience map • Reconstructed visual image • Motor signals to the limb • 3-D map of the world • Subject-dependent opportunities for • Labeled objects action (“affordances”) • Desired path of the hand in space David Marr J.J. Gibson
  • 26. Example: Decision-making What to do? Move the queen? Protect the pawn? Threaten the knight? How to do it? Which grasp point? “Selection” What trajectory? How to avoid obstacles? “Specification” • Classical model: – First decide what to do (select) then plan the movement (specify) – Sense, think, act
  • 27. Decision-making in the wild • The world presents animals with multiple opportunities for action (“affordances”) • Cannot perform all actions at the same time • Real-time activity is constantly modifying affordances, introducing new ones, etc.
  • 30. Action specification and selection must occur in parallel
  • 32. Sensorimotor contingencies influence how selection should be done
  • 33. Specification and selection in parallel A population of tuned neurons Distance Cell activity Direction • Action Specification: Activation of parameter regions corresponding to potential actions • Action Selection: Competition between distinct regions of activity
  • 34. What are the neural substrates?
  • 35. attention Specification in the dorsal visual stream – Cells sensitive to spatial visual information (Ungerleider & Mishkin …) – Involved in action guidance (Milner & Goodale) – Divergence into separate sub-streams, each specialized toward different kinds of actions (Stein; Andersen; Colby & Goldberg; Matelli & Luppino ...) – An increasing influence of attentional effects, enhancing information from particular regions of interest (Duncan & Desimone; Posner & Gilbert; Treue; Boynton ...) – Parietal representation of external world is “sparse” (Goldberg)
  • 36. potential actions attention Fronto-parietal system – Activity related to potential motor actions (Andersen; Georgopoulos; Kalaska; Wise; Hoshi & Tanji) – Competition between potential actions – Various biasing factors • attention (Goldberg; Steinmetz) • behavioral relevance (Mountcastle; Seal & Gross) • probability (Glimcher; Shadlen) • reward (Glimcher; Olson)
  • 37. potential actions attention behavioral biasing Basal ganglia – Cortico-striatal-pallido-thalamo-cortical loops (Alexander; Middleton & Strick) – Selection of actions from among alternatives (Mink; Redgrave et al.) – Reward (Hikosaka; Schultz)
  • 38. potential actions attention cognitive decision-making behavioral biasing Prefrontal cortex – High-level decisions based on knowledge object about object identity identity (Fuster; Miller; Tanji…) – Receives ventral stream information on object identity (Sakata…)
  • 39. potential actions attention cognitive decision-making predicted behavioral feedback biasing Execution – Fast visual feedback (Prablanc; Desmurget) object – Forward models identity (Ito; Wolpert; Miall) visual feedback motor command
  • 40. potential actions attention cognitive decision-making predicted behavioral feedback biasing object identity visual feedback motor command
  • 41. “Affordance competition hypothesis” potential actions Cisek (2007) Phil.Trans.Royal Soc. B. •attention Continuous specification of currently available potential actions cognitive decision-making • Competition between potential action representations in fronto- parietal regions • Biasing from frontal and subcortical areas predicted behavioral feedback biasing • Decision is made through a “distributed consensus” object identity visual feedback motor command
  • 42. Behavior Perception Cognition Action audition attention propositional proprioception vision logic forward inverse decision planning models kinematics making object vision trajectory action recognition of space reinforcement generation sequencing learning Behavior Action Action specification selection decision grasping reaching running attention making affect reinforcement forward vision proprio- inverse arm key stimulus action learning kinematics detection arm models of nearby ception sequencing space object propositional recognition logic
  • 43. Predictions • Multiple potential actions can be specified simultaneously • Biased competition between potential actions • Everything occurs in parallel
  • 44. Neural activity specifies multiple actions Classic model: – Store information, decide, then plan one action Affordance competition: – Specify both actions, then select one Time Ce Ce Primary llll P PD Motor D Cortex Caudal PMd Rostral PMd Cisek & Kalaska (2005) Neuron
  • 45. Predictions • Multiple potential actions can be specified simultaneously • Biased competition between potential actions • Everything occurs in parallel
  • 46. Biased choice task 1-TARGET 1 drop Alexandre CHT 2 drops Pastor-Bernier DELAY 3 drops GO THT Reward: 1 GO 2-TARGET FREE THT CHT Reward: 3 DELAY 67% GO THT 33% FORCED Reward: 1
  • 47. Neural activity in premotor cortex • No effect of value in 1T task • However, if another target is present, then activity increases with value of preferred target • If value of preferred target is constant, activity decreases with value of other target • Activity decreases with distance between targets Pastor-Bernier & Cisek (2011) J. Neurosci.
  • 48. Distance-dependent interactions • More activity when targets are closer • Compare the strength of the competition as a function of target distance – As distance increases, slope is increasingly negative • The competition is strongest between cells with the largest difference in preferred directions
  • 49. Why should it matter that distance matters? • The distance effect suggests that the decision is made within the sensorimotor system – If decisions were purely cognitive (“I prefer to get 3 drops of juice over 1 drop”), then they should be determined in an abstract space – The dynamics of the competition which determines choice depend on the spatial relationship between the movements themselves
  • 50. Predictions • Multiple potential actions can be specified simultaneously • Biased competition between potential actions • Everything occurs in parallel
  • 51. potential actions attention cognitive decision-making predicted behavioral feedback biasing object identity visual feedback motor command
  • 52. Timing potential actions • An animal is constantly interacting with the world attention – Continuous sensorimotor control of ongoing actions cognitive decision-making – Continuous specification of alternative actions – Continuous evaluation of value – Continuous tradeoffs between persisting in a given activity or switching to a different, currently available one predicted behavioral feedback biasing • Specification and selection must normally occur in parallel • However, if we put the animal in the lab – Time is broken into discrete “trials”object of which begins with a each stimulus and ends with a responseidentity – The stimulus is deliberately made independent from the response • What should we see? motor visual feedback command
  • 53. potential actions attention cognitive decision-making predicted behavioral feedback biasing object identity visual feedback motor command
  • 54. potential actions Wave 1. Fast feedforward sweep
  • 55. potential actions attention cognitive decision-making behavioral biasing object identity Wave 2. Attentional/Decisional modulation
  • 56. Two waves of activity Ledberg et al. (2007) Cerebral Cortex • Measured LFPs from various regions of cerebral cortex • Monkeys performed a conditional GO / NOGO task
  • 57. Two waves of activity 1. Fast feedforward sweep • Activation in ~50ms throughout dorsal stream and frontal cortex 2. Attentional/Decisional • About 150ms post- stimulus, discrimination of Go/Nogo throughout the cortex
  • 58. Summary 1: Experimental data • Simultaneous specification of multiple potential actions – Arm reaching system (PMd, PRR, M1) – Grasping system (AIP, PMv) – Saccade system (LIP, FEF, Superior colliculus) • Biased competition – Potential actions compete against each other within sensorimotor maps, influenced by a variety of biasing factors (e.g. reward) – NOTE: Similar mechanism as attention (Duncan & Desimone) • “Attention” is selection near sensors, “decision” is selection near effectors – Influences depend on geometry – decisions are not simply abstract • These are “pragmatic” representations, not “descriptive” – Decision is made through a “distributed consensus” • Parallel specification and selection systems
  • 59. Summary 2: Theoretical concepts • “Affordance competition hypothesis” – Instead of serial Perception, Cognition, & Action modules, we have parallel specification and selection systems – Better match to neural data – Better suited to the kinds of tasks that dominated animal behavior • “Pragmatic representations” – Neural activity aimed not at describing the world, but at mediating interaction with the world – Correlation with external and internal variables is necessary, but mixtures are useful (e.g. spatial direction mixed with reward values) – Conjecture: Most, but not all, neural activity is of this kind • “Descriptive” representations (e.g. in the ventral stream) emerged in evolution as specializations of pragmatic representations for advanced selection • Cognitive advances evolved through hierarchical elaboration – Diversification of fronto-parietal loops, cortico-striatal circuits, cortico- cerebellar circuits, into progressively anterior/abstract systems – Interaction lays the foundation for cognition (Piaget)
  • 60. Summary 3: Philosophical implications • There is no central executive – Decisions emerge through a distributed consensus • Classic problems in a different context – Binding problem: • Activity of separate streams is coherent by virtue of dealing with the same world – Symbol grounding problem: • Interaction has meaning by virtue of influencing the variables critical for life • Symbols are specializations (“shorthand notation”) that emerged late in evolution, already within the context of grounded interaction – The “Hard” problem • Feeling is different than doing – Being inside the loop is different than observing it from the outside – Private language, beetle in box, squirrel in head, 1 st person perspective, the “Umwelt” • The computer metaphor – With all due respect to Alan Turing, the computer metaphor is misleading as a model for the brain – What matters is control (Wiener, Ashby, Powers, Gibson, Dewey, etc.)
  • 61. “The great end of life is not knowledge but action” – T. H. Huxley (1825-1895) “Your head is there to move you around” – R.E.M. (1980-2011)
  • 62. THANK YOU • Lab members – Marie-Claude Labonté – Alexandre Pastor-Bernier – David Thura – Ignasi Cos – Matthew Carland – Jessica Trung • Alumni – Jean-Philippe Thivierge – Thomas Michelet – Valeriya Gritsenko EJLB THE FOUNDATION paul.cisek@gmail.com

Editor's Notes

  • #4: Define Perception, Cognition, Action Cartoon model - reality is much more complex Road from Perception to Cognition is not one-way Sometimes skip Cognition Nevertheless, Behavior is defined as… This architecture is built upon the borders… We see this architecture everywhere: Classification of questions Classification of scientists University curricula Taxonomy of journals Funding agencies Models (AI and NN) Interpretation of neural data (in particular, the borders) Many criticisms have been leveled against it Dependence on brittle internal representations No neural correlates of unified world model or motor plan I ask: Where does this view originate? Who do we cite? This view is not a hypothesis that was proposed and confirmed Instead, it is a framework that ha been inherited… from dualism
  • #5: Define Perception, Cognition, Action Cartoon model - reality is much more complex Road from Perception to Cognition is not one-way Sometimes skip Cognition Nevertheless, Behavior is defined as… This architecture is built upon the borders… We see this architecture everywhere: Classification of questions Classification of scientists University curricula Taxonomy of journals Funding agencies Models (AI and NN) Interpretation of neural data (in particular, the borders) Many criticisms have been leveled against it Dependence on brittle internal representations No neural correlates of unified world model or motor plan I ask: Where does this view originate? Who do we cite? This view is not a hypothesis that was proposed and confirmed Instead, it is a framework that ha been inherited… from dualism
  • #6: Dualism: A philosophical viewpoint that the mind is separate from the body Descendant of the theological distinction between the body and the soul This view dominated philosophy for the vast majority of its existence It forced 17th and 18th Cent philosophers to conceive of two interfaces When psychology was established as a science in the late 19th Cent, it was within this context of a non-physical mind Despite the mind being non-physical, it can be studied scientifically, using introspection Dualism was criticized. Most significant opponent was Behaviorism: No such thing as non-physical mind, not compatible with physics Perception and Action are directly linked The subject matter is linkage and the learning laws which establish it Behaviorism not ultimately satisfactory. Superceded by Cognitivism: There has to be something else between Perception and Action Cognition - takes the place of the mind, but it is physical Cognitivism is made possible by the computer metaphor Thus: The central tenet of dualism has been rejected, but the architecture which it established has been retained (go back to previous slide) But this time, psychologists have become too specialized to reconsider the structure I believe that the reason this architecture is so strongly dominant is because it is traditional, and not because it is supported by data How might we arrive at an architecture which is not encumbered by all this historical baggage?
  • #7: Dualism: A philosophical viewpoint that the mind is separate from the body Descendant of the theological distinction between the body and the soul This view dominated philosophy for the vast majority of its existence It forced 17th and 18th Cent philosophers to conceive of two interfaces When psychology was established as a science in the late 19th Cent, it was within this context of a non-physical mind Despite the mind being non-physical, it can be studied scientifically, using introspection Dualism was criticized. Most significant opponent was Behaviorism: No such thing as non-physical mind, not compatible with physics Perception and Action are directly linked The subject matter is linkage and the learning laws which establish it Behaviorism not ultimately satisfactory. Superceded by Cognitivism: There has to be something else between Perception and Action Cognition - takes the place of the mind, but it is physical Cognitivism is made possible by the computer metaphor Thus: The central tenet of dualism has been rejected, but the architecture which it established has been retained (go back to previous slide) But this time, psychologists have become too specialized to reconsider the structure I believe that the reason this architecture is so strongly dominant is because it is traditional, and not because it is supported by data How might we arrive at an architecture which is not encumbered by all this historical baggage?
  • #8: Dualism: A philosophical viewpoint that the mind is separate from the body Descendant of the theological distinction between the body and the soul This view dominated philosophy for the vast majority of its existence It forced 17th and 18th Cent philosophers to conceive of two interfaces When psychology was established as a science in the late 19th Cent, it was within this context of a non-physical mind Despite the mind being non-physical, it can be studied scientifically, using introspection Dualism was criticized. Most significant opponent was Behaviorism: No such thing as non-physical mind, not compatible with physics Perception and Action are directly linked The subject matter is linkage and the learning laws which establish it Behaviorism not ultimately satisfactory. Superceded by Cognitivism: There has to be something else between Perception and Action Cognition - takes the place of the mind, but it is physical Cognitivism is made possible by the computer metaphor Thus: The central tenet of dualism has been rejected, but the architecture which it established has been retained (go back to previous slide) But this time, psychologists have become too specialized to reconsider the structure I believe that the reason this architecture is so strongly dominant is because it is traditional, and not because it is supported by data How might we arrive at an architecture which is not encumbered by all this historical baggage?
  • #9: Dualism: A philosophical viewpoint that the mind is separate from the body Descendant of the theological distinction between the body and the soul This view dominated philosophy for the vast majority of its existence It forced 17th and 18th Cent philosophers to conceive of two interfaces When psychology was established as a science in the late 19th Cent, it was within this context of a non-physical mind Despite the mind being non-physical, it can be studied scientifically, using introspection Dualism was criticized. Most significant opponent was Behaviorism: No such thing as non-physical mind, not compatible with physics Perception and Action are directly linked The subject matter is linkage and the learning laws which establish it Behaviorism not ultimately satisfactory. Superceded by Cognitivism: There has to be something else between Perception and Action Cognition - takes the place of the mind, but it is physical Cognitivism is made possible by the computer metaphor Thus: The central tenet of dualism has been rejected, but the architecture which it established has been retained (go back to previous slide) But this time, psychologists have become too specialized to reconsider the structure I believe that the reason this architecture is so strongly dominant is because it is traditional, and not because it is supported by data How might we arrive at an architecture which is not encumbered by all this historical baggage?
  • #10: Dualism: A philosophical viewpoint that the mind is separate from the body Descendant of the theological distinction between the body and the soul This view dominated philosophy for the vast majority of its existence It forced 17th and 18th Cent philosophers to conceive of two interfaces When psychology was established as a science in the late 19th Cent, it was within this context of a non-physical mind Despite the mind being non-physical, it can be studied scientifically, using introspection Dualism was criticized. Most significant opponent was Behaviorism: No such thing as non-physical mind, not compatible with physics Perception and Action are directly linked The subject matter is linkage and the learning laws which establish it Behaviorism not ultimately satisfactory. Superceded by Cognitivism: There has to be something else between Perception and Action Cognition - takes the place of the mind, but it is physical Cognitivism is made possible by the computer metaphor Thus: The central tenet of dualism has been rejected, but the architecture which it established has been retained (go back to previous slide) But this time, psychologists have become too specialized to reconsider the structure I believe that the reason this architecture is so strongly dominant is because it is traditional, and not because it is supported by data How might we arrive at an architecture which is not encumbered by all this historical baggage?
  • #11: Define Perception, Cognition, Action Cartoon model - reality is much more complex Road from Perception to Cognition is not one-way Sometimes skip Cognition Nevertheless, Behavior is defined as… This architecture is built upon the borders… We see this architecture everywhere: Classification of questions Classification of scientists University curricula Taxonomy of journals Funding agencies Models (AI and NN) Interpretation of neural data (in particular, the borders) Many criticisms have been leveled against it Dependence on brittle internal representations No neural correlates of unified world model or motor plan I ask: Where does this view originate? Who do we cite? This view is not a hypothesis that was proposed and confirmed Instead, it is a framework that ha been inherited… from dualism
  • #18: Define Perception, Cognition, Action Cartoon model - reality is much more complex Road from Perception to Cognition is not one-way Sometimes skip Cognition Nevertheless, Behavior is defined as… This architecture is built upon the borders… We see this architecture everywhere: Classification of questions Classification of scientists University curricula Taxonomy of journals Funding agencies Models (AI and NN) Interpretation of neural data (in particular, the borders) Many criticisms have been leveled against it Dependence on brittle internal representations No neural correlates of unified world model or motor plan I ask: Where does this view originate? Who do we cite? This view is not a hypothesis that was proposed and confirmed Instead, it is a framework that ha been inherited… from dualism
  • #63: 44:20