Title: Introduction to Cognitive Science
116th International Summer School in Cognitive
Science, New Bulgarian University, Sofia,
Bulgaria, 2009
The Embodiment of Mind as a Natural Result of
Interactive Dynamics
Michael J. Spivey Department of Cognitive
Science University of California, Merced
2Embodied Cognition
COURSE OVERVIEW
Day 1 Embodied cognition is unavoidable in
an organism that allows its subsystems to richly
interact
Day 2 Findings in the Embodied Cognition
literature
Day 3 How classical symbolic cognitive science
would like to interpret embodied cognition
findings
Day 4 Findings of the motor system directly
constraining cognitive processes
Day 5 Computational models that exploit
the embodiment of cognition
3The Continuity of Mind
OUTLINE
The Embodiment of Mind
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
4The Continuity of Mind
OUTLINE
The Embodiment of Mind
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
5Theories of Embodied Mind
Embodiment of Language (e.g., Lakoff
Johnson, 1980, 1999 Sweetser, 1998 Gibbs,
2006 Langacker, 2008 Talmy, 2006) Embodiment
of Cognition (e.g., Barsalou, 1999 MacWhinney,
1999 Glenberg, 1997 Spivey, 2007 Varela,
Thompson, Rosch, 1992) Embodiment of
Perception (e.g., Gibson, 1979 Turvey, 1992
Hommel et al., 2001) Embodiment of Cognitive
Development (e.g., J. Mandler, 1992 L. Smith,
2005) Embodiment of Artificial Intelligence
(e.g., Brooks, 1991 Ballard et al., 1997 Roy,
2005 Steels, 2003)
6Findings of Embodied Mind
Page 1 of 2 Motor areas are active when
hearing action verbs (Pulvermüller, 1999)
Sentences evoke perceptual simulations (Stanfield
Zwaan, 2001) Sentences evoke motor
simulations (Glenberg Kaschak, 2002) Real
and fictive motion priming influences reasoning
about language (Boroditsky Ramscar, 2002
Matlock, Ramscar, Boroditsky, 2005) Image
schemas activated by language interfere with
perceptual input (Richardson, Spivey, Barsalou,
McRae, 2003 Bergen et al., 2007) Summaries
of much of this work can be found in Pecher
Zwaan (2005).
7Findings of Embodied Mind
Page 2 of 2 Sync in postural sway emerges
during mutual conversation (Shockley, Santana,
Fowler, 2003) Sync in eye movements at
shared scene emerges during conversation
(Richardson Dale, 2005) Fictive motion
sentences induce more directional scanning of
scene (Richardson Matlock, 2007) Motion
words influence visual perception of motion, and
vice versa (Meteyard, Bahrami, Vigliocco,
2007 Meteyard et al. 2008) Direction words
heard during a reach cause curvature in the
trajectory (Boulenger et al., 2006 Nazir et
al., 2008)
8The Continuity of Mind
OUTLINE
The Embodiment of Language
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
9Neural Dynamics
(Tyler Spivey, 2005)
10Neural Dynamics
11Neural Dynamics
12Neural Dynamics
13Neural Dynamics
14Neural Dynamics
15Neural Dynamics
16Neural Dynamics
17Neural Dynamics
18Neural Dynamics
19Neural Dynamics
20Neural Dynamics
21Neural Dynamics
Population Code for candy
22Neural Dynamics
Population Code for candle
23Neural Dynamics
0 ms
24Neural Dynamics
100 ms
25Neural Dynamics
200 ms
26Neural Dynamics
300 ms
27Neural Dynamics
400 ms
28Neural Dynamics
Population code for recognizing candy
29Neural Dynamics
Population code for recognizing candle
30Neural Dynamics
0ms
31Neural Dynamics
100ms
32Neural Dynamics
200ms
33Neural Dynamics
300ms
34Neural Dynamics
Population code for recognizing candle
400ms
35Visual Processing
Perrett, Oram, Ashbridge (1998)
600
frontal
Cumulative Response (spikes)
300
3/4 profile
profile
1/4 profile
back-of-head
0
0
500
1000
After Stimulus Onset (ms)
36Visual Processing
Temporal dynamics of population coding (Rolls
Tovee, 1995)
Cumulative Information (bits)
(ms)
If normal eye movements occur 3-4 times per
second, then a population code rarely gets enough
time to asymptote!
37Visual Processing
Multi-dimensional scaling of the 14 cells (Rolls
Tovee, 1995)
38Visual Processing
Trajectories in state space for recognizing faces
and objects
39Visual Processing
Trajectories in state space as a result of
free-viewing of a scene
40Artificial Neural Dynamics
McClelland Elmans (1986) TRACE Model of Speech
Processing
41Artificial Neural Dynamics
TRACE Model of Speech Perception
(McClelland Elman, 1986)
1-sum candle candy pencil penny
Normalized Activation
42Dynamical Systems
Energy Landscape
43Dynamical Systems
Vector Field
44Dynamical Systems
Vector Field
45Dynamical Systems
Vector Field
46Quantitative Equivalence
On the equivalence between dynamic neural
patterns and a trajectory through mental state
space
(Onnis Spivey, submitted)
47The Continuity of Mind
Fodors (1983) modularity of mind has been
giving way to a continuity of mind.
Visual Perception (Motter, 1993 Sekuler,
Sekuler, Lau, 1997 Spivey Spirn, 2000)
Spoken Word Recognition (Elman McClelland,
1988 Allopenna et al., 1998) Sentence
Processing (MacDonald Seidenberg, 1993
Tanenhaus Trueswell, 1995 Chambers,
Tanenhaus, Magnuson, 2004) Conceptual
Integration and Blending (Fauconnier Turner,
2002 Coulson, 2001) Construction Grammar,
eschewing the distinction between core grammar
and periphery (Fillmore, 1988 Goldberg, 2003)
48The Continuity of Mind
OUTLINE
The Embodiment of Language
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
49Dynamics and Eye Movements
Headband-mounted Eyetracking
50Dynamics and Eye Movements
Headband-mounted Eyetracking
51Dynamics and Eye Movements
Why headband-mounted eyetracking?
Eye position provides a continuous measure
without interrupting processing.
Eye movements are largely resistant to
strategic control.
Saccades are frequent 3-4 times per second.
Headband allows ecologically valid continuous
interaction between human and environment
Saccades are promiscuous (low threshold for
execution), and thus sensitive to subtle
probabilistic biases.
52Dynamics and Eye Movements
Vector Field
thresholds for a saccade
53Spoken Word Recognition
Pick up the candle.
(Tanenhaus, Spivey-Knowlton, Eberhard, Sedivy,
1996)
54Spoken Word Recognition
Pick up the candle.
(Tanenhaus, Spivey-Knowlton, Eberhard, Sedivy,
1996)
55Spoken Word Recognition
1.0
.8
.6
Probability of Fixation
.4
.2
0
(ms)
(Spivey-Knowlton, 1996)
56Spoken Word Recognition
McClelland Elmans (1986) TRACE Model of Speech
Processing
57Spoken Word Recognition
TRACE Model of Speech Processing
(Allopenna, Magnuson Tanenhaus, 1998)
58Spoken Word Recognition
Eye-movement data
(Spivey-Knowlton, 1996)
1.0
.8
.6
Probability of Fixation
.4
.2
0
(ms)
59Spoken Word Recognition
Saliency Map
Pick up the
(Reali, Spivey, Tyler, Terranova, 2006)
60Spoken Word Recognition
Saliency Map
Pick up the ca
(Reali, Spivey, Tyler, Terranova, 2006)
61Spoken Word Recognition
Saliency Map
Pick up the cand
(Reali, Spivey, Tyler, Terranova, 2006)
62Spoken Word Recognition
Saliency Map
Pick up the candle.
(Reali, Spivey, Tyler, Terranova, 2006)
63Spoken Word Recognition
Continuous Non-ballistic Movements
(Spivey, Grosjean, Knoblich, 2005)
64Spoken Word Recognition
Mouse-click start box at bottom
(Spivey, Grosjean, Knoblich, 2005)
65Spoken Word Recognition
Click the ladle
(Spivey, Grosjean, Knoblich, 2005)
66Spoken Word Recognition
900
800
700
600
y
500
400
300
200
0
200
400
600
800
1000
x
(Spivey, Grosjean, Knoblich, 2005)
67Spoken Word Recognition
(Spivey, Grosjean, Knoblich, 2005)
68Spoken Word Recognition
Click the beetle
(Spivey, Grosjean, Knoblich, 2005)
69Spoken Word Recognition
(Spivey, Grosjean, Knoblich, 2005)
70Spoken Word Recognition
Graded spatial attraction toward phonological
competitors visible in averaged trajectories
(Spivey, Grosjean, Knoblich, 2005)
71The Continuity of Mind
72The Continuity of Mind
OUTLINE
The Embodiment of Language
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
73Sentence Processing
Incrementality in Syntax
Sentence
Verb Phrase
Syntactic Ambiguity
Verb
Noun Phrase
Prep. Phrase
...
Preposition
Put
the
apple
on...
74Sentence Processing
In a Visual Context
(Tanenhaus, Spivey-Knowlton, Eberhard Sedivy,
1995)
Put the apple on the towel in the box
Ambiguous
Put the apple thats on the towel in the box
Unambiguous
One-Referent Context
Two-Referent Context
75Sentence Processing
One-Referent Context
Tanenhaus, Spivey-Knowlton, Eberhard Sedivy,
1995)
76Sentence Processing
Two-Referent Context
Tanenhaus, Spivey-Knowlton, Eberhard Sedivy,
1995)
77Sentence Processing
In a Visual Context
((Tanenhaus, Spivey-Knowlton, Eberhard Sedivy,
1995)
78Sentence Processing
Continuous Non-ballistic Reaching Movements
79Sentence Processing
Put the apple on the towel in the box
Ambiguous
Put the apple thats on the towel in the box
Unambiguous
Two-Referent Context
One-Referent Context
(Farmer, Anderson, Spivey, 2007)
80Sentence Processing
(Farmer, Anderson, Spivey, 2007)
81Sentence Processing
(Farmer, Anderson, Spivey, 2007)
82Sentence Processing
(Farmer, Anderson, Spivey, 2007)
83Sentence Processing
(Farmer, Anderson, Spivey, 2007)
84Sentence Processing
One-Referent Context, Ambiguous Sentence
(Farmer, Anderson, Spivey, 2007)
85Sentence Processing
(Farmer, Anderson, Spivey, 2007)
86Sentence Processing
(Farmer, Anderson, Spivey, 2007)
87Sentence Processing
(Farmer, Anderson, Spivey, 2007)
88Sentence Processing
(Farmer, Anderson, Spivey, 2007)
89Sentence Processing
(Farmer, Anderson, Spivey, 2007)
90Sentence Processing
(Farmer, Anderson, Spivey, 2007)
91Sentence Processing
(Farmer, Anderson, Spivey, 2007)
92The Continuity of Mind
OUTLINE
The Embodiment of Language
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
93Decision Making
YES
NO
Is a thousand more than a million?
start
(McKinstry, Dale, Spivey, 2008)
94Decision Making
YES
NO
Should you brush your teeth every day?
start
(McKinstry, Dale, Spivey, 2008)
95Decision Making
YES
NO
Is murder sometimes justifiable?
start
(McKinstry, Dale, Spivey, 2008)
96Decision Making
(McKinstry, Dale, Spivey, 2008)
97Decision Making
(McKinstry, Dale, Spivey, 2008)
98Decision Making
(McKinstry, Dale, Spivey, 2008)
99Decision Making
(McKinstry, Dale, Spivey, 2008)
100Continuity Among Mind and Body
OUTLINE
The Embodiment of Language
Temporal Dynamics in Neuronal Population Coding
Temporal Dynamics in Spoken Word Recognition
Temporal Dynamics in Sentence Processing
Temporal Dynamics in Question Answering
Mental Trajectories in Neuronal State Space
101Continuity Among Mind and Body
Toward an equivalence between dynamic neural
patterns and a trajectory through mental state
space
(Onnis Spivey, submitted)
102Continuity Among Mind and Body
103Continuity Among Mind and Body
The new form of insight can perhaps best be
called Undivided Wholenesss in Flowing Movement.
This view implies that flow is, in some sense,
prior to that of the things that can be seen to
form and dissolve in the flow. -David
Bohm, Wholeness and the Implicate Order (1980)
104Slides for questions
105A. Weights over time for alternative reaches
control condition
cohort condition
candy
candy
Relative Activation
candle foil
book foil
(Spivey, Dale, Grosjean, Knoblich, in press)
Time steps
B. Simulated reach movements
control
cohort
reach to foil
reach to target
Y (cm)
X (cm)
106The Continuity of Mind
Quasilinguistic thought while learning racquetball
107Visual Processing
Multi-dimensional scaling of the 14 cells (Rolls
Tovee, 1995)
108Visual Processing
Temporal dynamics of population coding (Rolls
Tovee, 1995)
109Visual Processing
Trajectories in state space for recognizing faces
and objects
110Visual Processing
Trajectories in state space as a result of
free-viewing of a scene
111The Continuity of Mind
Symbolic Dynamics