F. Gregory Ashby - Home | IMBS | UCI Social Sciences
Transcript of F. Gregory Ashby - Home | IMBS | UCI Social Sciences
F. Gregory Ashby
1
F. Gregory AshbyLaboratory for Computational Cognitive Neuroscience
University of California, Santa Barbara
Ori
enta
tion
A B
Except with many exemplars per category
Bar Width
Ori
enta
tion
Categorization rule is easy to describe
Bar Width
Ori
enta
tion
A B
A
Effective learning requires:
• no distractions
• active and effortful processing of feedback
But the nature and timing of feedback is not critical
Bar Width
A
B
Does this mammogram show a tumor?
i.e., is it in the category “tumor” or the category
“nontumor”?
Tumor!
Categorization rule is difficult to describe
Bar Width
Ori
enta
tion
A
B
Effective learning requires:
• consistent feedback immediately after response
• consistent mapping from category to response location
• no active feedback processing
Rule-Based Information-Integration
Rule Based Information Integration
Bar Width Bar Width
Is the information-integration task inherently more difficult?
Bar WidthBar Width
• explicit, logical-reasoning system
-- quickly learns explicit rules
(Ashby, Alfonso-Reese, Turken, & Waldron, Psychological Review, 1998)
• procedural- or habit-learning system
-- slowly learns similarity-based rules
• simultaneously active in all tasks (at least initially)
Romo, Merchant et al.
Low Speed Cell High Speed Cell
Merchant et al. (1997, J. of Neurophysiology)
• logical reasoning system
• uses working memory and executive attention
• prefrontal cortex, anterior cingulate, head of the caudate nucleus, thalamo-cortical loops, medial temporal lobe structures temporal lobe structures
• Working memory & attentional switching component – FROST (Ashby, Ell, Valentin, & Casale, 2005, J. of Cognitive Neuroscience)
15
ACC = Anterior CingulatePFC = Lateral Prefrontal CortexMDN = Medial Dorsal Nucleus of the ThalamusGP = Globus PallidusCD = Head of the Caudate NucleusVTA = Ventral Tegmental AreaSN = Substantia Nigra pars compactaHC = Hippocampus
Excitatory projection
Inhibitory projection
Dopamine projection
The Striatal Pattern Classifier (Ashby & Waldron, 1999)
PremotorPremotorPremotorPremotor
AreasAreasAreasAreasVisualVisualVisualVisual
AreasAreasAreasAreas
• Information-integration category learning should
be sensitive to feedback delay
• Rule-based category learning should not be• Rule-based category learning should not be
sensitive to feedback delay
Maddox, Ashby, & Bohil (2003, JEP:LM&C)
Maddox, Ashby, & Bohil (2003, JEP:LM&C)
• Results identical with 2.5 and 10 sec delays
• RB results replicated at 4 increased levels of difficulty difficulty
• Replication with a rule-based task that uses a conjunction rule?
Rule-Based Information-IntegrationDimensional-4 (Dim4) Non-Dimensional-4 (Non-Dim4)
(Note: Rule-based discriminability higher)
Frequency
Ori
enta
tion
Frequency
Ori
enta
tion
Maddox & Ing (2005, JEP:LM&C)
0.60
0.80
1.00
Pro
port
ion
Cor
rect
Delay
*
0.20
0.40
0.60
Dim4 Non-Dim4
Pro
port
ion
Cor
rect
Imm
Rule-Based Information-Integration
Maddox & Ing (2005, JEP:LM&C)
Feedback delay interferes with
information-integration category learning, information-integration category learning,
but not with rule-based category learning.
• Rule-based category learning requires active
processing of feedback signal
• Feedback processing is automatic in• Feedback processing is automatic in
information-integration category learning
ITI 2000 msec
7 (Y-N resp) Response
Terminated
Delay
500 msec
1000 msec
2500 msec
ITI 2000 msec
Delay
7 (Y-N resp) Response
Terminated
Delay
2 4 9 1
1000 msec
Time
2 4 9 1
2 4 9 1
Correct or
Error
Response Terminated
500 msec
500 msec 2500 msec Delay
Correct or
Error
Response Terminated
500 msec
Cat – Mem Scan – Delay (Interference)
Cat – Delay – Mem Scan (Control)
Maddox, Ashby, Ing, & Pickering (2004, Memory & Cognition)
Rule-Based Information-Integration
Ori
enta
tion
Ori
enta
tion
FrequencyO
rien
tati
onFrequency
Ori
enta
tion
Maddox, Ashby, Ing, & Pickering (2004, Memory & Cognition)
0.70
0.80
0.90
1.00
Short
0.40
0.50
0.60
0.70
Dim Non-Dim
Category Structure
Long
Control*
Rule-Based Information-Integration
Maddox, Ashby, Ing, & Pickering (2004, Memory & Cognition)
Asaad, Rainer, & Miller, 2000; Hoshi, Shima, & Tanji, 1998; Merchant, Zainos, Hernadez, Salinas, & Romo, 1997; Romo, Merchant, Ruiz, Crespo, & Zainos, 1995; White & Wise, 1999
Single-cell recording studies
Animal lesion experiments Eacott& Gaffan, 1991; Gaffan& Eacott, 1995; Gaffan& Harrison, 1987; Eacott& Gaffan, 1991; Gaffan& Eacott, 1995; Gaffan& Harrison, 1987; McDonald & White, 1993, 1994; Packard, Hirsch, & White, 1989; Packard & McGaugh, 1992; Roberts & Wallis, 2000
Neuropsychological patient studiesAshby, Noble, Filoteo, Waldron, & Ell, 2003; Brown & Marsden, 1988; Cools et al., 1984; Downes et al., 1989; Filoteo, Maddox, & Davis, 2001a, 2001b; Filoteo, Maddox, Ing, Zizak, & Song, in press; Filoteo, Maddox, Salmon, & Song, 2005; Janowsky, Shimamura, Kritchevsky, & Squire, 1989; Knowlton, Mangels, & Squire, 1996; Leng & Parkin, 1988; Snowden et al., 2001
Konishi et al., 1999; Lombardi et al., 1999; Nomura et al., in press; Poldrack, et al., 2001; Rao et al., 1997; Rogers, Andrews, Grasby, Brooks, & Robbins, 2000; Seger & Cincotta, 2002; Volz et al., 1997
Neuroimaging experiments
Traditional cognitive behavioral experiments Ashby & Ell, 2002; Ashby, Ell, & Waldron, 2003; Ashby, Maddox, & Bohil, Ashby & Ell, 2002; Ashby, Ell, & Waldron, 2003; Ashby, Maddox, & Bohil, 2002; Ashby, Queller, & Berretty, 1999; Ashby, Waldron, Lee, & Berkman, 2001; Maddox, Ashby, & Bohil, 2003; Maddox, Ashby, Ing, & Pickering, 2004; Maddox, Bohil, & Ing, in press; Waldron & Ashby, 2001; Zeithamova& Maddox, in press
"As I write, my mind is not preoccupied with how my fingers form the letters; my attention is fixed simply on the thought the words express. But there was a time when the formation of the letters, as each was a time when the formation of the letters, as each one was written, would have occupied my whole attention.”
Sir Charles Sherrington (1906)
“It has been widely held that although memory traces are at first formed in the cerebral cortex, they are finally reduced or transferred by long practice to subcortical levels” (p. 466)
Karl Lashley (1950) In search of the engram.Karl Lashley (1950) In search of the engram.
“Routine, automatic, or overlearned behavioral sequences, however complex, do not engage the PFC and may be entirely organized in subcortical structures” (p. 323)
Joaquin Fuster (2001). The prefrontal cortex – an update.
Category
Learning
Categorization
Expertise
Patients with Basal Ganglia Dysfunction
Impaired Unimpaired(Parkinson’s disease,
Huntington’s disease)
Impaired Unimpaired
Patients with certain visual cortex lesions
(category-specific agnosia)
Unimpaired if stimuli are perceived normally?
Impaired
A
A
B
A
Excitatory projection (glutamate)
Inhibitory projection (GABA)
Dopamine projection
Ashby, Ennis, & Spiering (2007, Psych Review)
[ ] [ ] ( )[ ],)(1)()()()(1)()()(
, tStStStStStStInwdt
tdSJJSbaseJSMSJ
KKJK
J −+−−−−
= ∑ εσγβ
Activation in striatal unit J at time t, denoted SJ(t) equals
where IK(t) is the input from visual cortical unit K at time t, and wK,iJ(n) is the strength of the synapse between cortical unit K and spine i on medium spiny cell J, and ,(t) is white noise.
dt K
Globus Pallidus: [ ]baseJGJJGJ GtGtGtS
dt
tdG −−−= )()()()( βα
Thalamus: ),()()()(
tTtTtGtdTJ βα −−=Thalamus: ),()()()(
tTtTtGdt
tdTJTJJT
J βα −−=
[ ] [ ] [ ],)(1)()()()()(1)()()()(
, tEtEtEtEtEtEtInvtTdt
tdEJJEbaseJEKEJK
KJKJE
J −+−−−−
+= ∑ εσγβα
Premotor Area:
Excitatory projection (glutamate)
Inhibitory projection (GABA)
Dopamine projection
3-factor learning
Hebbian learning
learning
vK,J(n) = strength of synapse between visual cortical cell K and premotor cell J on trial n
[ ] [ ]−−+=+ +θα
LTP
presynaptic activation
postsynaptic activation (above NMDA threshold)
[ ] [ ])(1)()()()1( ,,, nvtEtInvnv JKNMDAJkvJKJK −−+=+ +θα
[ ] )()()( , tvtEtI JKJNMDAkv+−− θβ
LTD postsynaptic activation (below NMDA threshold)
CorticalCortical--StriatalStriatal Learning Learning (3 factor)(3 factor)
[ ] [ ] [ ])(1)()()( nwDnDtrtS ++ −−−+ θα
)()1( ,, nwnw iJKiJK =+
LTP activation above NMDA threshold
dopamine above baseline (Correct Response)
[ ] [ ] [ ][ ] [ ]
[ ] ),()(
)()()()(
)(1)()()(
,,
,,
,,
nwtr
nwnDDtrtS
nwDnDtrtS
iJKiJKNMDAw
iJKbaseNMDAiJKJw
iJKbaseNMDAiJKJw
+
++
++
−−
−−−
−−−+
θγ
θβ
θα
LTD
activation below NMDA threshold activation above
NMDA threshold
dopamine below baseline (error)
Obtained Reward – Predicted Reward
Increases with:
where obtained reward on trial n + 1 equals
1 if correct feedback is received
1
1 if correct feedback is received
0 if no feedback is received
1 if error feedback is received nR +
= −
and
Bayer & Glimcher (2005, Neuron) Dopamine Release in SPEED
Obtained Reward – Predicted Reward
0.6
0.8
1
Do
pam
ine
0
0.2
0.4
1 101 201 301 401 501 601
Trial
Do
pam
ine
Romo, Merchant et al.
0.5
1P
rop
ort
ion
of
Lo
w R
esp
on
ses
Low High
Monkeys
SPEED
0
0.5
12 14 16 18 20 22 24 26 28 30
Cycles per Second
Pro
po
rtio
n o
f L
ow
Res
po
nse
s
Low High
Speed (mm/s)
Low Speed Cell High Speed Cell
Merchant et al. (1997)
Low Speed Cells High Speed Cells
Romo et al., 1997
Lever press to tone
70 trials/day
(1997, J. of Neuroscience)(1997, J. of Neuroscience)
Striatal Response
70 trials/day
18 days
Carelli et al. (1997, Journal of Neuroscience)
Carelli et al.
A
A
A
BB
rig
htn
ess
Munsell Color Patches – 3 Subjects – 1800 Trials
A
A
AB
B
B
B B
Bri
gh
tnes
s
Saturation
Model Performance
80
90
100P
erce
nt
Co
rrec
t
50
60
70
5 20 35 50 65 80 95 110
125
140
Block (N)
Per
cen
t C
orr
ect
Participant 1
1600
1800
2000
Mea
n R
espo
nse
Tim
e
SPEEDNosofsky & Palmeri (1997)
800
1000
1200
1400
1600
5 20 35 50 65 80 95110 125 140
Block (N)
Mea
n R
espo
nse
Tim
e
•fMRI
• Model automaticity development in:
-- neuropsychological populations -- neuropsychological populations
-- subjects under influence of drugs
• Automaticity in rule-based tasks
• Two category learning systems
• Explicit, logical reasoning system
-- Uses working memory & executive attention
-- Frontal cortex
• Procedural learning system-- Striatum
• Learning systems train long-term cortical representations
Collaborators:Learning
Leola Alfonso-Reese, Michael Beran, Robert Cook, Shawn Ell, Vince Filoteo, Todd Maddox, Alan
Pickering, David Smith, And Turken, Elliott Waldron, many others
AutomaticityJohn Ennis, Brian Spiering
Funding:Public Health Services Grant MH3760-2