computational models of cognitive control (i)

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Computational models of cognitive control (I) Matthew Botvinick Princeton Neuroscience Institute and Department of Psychology, Princeton University

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Computational models of cognitive control (I). Matthew Botvinick Princeton Neuroscience Institute and Department of Psychology, Princeton University. Atkinson & Shiffrin, 1968. Atkinson & Shiffrin, 1968. Structural elements. Atkinson & Shiffrin, 1968. Structural elements. Control elements. - PowerPoint PPT Presentation

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Page 1: Computational models of cognitive control (I)

Computational models of cognitive control (I)

Matthew BotvinickPrinceton Neuroscience Institute andDepartment of Psychology, Princeton University

Page 2: Computational models of cognitive control (I)

Atkinson & Shiffrin, 1968

Page 3: Computational models of cognitive control (I)

Atkinson & Shiffrin, 1968

Structural elements

Short-term store

Sensory register

Long-term store

Page 4: Computational models of cognitive control (I)

Atkinson & Shiffrin, 1968

Structural elements

Short-term store

Sensory register

Long-term store

Control elements

Search / RetrievalTransfer to/from STS

Which register?Forward into sts?

SearchRehearsal

Page 5: Computational models of cognitive control (I)

Baddeley, 1986/2007

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Baddeley, 1986/2007

“Slave systems”

Page 7: Computational models of cognitive control (I)

Shiffrin & Schneider, 1977

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Norman & Shallice, 1986

Contention scheduling system

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Norman & Shallice, 1986

Supervisory attentional system (SAS)

Contention scheduling system

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GREEN

Page 11: Computational models of cognitive control (I)

< < < > < < <

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-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

“Executive/Cognitive Control”

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AR

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-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

“Executive/Cognitive Control”

Page 18: Computational models of cognitive control (I)
Page 19: Computational models of cognitive control (I)

-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

“Executive/Cognitive Control”

Page 20: Computational models of cognitive control (I)
Page 21: Computational models of cognitive control (I)

-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

“Executive/Cognitive Control”

Page 22: Computational models of cognitive control (I)
Page 23: Computational models of cognitive control (I)

-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

“Executive/Cognitive Control”

Page 24: Computational models of cognitive control (I)
Page 25: Computational models of cognitive control (I)

-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

“Executive/Cognitive Control”

Page 26: Computational models of cognitive control (I)

-- Controlled (task-guided) attention: “attention for action” (Stroop)

-- Ignoring or inhibiting task-irrelevant stims/responses (Go/No-Go)

-- Manipulating information in working memory (N-Back)

-- Switching between tasks (Wisconsin Card Sort)

-- Planning / scheduling (Tower of London)

-- Navigating through extended, hierarchically structured tasks

GETTING WITH (AND STAYING WITH) THE PROGRAM

“Executive/Cognitive Control”

Page 27: Computational models of cognitive control (I)

GETTING WITH (AND STAYING WITH) THE PROGRAM

Encoding / Formulation Maintenance Projection Updating

Task Context

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GREEN

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Cohen, McClelland & Dunbar, 1990

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< < < > < < <

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Cohen, Servan-Schreiber & McClelland, AJP, 1992.

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Page 41: Computational models of cognitive control (I)

Cohen, Servan-Schreiber & McClelland, AJP, 1992.

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White & Wise, Exp Br Res, 1999

(See also: Assad, Rainer & Miller, 2000; Bunge, 2004; Hoshi, Shima & Tanji, 1998; Johnston & Everling, 2006; Wallis, Anderson & Miller, 2001; White, 1999…)

Page 46: Computational models of cognitive control (I)

From Curtis & D’Esposito, TICS, 2003, after Funahashi et al., J. Neurophysiol,1989.

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Questions…

-- What about manipulation in WM, etc? -- dynamics (switching, sequences)-- what controls control? (Homunculus)

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Intermission

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“A controlled process is a temporary sequenceof nodes activated under control of, andthrough attention by, the subject. Becauseactive attention by the subject is required,only one such sequence at a time may becontrolled without interference.”

Shiffrin & Schneider, 1977

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Ridderinkhof et al., Science, 2004 (Based on Picard & Strick, Curr. Op. Biol., 2001)

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Response override

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Response override Underdetermined responding

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Response override Underdetermined responding

Error commission

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Response override Underdetermined responding

Error commission

Conflict

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GREEN

GREEN

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< < < > < < <

> > > > > > >

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Botvinick, et al. (1999) Nature.

< < < > < < <

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QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Thompson-Schill et al., PNAS, 1997

High constraint: APPLE

Low constraint: BALL

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Carter, Braver, Barch, Botvinick, Noll & Cohen, Science, 1998

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Barch, et al. Cerebral Cortex, 2001 / Botvinick, Carter & Cohen, TICS, 2004

Ridderinkhoff et al., Science, 2004

Page 66: Computational models of cognitive control (I)

Botvinick, et al. (2001) Psychological Review.

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Botvinick, et al. (2001) Psychological Review.

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Botvinick, et al. (2001) Psychological Review.

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Carter, Braver, Barch, Botvinick, Noll & Cohen, Science, 1998

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Gratton et al., JEPG, 1992

Low controlHigh conflict

High controlLow conflict

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Botvinick, et al. (1999) Nature.

Low controlHigh conflict

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Tzelgov, et al. (1992) Memory & Cognition.

High controlLow conflict

Low controlHigh conflict

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Carter, MacDonald, Botvinick et al. (2000) PNAS.

Low controlHigh conflict

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Barch, Braver, Sabb & Noll, JCN, 2000

Underdeterminedresponding

ResponseOverride

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Yeung, Botvinick & Cohen, Psychological Review, 2004

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Stuphorn, Taylor & Schall, Nature, 2000

Ito et al., Science, 2000ACC

SEF

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Nakamura, Roesch & Olson, J. Neurophys. 2005

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Curtis et al., Cereb. Ctx., 2005

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Davis et al., J. Neurosci. 2005

Neutral Incongruent

44%

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WHY?

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Control

Conflict

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Gratton et al., JEPG, 1992

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Botvinick, et al. (2001) Psychological Review.

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Botvinick, et al. (2001) Psychological Review.

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Tzelgov, et al. (1992) Memory & Cognition.

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Botvinick, et al. (2001) Psychological Review.

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Botvinick, et al. (2001) Psychological Review.

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Mayr, Awh & Laurey, Nature Neuroscience, 2003

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Mayr, Awh & Laurey, Nature Neuroscience, 2003

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Ullsperger & Botvinick, PB&R, 2005 Kerns, et al. (2004) Science.

See also:Freitas, Bahar, Yang, and Banai, Psychological Science, 2007  Notebaert, Gevers, Verbruggen, & Liefooghe, Psychonomic Bulletin & Review, 2006  

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Freitas, Bahar, Yang, and Banai, Psychological Science, 2007 

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Kerns, et al. (2004) Science.

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DiPellegrino, Ciaramelli & Ladavas, J. Cog. Neuro., 2007

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Monitoring of action outcomes -- especially outcomes considered aversive or signaling reduction in reward

Gehring & Willoughby, Science, 2002Luu et al., Psychol. Sci., 2004 Niewenhuis et al., Cerebral Cortex, 2004Bush et al., PNAS, 2002Holroyd & Coles, Psychol. Rev., 2002

Use of outcome information to guide action selection

Matsumoto, et al. Science, 2003Bush, et al., PNAS, 2002Holroyd & Coles, Psychol. Rev. 2002Hadland, et al., J. Neurophysiol., 2003Kennerley, et al., Nature Neurosci., 2006

Action selection based on cost-benefit analysis

Rushworth, et al., TICS, 2004

Cost-benefit analysis might take effort into account

Walton, et al., J. Neurosci., 2003

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Johansen & Fields, Nature Neuroscience, 2004

Glu antagonist Glu agonist(kynurenic acid) (homocysteic acid)

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Jackson, Frost & Moghaddam, J. Neurochem., 2001

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Toward an integrative account

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Conflict is an outcome of action / strategy selection

Toward an integrative account

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Conflict is an outcome of action / strategy selection

Conflict is aversive (registers as a cost)

Toward an integrative account

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Conflict is an outcome of action / strategy selection

Conflict is aversive (registers as a cost)

Conflict informs subsequent decision making

Toward an integrative account

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Conflict is an outcome of action / strategy selection

Conflict is aversive (registers as a cost)

Conflict avoidance

Conflict informs subsequent decision making

Toward an integrative account

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task cue

strategy

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stimulus task cue

strategyresponse

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stimulus task cue

strategyresponse

conflict

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stimulus task cue

strategyresponse

conflict

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Law of least mental effort:

All else being equal, actions will be chosen so as to minimize the demand for cognitive control (indexed by processing conflict).

Law of least effort (Hull): All else being equal, actions will be chosen so as to minimize the amount of work performed.

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Macleod, Hunt & Mathews, Journal of Verbal Learning and Verbal Behavior, 1978

STAR ABOVE CROSS

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“One basis for strategy selection: minimization of cognitive workload.”

-- Reichle, Carpenter & Just, Cog. Psychol., 2003.

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4

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3

90% switch 10% switch

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Botvinick, CABN, 2007

Card

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Card

Botvinick, CABN, 2007

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Card

Botvinick, CABN, 2007

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Card

Botvinick, CABN, 2007

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Anticipatory skin conductance responses

Bechara, Damasio, Damasio, & Lee, Journal of Neuroscience, 1999.

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0

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Performance Decision

SCR (area)

High demand

Low demand

Botvinick & Rosen, Psych Res, in press

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Botvinick & Rosen, Psych Res, in press

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Performance Decision

SCR (area)

High demand

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Botvinick & Rosen, Psych Res, in press

SCR ACC (Nagai, Critchley, Featherstone, Trimble, & Dolan, 2004)

ACC damage loss of effort- and IGT-related SCR (Naccache et al., 2005))

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8

9

3

Deciding your pay…

X

6

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Deciding your pay…

$

2000 ms

2000 ms

2000-8000 ms

2000 ms

2000-8000 ms

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Deciding your pay…

X

6

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Deciding your pay…

$

2000 ms

2000 ms

2000-8000 ms

2000 ms

2000-8000 ms

X $

Botvinick, Huffstetler & McGuire, in press

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Botvinick, Huffstetler & McGuire, in press

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Conclusions

Conflict can be viewed as an index of the demand for control

The occurrence of conflict appears to be detected in the brain

Conflict detection appears to impact cognitive control

Conflict may also register as a cost

Tasks / strategies may be chosen so as to minimize conflict

Page 136: Computational models of cognitive control (I)

Where does this put us?

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Where does this put us?

Chipping away at the homunculus

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Where does this put us?

Chipping away at the homunculus

But this is just about modulating task representations

Page 139: Computational models of cognitive control (I)

Where does this put us?

Chipping away at the homunculus

But this is just about modulating task representations

How are task representations selected in the first place?

Page 140: Computational models of cognitive control (I)

Where does this put us?

Chipping away at the homunculus

But this is just about modulating task representations

How are task representations selected in the first place?

How are they sequenced?

Page 141: Computational models of cognitive control (I)

Where does this put us?

Chipping away at the homunculus

But this is just about modulating task representations

How are task representations selected in the first place?

How are they sequenced?

Dynamics (decision-making) and Learning