neural circuits for bias and sensitivity in decision-making jan lauwereyns associate professor,...
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Neural circuits for bias and sensitivity in decision-making
Jan LauwereynsAssociate Professor, Victoria University of Wellington, New Zealand
Long-term Invitation Fellow, Japanese Society for the Promotion of Science
Visiting Scholar, Tamagawa University, Tokyo, Japan
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The Perfect Grandpa
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The Perfect Grandpa
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Biological needs
The drive reduction hypothesis
Think: Inclusive fitness
Think: energy, reproduction
Approach
Avoid
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Biological needs
The drive reduction hypothesis
Several hours have passed since last meal
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Biological needs
The drive reduction hypothesis
Several hours have passed since last meal
Increased drive (hunger)
Increased exploratory activity
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Biological needs
Several hours have passed since last meal
Increased drive (hunger)
Increased exploratory activity
Find food, eat it
Drive is reduced (reinforcement)
The drive reduction hypothesis
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Biological needs
Several hours have passed since last meal
Find food, eat it
Drive is reduced (reinforcement)
The drive reduction hypothesis
Increased drive (hunger)
Increased exploratory activity
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Dopamine reward prediction(Schultz)
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Executive control
• Goals, beliefs, wishes, fears…
• Related to motivational control
• Some sensory information is valuable to the individual in the sense that it may be used in the strategic (“optimal”) control of behavior
• Executive control would seek to maximize the extraction of valuable sensory information
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How can executive control affect information processing?
Two general hypotheses:
• Sensitivity
– Selective improvement of
information processing
(actual perception)
• Bias:
– Selective preparation (“anticipation”)
of information processing
(virtual perception)
For example: “Reward”
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Distinguishing effects of sensitivity and bias
Signal detection theory (Green & Swets)
Probability of response
LATER model (Carpenter)
Latency of response
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Signal detection theory
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SignalNoise
Neuronal activity
Noise
Noise
Signal +
Signal +
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A different way to think about bias and sensitivity…
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Scheme of the original LATER model (RHS Carpenter)
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Nose Poke Paradigm:
Spatial choice, Gives us good reaction-time distributions
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Target side: 4 LEDsvs. Distracter side: 0-3 LEDs
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Lauwereyns & Wisnewski (2006, JEP:ABP)
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Lauwereyns & Wisnewski (2006, JEP:ABP)
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Theoretical example of bias
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Theoretical example of sensitivity
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How does it really work?
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• How does the brain incorporate reward value in the control of action?
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• How does the brain incorporate reward value in the control of action?
• Studied in monkeys using saccadic eye movement tasks
with asymmetrical reward schedule
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Biased Saccade Task (BST)
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Biased Saccade Task (BST)
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Biased Saccade Task (BST)
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Biased Saccade Task (BST)
Target position =
unpredictable
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Biased Saccade Task (BST)
Reward association = known
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Biased Saccade Task (BST)
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Biased Saccade Task (BST)
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Biased Saccade Task (BST)
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Biased Saccade Task (BST)
No escape!
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Asymmetric position-reward mapping in “ABA” design
• Frequent reversal of blocks
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Strong effect of reward value on saccade latency
• Range of 50 to 200 ms, faster on reward trials
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Saccade-related brain areas (macaque monkey)
FEF: frontal eye fieldSEF: supplementary eye fieldLIP: area LIP of parietal cortexCD: caudate nucleusSNr: substantia nigra pars reticulataSC: superior colliculusClbm: cerebellumSG: brainstem saccade generators
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Inputs to Striatal Medium Spiny Neuron
Smith & Bolam (1990)
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Medium Spiny Neuron in Striatum
Preston, Bishop & Kitai (1980)
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Single unit recording from Caudate Nucleus
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L-CD neuron: AllReward
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L-CD neuron: AllReward
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Population activity of CD neurons(with contra-bias, n=25)
Lauwereyns et al. (2002, Nature)
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Weakcorrelation
Strongcorrelation
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General increase
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Reward leads to general increase of neural activity = bias effect; no change in d’
Lauwereyns et al. (2002, Neuron)
Data from CD
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General increase:Prospective, additive
• Bias in anticipatory activity
• Linearly enhances sensory activity
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General increase:Prospective, additive
• Bias in anticipatory activity
• Linearly enhances sensory activity
Response = Input + Reward Bias
Prefrontal cortex, basal ganglia
Superior colliculus
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Is it all bias?
Or can we find examples of sensitivity?
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Improved discrimination
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Reward leads to improved discrimination of neural activity = change in d’, no bias effect
Kobayashi et al. (2002, J. Neurophysiol.)
Data from DLPFC
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Improved discrimination:Synergistic, multiplicative
• Sensory properties
• Non-linearly enhanced by reward
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Improved discrimination:Synergistic, multiplicative
• Sensory properties
• Non-linearly enhanced by reward
Response = Input * Reward Gain
Prefrontal cortex, parietal cortex
Superior colliculus
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Never the twain shall meet?
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Improved discrimination & General increase
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Combination of both mechanisms
• Seen in all areas• Loops between FC, BG and SC• But most common in Superior Colliculus
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0
2
4
6
8
10
12
Cue RF Cue nonRF
Neu
ron
al A
ctiv
ity
No reward
Reward
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Combination of both mechanisms
• Seen in all areas• Loops between FC, BG and SC• But most common in Superior Colliculus
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Combination of both mechanisms
• Seen in all areas• Loops between FC, BG and SC• But most common in Superior Colliculus
Response = (Input * Reward Gain) + Reward Bias
On toward the oculomotor plant
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Dopamine
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Dopamine
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DopamineExcitation
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DopamineExcitation
Disinhibition
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Synergistic,multiplicative
DopamineExcitation
DisinhibitionSensitivity
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Prospective, additive
Synergistic,multiplicative
DopamineExcitation
DisinhibitionSensitivity
Bias
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Prospective, additive
Synergistic,multiplicative
DopamineExcitation
DisinhibitionSensitivity
Bias
Thalamus
Back to LPFC,On to posterior cortices,Back to CD
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…
…
Only prefrontal cortex?Evolution of the dopamine system: toward innervation of more and more cortex
Nieoullon, 2002
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Effects of methamphetamine(METH) (speed)
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Prospective, additive
Synergistic,multiplicative
DopamineExcitation
DisinhibitionD1 > D2
D2 > D1
Thalamus
Back to LPFC,On to posterior cortices,Back to CD