Neural circuits for bias and sensitivity in decision-making Jan Lauwereyns Associate Professor, Victoria University of Wellington, New Zealand Long-term Invitation Fellow, Japanese Society for the Promotion of Science Visiting Scholar, Tamagawa University, Tokyo, Japan
The Perfect Grandpa
Biological needs The drive reduction hypothesis Think: Inclusive fitness Think: energy, reproduction Approach Avoid
Biological needs The drive reduction hypothesis Several hours have passed since last meal
Biological needs The drive reduction hypothesis Several hours have passed since last meal Increased drive (hunger) Increased exploratory activity
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
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
Dopamine reward prediction (Schultz)
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
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”
Distinguishing effects of sensitivity and bias Signal detection theory (Green & Swets) Probability of response LATER model (Carpenter) Latency of response
Signal detection theory
Signal Noise Neuronal activity Noise Signal +
A different way to think about bias and sensitivity…
Scheme of the original LATER model (RHS Carpenter)
Nose Poke Paradigm: Spatial choice, Gives us good reaction-time distributions
Target side: 4 LEDs vs. Distracter side: 0-3 LEDs
Lauwereyns & Wisnewski (2006, JEP:ABP)
Theoretical example of bias
Theoretical example of sensitivity
How does it really work?
How does the brain incorporate reward value in the control of action?
Studied in monkeys using saccadic eye movement tasks with asymmetrical reward schedule
Biased Saccade Task (BST)
Target position = unpredictable
Biased Saccade Task (BST) Reward association = known
Biased Saccade Task (BST)
No escape!
Asymmetric position-reward mapping in “ABA” design Frequent reversal of blocks
Strong effect of reward value on saccade latency Range of 50 to 200 ms, faster on reward trials
Saccade-related brain areas (macaque monkey) FEF: frontal eye field SEF: supplementary eye field LIP: area LIP of parietal cortex CD: caudate nucleus SNr: substantia nigra pars reticulata SC: superior colliculus Clbm: cerebellum SG: brainstem saccade generators
Inputs to Striatal Medium Spiny Neuron Smith & Bolam (1990)
Medium Spiny Neuron in Striatum Preston, Bishop & Kitai (1980)
Single unit recording from Caudate Nucleus
L-CD neuron: All Reward
L-CD neuron: All Reward
Population activity of CD neurons (with contra-bias, n=25) Lauwereyns et al. (2002, Nature)
Weak correlation Strong correlation
General increase
Reward leads to general increase of neural activity = bias effect; no change in d’ Lauwereyns et al. (2002, Neuron) Data from CD
General increase: Prospective, additive Bias in anticipatory activity Linearly enhances sensory activity
General increase: Prospective, additive Bias in anticipatory activity Linearly enhances sensory activity Response = Input + Reward Bias Prefrontal cortex, basal ganglia Superior colliculus
Is it all bias? Or can we find examples of sensitivity?
Improved discrimination
Reward leads to improved discrimination of neural activity = change in d’, no bias effect Kobayashi et al. (2002, J. Neurophysiol.) Data from DLPFC
Improved discrimination: Synergistic, multiplicative Sensory properties Non-linearly enhanced by reward
Improved discrimination: Synergistic, multiplicative Sensory properties Non-linearly enhanced by reward Response = Input * Reward Gain Prefrontal cortex, parietal cortex Superior colliculus
Never the twain shall meet?
Improved discrimination & General increase
Combination of both mechanisms Seen in all areas Loops between FC, BG and SC But most common in Superior Colliculus
Combination of both mechanisms Seen in all areas Loops between FC, BG and SC But most common in Superior Colliculus
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
Dopamine
Excitation
Dopamine Excitation Disinhibition
Synergistic, multiplicative Dopamine Excitation Disinhibition Sensitivity
Prospective, additive Synergistic, multiplicative Dopamine Excitation Disinhibition Sensitivity Bias
Prospective, additive Synergistic, multiplicative Dopamine Excitation Disinhibition Sensitivity Bias Thalamus Back to LPFC, On to posterior cortices, Back to CD
… … Only prefrontal cortex? Evolution of the dopamine system: toward innervation of more and more cortex Nieoullon, 2002
Effects of methamphetamine (METH) (speed)
Prospective, additive Synergistic, multiplicative Dopamine Excitation Disinhibition D1 > D2 D2 > D1 Thalamus Back to LPFC, On to posterior cortices, Back to CD