introduction by elisabeth rounis and louise whiteley
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Symposium: Decision-making in health and disease - Part 2 Given at Gresham College on 28th May 2009. Introduction By Elisabeth Rounis and Louise Whiteley. What affects a decision?. OR. ?. What affects a decision?. OR. ?. What affects a decision?. You have:. What would you rather…. OR. - PowerPoint PPT PresentationTRANSCRIPT
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Symposium: Decision-making in health and disease - Part 2
Given at Gresham College on 28th May 2009
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Introduction By Elisabeth Rounis and Louise Whiteley
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What affects a decision?
OR ?
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What affects a decision?
OR ?
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What affects a decision?
You have:
What would you rather…
OR ?
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What affects a decision?
OR
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What affects a decision?
OR
Healthy? Or not?
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What affects a decision?
Vs.
Wartime Peacetime
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Big decisions…
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Forming a decision
Decision
Information
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Behaviour
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Decision
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Decision
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Behaviour
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Neuronal recording
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The Start: Building a perceptual decision
100coh_circle.mov
http://monkeybiz.stanford.edu/movies/0coh_circle.qt
0coh_circle.mov
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LIP
. .Are the dots moving left or right?
0coh_circle.mov
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So what happens when we actually see something?
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Representation of sensory evidence
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Value
B
A
Compute V(A) and V(B)
Choose
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Value
B=£500
A=£1000
V(A) > V(B), so choose A
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Discounting
B
A
Compute V(A) and V(B)
Choose
Time
Value
Now!
3 weeks…
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Discounting
B = £500
A = £1000
V(Bt=now) > V(At=3 weeks) so choose B
3 weeks…
Now!
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Relative wealth
B
A
Compute V(A) and V(B) relative to your wealth now and in 3 weeks
Choose
Time
ValueNow!
3 weeks… Utility
Value
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Relative wealth
B = £500
A = £1000
Now, V(Bt=now, Wt=now) < V(At=3 weeks, Wt=3 weeks) so choose A
Plus pension of £1000 in 3 weeks!!
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Probability
B
A
Weight V(A) and V(B) by the probability they will occur
ChooseU = p * V
x p(A)
x p(B)
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Probability
B = £500
A = £1000
In other words… U(Bt=now, Wt=now) > U(At=3 weeks, Wt=3 weeks) so choose B
U = p * V
Risky bet
Safer bet
p = 0.1
p = 0.9
Now, V(Bt=now, Wt=now)*0.9 > V(At=3 weeks, Wt=3 weeks)*0.1 so choose B
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Deciding what we’re seeing
A
B p = 0.9
p = 0.1
On balance, we think we saw B
Choose
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Deciding what we’re seeing
Tumour
Healthy p = 0.7
p = 0.3
p(healthy|x-ray) > p(tumour|x-ray), so thought to be healthy…
Training a medical student…
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Priors
A
B p = 0.7 x prior
p = 0.3 x prior
Now we are not so sure…
Choose B is only rarely seen, small prior belief
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Priors
Tumour
Healthy
Smokes 40 a day
p = 0.3
p = 0.7
Now, p(healthy|x-ray) * p(healthy) < p(tumour|x-ray) * p(tumour), so more likely a tumour
Training a medical student…
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Value (again…)
A
B p = 0.7 x prior x value
p = 0.3 x prior x value
Better be safe than sorry – decide on “A”
Choose Detecting A is very important, detecting B is less so
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Value (again…)
Tumour
Healthy
Smokes 40 a day
p = 0.3
p = 0.7
Treat
All clear
Treat
All clear
V = 100
V = -500
V = -20
V= 0
In the real world…
1) U(“tumour”|tumour) = p(tumour) * p(tumour|x-ray) * V(treat, tumour)
2) U(“healthy”|tumour) = p(healthy) * p(healthy|x-ray) * V(all clear, tumour)
Then, U(“tumour”) = 1+3, U(“healthy”) = 2+4… choose which is bigger!
3) U(“tumour”|healthy) = p(healthy) * p(healthy|x-ray) * V(treat, healthy)
4) U(“healthy”|healthy) = p(healthy) * p(healthy|x-ray) * V(all clear, healthy)
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Putting it all together
Decision
Value
Discounting
Relative wealthRisk
Perceptualuncertainty
Priors
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Decision
Value
Discounting
Relative wealthRisk
Perceptualuncertainty
Priors
?
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Behaviour
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Neuronal recording
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Functional Imaging
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Functional vs Structural
Task-related activity Structure ?Pathology
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Need good hypotheses!
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So… how is decision made in the brain???
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An appropriate behavioural paradigm
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What is a decision, and what’s going on in the brain?
Elisabeth Rounis and Louise Whiteley
The mathematical brain:
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What is a decision?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
Choosing between different options….
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What is involved in making decisions?
OR ?
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Value
DecisionShort- vs. Long-term
gain
Context
Risk
Information gathering
Priors
Value
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What is involved in making decisions?
OR
?
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Short- vs. Long-term gain
DecisionShort- vs Long-term
gain
Context
Risk
Information gathering
Prior Beliefs
Value
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What is involved in making decisions?
You have:
What would you rather… OR ?
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Context
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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What is involved in making decisions?
OR
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Risk
DecisionShort- vs
Long-termgain
ContextRisk
Information gathering
Prior Beliefs
Value
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What is involved in making decisions?
Healthy? Or not?
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Information gathering
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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What is involved in making decisions?
Vs.
Wartime Peacetime
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Prior beliefs
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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What is involved in making a decision?
A model that helps us understand decision making, predict behaviour, and know kind of signals to look for in the brain…
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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How do we link brain, behaviour, and theory?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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Do a behavioural study…
Non-Dieters Dieters
What happens in the brain? What are the
differences in decision between dieters and
non-dieters?
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Brain has specialised areas that are interconnected… but what do these areas do?
Thinking, planning, moving
Feeling, recognising
Seeing
Understanding
‘Higher’ Order areas located in front…
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… Recording directly from brain cells (‘neurons’)
Neuron 1
Neuron 2
Ave
rage
act
ivity
Time
dendrites
soma
axon
synapses
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Functional Imaging of whole brain regions
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What is involved in a decision?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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Information gathering
OR
Healthy? Or not?
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Information gathering
• Enigma code breakers - how much time can you sacrifice to gather more information?
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Investigating information gathering in the brain
1. Think of a really simple decision
2. Find neurons in the brain that carry information important for our decision
3. Find neurons in the brain that add up this information over time
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1. A really simple decision…
Which overall direction are the dots moving in?
0% coherence (random)
100% coherence(all in one direction)
50% coherence
The more random dots there are, the longer you need to work out the direction of the non-random onesi.e. the more information you need to gather…
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Random dots
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Random dots… Can you see a direction?
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Random dots… now they’re moving right!
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2. Neurons that care about motion…
First, we need to find an area where the brain cells (neurons) carry information about the direction of motion…
Area MT neurons respond more to a ‘preferred’ direction Stimulating neurons that prefer ‘down’ produces ‘motion hallucinations’
MTa
ctiv
ity o
f ne
uro
ns preferred direction
Britten et al. 2002, Huk and Shadlen 2005
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3. Tracking information, adding it up…
MT
LIP
Gold and Shadlen 2007
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Video of activity in LIP
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Video of activity in LIP
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Video of activity in LIP
Roitman and Shadlen 2002
• Note the cell is always active but more so in the presence of the targets and as evidence accumulates
• Activity is lower if decision-maker has to choose a target that is not in the preferred direction of the cell
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So we’ve looked at dots, but there’s lots of other stuff in the world too - a range of brain areas track and gather information
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What is involved in making decisions?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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Prior Knowledge
Healthy? Or not?
What if we now find out the patient smokes 50 a day?
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Prior Knowledge
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Prior knowledge affects perception
What colour is a banana? YELLOW!!!
If you show people lots of bananas of different shades along the blue-yellow spectrum and ask them which one is grey?
they pick a slightly blue one, because our expectation that they will be yellow influences perception
true greyjudged grey Hansen et al. 2006
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So what about prior beliefs in the brain?
MT
LIP • This is still under investigation!
• Some candidates have been suggested, including ‘action’ areas of the visual system
• Understanding prior beliefs in the brain might help us decide between models
SC
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Perceptual decision making…
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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Information gathering
Is Wally on the right or the left hand side of the beach?
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Adding prior information
He’s definitely next to one of the boats…
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Next we consider the value of different options
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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Any questions…?
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A candidate brain area…
1 target
2 targets
4 targets
DimPossible Targets Select
8 targets
Accumulation of evidence over time is lower with more targets to choose from (ie more uncertainty as to probability of target location)
SC
act
ivity
at
‘DIM
’
TimeBasso and Wurtz 1998
Let’s ‘dim’ the lights…
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A candidate brain area…
Accumulation of evidence over time is lower with more targets to choose from (ie more uncertainty as to probability of target location)
SC
act
ivity
at
‘DIM
’
TimeBasso and Wurtz 1998
Let’s ‘dim’ the lights…
MT
LIP
SC
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The fussy brain:
What makes one option more attractive than another?
Steve Fleming and Louise Whiteley
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Value
Some decisions are about information gathering, where what matters is being accurate. Many everyday decisions are about what is valuable to us now, and in the future…
OR ?
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Predicting the future
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What is a decision?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
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Bentham and probability
Jeremy Bentham believed that using “felicific calculus” it was possible to work out the best action to take
“Nature has placed mankind under the guidance of two sovereign masters; pain and pleasure. It is for them alone to point out what we ought to do, as well as to determine what we shall do”
Jeremy Bentham, 1748-1832
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Darling’s investment – predicting the future
The value of the share can rise or fall…
Down5%
Up 10%p = 0.2
p = 0.8
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Darling’s investment – predicting the future
Down5%
Up 10%p = 0.2
p = 0.8
Expected value of share = weight each outcome by its probability, then add them all up
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Darling’s investment – predicting the future
Down5%
Up 10%p = 0.2
p = 0.8
Expected value of share = weight each outcome by its probability, then add them all up
EV(share) = outcomes p(outcome) x r(outcome)
= (0.2 x 10) + (0.8 x -5) = -2
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Darling’s investment – discounting the future
Down20%
Up 25%p = 0.2
p = 0.8Time
Value
Down20%
Up 15%p = 0.2
p = 0.8Time
Value
Share 1
Share 2
In six months…
In six weeks…
OR
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Darling’s investment – discounting the future
EV(share) = outcomes p(outcome) x r(outcome)
EV(share) = outcomes λ x p(outcome) x r(outcome)
Time
Value
Measuring impulsivity…
Time
Value
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How are these values learnt?
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What is a decision?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
+ Learning
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Investigating value in the brain
1.Find neurons that signal our preferences
2.Work out how these neurons learn from experience to predict future values
3.See how these neurons are affected by probability
4.See how these neurons are affected by when you get the reward
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1. Find neurons that signal our preferences
OFC – Orbitofrontal cortex
MT
LIP
OFC
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Neurons representing value of choice…
vs.
We want to know if OFC neurons can keep track of different preferences
V(pineapple) V(orange)
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orangepineapple
during instruction
just before reward
Preferences in the OFC
• Different groups of neurons within OFC are associated with different types of reward (e.g. orange vs. pineapple)
• OFC neurons also know how much reward is on offer - e.g. six apples vs. one piece of cake
Padoa-Schioppa & Assad (2006)
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2. Work out how neurons predict future values
• Learn from the past!
New value = prediction + new information
= difference between prediction and what happened…
So:
New value = prediction + α(outcome – prediction)
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How does the brain predict future values?
(outcome – prediction)
Schultz et al. (1997) Science
Reward unpredicted, reward occurs
Reward predicted, reward occurs
Reward predicted, reward absent
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Changing our predictions with new information
Time
Read label
It’s corked
Taste…
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New information in the brain…
Seymour et al. (2004)
Basal ganglia
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3. See how these neurons are affected by probability
p = 0.8 p = 0.2
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LIP
Platt & Glimcher (1997)
How does the brain respond to probability?
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Knutson et al. (2005)
OFC Basal ganglia
EV = outcomes p(outcome) x r(outcome)
How does the brain respond to probability?
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Would you like a) £900 now or b) £1000 in one month’s time?
4. See how these neurons are affected by when you get a reward
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Short- and long-term gain in the brain
Kable & Glimcher (2007)
OFC
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Brain data help us refine our theory
OFC
Kable & Glimcher (2007)
• Two theories: –a) brain region knows about “absolute” value, communicates it to somewhere else which knows about how far away it is in time–b) discounting the future is inherent to our value system
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What is involved in making a decision?
What happens when things get more complicated…?
DecisionShort- vsLong-term
gain
Context
Risk
Information gathering
Prior Beliefs
Value
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Many decision systems in parallel
We’ve been focusing on how the brain learns values from experience, building up habits that can be used again
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Many decision systems in parallel
Sometimes, we can’t learn habits, and need to look ahead in a more sophisticated way…
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Complicated or one-off decisions…
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Many decision systems in parallel
And sometimes we don’t need to bother - we have innate values attached to things like food and shelter
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Bentham again…
“the game of push pin is of equal value with poetry”
vs. J.S. Mill…
“it is better to be … Socrates dissatisfied than a fool satisfied”
Complicated value
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Many decision systems in parallel
In the next talk we hear more about these three systems, about how the brain chooses which system to use, and how
this can lead us astray…
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Any questions...?
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What is a decision?
DecisionShort- vs
Long-termgain
Context
Risk
Information gathering
Prior Beliefs
Value
![Page 126: Introduction By Elisabeth Rounis and Louise Whiteley](https://reader031.vdocuments.site/reader031/viewer/2022032207/5681358b550346895d9cf256/html5/thumbnails/126.jpg)
Neurons representing value of choice…
Padoa-Schioppa & Assad (2006)