week 8 - uncertainty, value, time

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24 Terms

1
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Fiorillo et al. (2003) - discrete coding of reward prob and uncertainity by dope neurons

pavlovian task experimental design

pavlovian conditioning > 5 stimuli predict rewards with diff probability but magnitude of reward holds constant. 

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Fiorillo et al. (2003) - discrete coding of reward prob and uncertainity by dope neurons

behavior response

as reward probability increased, licking went on for longer

<p>as reward probability increased, licking went on for longer</p>
3
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Fiorillo et al. (2003) - discrete coding of reward prob and uncertainity by dope neurons

reward response

with low probabilty of the reward, dope neurons respond to the reward itself, as probability increases dope neurons respond to the cue that predicts the reward with high probability. 

as reward probability increased > median response decreases (its expected, not a PDE)

<p>with low probabilty of the reward, dope neurons respond to the reward itself, as probability increases dope neurons respond to the cue that predicts the reward with high probability.&nbsp;</p><p></p><p>as reward probability increased &gt; median response decreases (its expected, not a PDE)</p>
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Fiorillo et al. (2003)

what was response of dope neurons when reward not delivered?

what was response to the cue as probability increased?

more supression in response when probability of the reward increases and reward is not delivered

response to cue increases as probability of the reward increase

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Fiorillo et al. (2003)

novel ramping activity?

subset of neurons with a differential response during the time between the cue and reward with the response betwen maximal at 50% probability.

these neurons encodes probability of reward outcome

<p>subset of neurons with a differential <strong>response during the time between the cue and reward</strong> with the response betwen <strong>maximal at 50% probability.</strong></p><p></p><p><strong>these neurons encodes probability of reward outcome</strong></p>
6
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model of uncertainty encoding

uncertainty = standard distribution of lottery

Max uncertainty = .5

<p><span style="color: rgb(0, 0, 0);">uncertainty = standard distribution of lottery</span></p><p><span style="color: rgb(0, 0, 0);"><span>Max uncertainty = .5</span></span></p>
7
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the neurons that respond during the time between the cue and reward and maximal at 50% probability are encoding standard deviation!

the response at the time of cue that increases as probability gets larger encodes expected value!!

true! one respone encodes EV (response to cue), the other encodes uncertainty (response between cue and reward), and we are most uncertain at 50/50

<p>true! one respone encodes EV (response to cue), the other encodes uncertainty (response between cue and reward), and we are most uncertain at 50/50</p>
8
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Fiorillo et al. (2003)

conclusion

uncertainty is related to probability of outcome

accuracy of prediction depends on being able to measure uncertainity in estime

increase in activity after cue and before outcomes encodes uncertainty

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Common Currency

what is common currency?

transformation of information into a common representational space > once all information is transformed in this sapce, comparisons can be made

10
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Schioppa et Assad (2006) - neurons in OFC encode economic val.

experimental design

1) monkeys fixate on screen

2) offer is made (1 yellow block vs 3 blue blocks) 

3) reaction time look to preferred option (saccade)

4) decision time

<p>1) monkeys fixate on screen</p><p>2) offer is made (1 yellow block vs 3 blue blocks)&nbsp;</p><p>3)&nbsp;reaction time look to preferred option (saccade)</p><p>4) decision time</p>
11
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Schioppa et Assad (2006) - neurons in OFC encode economic val.

choice preference results

the chance of picking B is less when the ratio of B is less in comparison to A

example

Strongly prefers 10 drops of blueberry to 1 drop of apple juice
Strongly prefers 1 drop of apple juice vs. 0 drops of blueberries

point of subjective equivalence = 4:1

monkey preference is represented on continum

<p>the<span><span> chance of picking B is less when the ratio of B is less in comparison to A</span></span></p><p><span><span>example</span></span></p><p><span><span>Strongly prefers 10 drops of blueberry to 1 drop of apple juice<br>Strongly prefers 1 drop of apple juice vs. 0 drops of blueberries</span></span></p><p></p><p><span><span>point of subjective equivalence = 4:1</span></span></p><p><span><span>monkey preference is represented on continum</span></span></p>
12
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Schioppa et Assad (2006)

how is value of blueberry vs apple assigned for sommone currency scale?

common currency is like..

4 blueberry drops = 1 apple drop

value(1A) = value(4B)

4 drops blue = 4

1 drop apple = 4


just multiply the number of apples by 4 to convert into common currency

1A  = 4.1B. when option is 0:1, monkey always select 1 apple which is value of 4.1 in framework.


common currency is like utility, everything must get converted into utility then compare

<p>4 blueberry drops = 1 apple drop</p><p>value(1A) = value(4B)</p><p>4 drops blue = 4</p><p>1 drop apple = 4</p><div data-type="horizontalRule"><hr></div><p>just multiply the number of apples by 4 to convert into common currency</p><p>1A&nbsp; = 4.1B. when option is 0:1, monkey always select 1 apple which is value of 4.1 in framework.</p><div data-type="horizontalRule"><hr></div><p>common currency is like utility, everything must get converted into utility then compare</p>
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c

Schioppa et Assad (2006)

choice results

1 drop A = 1.9 drop B > map data and find indifference point

B chosen for 3,4,6:1

A chosen for 1:3, 1:2, 1:1

activity observed just follow juice deliery is top graph, gray daata is from period before choice options visible

<p>1 drop A = 1.9 drop B &gt; map data and find indifference point</p><p></p><p>B chosen for 3,4,6:1</p><p>A chosen for 1:3, 1:2, 1:1</p><p></p><p>activity observed just follow juice deliery is top graph, gray daata is from period before choice options visible</p>
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in a pure reward signal, representatiosn should be independeent of what?

is the OFC response to juice a pure reward signal?

in a pure reward signal, representatiosn should be independeent of behavior and stimulus features

——

yes, no spatial or motor info contained in signal > no info about amount of taste encode in chosen value signal

<p>in a pure reward signal, representatiosn should be independeent of behavior and stimulus features</p><p>——</p><p>yes, no spatial or motor info contained in signal &gt; no info about amount of taste encode in chosen value signal</p>
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<p>offer value vs taste encoding</p><p>what is the order in which neurons encode info from choice task?</p>

offer value vs taste encoding

what is the order in which neurons encode info from choice task?

offer value: some neurons encode value info related to specific offer

taste: some neurons respond at the same level regardless of amount for a particular juice


1) offer value (value of each individual optoin)

2) chosen value repreentation (value of juice option that will be selected by monkey)

3) taste (before or after juice delivery)

16
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Schioppa et Assad (2006)

conclusions

  1. OFC neurons signals important for decisions-making

  2. OFC encoode chosen value > related for behaivor

  3. OFC has pure value signal > not related to stimlus propertie

  4. signal underlying choice

  5. neural representation of subjective value

17
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what did economist Jevons 1871 say?

to secure max benefit in life, all future events, pleasures, and plans should act upon us with the same force as if they were present

time plays an influence on our decision-making process > all things we know we need to concern about in the future, should evoke same concern as if it was present and in the moment but most people shrug off future things and push it off. 

examples: retirement, health care, disease, adddiction, diet

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modeling temporal discounting

over time, relative value decreases and the rate of decrease defines the concept of impulsivity vs self-control

<p>over time, relative value decreases and the rate of decrease defines the concept of impulsivity vs self-control</p>
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exponential discount function

Vreward= value / (1+r)^t

r = discount rate (baseline impulsivity)

t = time

small R = less discounting & more self control

big R = more discounting & more impulsive

used if only magnitude of outcome, not time considered

<p>Vreward= value / (1+r)^t</p><p>r = discount rate (baseline impulsivity)</p><p>t = time</p><p></p><p>small R =&nbsp;less discounting &amp; more self control</p><p>big R = more discounting &amp; more impulsive</p><p></p><p>used if only magnitude of outcome, not time considered</p>
20
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hyperbolic discount function

Vreward = magnitude / (1 +(k * delay))

k = steepness

small k = less discounting more self control

big k = more discounting more impulsive 

<p>Vreward = magnitude / (1 +(k * delay))</p><p>k = steepness</p><p>small k = less discounting more self control</p><p>big k = more discounting more impulsive&nbsp;</p>
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proximal vs distant

proximal = value small immediate

distant = value big delayed

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difference between hyperbolic and expontential

hyperbolic predicts reversal of preference, exponential does not

time considered in hyperbolic, time not considered in exponential; ideal for a utilty maximizer

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McClure et al (2004)

experimental design

choice taks betweeen small early and large but delayed

$5 now and $10 in two weeks
$5 tomorrow and $40 in a month

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McClure et al (2004)

brain regions of interest and results

PCC

MPFC

VS

MOFC

these clusters were activated for immediate rewards comapred to delayed. these brain regions recieve dopamine signals