Task 7 Flashcards
7.1: Where can the amygdala be found in the brain?
- part of limbic system
- part of temporal cortex
- before/anterior to hippocampus
7.1: Why is the amygdala relevant for goal-directed decision making, and therefore for neuro-economic theory?
- encodes emotional information
- can influence decision making directly by influencing emotions
7.2: What are the two major misconceptions about amygdala function that obscure its contribution to
goal-directed decision making?
- Misconception: A is only involved in negative emotions
2. Misconception: A essential for reward learning
7.2: Why is the first misconception wrong (A involved only in negative emotions)?
-A also processes positive affect
7.2: What’s the evidence that the A also processes positive affect? –> monkey studies
- study: recorded from single neurons in A while visual stimuli acquired a positive or negative valence through Pavlovian conditioning –> amygdala activity reflected stimulus–valence pairings
- -> one population of neurons encoded positive valence and a largely separate group of cells encoded negative valence in A (no obvious spatial segregation; most were in the basolateral portion)
- Study: role of the amygdala is limited to updating the monkeys’ estimation of the current biological value of food
7.2: What’s the evidence that the A also processes positive affect? –> rat studies
-Study of Pavlovian approach behaviour
• Rats are exposed – on separate occasions – to two different stimuli & food is provided in association with only one of them
• both stimuli appear simultaneously but no food shows up –> although the animals do not need to do or learn anything, they nevertheless spend more time near the stimulus associated with the food
• rats with lesions of the central nucleus of the amygdala (CeA) fail to show approach behavior
-Study: neuronal activity in rat’s BLA reflects stimulus–reinforcer associations, including positive ones!
7.2: What’s the evidence that the A also processes positive affect? –> human studies
-Study: right amygdala was selectively sensitive to faces that had been associated with emotional descriptions – either positive or negative (equally active)– compared with those with faces that had been associated with neutral information
o Study: images paired with a high, medium or low probability of food reward –> subjects expressed a preference for images paired with a high reward probability, although they remained unaware of the relationship between the images & food probability
–> anterior temporal lobe resection (including A): did not display such preferences
7.2: What’s the evidence that the A is NOT essential in stimulus reward learning?
- -> A seems to have crucial role in emotional reactions & only conditional one in reward processing
- -> amygdala is essential for linking objects with the current value of food rewards
- -> to the extent that an affective tag from the amygdala provides this value signal, the amygdala contributes to stimulus–reward association
So, what’s the (conditional) role of A in stimulus-reward learning?
- A seems to have crucial role in emotional reactions & only conditional one in reward processing
- A: affective tag provides a value signal for rewards
7.3: Explain the neuro-economics experiment described by De Martino et al. (2006)- AIM
Investigated neural basis of framing effect with fMRI & a financial decision-making task
7.3: What’s loss aversion?
=tendency to prefer avoiding losses to acquiring equivalent gains
=phenomenon where a real or potential loss is perceived as psychologically or emotionally more severe than an equivalent gain
7.3: How is loss aversion implemented in the task used?
-two different frames would lead to same amount of money when deciding for sure option (‘Keep 20$’ same as ‘Lose 30$’ of 50$ in total)
7.3: What are the main findings in De Martino’s experiment (regarding amygdala, MCC/preSMA & vmPFC)?
- Amygdala activation mediates framing effect –> more active when participants choose in accordance with framing effect (gain-sure & loss-gamble)
- MCC/pre-SMA: more active when subjects decision is counter framing effect
- OMPFC/ vmPFC: more active in subjects that act more rationally (against framing effect)
- -> strong reciprocal connections between amygdala & OMPFC
7.3: How do De Martino’s findings about the amygdala
confirm Murray’s hypothesized role for amygdala in goal-directed decision making?
-Amygdala: key role in processing contextual positive or negative emotional information presented by frame
–> through amygdala-omPFC route, frame-related value information is incorporated
==> evidence for amygdala-OFC pathway as suggested by Murray
7.3: What’s the framing effect?
human choices are susceptible to manner in which objects are presented
7.3: Explain the neuro-economics experiment described by De Martino et al. (2006)- METHODS
- Two different frames:
- -> Gain frame: gain money
- -> Lose frame: lose money
- Two response options:
- -> Gamble: certain probability of losing or gaining a certain amount of money
- -> Sure: certain amount of money that was either given or taken away
7.3: Explain the neuro-economics experiment described by De Martino et al. (2006)- RESULTS
- Framing significantly changed participants decision
- -> tended to choose sure option in gain frame (risk-averse)
- -> tended to choose gambling option in loss frame (risk seeking)
7.4: Assignment 7.4: reversal learning in healthy persons (Hampton et al., 2007) –> METHOD
-subjects choose between 2 stimuli & has to learn their outcomes
○ CORRECT choice : 70% monetary reward, 30% loss → overall gain
○ INCORRECT choice : 40% reward, 60% loss → overall loss
● when correct stimulus is chosen on 4 consecutive trials, stimulus-reward contingencies reverse &
participants have to infer that reversal took place
➔ subsequently, fMRI activity prior to switch vs non-switch/stay trials is compared
7.4: Assignment 7.4: reversal learning in healthy persons (Hampton et al., 2007) –> RESULTS: activity in switch trials
greater activity in switch trials in anterior frontal insula (AFI), lateral OFC & MCC
● AFI: increased cognitive control in response to negative feedback prior to scheme switch
● lOFC: negative feedback (from amygdala) on previously rewarded stimuli requires update on
stimulus-reward association → switching → updating → activity
● MCC: BOLD increase following negative feedback results in decision to switch responses in next trial
7.4: Assignment 7.4: reversal learning in healthy persons (Hampton et al., 2007) –> RESULTS: activity in stay trials
more activation of vmPFC in stay trials (–> DMN)
- 4: How do the results of Hampton’s experiment match conclusions of prior tasks?
- lOFC
- MCC
- vmPFC
-lOFC: storage & updating of stimulus-value associations
→ activity when update of association is required, i.e. in switch trials
-MCC: monitoring of response outcome & response errors
→ change in action-value requires decision to change (action)
-vmPFC: part of DMN, which has highest metabolic rate during rest
→ less de-activation (higher activity) when decision to stay is made
7.4: How do the results of Hampton’s experiment match conclusions of prior tasks? –> matches Camille et al’s experiment? (double dissociation)
-confirms that decision-making is a twofold process (as proposed by Rushworth T5) as involved areas show double dissociation in reversal learning task
○ patients with lesions in mOFC/vmPFC depict impairment in stimulus selection
○ patients with lesions in MCC depict impairment in action selection
→ confirmed by Hampton
+ Hampton delivers proof for role of lOFC = stimulus-value storage
7.4: What’s the effect of feedback on object & action selection cortices?
● provides affective signal for decision-making process
○ links stimuli with current reward value; initiates updating in case valence/value changes
→ Amygdala has connections to both
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> findings
- No signs of greater activity in AFI & lOFC during switch trials
- Probability reversal yielded much less of an updated stimulus reward association
- No signal from amygdala to OFC
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> findings regarding expected reward signals
- Weaker correlation between reward expectancy & mPFC activity (usually in HEALTHY pp: the higher the reward, the higher mPFC activity –> you’d stay& not switch but that’s NOT the case for lesioned patients)
- Reward computation differs from healthy subjects
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> How do Hampton et al’s finding about the amygdala confirm Murray’s theory about amygdala?
- Input from the amygdala is needed for the computation of expected reward (but not for the outcome representation)
- Amygdala is used in both positive & negative emotional processing –> findings confirm this bc amygdala plays a role in the sensitivity to both positive rewards & negative punishments
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> fMRI- responses to rewarding vs. punishing outcomes
- No difference to controls
- Feedback processing stays intact
7.5: apparent contradiction with Murray’s claim that amygdala doesn’t play a role in stimulus-reward learning (Hampton et al. report decreased reversal learning in the patients without amygdala, whereas Murray says that amygdala isn’t essential for reversal learning
🡪 Amygdala is not essential for reversal learning but it does help (affective value information + reward value information/computation that could help in learning the associations)
- -> ONLY seems like a contradiction
- -> without amygdala they can still do reversal learning but not as good
7.6: Murray’s model –> amygdala & OFC
- Amygdala: updates values of expected outcomes
- OFC: stores values of expected reward outcomes
- -> Direction of updating: from amygdala to OFC
7.6: Murray’s model –> IT/PRh & OFC
-IT/PRh interaction with the frontal cortex is necessary for implementation of visually guided rules
7.6: What does object-reversal learning probably depend on according to Murray?
possible that object-reversal learning, together with other visually guided rules, depends on IT/PRh–OFC mechanisms
7.6: Murray’s model –> IT/PRh & amygdala
-amygdala can modulate activity in IT/PRh to enhance sensory processing of biologically significant events& stimuli
7.6: Murray’s model: which two routes to OFC could subserve reward-based decisions generally?
- –> IT/PRh–OFC route processing visual information (including the visual, ‘informational’ aspect of foods & other rewards)
- -> amygdala–OFC route processing affective information
7.6: How does Murray’s model match Rushworth‘s model (T5)?
- lOFC: involved in learning & updating of stimulus-reward associations
- Murray: amygdala updates values of expected outcomes –> sends that to OFC
- -> OFC: stores values of reward outcomes
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> vmPFC activity?
- does NOT show a linear increase regarding low vs high reward expectancy in mPFC activity (compared to controls)
- pretty much the same activity in low vs high reward expectancy –> why they are more likely to stay even if it results in incorrect answer
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> which kind of signals do they lack?
lack of expected reward signals –> cannot be used to generate behavioural decisions
7.5: Hampton et al study: what’s the primary contribution of the amygdala?
computing expected reward values
7.5: Hampton et al experiment regarding the bilateral amygdala-lesioned patients –> vmPFC activity?
more likely to switch choices following reward than healthy controls
