lesson 7 Flashcards

(42 cards)

1
Q

Generality of Learning Laws (Initial Question)

A

Do the same rules of learning apply across different types of US (appetitive vs. aversive) and across different species?

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2
Q

Evolutionary Argument for One General Learning Process

A

Evolution is thrifty; if one learning system can solve multiple prediction problems, there’s no need for separate, costly systems.

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3
Q

Evolutionary Argument Against One General Learning Process

A

Argument: Different ecological challenges (e.g., finding food vs. avoiding predators) might require specialized learning systems for optimal outcomes, even if it’s more costly.

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4
Q

General Process Approach

A

he idea that there are some fundamental laws of learning that apply broadly across different species and situations.

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5
Q

Serial Reversal Task

A

An operant task (often in a Y-maze) where the rewarded choice alternates periodically. Tests the animal’s ability to learn the “rules of the game” (e.g., win-stay/lose-shift) beyond simple association.

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6
Q

Win-Stay/Lose-Shift Strategy

A

Rule: Continue with the same choice if it was rewarded; switch to the other choice if it was not rewarded. Optimal strategy for serial reversal tasks with unsignaled reversals.

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7
Q

Perseveration (in Reversal Learning)

A

The tendency to continue making a previously correct response even after the contingencies have reversed and it is no longer rewarded.

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8
Q

Learning Set Paradigm

A

A learning procedure similar to serial reversal but uses a new pair of stimuli for each discrimination problem. Tests the ability to learn the general rule that one stimulus in each pair is consistently correct.

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9
Q

Performance on Learning Set Tasks Across Species

A

Observation: Different species (and even different tasks within a species, e.g., visual vs. olfactory for rats) show varying levels of performance, suggesting potential differences in learning abilities or strategies.

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10
Q

Species-Specific Sensory Abilities and Learning

A

Influence: Differences in sensory organs (e.g., echolocation in bats, UV vision in bees) can make some species appear superior at tasks relying on those senses, but this doesn’t necessarily reflect general learning ability.

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11
Q

Cognitive Differences and Task Performance (Example: Ebbinghaus Illusion)

A

Observation: Different species can perceive the same stimuli differently (e.g., pigeons see the Ebbinghaus illusion reversed compared to humans), which can affect their performance on learning tasks involving those stimuli, independent of learning rules.

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12
Q

Salience of Stimuli Across Species

A

Influence: Different types of stimuli (e.g., odors for rats, visual cues for birds) have different levels of salience for different species, affecting how quickly they learn associations involving those stimuli.

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13
Q

Learning Strategies Across Species (Example: Pigeons and Memorization)

A

Observation: Some species (like pigeons) may rely on memorization of individual stimuli and their outcomes rather than learning general rules, especially when memory capacity is high relative to the complexity of the rule.

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14
Q

Unique Cognitive Skills (Example: Language in Humans)

A

Observation: Some species possess cognitive abilities (like human language) that appear to be unique and can fundamentally alter how they learn and solve problems.

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15
Q

Taste Aversion Learning (Introduction to the Lesson)

A

Significance (Early Research): Uncovered surprising properties that challenged the generality of existing learning laws and prompted a re-evaluation of learning principles.

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16
Q

Biological Function of Learning

A

Role: Learning serves to help organisms predict and prepare for biologically significant events, and evolutionary pressures shape what and how organisms learn.

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17
Q

Exaptation in Learning Mechanisms

A

Definition: A learning mechanism that evolved to solve one specific problem may be sufficiently effective for other problems as well.

18
Q

Adaptive Specialization in Learning

A

Definition: The evolution of a learning mechanism specifically adapted for one problem, potentially at the cost of efficiency in solving other types of problems.

19
Q

Relative Validity Effect (Generality)

A

bservation: Demonstrated across diverse species (rats, rabbits, pigeons, honeybees, humans in categorization/causal judgment), suggesting some fundamental learning principles are conserved despite independent brain evolution.

20
Q

Backward Blocking (Human Learning)

A

Definition: A learning phenomenon in humans (where prior learning about a US-B association can interfere with learning about a CS-US association even when the CS is presented before the US and B). It was not initially predicted by classical conditioning models but is prompting extensions to those models.

21
Q

Propositional Learning vs. Associative Learning

A

Debate: Some argue that conditioning involves learning propositions (declarative knowledge) about event relationships, while others emphasize associative links. The Perruchet effect (dissociation between CRs and verbal reports) suggests the latter might involve non-declarative processes.

22
Q

Long-Term Goal of Animal Learning Research

A

Aim: To uncover general laws of learning by examining the scope and generality of principles observed in the lab.

23
Q

Can you explain why food-poison pairings should be especially salient using our prediction lens? Jot down your thoughts and then click the button to see my thoughts.

A

Using our prediction lens can help explain the efficacy of taste aversion learning. Eating poison can be very dangerous – there are plenty of foods that will kill you if you eat them even once. Animals therefore don’t have the luxury of learning slowly what is good and what isn’t. Anything that makes you feel sick needs to be completely avoided from then on. It therefore makes sense for evolution to have made taste aversion learning very fast.

24
Q

Taste Aversion Learning

A

A type of learning where an animal associates the taste of a food with subsequent illness, leading to avoidance of that food. Ecologically important for survival.

25
Five Unusual Properties of Taste Aversion Learning (Initial Observations)
Selective CS-US associations. Long-delay learning. One-trial learning. Learning about non-events (safety). Apparent valuation of the CS (hedonic shift).
26
Garcia & Koelling (1966) Experiment - Setup
CS: "Bright, noisy, tasty water" (sugar + light + noise). US: Either mild shock (Audio-visual group) or radiation-induced illness (Gustatory group). Test: Response to the sugary water and the light + noise presented separately.
27
Term: Garcia & Koelling (1966) Experiment - Results
Audio-visual group (CS + shock): Aversion to light and sound, no aversion to taste. Gustatory group (CS + illness): Aversion to taste, no aversion to light or sound.
28
Stimulus Relevance
Definition: The principle that animals are predisposed to associate certain types of CSs with certain types of USs more readily than others, based on ecological plausibility. (e.g., taste with illness, auditory/visual cues with pain).
29
Term: Long-Delay Learning in Taste Aversion
Observation: Taste aversion can be learned even with long delays (hours) between the consumption of the food (CS) and the onset of illness (US), which contradicts typical contiguity requirements in other forms of learning.
30
Preparedness (in Taste Aversion)
Explanation for Long-Delay Learning: Evolution has prepared animals to associate tastes with delayed illness because the effects of toxins often take time to manifest. This helps in identifying and avoiding harmful foods.
31
Ecological Validity (in Taste Aversion and Preparedness)
Concept: Learning is more likely and efficient when the CS-US relationship aligns with how things typically occur in the animal's natural environment.
32
One-Trial Learning in Taste Aversion
Observation: A strong taste aversion can often be learned after just one pairing of a novel taste with illness.
33
Salience of Taste CS
Explanation for One-Trial Learning: Food and its flavor are highly salient cues for most animals due to their importance for survival, leading to rapid learning of negative consequences.
34
Learned Safety (in Taste Learning)
Initial Hypothesis: Animals might learn that a food is safe when consumption is not followed by illness. Current Understanding: Likely explained by latent inhibition; prior exposure to the taste without illness makes it harder to learn a subsequent aversion.
35
Hedonic Shift (in Taste Aversion)
Definition: The apparent change in the intrinsic value or pleasantness of a taste CS after it has been associated with illness; the taste itself becomes aversive.
36
US Revaluation Paradigm
Setup: CS → US1; then US1 is devalued or revalued (US2); test response to CS. Used to distinguish S-S and S-R learning.
37
Taste Aversion and US Revaluation
Observation: Unlike other forms of learning, taste aversion learning seems to be immune to the US revaluation effect. Changing the severity of the illness US after the initial aversion learning does not significantly alter the aversion to the taste CS.
38
Conclusion about Taste Aversion and Generality of Learning
Implication: Taste aversion learning exhibits several unique properties, suggesting that while some general learning principles exist, there are also specialized learning mechanisms shaped by ecological pressures and the specific nature of the CS and US.
39
Reflection Point Revisited: Evolutionary Arguments for/Against General Learning
The existence of specialized learning like taste aversion (with stimulus relevance, long-delay learning) provides evidence against a single, completely general learning process. Evolution has shaped learning to be efficient for specific ecological challenges. However, the fact that many general principles (like blocking, overshadowing, contiguity in most contexts) do apply across different US types and species still supports the idea of some underlying general mechanisms, possibly exapted for various functions. Arguments for generality might emphasize the efficiency of a single system for common prediction problems. Arguments against might highlight the fitness advantages of specialized systems for critical, domain-specific learning (like avoiding poisons). Real-world examples: General learning might be seen in learning about neutral cues predicting rewards or dangers. Specialized learning is evident in the rapid, long-delay aversion to tastes associated with illness.
40
Can you explain why food-poison pairings should be especially salient using our prediction lens? Jot down your thoughts and then click the button to see my thoughts.
Using our prediction lens can help explain the efficacy of taste aversion learning. Eating poison can be very dangerous – there are plenty of foods that will kill you if you eat them even once. Animals therefore don’t have the luxury of learning slowly what is good and what isn’t. Anything that makes you feel sick needs to be completely avoided from then on. It therefore makes sense for evolution to have made taste aversion learning very fast.
41
Jimmy and his sister Jane are at the dentist, having their teeth cleaned. They are in separate rooms and each being tended by a different dentist. Jimmy’s dentist, every so often, turns on a powerful overhead light and activates the machine that sucks out your saliva (technically called a saliva ejector). Whenever this happens, Jimmy feels a sharp pain in his tooth. Jane’s dentist also periodically turns on the light and activates the saliva ejector, and Jane then feels a pain in her eyes. Which of these will happen: Jimmy will learn to fear the light; Jane will learn to fear the saliva ejector Jimmy will learn to fear the saliva ejector; Jane will learn to fear the light Both Jimmy and Jane will learn to fear the saliva ejector Both Jimmy and Jane will learn to fear both the light and the saliva ejector
Jimmy will learn to fear the saliva ejector; Jane will learn to fear the light Correct! Due to the idea of stimulus relevance, Jimmy is more likely to associate the tooth pain with the saliva ejector than the light, and Jane is more likely to associate her eye pain with the light!
42
What are the five ways in which taste aversion learning seems to flaunt the normal (and presumably general) rules of learning?
Taste aversion: (1) only works with some pairings of CS and US; (2) works when the interval between CS and US is long; (3) shows strong learning in a single trial; (4) shows learning about non-events; (5) shows hedonic shift;