CH 12: Comparative Cognition II: Special Topics

Tool use

• Physical objects from the environment and detached from environment that is then transported to a location used to accomplish a task 

What doesn't count as tool use:

• Objects that stay attached to the environment

• Ex. scratching against trees, vine swinging

Water as tool use

• Complicated as it can be valid, and also invalid as tool use

• Shooting down prey using a stream of water

  • Ex. archer fish 

Tool use in digger wasps

Amophila species use a pebble as a hammer to compact the soil over their nest

Functional vs non-functional tools

• Animals are often actually looking at different qualities of objects 

  • Figuring out if objects would be a good fit or not

• Choosing between functional and non-functional tools is based on the animal

• Ex. hauser et al. 

  • Hooks that monkeys have to choose are generalized across irrelevant features (colour, texture) 

Tool modification

• altering/changing an item (or tools) into something useful

  • Often carry the tools around with them

Meta-tool use

• Using a tool to get another tool to accomplish a task 

• Shows animal can plan ahead 

• Mulcahy, Call, & Dunbar (2005) Gorillas and Orangutans

  • 2 apparatus → one is getting the tool, one is using the tool

  • Selected long enough tools if subjects couldn't see reward and tools at the same time 

  • Successfully choose the right tool and walk back = shows that subject understands what kind of tool they need

Causality

• When an animal pursues a target outcome 

• When an animal ceases to purse target outcome once achieved

• Helps rule out if it is decisions made with intention and not others

• Physical reasoning

• Physical process where a tool effects its outcome

Insight

• Do animals know smth about the physics of their environment + action to reason about goals

Food storing birds

• Adaption to survive predictable food shortages

• Includes:

  • Parids (chickadees, etc)

  • Corvids (jay, crows, etc) 

  • Sittids (nuthatches)

• Being able to store food during food shortages help the actual species live to produce offspring and live longer 

Neural specialization in Food storing birds

• Hippocampus is larger relative to their brain and body compared to non-storing birds

• Remembering when food shortage season is, where food is stored, how to store

Can birds rmbr where each item was stored and return to it? 

• Need to rule out other possible caching strategies:

  • Search randomly and get lucky

  • Store food in particular locations

  • Mark food storage sites

  • Olfactory cues 

Memory in caching birds - example

• Kamil + balda

• Forced clark’s nutcracker birds to cache in only 18 locations out of 180 total spots

  • birds not able to choose spots

  • Removed olfactory cues

• After retention interval (10 days) birds allowed to search food

• Birds went to all 18 spots reliably without cues

  • Can’t be due to marked sites 

  • Can’t be due to preference for location type 

  • Can’t be due to olfaction

Do food-storing birds rmbr when food caching was?

• Useful to know when food caching was to know if food has spoiled or deteriorated

• No method exists for determining animal consciousness

• Uses episodic-like memory

  • Memories that capture information about when, where, and what an event consisted of 

  • Also called where-when-what (WWW) memory 

jays and worms example

• Have jays learn that peanuts don't go bad fast, worms go bad fast when caching 

  • Jays prefer worms, but if worms go bad when it is cached then their preference shifts to the peanuts 

  • Jays remember when, what, where food was cached 

• In control group → birds prefer worms all the time when worms don't go bad 

Episode-like memory in birds - example

• Kibble and peanuts similar enough to birds

• Birds don't like to keep caching one thing → more variety

Perceptual categorization 

• Balance between stimulus discrimination and stimulus generalization 

  • Generalization within category/set stimuli

  • Discrimination between categories/sets of stimuli 

True category

• S+ → rewarded

• S- → unrewarded

Pseudo category

• Requires rote memorization to solve

• S+ → rewarded (isn't all one category - mixed) 

• S- → unrewarded (isn't all one category - mixed)

Generalization to novel exemplars

• Test for transfer of performance to stimuli that did not appear during training

  • Rules out rote memorization

• Evidence of generalization to new exemplars are critical for demonstrations of perceptual concept learning 

Call stimuli - example

• Provided different categories of bird calls

• Used discrimination training

  • Naturally-ordered (S+)

  • Scramble-ordered (S-)

• If they use category learning

  • They generalize similar calls (to new stimuli too) 

  • Learns that S+ calls get them food

• If didn't use category learning

  • They spend more time memorizing that EACH call is good or bad

  • Takes more time 

  • No generalization 

• We can compare learning speed of the true category group to the pseudo category group

Category learning mechanisms - Feature theory

• Members of a category have common feature

• Polymorphic rule: category membership based upon a certain number of relevant features

Category learning mechanisms - Higher level concepts

• natural/artificial

• Abstract concepts (same/different) 

Symbolic

• sounds and written symbols represent objects, actions, and ideas

Semantic

• meaning behind worlds and word combinations

Generative

limited number of symbols combined in an infinite number of ways to general new messages

Structured

rules that govern how components are put together in a meaningful way

Phonological rules

• how phonemes (sounds) are combined to create words

Morphological rules:

how morphemes (small units of meaning) are combined to create a word

Syntax

• system of rules for making sentences

Grammar

• Systematic rules of a language

  • Specifies how units of a language can be combined in a way that has meaning

  • Includes phonological, morphological, and syntactical rules

Chomsky’s nativist theory of language

• Language acquisition is possible after critical periods, but is most efficient during their critical periods

• Even in animals, they have critical periods to learn vocalizations/sounds

  • Sensitive period →  More accurate term 

Language abilities

• Attempts to teach orangutans, chimps, and gorillas to speak english 

• Failure due to different vocal tract structures

  • Humans have better fine motor control over mouths and tongue, as well as vocal cords

Artificial language

• American sign language

  • Used with some gorillas, etc

• Plastic token

  • Plastic objects varying in shape, size, colour, and texture

• Lexigrams

  • Symbols serving as words

  • Ex. bunny the dog

• Spoken english

  • English sounding sounds

  • Kanzi the gorilla

Is protolanguage really language?

• Difficulties with true grammar

• Difficult to analyze 

• Problems with definitions

• No evidence for complex sentences

  • Songbird vocal learning is closest ecological relative to human language learning 

Time scales

• Circadian

• Interval 

• Millisecond 

Peak procedures (duration production) 

• Food is delivered after a fixed interval

  • Stimulus 1 → FI 20s → food

  • Stimulus 2 → FI 40s → food

Midsession reversal

• Reverse operant contingency mid-session

• First half of session, reinforce one key

• Second half of session, reinforce other key 

• Optimal performance would be to make some response until reinforcement stops, then switch

  • One incorrect response total

  • Rest are correct

• However, no species really does that

• Passage of time can be clue for when to switch 

Anticipatory errors

• People tend to start making guesses early for switching 

• Ex. microwaving food and going to do smth else, rush back thinking food is ready but its only ben 10 seconds

Perseverative errors

• Still responding to old/previous

Closer to switchpoint midway in midsession reversal

• more struggle of picking other when getting close to midpoint, and picking old when past midpoint

  • Issue with inhibition

Changing length of ITI in midsession reversal

• More time → switching early

• Less time → switching later

Peak procedure results

• Peaks correct but 40s curve twice as wide as 20s curve 

  • 20s → increased time accuracy

  • 40s → decrease time accuracy

Counting

• Most recognize animals are not counting to tell time

• Rather using: 

  • Sense of number

  • Relative numerousness judgments

  • Relative quantity judgements 

• More similarities among different species than actual differences 

  • Suggests: existence of similar numerical systems among vertebrates 

Origin of numerical processing

• Humans have sophisticated symbolic systems for numbers and math concepts

  • Also have non-symbolic numerical abilities

• Non-symbolic numerical abilities: internal numerical quantities

  • Abilities seemed to be shared with other animals 

Shared system for ordering small and large number judgements (humans and monkeys)

• Small number judgements → more precise and easy to judge

• Large number judgements → less precise 

Distance effect:

• Discrimination is easier with blogger distance between numbers

Magnitude effect

• Discrimination between given absolute value is easier with small numbers than large ones

Webers law: ratio is what matters

• Ratio helps us discriminate between quantities

• Ex. 1 vs. 2 =   2 vs. 4   =   4 vs. 8    ect. 

• Ratio dependence shown for humans → non-humans tested with only small numbers

Current study of webers law

• Monkeys trained to order smaller numbers in pairs of 1-9

  • Then tested with numbers up to 30

• Results

  • More magnitude and distance = More speed and accuracy 

  • Less magnitude and distance = less speed and accuracy  

• Performance compared to humans 

  • Weber's law holds true → Monkeys showed similar rules to humans