Comparing intelligence Flashcards
the debate
2 schools of thought o Gradual (quantitative) difference between humans and other animals o Sharp (qualitative) distinction between humans and other animals
misapprehensions about evolution
That some species are “more evolved” than others: all species have been evolving for exactly the same amount of time
Evolution necessarily implies “improvement”: clearly complexity has come about through evolution, but evolution doesn’t always produce greater complexity
Evolution leads in the direction of being human-like
consequences of misapprehensions
Anthropomorphism: we assume that animal cognition is like human cognition (but not as good)
Anthropocentrism: we interpret “advanced” as meaning “more like us”
Social/political baggage: we place the kind of human we are at the top of the “ladder of nature” – historically had influence
Similar errors made before theory of evolution formulated
scala naturae
Cannot assume there is a “scala naturae”, a ladder of nature w/ Amoeba at bottom (least intelligent) and humans at top (most intelligent)
What are alternatives?
What do we know?
Why is concept of ladder of intelligence so appealing? – start with brain size
brain comparisons
Bigger brain higher intelligence?
o Some ev that works for some parts of brain, e.g. hippocampus and spatial memory – e.g. taxi drivers and the knowledge
Bigger animals have bigger brains anyway – doesn’t mean they’re more clever
“(En)cephalisation coefficient”
o EC = brain mass/body mass
Jerison: look for deviations from plot of brain v body mass
New World Monkeys, Old Word Monkeys and Apes follow diff regression line
Ev supports view that there are qual diffs in intelligence between diff species
Ev should be viewed w/ caution – factors determining brain/body ratio complex
Purple = average animal line – average to be able to survive
Lower than average = less intelligence
Amphibians spend lots of time in water – supports body weight – can be bigger for given brain size – may not have anything to do w/ IQ
see notes
behavioural correlates of intelligence
Typical suggestion: learning rate – w/fixed task, animals that learn faster must be more intelligent – but contextual variables issue
Commonly used example: Hebb-Williams maze (sequence of T-mazes)
More sophisticated example: not one task but “learning how to learn”
o Successive reversal
o Learning set
o Probability learning
Better = battery of tests, looking for patterns (Bitterman, 1965) – more like approach to IQ
examples: serial reversal learning (Mackintosh, 1974)
see notes
On later reversals, animal makes less errors in acquiring discrimination
Rate at which this occurs correlated with intelligence?
Maddingly sheep – use spatial version of task – down tunnel and can turn left/right – reversed – learns and changes direction – learn v. quickly – task may just particularly suit them
examples: learning sets (Harlow, 1949)
see notes
On later problems, animal makes less errors in acquiring discrim
In extreme cases makes just 1 error
Can we use rate of acquisition as index of intelligence?
learning sets across species
see notes
Case for some correlation between brain size and intelligence quite strong
Dangers
Comparisons across species difficult because hard to specify what optimal conditions for testing given species would be
Problem of contextual variables – e.g. sheep – just task could do well – monkeys v. similar to us
Macphail’s null hyp
E.g. 1982, 2000: there are no cog diffs between non-human animals – more refined version: no diffs amongst non-human vertebrates
Only imp diff is emergence of human language – language training may confer special abilities
If we find more sophisticated cognition in e.g. apes than other species, may be because can understand better how to test cognition in species like us “contextual variables” could be responsible for observed diffs in perf rather than genuine diffs in intelligence
the role of contextual variables
Goldfish discrim 1: they fail to learn
Goldfish discrim 2: they learn
o Need reward within certain time window
see notes
contextual variables and learning sets
Herman and Arbeit (1973) found that dolphins had difficulty forming learning sets with visual stim but could with auditory stim
How well animal forms learning set may depend on type of stim used to test them
Only valid test would be to compare animals with sensory and effector capabilities
ev in support of Macphail
Simple forms of learning (e.g. classical and operant conditioning) take place in same way and rate in all vertebrate species and some invertebrates
Sophisticated forms of learning turn up in invertebrates, e.g. molluscs, arthropods
see notes
Initial response to weak stim strengthened by pairing CS and US
Aplysia initially responds weakly to gentle touch on siphon by withdrawing both gill and siphon, but when paired with aversive shock to tail this response more vigorous – increase in response over and above that seen in sensitisation
Siphon sensory neuron synapses on motor neurons for siphon and gill – connection strength from siphon gill strengthens during course of conditioning because of fac by interneuron which occurs at same time as pathway activation
conditional discrim (Colwill et al., 1988)
Conditional discrim in Aplysia
Found could learn to provide differential responses to same stim in diff contexts
Context 1 was smooth white round bowl w/ lemony seawater
Context 2 was dark grey rectangular container w/ ridges and turbulence (aerator)
Pair prod w/ shock
Other condition = unpaired
Learn context where paired and greater gill withdrawal
see notes
learning in honeybees (Giurfa et al.)
Classical and instrumental conditioning
Contextual learning: C1: A+, B-; C2: A-, B+ - conditioning discrims
Categorisation:
o Bilaterally symmetrical v asymmetrical
o Diff types of abstract patterns
o Same v diff (matching and non-matching to sample)
o Neg patterning: A+, B+, AB-… w. olfactory stim – when paired = no reward – rat and humans take long time to learn but bees can learn quickly