BiologicalBasis 10 Comparing Intelligence.pdf

Comparing intelligencePSY2304Biological Basis of BehaviourLecture 10 We return to the question...•Do studies of animal cognition enable us to say which species of animals are most intelligent? •If so, what is the answer?•And are humans a special case? The debateTwo schools of thoughtgradual (quant...

Comparing intelligencePSY2304Biological Basis of BehaviourLecture 10 We return to the question...•Do studies of animal cognition enable us to say which species of animals are most intelligent? •If so, what is the answer?•And are humans a special case? The debateTwo schools of thoughtgradual (quantitative) difference between humans and other animalsSharp (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•That evolution necessarily implies “improvement”: clearly complexity has come about through evolution, but evolution does not always produce greater complexity•That evolution necessarily 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 kindof human we are at top of the “ladder of nature”•Obviously, similar errors were made before the theory of evolution was formulated Scala naturae•We cannotassume that there is a “scala naturae”, a ladder of nature, with the Amoeba at the bottom (least intelligent) and humans at the top (most intelligent)•So what are the alternatives?•And what dowe know?•And why is this concept of a ladder of intelligence so appealing? We start with the most obvious approach: brain size. Brain comparisons•Bigger brains → higher intelligence? There is some evidence that this works for some parts of the brain, e.g. hippocampus and spatial memory•But bigger animals have bigger brains in any case. Doesn't mean they're cleverer.•“(En)cephalisation coefficient”: EC=brain mass/body mass•Jerison: Look for deviationsfrom plot of brain mass vs. body mass. Once this is done, we start to get some interesting patterns emerging. A somewhat clearer version of the figure on the previous slide.Note how the New World Monkeys, Old World Monkeys and Apes seem to follow a different regression line to other mammals, and to reptiles and amphibians.Evidence of this kind supports the view that there are qualitative differences in intelligence across different species.But this evidence should be viewed with caution -the factors determining brain / body ratio are complex. Behavioural correlates of intelligence•Typical suggestion: learning rate –with a fixed task, animals that learn faster must be more intelligent -but contextual variables an issue.•Commonly used example: Hebb-Williams maze (sequence of T-mazes)•More sophisticated example: not one task but “learning how to learn”–Successive reversal–Learning set–Probability learning•Better, a batteryof tests, looking for patterns (Bitterman, 1965), more like the approach to IQ. Examples: Serial Reversal Learning: Mackintosh(1974)+-++--Learn this problem to a criterion of say 90% correct.Then it reverses -learn to same criterion again.It then reverses again -learn to same criterion -and so on.The result? On later reversals the animal makes less errors in acquiring the discrimination. Rate at which this occurs correlated with intelligence? Madingleysheep… Examples: Learning Sets: Harlow (1949)+-++--Learn this problem to a criterion of say 90% correct.Then it changes -learn to same criterion again.It then changes again -learn to same criterion -and so on.The result? On later problems the animal makes less errors in acquiring the discrimination. In extreme cases it makes only 1 error! Can we use the rate of acquisition of this problem as an index of intelligence? Learning sets across species.Compare the previous two graphs to this one. The case for some correlation between brain size and intelligence would seem to be quite strong. But there are dangers here. Comparisons across species are difficult because it is hard to specify in advance what the optimal conditions for testing any given species would be. This is the problem of contextual variables. Macphail’s null hypothesis•Macphail (e.g. 1982, 2000): there are no cognitive differences between non-human animals. A more refined version: There are no differences amongst non-human vertebrates.•The only important difference is the emergence of human language. Language training may confer special abilities.•If we find more sophisticated cognition in e.g. apes than other species, that may be because we can understand better how to test cognition in species that are like us. => “Contextual variables” could be responsible for the observed differences in performance rather than genuine differences in intelligence. Contextual variables and learning sets•Herman and Arbeit (1973) found that dolphins had difficulty forming learning sets with visual stimuli but could with auditory stimuli. •Thus, how well an animal forms a learning set may well depend on the type of stimuli used to test them.•The only valid test would be to compare animals with similar sensory and effector capabilities (we’lllook at this approach later). Evidence in support of Macphail•Simple forms of learning (e.g. classical and operant conditioning) take place in much the same way and at much the same rate in all vertebrate species and at least some invertebrates•Surprisingly sophisticated forms of learning turn up in invertebrates, e.g. molluscs, arthropods. An initial response to weak stimulation is strengthened by pairing CS and US.Aplysia initially responds weakly to a gentle touch on the siphon by withdrawing both gill and siphon, but when pairedwith an aversive shock to the tail this response becomes more vigorous. The increase in response is over and above that seen in sensitisation.Siphon sensory neuron synapses on motor neurons for siphon and gill. The connection strength from siphon to gill strengthens during the course of conditioning because of facilitation by the interneuron which occurs at the same time as pathway activation .ConditioningsiphonSN1MNgilltailSN2IN Conditional discrimination•Colwill, Absher and Roberts (1988)•Conditional discrimination in Aplysia•Found that Aplysia could learn to provide differential responses to the same stimulus in different contexts.•Context 1 was a smooth white round bowl with lemony seawater•Context 2 was a dark grey rectangular container with ridges and turbulence (an aerator). Learning in honeybees (M. Giurfa & colleagues)•Classical and instrumental conditioning•Contextual learning: C1: A+, B-; C2: A-, B+•Categorization: –bilaterally symmetrical vs.asymmetrical, –different types of abstract patterns,–same vs. different (matching and non-matching tosample)–negative patterning: A+, B+, AB-…w/ olfactorystimuli Journa l o f Experimenta l Psychology : Anima l Behavio r Processe s VOL . 7, Nc . 1 JANUAR Y Reasonin g in th e Chimpanzee : I . Analogica l Reasonin g Dougla s J. Gillan , Davi d Premack , an d Gu y Woodruf f Universit y of P e n n s y l v a n i a and Universit y of Pennsylvani a Primat e Facilit y Analogica l reasonin g in a 16-yr-ol d femal e chimpan7.e e (Sarah ) wa s studie d in five experiments . Th e genera l desig n of the analog y problem s wa s wher e sam e wa s Sarah' s plasti c symbo l fo r "same. " Sara h solve d analog y problem s wit h tw o type s of d i s p l a y s : (a) force d choice , in whic h she had to com - plet e an analog y by choosin g the correc t B' fro m a set of a l t e r n a t i v e s (Experi - ment s IA , In , and 3A ) and (b) same-different , in whic h she had to complet e an analog y by choosin g the correc t predicate , Sam e or Differen t (Experiment s 2 and JB) . In addition , sh e correctl y solve d bot h figura l analog y problems , in whic h the stimul i wer e geometri c figure s an d the relation s amon g the m wer e difference s in size , color , or m a r k i n g ( E x p e r i m e n t s IA , In , and 2), and concep - tual analog y problems , in whic h the stimul i wer e househol d object s an d the relation s wer e functiona l an d spatia l (Experiment s 3A an d 3n) . Simpl e mecha - nism s f or p r o b l e m s o l u t i o n , e . g . , p h y s i c a l m a t c h i n g , f e a t u r e c o m b i n a t i o n , a nd choic e on the basi s of association , wer e rule d out . Th e dat a strongl y indicat e tha t Sara h use d the relatio n betwee n A an d A' to solv e the analog y problem s (Experimen t IB) . Th e implication s for theorie s of h u m a n and anima l cognitio n are discussed . Are ther e cognitiv e abilitie s tha t ar e an d for T h o r n d i k e , reasonin g wa s the pi ii uniqu e to h u m a n s ? M o s t i n f l u e n t i a l n i n e t e e n t h pa l cognitiv e differenc e betwee n hu m centur y theorist s propose d tha t reasonin g an d nonhumans . In contrast , a fe w e; was restricte d to human s (e.g. , Hohhouse , theorist s suggeste d tha t nonhumu n ani n 1901 ; Huxley , 1897 ; James , 1890 ; Morgan , coul d reaso n (e.g. , Darwin , 1871 ; M: i 1894 ; Thorndike , 1898) ; in fact , fo r Morga n 1932 ; Romanes , 1883) ; for e x a m p l e , in so of the onl y experiment s on anima l rea s --- j ngi Maie r (1929 , 1931 , 1932 ) explaine d < This researc h wa s supporte d by Gra m BN S 77 - tai n maze-learnin g result s wit h rat s in lei 168;> 3 fro m (h e Nationa l Scienc e Foundatio n an d r n i . » • i Gra m i.poi-HD-10% 5 fro m th e Nationa l instate s ° / r e a s o n i n g . However , alternativ e expl a of H e a l t h . Th e firs t autho r w a s supporte d by a Cogni - tlon s tna t «' " no t P oslt reasonin g als o live Scienc e Fellowshi p fro m the Sloa n Foundation , counte d fo r Maier' s result s (se e Harl i The aulhois'lhan k Keit h Kennel , Sarah' s trainer , for 1951 ; Hull , 1952) , and replication s of Mai l his hel p in thes e experiment s experiment s supporte d thes e allerna l Request s fur reprint s shoul d be sen t to Duughi s J. ' . . ,,.,, , „ „ ,m, > T- I Gillan , wh o is now at T23 - 1. Genera l Food s Technica l explanation s (Wolf e & Spragg , 1934) . 1 h Center . 55 5 Sout h Broadway . Tarrylown . Ne w althoug h ther e wa s no lac k of controve ; Yor k 10591 . o n reasonin g in animal s lat e in the ninetee i Copyrigh t 1981 hy Ihe America n Psychologica l Associalkm . Inc. OW7 - 7 W 8 I '07(1 1 .OWISIX ) 75 1 A bit more about analogical reasoning…Gillan, Premack and Woodruff (1981)The one type of evidence that Macphailconcedes is evidence of higher order cognitive ability. Something different in kind, not merely different in quantity. A bit more about analogical reasoning…Gillan, Premack and Woodruff (1981).Here we have the conceptual analogical reasoning problem I referred to in an earlier lecture.Sarah can get these (mostly) right. By using two versions with the same alternatives, the experimenters rule out an explanation based on simple preference for one response item.Symbol for same A b i t m o r e a b o u t analogical reasoning…Gillan, Premack and Woodruff (1981).Here we have the kind of analogical reasoning problem used in IQ tests.Sarah can get these (mostly) right as well. She can basically pass the type of IQ test problem that might be used with humans –to a limited extent. Summary•It’s surprisingly difficult to rank-order animals in terms of intelligence.•Perhaps the message here is that we should be more impressed by the similarities between animals cognitive capabilities than their differences. This is not to say that some of the specialised adaptations that animals possess (e.g. spatial navigation in pigeons, spatial memory in food caching birds) aren’t impressive.•There may be some quantitative differences in intelligence across species -but even here do they reflect a general intellectual difference or just a specific adaptation to a particular niche? The only evidence I can find for something that goes beyond this is in language trained chimps –and that evidence is impressive but still falls short of what we can do.•But humans are different. They have language, and an intelligence that other animals simply don’t have. On the other hand, I shall argue next year in my final year module that we also have this other, associative mode of processing that we share with other animals. So perhaps it’s not so much that other animals are like us, but more that we’re like them… In conclusion…In my component of this module, I’ve tried to show:•That it is helpful to use ideas from general cognitive psychology in understanding animal behaviour•That it is helpful to use ideas from animal cognition to help understand our behaviour!•That associative learning is an incredibly powerful mechanism that plays a significant role in animal cognition and most likely in ours as well.•Next year in the Associative Mind module I develop these ideas further, but this time focussing on humanlearning, memory and cognition. References•Bitterman, M. E. (1965). Phyletic differences in learning. American Psychologist, 20, 396-410.•Giurfa, M., & Capaldi, E. A. (1999). Vectors, routes and maps: new discoveries about navigation in insects. Trends in Neurosciences, 22, 237-242.•Giurfa, M., Eichmann, B., & Menzel, R. (1996). Symmetry perception in an insect. Nature, 382, 458-461.•Giurfa, M., Zhang, S. W., Jenett, A., Menzel, R., & Srinivasan, M. V. (2001). The concepts of 'sameness' and 'difference' in an insect. Nature, 410, 930-933.•Jerison, H. J. (1973). Evolution of the Brain and Intelligence. Columbia University Press.•Jerison, H. J. (1969). Brain evolution and dinosaur brains. American Naturalist, 103, 575-588.•Macphail, E. M. (1982). Brain and Intelligence in Vertebrates. Oxford University Press. Chapters 1, 2, pp. 207-211 and pp. 277-282•Mackintosh, N. J. (1988). Approaches to the study of animal intelligence. British Journal of Psychology79, 509-525.•Premack, D. (1983). The codes of man and beasts. The behavioral and Brain Sciences, 6, 125-67.•Premack, D. & Premack, A.J. (1983). The mind of an ape. New York, Norton.•Wilson, Bundy, Mackintosh, N. J. and Boakes, R. A. (1985) 'Transfer of relational rules in matching and oddity learning by pigeons and corvids', The Quarterly Journal of Experimental Psychology Section B, 37:4, 313 -332.Reading•Pearce chapters 1 and 14 (3rd edition ) or Pearce (2nd Edition). Chapters 1, and 11.