1 / 41

Origin of Language: the Hardest Problem in Science?

Origin of Language: the Hardest Problem in Science?. Eörs Szathmáry. Collegium Budapest Eötvös University. The major transitions (JMS & ES, 1995). *. *. *. *. * These transitions are regarded to be ‘difficult’. Why is language so interesting?.

yoland
Download Presentation

Origin of Language: the Hardest Problem in Science?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Origin of Language: the Hardest Problem in Science? Eörs Szathmáry Collegium Budapest Eötvös University

  2. The major transitions (JMS & ES, 1995) * * * * * These transitions are regarded to be ‘difficult’

  3. Why is language so interesting? • Because everybody knows that only we talk • …although other animals may understand a number of words • Language makes long-term cumulative cultural evolution possible • A novel type of inheritance system with showing “unlimited hereditary” potential

  4. What is so special about human language? • Basically, it is the fact that we make sentences using grammar • Languages are translatable into one another with good efficiency • Some capacity for language acquisition seems to be innate • THE HOLY GRAIL IS THE EMERGENCE OF SYNTAX

  5. Understanding language evolution is difficult

  6. Three interwoven processes • Note the different time-scales involved • Cultural transmission: language transmits itself as well as other things • A novel inheritance system

  7. protein protein germ DNA DNA soma soma sentence sentence germ germ germ Neural representation Neural representation germ Language is not Weismannian

  8. Design features of language • Compositionality (meaning dependent on how parts are combined) • Recursion (phrases within phrases) • Symbolicism (versus icons and indices) • Cultural transmission (rather than genetic) • SYMBOLIC REFERENCE and SYNTAX

  9. A simple experiment (Hauser & Fitch) • Finite state grammar (AB)n is recognizable by tamarins • Phrase structure grammar AnBn is NOT. • Humans recognize both

  10. Our evolutionary relatives What has happened on our linage in the past few million years so that our genes allow for the development of a brain that can sustain syntax?

  11. Words are symbols, Saussurean signs Object Concept Symbol TREE

  12. Word representation is distributed… …and is related to the somatosensory handling of the designated object

  13. Principles and parameters • Principle: a universal property of human language, assumed to be innate. • Parameter: a two (or more) valued choice determining a general property distinguishing one type of language from another.

  14. Syntactic processes and information • Colourless green ideas sleep furiously • Structure building (phrases, etc.) • Checking agreement (e.g. in German noun phrases must be marked for case) • Mapping thematic roles (John loves Mary, Mary loves John) • Complexity (the dog was chased by the cat) • SYNTAX IS NOT WORD ORDER!!!

  15. The D- and S-structures • The sentence is: Mary was chosen

  16. The traditional view • Broca’s area: the “seat of syntax” • Wenicke’s area: the seat of semantics (fluent aphasia) • Double dissociation • Unfortunately (?) not quite true

  17. New data on Broca • One can have syntactic deficit with intact Broca • Affected Broca does not always produce problems in morphosyntax • Some Broca aphasics have problems with semantics as well • Broca lesion neither necessary nor sufficient for syntactic deficit • BUT may be essential for COMPLEX sentences (a problem with working memory?)

  18. Neuroimaging studies of syntactic processing • By comparing syntactically complex to simple sentences • By comparing sentences to lists of unrelated words • By comparing sentences containing non-real words to normal ones • Comparing sentences with syntactic violation to those without

  19. Semantic and syntactic violations Syntactic violation versus • Correct sentences • Semantic violation • Other violation • Semantic violation versus • Correct sentences • Syntactic violation

  20. Where is syntax in the brain? • In many areas • These include some parts of the RIGHT hemisphere • None of these areas is exclusively dedicated to syntax • Broca: semantics phonology, memory, music perception • INCONSISTENT WITH A STRICTLY ANATOMICAL MODULAR VIEW

  21. Resolution (Kaan & Swaab, 2002)? • Maybe there is a dissociation at the cellular level between these functions, below resolution • Maybe the combination of these areas forms a unique network • Different parts of the network are recruited to different syntactical tasks • MAYBE, BUT WHY NOT IN APES?

  22. An even more radical resolution: The Language AmoeBa (LAB) hypothesis • Szathmáry, E. (2001) Origin of the human language faculty: the language amoeba hypothesis. In (J. Trabant & S. Ward, Eds.): New Essays on the Origin of Language. Berlin/New York: Mouton/de Gruyter, pp. 41-51.

  23. Recuerdos de mi vida (Cajal, 1917, pp. 345–350) “At that time, the generally accepted idea that the differences between the brain of [non-human] mammals (cat, dog, monkey, etc.) and that of man are only quantitative, seemed to me unlikely and even a little offensive to human dignity. . . but do not articulate language, the capability of abstraction, the ability to create concepts, and, finally, the art of inventing ingenious instruments. . . seem to indicate (even admitting fundamental structural correspondences with the animals) the existence of original resources, of something qualitatively new which justifies the psychological nobility of Homo sapiens?. . . ’’.

  24. Species-specific differences in cortical microstructures do exist

  25. Differences in the primary visual cortex among primates (Preuss et al) In monkeys: the honeycomb Modifications in evolution

  26. The difference in gene expression patterns • Despite our close genetic relationship to chimps • The epigenetic difference in the brains seems enormous

  27. genes selection development learning behaviour environment The evolutionary approach Impact of evolution on the developmental genetics of the brain!

  28. Crucial facts for LAB • Localisation of language is not fully genetically determined: even large injuries can be tolerated before a critical period. • Language localisation to certain brain areas is a highly plastic process, both in its development and its end result. • It does seem that a surprisingly large part of the brain can sustain language: there are (traditionally recognised) areas that seem to be most commonly associated with language, but by no means are they exclusive, either at the individual or the population level, during either normal or impaired ontogenesis. • Whereas a large part of the human brain can sustain language, no such region exists in apes.

  29. Crucial theses of LAB • The language amoeba is the neuronal activity pattern that essentially contributes to processing of linguistic information, especially syntax. It is a dynamical manifestation of Chomsky’s language organ, as it were • An appropriate and rather widespread connectivity pattern of the immature human brain renders it a potential habitat for the emerging language amoeba. • This condition does not require too many altered (probably regulatory) genes, but there are great risks involved, which make this “major transition” difficult indeed.

  30. Variation and selection in neural development • Changeux’s version • There is vast overproduction of synapses • Transient redundancy is selectively eliminated according to functional needs • The statistics and the pruning rules for the network architecture are under genetic control

  31. The structure of the visual system Partial crossing at the chiasm allows for stereoscopic vision

  32. Development of the columns of ocular dominance • The initial overlap decreases with time • Visual input is NECESSARY for columnar development

  33. Genes and visual input make up for normal vision • Synapses are pruned during development • A blindfolded eye does not send sensory information to the cortex • It’s column shrinks to negligible size • Reversible within the CRITICAL PERIOD

  34. The FOXP2 gene is mutant in a family with SLI • SLI: specific language impairment • In the KE family the mutation is a single autosomal dominant allele • Another individual has one copy deleted • TWO intact copies must be there in humans! • The mutation affects morphosyntax: Yesterday I went to the church

  35. Possible regulatory modes of the FOXP2 gene

  36. Interpreting the nature of SLI-related conditions • Sometimes SLI affects specifically grammar • Sometimes if affects other linguistic functions • Sometimes several other functions are affected • Outcome must depend on the region of expression of the (genetic) disturbance in the developing brain

  37. Nucleotide substitutions in the FOXP2 gene • Bars are nucleotide substitutions • Grey bars indicate amino acid changes • Likely to have been recent target of selection

  38. Coevolution of the language and the brain • An old idea (Wilson): increased brain size leads to more complex behaviour • Which in turn, due to increased environmental complexity, selects for increased brain size • Another crucial component: genetic assimilation Rapoport’ scheme applied to language

  39. One method of finding out (within ECAgents) • Simulated dynamics of interacting agents • Agents have a “nervous system” • It is under partial genetic control • Selection is based on learning performance for symbolic and syntactical tasks • If successful, look and reverse engineer the emerging architectures

  40. Between linguistic input and output…

  41. Transmission dynamics in simulated agents

More Related