1. SYNTAX 5 NOV 18, 2015 – DAY 35 Brain & Language LING 4110-4890-5110-7960 NSCI 4110-4891-6110 Fall 2015

2. Course organization Schedule: http://www.tulane.edu/~howard/BrLg/t1-Intro.html#schedule-of- topics http://www.tulane.edu/~howard/BrLg/t1-Intro.html#schedule-of- topics Today's chapter: http://www.tulane.edu/~howard/BrLg/t19-aIFG.html Fun with https://www.facebook.com/BrLg15/https://www.facebook.com/BrLg15/ Quiz before Thanksgiving will be in class & on Blackboard. 11/18/15Brain & Language - Harry Howard - Tulane University 2

3. Grades Q1Q2Q3Q4Q5Q6Q7 MIN 6554734 AVG 9.08.8 8.49.27.58.7 MAX 10 11/18/15Brain & Language - Harry Howard - Tulane University 3

4. COMBINATORIAL NET 2 11/18/15Brain & Language - Harry Howard - Tulane University 4

5. The lexical interface 11/18/15Brain & Language - Harry Howard - Tulane University 5

6. Models of sentence processing Traditional generative model A separate mental module parses sentences just like we just did. Lexical access happens first. Then one syntactic hypothesis is considered at a time. There is no influence of meaning. More recent interactive model There is no separate module for parsing Lexical access, syntactic structure assignment, and meaning assignment happen at the same time (in parallel). Several syntactic hypotheses can be considered at a time. 11/18/15Brain & Language - Harry Howard - Tulane University 6 How to decide? On-line processing

7. Two types of processing on-line Happens in real time. Instructions for an experiment to test it: You will read a sentence, one word at a time. Push a key after each word. off-line Happens after the fact. Instructions for an experiment to test it: You will read a sentence. Point to the picture that describes it best. 11/18/15Brain & Language - Harry Howard - Tulane University 7

8. Working memory & syntax 11/18/15Brain & Language - Harry Howard - Tulane University 8 Left-to-right solution of arithmetic 1 + 1 + 1 = ? (1 + 1) + 1 = ? 2 + 1 = 3 Left-to-right parsing of a sentence. [ S [ NP a cat] [ VP is [ PP on [ NP the couch]]]] S NP a cat VP V is PP on the couch

9. Working memory span or capacity The amount of material that you can keep on your ‘scratch pad’ is known as your working memory span or capacity. How much is it? Miller’s number: 7 ± 2 It varies a little from person to person and even from domain to domain in the same person. That’s the meaning of the “± 2” Working memory span can be impaired in brain injury. It has recently been shown to be correlated with fluid intelligence. 11/18/15Brain & Language - Harry Howard - Tulane University 9

10. The working memory needed for parsing … … is part of a general purpose working memory Individual differences in working memory are implicated in strategies for understanding complex spoken sentences. … constitutes its own specialized store of working memory. Some patients who share severe deficits of general purpose working memory are still able to understand complex spoken sentences. Individual differences in working memory are usually not implicated in on-line language understanding. 11/18/15Brain & Language - Harry Howard - Tulane University 10

11. SYNTAX 4 Sentence comprehension and syntactic parsing 11/18/15Brain & Language - Harry Howard - Tulane University 11

12. Syntax vs. pragmatics: Ferreira & Clifton Self-paced reading (on-line) task Sentence Relative clause SubjectLatency at by 1. The evidence examined by the lawyer shocked the jury. reducedinanimatesame as 3 2. The evidence that was examined by the lawyer shocked the jury. unreducedinanimatequicker than 1 3. The defendant examined by the lawyer shocked the jury. reducedanimatesame as 1 4. The defendant that was examined by the lawyer shocked the jury. unreducedanimatequicker than 3 11/18/15Brain & Language - Harry Howard - Tulane University 12 The fact that there is no garden path at by in (3) shows that syntax can perform the parse without access to pragmatics.

13. Just & Carpenter Low reading span Latency at by unreduced relative clause reduced relative clause inanimate subject ~450 ms~500 ms animate subject ~450 ms~500 ms High reading span Latency at by 11/18/15Brain & Language - Harry Howard - Tulane University 13 unreduced relative clause reduced relative clause inanimate subject ~350 ms~400 ms animate subject ~425 ms~475 ms Same as before: no competition from pragmatics to confuse (and slow down) syntactic parse Different: latency is indeed longer in bottom cell than top cell of reduced relative clause > pragmatics creates a garden path

14. Why? ‘Cognitive capacity’ Low span readers only have enough capacity to process syntactic cues; nothing is left over to process pragmatics > modular processing (syntax first). High span readers have enough capacity to process syntactic cues and pragmatics > interactive processing (all cues considered simultaneously). 11/18/15Brain & Language - Harry Howard - Tulane University 14

15. Syntactic complexity How about these sentences? 8a) The dog chased the cat. 8b) The cat hunted the rat. 8c) The rat nibbled the cheese. 9) The rat the cat hunted nibbled the cheese. 10) The rat the cat the dog chased hunted nibbled the cheese. 11/18/15Brain & Language - Harry Howard - Tulane University 15

16. Center embedding 11/18/15Brain & Language - Harry Howard - Tulane University 16 9) The rat the cat hunted nibbled the cheese. The rat which the cat hunted nibbled the cheese. 10) The rat the cat the dog chased hunted nibbled the cheese. The rat which the cat which the dog chased hunted nibbled the cheese.

17. How might this be processed? 11/18/15Brain & Language - Harry Howard - Tulane University 17 thematic role for ‘the rat’ thematic role for ‘the cat’ thematic role for ‘the dog’ The parser encounters … the rat > look for a predicate to supply a thematic role … the cat > wait, put the previous search on hold & look for another predicate to supply a thematic role … the dog > wait, put the previous search on hold & look for yet another predicate to supply a thematic role … Ok, now I am lost. push-down stack

18. Interim conclusion The limit on center embedded is 2. Given that Miller’s number is much larger, it would appear that there is a working memory specialized for parsing. 11/18/15Brain & Language - Harry Howard - Tulane University 18

19. ‘Edge’ embedding does not create this problem 11/18/15Brain & Language - Harry Howard - Tulane University 19 i) The dog chased the cat that hunted the rat that nibbled the cheese. ii) The dog that chased the cat that hunted the rat that nibbled the cheese was a dachshund.

20. Thinking about sentences, and science 1. Mary bought a book for John. The direct object THEME follows the verb in English. 2. Which book did Mary buy for John? The direct object THEME follows the verb in English or precede its clause when it is introduced by which. 3. John asked Mary about a student. TOPIC is the object of the preposition about. 4. Which student did John ask Mary about? TOPIC is the object of the preposition about, or it precedes its clause when it is introduced by which. Is adding "it precedes its clause when it is introduced by which" a good idea? 11/18/15Brain & Language - Harry Howard - Tulane University 20

21. Generalization You should have gotten the idea that every statement that is made about NPs in English must be duplicated to take into account questions with which. But clefting requires a tripling of statements about NPs: This book is what Mary bought for John. Leprechauns is what John asked Mary about. And there are even more constructions that require even more duplication. Is this a good way to describe the grammar of English? NO! because we lose track of perfectly good generalizations like the direct object follows the verb or THEME is usually the direct object. Is there a principle of science that can help us out here? 11/18/15Brain & Language - Harry Howard - Tulane University 21

22. Leprechauns! Think of an explanation for something: 1. The Earth spinning on its axis makes day and night. 2. The Earth spinning on its axis or leprechauns pushing it, makes day and night. 3. Rain falls when water condenses in the atmosphere. 4. Rain falls when water condenses in the atmosphere or leprechauns piss from clouds. Does adding leprechauns to all our explanations make them better? 11/18/15Brain & Language - Harry Howard - Tulane University 22

23. Ockham’s razor, simplicity, economy lex parsimoniae Ockham’s razor is a principle that generally recommends selecting from among competing hypotheses the one that makes the fewest new assumptions. Einstein-ish: “Make things as simple as possible, but not simpler.” 11/18/15Brain & Language - Harry Howard - Tulane University 23

24. Back to our sentences The sentences and their leprechauns a. Mary bought a book for John. b. Which book did Mary buy for John? c. John asked Mary about a student. d. Which student did John ask Mary about? How to get rid of the leprechauns a. Mary bought a book for John. b. Which book i did Mary buy ____ i for John? c. John asked Mary about a student. d. Which student i did John ask Mary about ____ i ? (b, d) are called filler-gap constructions, though the gap is also called a trace. 11/18/15Brain & Language - Harry Howard - Tulane University 24

25. Final project Improve a Wikipedia article about any of the topics mentioned in class or any other topic broadly related to neurolinguistics. Write a short essay explaining what you did and why you did it. Print the article before you improve it, highlighting any subtractions. Print the article after you improve it, highlighting your additions. 11/18/15Brain & Language - Harry Howard - Tulane University 25

26. NEXT TIME More syntax 11/18/15Brain & Language - Harry Howard - Tulane University 26