Word semantics 3 DAY 28 – Nov 1, 2013

1. Word semantics 3DAY 28 – Nov 1, 2013 Brain & Language LING 4110-4890-5110-7960 NSCI 4110-4891-6110 Harry Howard Tulane University

2. Brain & Language - Harry Howard - Tulane University Course organization • The syllabus, these slides and my recordings are available at http://www.tulane.edu/~howard/LING4110/. • If you want to learn more about EEG and neurolinguistics, you are welcome to participate in my lab. This is also a good way to get started on an honor's thesis. • The grades are posted to Blackboard.

3. Brain & Language - Harry Howard - Tulane University Review

4. Brain & Language - Harry Howard - Tulane University Linguistic model, Fig. 2.1 p. 37 Discourse model Semantics Sentence level Syntax Sentence prosody Word level Morphology Word prosody Segmental phonology perception Segmental phonology production Acoustic phonetics Feature extraction Articulatory phonetics Speech motor control INPUT

5. Brain & Language - Harry Howard - Tulane University Hierarchy of categories furniture | chair | bench domain-level | basic/prototype | subordinate

6. Brain & Language - Harry Howard - Tulane University Basic is special • Response Times: in which queries involving a prototypical members (e.g. is a robin a bird) elicited faster response times than for non-prototypical members. • Priming: When primed with the higher-level (superordinate) category, subjects were faster in identifying if two words are the same. Thus, after flashing furniture, the equivalence of chair-chair is detected more rapidly than stove-stove. • Exemplars: When asked to name a few exemplars, the more prototypical items came up more frequently.

7. Brain & Language - Harry Howard - Tulane University Basic is really special • It is the highest level at which a single mental image can represent the entire category (you can’t get a mental image of vehicle or furniture). • It is the highest level at which category members have a similarly perceived overall shape. • It is the highest level at which a person uses similar motor actions for interacting with category members. • It is the level at which most of our knowledge is organized.

8. Brain & Language - Harry Howard - Tulane University Early and late visionearly vision is beneath the surface; late vision is on it

9. Constructivist approach ventral ~ identification the stimulation is inherently insufficient, necessitating an “intelligent” perceptual system that relies on inference perception is indirect/multistage process between stimulation and percept memory, stored schemata, and past experience play an important role in perception excels at analyzing the processes and mechanisms underlying perception Ecological approach dorsal ~ visual control of motor behavior the information in the ambient environment suffices and is not equivocal, and thus, no “mental processes” are needed to enable the pick-up of relevant information perception is direct/single-stage process no role for memory or related phenomena excels at the analysis of the stimulation reaching the observer affordances Brain & Language - Harry Howard - Tulane University Norman (2002)

10. Brain & Language - Harry Howard - Tulane University Lexical semantics 3 Visual object identification

11. Brain & Language - Harry Howard - Tulane University Category-specific deficits

12. Brain & Language - Harry Howard - Tulane University Do you see any difference between (a) and (b)?

13. Brain & Language - Harry Howard - Tulane University Category-specific semantic impairmentsFigure 11.1 concrete (picture-able) abstract 3:1 animate inanimate animals plants ? ? tools transport fruit & veggie | apple banana processed food | pizza cider musical instrument | piano drum wild | lion shark domestic | cat goldfish inedible | tree flower hammer pencil car bike belief shame

14. Brain & Language - Harry Howard - Tulane University The anatomy of object processing: The role of anteromedial temporal cortex Bright, Moss, Stamatakis & Tyler (2005)

15. Brain & Language - Harry Howard - Tulane University Semantic feature assignmentTable 11.2 Semantic similarity scoresTable 11.3

16. Brain & Language - Harry Howard - Tulane University Features as a network 1excitation woman man boy human female mature colt girl Activation of ‘man’ will wind up activating ‘female’, which is a contradiction. mare

17. Brain & Language - Harry Howard - Tulane University Features as a network 2excitation, inhibition woman man boy human female mature colt girl mare Activation of ‘man’ will still wind up activating ‘female’, but inhibition will now turn it off.

18. Brain & Language - Harry Howard - Tulane University In cortex, long-distance connections are excitatory, while short-distance connections are inhibitory. Features as a network 3excitation, inhibition woman man boy human female mature colt girl mare Activation of ‘man’ will wind up activating ‘female’, but inhibition of ‘woman’ will turn it off.

19. Brain & Language - Harry Howard - Tulane University Correlated feature theory • The way we go from feature representation to neural organization is by hypothesizing that correlation among the features of an object leads to mutually reinforcing activation (co-activation) in the features' neural representation • shared properties are inter-correlated and so become strongly activated and less susceptible to damage, • distinctive properties are weakly correlated and so become weakly activated and more susceptible to damage. • Performance depends on task • If the task requires access to the distinctive features of an object, then a deficit for animates will emerge, due to the lesser degree of correlation among their distinctive features. • So the CSA proposes that category-specific deficits develop • from damage to a unitary, distributed semantic system, • not from damage to anatomically distinct, content-specific stores

20. Brain & Language - Harry Howard - Tulane University Feature network for animatesexcitation,mutually reinforcing activation (excitation) camel crocodile head hump eyes zebra bill torso stripes legs duck penguin

21. Brain & Language - Harry Howard - Tulane University Inanimate vs. animate, side by side Inanimate Animate many overlapping and inter-correlated features (legs, eyes, teeth), few distinctive features (mane, hump, pouch), and they are only weakly correlated with one another. ∴ animate concepts are easy to confuse with one another. • few overlapping and inter-correlated features, • relatively more distinctive features, • and they tend to be more strongly correlated with one another. • ∴ inanimate concepts are less easy to confuse with one another.

22. Brain & Language - Harry Howard - Tulane University Problem • Correlated feature theory cannot account for other patterns of impairment, such as cases in which artifacts are more poorly identified than living things.

23. Brain & Language - Harry Howard - Tulane University Sensory/functional theory • Knowledge of objects organized into: • networks of sensory features: form, motion, color, taste, etc., and • networks of functional features: how, when, and where the object is typically used. • A CSSD arises when one of these networks is disrupted • animates are mostly comprised of sensory features; • inanimatesare mostly comprised of functional features. (??)

24. Brain & Language - Harry Howard - Tulane University Domain-dependent hypothesis • The brain has evolved dedicated neural machinery for recognizing and responding to certain categories of objects that have high survival significance: • face recognition, predator detection, food identification • These categories are recognized on the basis of prototypes: • A given exemplar (instance) is matched to the best prototype. • They are modular, but not necessary localized to a single region (i.e. they could be distributed networks).

25. Brain & Language - Harry Howard - Tulane University Example of patient FAV • Read about him/her and the explanation(s) for his/her deficit, Ingram pp. 235-8.

26. Brain & Language - Harry Howard - Tulane University NEXT TIME Q8 More word semantics