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P10. LA NEUROSINTAXIS 11 ABR 2011 – DÍA 36. Neurolingüística del español SPAN 4270 Harry Howard Tulane University. ORGANIZACIÓN DEL CURSO. http://www.tulane.edu/~howard/SPAN4130-Neurospan/ El curso es apto para un electivo en neurociencia.

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P10

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  1. P10 SPAN 4130 - Harry Howard - Tulane University

  2. LA NEUROSINTAXIS11 ABR 2011 – DÍA 36 Neurolingüística del español SPAN 4270 Harry Howard Tulane University

  3. ORGANIZACIÓN DEL CURSO • http://www.tulane.edu/~howard/SPAN4130-Neurospan/ • El curso es apto para un electivo en neurociencia. • Neurolinguistics and linguistic aphasiology está en reserva en la biblioteca. • Human Research Protection Program • http://tulane.edu/asvpr/irb/index.cfm • Before beginning research at Tulane University, all research personnel must complete the CITI Training Program; this can be completed at www.citiprogram.org. SPAN 4130 - Harry Howard - Tulane University

  4. REPASO SPAN 4130 - Harry Howard - Tulane University Ha sido la prueba.

  5. NEUROSINTAXIS SPAN 4130 - Harry Howard - Tulane University

  6. EEG • Electroencephalography (EEG) is the measurement of electrical activity produced by the brain as recorded from electrodes placed on the scalp. SPAN 4130 - Harry Howard - Tulane University

  7. SCALP (CUERO CABELLUDO) EEG • Scalp EEG is collected from tens to hundreds of electrodes positioned on different locations at the surface of the head. • EEG signals (in the range of millivolts) are amplified and digitalized for later processing. SPAN 4130 - Harry Howard - Tulane University

  8. ERP (POTENCIA EVOCADA) • Event-related brain potentials (ERPs) are positive and negative voltage fluctuations (or components) in the ongoing EEG that are time-locked to the onset of a sensory, motor, or cognitive event. • ERPs reflect brain activity that is specifically related to some stimulus or other event. • This activity cannot be directly observed in the EEG • the EEG is a composite of simultaneously occurring brain activity • it doesn't reflect just the activity associated with the event of interest • In other words, the "signal" (the brain response to some event) is swamped by the "noise" (the brain activity that is unrelated to that event). SPAN 4130 - Harry Howard - Tulane University

  9. SIGNAL AVERAGING • The solution to this problem is to present not just one instance of the event of interest, but many instances. • Epochs of brain activity, each one time-locked to the onset of an event, are then averaged together. • The "random" activity washes out during averaging, whereas the brain activity of interest - namely, what is constant over presentations of the event of interest - stays in the signal. • Through this signal-averaging procedure, it is possible to isolate the brain response that is specifically elicited in response to some event of interest. SPAN 4130 - Harry Howard - Tulane University

  10. ERP PROCEDURE SPAN 4130 - Harry Howard - Tulane University

  11. ERP COMPONENTSNAMED BY THEIR POLARITY AND PEAK LATENCY (IN MS) SPAN 4130 - Harry Howard - Tulane University

  12. INVERSE SOLUTION • Ideally, one would like to identify the precise neural sources that generate the ERPs (known as the "inverse solution"). • Unfortunately, the inverse solution is impossible to compute with certainty, because any given scalp distribution could, in principle, be generated by any number of source configurations within the brain. • However, researchers have developed powerful tools that provide good estimates of these neural sources, given some reasonable assumptions. SPAN 4130 - Harry Howard - Tulane University

  13. LORETA • One such method is known as "LORETA", which provides an estimate of the current distribution throughout the entire 3-dimensional space within the brain. • An example of a LORETA solution, mapped onto a normalized brain space, is provided below. SPAN 4130 - Harry Howard - Tulane University

  14. THE LINGUISTIC ERPS SPAN 4130 - Harry Howard - Tulane University Friederici (2002)

  15. NEUROCOGNITIVE MODEL OF AUDITORY SENTENCE PROCESSING SPAN 4130 - Harry Howard - Tulane University

  16. PHASES OF AUDITORY SENTENCE PROCESSING • The temporal scale along the bottom comes from ERP (and MEG) studies, which Friederici divides into three main phases, initiated by a ‘zeroth’ phase of phonological processing: • N100: phase 0, phonological processing • ELAN (early left anterior negativity): phase 1, syntactic structure building • N400/LAN: phase 2, establish semantic relations • P600: phase 3, syntactic repair SPAN 4130 - Harry Howard - Tulane University

  17. Brodmann areas in the left hemisphere Inferior frontal gyrus (IFG) = green, Superior temporal gyrus (STG) = red Middle temporal gyrus (MTG) = blue SPAN 4130 - Harry Howard - Tulane University

  18. The ELAN SPAN 4130 - Harry Howard - Tulane University Early left anterior negativity

  19. INTRODUCTION • The first phase (100-300 ms) represents the time window in which the initial syntactic structure is formed on the basis of information about word category. • For instance, the insertion of a contracted preposition+article between an auxiliary verb and past participle in German, produces a significantly higher ERP amplitude during this period than the same sentence without the intrusive material • Die Gans wurde (*im) gefüttert. • The goose was (*in the) fed. SPAN 4130 - Harry Howard - Tulane University

  20. PHRASES CAN BE PUT TOGETHER TO FORM SENTENCES • Striped orange cats slept soundly. • Colorless green ideas slept furiously. SPAN 4130 - Harry Howard - Tulane University

  21. SINCE THE MEANING DOESN’T MATTER, WE CAN WRITE WORD-ORDER RULES BASED ON CATEGORIES • A noun phrase (NP) consists of … ? • An optional determiner followed by one or more adjectives followed by a noun • NP  (Det) Adj (Adj) N • A verb phrase (VP) consists of … ? • A verb followed by an adverb • VP  V Adv • A sentence consists of … ? • A noun phrase followed by a verb phrase • S  NP VP SPAN 4130 - Harry Howard - Tulane University

  22. BUT SUCH A REAL GRAMMAR IS FAIRLY COMPLEX • Perhaps too complex for direct study • They can teach subjects a simplified set of rules from a language that they do not know. • But even better is to teach subjects an artificial grammar (the syntactic analog of a nonsense word) which have easy-to-control properties. SPAN 4130 - Harry Howard - Tulane University

  23. A REGULAR GRAMMAR • The rules • S  Xab • X  Xab • X  ab • How would you generate the string “ababab”? • This language is known as (ab)n. • From fMRI we know that violations of this grammar activate BA 44 and BA 6. • The English grammar that we made up is also of this type. • So are the violations of German grammar. SPAN 4130 - Harry Howard - Tulane University

  24. A CONTEXT-FREE GRAMMAR • The rules • S  aXb • X  aXb • X  ab • How would you generate the string “aaabbb”? • How would you generate the string “ababab”? • This language is known as anbn. • From fMRI we know that violations of this grammar activate BA 44, but not BA 6. SPAN 4130 - Harry Howard - Tulane University

  25. EL PRÓXIMO DÍA SPAN 4130 - Harry Howard - Tulane University Más neurosintaxis

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