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What is language? What is it for?
• Rapid efficient communication– (as such, other kinds of communication might be
called language for our purposes and might share underlying neural mechanisms)
• Two broad but interacting domains:– Comprehension– Production
Speech comprehension
• Is an auditory task – (but stay tuned for the McGurk Effect!)
• Is also a selective attention task– Auditory scene analysis
• Is a temporal task– We need a way to represent both frequency
(pitch) and time when talking about language -> the speech spectrogram
Speech comprehension
• Is also a selective attention task– Auditory scene analysis
• Which streams of sound constiutute speech?
• Which one stream constitutes the to-be-comprehended speech
• Not a trivial problem because sound waves combine prior to reaching the ear
Speech comprehension
• Is a temporal task– Speech is a time-varying signal
– It is meaningless to freeze a word in time (like you can do with an image)
– We need a way to consider both frequency (pitch) and time when talking about language -> the speech spectrogram
What forms the basis of spoken language?
• Phonemes
• Phonemes strung together over time with prosody
What forms the basis of spoken language?
• Phonemes = smallest perceptual unit of sound
• Phonemes strung together over time with prosody
What forms the basis of spoken language?
• Phonemes = smallest perceptual unit of sound
• Phonemes strung together over time with prosody = the variation of pitch and loudness over the time scale of a whole sentence
What forms the basis of spoken language?
• Phonemes = smallest perceptual unit of sound
• Phonemes strung together over time with prosody = the variation of pitch and loudness over the time scale of a whole sentence
To visualize these we need slick acoustic analysis software…which I’ve got
Is speech comprehension therefore an image matching problem?
• If your brain could just match the picture on the basilar membrane with a lexical object in memory, speech would be comprehended
Problems facing the brain
•Acoustic - Phonetic invariance –says that phonemes should match one and only one pattern in the spectrogram
–This is not the case! For example /d/ followed by different vowels:
Problems facing the brain
• The Segmentation Problem:– The stream of acoustic input is not physically segmented into discrete
phonemes, words, phrases, etc.
– Silent gaps don’t always indicate (aren’t perceived as) interruptions in speech
Problems facing the brain
• The Segmentation Problem:– The stream of acoustic input is not physically segmented into discrete
phonemes, words, phrases, etc.
– Continuous speech stream is sometimes perceived as having gaps
How (where) does the brain solve these problems?
– Note that the brain can’t know that incoming sound is speech until it first figures out that it isn’t !?
– Signal chain goes from non-specific -> specific
– Neuroimaging has to take the same approach to track down speech-specific regions
Functional Anatomy of Speech Comprehension
• low-level auditory pathway is not specialized for speech sounds
• Both speech and non-speech sounds activate primary auditory cortex (bilateral Heschl’s Gyrus) on the top of the superior temporal gyrus
Functional Anatomy of Speech Comprehension
• Which parts of the auditory pathway are specialized for speech?
• Binder et al. (2000)– fMRI– Presented several kinds of stimuli:
• white noise• pure tones• non-words• reversed words• real words
These have non-word-like acoustical properties
These have word-like acoustical properties but no lexical associations
word-like acoustical properties and lexical associations
Functional Anatomy of Speech Comprehension
• Relative to “baseline” scanner noise
– Widespread auditory cortex activation (bilaterally) for all stimuli
– Why isn’t this surprising?
Functional Anatomy of Speech Comprehension
• Statistical contrasts reveal specialization for speech-like sounds– superior temporal gyrus– Somewhat more prominent on left side
Functional Anatomy of Speech Comprehension
• Further highly sensitive contrasts to identify specialization for words relative to other speech-like sounds revealed only a few small clusters of voxels
• Brodmann areas– Area 39– 20, 21 and 37– 46 and 10