Transcript ppt - University of Rochester

Language and the brain
Rajeev Raizada
Dept. of Brain & Cognitive Sciences
[email protected]
raizadalab.org
Language and the brain:
why bother with brain stuff in the first place?
Key language areas, and lesion deficits
Lots of interactive brain areas
• It’s not just a couple of areas on the left
Interpreting brain activation:
• Who cares which bit of the brain lights up?
• We want brain imaging to tell us about
linguistic information processing, or linguistic
representations
Language areas in the brain
Some brain areas are specialised for language
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Broca's area: speech production
Wernicke's area: speech perception
On the left side of the brain (in 95% of people)
This is pretty much the only left-brain / right-brain saying that is
actually true
What does "specialised for language" actually mean?
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If you lose these areas, you lose language
When you use language, you use those areas
BUT: That does not mean that they only do language
E.g. Broca's area may be involved in music perception
Broca's area: crucial for speech production
Paul Broca (1861): patient "Tan"
• Severe deficit in speech production: could only say "tan"
• Good language comprehension
Tan's brain: lesion (injury) in left frontal cortex
Auditory cortex and Wernicke's area
Auditory cortex: all sounds pass into here
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Mostly specialised for low-level features, e.g. raw frequency
Bilateral (on both left and right sides of the brain)
Wernicke's area (Carl Wernicke, 1874)
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Patient with very poor speech comprehension
Good speech production
Lesion on left side, just behind auditory cortex
Specialised for processing "higher level" sounds: speech
Auditory cortex and Wernicke's area
From http://www.physiology.wisc.edu/neuro524/
Language areas in the brain
From University of Washington's Digital Anatomist project
An example of Broca's aphasia in the news:
Gabby Giffords
http://www.youtube.com/watch?v=rx3nfUKvrZ8
Start at 2mins
Wernicke's aphasia
Deficit of comprehension, not production.
Fluent speech, but lacking coherent meaning
https://www.youtube.com/watch?v=aVhYN7NTIKU
There's more to language in the brain
than just Broca's and Wernicke's
Friederici, A. D. (2012). The cortical language circuit: from
auditory perception to sentence comprehension. Trends in
cognitive sciences, 16(5), 262-268.
The claim "language is on the left"
is a total over-simplification
Specht, K. (2013).
Mapping a
lateralization
gradient within the
ventral stream for
auditory speech
perception.
Frontiers in human
neuroscience, 7.
The claim "language is on the left"
is a total over-simplification
Peelle, J. E. (2012).
The hemispheric
lateralization of
speech processing
depends on what
"speech" is: a
hierarchical
perspective.
Frontiers in human
neuroscience, 6.
What does brain imaging do,
and what can it tell us?
And what does it not tell us?
Problem:
This picture does not show any
neural mechanisms
MRI
Magnetic Resonance Imaging
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Takes a 3D picture of the inside of
body, completely non-invasively
One picture, just shows the structure
http://www.coppit.org/brain/
fMRI
functional Magnetic Resonance Imaging
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Shows brain activity (indirectly)
Takes a series of pictures over time,
e.g. one every three seconds
The “f” in fMRI means functional, i.e.
you get a movie of brain function, not
a still image of brain structure
http://www.fmrib.ox.ac.uk/image_gallery/av/
What are we actually measuring with fMRI?
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An MRI machine is just a big magnet (30,000 times
stronger than Earth's magnetic field)
The only things it can measure are changes in the
magnetic properties of things inside the magnet: in this
case, your head
When neurons are active, they make electrical activity,
which in turns creates tiny magnetic fields
BUT far too small for MRI to measure (100 million
times smaller than Earth's magnetic field)
So, how can we measure neural activity with MRI?
What makes fMRI possible:
Don't measure neurons, measure blood
Two lucky facts make fMRI possible
• When neurons in a brain area become active,
extra oxygen-containing blood gets pumped to
that area. Active cells need oxygen.
• Oxygenated blood has different magnetic
properties than de-oxygenated blood.
Oxygenated blood gives a bigger MRI signal
End result: neurons fire => MRI signal goes up
This fMRI method is known as BOLD imaging:
Blood-Oxygenation Level Dependent imaging.
Invented in 1992.
But neurons do the real work, not blood.
Neurons represent and process information
Individual nerve cells (neurons) represent information
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Sensitive to “preferred stimuli”, e.g. /ba/
These stimuli make them active
Firing activity: send electrical spikes to other neurons
/ba/
/ba/-sensitive neuron
Populations of neurons
process information together
Information is distributed across
large populations of neurons, and
across brain areas
There's no “grandmother cell”:
the one single cell that
recognizes your grandmother
To really understand the brain,
we'd need somehow to read the
information from millions of
individual neurons at once!
The basic design of an fMRI experiment
Aim:
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Find which brain areas are active during a given task
E.g. discriminating speech sounds, producing speech
Typical design:
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Present blocks, e.g. 30s of task, 30s of rest
Measure fMRI activity regularly every few seconds
Look for brain areas which are more active during the
task periods, compared to rest periods
Example time-courses
Time-course of task versus rest periods
Task
Rest
Task
Rest
Rest
MRI signal from voxel that correlates well with task: Active
Signal from voxel that does NOT correlate with task: Inactive
TIME
What are those little coloured blobs, actually?
Colour represents
statistical significance of
how well the voxel's
activation correlates with
the task.
The hi-res grayscale
anatomical picture
underneath the coloured
blobs is a completely
different type of image,
from a different type of
scan. Shows the anatomy
at the spot where the
significant voxel's timecourse was recorded.
The key problem
Interpreting what brain activation means
Reverse inference
Why it's hard to infer processing from activation:
Brain areas are multi-functional
???
Attention
Intention
Spatial reasoning
Numerical magnitude
Parietal cortex
A famously horrible example
“You love your iPhone, literally”
http://www.nytimes.com/2011/10/01/opinion/you-love-your-iphone-literally.html
“But most striking of all was the flurry of activation in the insular
cortex of the brain, which is associated with feelings of love and
compassion. The subjects' brains responded to the sound of
their phones as they would respond to the presence or proximity
of a girlfriend, boyfriend or family member.
In short, the subjects didn't demonstrate the classic brain-based
signs of addiction. Instead, they loved their iPhones.”
An example of reverse inference
from everyday life
If you have Ebola, you will start off by having
flu like symptoms
“I am having flu like symptoms”
“Oh no! I must have Ebola!”
Interpreting brain activation
Who cares which bit of the brain lights up?
We want brain imaging to tell us about linguistic
information processing, or linguistic representations
Example study:
Does a person’s brain have well-structured
representations for performing a given language task?
Well-structured representations for doing a task,
versus poorly-structured
Sumo wrestlers
Basketball
Students
Weight
Weight
Faculty
players
Height
Height
Wanted:
• One single task, one set of stimuli
• BUT: Some people can do task, other people cannot
Different languages carve up acoustic space differently:
/ra/ and /la/ in English and Japanese speakers
Raizada et al., Cerebral Cortex (2010)
Formants and perceptual discriminability
Raizada et al.,
Cerebral Cortex
(2010)
Prediction: fMRI patterns for /ra/ and /la/ are
more separable in the brains of
English speakers than in Japanese speakers
English speakers:
Can perceive /r/-l/ distinction
fMRI patterns are separable
/ra/
/ra/
/ra/
/ra/
/ra/
/la/
/ra/
Japanese speakers:
Cannot perceive /r/-l/ distinction
fMRI patterns are not separable
/ra/
/la/
/la/
/ra/
/ra/
/la/
/la/
/la/
/la/
/ra/ /la/ /ra/
/la/
/la/
/la/
/ra/
/ra/
/ra/
/la/
/la/
/la/
/ra/
/la/
/ra/
/la/
Will neural pattern separability
match perceptual discriminability?
Predicted pattern-separability, if it matches perception:
English: F3-difference > F2-difference
Japanese:
F3-difference = F2-difference
fMRI pattern separability contrast:
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F3-separability minus F2-separability
Is this neural difference greater for English than Japanese?
Key point: the classifier doesn't get told anything about
people's behaviour, or about who is English or Japanese
Individual differences:
Neural pattern separability predicts behavioural performance
Raizada et al.,
Cerebral
Cortex (2010)
Correlation after partialling out effects of group membership: r = 0.389, p < 0.05
Summary
The brain is astonishingly good at processing language
• Nobody understands how it achieves this
• But we do have some exciting leads
Lots of brain areas, all representing multiple types of
information, all communicating with each other
• Not just Broca’s and Wernicke’s areas
• Not just in the left hemisphere
Challenges for neuroscience
• What information processing tricks does the brain use?
• What representations does it use, how does it use them?