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Language & Brain
Why bother? What could we learn?
• something about how language works
• something about how the brain works
• nothing (interdisciplinary cross-sterilization)
Chomsky 1959
Two enduring ideas deriving from Gall
• Faculty psychology
The mind has a ‘parts list.’
• Experience-dependent plasticity
Using the parts changes
their neuronal realization.
Phineas Gage, 1848
Before: responsible, well-
mannered, well-liked,
efficient worker, pious
After: capricious, impulsive,
irreverent, hypersexual
Damage involved VMPFC
Broca’s Area
“production”
“syntax”
Wernicke’s Are
“reception”
“semantics”
Visual system
(van Essen)
Auditory system
(Hackett)
The visual and auditory systems are highly articulated. Is there any a priori reason to believe
that language will be an order of magnitude simpler, captured by two brain areas?
Functional anatomy of speech perception.
Hickok & Poeppel 2007
Non-invasive
recording from
human brain
(Functional
brain imaging)
Positron emission
tomography
(PET)
Functional magnetic
resonance imaging
(fMRI)
Electro-
encephalography
(EEG)
Excellent spatial
resolution (<1 mm)
Limited temporal
resolution (~1sec)
Limited spatial
resolution (<1 cm)
Excellent temporal
resolution (<1msec)
Hemodynamic
techniques
Electro-magnetic
techniques
Magneto-
encephalography
(MEG)
D. Poeppel , A. Braun et al.
Language is not monolithic
Phonetics/phonology
sound structure
Morphology
word structure
Lexical semantics
word meaning
Syntax
sentence structure
Prosody
sentence melody
Compositional semantics
sentence meaning
Discourse
larger meaning scale
language-o-topy
The wave of the past
“Intuitive psychological organology ”
The wave of the present
“Cognitive psychological organology”
syntax
phonology
semantics
Linguistics Neuroscience
Fundamental elements of representation
distinctive feature dendrites, spines
syllable neuron
morpheme cell-assembly/ensemble
noun phrase population
clause cortical column
Fundamental operations on primitives
concatenation long-term potentiation
linearization receptive field
phrase-structure generation oscillation
semantic composition synchronization
?
?
Is there a future? Problems for interdisciplinarity and unification I
There is an absence of ‘linking hypotheses’ by which we explore how brain mechanisms
form the basis for linguistic computation.
Aligning the alphabets or primitives or atoms is a formidable challenge.
Is there a future? Problems for interdisciplinarity and unification II
Ontological Incommensurability Problem (neurolinguistics in principle):
The units of linguistic computation and the units of neurobio-
logical computation are incommensurable.
Therefore, an attempt at reduction makes no sense.
Why are there no linking hypotheses?
Granularity Mismatch Problem (neurolinguistics in practice):
Linguistic and neuroimaging studies of language operate
with objects of different granularity.
linguistics --- fine-grained distinctions
neuroscience --- broader conceptual distinctions
Neuroscience cannot succeed in seeking “syntax” (or “phonology”)
because syntax etc. are not monolithic but have many parts.
Poeppel & Embick, 2005
Is there a future? Problems for interdisciplinarity and unification III
Linguistics Neuroscience
distinctive feature dendrites, spines
morpheme cell-assembly/ensemble
noun phrase population
clause cortical column
concatenation long-term potentiation
linearization receptive field
phrase-structure generation oscillation
semantic composition synchronization
fractionate into
generic formal operations
segmentation
concatenation
comparison
recursion
identify basis for
generic formal operations
segmentation
concatenation
comparison
recursion
?
Desiderata for a model bridging neuronal mechanisms
and linguistic representation
x---y
yx
z
concatenation constituency recursion
Neurobiological mechanisms that can form the basis of elemental
steps involved in most linguistic computation:
Is there a future? Problems for interdisciplinarity and unification IV
This is the granularity - and level of abstractness - of operations
that can profitably be studied in animal research as well, doing
away with questions such as “are humans different or better or
higher, or not” and turning to the typical questions such as:
“How does this work?”
Putative primitives - the view on irreducible representations and operations
from semantics (Pietroski) and syntax (Hornstein)
• Variables, a way to link variables
• One-place predicates, thematic roles
• Operation with the power of conjunction and existential closure
• Concatenation (a-directional)
• Labeling: concatenate turns into one of its constituents
• Some mechanism (copy) to deal with positional specificity of variables
‘Unification Problem’
Marr’s computational approach
permits development of linking hypotheses
computational algorithmic implementational
How much can be gained by focusing only on localization by way of
imaging?
Not much, at this point - it is the ‘homework problem’, that is, an
important but ultimately uninteresting step from the point of view of
explanation.
Can we achieve unification by working on localization?
No! We need explicit linking hypotheses between well
characterized brain mechanisms and linguistic computation.
WRONG QUESTION: where are syntax/phonology/
semantics mediated?
RIGHT QUESTION: what kind of computations in the
brain form the basis of linguistic
representations and operations?
Is there a future? Problems for interdisciplinarity and unification V
xx yy
xxx yy
zzzz
zzz
ppppp
pppp
qqqq
qqq
oojjjoo
oooojj
ooooojjjj
There is localisation, but what is localized is tissue that executes specific
computations, such as, say, addition (xxx) or subtraction (zzz) or division (qq),
over representations (data structures) of certain types.
sss
sss
The cognitive faculties (the “parts”
of the human cognome) are not
monolithic but composed of multiple computational subroutines.
The wave of the past
“Intuitive psychological organology ”
The wave of the present
“Cognitive psychological organology”
syntax
phonology
semantics
The wave of the future
“Computational organology”
recursion
constituency
sequencing
linearization
Localization of generic
computational subroutines
÷÷÷
÷÷÷
! ! !"""
"""
[+ cons, -son] [-cons, +son] [+ cons, -son]
x xx
c ta
LAR/PHAR LAR/PHAR LAR/PHAR
[-cont] [-cont]
PLACE PLACEPLACE
GLOT
[-voice]
DORSAL [-ATR] DORSAL CORONAL
[-back, -high, +low]]
GLOT
[-voice] [+ant]
?
(a) (b)
(c)
(d)
phonological
primal sketch
Phase Patterns of Neuronal Responses Reliably
Discriminate Speech in Human Auditory Cortex
Huan Luo & David Poeppel
Single-unit responses robustly encode conspecific vocalizations
Machens et al., Nat. Neurosci. 2003
Grasshopper (peripheral auditory
neurons)
Narayan et al., J. Neurophys. 2006
Zebra Finch (Field L)
“Many natural sounds including vocal communication
sounds display striking time-varying structure over
multiple time scales”
“We demonstrate the existence of distinct time scales for
temporal resolution and temporal integration and explain
how they arise from cortical neural responses to complex
dynamic sounds.” [~10 ms and ~ 500 ms]
Materials:
Smith, Delgutte, and
Oxenham, Nature, 2002
Luo & Poeppel, Neuron, 2007
Theta phase has the sensitivity to discriminate based on single trials
Theta phase tracking displays the specificity to discriminate sentences
Luo & Poeppel, Neuron, 2007
Classification analysis
Luo & Poeppel, Neuron, 2007
A ~ 200 ms window analyzes the input signal -- The syllable as primitive
Distribution of intrinsic cortical rhythms
Combined EEG/fMRI recordings
N=12 + 8 subjects at rest (twice 20 min.)
EEG, 32 channels, continuous acquisition.
fMRI, 1.5 T and 3 T Siemens, sparse acquisition
No auditory input beyond the MRI scanner noise.
Analyses from central electrodes to observe
temporal asymmetries with minimal lateralization
bias.
Giraud et al. 2007, Neuron
3–6 Hz
0 50 100 150 200 250 300
0
5
0 50 100 150 200 250 3000
5
time [scan number]
Continuous EEG recording (20 min.)
Sparse fMRI acquisition (20 min.)
Re
gre
sso
rs
FF
T
po
wer
[10
10
uV
2]
3sgap1s
fMRI3s
gap1s
fMRI3s
gap1s
Segments of
EEG trace
Sequence of
fMRI acquisition
Raw dataEstimated data (raw data convolved with hemodynamic function)
Combined EEG/fMRI recordings: Approach
28 – 40 Hz
Giraud et al. 2007, Neuron
Mouth
Tongue
3-6 Hz EEG band
28-40 Hz EEG band
Heschl
Experiment 1 (1.5T) Experiment 2 (3T)
Group results: topography of theta and gamma
in premotor cortex
Giraud et al. 2007, Neuron
Motor constraints on speech (Frame/Content theory, MacNeilage and Davis, Current Opinion Neurobiol. 2001)
Mechanical properties of the speech apparatus (e.g.,spontaneous
oscillation frequency of the jaw) determine rhythmic properties of spoken
language (e.g. syllabic rate - theta rhythm)
Giraud et al. 2007, Neuron
Speech
analysis
Functional interactions between perceptualand motor speech systems: internal forward
model at time scales ‘of interest’
Motor output
Sensory feedbackEfference copies
Fine articulatory tuning
Three messages
1. Language is not monolithic.
(Even subroutines of language
comprehension, such as
speech perception, are highly
complex.) The constituent
elementary computations are
likely mediated by an array of
cortical areas.
2. MEG is a useful -- and
underutilized - tool to
investigate a range of issues
in cognitive neuroscience.
The data can provide an
interesting bridge to
questions of neural coding.
3. The phase of low frequency
responses (e.g. theta)
provides a sensitive (trial by
trial) neurophysiological
index of online processing
and can be used to assess
the ‘temporal granularity’ of
perceptual analysis (sliding
temporal window).
UQAM -- Origins of Language, 6/24/10
David Poeppel
NYU Psychology and Neural Science
http://psych.nyu.edu/clash/poeppellab.html
http://talkingbrains.blogspot.com/