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Ling 411 – 15
Right Hemisphere in Language Processing
Coarse and Fine Coding
Major nodes of
a hypothesized
functional word
web for a
manipulable
object:
Ignition from
speech input
T
M
C
PP
PA
PR
V
Ignition from
visual input
3
M
PP
T
3
4
PA
4
PR
C
2
3
V
1
1
Ignition from
tactile input
3
M
PP
T
1
C
4
PA
4
PR
3
2
3
V
1
Ignition from
conceptual
input
2
M
PP
T
2
3
PA
3
PR
C
2
1
2
V
1
RH Linguistic Functions
 Inference, Metaphor
 Coarse coding
 Music
Some findings w.r.t. RH speech perception
 Vowel qualities
 Intonation
 Tones in tone languages
Possible bases for RH/LH difference
 Higher ratio of white to gray matter in RH
• Therefore, higher degree of connectivity in RH
 Difference in dendritic branching
 Different density of interneurons
 Evoked potentials (EEG) are more diffuse
over the RH than over LH
Beeman 257
Anatomical differences between LH and RH
 Geschwind & Levitsky (1968)
• 100 brain specimens examined
• Planum temporale
•
 Larger in LH: 65%
 Larger in RH: 11%
 About the same, both sides: 24%
Correlates with shape of Sylvian fissure
 Shorter horizontal extent in RH
Goodglass 1993:60
Experiments (described by Beeman)
 Words presented to rvf-LH or lvf-RH
 RH more active than LH
• Synonyms
• Co-members of a category: table, bed
• Polysemy: FOOT1 – FOOT2
• Metaphorically related connotations
• Sustains multiple interpretations
 LH about same as RH
• Other associations: baby-cradle
 LH more active than RH
• Choose verb associated with noun
Patients with brain-damage
 Some patients with LH damage
• Can’t name fruits but can say that they are
fruits
 Patients with RH damage
• Impaired comprehension of metaphorical
•
statements
More difficulty producing words from a
particular semantic category than producing
words beginning with a particular letter (258)
Imaging studies
 When listening to spoken discourse,
cerebral blood flow increases in
• Wernicke’s area
• Broca’s area
• RH homologues of Wernicke’s and Broca’s areas
 More cerebral blood flow in RH when
subjects read sentences containing
metaphors than literal sentences
Experiments on speech perception
 Dichotic listening – normal subjects
• Right ear (i.e. LH) advantage for distinctions of
•
•
 Voicing
 Place of articulation
Left hear (RH) advantage for
 Emotional tone of short sentences
Sentences presented in which only intonation
could be heard
 RH advantage for identifying sentence type –
declarative, question , or command
Experiments on speech perception
 Split brain patients
• They hear a consonant
• Then written representations are presented
• ‘Point to the one you heard’
• rvf-LH exhibited strong advantage
Patients with right-brain damage
 Posterior RH lesions result in deficits in
interpreting emotional tone
 Anterior RH lesions abolish the ability to
control the production of speech intonation
Split-brain studies
 Isolated RH has ability to read single
words
• But not as fast nor as accurate as LH
• Ability declines with increasing word length
• Lexical context does not assist letter
identification
 In Japanese subjects
• RH is better at reading kanji than kana
 Kanji: from Chinese characters
 Kana: syllabic writing system
• LH is better at reading kana
Musical abilities and the hemispheres








Pitch, melody, intensity, harmony, etc. in RH
Rhythm in LH
Absolute pitch (if present) in LH temporal plane
Musicians’ ability to analyze chord structures in LH
Appreciation of chord harmony in RH
Discrimination of local melody cues more in LH
Timbre discrimination in anterior right temporal lobe
Melody recognition in anterior right temporal lobe
Evidence from results of brain lesions/surgery,
from dichotic listening experiments, from
Wada test experiments, and from imaging
An MSI study from Max Planck Institute
Right hemisphere in speech perception
 The primary substrate for speech
perception is the left pSTP
•
pSTP – Heschl’s gyrus plus planum temporale
 Yet another type of conduction aphasia:
• Some patients with damage to left pSTP show
symptoms of conduction aphasia (Hickock 2000)
 Apparent paradox:
• In conduction aphasia, comprehension is
preserved
 Explanation:
• Speech perception is subserved by pSTP in
both hemispheres
(Hickock 2000: 90)
RH involvement in speech perception
Isolated RH
 Evidence from tests of isolated RH
• Split-brain studies
• Wada test
•
•
 Sodium amytol, sodium barbitol
Discrimination of speech sounds
Comprehension of syntactically simple speech
(Hickok 2000: 92)
Caution – Split-Brain Studies
 These patients are generally epileptics
 Usually the onset of seizures is several to
many years before the surgery
 Often the onset of seizures was during
childhood
 Therefore the brain has had time to adapt
– perhaps reorganize some linguistic
functions
RH involvement in speech perception
Intra-operative recording
 Evidence from intraoperative recording
 Sites found in STG of both hemispheres for
• Phoneme clusters
• Distinguishing speech from backwards speech
• Distinguishing mono- from polysyllabic words
(Hickok 2000: 92-3)
RH involvement in speech perception
Imaging
 Evidence from imaging
•
•
•
PET
fMRI
MEG
•
More activity in LH
 Subjects passively listen to speech
 Both hemispheres show activity
 Some evidence for differential
contributions of the two hemispheres
(Hickok & Poeppel, another publication)
(Hickok 2000: 93)
Coarse and fine coding
 Coarsely coded node
• Responds to a relatively large range of values
 Finely coded node
• Responds to a narrow range
• Needed for sharp contrasts
• Examples
 Phonology
 Morphology
 Mathematics
Receptive fields of nodes






Every perceptual node has a receptive field
Can be called its value
The node is activated by tokens of that field
Its function is to recognize input of that field
Coarse coding: receptive field is broad
Fine coding: receptive field is narrow
Uses of coarse and fine coding
 Fine coding for
• Sharp contrasts
 Voiced vs. voiceless stops
 Edges in vision
 Coarse coding for
• Meanings with broad range of semantic
•
properties
General visual impressions
Coarse and fine coding:
Low-level nodes
 Low-level: near bottom of hierarchy
• Lowest level: primary areas
• Lowest level nodes are coarse-coded
 At other low levels, coarse and fine coding
 Colors (visual cortex)
• Fine coding for fine color discrimination
• Coarse coding for range of color
 Frequencies (auditory cortex)
• Fine coding for fine pitch discrimination
• Coarse coding for range of pitches
Inhibitory connections
Based on Mountcastle (1998)
 Columnar specificity is maintained by
pericolumnar inhibition (190)
• Activity in one column can suppress that in
its immediate neighbors (191)
 Inhibitory cells can also inhibit other inhibitory
cells (193)
 Inhibitory cells can connect to axons of other
cells (“axoaxonal connections”)
 Large basket cells send myelinated projections
as far as 1-2 mm horizontally (193)
The anatomy of lateral inhibition
 Inhibitory connections
 Extend horizontally to other columns in
the vicinity
• These columns are natural competitors
 Enhances contrast
Coarse coding at low levels
 Typical situation for sensory neurons
 Neurons fire..
• Occasionally at random even when not
•
•
receiving activation
More strongly when receiving activation
More strongly yet when receiving a lot of
activation
 Hence, low level nodes have broad
receptive fields
• Locally, they are coarsely coded
Typical Low-level Node: Coarsely Coded
Responds to a range of inputs
How to get fine coding
 Neurons (hence also columns, presumably)
are inherently, locally, coarse-coded
 For linguistic processing we often need
much greater precision: fine coding
 Problem: How to get finely coded nodes if
neurons are inherently coarsely coded?
Response curve of a coarsely coded node
Responds to a wide range of inputs
Response curve of node A (coarsely coded)
Node A is coarsely
coded for
Range of colors
Response curve of node B (coarsely coded)
Node B is coarsely
coded for
(Node A is coarsely
coded for
)
Overlapping receptive fields
“…each individual representation (e.g. receptive field)
is inexact, or coarse, but … the overall system of
overlapping representations can provide precise
interpretations.
Mark Beeman (1998), 256
Overlapping receptive fields
Node A
Node B
Higher-level node C
C
Response curve of C
Response curve of B
Response curve of A
A
B
A
B
Node C is
more finely
coded
Enhance fine-coding with inhibition
Node C can be yet more finely
coded by receiving
inhibitory inputs from
nodes for
C
and
A
A
B
B
Further enhancement by raising threshold
C
A
B
Threshold
A
B
Coarse coding at higher levels
 A node with a large number of incoming
connections and a relatively low threshold
 This arrangement allows it to respond to any of a
broad range of situations
 Coarse coding is the usual situation at the
conceptual level
• A concept node generally represents a
category, not just a single thing
• Different members of the category, with
differing features, activate the category node
Coarse and fine coding:
High-level nodes
 High-level nodes – concepts, meanings
• Coarse coding
•
 More coarse in RH
 Broad range of semantic properties
 In RH, not necessarily logical
Fine coding
 Mainly in LH
 Narrow range of semantic properties
A coarsely-coded category
The head node
CUP
T
MADE OF GLASS
SHORT
CERAMIC
HAS HANDLE
Properties
Therefore, the CUP node is
activated by varying combinations of a large range of
properties
Coarse coding and RH
 Coarse coding is particularly
prominent in RH
 Beeman: “diffuse activation” in RH (as
opposed to “focused activation” in LH)
Coarsely coded concept nodes
 Cups
•
•
A great variety of cups activate the ‘CUP’ node
To different degrees
 Properties of prototypical cups activate the
node more strongly
 Your grandmother
•
A specific person, but a coarsely coded node
•
Why coarsely coded?
 Wearing different clothes
 Doing different things
 Seen live or in a picture
 At different ages
 Etc.
•
Top of a hierarchical functional web
Summary: Coarse and fine coding
 Low-level nodes (as in primary areas)
• Tend to be coarsely coded
 Upper-level nodes
• For course coding
•
 Large number of incoming links
 Low activation threshold
For fine coding
 Threshold high in relation to number
of incoming links
 Lateral inhibition
end