Mind your Language, All Right?

Linköping
University
medical
dissertations,
No.
1358
 
 
 
 
 
 
 Mind your Language, All Right?  Performance‐dependent
neural
patterns
of
language
 ...
Author: Rosamond Price
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Linköping
University
medical
dissertations,
No.
1358
 
 
 
 
 
 


Mind your Language, All Right?  Performance‐dependent
neural
patterns
of
language
 
 
 
 


Helene van Ettinger‐Veenstra  



 
 


Center
for
Medical
Image
Science
and
Visualization
 


Division
of
Radiological
Sciences
 Department
of
Medical
and
Health
Sciences
 Linköping
University,
Sweden
 
 
 
 





 
 


Linköping
2013
 


  


    


          
 
 
 
 
 
 
 
 
 
 
 
 
 
 ©
Helene
van
Ettinger‐Veenstra,
2013
 [email protected]
 
 Published
papers
have
been
reprinted
 with
permission
of
the
copyright
holders
 
 Cover
design:
Tjeerd
Veenstra
www.tjeerdveenstra.nl
 
 Printed
in
Sweden
by
LiU
Tryck,
Linköping,
Sweden,
2013
 
 
 ISSN
0345‐0082
 ISBN
978‐91‐7519‐668‐8
 







 


      voor mijn lieve Lucas Levi  
 
 
 
 
 
  

They say the left side of the brain  Dominates the right  And the right side has to labor through  The long and speechless night  …  Maybe I think too much  
‘Think
Too
Much
(b)’
‐
Paul
Simon








ABSTRACT  
 
 The
 main
 aim
 of
 this
 dissertation
 was
 to
 investigate
 the
 difference
 in
 neural
 language
 patterns
 related
 to
 language
 ability
 in
 healthy
 adults.
 The
 focus
 lies
 on
 unraveling
 the
 contributions
 of
 the
 right‐hemispheric
homologues
to
Broca’s
area
in
the
inferior
frontal
gyrus
(IFG)
and
Wernicke’s
area
 in
the
posterior
temporal
and
inferior
parietal
lobes.
The
functions
of
these
regions
are
far
from
fully
 understood
 at
 present.
 Two
 study
 populations
 consisting
 of
 healthy
 adults
 and
 a
 small
 group
 of
 people
 with
 generalized
 epilepsy
 were
 investigated.
 Individual
 performance
 scores
 in
 tests
 of
 language
ability
were
correlated
with
brain
activation
obtained
with
functional
magnetic
resonance
 imaging
during
semantic
and
word
fluency
tasks.
Performance‐dependent
differences
were
expected
 in
 the
 left‐hemispheric
 Broca’s
 and
 Wernicke’s
 area
 and
 in
 their
 right‐hemispheric
 counterparts.
 PAPER
 I
 revealed
 a
 shift
 in
 laterality
 towards
 right‐hemispheric
 IFG
 and
 posterior
 temporal
 lobe
 activation,
 related
 to
 high
 semantic
 performance.
 The
 whole‐brain
 analysis
 results
 of
 PAPER
 II
 revealed
numerous
candidate
regions
for
language
ability
modulation.
PAPER
II
also
confirmed
the
 finding
of
PAPER
I,
by
showing
several
performance‐dependent
regions
in
the
right‐hemispheric
IFG
 and
the
posterior
temporal
lobe.
In
PAPER
III,
a
new
study
population
of
healthy
adults
was
tested.
 Again,
the
right
posterior
temporal
lobe
was
related
to
high
semantic
performance.
A
decrease
in
left‐ hemispheric
 IFG
 activation
 could
 be
 linked
 to
 high
 word
 fluency
 ability.
 In
 addition,
 task
 difficulty
 was
 modulated.
 Increased
 task
 complexity
 showed
 to
 correlate
 positively
 with
 bilateral
 IFG
 activation.
Lastly,
PAPER
IV
investigated
anti‐correlated
regions.
These
regions
are
commonly
known
 as
 the
 default
 mode
 network
 (DMN)
 and
 are
 normally
 suppressed
 during
 cognitive
 tasks.
 It
 was
 found
that
people
with
generalized
epilepsy
had
an
inadequate
suppression
of
regions
in
the
DMN,
 and
showed
poorer
performance
in
a
complex
language
test.
The
results
point
to
neural
adaptability
 in
 the
 IFG
 and
 temporal
 lobe.
 Decreased
 left‐lateralization
 of
 the
 IFG
 and
 increased
 right‐ lateralization
of
the
posterior
temporal
lobe
are
proposed
as
characteristics
of
individuals
with
high
 language
ability.





 I




II






SAMMANFATTNING 

Som
vuxna
människor
är
vi,
även
då
vi
är
friska,
väldigt
olika,
med
olika
förmågor.
Så
är
det
 också
 med
 språklig
 förmåga.
 Det
 varierar
 betydligt
 mellan
 olika
 personer
 hur
 bra
 läsförståelse
man
har,
eller
hur
lätt
man
har
att
hitta
på
ord.
Denna
avhandling
bygger
på
att
 dessa
 mätbara
 språkliga
 skillnader
 också
 kan
 synliggöras
 i
 hjärnan
 med
 hjälp
 av
 hjärnscanning,
 så
 kallad
 funktionell
 magnetresonanstomografi.
 Hjärnaktivering
 vid
 språkfunktion
 är
 ofta
 koncentrerad
 i
 den
 vänstra
 hjärnhalvan;
 i
 nedersta
 delen
 av
 pannloben
 samt
 i
 bakre
 delen
 av
 tinningloben,
 men
 även
 den
 högra
 hjärnhalvan
 kan
 aktiveras
av
flera
olika
språkfunktioner.
Speciellt
finns
de
funktioner
som
får
en
person
att
 förstå
 komplicerade
 språkkomponenter,
 till
 exempel
 bildspråk
 eller
 andra
 typer
 av
 underliggande
 betydelser
 i
 språket,
 i
 den
 högra
 hjärnhalvan.
 I
 studierna
 som
 ligger
 till
 grund
för
denna
avhandling
förväntades
att
hjärnaktiveringen
i
vanliga
språkområden
i
den
 vänstra
 hjärnhalvan
 skulle
 variera
 med
 språklig
 förmåga.
 Om
 personer
 som
 är
 bättre
 på
 språk
har
en
hjärna
som
fungerar
mer
effektivt,
så
skulle
det
visa
sig
som
mindre
aktivering
 i
 vänstersidiga
 språkområden.
 Å
 andra
 sidan,
 om
 personer
 som
 presterar
 bra
 har
 bättre
 kognitiv
 förmåga
 än
 sämre
 presterande,
 skulle
 det
 kunna
 synas
 som
 mer
 aktivering
 i
 de
 understödjande
 språkområdena
 i
 höger
 hjärnhalva.
 Resultaten
 som
 framgår
 i
 denna
 avhandling
 är
 framför
 allt
 att
 aktivering
 i
 höger
 tinninglob
 är
 involverad
 i
 bättre
 språklig
 förmåga.
 Det
 finns
 också
 antydningar
 att
 nedre
 delen
 av
 den
 högra
 pannloben
 är
 mer
 aktiverad
när
man
är
bra
på
språk.
Resultaten
visade
sig
dock
att
variera
med
språkuppgift;
 det
finns
bevis
för
mer
aktivering
i
höger
pannlob
i
samband
med
bättre
språkförståelse
och
 för
 mindre
 aktivering
 i
 vänster
 pannlob
 i
 samband
 med
 bättre
 förmåga
 att
 generera
 ord.
 Dessutom
är
den
nedre
delen
av
pannloben
mer
aktiv
vid
svårare
språkförståelseuppgifter.
 Slutsatsen
av
dessa
studier
är
att
aktivering
i
den
nedre
pannloben
är
beroende
av
kognitiv
 kapacitet,
 men
 att
 aktivering
 i
 den
 högersidiga
 bakre
 tinningloben
 är
 specifik
 för
 språkförståelse.
De
studier
som
är
inkluderade
i
avhandlingen
visar
att
desto
bättre
man
är
 på
språk,
desto
mindre
använder
man
 enbart
 den
 vänstra
hjärnhalvan
 när
 man
 läser
 eller
 genererar
ord.
 





III






IV




LIST OF PUBLICATIONS  
 
 This dissertation is based on the following original papers, which are referred to throughout the text by  their Roman numerals:    PAPER I


Van
 Ettinger‐Veenstra
 HM,
 Ragnehed
 M,
 Hällgren
 M,
 Karlsson
 T,
 Landtblom
 A‐M,
 Lundberg
 P,
 and
 Engström
 M
 (2010).
 Right‐hemispheric
 brain
 activation
 correlates
 to
language
performance.
NeuroImage
49(4):
3481–3488.


PAPER II


Van
Ettinger‐Veenstra
HM,
Ragnehed
M,
McAllister
A,
Lundberg
P,
and
Engström
M
 (2012).
 Right‐hemispheric
 cortical
 contributions
 to
 language
 ability
 in
 healthy
 adults.
Brain
and
Language
120(3):
395–400.


PAPER III


Gauffin
 H*,
 Van
 Ettinger‐Veenstra
 HM*,
 Landtblom
 A‐M,
 Ulrici
 D,
 McAllister
 A,
 Karlsson
 T,
 and
 Engström
 M.
 Impaired
 language
 function
 in
 generalized
 epilepsy:
 Inadequate
 suppression
 of
 the
 default
 mode
 network.
 Accepted
 in
 Epilepsy
 &
 Behavior,
2013.


PAPER IV


Van
 Ettinger‐Veenstra
 HM,
 Karlsson
 T,
 McAllister
 A,
 Lundberg
 P,
 and
 Engström
 M.
 Laterality
shifts
in
neural
activation
coupled
to
language
ability.
Submitted
to
 PLoS
 ONE,
2013.



 * The first two authors contributed equally to this paper  
 


Related Peer‐Reviewed Conference Abstracts   

Veenstra
HM,
Ragnehed
M,
Hällgren
M,
Lundberg
P,
and
Engström
M.
Brain
lateralization
assessed
by
 fMRI
and
dichotic
listening.
Paper
presented
at
the
 15th
Annual
Meeting
of
the
Organization
for
 Human
Brain
Mapping,
California,
USA,
2009.
 Veenstra
HM,
Pettersson
J,
Nelli
C,
Ragnehed
M,
McAllister
A,
Lundberg
P,
and
Engström
M.
Influence
 of
 performance‐related
 language
 ability
 on
 cortical
 activation.
 Paper
 presented
 at
 the
 15th
 Annual
Meeting
of
the
Organization
for
Human
Brain
Mapping,
California,
USA,
2009.
 Van
Ettinger‐Veenstra
H,
Karlsson
T,
Ulrici
D,
Gauffin
H,
Landtblom
AM,
and
Engström
M.
Language
 ability
 in
 healthy
 and
 epilepsy
 participants:
 an
 fMRI
 investigation.
 Paper
 presented
 at
 the
 43rd
 European
Brain
and
Behaviour
Society
Meeting,
Seville,
Spain,
2011.
 Van
Ettinger‐Veenstra
H,
Gauffin
H,
McAllister
A,
Lundberg
P,
Ulrici
D,
Landtblom
A‐M,
and
Engström
 M.
Language
deficits
in
Epilepsy,
an
fMRI
study.
Paper
presented
at
the
 18th
Annual
Meeting
of
 the
Organization
for
Human
Brain
Mapping,
Beijing,
China,
2012.





V


 

AT A GLANCE 

   

 

 

PAPER (study) 

METHODS 

 

 


 


    I 

 

14
healthy
adults.
fMRI:
Lateralization
Index


(A) 

from
sentence
reading
(SENCO)
task
was
 correlated
with
Read,
BeSS,
FAS
&
BNT
 performance
scores.
Also,
Dichotic
Listening
 laterality
measurements
were
investigated.


    
   II 

(A) 

 

III 

18
healthy
adults.
Whole‐brain
analyses
from


sentence
reading
(SENCO)
and
word
fluency
 (WORGE);
activation
was
correlated
with
 Read,
BeSS,
FAS
&
BNT
performance
scores.


   

       


 27
healthy
adults.
Lateralization
Index
from
 (B) 

   

ROI
analyses
of
sentence
reading
(SEN)
and
 word
fluency
(WORD),
correlated
with
 performance
scores
on
BeSS
and
FAS.
Also,
 task
difficulty
related
brain
activation
was
 investigated
with
multiple
regression.
 
 27
healthy
&
11
Generalized
Epilepsy


 

IV 

 

 


  

 

(B) 

   

participants.
Investigated
for
deactivation
in
 the
default
mode
network
during
sentence
 reading
(SEN).
Also,
language
performance
 measurements
of
the
epilepsy
group.


   



     



VI




 

 

 

 

 

 

 

  CONCLUSIONS 

RESULTS 


 
 
 
 Both
dichotic
listening
and
fMRI
results
point
to
a
 right‐hemispheric
activation
as
a
characteristic
 for
high
language
ability.


    Activation
in
the
right‐hemispheric
ROIs
was
 more
pronounced
for
high
performance.
This
 correlated
with
the
dichotic
listening
results.
 Especially
high
BeSS
and
Read
scores
 correlated
with
increased
right‐lateralization.







 Regions
in
inferior
frontal
gyrus
(BA
47)
and
 middle
temporal
gyrus
(BA
21)
are
related
to
high
 semantic
language
ability.


Several
clusters
in
right
IFG
and
temporal
lobe
 showed
to
correlate
with
BeSS
and
Read
on
 the
sentence
reading
fMRI
task.
No
such
 results
for
word
fluency.



 
 
 Activation
in
the
inferior
frontal
gyrus
is
 modulated
by
semantic
difficulty,
while
right
 temporal
lobe
activation
is
specific
for
semantic
 ability.



 Activation
in
the
temporal
lobe
was
more
 right‐lateralized
for
high
BeSS
performance.
 Activation
in
left
IFG
was
less
left‐lateralized
 for
high
FAS
performance.
The
difficult
 incongruent
sentence
reading
condition
was
 characterized
by
bilateral
IFG
activation






People
with
Generalized
Epilepsy
experience
 language
difficulties.
This
could
be
explained
by
 aberrant
suppression
of
activation
in
the
default
 mode
network.
A
failure
to
suppress
default
 mode
network
activation
is
disturbing
for
 cognitive
functioning.


People
with
Generalized
Epilepsy
showed
 worse
performance
in
BeSS
than
healthy
 controls.
They
also
showed
diminished
DMN
 deactivation,
notable
was
the
decreased
left
 temporal
lobe
deactivation
and
increased
 hippocampal
activation.








VII




VIII




ABBREVIATIONS  
 
 BA




BeSS
 BNT


Brodmann
Area
 “Bedömning
av
Subtila
Språkstörningar”
–
Assessment
of
Subtle
Language
Deficits




Boston
Naming
Test


BOLD
 


Blood
Oxygen
Level
Dependent


DMN




Default
Mode
Network


fMRI




functional
Magnetic
Resonance
Imaging


FWE




Family‐Wise
Error


GE




Generalized
Epilepsy


GLM




General
Linear
Model


IFG




Inferior
Frontal
Gyrus


LI




Laterality
Index


MNI




Montreal
Neurological
Institute


MRI




Magnetic
Resonance
Imaging


P‐FIT




Parieto‐Frontal
Integration
Theory


ROI




Region
of
Interest


SEN




sentence
reading
fMRI
task
used
in
PAPER
III
&
PAPER
IV


SENCO
 


sentence
completion
fMRI
task
used
in
PAPER
I
&
PAPER
II


WORD
 


word
generation
fMRI
task
used
in
PAPER
III


WORGE



word
generation
fMRI
task
used
in
PAPER
II

     




IX


  


CONTENTS 


 
 ABSTRACT 

I


SAMMANFATTNING 

III


LIST OF PUBLICATIONS 

V


AT A GLANCE 

VI


ABBREVIATIONS 

IX


1
 INTRODUCTION  1.1
 LANGUAGE ABILITY  1.1.1
 Language
Abilities
 1.1.2
 Language
Dysfunctions
 1.2
 NEURAL CORRELATES TO LANGUAGE  1.2.1
 Language
Models
 1.2.2
 Semantics
 1.2.3
 Word
Fluency
 1.2.4
 Right‐Hemispheric
Influences
 1.2.5
 Laterality
 1.2.6
 Anti‐correlated
Brain
Activation
 1.3
 INTELLIGENCE MODELS FOR LANGUAGE ABILITY  1.3.1
 Relation
Language
Ability
and
Intelligence
 1.3.2
 Intelligence
Models
 1.4
 AIMS  2
 METHODS  2.1
 NEUROLINGUISTIC MEASURES  2.1.1
 Tests
of
Language
Ability
 2.1.2
 Dichotic
Listening
 2.1.3
 fMRI
Language
Paradigms
 2.1.4
 Study
Population
 2.1.5
 Generalized
Epilepsy
 2.2
 FUNCTIONAL MRI  2.2.1
 Properties
of
Functional
MRI
 


1
 2


2
 3


4


4
 8
 8
 8
 9
 10


11


11
 11


13
 15
 15


15
 16
 16
 17
 17


18


18



 
 
 
 
 
 
 
 
 
 
 
 2.2.2
 Region
of
Interest
Analysis
 2.2.3
 Laterality
Index
Analysis


3
 RESULTS  3.1
 3.2
 3.3
 3.4


19
 20


23


MULTIPLE REGRESSION ANALYSES  LATERALITY ANALYSES  TASK DIFFICULTY MODULATION  LANGUAGE DYSFUNCTIONS IN EPILEPSY 

4
 DISCUSSION 

24
 27
 28
 29
 31


4.1
 NEURAL CORRELATES TO PERFORMANCE  4.1.1
 Multiple
Regression
Analyses
 4.1.2
 Laterality
Analyses
 4.1.3
 Task
Difficulty
Modulation
 4.1.4
 Language
Dysfunctions
in
Epilepsy
 4.2
 HEALTHY ADULTS  4.3
 INTERPRETATION OF ACTIVATION PATTERNS  4.4
 FUTURE DIRECTIONS 

31
 31
 33
 34
 35
 36
 37
 42


5
 CONCLUSIONS 

45


ACKNOWLEDGMENTS 

46


REFERENCES 

49


PAPER I
 PAPER II  PAPER III  PAPER IV 








 
 
 
 
 
 
 
 
 
 
 
 
 
 
 


Big black cloud  On a yellow plain  Sure enough it  Looks like rain  Packin' up all our  Faith and trust  Me and the wanderlust   ‘Wanderlust’
‐
Mark
Knopfler



 
 
 





 
 
 


1 INTRODUCTION  
 
 Mapping
 of
 language
 disability
 patterns
 requires
 a
 thorough
 understanding
 of
 language
 ability
 patterns.
 The
 neural
 pathways
 for
 perceiving
 and
 generating
 language
 are
 slowly
 being
 unraveled,
 but
the
exact
contributions
of
typical
left‐hemispheric
language
areas
(Broca’s
and
Wernicke’s
area)
 are
 not
 yet
 completely
 clear.
 Neither
 is
 the
 role
 of
 language‐related
 regions
 in
 the
 –
 usually
 non‐ dominant
–
right
hemisphere.
The
opinion
about
how
right‐hemispheric
regions
influence
language
 has
 changed.
 In
 the
 past,
 activation
 in
 the
 right
 hemisphere
 during
 language
 tasks
 was
 largely
 overlooked;
but
over
time,
researchers
gained
an
understanding
of
the
emotional
content
processing
 aspects.
At
present,
additional
roles
of
the
right
hemisphere
in
language
are
being
explored,
including
 language
 comprehension
 aspects.
 Evidence
 of
 these
 right‐hemispheric
 comprehensive
 aspects
 is
 presented
in
this
dissertation
within
a
framework
of
manifestations
of
language
ability
in
the
brain.
 This
 dissertation
 presents
 four
 papers
 that
 investigated
 language
 ability,
 which
 was
 defined
 as
 language
production
and
comprehension
abilities.
The
first
three
papers
describe
how
healthy
adults
 were
 tested
 for
 brain
 activation
 evoked
 by
 neurolinguistic
 functional
 magnetic
 resonance
 imaging
 (fMRI)
 tasks.
 These
 fMRI
 tasks
 measured
 semantic
 processing
 and
 word
 fluency
 activations.
 The
 results
 were
 related
 to
 individual
 performance
 measurements
 in
 various
 tests
 of
 language
 ability,
 including
 reading,
 word
 fluency,
 picture
 naming
 and
 use
 of
 complex
 language.
 The
 fourth
 paper
 discusses
how
the
brains
of
people
with
generalized
epilepsy
can
express
altered
activation
patterns
 in
relation
to
lower
language
ability.





1


1.

INTRODUCTION


1.1   Language Ability  


1.1.1   Language Abilities  The
ability
to
produce
language
enables
one
to
communicate
one’s
own
thoughts
and
express
oneself.
 Comprehension
of
language
will
enable
one
to
perceive
information
that
might
be
new
or
interesting.
 As
in
all
skills;
individual
differences
are
present.
The
origins
of
these
differences
might
be
attributed
 to
 the
 amount
 of
 exposure
 to
 language,
 or
 to
 one’s
 own
 interests
 in
 reading
 or
 verbal
 expression.
 Whenever
people
manifest
differences
in
behavior,
neuroimagers
will
look
for
the
neural
correlates
 to
 these
 differences.
 Indeed,
 the
 rationale
 behind
 the
 performed
 experiments
 that
 led
 to
 this
 dissertation
was
to
visualize
language
ability
differences
in
healthy
subjects.
The
current
sub‐chapter
 will
 present
 previous
 research
 on
 language
 ability
 variation.
 In
 the
 following
 sub‐chapter,
 ‘Neural
 Correlates
to
Language’,
a
more
detailed
framework
for
language
ability
will
be
introduced.
 Language
 discussions
 often
 refer
 to
 the
 classical
 language
 areas
 of
 Broca’s
 area
 in
 the
 left
 inferior
 frontal
gyrus
(IFG)
and
Wernicke’s
area
in
the
left
posterior
temporal
lobe.
It
is
also
known
that
other
 functional
regions
are
involved
in
language
processes;
these
will
be
explored
in
the
next
sub‐chapter.
 It
 seems
 that
 differences
 in
 language
 performance
 can
 be
 –
 at
 least
 partly
 –
 explained
 by
 differentiations
 in
 activation
 in
 Broca’s
 and
 Wernicke’s
 language
 areas,
 although
 their
 exact
 contribution
is
not
yet
clear.
Studies
investigating
high
performance
in
word
fluency
have
shown
an
 increase
 of
 left‐hemispheric
 IFG
 activation
 for
 high
 performance
 (Wood
 et
 al.,
 2001),
 but
 also
 no
 difference
 at
 all
 (Dräger
 et
 al.,
 2004).
 When
 semantic
 tasks
 are
 studied,
 increased
 activation
 of
 posterior
temporal
and
parietal
regions
is
shown
for
high
performance
(Booth
et
al.,
 2003;
Meyler
et
 al;
2007;
Weber
et
al.,
2006).
 However,
 an
 opposing
 view
 emerges
 from
 an
 increasing
 number
 of
 works
 revealing
 a
 relationship
 between
reading
and
sentence
comprehension
and
decreased
activation
in
left
hemispheric
language
 areas
 (Reichle
 et
 al.,
 2000;
 Prat
 et
 al.,
 2007;
 2011,
 Prat
 &
 Just,
 2011).
 The
 mechanism
 behind
 this
 activation
reduction
is
thought
to
be
a
more
efficient
neural
functioning.
Efficacy
in
recruiting
neural
 regions
 or
 pathways
 enables
 a
 person
 to
 re‐attribute
 cognitive
 resources
 guided
 by
 task
 demand.
 Thus,
a
person
skilled
in
language
may
use
his
or
her
brain
in
a
more
optimal
way
for
the
presented
 task.
Furthermore,
there
is
evidence
of
a
specific
role
of
the
right‐hemispheric
homologues
of
Broca’s
 and
Wernicke’s
area
in
high
language
performance.
Many
of
the
results
presented
in
the
papers
that
 are
 included
 in
 this
 dissertation
 point
 also
 to
 a
 right‐hemispheric
 contribution
 to
 high
 language
 ability.
If
people
with
a
high
language
ability
recruit
additional
language‐supporting
areas,
this
may
 indicate
that
a
high
adaptability
of
neural
resources
is
an
explanatory
mechanism
for
language
ability
 differences.
 Research
 supporting
 the
 theories
 of
 neural
 adaptability
 and
 neural
 efficiency
 as




2






1.

INTRODUCTION


explicatory
 for
 high
 language
 ability
 will
 be
 presented
 in
 the
 sub‐chapter
 ‘Intelligence
 models
 for
 Language
Ability’
 


1.1.2   Language Dysfunctions  The
 introduction
 started
 out
 by
 stating
 that
 knowledge
 of
 language
 ability
 will
 lead
 to
 an
 understanding
 of
 language
 disability.
 PAPER
 IV
 presents
 a
 group
 of
 people
 with
 epilepsy
 showing
 subtle
language
disabilities,
and
compares
them
with
healthy
subjects
performing
on
a
normal
level.
 The
reverse
statement
to
the
one
above
is
also
true;
upon
investigating
language
disabilities,
a
model
 for
 language
 abilities
 can
 be
 created.
 Much
 of
 our
 knowledge
 about
 the
 language
 system
 has
 been
 gained
 from
 lesion
 studies
 notably
 those
 on
 left‐hemispheric
 lesioned
 patients
 showing
 word
 production
problems,
as
presented
a
little
later
in
this
section.
 Language
 impairment
 can
 have
 a
 variety
 of
 underlying
 causes;
 impaired
 language
 functioning,
 cognitive
 ability,
 or
 sensory/motoric
 abilities,
 or
 lack
 of
 training
 or
 exposure
 to
 language.
 A
 disruption
 in
 any
 component
 of
 language
 production
 or
 comprehension
 in
 the
 language
 model1
 evidently
will
result
in
a
disruption
of
language
ability.
Since
the
studies
included
in
this
dissertation
 measure
word
generation
and
sentence
reading,
this
section
discusses
reading
impairment
(dyslexia)
 and
production
problems.
 Developmental
 dyslexia
 is
 characterized
 by
 various
 neurological
 differences
 throughout
 the
 brain,
 probably
 caused
 by
 anomalies
 during
 the
 development
 of
 language
 systems
 in
 the
 brain
 (Catts
 &
 Kamhi,
 2005;
 Démonet
 et
 al.,
 2005).
 It
 has
 been
 suggested
 that
 this
 type
 of
 dyslexia
 is
 related
 to
 abnormal
 dominance
 patterns
 or
 abnormal
 development
 of
 dominance
 (Heim
 et
 al.,
 2010),
 but
 the
 causes
are
though
probably
multiple
and
more
complex
(Crystal
 2010).
Acquired
dyslexia
can
occur
 after
a
lesion
in
one
out
of
various
brain
regions
(Price
et
al.,
2003).
Functional
imaging
studies
on
the
 neurological
 differences
 between
 people
 with
 dyslexia
 and
 normal
 performers
 show
 a
 diminished
 activation
 in
 temporal
 and
 parietal
 regions
 (Salmelin
 et
 al.,
 1996;
 Shaywitz
 et
 al.,
 1998),
 and
 an
 increase
in
inferior
frontal
activation
(Shaywitz
et
al.,
1998).
Both
the
presence
of
expected
activation
 and
 the
 absence
 of
 unexpected
 activation
 in
 the
 right
 hemisphere
 have
 been
 observed
 to
 act
 as
 distinguishers
of
people
with
dyslexia
from
people
without
reading
impairment
(Paulesu
et
al.,
 1996;
 Simos
et
al.,
2000).
 Word
 production
 problems
 are
 often
 not
 development‐related
 but
 result
 from
 lesions
 in
 the
 language‐dominant
hemisphere.
Problems
with
word
fluency
are
seen
in
people
with
dementia
and
 with
left
temporal
lobe
epilepsy
(Ruff
et
al.,
 1997).
Named
after
the
location
of
brain
damage,
aphasia


























































 1
e.g.
the
space
station
model
presented
in
the
following
sub‐chapter
‘Brain
Functioning’





3


1.

INTRODUCTION


can
 be
 classified
 as
 Broca’s
 aphasia,
 Wernicke’s
 aphasia
 or
 global
 aphasia
 –
 the
 latter
 being
 a
 combination
 of
 Broca’s
 and
 Wernicke’s
 aphasia.
 It
 is
 now
 known
 that
 in
 Broca’s
 aphasia,
 brain
 regions
posterior
to
Broca’s
area
are
often
damaged;
and
that
in
Wernicke’s
aphasia
the
location
of
 damage
 can
 vary
 (Crystal
 2010).
 Broca’s
 aphasia
 results
 in
 deficits
 in
 expressive
 abilities
 and
 is
 characterized
 by
 non‐fluent
 speech
 which
 is
 grammatically
 incorrect.
 Wernicke’s
 aphasia
 occurs
 when
 receptive
 systems
 are
 damaged
 and
 results
 in
 both
 comprehension
 problems
 and
 problems
 producing
 intelligible
 speech,
 even
 though
 it
 appears
 to
 be
 fluent.
 Furthermore,
 word
 retrieval
 problems
are
a
common
deficiency
(Crystal
2010).
 Studies
 on
 language
 disabilities
 can
 help
 us
 to
 find
 regions
 of
 interest
 for
 the
 investigation
 of
 language
 abilities.
 Lesion
 studies
 that
 have
 led
 to
 an
 understanding
 of
 language
 disabilities
 have
 shown
 that
 disruption
 of
 language
 functioning
 in
 the
 language‐dominant
 hemisphere
 has
 a
 much
 higher
impact
than
a
disruption
in
the
non‐dominant
hemisphere.
Thus,
the
language
functions
in
the
 non‐dominant
 hemisphere
 may
 not
 be
 compulsory
 for
 language
 production,
 but
 may
 support
 complex
processing.


 



1.2   Neural Correlates to Language  


1.2.1   Language Models  There
 are
 many
 possible
 theoretical
 models
 to
 describe
 the
 complex
 structure
 of
 language.
 Often,
 these
 models
 use
 similar
 distinctions
 between
 word
 forms,
 word
 structure,
 word
 meaning
 and
 understanding
 of
 text
 or
 speech.
 In
 other
 words,
 many
 models
 describe
 language
 as
 a
 process
 defining
 the
 range
 of
 linguistic
 information
 from
 small
 building
 blocks
 to
 complex
 meaningful
 communication.
 To
 understand
 language
 in
 the
 context
 of
 this
 dissertation,
 a
 useful
 model
 is
 the
 space
station
model
as
presented
by
Crystal
(2010),
and
represented
in
Figure
1.
 This
 model
 describes
 an
 interactive
 framework
 integrating
 the
 components
 of
 language
 that
 are
 investigated
 in
 the
 papers
 included
 in
 this
 dissertation.
 The
 different
 components
 are:
 phonetics
 (pronunciation
 attributes)
 and
 phonology
 (sounds
 that
 convey
 different
 meanings),
 morphology
 (word
 structure)
 and
 syntax
 (sentence
 structure),
 semantics
 (meaningful
 content)
 and
 pragmatics
 (discourse
information).
The
connection
between
these
components
is
not
uni‐directional,
but
rather
 interconnected
 as
 represented
 in
 the
 space
 station
 model.
 This
 is
 consistent
 with
 the
 neural
 organization
 of
 language,
 where
 both
 top‐down
 and
 bottom‐up
 processes
 can
 be
 observed
 during
 language
processes
(Friederici
2012).




4






1.

INTRODUCTION


Figure
1. Representation of the Space Station Language Model. The linguistic levels presented in the  circles are interconnected, indicating free exchange of linguistic information between levels; thus all  information is available at once for an external researcher. Figure adapted from Crystal (2010).  
 Measures
 of
 language
 ability
 preferably
 test
 for
 many
 linguistic
 components,
 including
 production
 and
perception
of
language,
and
have
a
high
enough
difficulty
level
to
measure
variability
in
language
 skills.
 On
 the
 other
 hand,
 the
 total
 test
 duration
 should
 be
 kept
 to
 a
 minimum
 as
 to
 impose
 only
 minimally
 on
 the
 participants,
 especially
 on
 those
 with
 cognitive
 disabilities.
 The
 tests
 used
 in
 our
 studies,
 (see
 also
 Methods
 section
 for
 their
 description),
 show
 two
 approaches
 towards
 this
 goal.
 First;
established
tests
such
as
the
Boston
Naming
Test
(Kaplan
et
al.,
 1983)
or
word
fluency
tests
– testing
word
retrieval
and
word
production
skills
–
are
used
in
many
research
studies
that
describe
 the
 neural
 mechanisms
 that
 lie
 behind.
 Moreover,
 these
 tests
 are
 easily
 translated
 to
 the
 magnetic
 resonance
scanner
environment
without
much
adapting.
However,
both
tasks
are
very
focused;
they
 do
 not
 test
 for
 the
 full
 spectrum
 of
 language
 ability.
 Other
 tests,
 such
 as
 comprehensive
 reading,
 investigate
 language
 perception
 and
 comprehension
 and
 could
 be
 translated
 to
 the
 scanner
 environment
with
some
modification.
A
second
approach
is
to
gather
multiple
language
ability
tests
 in
a
battery,
such
as
the
Assessment
of
Subtle
Language
Deficits
or
BeSS
test
(Laakso
et
al.,
2000).
This
 relatively
 new
 complex
 language
 ability
 test
 is
 not
 yet
 established,
 but
 can
 detect
 subtle
 language
 dysfunctions
without
showing
a
ceiling
effect
(as
the
results
of
our
papers
will
show).
Moreover,
this
 is
a
compact
test,
so
that
language
ability
can
be
assessed
quickly
without
too
much
imposing
on
the





5


1.

INTRODUCTION


concentration
 skills
 of
 people
 with
 language
 dysfunctions
 (such
 as
 the
 people
 with
 generalized
 epilepsy
from
our
PAPER
IV).
However,
this
test
is
less
practical
in
a
scanner
environment.

 Neurological
models
are
often
based
on
the
classical
Wernicke‐Geschwind
model
(Geschwind
 1965),
 which
 describes
 the
 neurological
 dissociation
 between
 language
 production/speech
 attributed
 to
 Broca’s
area,
and
language
semantic
comprehension
(semantics)
attributed
to
Wernicke’s
area.
Many
 later
 studies
 have
 shown
 that
 this
 description
 is
 insufficient,
 as
 it
 does
 not
 take
 into
 account
 other
 functional
areas,
nor
does
it
describe
accurately
the
precise
boundaries
of
linguistic
functional
areas
 (Price
2000;
2012;
Démonet
et
al.,
2005;
Smits
et
al.,
2006).
 An
overview
of
the
segregation
in
left‐hemispheric
language
areas
is
given
in
Figure
 2.
For
instance,
 Broca’s
area
contains
regions
involved
in
semantics
as
well
as
in
syntax
processing
(cf.
Price
 2012).
 Interestingly,
 although
 language
 studies
 often
 focus
 on
 the
 language‐dominant
 left
 hemisphere
 (Vigneau
et
al.,
 2006),
the
right
hemisphere
often
shows
a
similar
activation
pattern
(Démonet
et
al.,
 2005).
Nevertheless,
aspects
of
neural
correlates
to
the
Wernicke‐Geschwind
model
are
supported
by


recent
lesion
studies
investigating
aphasia
(Yang
et
al.,
2008)
and
by
functional
imaging
studies
(Price
 2000;
 Bookheimer
 2002).
 Therefore,
 Broca’s
 and
 Wernicke’s
 area
 are
 used
 as
 regions
 of
 interest
 in


several
 of
 our
 analyses,
 in
 combination
 with
 other
 regions
 that
 were
 found
 in
 relation
 to
 semantic
 and
word
fluency
tasks.
 When
 using
 the
 labels
 of
 Broca’s
 and
 Wernicke’s
 areas,
 it
 is
 important
 to
 define
 their
 extent;
 the
 definition
 of
 Wernicke’s
 area
 in
 particular
 can
 vary
 from
 including
 only
 the
 posterior
 superior
 temporal
 gyrus
 to
 the
 inclusion
 of
 large
 parts
 of
 the
 parietal
 and
 temporal
 cortex.
 Throughout
 this
 dissertation,
 including
 all
 articles,
 the
 definition
 used
 is
 as
 follows:
 Broca’s
 area
 comprises
 the
 left
 IFG;
 specifically
 Brodmann
 areas
 (BA)
 44
 and
 45.
 Wernicke’s
 area
 comprises
 the
 left
 posterior
 superior
temporal
gyrus
(BA
22)
and
the
posterior
part
of
BA
21,
as
well
as
the
posterior
perisylvian2
 region
which
consists
of
the
left
angular
gyrus
and
the
supramarginal
gyrus
(BA
 39
&
inferior
BA
40).
 The
 right‐hemispheric
 counterparts
 of
 these
 areas
 are
 referred
 to
 as
 Broca’s
 and
 Wernicke’s
 area
 homologues.
 Language
 production
 and
 perception
 are
 by
 no
 means
 controlled
 solely
 by
 these
 regions3.
 The
 regions
 important
 for
 language
 will
 be
 discussed
 in
 the
 following
 sections
 which
 introduce
an
overview
of
activation
related
to
semantic
and
word
fluency
tasks.
Since
the
topic
of
this
 dissertation
is
language
ability,
neural
processes
not
directly
related
to
language
are
not
introduced
 here.


























































 2
Perisylvian
indicates
the
region
around
the
Sylvian
fissure.
This
fissure
divides
the
frontal
and


parietal
lobules
from
the
temporal
lobe.


3
An
example
is
given
by
(Dronkers
et
al.,
2007),
who
found
that
the
patients
of
Paul
Broca
–
whose


brains
evidenced
the
theory
of
speech
production
located
in
left
IFG
–
had
lesions
that
were
spread
 over
a
wider
region
than
just
Broca’s
area.




6






1.

INTRODUCTION



 Figure
 2.  Finite  overview  (based  on  imaging  studies  by  Cathy  Price)  of  the  segregation  of  functional  language­related  areas  in  the  left  hemisphere.  The  colored  areas  each  refer  to  different  tasks,  either  differing in modality (auditory/visual) or in linguistic component. Figure reprinted with permission. See  Price (2012) for details.  





7


1.

INTRODUCTION


1.2.2   Semantics  Our
 studies
 have
 used
 semantic
 sentence
 reading
 fMRI
 tasks,
 either
 requiring
 completion
 of
 sentences
 or
 reading
 of
 congruent/incongruent
 sentences.
 Semantic
 tasks
 such
 as
 reading
 (Price
 2000),
 and
 sentence
 and
 story
 comprehension
 (Sakai
 et
 al.,
 2001;
 Kaan
 &
 Swaab,
 2002)
 typically


activate
Broca’s
and
Wernicke’s
area
in
the
left
hemisphere
(Price
et
al.,
 2003;
overview
in
Binder
et
 al.,
 2009).
 In
 the
 left
 IFG,
 BA
 47
 plays
 also
 a
 role
 in
 semantic
 processing
 (Dapretto
 &
 Bookheimer,
 1999;
 Bookheimer
 2002).
 Furthermore,
 the
 anterior
 temporal
 cortex
 and
 the
 fusiform
 gyrus
 are


involved
in
semantic
processing
(Price
et
al.,
 2003;
overview
in
Price
 2012).
Activation
in
the
parietal
 perisylvian
region
has
been
shown
to
correlate
with
linguistic
complexity
in
sentences
(Carpenter
et
 al.,
 1999)
 and
 semantic
 associating
 (Price
 2000).
 Semantic
 processing
 often
 also
 activates
 right‐ hemispheric
IFG
and
temporal
lobe
(Bookheimer
2002),
which
will
be
discussed
in
the
section
‘Right‐ Hemispheric
Influences’.
 


1.2.3   Word Fluency  Word
 generation
 (or:
 word
 fluency)
 tasks
 are
 frequently
 used
 to
 determine
 language
 lateralization
 by
fMRI
(Cuenod
et
al.,
1995;
Hertz‐Pannier
et
al.,
1997).
The
generation
of
words
evokes
activation
in
 the
left
middle
and
inferior
frontal
gyrus
(Fu
et
al.,
 2002;
Costafreda
et
al.,
 2006),
with
a
particularly
 important
 role
 for
 the
 pars
 opercularis
 (Price
 2000).
 Furthermore
 is
 activation
 observed
 in
 the
 inferior
temporal
cortex
and
in
the
adjacent
fusiform
area
(Price
 2000),
and
in
the
anterior
cingulate
 cortex
 (Fu
 et
 al.,
 2002)
 The
 sub‐regions
 in
 the
 IFG
 have
 specific
 roles
 and
 the
 activation
 pattern
 is
 dependent
on
the
nature
of
the
fluency
task
(Heim
et
al.,
2009).
 


1.2.4   Right‐Hemispheric Influences  Most
language
tasks
evoke
activation
in
bilateral
frontal,
temporal
or
parietal
areas;
the
specific
role
 of
right‐hemispheric
language
areas
is
often
interpreted
as
abstract
linguistic
functioning.
Although
 lesion
studies
often
indicate
that
the
right‐hemisphere
is
not
indispensable
for
language
production,
 neuroimaging
 studies
 show
 that
 the
 right
 hemisphere
 plays
 an
 important
 and
 often
 distinct
 role,
 something
we
found
evidence
of
in
our
studies
as
well.
Vigneau
and
colleagues
(2011)
discuss
in
their
 meta‐analysis
the
right
hemisphere
in
relation
to
language
processing.
They
conclude
that
the
right‐ hemispheric
IFG
seems
to
have
no
access
to
phonemic
representations,
unlike
the
left
IFG.
Activation
 in
 the
 right
 IFG
 is
 observed
 during
 processing
 of
 metaphors
 (Schmidt
 &
 Seger,
 2009)
 and
 the
 perception
of
prosody
(Buchanan
et
al.,
 2000).
Furthermore,
the
right
IFG
is
active
when
information
 is
 conflicting
 during
 complex
 language
 tasks;
 this
 is
 related
 to
 figurative
 language
 and
 increasing




8






1.

INTRODUCTION


ambiguity
(Bookheimer
2002;
Snijders
et
al.,
2009).
Bookheimer
suggests
that
the
role
of
the
right
IFG
 might
be
to
help
making
decisions
based
on
linguistic
information.
 The
 right
 hemisphere
 is
 also
 important
 for
 understanding
 and
 integrating
 spoken
 and
 written
 information
(Bookheimer
2002).
In
particular,
the
understanding
of
context
processing
or
pragmatics
 –
which
is
necessary
for
interpreting
for
example
ambiguous
or
emotionally
loaded
information
–
is
 attributed
to
the
right
temporal
lobe
(Vigneau
et
al.,
2011).
Examples
of
right
temporal
lobe
activation
 are
seen
in
studies
investigating
the
interpretation
of
prosody
(Vigneau
et
al.,
 2011),
the
integration
 of
 semantic
 information
 (Caplan
 &
 Dapretto,
 2001),
 or
 the
 processing
 of
 metaphors
 (Bottini
 et
 al.,
 1994;
Mashal
et
al.,
 2005;
Ahrens
et
al.,
 2007).
The
neural
activation
resulting
from
the
processing
of


metaphors
is
possibly
related
to
the
metaphors
being
perceived
as
nonsensical
or
 containing
 novel
 semantic
 information
 (Mashal
 et
 al.,
 2009).
 The
 right
 hemisphere
 is
 thus
 involved
 in
 pragmatic
 processing
on
a
meta‐syntactic
level
(Mitchell
&
Crow,
2005).
 


1.2.5   Laterality  The
 dominance
 of
 a
 hemisphere
 in
 language
 processing
 can
 be
 quantified
 as
 the
 degree
 of
 lateralization.
 A
 non‐typical
 degree
 of
 lateralization
 has
 been
 attributed
 to
 both
 language
 abilities
 and
 disabilities
 (cf.
 the
 first
 section
 ‘Language
 Abilities’).
 Knecht
 and
 colleagues
 (2000)
 tested
 188
 healthy
right‐handed
adults
for
language
lateralization
in
the
brain
with
a
word
generation
fMRI
task.
 This
task
has
been
widely
reported
to
be
a
powerful
and
effective
paradigm
for
generating
language
 production
 (Neils‐Strunjas
 1998).
 Language
 lateralization
 study
 results
 have
 indicated
 that
 there
 is
 no
 difference
 in
 language
 lateralization
 ratios
 between
 males
 and
 females.
 Furthermore,
 a
 left‐
 to
 right‐hemispheric
 dominance
 ratio
 of
 13
 to
 1
 was
 established
 (Knecht
 et
 al.,
 2000).
 Besides
 fMRI,
 dichotic
 listening
 is
 an
 alternative
 and
 feasible
 non‐invasive
 method
 to
 test
 for
 language
 lateralization
 (Hugdahl
 2011).
 The
 dichotic
 listening
 method
 is
 based
 on
 the
 notion
 that
 bi‐aural
 auditory
 stimuli
 travel
 more
 easily
 to
 the
 contralateral
 rather
 than
 ipsilateral
 hemisphere,
 due
 to
 more
 extensive
 contralateral
 than
 ipsilateral
 pathways
 from
 the
 ear
 to
 the
 auditory
 cortex.
 Also,
 there
 is
 a
 blocking
 of
 ipsilateral
 pathways
 during
 conflicting
 input.
 After
 travelling
 to
 the
 contralateral
cortex,
the
auditive
signals
are
processed
more
automatically
in
the
hemisphere
that
is
 dominant
for
language.
Ergo,
the
language‐dominant
hemisphere
presumably
resides
contralateral
to
 the
ear
that
processes
more
stimuli
during
bi‐aural
stimulation
(Kimura,
2011).





9


1.

INTRODUCTION


Differences
 between
 methods
 to
 test
 for
 laterality
 are
 discussed
 by
 Abou‐Khalil
 (2007),
 who
 concluded
 that
 fMRI
 was
 one
 of
 the
 most
 realizable
 techniques4.
 The
 clear
 advantage
 of
 fMRI
 over
 dichotic
 listening
 is
 that
 fMRI
 can
 localize
 activation.
 Nonetheless,
 dichotic
 listening
 is
 superior
 in
 practicality,
both
in
terms
of
costs
and
of
convenience.
It
is
also
important
to
realize
that
the
laterality
 measurements
 obtained
 by
 fMRI
 are
 very
 much
 dependent
 on
 which
 language
 task
 is
 chosen.
 Both
 word
 fluency
 and
 sentence
 comprehension
 seem
 to
 be
 indicative
 of
 determining
 language
 lateralization
(Niskanen
et
al.,
2012).
 Besides
ear
dominance,
hand
dominance
is
also
seen
to
have
a
direct
connection
to
the
contralateral
 hemispheric.
Right‐handedness
is
highly
correlated
with
left‐hemispheric
language
dominance
(in
94
 –
 96
 %
 of
 right‐handers).
 In
 left‐handers,
 it
 is
 slightly
 more
 common
 to
 have
 right‐hemispheric
 dominance,
yet
78
%
of
the
left‐handed
population
is
also
left
dominant
for
language
(Szaflarski
et
al.,
 2002).


Language
lateralization
is
thought
to
correlate
with
differences
in
gray
matter
between
hemispheres,
 and
 when
 the
 cortex
 is
 damaged,
 language
 lateralization
 for
 expressive
 language
 functions
 can
 change
(Lee
et
al.,
 2008).
Josse
and
colleagues
(2009)
investigated
how
gray
matter
differences
could
 predict
language
lateralization,
and
showed
that
when
gray
matter
is
analyzed
with
a
voxel‐by‐voxel
 method,
 structural
 asymmetry
 correlated
 well
 with
 language
 lateralization.
 However,
 these
 correlations
 were
 lost
 when
 global
 lateralization
 was
 compared
 with
 regional
 gray
 matter
 asymmetries.
Nowadays,
local
lateralization
is
of
interest
and
many
researchers
prefer
to
investigate
 the
lateralization
of
separate
regions
(Seghier
et
al.,
 2011b).
A
strong
lateralization
of
cognition
has
 been
linked
to
high
cognitive
performance
(Güntürkün
et
al.,
 2000).
Recently,
an
opposing
view
has
 emerged,
namely
that
the
optimal
degree
of
lateralization
for
high
cognitive
performance
was
small.
 In
other
words;
a
higher
degree
of
bilaterality
might
be
more
favorable
for
performance
(Hirnstein
et
 al.,
2010).
 


1.2.6   Anti‐correlated Brain Activation  In
 PAPER
 IV
 we
 examine
 activation
 that
 is
 correlated
 negatively
 with
 language
 tasks;
 this
 can
 be
 labeled
as
deactivation.
Deactivation
is
the
decrease
of
signal
in
regions
that
are
activated
during
rest
 but
not
during
task
condition,
thus
functions
in
these
regions
are
thought
to
be
suppressed.
Some
of
 these
regions
form
a
network
that
is
consistently
activated
during
rest
and
deactivated
during
tasks;
 this
 is
 called
 the
 Default
 Mode
 Network
 (DMN).
 DMN
 activation
 is
 associated
 with
 ‘free
 thinking’


























































 4
cf.
(Medina
et
al.,
2007),
who
presents
an
overview
of
the
reliability
of
fMRI‐obtained
laterality


measurement.




10






1.

INTRODUCTION


processes
 –
 often
 referred
 to
 as
 thinking
 about
 the
 day,
 shopping
 lists,
 and
 what’s
 for
 dinner
 –
 therefore
 the
 suppression
 of
 DMN
 activation
 enables
 a
 person
 to
 allocate
 more
 cognitive
 power
 to
 the
task.
Heterogeneity
of
the
anti‐correlation
during
a
semantic
task
in
the
different
regions
of
the
 DMN
is
to
be
expected
(Seghier
&
Price,
 2012).
A
difference
in
suppression
of
the
DMN
between
the
 task
and
control
condition
can
also
be
expected,
depending
on
how
engaging
the
control
condition
is.
 Deactivation
patterns
might
be
just
as
necessary
as
activation
patterns
to
explain
brain
functioning
 (Binder
2012).
 




1.3   Intelligence models for Language Ability  


1.3.1   Relation Language Ability and Intelligence  There
 is
 an,
 although
 limited,
 correlation
 between
 language
 ability
 and
 intelligence
 (e.g.
 word
 fluency:
 Haier
 et
 al.,
 1992;
 Roca
 et
 al.,
 2010;
 semantics:
 Prat
 et
 al.,
 2007).
 Some
 intelligence
 models
 describe
 processes
 that
 can
 be
 applied
 to
 language
 ability
 as
 well,
 and
 help
 to
 understand
 the
 differences
 in
 language
 performance
 observed
 in
 previous
 and
 our
 current
 work.
 Intelligence
 is
 attributed
to
a
parieto‐frontal
network
that
includes
several
regions
and
connections
that
are
shared
 with
 language
 processing
 functions.
 This
 network
 is
 described
 in
 the
 Parieto‐Frontal
 Integration
 Theory
 of
 intelligence
 (Jung
 &
 Haier,
 2007).
 A
 second
 intelligence
 theory
 is
 the
 neural
 efficiency
 hypothesis
of
intelligence
(Haier
et
al.,
 1992).
This
theory
describes
how
well‐developed
skills
can
be
 characterized
 by
 a
 more
 effective
 manner
 of
 processing
 in
 the
 brain.
 Thus;
 high‐skilled
 individuals
 will
show
a
decreased
brain
activation
compared
with
lower‐skilled
persons.
This
reasoning
can
be
 applied
 to
 language
 skills
 as
 well,
 as
 will
 be
 put
 forward
 in
 the
 next
 section.
 Lastly,
 neural
 adaptability
is
discussed;
this
is
a
trait
observed
in
high‐skilled
individuals.
These
theories
together
 may
explain
the
functional
activation
patterns
observed
in
high
performers
(e.g.
Prat
 2011;
Langer
et
 al.,
2012).
 


1.3.2   Intelligence Models  The
Parieto­Frontal Integration Theory (P­FIT) of intelligence
is
a
summation
of
regions
in
a
network
 found
to
show
activation
dependent
on
intelligence
level
(Jung
&
Haier,
2007).
It
has
been
known
that
 neural
correlates
to
high
intelligence
are
located
in
the
prefrontal
cortex
(Thompson
et
al.,
2001),
and
 that
increased
gray
and
white
matter
is
observed
in
both
frontal
and
parietal
regions
in
correlation





11


1.

INTRODUCTION


with
 high
 intelligence
 (Neubauer
 &
 Fink,
 2009).
 The
 P‐FIT
 of
 intelligence
 states
 that
 it
 takes
 a
 network
 of
 interactive
 regions
 to
 provide
 high
 abilities.
 The
 functions
 are
 divided
 within
 this
 network
from
caudally
located
rule
generating
processes,
to
rostral
functions
such
like
selecting,
and
 testing
of
answers.
The
network
includes
the
language
processing
areas
in
the
posterior
perisylvian
 region.
 The
Neural efficiency hypothesis of intelligence
states
that
networks
for
cognitive
functions
work
in
a
 more
efficient
manner
in
intelligent
brains.
Therefore,
intelligent
brains
will
show
less
activation
in
 task‐specific
networks
during
imaging
studies.
Haier
and
colleagues
(1992)
state
that
the
mechanism
 behind
 neural
 efficiency
 might
 be
 deactivation
 of
 irrelevant
 brain
 areas,
 or
 a
 more
 specific
 use
 of
 task‐related
 areas.
 The
 neural
 efficiency
 hypothesis
 of
 intelligence
 appears
 to
 be
 limited
 to
 frontal
 regions,
 and
 conditional
 on
 task
 as
 well
 as
 task‐difficulty
 (Neubauer
 &
 Fink,
 2009).
 Predominantly
 frontal
 activation
 patterns
 in
 high
 performers
 show
 efficient
 behavior
 during
 easy
 to
 moderately
 difficult
 tasks.
 Activation
 in
 the
 frontal
 region
 has
 previously
 been
 shown
 to
 decrease
 upon
 automation
of
processes
(Ramsey
et
al.,
 2004).
When
demands
get
high,
this
is
no
longer
true;
high
 performers
then
recruit
more
brain
regions
to
solve
the
task.
The
high
intelligent
individuals
might
 have
more
adaptive
strategies
than
low
performers
and
can
–
depending
on
task
demand
–
either
use
 their
brain
efficiently
or
call
in
the
help
of
supporting
brain
regions
(Doppelmayr
et
al.,
 2005).
Neural
 efficiency
 patterns
 have
 been
 observed
 in
 high
 capacity
 readers
 during
 sentence
 comprehension
 (Maxwell
et
al.,
1974;
Prat
et
al.,
2007;
Prat
&
Just,
2011).
 The
 additional
 recruitment
 of
 supporting
 neural
 resources
 whenever
 a
 task
 is
 difficult
 may
 be
 described
 as
 Neural  adaptability
 (Prat
 et
 al.,
 2007).
 It
 is
 hypothesized
 that
 individuals
 highly
 proficient
in
language
show
more
neural
adaptability
compared
with
people
with
lower
proficiency.
 This
can
be
observed
as
activation
in
language‐related
regions,
either
in
main
language
regions
or
in
 additional
supportive
regions.

 Evidently,
the
theories
above
outline
a
varied
pattern
of
the
relation
between
high
performance
and
 neural
 activation
 or
 deactivation.
 This
 pattern
 is
 dependent
 on
 task,
 task
 demands
 and
 functional
 region.
In
the
Discussion
the
considerations
concerning
the
interpretation
of
brain
activation
will
be
 further
explored.
 
 




12






1.

INTRODUCTION


1.4   Aims  
 Language
 ability
 in
 healthy
 adults
 was
 expected
 to
 be
 visualized
 as
 a
 modulation
 of
 activation
 in
 language‐related
regions,
with
respect
to
the
level
of
activation,
but
also
the
degree
of
lateralization
 between
hemispheres.
 PAPER
 I
 aimed
 to
 determine
 regional
 lateralization
 of
 semantic
 language
 functions
 in
 relation
 to
 performance
 in
 tests
 of
 language
 ability.
 It
 was
 expected
 to
 find
 laterality
 differences
 related
 to
 performance
 in
 the
 IFG
 and
 posterior
 temporal
 lobe,
 for
 both
 fMRI‐obtained
 laterality
 and
 for
 dichotic
listening.
 PAPER
 II
 aimed
 to
 find
 the
 neural
 correlates
 to
 language
 ability
 throughout
 the
 whole
 brain.
 The
 expectation
was
to
find
specific
regions
in
the
right
IFG
and
posterior
temporal
lobe
activated
during
 from
a
semantic
task
that
were
related
to
high
performance
in
tests
of
language
ability.
Furthermore,
 brain
activation
during
word
fluency
was
investigated
and
compared
with
semantic
results,
in
order
 to
find
whether
there
were
similarities
in
activation
patterns
related
to
high
language
ability.
 PAPER
III
aimed
to
reproduce
the
findings
of
PAPER
I
and
PAPER
II
in
a
new
study
population.
Thus,
 activation
 during
 semantic
 and
 word
 fluency
 tasks
 that
 emerged
 in
 the
 right‐hemispheric
 homologues
 of
 Broca’s
 and
 Wernicke’s
 area
 were
 investigated
 for
 their
 correlation
 with
 high
 performance
 in
 tests
 of
 language
 ability.
 In
 addition,
 activation
 related
 to
 task
 demand
 was
 investigated.
 Brain
 activation
 patterns
 related
 to
 high
 performance
 were
 expected
 to
 show
 neural
 efficiency
 for
 low‐demand
 tasks
 in
 the
 IFG.
 Furthermore,
 high
 language
 ability
 was
 expected
 to
 be
 characterized
by
neural
adaptability;
i.e.
increased
right‐hemispheric
contributions.
 PAPER
IV
aimed
to
investigate
language
deficits
in
people
with
generalized
epilepsy.
This
group
was
 also
expected
to
show
an
inadequate
suppression
of
the
default
mode
network
that
is
normally
 highly
anti‐correlated
with
the
task.




13



 
 
 
 
 
 
 
 


 

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Stipe,
Peter
Buck,
Michael
Mills
 




14




  
 


2 METHODS  
 


2.1   Neurolinguistic Measures  


2.1.1   Tests of Language Ability  In
PAPER
I
and
PAPER
II,
four
tests
to
measure
language
ability
were
used:
FAS
and
BNT
measured
 word
retrieval
abilities,
and
BeSS
and
Read
measured
language
comprehension
abilities.
In
PAPER
III
 and
IV,
only
BeSS
and
FAS
were
used.
 FAS
 is
 a
 phonemic
 word
 generation
 test
 in
 which
 participants
 are
 cued
 with
 a
 letter
 (F,
 A,
 S),
 and
 have
to
generate
as
many
words
as
possible,
starting
with
the
cue
letter.
Total
score
is
the
number
of
 generated
words
for
all
three
letters.
BNT
is
the
established
Boston
Naming
Test.
During
the
test,
the
 participant
is
presented
with
60
pictures
that
have
to
be
named.
 BeSS
(
“Bedömning
av
Subtila
Språkstörningar”
or
Assessment
of
Subtle
Language
Deficits)
tests
for
 the
use
of
complex
language
by
means
of
seven
subtasks
(Laakso
et
al.,
2000).
Those
subtasks
are:





REP



repetition
of
long
sentences
(9‐16
words)


CON



sentence
construction
(from
three
words,
with
given
context,
under
time
pressure)


INF



inferential
reasoning
(based
on
a
read
text)


COM



comprehension
of
complex
embedded
sentences


GAR



comprehension
of
garden‐path
or
ambiguous
sentences


MET



comprehension
of
metaphors


VOC



vocabulary
–
word
definition


15


2.

METHODS


Maximum
score
was
210
points.
 The
Read
test
is
selected
from
a
Swedish
exam
for
university
students.
Participants
had
to
read
three
 texts
and
answer
four
questions
on
each
text.
The
total
score
was
the
number
of
correctly
answered
 questions.
 


2.1.2   Dichotic Listening  Dichotic
Listening
scores
were
acquired
in
PAPER
I
with
the
use
of
a
version
of
the
Bergen
Dichotic
 Listening
 Test
 (Hugdahl
 1995),
 which
 is
 a
 consonant‐vowel
 test.
 Auditive
 stimuli
 created
 from
 the
 combination
of
a
stop
consonant
and
the
vowel
‘a’
(e.g.
ba
–
ga
–
pa)
were
presented
bi‐aurally
to
the
 participants.
Depending
on
the
instructions,
the
participants
had
to
report
the
stimuli;
either
heard
in
 the
left
or
the
right
ear;
in
both
ears;
or
the
most
salient
stimulus.
The
results
were
calculated
as
a
 right
ear
advantage;
subtracting
correct
responses
perceived
by
the
left
ear
from
those
heard
in
the
 right
 ear,
 then
 dividing
 this
 figure
 by
 the
 number
 of
 total
 correct
 responses.
 A
 high
 right
 ear
 advantage
meant
that
the
subject
was
better
at
reproducing
stimuli
heard
in
the
right
ear,
compared
 with
 the
 left
 ear.
 This
 was
 interpreted
 as
 a
 lateralization
 index
 for
 language;
 a
 high
 right
 ear
 advantage
meant
strong
left‐hemispheric
lateralization.
 


2.1.3   fMRI Language Paradigms  The
word
generation
task
WORGE
from
PAPER
II
was
as
described
in
(Engström
et
al.,
2010)
but
with
 moderation
of
the
control
condition.
The
participants
were
cued
with
a
letter
taken
from
the
Swedish
 alphabet,
excluding
C,
Q,
W,
X,
Y,
Z,
Å,
Ä,
and
Ö.
They
were
instructed
to
generate
words
with
the
cued
 letter,
as
many
as
possible
within
the
given
time
of
 5
s.
The
cue
letters
were
varied
and
presented
in
 blocks
 containing
 three
 to
 five
 letters,
 pseudorandomly
 ordered.
 The
 baseline
 or
 control
 task
 consisted
of
presentation
of
an
asterisk
alternated
with
a
row
of
asterisks.
 The
 word
 generation
 task
 WORD
 is
 described
 in
 PAPER
 III.
 Similarly
 to
 WORGE,
 a
 cue
 letter
 was
 presented,
 but
 this
 time
 the
 cue
 letters
 were
 divided
 into
 two
 difficulty
 categories;
 ‘easy’
 (frequent
 starting
 letter
 in
 a
 Swedish
 word
 list)
 and
 ‘hard’
 (infrequent
 starting
 letter).
 The
 letters
 were
 presented
per
category
in
a
block
of
seven
letters,
alternating
with
control
blocks.
The
control
block
 differed
from
WORGE
in
the
sense
that
only
one
asterisk
was
presented
each
trial.
 The
sentence
completion
task
SENCO
is
described
in
PAPER
I.
This
was
a
cloze
task;
the
participant
 had
to
silently
generate
the
missing
last
word
of
a
sentence.
The
sentences
were
presented
in
blocks,




16






2.

METHODS


the
presentation
duration
of
a
sentence
was
 3
s
followed
by
display
of
an
asterisk
for
 2
s.
The
control
 condition
consisted
of
asterisks
mimicking
a
short
sentence.
 The
 congruent/incongruent
 sentence
 reading
 task
 SEN
 is
 described
 in
 PAPER
 III.
 The
 participants
 were
 presented
 with
 blocks
 differing
 in
 difficulty
 level;
 either
 congruent
 (‘easy’
 condition)
 or
 incongruent
(‘hard’
condition)
sentences,
or
control
blocks
containing
a
row
of
asterisks
and
arrows.
 The
 participants
 had
 to
 judge
 whether
 the
 situation
 described
 in
 the
 sentence
 took
 place
 inside
 or
 outside.
During
the
control
condition,
the
participants
had
to
report
in
which
direction
the
arrow
was
 pointing.
 


2.1.4   Study Population  Study
A
investigated
a
healthy
adult
population
of
 18
participants:
nine
females
and
nine
males
aged
 21‐64
 (mean
 age:
 40).
 For
 PAPER
 1,
 a
 subset
 of
 14
 participants
 (seven
 females,
 seven
 males)
 were


investigated,
aged
21‐55
(mean
age:
36.9).
 Study
B
investigated
two
groups.
First,
a
healthy
adult
population
of
 27
participants:
 14
females
and
 13
males
aged
18‐35
(mean
age:
25.5)
was
investigated.
The
analyses
from
PAPER
III
were
performed


on
data
from
this
group.
For
PAPER
IV;
the
healthy
control
group
was
compared
with
a
group
of
 11
 people
with
generalized
epilepsy:
six
females
and
five
males,
with
an
age
range
of
 20‐35
years
(mean
 age:
 26.5).
 In
 both
 the
 healthy
 control
 group
 and
 in
 the
 group
 of
 people
 with
 generalized
 epilepsy
 there
was
a
left‐handed
individual.
 All
participants
had
Swedish
as
their
first
language
and
were
screened
by
means
of
a
questionnaire
 on
 the
 absence
 of
 neurological,
 cognitive
 or
 psychiatric
 disorders
 and
 magnetic
 resonance
 contra‐ indications.



 2.1.5   Generalized Epilepsy  The
 different
 types
 of
 epilepsy
 can
 be
 classified
 according
 to
 etiology.
 This
 results
 in
 a
 distinction
 between
 generalized
 epilepsies
 with
 genetically
 inherited
 origin,
 and
 focal
 epilepsies
 (Berg
 et
 al.,
 2010;
Poduri
&
Lowenstein,
2011).
People
with
generalized
epilepsy
(GE)
show
a
widespread
atypical


cortical
activity
(Marini
et
al.,
2003)
and
may
experience
language
problems
(Chaix
et
al.,
2006;
Caplan
 et
al.,
2009).
GE
is
also
related
to
an
abnormal
connectivity
in
the
default
mode
network
(McGill
et
al.,
 2012).








17


2.

METHODS


2.2   Functional MRI  


2.2.1   Properties of Functional MRI  Functional
 MRI
 can
 detect
 susceptibility
 changes
 in
 the
 blood
 that
 arise
 depending
 on
 the
 amount
 oxygen
 that
 is
 present.
 Neurons
 that
 are
 activated
 exchange
 neurotransmitters,
 and
 this
 exchange
 process
 consumes
 oxygen.
 This
 is
 overcompensated
 by
 transport
 of
 an
 abundance
 of
 oxygenated
 blood5
to
the
activated
area,
the
oxygenated
blood
differs
from
the
surrounding
deoxygenated
blood
 in
magnetic
properties.
This
process
is
called
the
blood
oxygen
level
dependent
(BOLD)
response
and
 is
 measured
 using
 susceptibility
 sensitive
 magnetic
 resonance
 sequences6.
 Since
 changes
 in
 blood
 flow
are
slow,
the
fMRI
signal
has
a
low
temporal
aspect.
Furthermore,
the
magnetization
difference
 is
very
subtle,
with
a
low
signal‐to‐noise
ratio.
Therefore,
a
common
approach
is
to
repeat
the
action
 or
stimulus
that
evokes
the
pattern
of
interest
many
times,
and
calculate
the
average
of
the
response.
 The
 highest
 power
 is
 obtained
 when
 stimuli
 are
 presented
 in
 blocks,
 and
 the
 blocks
 for
 different
 conditions
 and
 the
 baseline
 are
 presented
 in
 an
 alternating
 sequence.
 To
 get
 a
 measure
 of
 neural
 activation
per
condition
in
each
spatial
unit
(i.e. voxel),
a
standard
approach
is
to
model
the
expected
 BOLD
response
with
the
general
linear
model
(GLM),
which
is
then
fitted
to
the
data.
This
model
is
 time‐variant.
An
equation
for
the
GLM
is
given
as

Y
=
Xβ
+
ε
,
in
which
Y
is
the
data
represented
by
 the
 design
 matrix
 X
 (the
 design
 matrix
 models
 aspects
 of
 the
 experiment
 such
 as
 conditions
 or
 performance
 covariates)
 times
 the
 parameter
 estimates
 β
 (estimates
 for
 the
 data
 that
 explain
 as
 much
 as
 possible).
 The
 ε
 is
 the
 residual
 error
 term.
 In
 our
 studies,
 we
 used
 statistical
 parametric
 mapping
(SPM)7
to
model
the
GLM
on
our
data.
All
our
studies
were
collected
with
a
Philips
Achieva
 1.5
 tesla
 scanner,
 using
 gradient‐echo
 planar
 imaging
 sequences.
 The
 obtained
 images
 were
 all


normalized
to
a
standard
brain
with
coordinates
in
Montreal
Neurological
Institute
(MNI)
space.
 The
 activation
 pattern
 for
 each
 condition
 can
 be
 quantified
 by
 subtracting
 the
 number
 of
 activated
 voxels
 in
 one
 condition
 from
 another.
 Most
 often
 are
 task
 conditions
 compared
 to
 a
 baseline
 condition.
Subsequently,
the
significance
of
the
first‐level
analysis
results
(testing
individuals)
can
be
 tested
by,
for
example,
t‐tests.
Thus,
testing
for
activation
related
to
a
certain
condition
can
be
done
 by
subtracting
baseline
activation
from
activation
during
the
condition.
Testing
for
deactivation
can


























































 5
To
be
precise;
it
is
the
hemoglobin
protein
that
transports
oxygen
in
the
blood.
Hence
the
term


‘hemodynamic
response
function’
that
is
used
to
describe
the
overcompensation
of
oxygen
 transport
to
active
neurons.
 6
Paramagnetic
deoxygenated
blood
disturbs
the
magnetic
resonance
signal,
by
hastening
the
 dephasing
of
protons
that
emit
this
signal.
If
the
amount
of
oxygenated
blood
increases,
the
 measured
signal
increases
as
well.
 7
www.fil.ion.ucl.ac.uk/spm/software




18






2.

METHODS


be
 done
 by
 subtracting
 condition
 activation
 from
 baseline
 activation.
 The
 resulting
 statistical
 maps
 can
be
entered
into
a
second‐level
analysis
to
test
on
group
level.
Two
groups
can
be
compared
with
 a
 two‐sample
 t‐test,
 or
 if
 data
 fluctuation
 depending
 on
 individual
 performance
 scores
 is
 investigated,
a
multiple
regression
approach
can
be
taken.
For
our
multiple
regression
analysis,
we
 corrected
for
age
by
modeling
age
as
a
covariate
and
tested
for
individual
performance
differences
by
 modeling
performance
score
as
a
covariate
of
interest.
 


2.2.2   Region of Interest Analysis  If
the
location
of
expected
activation
is
reasonably
certain,
and
an
analysis
of
the
whole
brain
is
not
 required,
 the
 analysis
 can
 be
 restricted
 to
 regions
 of
 interest
 (ROIs).
 In
 our
 studies,
 ROIs
 were
 obtained
in
different
ways,
a posteriori
and
a priori,
to
answer
different
questions.
In
PAPER
II,
the
 whole‐brain
 analysis
 results
 were
 used
 to
 guide
 placement
 of
 small
 spherical
 ROIs
 at
 significant
 peaks
 of
 activation.
 Parameter
 estimates
 were
 calculated
 from
 an
 ROI
 analysis
 and
 then
 tested
 for
 their
 correlation
 strength
 with
 performance.
 To
 report
 the
 strength
 of
 these
 correlations
 as
 a
 measure
 of
 significance
 would
 give
 an
 inflated
 measurement,
 since
 this
 is
 a
 second
 correlation
 of
 fMRI
 data
 with
 performance
 scores.
 Therefore,
 our
 post­hoc
 results
 were
 merely
 used
 to
 filter
 out
 low‐significant
correlations
from
the
regions
that
were
significant
in
the
multiple
regression
analysis
 with
 a
 p‐value
 threshold
 of
 0.01,
 corrected
 for
 multiple
 measurements
 by
 means
 of
 the
 false
 discovery
rate
 In
 Study
 B
 that
 led
 to
 PAPER
 III
 and
 PAPER
 IV,
 we
 had
 an
 expectation
 of
 which
 regions
 would
 be
 active.
 Therefore,
 we
 were
 able
 to
 restrict
 our
 statistical
 tests
 to
 include
 only
 the
 voxels
 in
 the
 predicted
 regions
 and
 thus
 correct
 the
 significance
 calculation
 for
 the
 small
 volumes
 used.
 For
 the
 unpublished
 results
 related
 to
 the
 healthy
 population
 in
 Study
 B
 that
 are
 discussed
 in
 this
 dissertation,
we
used
the
following
ROIs:
the
IFG
pars
opercularis
(BA
 44),
IFG
pars
triangularis
(BA
 45),
 IFG
 pars
 orbitalis
 (BA
 47),
 the
 middle
 and
 superior
 temporal
 gyri
 –
 described
 as
 the
 ‘posterior


temporal
lobe’,
and
the
angular
gyrus
(BA
39).
Here,
only
results
significant
at
p