Functional network organizations of two contrasting temperament groups in dimensions of novelty...
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Functional Network Organisations of two contrasting temperament groups in dimensions of novelty seeking and harm avoidance
Sunghyon KyeongNational Institute for Mathematical Science (NIMS), Daejeon, Republic of Korea
Published at Brain ResearchDOI: 10.1016/j.brainres.2014.05.037
Joint work with Eunjoo Kim, Hae-Jeong Park, and Dong-Uk Hwang
Application of Graph Theoretical Methodology "
to"
Behavioural Neuroscience
In behavioural neuroscience,"behavioural characteristics of individuals originating from the different patterns of functional activity and morphometric variation in the brain
In psychology,"patterns of an individuals’s emotion, thoughts and behaviours"generally stable throughout his or her life and across situations.
Personality
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
TCI, a measure of personality
• Temperament and character Inventory (TCI) was developed by Cloninger (1994).
• TCI traits were originally proposed to be independent of one another.
• However, meta-study found a significant negative correlation between Harm Avoidance (HA) and Novelty Seeking (NS) (Miettunen et al. 2008).
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
HA and NS• Harm avoidance (HA) is a personality trait
characterised by excessive worrying, shyness, and being fearful, doubtful, and easily fatigued.
• Novelty seeking (NS) is a personality trait associated with exploratory activity in response to novel stimulation, impulsive decision making, and quick loss of temper and avoidance of frustration.
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
Think about your friends
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• Novelty seeking is positively related to active, energetic activity."
• A high novelty seeking trait has been suggested to be related to high dopaminergic activity.
• Harm avoidance is positively related to passive, avoiding, hesitating behaviours."
• A high harm avoidance trait has been suggested to be related to avoid high risky (or harmful) activity.
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
• Our goal is to identify the characteristics of the functional network modular organisations that make two contrasting temperament groups different."
• Existing studies didn’t show how the brain networks are organised across personality groups."
• Recently, brain modular organisations of three different impulsivity groups (i.e. low, medium, and high) were revealed (F. Caroline Davis et al. (2012)).
Objective
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
Key Regions associated with Temperament
Prefrontalprefrontal cortex, orbitofrontal cortex,
anterior cinculate cortex
Basal Ganglia Caudate,Putamen,Pallidum,Thalamus
LimbicAmygdala,Hippocampus,Parahippocampal gyrus
Cremers H et al. 2011, Omura K et al. 2005, Yamasue H et al. 2008 Deckersbach T et al. 2006
Yamasue H et al. 2008, Iidaka T et al. 2006, Omura K et al. 2005
Haier RJ T et al. 1987, O’Gorman RL et al. 2006
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Prefrontal
Limbic
Temperament traits & Regional association
Personality & Local brain
activity
GLM approach
“connectome” approach
Materials and Methods
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
10 20 30 40 50 60 700
10
20
10 20 30 40 50 60 700
5
10
15
90 100 110 120 130 1400
5
10
Subjects and Materials
...
high-resolution T1 resting state fMRI (404 scans with TR=2s)
• Brain Images Acquisition at Severance:
• 40 healthy male subjects (25.2 ± 3.3 years)
• TCI with 140 items & K-WAIS at Severance
NS HA IQ
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
the mean of points in Si
The goal of k-means clustering is to minimise the within-cluster sum of squares.
V =2X
i=1
X
xj2Si
||xj
� µ
i
||2 S = {S1, S2}
p=0.0024 p<0.0001 p=0.0004 p=0.0115 p<0.0001 p=0.0436 p=0.0122
20 30 40 50 60 700
10
20
30
40
50
60
70
Novelty Seeking
Har
m A
void
ance
IntrovertsExtravertsCentroids
20 30 40 50 60 70 Novelty Seeking
Harm
Avo
idan
ce
70
60
50
40
30
20
10
0
Subject Clustering
A. k-means Clustering B. Group comparison of TCI traits
high HA & low NS low HA & high NSCentroids×
high HA & low NS group
low HA & high NS group
Trai
t Sco
re
010203040506070
NS HA P SD C STRD
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
Mechanism of BOLD fMRI
Time
Signal
Mo sinθ
T2* (task)
T2* (control)
TEoptimum
Stask
Scontrol ΔS
↑ Neural Activity ↑ Blood Flow ↑ Oxyhemoglobin
↑ T2*
↑ MR Signal
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
Network Construction
...
...
Spatial Preprocessingrealignment, co-registration, normalisation, and smoothing
Parcellation into 116 brain regions
Adjacent Matrix
AAL atlas
Akij
Individual functional network for k-th subject
• Network extraction in individual level
FN `ij =
1
nl
X
k2G`
Akij
G`
FN `ij
Adjacency matrices in a group
Group Averaged FN
where is a set of subjects within group l
• Group averaged functional network (FN)
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
Community Detection
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Functional network communities of each group was detected by the Louvain method which maximises the modularity, Q.
where si is the sum of the weights of the edges attached to node i; Ci is the modular (community) structure to which vertex i is assigned.
A community is a dense subnetwork within a larger network.
Results
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
Functional Network (FN)A. high HA and low NS group B. low HA and high NS group
Modules:$Visual,$Motor,$Frontal,$BG/THL,$PFC+Limbic Modules:$Visual,$Motor,$Frontal,$Limbic,$PFC+BG/THL
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
PFC Limbic BG/THL
0.5
0.4
0.3
0.2
0.1
0
FN Density (high HA and low NS)"(numbers represent group average FN density)
FN Density (low HA and high NS) (numbers represent group average FN density)
Two sample T-Test(numbers represent p-value)
0.39
0.0655 0.0089 0.8193
0.178 0.0681
0.6718
0.43 0.14 0.1
0.38 0.08
0.4
0.37 0.07 0.11
0.42 0.12
0.39
PFC Limbic BG/THLPFC Limbic BG/THL
OLF.L
ACC.R
ACC.LACC.L
RG.L
mOFC.L
OLF.R
AMYG.L AMYG.R
HIP.L
HIP.RPHG.L
PHG.R
CAU.R
CAU.L
TAL.R
TAL.L
PUT.L
SOFC.R
SOFC.LmOFC.R
0.37
0.39 0.42
0.11 0.07
0.12
PAL.R
PAL.L
PUT.R
OLF.L
ACC.R
ACC.LACC.L
RG.L
mOFC.L
OLF.R
AMYG.L AMYG.R
HIP.RPHG.L
PHG.R
CAU.R
CAU.L
TAL.R
TAL.L
PAL.R
PAL.L
PUT.R
PUT.L
SOFC.R
SOFC.LmOFC.R
0.43
0.40 0.38
0.10 0.14
0.08
HIP.L
FN Sub-Graph and FCD
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PFC
BG/THL Limbic
PFC
BG/THL Limbic
A. high HA and low NS B. low HA and high NS
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
20 30 40 50 60
−0.2
−0.1
0
0.1
0.2
Novelty Seeking20 30 40 50 60
−0.2
−0.1
0
0.1
0.2
Harm Avoidance
Corr. (FCD, TCI)
0.2
0.1
0
C0.1
C0.2
Novelty Seeking20 30 40 50 60
Dens
ity o
f fun
ctio
nal c
onne
ctivi
ty
of th
e PF
C an
d Li
mbi
c Cl
uste
rs 0.2
0.1
0
C0.1
C0.2
Harm Avoidance20 30 40 50 60
r=0.30 (p=0.0588)r=-0.52 (p=0.0006)
correlation was computed while controlling age.
correlation between functional connectivity density (FCD) and temperament traits: (1) FCD between PFC and Limbic territories and NS; (2) FCD between PFC and Limbic territories and HA.
High HA and low NSLow HA and high NSFitting Curve
High HA and low NSLow HA and high NSFitting Curve
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
3.5 4 4.5
20
30
40
50
60
BG/THL Volume (cm3)4.2 4.6 5 5.4 5.8
20
30
40
50
60
Limbic Volume (cm3)
Harm
Avo
idan
ce
r=0.37 (p=0.0188) r=0.50 (p=0.0013)
60
50
40
30
20
70
3.5 4 4.5
20
30
40
50
60
BG/THL Volume (cm3)4.2 4.6 5 5.4 5.8
20
30
40
50
60
Limbic Volume (cm3)
Nove
lty S
eekin
g
r=-0.32 (p=0.0466) r=-0.30 (p=0.0659)
60
50
40
30
20
70
Volume of Limbic (cm3)4.2 4.6 5.0 5.4 5.8
Volume of BG/THL (cm3)4.6 5.0 5.4
Harm
Avo
idan
ceNo
velty
See
king
60
50
40
30
20
70
60
50
40
30
20
70
Corr. (GMV, TCI)High HA and low NS Low HA and high NS Fitting Curve
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correlation was computed while controlling age.
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
4 4.5 5 5.5 6−0.3
−0.2
−0.1
0
0.1
0.2
0.3
Volume of Limbic (cm3)
FC D
ensi
ty (b
etw
een
PFC
and
Lim
bic)
Volume$of$Limbic$(cm3)4.0 4.5 5.0 5.5 6.0
Density$of$Functional$Connectivity
of$PFC$and$Limbic$Clusters
0.3
0.2
0
C0.1
C0.2
0.1
C0.3
r= 0.45 (p=0.0033)
High$HA$and$low$NS
Low$HA$and$high$NSFitting$Curve
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Coupling (FCD, VBM)
Discussion
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
• Female subjects should be included to generalise the results regardless of gender."
• Structural networks from diffusion tensor imaging data could be considered to promote deeper insights into the neural correlates of personality."
• Cross-cultural study would advance the understanding of personality."
• Other questionnaires (Eysenck’ personality scale) should be performed to check the extraversion score directly.
In the future study,the followings should be considered.
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |24
Neural Substrates for high HA and low NS group
PFC
BG/THL
Limbic
• The neural substrate of the individuals with ‘high HA and low NS’ group arise from the increased connectivity between PFC and Limbic. "
• Individuals with High HA and low NS showed the inhibited behaviour because the regulatory brain region such as the PFC is strongly association with fear related brain region such as the limbic system.
Designed(by( Eunha&Lim
Neural Network for Introverted Individuals
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S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |25
Neural Substrates for low HA and high NS group• The neural substrate of the individuals with low HA and high NS arise
from the strong connectivity between PFC and BG/THL. "
• Active and facilitating, extravert-like behaviour of the low HA and high NS group arise from the functional connection between PFC and BG/THL. The increased connectivity across the regions of dopamine pathway might related to behavioural characteristics of this group.
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PFC
BG/THL
Limbic
“I am my connectome"by Sebastian Seung
S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain |
• We classified the 40 subjects into two contrasting temperament groups: high HA and low NS vs. low HA and high NS.
• The different functional network organisation among the PFC, BG/THL, and limbic system are the neural basis of two contrasting temperament groups
• Watching your neighbours and telling them the neural basis of behaviours
• This study was recently published online at Brain Research. DOI: 10.1016/j.brainres.2014.05.037
Conclusion
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Thank you 8-)