Functional network organizations of two contrasting temperament groups in dimensions of novelty seeking and harm avoidance

Functional Network Organisations
of two contrasting temperament groups
in dimensions of novelty seeking and harm avoidance
Sunghyon Kyeong
National Institute for Mathematical Science (NIMS),  
Daejeon, Republic of Korea
Published at Brain Research 
DOI: 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).
4

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.
5

Think about your friends
6
• 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.

• 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
7

Key Regions
associated with  
Temperament
Prefrontal 
prefrontal cortex, orbitofrontal cortex,  
anterior cinculate cortex
Basal Ganglia 
Caudate,Putamen,Pallidum,Thalamus
Limbic 
Amygdala,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
8

Prefrontal
Limbic
Temperament traits &
Regional association
Personality &
Local brain
activity
GLM
approach
“connectome” approach

10 20 30 40 50 60 70
0
10
20
10 20 30 40 50 60 70
0
5
10
15
90 100 110 120 130 140
0
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
11

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
xj 2Si
||xj µi||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 70
0
10
20
30
40
50
60
70
Novelty Seeking
HarmAvoidance
Introverts
Extraverts
Centroids
20 30 40 50 60 70
Novelty Seeking
HarmAvoidance
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 NS
Centroids×
high HA & low NS group
low HA & high NS group
TraitScore
0
10
20
30
40
50
60
70
NS HA P SD C STRD
12

Mechanism of BOLD fMRI
Time
Signal
Mo sinθ
T2* (task)
T2* (control)
TEoptimum
Stask
Scontrol ΔS
↑ Neural Activity ↑ Blood Flow ↑ Oxyhemoglobin
↑ T2*
↑ MR Signal
13

Network Construction
...
...
Spatial Preprocessing 
realignment, co-registration,
normalisation, and smoothing
Parcellation  
into 116 brain regions
Adjacent Matrix
AAL atlas
Ak
ij
Individual
functional network
for k-th subject
• Network extraction in individual level
FN`
ij =
1
nl
X
k2G`
Ak
ij
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)
14

Community Detection
15
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.

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
17

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/THL
PFC 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
18
PFC
BG/THL Limbic
PFC
BG/THL Limbic
A. high HA and low NS B. low HA and high NS

20 30 40 50 60
−0.2
−0.1
0
0.1
0.2
Novelty Seeking
20 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 Seeking
20 30 40 50 60
Densityoffunctionalconnectivity 
ofthePFCandLimbicClusters
0.2
0.1
0
C0.1
C0.2
Harm Avoidance
20 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 NS
Low HA and high NS
Fitting Curve
High HA and low NS
Low HA and high NS
Fitting Curve
19

3.5 4 4.5
20
30
40
50
60
BG/THL Volume (cm
3
)
4.2 4.6 5 5.4 5.8
20
30
40
50
60
Limbic Volume (cm
3
)
HarmAvoidance
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 (cm
3
)
4.2 4.6 5 5.4 5.8
20
30
40
50
60
Limbic Volume (cm
3
)
NoveltySeeking
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
HarmAvoidanceNoveltySeeking
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
20
correlation was computed
while controlling age.

4 4.5 5 5.5 6
−0.3
−0.2
−0.1
0
0.1
0.2
0.3
Volume of Limbic (cm3
)
FCDensity(betweenPFCandLimbic)
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$high$NS
Fitting$Curve
21
Coupling (FCD, VBM)

• 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.
23

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
24

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.
25
PFC
BG/
THL
Limbic

“I am my connectome"
by Sebastian Seung

• 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
27

Functional network organizations of two contrasting temperament groups in dimensions of novelty seeking and harm avoidance

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