1.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

2. Application of Graph Theoretical Methodology " to" Behavioural Neuroscience 3. 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 individualss emotion, thoughts and behaviours" generally stable throughout his or her life and across situations. Personality 4. 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 signicant negative correlation between Harm Avoidance (HA) and Novelty Seeking (NS) (Miettunen et al. 2008). 4 5. 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. 5 6. S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain | 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. 7. 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 didnt 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 8. S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain | 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, OGorman RL et al. 2006 8 9. Prefrontal Limbic Temperament traits & Regional association Personality & Local brain activity GLM approach connectome approach 10. Materials and Methods 11. S. Kyeong (NIMS) | Functional Modular Organisations | NDy14 @ Castro-Urdiales, Spain | 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 12. 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 xj 2Si ||xj i||2 S = {S1, S2} p=0.0024 p