Clinical Cognitive Neuroscience Center

Seoul National University

Node Identification Using Inter-Regional Correlation Analysis for Mapping Detailed Connections in Resting State Networks

Typical analysis of functional brain networks investigates network connectivity based correlations between large brain regions. We proposed a new method where functional nodes are identified in each region based on their maximum connectivity to another brain region in a given network, which makes us to obtain a more detailed description of network connectivity. This method provides a more detailed map of brain connectivity and determine new measures of network connectivity because the new approach identify functionally relevant nodes in a given network. We suggest that analysis using key relative network hub regions based on regional correlation can be used to detect detailed changes in resting state network connectivity.

Breakdown of regional areas from major networks allows for the calculation of connectivity between specific nodes within each network.

Sohn et al., 2017, Front Neurosci


Unravelling the Intrinsic Functional Organization of the Human Striatum: A Parcellation and Connectivity Study Based on Resting-State fMRI

It is still unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. We applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity.

Striatal subdivisions and their functional connectivity maps.

Jung et al., 2014, PLoS One


Exploring the brains of Baduk (Go) experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis

Experts in board games, such as Baduk and Chess, are believed to be better in intuitive judgment, which is an  automatic process whereby patterns stored in memory through long-term training are recognized. Long-term training may influence brain structure and function, and it was revealed in chess experts. However, characteristics of brain structure and function are less known in brain s of Baduk experts (BEs) compared with those in other strategy games. We found differences of brain structure in amygdala and nucleus accumbens (NA), and differences of functional connectivity between amygdala and frontal cortex and between NA and frontal cortex. In addition, we identified different integration of brain networks in various brain regions while playing Baduk. Our study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in BEs.

Regions with gray matter volume differences and brain regions showing correlation with Baduk training years.


Within- and between-group differences in resting-state functional connectivity.


Correlations between each nodal metric and training duration of BEs.

Jung et al., 2013, Front Hum Neurosci


White matter neuroplastic changes in long-term trained players of the game of “Baduk” (GO): A voxel-based diffusion-tensor imaging study

The Baduk is known to require many cognitive processes, such as attention control, working memory, executive control, and problem-solving. We expected long-term training in such processes would bring structural changes in the associated brain regions. We found fractional anisotropy (FA) was increased in white matter (WM) regions related to the cognitive processes we expected. Long-term Baduk training appears to influence structural brain changes associated with many cognitive aspects necessary for the game play.

Two regions regarding to long-term Baduk training: a) left inferior temporal gyrus; b) bilateral premotor area.

Lee et al., 2010, Neuroimage