Neuroimaging Studies in Normal Population

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



Neurocognitive & Psychological Studies in Normal Population

Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Even though intelligence and cognitive function have been believed to be associated with multiple structures in brain at the network level, their associations with the grey matter (GM) structural network were not well understood. In this study, multivariate approach was applied to identify the pattern of GM and its link to intelligence and cognitive functions. We found that the cerebello-parietal component and the frontal component were related to intelligence and that the cerebellar component was associated with visuomotor ability. Our results support the parietal-frontal integration theory of intelligence and cognitive functions of cerebellum.

The structural components discovered by source-based morphometry. a) precuneus; b) fronto-temporal; c) cerebello-parietal; d) frontal; e) cerebellar; f) temporal component


The association between structural networks and IQ


The association between the cerebellar component and visuomotor ability

Yoon et al., 2017, Scientific Reports


The effect of meditation on brain structure: cortical thickness mapping and diffusion tensor imaging

Neuroscientific evidence suggests that meditation alters the functional and structural plasticity of distributed neural processes underlying attention and emotion. We aimed to examine the brain structural differences between long-term meditators and controls. Meditators showed greater cortical thickness in the anterior regions and thinner thickness in the posterior regions of the brain. Moreover, higher FA values in medial prefrontal cortex were observed in meditators. Our findings suggest that long-term meditators have structural differences in both gray and white matter.

Regional maps showing differences in a) cortical thickness and b) FA between meditation practitioners and control subjects.


Duration of meditation practice were correlated with cortical thickness of left superior frontal cortex.

Kang et al., 2013, Soc Cogn Affect Neurosci


Integration of cross-modal emotional information in the human brain: An fMRI study

The interaction of information derived from the voice and facial expression of a speaker contributes to the interpretation of the emotional state of the speaker and to the formation of inferences about information that may have been merely implied in the verbal communication. We investigated the brain processes responsible for the integration of emotional information originating from different sources. We found the different brain activations in the superior temporal gyrus, inferior frontal gyrus, and parahippocampal gyrus, under bimodal vs. unimodal condition. In addition, we found emotion-specific (e.g., angry- or happiness-specific) activations were found in different brain regions. The results suggest that each emotion uses a separate network to integrate bimodal information and shares a common network for cross-modal integration.

Experimental design consisting three emotions and three conditions (face, voice , and both).


Brain regions showing strong activation in bimodal conditions and pattern of the signal change across modality.

Park et al., 2010, Cortex


Cortical network dynamics during source memory retrieval: Current density imaging with individual MRI

We investigated the neural correlates of source memory retrieval using low-resolution electromagnetic tomography (LORETA) with EEG and MRI. Participants performed the source memory task for the voice of the speaker in spoken words. The results of source analysis suggest that the activation of the right inferior parietal region may reflect retrieval of source information. The source elicited by the difference ERPs between the source correct and incorrect conditions exhibited dynamic change of current density activation during source memory retrieval.

ERPs elicited by source correct, incorrect, and rejection conditions.


Statistical parametric map for ERP generator elicited by source correct, incorrect, and rejection conditions at latency of 604 ms and 1,100 ms.


Statistical parametric map for cortical generator elicited by difference ERP between source correct and incorrect conditions at different latencies.

Kim et al., 2009, Hum Brain Mapp


Objects and their icons in the brain: The neural correlates of visual concept formation

We are constantly exposed to symbols such as traffic signs, emoticons, or other abstract representations of objects as well as the written words. However, aside from the word reading, little is known about the way our brain responds when we read non-lexical iconic symbols. We found that the watching of icons recruited manifold brain areas including frontal and parietal cortices in addition to the temporo-occipital junction. Remarkably, the brain response for icons was contrasted with the response for corresponding concrete objects with the pattern of ‘hyper-cortical and hypo-subcortical’ brain activation.

The experimental design. Different photographs of the same type were used as stimuli.


The brain regions showing a main effect of objects versus their icons.

Shin et al., 2008, Neurosci Letters