Quantitative analysis of neuronal morphologies usually begins with choosing a particular feature representation in order to make individual morphologies amenable to standard statistics tools and machine learning algorithms. Many different feature rep...
Hybrid circuits built by creating mono- or bi-directional interactions among living cells and model neurons and synapses are an effective way to study neuron, synaptic and neural network dynamics. However, hybrid circuit technology has been largely u...
Electro- and magneto-encephalography are functional neuroimaging modalities characterised by their ability to quantify dynamic spatiotemporal activity within the brain. However, the visualisation techniques used to illustrate these effects are curren...
Segmentation of medical images using multiple atlases has recently gained immense attention due to their augmented robustness against variabilities across different subjects. These atlas-based methods typically comprise of three steps: atlas selectio...
Multi-voxel pattern analysis (MVPA) has been successfully applied to neuroimaging data due to its larger sensitivity compared to univariate traditional techniques. Searchlight is the most widely employed approach to assign functional value to differe...
We performed this research to 1) evaluate a novel deep learning method for the diagnosis of Alzheimer's disease (AD) and 2) jointly predict the Mini Mental State Examination (MMSE) scores of South Korean patients with AD. Using resting-state function...
Regional morphological analysis represents a crucial step in most neuroimaging studies. Results from brain segmentation techniques are intrinsically prone to certain degrees of variability, mainly as results of suboptimal segmentation. To reduce this...
Fractional amplitude of low-frequency fluctuation (fALFF) has been widely used for resting-state functional magnetic resonance imaging (rs-fMRI) based schizophrenia (SZ) diagnosis. However, previous studies usually measure the fALFF within low-freque...
Geodesic based tractography on diffusion magnetic resonance data is a method to devise long distance connectivities among the brain regions. In this study, cellular automata technique is applied to the geodesic tractography problem and the algorithm ...
Functional connectivity networks, derived from resting-state fMRI data, have been found as effective biomarkers for identifying mild cognitive impairment (MCI) from healthy elderly. However, the traditional functional connectivity network is essentia...