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Universal Design for Learning (UDL) has been proposed to facilitate the training processes and improve the learning outcome. The article reviews the theories in neuroscience-based learning and evidences of brain imaging studies that relates to the principles and design of UDL. Neuroimaging based assessment strategy is also reviewed as it may provide an objective means of evaluating learning outcomes...
Functional intrinsic brain networks (IBNs) has been widely studied due to its close relationship to different brain functions and diseases. In these studies, linear metrics, e.g., correlation, have been commonly used in identifying brain networks, especially on functional magnetic resonance imaging (fMRI) data. However, nonlinear mechanism is believed to exist in forming brain networks. In the present...
A key ability of the human brain is to monitor erroneous events and adjust behaviors accordingly. Electrophysiological and neuroimaging studies have demonstrated different brain activities related to errors. Meanwhile, the recognition of error-related brain activity as one aspect of performance monitoring has been reported for potential applications in clinical neuroscience and brain-machine interface,...
Functional magnetic resonance imaging (fMRI) studies utilizing measures of hemodynamic signal, such as the blood-oxygenation-level dependent (BOLD) signal, have discovered that resting-state brain activities are organized into multiple large-scale functional networks, coined as resting state networks (RSNs). However, an important limitation of the available fMRI studies is that hemodynamic signals...
Mal de debarquement syndrome (MdDS) is a chronic disorder of imbalance characterized by a feeling of rocking and swaying. The medical treatment for MdDS is still limited. Motivated by our previous pilot study that demonstrates the promising clinical efficacy of repetitive transcranial stimulation (rTMS) in MdDS patients, a novel rTMS paradigm, i.e., 1 Hz stimulation over ipsilateral dorsal lateral...
We investigated the performance of a new sparse neuroimaging method, i.e., Variation-Based Sparse Cortical Current Density (VB-SCCD) using magnetoencephalography (MEG) data to reconstruct extended cortical sources and their spatial distributions on the cortical surface. We conducted Monte Carlo simulation studies to compare the performance of the VB-SCCD method with different number of cortical sources...
Frequency-derived identification of the propagation of information between brain regions has quickly become a popular area in the neurosciences. Of the various techniques used to study the propagation of activation within the central nervous system, the directed transfer function (DTF) has been well used to explore the functional connectivity during a variety of brain states and pathological conditions...
This paper proposes the application of the directed transfer function (DTF) to a set of time-varying coefficients obtained through the use of a multivariate adaptive autoregressive (MVAAR) model. We define this time-varying measure of causality as the adaptive directed transfer function (ADTF) and compare its ability to discern changes in the causal interaction pattern as compared with the conventional...
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