Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Mult...
Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascendin...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jan 26, 2018
With ever-increasing advancements in technology, neuroscientists are able to collect data in greater volumes and with finer resolution. The bottleneck in understanding how the brain works is consequently shifting away from the amount and type of data...
Computational and mathematical methods in medicine
Jan 23, 2018
Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on diffe...
A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treat...
IEEE transactions on pattern analysis and machine intelligence
Jan 17, 2018
Discriminative methods commonly produce models with relatively good generalization abilities. However, this advantage is challenged in real-world applications (e.g., medical image analysis problems), in which there often exist outlier data points (sa...
The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature table...
Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI pe...
BACKGROUND: AD is the most frequent neurodegenerative disease, severely impacting our society. Early diagnosis and prognosis are challenging tasks in the management of AD patients.
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rap...
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