Developing models for identifying mild traumatic brain injury (mTBI) has often been
challenging due to large variations in data from subjects, resulting in difficulties for the mTBI …

We consider unnormalized models in which the probability density function contains an
unknown normalization constant. This term normalizes the model so that its probability …

Cognitive ability refers to the degree to which an individual acquires, processes, memorizes,
stores, summarizes, and condenses external knowledge. Given the dynamic changes of …

Non-parametric regression has been shown to be useful in extracting relevant features from
Local Field Potential (LFP) signals for decoding motor intentions. Yet, in many instances …

Eye movements require neuronal processing of visual stimuli and transmission of motor
commands to the eye muscles. The brain circuitry and cortical regions responsible for …

Subject-to-subject variability is a common challenge both generalizing models of neural
data across subjects, discriminating subject-specific and inter-subject features in large …

Objective. In this paper, we consider the problem of cross-subject decoding, where neural
activity data collected from the prefrontal cortex of a given subject (destination) is used to …

Understanding how the brain functions have been one of the major goals of neuroscience.
To approach this challenging topic, artificial intelligence (AI) and various computational …

The non-stationary nature of neural activity prevents Brain-Computer Interfaces (BCIs) from
leveraging data sets collected at different recording sites, such as cortical depths. As a …