Given a stationary state-space model that relates a sequence of hidden states and corresponding measurements or observations, Bayesian filtering provides a principled statistical framework for …
Electroencephalography (EEG) signals are created by electrical currents from pyramidal neurons in the outer layer of the brain. These signals are easy to obtain and …
Deep neural networks (DNNs), which are based loosely on the ventral stream pathway of the primate visual system, are good models of the visual system …
Biological brains are dynamic. Recent advances in electrophysiology and neuroimaging have helped uncover various mechanisms through which brains construct and utilize rich variations in neural …
The need to arrest ongoing or planned actions is a hallmark of adaptive control that is crucial for goal-directed behaviors and survival. When the brain …
In many real-world applications, e.g., brain imaging and or weather patterns, data are captured over particular periods or intervals, which we call time series. Time …
Information processing in the brain serves to meet body needs—to adapt behavior to best create the behaviors that will address the needs of the system. …
Progress in deep feedforward neural networks has spawned great successes in many practical applications, but these models struggle to reproduce human-level generalization in tasks that …
Visual spatial attention serves to select locations of interest in the visual field and enhances the cortical representation of objects at those locations. Previous studies …
Spinal neuromonitoring is a medical technique that involves monitoring the function of the spinal cord and nerve roots during surgery or other procedures to minimize …
How do humans learn to adaptively function in a fundamentally uncertain social world? Since we cannot directly observe the contents of other people’s minds, the …
In my dissertation, I present solutions, best practices, and lessons learned for tailoring implantable neural devices to a psychiatric population toward enabling neural biomarker identification …
It is argued that convolutional neural networks (CNNs) struggle to represent the relations among items in a visual scene efficiently. We claim this is a …
In the mouse olfactory bulb glomerular layer, computations are largely mediated by a set of interneurons, known as the periglomerular cells (PGCs). I hypothesized that …