Recent models of movement generation in motor cortex have sought to explain neural
activity not as a function of movement parameters, known as representational models, but as …

As improved recording technologies have created new opportunities for neurophysiological
investigation, emphasis has shifted from individual neurons to multiple populations that form …

In this article, which consists of two parts (Part I: representation results; Part II: estimation and
forecasting methods), we set up the theoretical foundations for a high‐dimensional …

Objective: Modeling of human motor intention plays an essential role in predictively
controlling a robotic system in human-robot interaction tasks. In most machine learning …

Motor dysfunction of the upper extremity can result from stroke, cortical injury and
neurological diseases and causes significant disruption of activities of daily living. While …

Basic neurophysiological research with monkeys has shown how neurons in the motor
cortex have firing rates tuned to movement direction. This original finding would have been …

As one of the most powerful tools for examining the association between functional
covariates and a response, the functional regression model has been widely adopted in …

Factor models are widely used for dimension reduction in the analysis of multivariate data.
This is achieved through decomposition of ap× p covariance matrix into the sum of two …

We present a new method for estimating multivariate, second-order stationary Gaussian
Random Field (GRF) models based on the Sparse Precision matrix Selection (SPS) …

This thesis investigates the modeling of human motor behavior, which is essential for
applications such as human-robot interaction and healthcare for instance. We present a …