Principal Investigators: Dr. JA Scott Kelso and Dr. Emmanuelle Tognoli
The science of coordination aims to understand how the very many different elements of living things - from genes to cells, to neural ensembles, to brains, to societies - are functionally coordinated in space and time. Our current research uses non-invasive imaging methods (EEG, MEG, fMRI, DTI etc) and behavioral measures to investigate brain areas that underlie human learning, cognition, and the disorders thereof.
Principal Investigator: Dr. Robert Vertes
Subcortical systems control the hippocampal EEG and its functional significance. We examine brainstem-diencephalic networks that control the theta rhythm and non-theta states of the hippocampal EEG and their role in memory processing functions of the hippocampus.
How does the brain encode the external world to guide behavior? We are using behavioral, neurophysiological and embedded computational ( robotics) approaches to study the brain and behavior with the goal of developing a broad theoretical framework of neural function.
Principal Investigator: Dr. Howard Hock
The focus of our laboratory is on the identification of mechanisms responsible for the detection of motion, and on the interactions among local motion detectors that result in the formation of global motion patterns. Nonlinear dynamics constitutes the unifying theoretical framework for these studies and is the basis for the computational models through which we simulate our experimental results.
Principal Investigator: Dr. Robert W. Stackman
The principal research interest is the neurobiology of learning and memory. The lab uses a systems and behavioral neuroscience approach to understand the basic neural mechanisms that underlie mammalian learning and memory - from the analysis of individual cells and molecules to the study of circuits supporting memory processes.
Principal Investigator: Dr. Will Alexander
Our research investigates the computational and neural mechanisms underlying cognitive control, decision making and learning.
Principal Investigator: Dr. Howard Prentice
Dr. Prentice’s recent investigations have included gene therapy strategies in models of retinal disease. In addition Dr. Prentice has investigated ischemic tissue protection including anti-apoptotic mechanisms and preconditioning pathways. Dr. Prentice’s translational studies have resulted in recent patent awards and these investigations have included analyses of the mechanisms underlying novel stroke therapies.
Research area: development of visual and social cognition, functional brain development
Principal Investigator: Dr. Wen Shen
Our primary research interests focus on the mechanisms of visual information processing within the retina.
Principal Investigator: Dr. Summer Sheremata
Our primary research focuses on the investigation of attention through various neuroimaging modalities.
Principal Investigator: Dr. Jang Yen Wu
Our research interests are focused on the fundamental principles underlying normal brain function as well as brain diseases.
Principal Investigator: Dr. Erik Engeberg
Research interests: Robotics and Prosthetics, Energy Harvesting, Sensor Design, Brain-Machine Interfaces, Bioinspiration and Biomimetics
Principal Investigator: Dr. Sammy Hong
The long-term objective of my research is to provide a better understanding how the human visual system constructs neural representations based on sensory inputs and what neural mechanisms make it possible for us to consciously experience the world based on those representations.
Principal Investigator: Dr. Carmen Varela
The goal of my lab is to figure out how the interactions between the cellular networks of the limbic thalamus underlie complex processes like the retrieval of memory, its use in learning, or the modulation of learning and memory by internal states (emotion, sleep).
Principal Investigator: Dr. Behnaz Ghoraani
The goal of my lab is to generate clinically relevant engineering solutions that can benefit global health care, developing signal analysis and machine learning algorithms to tackle significant bottlenecks in data analytics.