Affiliated Research Groups

The Department of Mathematics is one of two main foci of the CBD. The mathematics group collaborates with the other members of the CBD on questions concerning neural dynamics, fluid dynamics, mechanical oscillations and pattern formation.

The mission of the Applied BioDynamics Lab (ABL) is to develop and implement techniques and concepts from nonlinear dynamics and statistical physics to study and improve the function of various physiological systems. The ABL is designed for conducting human movement, balance, and sensory studies, as well as computational biological studies. The lab includes a Vicon motion analysis system, a Kistler force platform, electromyographic equipment, psychophysical equipment, a network of Sun workstations, and several personal computers.

Our research focuses on investigating the neural responses of the zebra finch Field L region, a primary auditory area analogous to the human auditory cortex. Neurophysiological and behavioral experiments explore the responses to natural and artificial variations in zebra finch songs at the neural and whole-organism level, while our computational work seeks to quantify the response properties of auditory neurons, match neural and behavioral responses and song discrimination, and develop biologically-plausible neural circuits to account for the observed responses.

The Neural Dynamics Group focuses on the physiological bases of rhythmic activity in the nervous system and the interactions of the different frequency bands in vivo and in vitro. We are interested in how the many different types of dynamics come about mechanistically and the roles that they play in sensory processing, cognition, and motor planning. Finally, we work on questions of how changes in physiology can lead to pathologies in rhythms and function in a variety of neurological diseases, including schizophenia, Parkinson's disease and epilepsy.

We study how the nervous system encodes odor information and how the brain processes this information. In other words, how does the brain identify smells? A major interest of the lab is in understanding olfaction as an active sense in which the detection, encoding, and processing of odor information is shaped by the animal's behavior. We use optical imaging to directly visualize neural activity as an animal smells an odor. We image activity in the earliest stages of the olfactory pathway - among olfactory receptor neurons, which detect odorants, and neurons in the olfactory bulb, the first stage of processing in the brain. We also integrate imaging data with other approaches including behavior, electrophysiology, and computational modeling, with the goal of understanding how neural activity represents odor information and how this representation changes as a result of neural processing in the behaving animal.

Formerly called the BU Robotics Lab, the mission of the Laboratory for Intelligent Mechatronic Systems (LIMS), which is directed by John Baillieul, is to understand the design and integration of novel sensing and actuation technologies for a wide variety of control applications. The Lab is particularly interested in active materials exploiting electrostrictive and magnetostrictive effects, as well as the rapidly growing variety of silicon-based microelectromechanical (MEMs) devices. Incorporating these into actuator and sensor arrays, the Lab studies mechatronic systems in which global dynamical effects are achieved through the aggregation of distributed parallel local actions. Control of pattern formation in multiagent systems in which band limited communication channels mediate real-time data-flow between sensor and actuator arrays is central to the research. Applications of interest include fluid structure interactions, robotic system interactions with fluids and elastic solids, microelectromechanisms, rotating shafts, and turbine dynamics.

Research in this laboratory, directed by Michael Hasselmo, focuses on understanding the role of neuromodulators such as acetylcholine and norepinephrine in cortical function, using a combination of neurophysiological and behavioral experiments along with computational modeling.