Research Interests - Rob Butera
Most of my research interests fall into the general area of Computational
Neuroscience - what are the "computational properties" of neurons?
This question does not have one answer, or neuroscience would be a pretty
mundane field of research and we'd know how the brain works by now! This
question can be explored in many contexts, for example learning and memory.
Most of my research interests, however, fall into the area of central pattern
generation. Central pattern generators (CPGs) are a ubiquitous feature
of virtually all nervous systems, from Aplysia Californica to Homo
Sapiens. My particular interests involve theoretical/computational
studies of the role of CPGs in autonomic control (specifically, the neural
control of respiration) and locomotor pattern generation. My approaches
range from models of single neurons to large populations. Individual models
may be represented by a complex combination of ion channels, or as simply
as a single phase variable - it's all a matter of what we are trying to
learn. My own experience has told me that it is often useful to tackle
a given computational modeling problem at two different scales of complexity
and compare the results.
For those not familiar with computational neuroscience, most of my research
involves the application of systems engineering (if you're an engineer)
or dynamical systems theory (if you're a mathematician) to the analysis
of complex biological systems. Mathematically, most of these models are
large systems of nonlinear ordinary or partial differential equations (personally,
I prefer the ordinary kind). These approaches have been applied to the
modelling of electrically excitable cells (neural and cardiac) and the
analysis and reduction of such cells. I take particular "joy" in modeling
complex systems and then attempting to distill those models to the simplest
possible system that still contain the essential dynamics of the phenomena
to be investigated.
At present most of my efforts are in collaboration with Jeff
Smith (Lab of Neural Control) and John Rinzel investigating the cellular
and emergent network properties of neurons in the brainstem of neonatal
rats which we believe are responsible for generating the motor patters
which underly breathing in mammals. I have also recently completed a theoretical
paper investigating the origin of multiple bursting solutoion in bursting
neurons. Other past and present interests include activity-dependent gene
regulation, nonlinear circuit phenomena, models of
cardiac and nerve conduction, and electrophysiological instrumentation.
A summary of specific things I've done (or am doing), in a somewhat
chronological order (earliest first).
Links to publication abstracts are provided when published.
Simulated the adequacy of single-electrode voltage-clamp measurements of
sodium currents in cardiac myocytes.
Modeled the effects of neuromodulators on neuron R15 in Aplysia.
Studied the effects of the neuromodulators on the bursting activity and
the cell's response to transient input. Even did a few experiments. [PubMed
Analyzed the geometry of our bursting cell model and reduced it to a low-order
(nonspiking) system that responded to parameter changes in a manner similar
to the original model. [PubMed
Analyzed in phase-space the the effects of neuromodulators on the responses
of R15 to transient input. Contrasted this approach with a previous I-V
based method. [Journal
Analyzed the phase-response curve (PRC) and entrainment properties of a
model of R15. Related these properties to specific biophysical mechanisms
within the model. [PubMed
Studied the utility of the PRC in predicting activity modes of rings of
coupled neuron models, with application to mechanisms for quadruped gait
Developed a theoretical framework to explain coexisting multiple oscillations
in a bursting neuron model. Abstract.
Modeling studies of pacemaking neurons responsible for respiratory rhythmogenesis
(in progress) CNS 97 Abstract
Theoretical studies of synchronization and frequency control in networks
of bursting cells with excitatory coupling (in progress)
- Application of real-time operating systems (RTOS), specifically RTLinux,
to model-reference control of electrophysiological experiments.