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Stability and Flexibility of Small Neural Circuits (CPGs) |
OverviewHow can oscillatory neural circuits generate spatio-temporal activity patterns that are robust in the presence of noise yet flexible enough to provide specific, reproducible, adaptive responses to inputs? This problem is central to sensory processing as well as motor coordination. Our approach to this question involves a well-established and productive, interdisciplinary team from Biology, Physics and Nonlinear Dynamics. It combines nonlinear dynamical analysis, computational and electronic modeling, and neurophysiological studies of a tractable, oscillatory motor circuit from the crustacean stomatogastric system. Using these approaches, we search for the origin of robustness and flexibility at 3 levels of organization: the individual neuron, subcircuits of identified neurons and small microcircuits made up of identified neurons and synapses. Each level is studied using neurophysiological, modeling and dynamical analytical techniques. To validate our computations, we use dynamical neuron models, implemented in hardware and operating in real time, as substitutes for biological neurons in real neural circuits, and as components of simulated networks. Dynamics of individual neurons. Here and in the other projects, we probe robustness by the response to stochastic signals, flexibility by responses to deterministic inputs. Cooperative dynamics in subcircuits. Using natural or simulated synapses, we connect real and/or artificial neurons in small microcircuits. We ask two principal questions: How can neurons operating with complex, variable dynamics interact synaptically to generate stable yet flexible rhythms Robustness and flexibility in highly interconnected microcircuits. Using the pyloric and gastric CPG and model circuits, we test the functional role of heterogenous neuronal dynamics, synaptic properties, redundancy and multiple interconnections. |
PeopleA. SelverstonR. Levi R. C. Elson A. Szücs A. Volkovskii M. I. Rabinovich, R. Huerta R. Pinto P. Varona |
Publications
A. Szûcs, R. D. Pinto, M. I. Rabinovich, H. D. I. Abarbanel, A. I. Selverston
(2003). Synaptic modulation of the interspike interval signatures of
bursting pyloric neurons.
Szücs A, Elson RC, Rabinovich MI, Abarbanel HD,
Selverston AI. Nonlinear behavior of sinusoidally forced pyloric pacemaker
neurons.
Pinto RD, Elson RC, Szücs A, Rabinovich MI, Selverston AI, Abarbanel HD.
Extended dynamic clamp: controlling up to four neurons using a single
desktop computer and interface.
Elson RC, Selverston AI, Abarbanel HD, Rabinovich MI. Inhibitory
synchronization of bursting in biological neurons: dependence on synaptic
time constant.
P. Varona, J.J. Torres, R. Huerta, H.D.I. Abarbanel, M.I. Rabinovich
Regularization mechanisms of spiking-bursting neurons
F.B. Rodríguez, P. Varona, R. Huerta, M.I. Rabinovich, H.D.I. Abarbanel
Richer network dynamics of intrinsically non-regular neurons
measured through mutual information
M.I. Rabinovich, P. Varona, H.D.I. Abarbanel Nonlinear Cooperative
Dynamics of Living Neurons
M.I. Rabinovich, P. Varona, J.J. Torres, R. Huerta,
H.D.I. Abarbanel Slow dynamics and
regularization phenomena in ensembles of chaotic neurons
P. Varona, J. J. Torres, H. D. I. Abarbanel, M. I. Rabinovich, and R. Elson
Dynamics of Two Electrically Coupled Chaotic Neurons: Experimental
Observations and Model Analysis
R. Huerta, P. Varona, M. I. Rabinovich, H.D.I. Abarbanel.
Topology selection by chaotic neurons of a pyloric central pattern
generator,
A. I. Selverston, M. I. Rabinovich, H. D. I. Abarbanel,
R. Elson, A. Szücs, R. Pinto, R. Huerta, P. Varona.
Reliable circuits from irregular neurons: a dynamical approach to
understanding central pattern generators
M. Falcke, R. Huerta, M. I. Rabinovich, Henry D. I. Abarbanel, Robert
C. Elson, Allen I. Selverston.
Modeling Observed Chaotic Oscillations in Bursting Neurons: The Role of
Calcium Dynamics and IP3.
Szücs A, Varona P, Volkovskii AR, Abarbanel HD, Rabinovich MI,
Selverston AI. Interacting biological and electronic neurons generate
realistic oscillatory rhythms.
R. Huerta, M. A. Sánchez-Montañés, F. Corbacho, J. A. Sigüenza.
A central pattern generator to control a pyloric-based system,
Selverston A. What invertebrate circuits have taught us about the brain.
R. C. Elson, R. Huerta, Rabinovich M, Abarbanel, A. I. Selverston,
Dynamic Control of Irregular Bursting in an Identified Neuron of an
Oscillatory Circuit
Selverston A. General principles of rhythmic motor pattern generation
derived from invertebrate CPGs.
Selverston A, Elson R, Rabinovich M, Huerta R, Abarbanel H,
Basic principles for generating motor output in the stomatogastric
ganglion,
R. C. Elson, A. I. Selverston, R. Huerta, N. F. Rulkov, M. I. Rabinovich and
H. D. I. Abarbanel, Synchronous Behavior of Two Coupled biological
Neurons,
M. I. Rabinovich, H. D. I. Abarbanel, R. Huerta, R. Elson, y A. Selverston,
Self-regularization of Chaos in Neural Systems: Experimental and
Theoretical Results.
M. I. Rabinovich, A. Selverston, L. L. Rubchinsky and R. Huerta. Dynamics
and kinematics of simple neural systems.
H. D. I. Abarbanel, M.I. Rabinovich, A. Selverston, M.V.Bazhenov, R.Huerta,
L.L. Rubchinsky, and M.M.Sushchik, The synchronization of Neural
Assemblies,
H. D. I. Abarbanel, R. Huerta, M. I. Rabinovich, N. F. Rulkov, P. F. Rowat
and A. Selverston, Synchronized Action of Synaptically Coupled Chaotic
Model Neurons, |
| Comments? Contact | Terry Peters, Phone +1-858-534-7753, tpeters (at) ucsd.edu |