Authors:
Rahul Agarwal
and
Sridevi V. Sarma
Affiliation:
Johns Hopkins University, United States
Keyword(s):
lay Neurons, Thalamus, Reliability, Hodgkin Huxley Type Models.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Nonlinear Signals and Systems
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Identification
;
System Modeling
Abstract:
Relay cells are prevalent throughout sensory systems and receive two types of inputs: driving and modulating.
The driving input contains receptive field properties that must be relayed while the modulating input alters
the reliability of this relay. In this paper, we analyze a biophysical based nonlinear model of a relay cell
and use systems theoretic tools to construct analytic bounds on how well the cell transmits a driving input
as a function of the neuron’s electrophysiological properties, the modulating input, and the driving signal
parameters. Our analysis applies to both 2nd & 3rd order model as long as the neuron does not spike without
a driving input pulse and exhibits a refractory period. Our bounds suggest, for instance, that if the frequency
of the modulating input increases and the DC offset decreases, then reliability increases. Our analysis also
shows how the biophysical properties of the neuron (e.g. ion channel dynamics) define the oscillatory patterns
needed in the
modulating input for appropriately timed relay of sensory information.
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