Abstract
We study the dynamics of a low-dimensional system of coupled model neurons as a step towards understanding the vastly complex network of neurons in the brain. We analyze the bifurcation structure of a system of two model neurons with unidirectional coupling as a function of two physiologically relevant parameters: the external current input only to the first neuron and the strength of the coupling from the first to the second neuron. Leveraging a timescale separation, we prove necessary conditions for multiple timescale phenomena observed in the coupled system, including canard solutions and mixed mode oscillations. For a larger network of model neurons, we present a sufficient condition for phase locking when external inputs are heterogeneous. Finally, we generalize our results to directed trees of model neurons with heterogeneous inputs.
Original language | English (US) |
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Article number | 033105 |
Journal | Chaos |
Volume | 29 |
Issue number | 3 |
DOIs | |
State | Published - Mar 1 2019 |
All Science Journal Classification (ASJC) codes
- Applied Mathematics
- Statistical and Nonlinear Physics
- General Physics and Astronomy
- Mathematical Physics