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Spiking dynamics of interacting oscillatory neurons
V B Kazantsev1, V I Nekorkin, S Binczak
1Institute of Applied Physics, Russian Academy of Sciences, 46 Uljanov Str., 603950 Nizhny Novgorod, Russia.
Chaos (Woodbury, N.Y.)
|July 23, 2005
Summary
This study explores how coupled neurons generate complex spiking patterns. We demonstrate that the interaction strength controls neuronal responses, offering insights into information encoding in neural networks.
Area of Science:
- Computational Neuroscience
- Dynamical Systems Theory
Background:
- Neuronal oscillations and spiking are fundamental to brain function.
- Understanding how coupled neurons process information is crucial for neuroscience.
Purpose of the Study:
- Investigate spiking sequences from coupled oscillatory neurons.
- Analyze the impact of interaction strength on neuronal response dynamics.
- Explore mechanisms of neuronal information encoding.
Main Methods:
- Theoretical and experimental investigation of coupled FitzHugh-Nagumo neuron models.
- Analysis of modified excitability (MFHN) units.
- Generation of spiking phase maps to describe response dynamics.
Main Results:
- Identified complex spiking sequences from unidirectionally coupled MFHN units.
- Demonstrated control over response spike trains via interaction parameter.
- Observed complex phase locking and chaotic spike trains in the slave unit.
Conclusions:
- Neuronal response dynamics are highly dependent on interaction strength.
- The interaction parameter effectively controls neuronal output.
- Findings provide insights into neuronal information encoding strategies.