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Recurrence plots of neuronal spike trains
1Nencki Institute of Experimental Biology, Department of Neurophysiology, Warsaw, Poland.
Biological Cybernetics
|January 1, 1993
Summary
Recurrence plots reveal that neuronal firing patterns in cats exhibit complex, non-random dynamics. These findings suggest spontaneous modulations in neural complexity, aligning with attractor neural network models.
Area of Science:
- Neuroscience
- Dynamical Systems Theory
Background:
- Neuronal spike trains exhibit complex dynamics.
- Understanding neural firing patterns is crucial for brain function research.
Purpose of the Study:
- To analyze the dynamics of neuronal spike trains using recurrence plots.
- To investigate changes in firing patterns within the cerebellum and red nucleus.
Main Methods:
- Application of recurrence plots, a qualitative diagnostic method for dynamical systems.
- Analysis of neuronal spike trains recorded from the cerebellum and red nucleus of anesthetized cats.
Main Results:
- Recurrence plots identified significant changes in the similarity structure of interspike interval sequences.
- Deviations from randomness were observed in the serial ordering of intervals.
- Recurring episodes of quasi-deterministic firing patterns suggest spontaneous modulation of neural complexity.
Conclusions:
- The observed modulations in neuronal firing dynamics are linked to changing properties of the spike-train-generating system.
- These findings are consistent with the information processing principles of attractor neural networks.