Abstract
The possible existence of nonlinear determinism in complex interspike interval (ISI) patterns of rat suprachiasmatic nucleus (SCN) neurons is investigated in hypothalamic slice preparations. ISI sequences are recorded from 173 neurons using a cell-attached patch recording technique, and their correlation dimensions (D2) are estimated. These values are then compared with those of the randomly shuffled surrogate data. Among 173 neurons, 16 neurons are found to exhibit deterministic ISI patterns of spikes. We show, using clustering analysis, that SCN neurons is divided into two subgroups of neurons each having distinct values of skewness (SK) and coefficient of variation (CV : a group of irregularly spiking SCN neurons having large values of SK (2.0 < SK < 10.0) and CV (0.4 < CV < 0.8) and the other group of regular SCN neurons with smaller SK (-1.0 < SK < 2.0) and CV (0.1 < CV < 0.4) values. Interestingly, most deterministic SCN neurons (14/16) belong to the group of irregularly spiking neurons.
Original language | English |
---|---|
Pages (from-to) | 813-818 |
Number of pages | 6 |
Journal | Neurocomputing |
Volume | 52-54 |
DOIs | |
Publication status | Published - 2003 Jun |
Bibliographical note
Funding Information:This work was supported by Creative Research Initiatives of the Korean Ministry of Science and Technology.
Keywords
- Heterogeneity
- Nonlinear determinism
- Suprachiasmatic nucleus
ASJC Scopus subject areas
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence