Cooperative effects of neuronal ensembles.
Electrophysiological properties of neurons as the basic cellular elements of the central nervous system and their synaptic connections are well characterized down to a molecular level. However, the behavior of complex noisy networks formed by these constituents usually cannot simply be derived from the knowledge of its microscopic parameters. As a consequence, cooperative phenomena based on the interaction of neurons were postulated. This is a report on a study of global network spike activity as a function of synaptic interaction. We performed experiments in dissociated cultured hippocampal neurons and, for comparison, simulations of a mathematical model closely related to electrophysiology. Numeric analyses revealed that at a critical level of synaptic connectivity the firing behavior undergoes a phase transition. This cooperative effect depends crucially on the interaction of numerous cells and cannot be attributed to the spike threshold of individual neurons. In the experiment a drastic increase in the firing level was observed upon increase of synaptic efficacy by lowering of the extracellular magnesium concentration, which is compatible with our theoretical predictions. This "on-off" phenomenon demonstrates that even in small neuronal ensembles collective behavior can emerge which is not explained by the characteristics of single neurons.
Rose
G
G
Department of Neurology, Heinrich-Heine-University Düsseldorf, Germany.
Siebler
M
M
D000818:Animals; D002450:Cell Communication / Q000502:physiology*; D002478:Cells, Cultured; D004594:Electrophysiology; D005110:Extracellular Space / Q000502:physiology; D006624:Hippocampus / Q000166:cytology / Q000502:physiology; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000166:cytology / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D051381:Rats; D017208:Rats, Wistar; D012032:Refractory Period, Electrophysiological / Q000502:physiology; D013569:Synapses / Q000502:physiology