Precise Long-Range Synchronization of Activity and Silence in Neocortical Neurons during Slow-Wave Sleep

• Published in: The Journal of neuroscience Vol. 26; no. 21; pp. 5665 - 5672
• Main Authors: Volgushev, Maxim, Chauvette, Sylvain, Mukovski, Mikhail, Timofeev, Igor
• Format: Journal Article
• Language: English
• Published: Soc Neuroscience 24.05.2006; Society for Neuroscience
• DOI: 10.1523/JNEUROSCI.0279-06.2006
• ISSN: 0270-6474

Slow-wave sleep is characterized by alternating periods of activity and silence in corticothalamic networks. Both activity and silence are stable network states, but the mechanisms of their alternation remain unknown. We show, using simultaneous multisite intracellular recordings in cats, that slow rhythm involves all neocortical neurons and that both activity and silence started almost synchronously in cells located up to 12 mm apart. Activity appeared predominantly at the area 5/7 border and spread in both anterior and posterior directions. The activity started earlier in fast-spiking cells and intrinsically bursting cells than in regular-spiking neurons. These results provide direct evidence for two mechanisms of active state generation: spread of activity from a local focus and synchronization of weaker activity, originating at multiple locations. Surprisingly, onsets of silent states were synchronized even more precisely than the onsets of activity, showing no latency bias for location or cell type. This most intriguing finding exposes a major gap in understanding the nature of state alternation. We suggest that it is the synchronous termination of activity and occurrence of silent states of the neuronal network that makes the EEG picture during slow-wave sleep so characteristic. Synchronous onset of silence in distant neurons cannot rely exclusively on properties of individual cells and synapses, such as adaptation of neuronal firing or synaptic depression; instead, it implies the existence of a network mechanism. Revealing this yet unknown large-scale mechanism, which switches network activity to silence, will aid our understanding of the origin of brain rhythms in normal function and pathology.