Reciprocal actions between sensory signals and sleep

Ricardo A. Velluti, José L. Peña, Marisa Pedemonte

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


To the best of our knowledge, there is no simple way to induce neural networks to shift from waking mode into sleeping mode. Our best guess is that a whole group of neurons would be involved and that the process would develop in a period of time and a sequence which are mostly unknown. The quasi-total sensory deprivation elicits a new behavioral state called somnolence. Auditory stimulation as well as total auditory deprivation alter sleep architecture. Auditory units exhibiting firing shifts on passing to sleep (augmenting or diminishing) are postulated to be locked to sleep-related networks. Those (~50%) that did not change during sleep are postulated to continue informing the brain as in wakefulness. A rhythmic functional plasticity of involved networks is postulated. A number of auditory and visual cells have demonstrated a firing phase locking to the hippocampal theta rhythm. This phase locking occurs both during wakefulness and sleep phases. The theta rhythm may act as an organizer of sensory information in visual and auditory systems, in all behavioral states adding a temporal dimension to the sensory processing. Sensory information from the environment and body continuously modulates the central nervous system activity, over which sleep phenomenology must develop. It also produces a basal tonus during wakefulness and sleep, determining changes in the networks that contribute to sleep development and maintenance and, eventually, it also leads to sleep interruption.

Original languageEnglish (US)
Pages (from-to)297-308
Number of pages12
Issue number6
StatePublished - Oct 12 2000
Externally publishedYes


  • Auditory
  • Hippocampus
  • Processing
  • Processing
  • Sensory signals
  • Sleep
  • Theta rhythm
  • Visual
  • Wakefulness

ASJC Scopus subject areas

  • Neurology
  • Developmental Neuroscience
  • Cellular and Molecular Neuroscience


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