Sleep spindle

Sleep spindles are bursts of neural oscillatory activity that are generated by interplay of the thalamic reticular nucleus (TRN) and other thalamic nuclei during stage 2 NREM sleep in a frequency range of ~11 to 16 Hz (usually 12–14 Hz) with a duration of 0.5 seconds or greater (usually 0.5–1.5 seconds).[1][2][3] After generation as an interaction of the TRN neurons and thalamocortical cells,[4] spindles are sustained and relayed to the cortex by thalamo-thalamic and thalamo-cortical feedback loops regulated by both GABAergic and NMDA-receptor mediated glutamatergic neurotransmission.[5] Sleep spindles have been reported (at face value) for all tested mammalian species. Considering animals in which sleep-spindles were studied extensively (and thus excluding results mislead by pseudo-spindles[6]), they appear to have a conserved (across species) main frequency of roughly 9–16 Hz. Only in humans, rats and dogs is a difference in the intrinsic frequency of frontal and posterior spindles confirmed, however (spindles recorded over the posterior part of the scalp are of higher frequency, on average above 13 Hz).[7]

Research supports that spindles (sometimes referred to as "sigma bands" or "sigma waves") play an essential role in both sensory processing and long term memory consolidation. Until recently, it was believed that each sleep spindle oscillation peaked at the same time throughout the neocortex. It was determined that oscillations sweep across the neocortex in circular patterns around the neocortex, peaking in one area, and then a few milliseconds later in an adjacent area. It has been suggested that this spindle organization allows for neurons to communicate across cortices. The time scale at which the waves travel at is the same speed it takes for neurons to communicate with each other.[8] Doubts, however, remain whether a link exists between sleep spindles and memory with a recent meta-review of 53 studies concluding that "there is no relationship between sleep spindles and memory, and thus it is unlikely that sleep spindles are indeed generally implicated in learning and plasticity".[9]

Although the function of sleep spindles is unclear, it is believed that they actively participate in the consolidation of overnight declarative memory through the reconsolidation process. The density of spindles has been shown to increase after extensive learning of declarative memory tasks and the degree of increase in stage 2 spindle activity correlates with memory performance.

Among other functions, spindles facilitate somatosensory development, thalamocortical sensory gating, synaptic plasticity, and offline memory consolidation.[10] Sleep spindles closely modulate interactions between the brain and its external environment; they essentially moderate responsiveness to sensory stimuli during sleep.[11] Recent research has revealed that spindles distort the transmission of auditory information to the cortex; spindles isolate the brain from external disturbances during sleep.[12] Another study found that re-exposure to olfactory cues during sleep initiate reactivation, an essential part of long term memory consolidation that improves later recall performance.[13] Spindles generated in the thalamus have been shown to aid sleeping in the presence of disruptive external sounds. A correlation has been found between the amount of brainwave activity in the thalamus and a sleeper's ability to maintain tranquility.[14] Spindles play an essential role in both sensory processing and long term memory consolidation because they are generated in the TRN.

During sleep, these spindles are seen in the brain as a burst of activity immediately following muscle twitching. Researchers think the brain, particularly in the young, is learning about what nerves control what specific muscles when asleep.[15][16]

Sleep spindle activity has furthermore been found to be associated with the integration of new information into existing knowledge[17] as well as directed remembering and forgetting (fast sleep spindles).[18]

During NREM sleep, the brain waves produced by people with schizophrenia lack the normal pattern of slow and fast spindles.[19] Loss of sleep spindles are also a feature of familial fatal insomnia, a prion disease.[20] Changes in spindle density are observed in disorders. There are some studies that show a change in sleep spindles in autistic children.[21] Also some studies suggest a lack of sleep spindles in epilepsy.[22][23]

Research is currently underway to develop a web-based automatic sleep spindle detection system by using machine learning techniques. The results of the present study show that the automatic sleep spindle detection system has great potential in practical application.[24]

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  8. ^ Muller, Lyle; Piantoni, Giovanni; Koller, Dominik; Cash, Sydney S; Halgren, Eric; Sejnowski, Terrence J (2016-11-15). Skinner, Frances K (ed.). "Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night". eLife. 5: e17267. doi:10.7554/eLife.17267. ISSN 2050-084X. PMC 5114016. PMID 27855061.
  9. ^ Ujma, Péter Przemyslaw (2024). "Meta-analytic evidence suggests no correlation between sleep spindles and memory". Neuropsychologia. 198: 108886. doi:10.1016/j.neuropsychologia.2024.108886.
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  21. ^ Merikanto, Ilona; Kuula, Liisa; Makkonen, Tommi; Salmela, Liisa; Räikkönen, Katri; Pesonen, Anu-Katriina (2019-03-15). "Autistic Traits Are Associated With Decreased Activity of Fast Sleep Spindles During Adolescence". Journal of Clinical Sleep Medicine. 15 (3): 401–407. doi:10.5664/jcsm.7662. ISSN 1550-9389. PMC 6411178. PMID 30853050.
  22. ^ Iranmanesh S, Rodriguez-Villegas E (August 2017). "An Ultralow-Power Sleep Spindle Detection System on Chip". IEEE Transactions on Biomedical Circuits and Systems. 11 (4): 858–866. doi:10.1109/TBCAS.2017.2690908. hdl:10044/1/46059. PMID 28541914. S2CID 206608057.
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  24. ^ L. Wei; S. Ventura; S. Mathieson; G. B. Boylan; M. Lowery; C. Mooney (Jan 2022). "Spindle-AI: Sleep Spindle Number and Duration Estimation in Infant EEG". IEEE Transactions on Biomedical Engineering. 69 (1): 465–474. doi:10.1109/TBME.2021.3097815. PMID 34280088. S2CID 236141540.

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