How to Study Sleep PDF

How to study sleep? ex how late do you go to bed/ do you sleep walk etc Subjective estimation (questionnaires, interviews) Retrospective past - ex past months Prospective future/ present - ex keep a daily diary for one week Objective meas...

How to study sleep? ex how late do you go to bed/ do you sleep walk etc Subjective estimation (questionnaires, interviews) Retrospective past - ex past months Prospective future/ present - ex keep a daily diary for one week Objective measures scientists Behavioural observation (e.g. video recording) watch people sleep, monitor Polysomnography PSG - measure electro activity during sleep - diagnose sleep disorder Actigraphy measure physical activity - ex if animal don’t move asleep Brain Imagery Other physiological measures ex apple watch, fitbit - measure movement/ heart rate pattern (c) Elizaveta Solomonova, 2024 3 Subjective estimation of sleep quality and length Retrospective ask longer durations (from past) Questionnaires, i.e. Pittsburgh Sleep Quality Index Interviews Pros: easy to obtain cheap, convenient Cons: often unreliable, don’t correlate perfectly with objective measures, subject to bias (e.g.,I can never fall asleep!) people overestime bad things ex say sleep bad ALL the time - retrospective bias Prospective ask short durations Sleep diaries Pros: Can be modified to target a specific sleep problem, e.g. insomnia, sleep-walking, nightmares, etc.; eliminate some of the retrospective biases Cons: Are labor-intensive, require motivation, only capture limited subjective information need to commit every morning to fill out diary bias - if asked to track dream, tend to remember dream more - that demand changes the way we dream (c) Elizaveta Solomonova, 2024 4  example of questionnaire (c) Elizaveta Solomonova, 2024 5 Prospective sleep diary example (c) Elizaveta Solomonova, 2024 6 Actigraphy classic method - track physical activity (movement) - active vs inactive A watch-like device equipped with an accelerometer and with light sensor light sensor/ meter added to confirm person is asleep (day or night?) ex if person watch tv, is inactive but not asleep Measures gross levels of motor activity record when active and non-active Worn for many days to estimate sleep-wake patterns Often used in conjunction with sleep diaries Advantages: non-invasive, can be used at home, can collect data over multiple days For sleep: estimates sleep latency; sleep length, sleep fragmentation, restless legs Disadvantages: only records activity-rest patterns, thus limited sleep data (c) Elizaveta Solomonova, 2024 7  ‘Regular’ sleep cycle Text Brigham and Women’s Hospital, Harvard Medical School(c) Elizaveta Solomonova, 2024 8 https://sleepepi.partners.org/2012/08/16/project-spotlight-sueno/  movement happens during sleep due to thermoregulation, mental activity (ex bad dream, acting out dream) etc Video recording of sleep 3/4am drop in temp (go undercovers) > temp increase again later David Ichioka, http://www.bunrab.com/photohutch/ichioka_photos/sleepy_set1.html (c) Elizaveta Solomonova, 2024 9 http://www.bunrab.com/photohutch/ichioka_photos/sleepy_set2.html (c) Elizaveta Solomonova, 2024 10  (c) Elizaveta Solomonova, 2024 11 http://www.bunrab.com/photohutch/ichioka_photos/sleepy_set6.html Brain imaging good spatial, bad temporal Imaging (MRI, fMRI, SPECT, PET) is possible but… low temporal when resolution and subjectively uncomfortable: subjects cannot move, invasive, expensive (c) Elizaveta Solomonova, 2024 12 Functional near-infrared spectroscopy Newer technique Non-invasive, portable Similar to fMRI &EEG Measures hemoglobin concentration, absorption of near infrared light (c) Elizaveta Solomonova, 2024 13  Portable EEG and other devices Muse Dreem https://www.wareable.com/wearable-tech/muse-s-review-8255 https://startuptv.io/video/dreem-gadget-app-sleep/ Oura – heart rate variability, body temperature +++ probably lots more devices available And coming (c) Elizaveta Solomonova, 2024 14 Oura ring measure heart rate Portable EEG recordings (c) Elizaveta Solomonova, 2024 15 WHERE things happen bad spatial, good temporal good spatial, bad temporal WHEN things happen (c) Elizaveta Solomonova, 2024 Kameyama et al,162016 Depth electrodes EEG - implant electrodes, measure surface brain (only neocrotex), bad spatial/ WHERE brain only organ that has no nerve ending, do not feel electrode Used in context of pre- operative/diagnostic epilepsy non-responsive to medication Intra-cranial EEG Implanted for many days, thus possible to record sleep patterns (c) Elizaveta Solomonova, 2024 17  Single cell recordings, local cortical field potentials animal research Very precise, but very invasive Recordings from individual cells Recordings from extracellular space (summed activity from nearby electrodes), measures level of synchrony McGinty (c) Elizaveta Solomonova, 2024 & Szymusiak, 2017 PPSM 18  Polysomnography used in humans, non invasive Gold standard in sleep research Used for fundamental research, experimental research and for diagnosing sleep disorders. An objective method of sleep scoring EEG, EOG, EMG, EKG + any other sensors, proper to a particular research/clinical project (respiration, skin conductance, vasoconstriction, etc…) http://accessscience.com/search.aspx?rootID=797036 (c) Elizaveta Solomonova, 2024 19 standardized (used in many countries) so easy to replicate can also be limitation, hard to deviate Polysomnography put electrodes on people’s faces o - occipital p - parietal etc http://www.bem.fi/book/13/13.htm (c) Elizaveta Solomonova, 2024 20  EOG put electrodes around people’s eyes Électrooculogram Measures eye movements (can detect vertical and horizontal EMs) Used to categotize REM sleep, slow rolling eye movements during SWS https://en.wikipedia.org/wiki/Polysomnograph y#/media/File:Sleep_Stage_REM.png Malmivuo andPlonsey, (c) Elizaveta Solomonova,1995 2024 http://www.bem.fi/book/28/28.htm 21  EMG atonia = REM sleep muscle paralysis Electromyogram; measures muscle tonus Typical measures for PSG: chin, legs, sometimes arms. Used to detect muscle atonia characteristic of REM sleep, for body movements furing sleep and for diagnostic of some sleep disorders (teech grinding, restless legs) irresistble urge to move leg at night - can see leg twitch Bruxism Periodic leg movements typical of restless legs syndrome grind teeth at night Lavigne et al, Clin Neurophysiology, 2002 Trenkwalder (c) Elizaveta Solomonova, 2024 et al, Lancet Neurology, 22 2005  EKG (ECG) classic, derivative of PSG Electrocardiogram Heart rate Used to measure heart rate variability and for diagnosis of cardiac anomalies in sleep electrodes around chest and abdomen (c) Elizaveta Solomonova, 2024 23 http://www.ambulancetechnicianstudy.co.uk/10Rules/Title.gif EEG 1st EEG recording on a human brain. The brain frequency is here compared to a constant 10Hz frequency. (Berger, 1929) in Germany showed brain activity not constant Electroencephalogram: recording of the brain’s electrical activity Used for detection of sleep onset, determination of sleep stages and for detection of anomalies (e.g. seizures) detect when someone falls asleep, has sleep order etc (c) Elizaveta Solomonova, 2024 24 frequency - how often electrical discharge (in neuron) amplitude - how synchronized neurons are amplitude - how far wave deviate from base line - HIGHER amplitude = HIGHER synchronized brain activity (c) Elizaveta Solomonova, 2024 25  EEG small limitation - do not capture activity in subcortical areas or parallels areas An EEG signal, the « brain wave » consists of an aggrecated activity of thousands of pyramidal neurons perpendicular to the scull. allow to build model The amplitude signifies the level of synchrony of neuronal activity (c) Elizaveta Solomonova, 2024 26 Neuronal synchrony higher wave, higher amplitude (c) Elizaveta Solomonova, 2024 27 Singer, 1999, Neuron EEG There is never just one frequency present. Many frequencies are combined and can be further seen using the method of spectral analysis There is usually, however a dominant frequency (c) Elizaveta Solomonova, 2024 28 EEG frequency bands in EEG wave form shape can determine sleep stage Wake beta - disynchronized and fast Resting wake, eyes closed alpha (rest eye) - synchronized and slower same freq but diff amplitude Sleep onset, NREM sleep stage 1,2, REM theta (fall asleep) - increase in amplitude Slow Wave Sleep, NREM 3 delta - high amp/sync and very slow - deep sleep/ NREM 3 (c) Elizaveta Solomonova, 2024 29 http://www.bem.fi/book/13/13x/1305x.htm Sleep Stages REM sleep vs NREM (non rem, stage W/N1/N2/N3) sleep wake REM deep sleep model for 20s/30s person (c) Elizaveta Solomonova, 2024 30  graphic representation (sleep architecture) Hypnogram earlier in the night - slow wave sleep slow wave sleep is thought to be evolutionary important (c) Elizaveta Solomonova, 2024 31 REM stage 4 is stage 3! (stage 4 is from old manual) Hypnogram Hypnogram represents in visual terms progression of sleep stages during the period of recording (night, nap, etc.). Also denotes sleep architecture red - REM sleep sleep is dynamic, it compensate (c) Elizaveta Solomonova, 2024 32 ideal nap is 23 mins - cycle about 90 mins - do not want to go into deep sleep (delta sleep) because hard to wake up from Waking EEG Muscular Beta activity artefacts EEG Saccades EOG Muscular activity EMG (c) Elizaveta Solomonova, 2024 33  Waking EEG: eyes closed EEG slowing, alpha indicate sleepiness « rolling » eye movements Lower muscle tonus muscle tonus not flat yet but relaxed (c) Elizaveta Solomonova, 2024 34 Sleep onset gradually falling asleep, gradually into theta It is hard to pinpoint the exact moment of sleep onset Sleep onset is a gradual process Sleepiness is felt well before sleep onset NREM1 Characterized by General slowing of brain activity Eye movements – « rolling » Diminished responsiveness to outside stimuli and of cognitive Cortico-thalamic neuron recording: processes gradual slowing down of the firing Hypnagogic imagery rate between neocortex and thalamus transition from wake to sleep Neuron stops firing for periods of 0.3-0.4 sec. during the transition into sleep Steriade in Chokroverty (c) Elizaveta Solomonova, 2024 35