The Measurement of Sleep: The Measurement of Sleep: A Practical Workshop for InvestigatorsA Practical Workshop for Investigators

PolysomnographyPolysomnography

Patrick J. Strollo M.D.Patrick J. Strollo M.D.Martica Hall, Ph.D. Martica Hall, Ph.D. Neuroscience – Clinical & Translational Neuroscience – Clinical & Translational Research Center Laboratory TeamResearch Center Laboratory Team

Pittsburgh Mind-Body Center on Sleep WorkshopPittsburgh Mind-Body Center on Sleep WorkshopPittsburgh, PAPittsburgh, PAApril 11, 2008April 11, 2008

AgendaAgenda1.1. Brief review of polysomnography (PSG) Brief review of polysomnography (PSG)

Goal: Learn what is meant by poly (many) somnus (sleep) graphein Goal: Learn what is meant by poly (many) somnus (sleep) graphein (to write)(to write)

2.2. Tour of N-CTRC sleep laboratory Tour of N-CTRC sleep laboratory Goal: learn about the different types of studies that can be conducted Goal: learn about the different types of studies that can be conducted

in the N-CTRCin the N-CTRC3.3. Meet sleep technician and sleep study “participant” to see what’s Meet sleep technician and sleep study “participant” to see what’s

involved in using PSG to measure sleepinvolved in using PSG to measure sleep GGoal: learn what all of the electrodes & monitors measureoal: learn what all of the electrodes & monitors measure

4.4. Watch as signals are collected from participant and review how different Watch as signals are collected from participant and review how different signals change with behavior signals change with behavior Goal: learn what different signals look likeGoal: learn what different signals look like

5.5. Review examples of sleep pathologiesReview examples of sleep pathologies Goal: learn about some of the signals that indicate sleep pathologiesGoal: learn about some of the signals that indicate sleep pathologies

6.6. Review two kinds of advanced signal processingReview two kinds of advanced signal processing Goal: learn what is meant by spectral analysis of the EEG and EKG Goal: learn what is meant by spectral analysis of the EEG and EKG

during sleepduring sleep

Advanced Signal Processing Advanced Signal Processing Spectral analysis of signals collected during sleep studiesSpectral analysis of signals collected during sleep studies

What is spectral analysis? What is spectral analysis? Decompose a complex, multi-determined signal Decompose a complex, multi-determined signal

Move from time to frequency domain (power is variabilityMove from time to frequency domain (power is variability22)) Spectral analysis of the EEGSpectral analysis of the EEG

ExampleExample: EEG profile in patients with insomnia differs by gender : EEG profile in patients with insomnia differs by gender and across the nightand across the night

Spectral analysis of heart rate variabilitySpectral analysis of heart rate variability Example 1Example 1: Methods: Methods Example 2Example 2: Lab stressor affects HRV during sleep: Lab stressor affects HRV during sleep

Delta & REM Counts and vPSG Delta & REM Counts and vPSG Sleep HistogramSleep Histogram

Compute:Compute: Total powerTotal power Relative powerRelative powerFor:For: All NightAll Night Individual Sleep CyclesIndividual Sleep Cycles

Frequency (hz)

LN

(Me

an

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0 10 20 30 40 50

-6-4

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NREM1 (#202433)

BetaBeta16 – 32 Hz.16 – 32 Hz.

QEEG BandwidthsQEEG BandwidthsDeltaDelta

.5 – 4 Hz..5 – 4 Hz.

ThetaTheta4 – 8 Hz.4 – 8 Hz.

AlphaAlpha8 - 12 Hz.8 - 12 Hz.

SigmaSigma12 - 16 Hz.12 - 16 Hz.

Compute:Compute: Total powerTotal power Relative powerRelative powerFor:For: All NightAll Night Individual Sleep CyclesIndividual Sleep Cycles

Delta Power and VPSG Sleep Delta Power and VPSG Sleep HistogramHistogram

Example…Example…

Frequency and time domain analysis of EEG Frequency and time domain analysis of EEG power during NREM sleep in primary insomniapower during NREM sleep in primary insomnia

Supported by MH24652, RR024153, RR00052 (D. Buysse, PI)Supported by MH24652, RR024153, RR00052 (D. Buysse, PI)

Insomnia is a clinical disorder with sleep and waking Insomnia is a clinical disorder with sleep and waking symptomssymptoms

Etiology uncertain, but Etiology uncertain, but hyperarousalhyperarousal often felt to be a often felt to be a critical componentcritical component– Subjective symptomsSubjective symptoms– Hypothalamic-pituitary-adrenal axisHypothalamic-pituitary-adrenal axis– Functional neuroanatomy using FDG PET studiesFunctional neuroanatomy using FDG PET studies– Beta power in quantitative EEG during NREMBeta power in quantitative EEG during NREM

- Krystal SLEEP 2002; Perlis Sleep Med Rev 2001, Krystal SLEEP 2002; Perlis Sleep Med Rev 2001, Perlis J Sleep Res 2001; Merica Eur J Neurosci Perlis J Sleep Res 2001; Merica Eur J Neurosci 1998)1998)

ParticipantsParticipants GeneralGeneral

– PI and GSC recruited in 3:1 ratioPI and GSC recruited in 3:1 ratio– Age 20-50 years, men and womenAge 20-50 years, men and women– Medical history, psychiatric history (SCID), sleep Medical history, psychiatric history (SCID), sleep

disorders history, screening PSG (AHI, PLMAI < 15)disorders history, screening PSG (AHI, PLMAI < 15) PI (n = 48)PI (n = 48)

– DSM-IV Primary InsomniaDSM-IV Primary Insomnia– PSQI PSQI ≥ 7≥ 7– No specific quantitative criteria by diary or PSGNo specific quantitative criteria by diary or PSG

GSC (n = 25)GSC (n = 25)– No sleep disorderNo sleep disorder– PSQI ≤ 5PSQI ≤ 5– Equated for age and sex with PIEquated for age and sex with PI

Power-frequency plots: Whole nightPower-frequency plots: Whole nightWhole Night

Frequency

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Control (n=25)Insomnia (n=48)

Whole Night

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Whole Night Men

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Control (n=10)Insomnia (n=19)

Whole Night Women

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Control (n=15)Insomnia (n=29)

Whole Night Men

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Whole Night Women

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Power-frequency plots by NREM period: WomenPower-frequency plots by NREM period: Women

NREM1

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6Control (n=15)Insomnia (n=29)

NREM1

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F R

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02468

1012141618

NREM2

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NREM3

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NREM4

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6Control (n=12)Insomnia (n=28)

NREM2

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F R

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02468

1012141618

NREM3

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1012141618

NREM4

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F R

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1012141618

Power-frequency plots by NREM period: MenPower-frequency plots by NREM period: Men

NREM1

Frequency

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6Control (n=9)Insomnia (n=18)

NREM1

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NREM2

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6Control (n=9)Insomnia (n=19)

NREM3

Frequency

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6Control (n=10)Insomnia (n=18)

NREM4

Frequency

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6Control (n=9)Insomnia (n=17)

NREM2

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NREM3

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NREM4

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Heart Rate Variability: What is it? Heart Rate Variability: What is it? Heart rate is rhythmic and varies dynamically in response to intrinsic and extrinsic inputs and Heart rate is rhythmic and varies dynamically in response to intrinsic and extrinsic inputs and

demands demands (CNS activity, mechanical changes, reflex-related changes, behavior, psychological stress, (CNS activity, mechanical changes, reflex-related changes, behavior, psychological stress, affect).affect).

Interbeat intervals (IBIs) refer to milliseconds between beats. Evaluate in the Interbeat intervals (IBIs) refer to milliseconds between beats. Evaluate in the time domaintime domain or or frequency domainfrequency domain..

Two main components of HRVTwo main components of HRV Low frequency changes (~3-9 cycles/min.) Low frequency changes (~3-9 cycles/min.)

Multiply-determined: input from PNS and SNSMultiply-determined: input from PNS and SNS High frequency changes (9-24 cycles/min.) High frequency changes (9-24 cycles/min.)

Related to PNS (‘vagal’ ‘RSA’)Related to PNS (‘vagal’ ‘RSA’) Low-to-High frequency ratioLow-to-High frequency ratio

Index of sympatho-vagal activityIndex of sympatho-vagal activity

60-minute IBI sequence 60-minute IBI sequence

IBI variability is partitioned along a frequency spectrum using frequency-IBI variability is partitioned along a frequency spectrum using frequency-modeling techniques (e.g., fast Fourier Transformations (FFTs), autoregressive modeling techniques (e.g., fast Fourier Transformations (FFTs), autoregressive spectral analyses).spectral analyses).Amount of variability (spectral power) is estimated for given frequency Amount of variability (spectral power) is estimated for given frequency components (bandwidths).components (bandwidths).Low Frequency = .05-.149 Hz, High Frequency = .15 - .40 HzLow Frequency = .05-.149 Hz, High Frequency = .15 - .40 Hz

10 (shaded) minute IBI sequence10 (shaded) minute IBI sequence

Power spectral estimatesPower spectral estimatesof variability in 10-minuteof variability in 10-minuteIBI epoch (raw, smoothed) IBI epoch (raw, smoothed)

Slide courtesy of Julian F. ThayerSlide courtesy of Julian F. Thayer

Frequency Domain Estimates of HRV (QEKG)Frequency Domain Estimates of HRV (QEKG)

Sleep SCORE: Study Sleep SCORE: Study ProtocolProtocol(HL(HL076379, Investigators: K. Matthews, M. Hall, 076379, Investigators: K. Matthews, M. Hall, D. Buysse, P. Strollo, T. Kamarck, S. Reis)D. Buysse, P. Strollo, T. Kamarck, S. Reis)

DAY 1 DAY 1

DAILY: Fill out Sleep Diary and Wear Wrist ActigraphDAILY: Fill out Sleep Diary and Wear Wrist Actigraph

PSG Sleep PSG Sleep Study Study

(2 nights)(2 nights)

DAY 10DAY 10

Ambulatory Ambulatory BP BP

(48 hours)(48 hours)

EEG, EMG, EOG, EKG EEG, EMG, EOG, EKG

SCORINGSCORING PSGPSG visual sleep stage scoring in 20 second epochsvisual sleep stage scoring in 20 second epochsEKG EKG HRV processing in 2-minute epochsHRV processing in 2-minute epochs

GNTGNT GMT GMT

Heart rate variability: Processing & linking Heart rate variability: Processing & linking HRV and vPSG dataHRV and vPSG data

HRV records processedHRV records processed: : 101 (Night 2)101 (Night 2)

Mean sleep durationMean sleep duration:: 7 hours (420 minutes)7 hours (420 minutes)

210 (2-minute) epochs210 (2-minute) epochs total number of epochs (101 x 210) total number of epochs (101 x 210) > 21,120> 21,120

HRV OutputHRV Output:: LF power, HF power, LF:HF Ratio, Respiration Rate, etc.LF power, HF power, LF:HF Ratio, Respiration Rate, etc.

WAKEWAKE NREM NREM

WW W W W W W 2 W W W W W 2 3 3 4 4 3 3 3 4 4 3vPSGvPSG

HRVHRV

NREM differs from Wakefulness & REMNREM differs from Wakefulness & REM

HF PowerHF Power LF:HFLF:HF

Number of HF HRV epochs during NREM for Number of HF HRV epochs during NREM for G = 0.8G = 0.8 NREM Whole Night = NREM Whole Night = 55; NREM 1 = ; NREM 1 = 77; NREM 2 = ; NREM 2 = 77, NREM 3 = , NREM 3 = 66, NREM 4 = , NREM 4 = 33

Number of 2-Minute Epochs

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G C

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NREM Whole NightNREM1NREM2NREM3NREM4

How Many HF HRV Epochs During NREM Sleep Are How Many HF HRV Epochs During NREM Sleep Are Enough?Enough?

Number of LF:HF HRV epochs during NREM for Number of LF:HF HRV epochs during NREM for G = 0.8G = 0.8NREM Whole Night = NREM Whole Night = 1313; NREM 1 = ; NREM 1 = 1313; NREM 2 = ; NREM 2 = 1515, NREM 3 = , NREM 3 = 1717, NREM 4 = , NREM 4 = 77

Number of 2-Minute Epochs

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G C

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NREM Whole NightNREM1NREM2NREM3NREM4

How Many LF:HF HRV Epochs During NREM Sleep How Many LF:HF HRV Epochs During NREM Sleep Are Enough?Are Enough?

NREM Period

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F)

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Does HF HRV During NREM Sleep Change Does HF HRV During NREM Sleep Change Across The Night?Across The Night?

TimeTime F (3,100) = 2.43, p < .07 F (3,100) = 2.43, p < .07

Does LF:HF HRV During NREM Sleep Change Does LF:HF HRV During NREM Sleep Change Across The Night?Across The Night?

TimeTime F (3,99) = 3.99, p < .02 F (3,99) = 3.99, p < .02

STUDY 1: Acute Laboratory StressSTUDY 1: Acute Laboratory Stress

Ambient Stress Acute Stress Heart Period Variability Sleep QualityAmbient Stress Acute Stress Heart Period Variability Sleep Quality

SleepSleepExperimentalExperimentalManipulationManipulation

8:00 p.m.8:00 p.m. a.m.a.m.

SUBJECTS:SUBJECTS:59 healthy undergraduate men and women (50% female, mean age = 19.6 years).59 healthy undergraduate men and women (50% female, mean age = 19.6 years).

Hall et al., Psychosomatic Medicine, 2004Hall et al., Psychosomatic Medicine, 2004

Parasympathetic Activity During Parasympathetic Activity During NREM and REM SleepNREM and REM Sleep

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NREM REMNREM REMParasympathetic Activity = high frequency bandwidth Parasympathetic Activity = high frequency bandwidth (0.15-0.4 Hz)(0.15-0.4 Hz)