Sleep restriction affects vigilant attention:

Behavioural and neural correlates

Deborah Apthorp & Lourdes Machin

University of New England, NSW

Talk information

  • This talk was written in Quarto (R Markdown/R Studio) & is available online

Stages of sleep

  • Staging sleep involves classifying the EEG signal, often still by hand
  • Modern wearable technology enables much easier sleep tracking
  • Accuracy not as good as polysomnography, but improving
  • Enables inexpensive in-home sleep assessments
  • Big data?
  • Also relatively cheap

Sleep restriction vs. sleep deprivation

Sleep loss can cause daytime sleepiness (image credit: Jude Conning Photography)
  • Much research looks at total sleep deprivation (no sleep overnight)
  • Profound effects on cognition (memory, attention, etc)
  • But sleep restriction (less sleep than usual) is much more common
  • Effects on cognition not as well researched
  • But this type of sleep loss is much more common!


  • These data were originally collected in 2015 as part of an Honours project by Lucienne Shenfield at ANU
  • Now working as a clinical psychologist specialising in sleep
  • Some of this work is now published
  • What we’ll mainly talk about is the work of another Honours student Lourdes Machin (UNE, 2022)
  • Lourdes analysed the during-task EEG data for the Psychomotor Vigilance Task

Lucienne Shenfield Lourdes Machin


  • CNS centres regulating sleep overlap with those regulating attention & arousal
  • Disrupting sleep disrupts attention
  • But what is attention?
  • Catch-all term for multiple processes
  • Here we focus on sustained attention/vigilance

“Attention is psychology’s weapon of mass explanation” - David Burr, personal communication


  • Inclusion criteria: 18 – 65 years; regular sleep 7-8 h/night

  • Exclusion criteria:

    • Regular smokers
    • Shift work
    • High caffeine consumption (> 5 cups/day)
    • Diagnosed ADD or sleep problems
    • Recent head injury or history of seizures
  • Final sample: 25 participants (15 females)

    • Age: 21 – 55 (M – 24.79 years, SD = 6.82)

Experimental design

  • Within-subjects: Normal sleep (NS) and Sleep-restricted (SR)
  • Sleep restriction: Delay bedtime by 3 hrs, set alarm for 5 hrs later
  • Counterbalanced order
  • Sleep monitoring: Sleep diary and FitBits
  • Tasks: Attentional Blink (AB) and Psychomotor Vigilance Task (PVT)
  • EEG: Resting state and ERP (during tasks)

Sleep restriction

Minutes of Sleep: Diary and FitBit

Task: Psychomotor Vigilance Task

  • 10 minutes long
  • Participants press a button as soon as they see red numbers appear
  • Numbers appear at random intervals (2-10s apart)
  • Reaction time (ms) is measured
  • Also lapses (>500ms), false starts (<100ms)
  • ~80 trials per session


  • Compumedics NuAmps 32-channel EEG system
  • Electrodes 10/20 system
  • Electrode maximum impedance: 5 \(k\Omega\)
  • Signal recorded at 1000 Hz
  • NuAmps digital amplifier
  • Curry 7.0.9 software
  • Resting state and during-task recording

EEG preprocessing

flowchart TD
  A[1. Import data, event markers, channel locations into EEGLAB] --> B[2. Down-sample EEG data to 256 Hz]
  B --> C[3. Apply Finite Impulse Response filter: 1-40 Hz ]
  C --> D[4. Remove non-relevant channels - EOG, Mastoids]
  D --> E[5. Manually remove channels with uncommonly high or low power]
  E --> F[6. Re-reference data to common average]
 F --> G[7. Interpolate removed electrodes, using spherical interpolation]
flowchart TD
  A(8. Visual inspection of  channel plots. Removal of large artifacts ) --> B(9. Run independent components analysis )
  B --> C(10. Run ICLabel - Remove muscle and eye IC artifacts )
  C --> D(11. Remove remaining blink-like ICs with probability between 0.8 and 0.9 )
  D --> E(12. Extract epochs of 3s length for ERP and time frequency analysis )
  E --> F[13. Locked to stimulus onset: -1s, +2s ]
  E --> G[14. Locked to stimulus onset: -1.5s, +1.5s ]

Behavioural data

Mean reaction times by sleep condition

Subjective sleepiness

Mean Karolinska Sleepiness Scale scores by sleep condition

ERP data

ERP amplitude differences: ERP Topographic Maps 250-500 ms

ERP data - differences - Pz

Grey bar shows statistically significant differences in amplitude at the start of P3

ERP data - differences - CPz

Grey bar shows statistically significant differences in amplitude at the start of P3

Source localisation - NS - SR

eLORETA Source Localisation of Current Source Density Differences (from ERP) between NS and SR

Source localisation - NS - SR

328 ms

332 ms

336 ms

340 ms
  • Best Match - Brodmann area 5, postcentral gyrus, parietal lobe

  • Somatosensory cortex - motor preparation affected?

Resting state data

  • We also measured resting state EEG (eyes open and closed)
  • Divided into regions of interest (ROIs)
  • L & R frontal, central, occipital
  • Significant increases in alpha & decreases in delta relative frequency after sleep restriction
  • Most prominent in right central ROI (C4, T4, CP4, TP8)

Resting state changes - right central ROI, eyes closed

Relative alpha frequencies

Relative delta frequencies

Individual variation in effects of sleep restriction

Relative alpha change

Relative delta change

Subjective sleepiness change


  • Mild sleep restriction caused changes in resting state frequencies in right central areas
  • Small increase in reaction times in a vigilance task (PVT)
  • Increase in ERPs (P3) at central sites during the PVT
  • Source localisation using eLORETA suggests the post-central gyrus (Brodmann Area 5) as the origin of this difference
  • This area has not previously been associated with sustained attention - motor preparation/execution differences?
  • Individual variations in effects of sleep restriction - behavioural and neural effects correlate