Local Sleep / Waking Sleep-Like Slow Waves - Relevance to ME/CFS

1 Pinggal et al. 2026 — Core Seed: Waking Slow Waves in ADHD

• Full Citation:: Pinggal E, Jackson J, Kusztor A, Chapman D, Windt J, Drummond SPA, Silk TJ, Bellgrove MA, Andrillon T. Sleep-like slow waves during wakefulness mediate attention and vigilance difficulties in adult attention-deficit/hyperactivity disorder. Journal of Neuroscience. 2026;46(15):e1694252025. (Pinggal et al. 2026)
• DOI:: 10.1523/JNEUROSCI.1694-25.2025
• PMID:: 41839570
• PMCID:: PMC13086247
• Published:: April 15, 2026
• Study Design:: Cross-sectional case-control EEG
• Sample Size:: n=32 ADHD adults, n=31 neurotypical controls
• Key Findings::
  • ADHD adults exhibited higher waking slow wave density over parieto-temporal electrodes vs controls
  • More commission errors, mind wandering, mind blanking, and theta oscillations in ADHD
  • SW density mediated ADHD-related attentional difficulties (omission errors, slower RT, greater RT variability)
  • SW density correlated with elevated sleepiness ratings; on-task reports negatively correlated with SW density
  • First direct evidence that local sleep intrusions during wakefulness mechanistically explain attentional dysfunction in ADHD
• Conclusion:: Sleep-like slow waves during wakefulness are a neural mechanism underlying attentional difficulties in ADHD. Local sleep represents a porous boundary between sleep and wake states.
• Limitations:: Single study (N=63); cross-sectional design; ADHD population only; no ME/CFS data; EEG detects SW but not underlying cellular mechanisms.
• Certainty Assessment::
  • Quality:: High (J Neuroscience; rigorous EEG methodology; peer-reviewed)
  • Sample:: Medium (n=63 total); single-center
  • Replication:: Not yet replicated; preceded by Pinggal 2022 pharmacological study
  • Score:: 0.80 (weight: 0.85; discounted: 0.68)

2 Pinggal et al. 2022 — Pharmacological Modulation of Waking Slow Waves

• Full Citation:: Pinggal E, Dockree PM, O’Connell RG, Bellgrove MA, Andrillon T. Pharmacological manipulations of physiological arousal and sleep-like slow waves modulate sustained attention. Journal of Neuroscience. 2022;42(43):8113–8124. (Pinggal et al. 2022)
• DOI:: 10.1523/JNEUROSCI.0836-22.2022
• PMID:: 36109167
• PMCID:: PMC9637000
• Published:: October 26, 2022
• Study Design:: Double-blind, randomized, placebo-controlled, 4-way crossover trial
• Sample Size:: n=32 healthy male participants
• Key Findings::
  • Methylphenidate (↑dopamine/noradrenaline) improved sustained attention performance
  • Atomoxetine (↑noradrenaline, frontal-predominant) increased impulsive responding
  • Citalopram (↑serotonin) increased sleep-like slow waves and missed trials
  • Slow waves differentially predicted both misses (sluggishness) and faster incorrect responses (impulsivity) in region-specific fashion
  • Slow waves outperformed alpha power as a predictor of attentional lapses
• Conclusion:: Monoamine arousal systems gate local sleep intrusions. Serotonergic tone promotes slow wave generation; catecholaminergic tone suppresses it.
• Limitations:: Male-only sample; healthy young adults; single dose per drug; pharmacological specificity limited.
• Certainty Assessment::
  • Quality:: High (J Neuroscience; RCT crossover design; double-blind)
  • Sample:: Small (n=32); male-only; healthy (not clinical)
  • Replication:: Single study; no independent replication
  • Score:: 0.78 (weight: 0.90; discounted: 0.70)

3 Gong et al. 2026 — Waking SWA Subtype Specificity in Pediatric ADHD

• Full Citation:: Gong S, Lu X, Wang H, Wang Y. Sleep-like slow waves in ADHD: regional specificity in combined type. International Journal of Psychophysiology. 2026;222:113349. (Gong et al. 2026)
• DOI:: 10.1016/j.ijpsycho.2026.113349
• PMID:: 41724214
• Published:: April 2026
• Study Design:: Cross-sectional case-control EEG
• Sample Size:: n=120 children (healthy controls, ADHD-I, ADHD-C)
• Key Findings::
  • Waking SWA elevated in both ADHD subtypes; highest in combined type
  • Global SWA parameters distinguished ADHD from typical development
  • Topographic analysis revealed prefrontal SWA features selectively distinguished ADHD-C from ADHD-I
  • Prefrontal SWA correlated with executive control and orientation deficits in ADHD-C only
  • ADHD subtype significantly modulated the relationship between SWA and behavioral performance
• Conclusion:: Waking slow waves show subtype-specific topography in ADHD. Prefrontal local sleep characterizes the combined subtype. SWA dynamics may enable neurophysiological stratification.
• Limitations:: Pediatric population only; single-center (China); no EEG source localization; ANT task may not capture all attention domains.
• Certainty Assessment::
  • Quality:: Medium (Int J Psychophysiol; well-designed but single-center)
  • Sample:: Good (n=120); pediatric only
  • Replication:: First subtype analysis; replicates Pinggal2026 core finding in children
  • Score:: 0.65 (weight: 0.85; discounted: 0.55)

4 Andrillon & Oudiette 2023 — Local Sleep Review

• Full Citation:: Andrillon T, Oudiette D. What is sleep exactly? Global and local modulations of sleep oscillations all around the clock. Neuroscience & Biobehavioral Reviews. 2023;155:105465. (Andrillon and Oudiette 2023)
• DOI:: 10.1016/j.neubiorev.2023.105465
• PMID:: 37972882
• Published:: December 2023
• Study Design:: Comprehensive narrative review
• Key Findings::
  • Sleep is a local, not purely global, phenomenon — local sleep occurs during both sleep and wakefulness
  • Evidence from animals and humans, healthy and pathological brains
  • Local sleep provides unified framework for: dreaming in NREM/REM, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness
  • Behavioral, phenomenological, and physiological dimensions of sleep can dissociate
  • Physiological origins and functions of local sleep remain unclear
• Conclusion:: The notion of local sleep provides a unified account for phenomena spanning sleep disorders and waking cognitive dysfunction. Exploring local sleep could provide a novel perspective on how and why we sleep.
• Limitations:: Narrative review (not systematic); many studies cited are animal models or small human samples; incomplete mechanistic understanding.
• Certainty Assessment::
  • Quality:: High (Neurosci Biobehav Rev; comprehensive; senior authors)
  • Sample:: N/A (review)
  • Replication:: Well-replicated phenomenon across species and labs
  • Score:: 0.82 (weight: 0.95; discounted: 0.78)

5 Deboer 2026 — Two Types of Local Sleep

• Full Citation:: Deboer T. Global and regional vigilance: are there two types of local sleep? Brain and Behavior. 2026;16(4):e71362. (Deboer 2026)
• DOI:: 10.1002/brb3.71362
• PMID:: 41913650
• PMCID:: PMC13112011
• Published:: April 2026
• Study Design:: Perspective article
• Key Findings::
  • Distinguishes Type 1 local sleep (distinct vigilance states simultaneously, subcortical origin) from Type 2 local sleep (use-dependent local neuronal changes, cortical origin)
  • Type 1: uni-hemispheric sleep, NREM parasomnias in humans
  • Type 2: local slow waves induced by prior workload, waking SW intrusions
  • Mechanistic differences: subcortical vs cortical origin; different regulatory drivers
• Conclusion:: Waking slow wave intrusions are Type 2 cortical local sleep driven by use-dependent fatigue. Recognizing this distinction clarifies mechanistic questions.
• Limitations:: Perspective (no new data); conceptual distinction may oversimplify mixed cases.
• Certainty Assessment::
  • Quality:: Medium (Brain and Behavior; perspective article)
  • Sample:: N/A (perspective)
  • Replication:: Conceptual — builds on established literature
  • Score:: 0.60 (weight: 0.80; discounted: 0.48)

6 Van Dongen 2025 — Local vs Global Sleep Theory

• Full Citation:: Van Dongen HPA. Local versus global sleep organization and the quest to determine sleep function. Neurobiology of Sleep and Circadian Rhythms. 2025;18(Suppl):100117. (Van Dongen 2025)
• DOI:: 10.1016/j.nbscr.2025.100117
• PMID:: 40703581
• PMCID:: PMC12282847
• Published:: May 2025
• Study Design:: Theoretical paper
• Key Findings::
  • Extends Krueger’s neuronal/glial assembly model
  • Local sleep is physics-based: information processing depletes energy, increases entropy → local quiescence is inevitable, has no function
  • Global sleep is biology-based adaptation to manage local sleep pressure while the organism is relatively safe
  • Global sleep regulation is subject to evolutionary shaping and species-specific optimization
  • “Sleep may just be the unavoidable, but worthwhile, price we pay for cognition”
• Conclusion:: Local sleep is an inevitable physics-based consequence of neural computation. Global sleep evolved to preemptively manage local sleep pressure. This framing has implications for conditions where energy metabolism is impaired.
• Limitations:: Theoretical only; no empirical testing of proposed model; highly speculative physics framing.
• Certainty Assessment::
  • Quality:: Medium (Neurobiol Sleep Circ Rhythms; theoretical; respected author)
  • Sample:: N/A (theory)
  • Replication:: Speculative; consistent with use-dependent local sleep evidence
  • Score:: 0.55 (weight: 0.75; discounted: 0.41)

7 Alfonsa et al. 2023 — Chloride Mechanism for Local Sleep Pressure

• Full Citation:: Alfonsa H, Burman RJ, Brodersen PJN, Newey SE, Mahfooz K, Yamagata T, Panayi MC, Bannerman DM, Vyazovskiy VV, Akerman CJ. Intracellular chloride regulation mediates local sleep pressure in the cortex. Nature Neuroscience. 2023;26(1):64–78. (Alfonsa et al. 2023)
• DOI:: 10.1038/s41593-022-01214-2
• PMID:: 36510112
• Published:: January 2023
• Study Design:: Animal experimental (mouse)
• Key Findings::
  • Intracellular chloride accumulates in cortical neurons during wakefulness
  • Chloride accumulation drives local sleep pressure — the longer a cortical region works, the more chloride accumulates
  • KCC2/NKCC1 chloride transporter manipulation alters slow wave expression
  • Provides molecular mechanism for use-dependent local sleep
• Conclusion:: Intracellular chloride concentration acts as a cellular proxy for time-spent-awake, directly gating local sleep pressure in cortical circuits.
• Limitations:: Mouse model only; chloride measurement in vivo is technically challenging; human translation unknown.
• Certainty Assessment::
  • Quality:: High (Nature Neuroscience; elegant experiments; rigorous controls)
  • Sample:: N/A (animal model)
  • Replication:: Builds on established chloride/sleep work; specific mechanism needs independent replication
  • Score:: 0.78 (weight: 0.85; discounted: 0.66)

8 ElGrawani et al. 2024 — BDNF-TrkB Drives Local Sleep Buildup

• Full Citation:: ElGrawani W, Sun G, Kliem FP, et al. BDNF-TrkB signaling orchestrates the buildup process of local sleep. Cell Reports. 2024;43(7):114500. (ElGrawani et al. 2024)
• DOI:: 10.1016/j.celrep.2024.114500
• PMID:: 39046880
• Published:: July 23, 2024
• Study Design:: Animal experimental (mouse)
• Key Findings::
  • BDNF-TrkB signaling identified as molecular driver of local sleep buildup
  • BDNF application during wakefulness increases subsequent local slow wave activity
  • TrkB blockade prevents use-dependent SWA increase
  • Links synaptic plasticity marker (BDNF) to sleep pressure regulation
• Conclusion:: BDNF-TrkB is a key molecular pathway translating prior neural activity into local sleep pressure. Synaptic potentiation and sleep pressure share this pathway.
• Limitations:: Mouse only; pharmacological manipulations may not capture endogenous dynamics; BDNF has pleiotropic functions.
• Certainty Assessment::
  • Quality:: Medium-High (Cell Reports; mechanistic, well-controlled)
  • Sample:: N/A (animal model)
  • Replication:: Single study; builds on BDNF/sleep literature
  • Score:: 0.70 (weight: 0.80; discounted: 0.56)

9 Leemburg et al. 2025 — LPS Inflammation Triggers Local Sleep

• Full Citation:: Leemburg S, Kala A, Nataraj A, Karkusova P, et al. LPS-induced systemic inflammation disrupts brain activity in a region- and vigilance-state specific manner. Brain, Behavior, and Immunity. 2025;120:12–24. (Leemburg et al. 2025)
• DOI:: 10.1016/j.bbi.2025.05.002
• PMID:: 40349731
• Published:: August 2025
• Study Design:: Animal experimental (unspecified species)
• Key Findings::
  • LPS-induced systemic inflammation disrupts EEG activity in region- and vigilance-state specific ways
  • Certain cortical areas show sleep-like activity (slow waves) during behavioral wakefulness — inflammation-induced local sleep
  • Peripheral inflammation → CNS EEG disruption is regionally heterogeneous
• Conclusion:: Systemic inflammation can directly trigger waking slow wave intrusions in specific cortical regions. Provides mechanistic bridge from peripheral inflammation → neuroinflammation → local sleep → cognitive dysfunction.
• Limitations:: Animal model; LPS is an acute bolus, not chronic low-grade inflammation; human translation uncertain.
• Certainty Assessment::
  • Quality:: Medium (Brain Behav Immun; well-designed but single study)
  • Sample:: N/A (animal model)
  • Replication:: Single study; consistent with sickness behavior/neuroinflammation literature
  • Score:: 0.55 (weight: 0.70; discounted: 0.39)

10 Maness et al. 2019 — ME/CFS Common in Hypersomnolent Patients

• Full Citation:: Maness C, Saini P, Bliwise DL, Olvera V, Rye DB, Trotti LM. Systemic exertion intolerance disease/chronic fatigue syndrome is common in sleep centre patients with hypersomnolence: a retrospective pilot study. Journal of Sleep Research. 2019;28(3):e12689. (Maness et al. 2019)
• DOI:: 10.1111/jsr.12689
• PMID:: 29624767
• PMCID:: PMC6173992
• Published:: June 2019
• Study Design:: Retrospective pilot study
• Sample Size:: n=187 hypersomnolent sleep center patients
• Key Findings::
  • 21% of hypersomnolent patients met SEID/ME/CFS criteria
  • SEID frequency did not differ across sleep diagnoses (idiopathic hypersomnia, NT2, OSA, short sleep, normal study)
  • SEID patients had more profound fatigue and were less responsive to wake-promoting agents (88.6% non-response vs 67.7%)
  • SEID patients did not differ by gender, age, ESS, depressive symptoms, or PSG parameters
• Conclusion:: ME/CFS is a common comorbidity in patients presenting with hypersomnolence; not specific to any hypersomnolence subtype. Excessive daytime sleepiness may mask underlying ME/CFS.
• Limitations:: Retrospective; single-center (Emory); small subgroups; SEID criteria applied via chart review not prospective assessment.
• Certainty Assessment::
  • Quality:: Medium (J Sleep Res; retrospective design; pilot)
  • Sample:: Moderate (n=187); single-center
  • Replication:: Not replicated
  • Score:: 0.65 (weight: 0.85; discounted: 0.55)

11 Neu et al. 2015 — SWS Power Spectra in CFS vs Insomnia

• Full Citation:: Neu D, Mairesse O, Verbanck P, Le Bon O. Slow wave sleep in the chronically fatigued: power spectra distribution patterns in chronic fatigue syndrome and primary insomnia. Clinical Neurophysiology. 2015;126(10):1926–1933. (Neu et al. 2015)
• DOI:: 10.1016/j.clinph.2014.12.016
• PMID:: 25620040
• Published:: October 2015
• Study Design:: Cross-sectional case-control EEG with power spectral analysis
• Sample Size:: CFS, primary insomnia, and healthy controls (drug-free, no comorbidities)
• Key Findings::
  • Both CFS and primary insomnia showed decreased central ultra-slow power (0.3–0.79 Hz) during SWS
  • CFS had increased SWS duration but qualitatively impaired — quantitative compensation without qualitative restoration
  • PI showed additional increase in frontal faster-frequency power during SWS (correlated with affective symptoms)
  • Central ultra-slow power reduction correlated with fatigue severity and poor sleep quality
• Conclusion:: SWS is present in CFS at normal or increased duration but with impaired spectral quality — lower proportion of the slowest (most restorative) oscillations. Suggests altered sleep homeostatic regulation.
• Limitations:: Small sample sizes; single-center (Brussels); no waking EEG to assess local sleep; cross-sectional.
• Certainty Assessment::
  • Quality:: Medium-High (Clin Neurophysiol; rigorous EEG spectral analysis; drug-free patients)
  • Sample:: Small; single-center
  • Replication:: Not directly replicated; consistent with Fatt 2020 and broader CFS sleep literature
  • Score:: 0.72 (weight: 0.85; discounted: 0.61)

12 Fatt et al. 2020 — Reduced Parasympathetic Activity During SWS in CFS

• Full Citation:: Fatt SJ, Beilharz JE, Joubert M, Wilson C, Lloyd AR, Vollmer-Conna U, Cvejic E. Parasympathetic activity is reduced during slow-wave sleep, but not resting wakefulness, in patients with chronic fatigue syndrome. Journal of Clinical Sleep Medicine. 2020;16(1):19–28. (Fatt et al. 2020)
• DOI:: 10.5664/jcsm.8114
• PMID:: 31957647
• PMCID:: PMC7053003
• Published:: January 15, 2020
• Study Design:: Cross-sectional case-control (home-based PSG + HRV)
• Sample Size:: n=24 CFS, n=24 matched healthy controls
• Key Findings::
  • CFS patients had slower sleep onset, more awakenings, larger proportion of SWS
  • Parasympathetic activity (normalized HF power) reduced in CFS specifically during deeper sleep stages
  • Reduced parasympathetic signaling was NOT present during wake before sleep, REM, or with time spent in SWS
  • Reduced nocturnal parasympathetic activity associated with poorer self-reported wellbeing and sleep quality
• Conclusion:: Autonomic hypervigilance during deeper, recuperative sleep stages — patients are in SWS but not in a restorative autonomic state. Causal links need confirmation but provide intervention targets for unrefreshing sleep.
• Limitations:: Small sample (n=48); single-center; correlational design; HRV as indirect autonomic measure.
• Certainty Assessment::
  • Quality:: Medium-High (J Clin Sleep Med; well-controlled; home-based recording improves ecological validity)
  • Sample:: Small (n=48)
  • Replication:: Consistent with earlier CFS autonomic sleep literature; not independently replicated
  • Score:: 0.72 (weight: 0.85; discounted: 0.61)

13 Ruby et al. 2024 — Sleep-to-Wake Transition and Local Sleep

• Full Citation:: Ruby P, Evangelista E, Bastuji H, et al. From physiological awakening to pathological sleep inertia: neurophysiological and behavioural characteristics of the sleep-to-wake transition. Neurophysiologie Clinique. 2024;54(2):102934. (Ruby et al. 2024)
• DOI:: 10.1016/j.neucli.2023.102934
• PMID:: 38394921
• Published:: April 2024
• Study Design:: Narrative review
• Key Findings::
  • Sleep inertia = persistent local sleep in specific brain regions after behavioral awakening
  • Neurophysiological characteristics: regional slow wave persistence, reduced functional connectivity
  • Sleep-deprived individuals show longer and more intense sleep inertia
  • Pathological sleep inertia linked to disorders of arousal
• Conclusion:: The sleep-to-wake transition is not instantaneous or uniform — some brain regions can remain in local sleep after awakening. This may explain unrefreshing sleep: failure of complete local sleep dissipation.
• Limitations:: Narrative review (not systematic); limited human neuroimaging data during transitional states; sparse literature on pathological sleep inertia.
• Certainty Assessment::
  • Quality:: Medium (Neurophysiol Clin; review by established French sleep group)
  • Sample:: N/A (review)
  • Replication:: Emerging literature; local sleep during wakefulness concept is gaining support
  • Score:: 0.65 (weight: 0.80; discounted: 0.52)

14 Ortelli et al. 2022 — Post-COVID Attentional Slowing

• Full Citation:: Ortelli P, Benso F, Ferrazzoli D, et al. Global slowness and increased intra-individual variability are key features of attentional deficits and cognitive fluctuations in post COVID-19 patients. Scientific Reports. 2022;12:13123. (Ortelli et al. 2022)
• DOI:: 10.1038/s41598-022-17463-x
• PMID:: 35907947
• Published:: July 30, 2022
• Study Design:: Cross-sectional case-control neuropsychological assessment
• Sample Size:: n=65 post-COVID, n=52 healthy controls
• Key Findings::
  • Post-COVID patients showed global slowing and increased intra-individual variability in attentional tasks
  • The behavioral signature — RT slowing, variability, attentional fluctuations — is identical to the waking slow wave signature described in Pinggal 2026
  • Attention was the most affected cognitive domain
• Conclusion:: Post-viral cognitive dysfunction exhibits the behavioral fingerprint of local sleep intrusions. Attention lapses and RT variability in post-COVID may reflect the same waking slow wave mechanism as ADHD.
• Limitations:: No EEG recorded — behavioral inference only; cross-sectional; heterogeneous post-COVID severity; small sample.
• Certainty Assessment::
  • Quality:: Medium (Scientific Reports; well-designed but no neurophysiology)
  • Sample:: Moderate (n=117); single-center
  • Replication:: Consistent with broader post-COVID cognition literature
  • Score:: 0.60 (weight: 0.80; discounted: 0.48)

References

Alfonsa, Hannah, Robert J. Burman, Peter J. N. Brodersen, Sarah E. Newey, Kashif Mahfooz, Tomoko Yamagata, Marios C. Panayi, David M. Bannerman, Vladyslav V. Vyazovskiy, and Colin J. Akerman. 2023. “Intracellular Chloride Regulation Mediates Local Sleep Pressure in the Cortex.” Nature Neuroscience 26 (1): 64–78. https://doi.org/10.1038/s41593-022-01214-2.

Andrillon, Thomas, and Delphine Oudiette. 2023. “What Is Sleep Exactly? Global and Local Modulations of Sleep Oscillations All Around the Clock.” Neuroscience & Biobehavioral Reviews 155: 105465. https://doi.org/10.1016/j.neubiorev.2023.105465.

Deboer, Tom. 2026. “Global and Regional Vigilance: Are There Two Types of Local Sleep?” Brain and Behavior 16 (4): e71362. https://doi.org/10.1002/brb3.71362.

ElGrawani, Wael, Guoxin Sun, Florian P. Kliem, et al. 2024. “BDNF-TrkB Signaling Orchestrates the Buildup Process of Local Sleep.” Cell Reports 43 (7): 114500. https://doi.org/10.1016/j.celrep.2024.114500.

Fatt, Scott J., Jessica E. Beilharz, Michelle Joubert, Chloe Wilson, Andrew R. Lloyd, Ute Vollmer-Conna, and Erin Cvejic. 2020. “Parasympathetic Activity Is Reduced During Slow-Wave Sleep, but Not Resting Wakefulness, in Patients with Chronic Fatigue Syndrome.” Journal of Clinical Sleep Medicine 16 (1): 19–28. https://doi.org/10.5664/jcsm.8114.

Gong, Shuai, Xi Lu, Haixia Wang, and Yupeng Wang. 2026. “Sleep-Like Slow Waves in ADHD: Regional Specificity in Combined Type.” International Journal of Psychophysiology 222: 113349. https://doi.org/10.1016/j.ijpsycho.2026.113349.

Leemburg, Simone, Andrea Kala, Amita Nataraj, Petra Karkusova, et al. 2025. “LPS-Induced Systemic Inflammation Disrupts Brain Activity in a Region- and Vigilance-State Specific Manner.” Brain, Behavior, and Immunity 120: 12–24. https://doi.org/10.1016/j.bbi.2025.05.002.

Maness, Carissa, Prabhjyot Saini, Donald L. Bliwise, Victoria Olvera, David B. Rye, and Lynn Marie Trotti. 2019. “Systemic Exertion Intolerance Disease/Chronic Fatigue Syndrome Is Common in Sleep Centre Patients with Hypersomnolence: A Retrospective Pilot Study.” Journal of Sleep Research 28 (3): e12689. https://doi.org/10.1111/jsr.12689.

Neu, Daniel, Olivier Mairesse, Paul Verbanck, and Olivier Le Bon. 2015. “Slow Wave Sleep in the Chronically Fatigued: Power Spectra Distribution Patterns in Chronic Fatigue Syndrome and Primary Insomnia.” Clinical Neurophysiology 126 (10): 1926–33. https://doi.org/10.1016/j.clinph.2014.12.016.

Ortelli, Paola, Francesco Benso, Davide Ferrazzoli, et al. 2022. “Global Slowness and Increased Intra-Individual Variability Are Key Features of Attentional Deficits and Cognitive Fluctuations in Post COVID-19 Patients.” Scientific Reports 12: 13123. https://doi.org/10.1038/s41598-022-17463-x.

Pinggal, Elaine, Paul M. Dockree, Redmond G. O’Connell, Mark A. Bellgrove, and Thomas Andrillon. 2022. “Pharmacological Manipulations of Physiological Arousal and Sleep-Like Slow Waves Modulate Sustained Attention.” Journal of Neuroscience 42 (43): 8113–24. https://doi.org/10.1523/JNEUROSCI.0836-22.2022.

Pinggal, Elaine, James Jackson, Anneke Kusztor, David Chapman, Jennifer Windt, Sean P. A. Drummond, Tim J. Silk, Mark A. Bellgrove, and Thomas Andrillon. 2026. “Sleep-Like Slow Waves During Wakefulness Mediate Attention and Vigilance Difficulties in Adult Attention-Deficit/Hyperactivity Disorder.” Journal of Neuroscience 46 (15): e1694252025. https://doi.org/10.1523/JNEUROSCI.1694-25.2025.

Ruby, Perrine, Elisa Evangelista, Hélène Bastuji, et al. 2024. “From Physiological Awakening to Pathological Sleep Inertia: Neurophysiological and Behavioural Characteristics of the Sleep-to-Wake Transition.” Neurophysiologie Clinique 54 (2): 102934. https://doi.org/10.1016/j.neucli.2023.102934.

Van Dongen, Hans P. A. 2025. “Local Versus Global Sleep Organization and the Quest to Determine Sleep Function.” Neurobiology of Sleep and Circadian Rhythms 18 (Suppl): 100117. https://doi.org/10.1016/j.nbscr.2025.100117.