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. 2024 Dec 12;71:101487. doi: 10.1016/j.dcn.2024.101487

Co-developing sleep-wake and sensory foundations for cognition in the human fetus and newborn

Kimberley Whitehead 1
PMCID: PMC11699341  PMID: 39675060

Abstract

In older children and adults, cognition builds upon waking sensory experience which is consolidated during sleep. In the fetus and newborn, sensory input is instead largely experienced during sleep. The nature of these sensory inputs differs within sleep, between active and quiet sleep, as well as versus wakefulness. Here, sleep-wake organisation in the fetus and newborn is reviewed, and then its interaction with sensory inputs discussed with a focus on somatosensory and auditory modalities. Next, these ideas are applied to how neurological insults affect early development, using fetal growth restriction as a test case. Finally, the argument is made that taking account of sleep-wake state during perinatal functional neuroimaging can better index sensorimotor, language, and cognitive brain activities, potentially improving its diagnostic and prognostic value. To sum up, sensory and sleep-wake functions go hand in hand during early human development. Perturbation of these twinned functions by neurological insults may mediate later neurodevelopmental deficits. Perinatal neuroimaging has the potential to track these trajectories, feasibly identifying opportunities to therapeutically intervene.

Keywords: Neonate, Infant, Behaviour, Motor, Intrauterine growth restriction

Graphical Abstract

graphic file with name ga1.jpg

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Highlights

  • •

    Sensory inputs are organised by sleep-wake state in the fetus and newborn.

  • •

    Sleep-wake and sensory processing foundations for cognition are intertwined.

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    Perinatal brain insults perturb both foundations.

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    Perinatal functional neuroimaging can beneficially account for sleep-wake state.

1. Introduction

In older children and adults, cognition builds upon waking sensory experience which is consolidated during sleep (Buzsáki, 1989). In the fetus and newborn, sensory input is instead largely experienced during sleep. This sleep can be broadly categorised as active sleep (precursor to rapid eye movement (REM) sleep) or quiet sleep (precursor to non-REM sleep). This review focuses on interactions between sleep-wake and sensory functions during the unique perinatal period, before a switch point to adult-like features at 2–3 months of age which include circadian rhythmicity, REM sleep muscle atonia, non-REM onset sleep, and mature cortical signatures of sleep-wake state (e.g. spindles during non-REM sleep, alpha and mu rhythms during wakefulness) (Grigg-Damberger, 2016, Jenni et al., 2006, Kohyama, 1996, Saby and Marshall, 2012, Sokoloff et al., 2021). It is argued here that perinatal sleep-wake organisation cannot be fully appreciated isolated from its sensory correlates. Next, the case is made that perinatal brain insults perturb twinned sleep-wake and sensory functions, and that accounting for this deepens understanding of how insults impact early development.

2. Sleep-wake state organisation in the human fetus and newborn

Rudimentary behavioural cycling emerges in the fetus during the final trimester of gestation from an ‘indeterminate’ state to well-defined active and quiet periods. During active states, movement patterns include limb and rapid eye movements, respiratory ‘breathing’ movements, and hiccups (Gazzolo et al., 1995, Groome et al., 1997a, Shuffrey et al., 2019, Ten Hof et al., 2002). During the quiet state, the fetus is almost completely quiescent. In parallel, heart rate variability is relatively high during active states and lower in the quiet state (Nijhuis et al., 1982, de Vries and Fong, 2006, Zavala et al., 2020).

Postnatally, active states can be subdivided into wakefulness and active sleep, with quiet sleep occupying the remainder. Example proportions in an early-term neonate are approximately 10 % wakefulness, 60 % active sleep, and 30 % quiet sleep (Graphical Abstract) (Georgoulas et al., 2021, Groome et al., 1997b, Roffwarg et al., 1966). Both active states are associated with relatively continuous low-amplitude cortical activity, while quiet sleep is characterised by relatively alternating high-amplitude cortical activity (Fig. 1). State-organised motor behaviour continues, as during the fetal period, and now also incorporates vocalisations, and scanning open eye movements when awake (Fig. 1). As in the fetus, heart rate variability is higher during active states than quiet sleep (Isler et al., 2016), meaning that this index of state is continuous from fetal to neonatal data, facilitating their integration.

Fig. 1.

Fig. 1

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Motor behaviour (upper panel) and cortical activity (lower panel) during sleep-wake states. Electroencephalography (EEG) examples are from an infant aged 42 corrected gestational weeks (Whitehead et al., 2018a).

3. Self-generated sensory inputs across sleep-wake states

Spontaneous motor behaviour self-generates sensory inputs. Every movement, vocalisation, and open eye movement will generate incoming somatosensory, auditory, and visual input respectively. Because these motor behaviours are organised across the sleep-wake cycle (Fig. 1), so too is self-generated sensory input (Graphical Abstract).

3.1. Somatosensory inputs

Spontaneous movements evoke incoming somatosensory input, via proprioceptive feedback as the body moves through space and/or via tactile inputs from the body brushing its surroundings. These movements vary between sleep-wake states. During quiet sleep, long periods of behavioural quiescence are interrupted by whole-body reflexive ‘startles’ (de Groot et al., 2022, Hadders-Algra et al., 1993) and, more subtly, discrete respiratory movement events comprising large-magnitude sighs (Edwards et al., 2018, Fleming et al., 1984). During active sleep, movements are profuse, with isolated limb movements a hallmark of the motor repertoire, which cluster alongside rapid eye movements (Curzi-Dascalova et al., 1993, Hadders-Algra et al., 1993, Kohyama, 1996, Sokoloff et al., 2020, Sokoloff et al., 2021, Whitehead et al., 2019c, Whitehead et al., 2020); Fig. S2 in (Koskela et al., 2021). Respiratory movement events are also prominent, with large-magnitude sighs interspersed with periods of shallow breathing (hypopnea), and variations in breathing frequency (Fig. 2) (Shiraki et al., 2024). Wakefulness is characterised by gross and largely continuous, rather than isolated, body movements, although these appreciably wax and wane (Hadders-Algra et al., 1992, Hadders-Algra et al., 1993), and some behavioural scoring systems use this variance to distinguish ‘active’ from ‘quiet’ wakefulness (e.g. (Stevens et al., 2014)). Respiratory movement patterning during wakefulness is comparable to active sleep, although extremely large-magnitude events – hiccups – are more prevalent (Brouillette et al., 1980, Whitehead et al., 2019b).

Fig. 2.

Fig. 2

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Vocalisations during wakefulness and active sleep. Examples of vocalisations (‘V’) recorded with a collar-affixed microphone (Unimed Electrode Supplies, Mic), and their time-frequency representation (EEGLAB v. 2024.2), time-locked to EEG at temporal channels T8 and T7 which overlie auditory cortex, ECG, and respiratory movement (Resp). Left: Infant aged 35 corrected gestational weeks exhibits a sequence of cries during wakefulness. Note the sustained electromyographic artefact on the EEG channels, consistent with wakefulness. Right: Infant aged 35 corrected gestational weeks exhibits an isolated ‘squeak’ during active sleep (associated to Supplementary Audio File). Note the lack of sustained electromyographic artefact, consistent with sleep. All data were sampled at 2000 Hz. EEG data were high-pass filtered at 0.3 Hz and baseline corrected.

Taken together, movement varies between states but also fluctuates within-states, effectively representing an additional layer of intra-state organisation. This behaviour is tracked by the neonate’s brain activity, because spontaneous movements evoke cortical responses, even during sleep. These ∼1 second duration responses are somatotopic, i.e. correspond to the way that the body is represented within sensorimotor cortex. For example, symmetrical movements, like startles and hiccups, evoke responses with a midline central distribution (Losito et al., 2017, Whitehead et al., 2019b), while unilateral hand movements evoke responses with a contralateral central distribution (Allievi et al., 2016, Milh et al., 2007, Vanhatalo et al., 2009, Whitehead et al., 2018b). In sum, sleep-wake state is the organisational backbone of perinatal motor activity, which evokes somatotopic brain responses at a time of rapid body map functional development (Allievi et al., 2016, Dall’Orso et al., 2018, Whitehead et al., 2019a). These body maps are proposed to underlie infants’ distinction of ‘self’ versus ‘other’: a crucial prerequisite for social cognition (Marshall and Meltzoff, 2015).

3.2. Auditory inputs

An infant’s vocalisations provide incoming auditory input to their developing brain, and are likewise organised across sleep-wake states. In quiet sleep, vocalisations are absent. In active sleep, vocalisations are present as intermittent grunts, cries and squeaks (Fig. 2 and Supplementary Audio File) (de Groot et al., 2022). During wakefulness, vocalisations fall into three categories. First, they are present as comparable intermittent vocalisations to those observed during active sleep, but here termed ‘protophones’, meaning precursors to speech (Oller et al., 2019, Zhang and Ghazanfar, 2016). Second, other sections of wakefulness are dominated by sustained crying, although with a clear embedded temporal structure (Fig. 2) (Cabana et al., 2021, Sahni et al., 1995). Third, so-called ‘vegetative’ vocalisations include the self-generated sound caused by abrupt closure of the glottis during hiccups, and burps and sneezes (Oller et al., 2019). Like somatosensory inputs, auditory inputs evoke brain responses in the neonate (Chipaux et al., 2013, Dall’Orso et al., 2021, Fifer et al., 2010, Kaminska et al., 2018), although these have not been specifically studied after self-generated stimuli except hiccups (Whitehead et al., 2019b).

As with self-generated somatosensory input then, self-generated auditory input varies both between and within-states. Parallels include active sleep being characterised by both movements and vocalisations which are discrete and isolated (Fig. 2), while wakefulness is marked by ‘noisier’ and more continuous sensory inputs. Nevertheless, even apparently ‘noisy’ signals like crying, contain temporal structure (Fig. 2). The auditory system is built on the organisational system of tonotopy, with sounds of different frequency spatially represented across auditory cortex, just as the somatosensory system is built on that of somatotopy. Therefore, the varied and multi-frequency vocalisations across sleep and wakefulness may be well-suited to refine cortical encoding of this range, which subserves recognition of and attendance to human speech, also important for social cognition (Oller et al., 2019).

3.3. Visual inputs

During either quiet or active sleep, the closed eyelids mean that only gross external visual inputs – like flashes – evoke cortical responses (Colonnese et al., 2010). Wakefulness – during which the eyes are open and exhibit scanning saccadic movements – is the only state to provide patterned visual input corresponding to the external world, albeit low resolution, to the developing cortex (Fantz, 1963, Miranda, 1970, Wolff, 1965).

3.4. Summary of sensory inputs across sleep-wake states

Drawing this section together, each sleep-wake state has a signature of motor behaviour and associated somatosensory, auditory, and visual self-generated input (Fig. 1 and Graphical Abstract), at a time when the developing brain is beginning to exhibit multimodal sensory learning (Dall’Orso et al., 2021, Fifer et al., 2010). Further to motor behaviours self-generating sensory inputs, they also provoke supportive sensory caregiving activities, creating early conditioning associations between self-actions and positive results. Gross movements, crying, and eye opening during wakefulness likely contribute to the short latency to being picked up upon awakening (Fig. S4 in (Georgoulas et al., 2021)). The more subtle motor activity and vocalisations of active sleep may also trigger sensory interventions, given that longer active sleep bouts are associated with higher frequency of caregiver contacts (Bowe and Anders, 1979). In fact, it is likely that active sleep is regularly mistaken for wakefulness, given that even neonatal healthcare staff can rarely distinguish them behaviourally, partly owing to lack of awareness that sustained eye opening is an important signature of wakefulness (de Groot et al., 2023)

4. Sleep organisation in the fetus and newborn affected by a neurological insult

As described above, the human fetus exhibits a repertoire of motor behaviour including limb movements and hiccups. The importance of this motor behaviour is emphasised by it being an index of perinatal neurological health. Fetal limb and respiratory ‘breathing’ movements positively correlate with oxygen and glucose levels (Bocking et al., 1982, Vasung et al., 2022), and fewer fetal movements and hiccups predicts stillbirth, or adverse neurodevelopment in survivors (Thompson et al., 2021, Zamstein et al., 2019). However, these data are rarely interpreted using the lens of sleep.

A form of fetal compromise often associated with reduced fetal movements is intrauterine growth restriction secondary to placental insufficiency (Gordijn et al., 2016, Higgins et al., 2018, Lucchini et al., 2021, Mainous and Hueston, 1994). Unlike constitutionally small fetuses – termed ‘small for gestational age’ – growth-restricted fetuses are small because of chronic hypoxemia and hypoglycaemia in utero. It is often noted that these fetuses likely stop moving to minimise expenditure of their limited resources. Combining these observations with fetal sleep data implies that at least part of the attenuation in motor activity could be associated with reduced active sleep (Fig. 3) (also observed in a sheep model of the condition (Keen et al., 2011)). Like motor activity, active sleep is metabolically demanding, with oxygen consumption higher than in quiet sleep (Azaz et al., 1992, Scopes and Ahmed, 1966, Stabell et al., 1977, Stothers and Warner, 1978). In line with this, active sleep accentuates the fetal heart rate abnormalities characteristic of intrauterine growth restriction (Sriram et al., 2013).

Fig. 3.

Fig. 3

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Intrauterine growth restriction is associated with reduced active sleep and reduced movements antenatally. Upper panel: data sourced from (Gazzolo et al., 1995). Lower panel: data sourced from (Higgins et al., 2018). Please see Supplementary Methods and Supplementary Spreadsheet for details. QS = Quiet Sleep; AS = Active Sleep.

While reduced motor activity and active sleep may be advantageous to the compromised fetus in the short-term, both are thought to be necessary for appropriate sensorimotor and cognitive development based on theoretical and animal models (Blumberg et al., 2020, Cao et al., 2016, Frank et al., 2001, Jha et al., 2005). Consequently, the adverse motor, language and cognitive outcomes observed in survivors of fetal growth restriction could result not only from the insult itself, but these adaptations (Lingam et al., 2023, Sacchi et al., 2021). This might explain why those affected display more active sleep during the neonatal period once they have left the constraints of the uterine environment, in an attempt to counteract its earlier shortage (Hoppenbrouwers et al., 2005).

In many cases, the effects of intrauterine growth restriction on antenatal sleep are then compounded by the effects of premature birth on postnatal sleep, because affected pregnancies often require medically-indicated preterm delivery (Lingam et al., 2023). These include that some preterm infants exhibit relatively little differentiation between cortical activity in each sleep-wake state, which predicts adverse sensorimotor and cognitive outcomes (Conde et al., 2005, El-Dib et al., 2014, Hellström-Westas et al., 1991, Tokariev et al., 2019, Weisman et al., 2011, Wikström et al., 2012).

Finally, preterm infants born after intrauterine growth restriction require particularly long neonatal intensive care unit (NICU) admissions (Lingam et al., 2023). This means that the disruptive effects on sleep of i) intrauterine growth restriction, and ii) prematurity, are finally exacerbated by iii) extended disturbance associated to the sensory environment of the NICU. Clinically necessary painful and other care procedures, and physiological stress, evoke and extend awakenings, especially from the late preterm period onwards (Georgoulas et al., 2021, Grunau et al., 2000, Holditch-Davis et al., 1995). This means that sleep disturbance could be a mediator of the reported association between pain experience in preterm infants and abnormal neurological outcomes (Brummelte et al., 2012, Maitre et al., 2017, Ranger et al., 2013). In summary, in the test case of an infant who suffers intrauterine growth restriction, is born preterm, and then spends weeks on the NICU, all three experiences are likely to contribute to suboptimal sleep.

5. Accounting for sleep-wake state during neonatal functional neuroimaging

The literature reviewed up to now shows that sleep interacts with sensory, language and cognitive brain development. Hence, there are advantages to accounting for sleep-wake state during functional neuroimaging of the young brain. Indeed, unlike in adult neuroimaging, when the subject is almost exclusively awake, fetal and neonatal neuroimaging almost always occurs during natural sleep, because this is so prevalent (Georgoulas et al., 2021). Particularly relevant for the sensory experimental paradigms typically used in this immature population, sleep state affects how sensory input is processed from periphery to cortex. For the visual system, the neonatal retina exhibits higher amplitude evoked responses during active than quiet sleep (Peña et al., 1999), and visual cortical potentials are more reliably elicited in active sleep too (Cubero-Rego et al., 2018). On the other hand, somatosensory and auditory cortical responses are higher amplitude during quiet than active sleep, particularly for higher-order potentials (beyond primary sensory cortex) (Desmedt and Manil, 1970, Kaminska et al., 2018, Nevalainen et al., 2008, Pihko et al., 2004).

While the results discussed above suggest the value of modelling the effect of sleep-wake state on functional neuroimaging data, this can be challenging in developmental populations. Solutions applicable to fetal functional magnetic resonance imaging (fMRI) data include to leverage the timings of movement-related artefact (Ji et al., 2023). In neonates undergoing fMRI, strategies could also utilise the associated cardiorespiratory data (recorded during the scan for safety reasons), especially if synchronised EEG could provide a ‘ground truth’ reference point in at least a small population (Arichi et al., 2017). Similarly, in near infra-red spectroscopy (NIRS) recordings, behavioural sleep-wake staging can be strengthened with concurrent EEG (Gossé et al., 2023, Lee et al., 2020, Shellhaas et al., 2014, Shiraki et al., 2024). Other options include to account for sleep state, even if not treating it as a variable of interest (Colonnese et al., 2010, Whitehead et al., 2019a), separate data into quiet versus active states (pooling active sleep and wakefulness, given their comparable cortical activity (Fig. 1)) (Bongers-Schokking et al., 1989, Montazeri et al., 2022b), or pragmatically treat sleep as an overall state in the youngest preterm subjects for whom active and quiet sleep are less well-defined (Whitehead et al., 2022).

Taking a wider view, accounting for sleep could help to address the larger issue in science of reproducibility failures, in conjunction with greater availability of open-access sleep data and algorithms. For example, open-access sleep-staged EEG and associated data from preterm and older infants are available via (Blumberg and Sokoloff, 2021, Jones et al., 2018, Lee et al., 2022, Whitehead and Fabrizi, 2024). Further, two open-access EEG datasets (not originally associated to sleep stages) have now been sleep scored: the (Stevenson et al., 2019) dataset by (Tamburro et al., 2022), and the (O’Toole et al., 2022) dataset by (Montazeri et al., 2022a). The sleep scoring algorithm employed by the latter, and its visualization tools, can be used openly via a cloud service by requesting access from the authors (Montazeri et al., 2022b). Maternal-fetal open-access resources are rarer, but an interesting recently released example integrates fetal heart rate data with maternal sleep staging (DiPietro et al., 2021, DiPietro et al., 2023, DiPietro, 2023).

6. Conclusion

In early human development, sensory and sleep-wake functions go hand in hand. Perturbation of these twinned functions by neurological insults may mediate later sensorimotor, language and cognitive deficits. Perinatal neuroimaging modalities have the potential to track these trajectories, offering diagnostic and prognostic value, as well as identifying opportunities to therapeutically intervene. Promoting of this, developmental sleep neurology is a burgeoning research field, widely supported by families and stakeholders (de Groot et al., 2023, van den Hoogen et al., 2017, Whitehead, 2024).

CRediT authorship contribution statement

Kimberley Whitehead: Writing – original draft.

Declaration of Competing Interest

The author declares that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

I warmly thank the families who have contributed to my perinatal sleep research. The data illustrated in Fig. 1 and Fig. 2 were acquired during work supported by Brain Research UK (awardee: KW) and the Medical Research Council (awardee: Professor Lorenzo Fabrizi (MR/L019248/1)).

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.dcn.2024.101487.

Appendix A. Supplementary material

Supplementary material

mmc1.docx (24.9KB, docx)

Supplementary material

mmc2.xlsx (34.7KB, xlsx)

Supplementary material

Download audio file (203.5KB, mp3)

Data availability

Open-access data were used to generate Fig. 3: please see Supplementary Methods and Supplementary Spreadsheet for details.

References

  1. Allievi A.G., Arichi T., Tusor N., Kimpton J., Arulkumaran S., Counsell S.J., Edwards A.D., Burdet E. Maturation of sensori-motor functional responses in the preterm brain. Cereb. Cortex. 2016;26:402–413. doi: 10.1093/cercor/bhv203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Arichi T., Whitehead K., Barone G., Pressler R., Padormo F., Edwards A.D., Fabrizi L. Localization of spontaneous bursting neuronal activity in the preterm human brain with simultaneous EEG-fMRI. eLife. 2017;6 doi: 10.7554/eLife.27814. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Azaz Y., Fleming P.J., Levine M., McCabe R., Stewart A., Johnson P. The relationship between environmental temperature, metabolic rate, sleep state, and evaporative water loss in infants from birth to three months. Pedia Res. 1992;32:417–423. doi: 10.1203/00006450-199210000-00010. [DOI] [PubMed] [Google Scholar]
  4. Blumberg M., Sokoloff G. (2021): Sleep, myoclonic twitching, and EEG activity in human infants. 〈http://databrary.org/volume/1281〉.
  5. Blumberg M.S., Lesku J.A., Libourel P.-A., Schmidt M.H., Rattenborg N.C. What Is REM Sleep? Curr. Biol. CB. 2020;30:R38–R49. doi: 10.1016/j.cub.2019.11.045. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bocking A., Adamson L., Cousin A., Campbell K., Carmichael L., Natale R., Patrick J. Effects of intravenous glucose injections on human fetal breathing movements and gross fetal body movements at 38 to 40 weeks’ gestational age. Am. J. Obstet. Gynecol. 1982;142:606–611. doi: 10.1016/s0002-9378(16)32427-9. [DOI] [PubMed] [Google Scholar]
  7. Bongers-Schokking C.J., Colon E.J., Hoogland R.A., Van Den Brande J.L., De Groot K.J. The somatosensory evoked potentials of normal infants: Influence of filter bandpass, arousal state and number of stimuli. Brain Dev. 1989;11:33–39. doi: 10.1016/s0387-7604(89)80006-3. [DOI] [PubMed] [Google Scholar]
  8. Bowe T.R., Anders T.F. The use of the Semi-Markov model in the study of the development of sleep-wake states in infants. Psychophysiology. 1979;16:41–48. doi: 10.1111/j.1469-8986.1979.tb01436.x. [DOI] [PubMed] [Google Scholar]
  9. Brouillette R.T., Thach B.T., Abu-Osba Y.K., Wilson S.L. Hiccups in infants: characteristics and effects on ventilation. J. Pedia. 1980;96:219–225. doi: 10.1016/s0022-3476(80)80806-7. [DOI] [PubMed] [Google Scholar]
  10. Brummelte S., Grunau R.E., Chau V., Poskitt K.J., Brant R., Vinall J., Gover A., Synnes A.R., Miller S.P. Procedural pain and brain development in premature newborns. Ann. Neurol. 2012;71:385–396. doi: 10.1002/ana.22267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Buzsáki G. Two-stage model of memory trace formation: A role for “noisy” brain states. Neuroscience. 1989;31:551–570. doi: 10.1016/0306-4522(89)90423-5. [DOI] [PubMed] [Google Scholar]
  12. Cabana M.D., Wright P., Scozzafava I., Olarte A., DiSabella M., Liu X., Gelfand A.A. Newborn daily crying time duration. J. Pedia Nurs. 2021;56:35–37. doi: 10.1016/j.pedn.2020.10.003. [DOI] [PubMed] [Google Scholar]
  13. Cao M., He Y., Dai Z., Liao X., Jeon T., Ouyang M., Chalak L., Bi Y., Rollins N., Dong Q., Huang H. Early development of functional network segregation revealed by connectomic analysis of the preterm human brain. Cereb. Cortex. 2016 doi: 10.1093/cercor/bhw038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Chipaux M., Colonnese M.T., Mauguen A., Fellous L., Mokhtari M., Lezcano O., Milh M., Dulac O., Chiron C., Khazipov R., Kaminska A. Auditory stimuli mimicking ambient sounds drive temporal “delta-brushes” in premature infants. PLoS ONE. 2013;8 doi: 10.1371/journal.pone.0079028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Colonnese M.T., Kaminska A., Minlebaev M., Milh M., Bloem B., Lescure S., Moriette G., Chiron C., Ben-Ari Y., Khazipov R. A conserved switch in sensory processing prepares developing neocortex for vision. Neuron. 2010;67:480–498. doi: 10.1016/j.neuron.2010.07.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Conde J.R.C., Hoyos A.L.R. de, Martínez E.D., Campo C.G., Pérez A.M., Hernández Borges A.A. Extrauterine life duration and ontogenic EEG parameters in preterm newborns with and without major ultrasound brain lesions. Clin. Neurophysiol. 2005;116:2796–2809. doi: 10.1016/j.clinph.2005.08.020. [DOI] [PubMed] [Google Scholar]
  17. Cubero-Rego L., Corsi-Cabrera M., Ricardo-Garcell J., Cruz-Martínez R., Harmony T. Visual evoked potentials are similar in polysomnographically defined quiet and active sleep in healthy newborns. Int. J. Dev. Neurosci. 2018;68:26–34. doi: 10.1016/j.ijdevneu.2018.04.007. [DOI] [PubMed] [Google Scholar]
  18. Curzi-Dascalova L., Figueroa J.M., Eiselt M., Christova E., Virassamy A., D’allest A.M., Guimarâes H., Gaultier C., Dehan M. Sleep state organization in premature infants of less than 35 weeks’ gestational age. Pedia Res. 1993;34:624–628. doi: 10.1203/00006450-199311000-00013. [DOI] [PubMed] [Google Scholar]
  19. Dall’Orso S., Steinweg J., Allievi A.G., Edwards A.D., Burdet E., Arichi T. Somatotopic mapping of the developing sensorimotor cortex in the preterm human brain. Cereb. Cortex. 2018;28:2507–2515. doi: 10.1093/cercor/bhy050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Dall’Orso S., Fifer W.P., Balsam P.D., Brandon J., O’Keefe C., Poppe T., Vecchiato K., Edwards A.D., Burdet E., Arichi T. Cortical processing of multimodal sensory learning in human neonates. Cereb. Cortex. 2021;31:1827–1836. doi: 10.1093/cercor/bhaa340. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. van den Hoogen A., Teunis C.J., Shellhaas R.A., Pillen S., Benders M., Dudink J. How to improve sleep in a neonatal intensive care unit: A systematic review. Early Hum. Dev. 2017;113:78–86. doi: 10.1016/j.earlhumdev.2017.07.002. [DOI] [PubMed] [Google Scholar]
  22. Desmedt J.E., Manil J. Somatosensory evoked potentials of the normal human neonate in REM sleep, in slow wave sleep and in waking. Electro Clin. Neurophysiol. 1970;29:113–126. doi: 10.1016/0013-4694(70)90114-8. [DOI] [PubMed] [Google Scholar]
  23. DiPietro J.A. (2023): Maternal Sleep in Pregnancy and the Fetus. 〈https://sleepdata.org/datasets/msp〉.
  24. DiPietro J.A., Raghunathan R.S., Wu H.-T., Bai J., Watson H., Sgambati F.P., Henderson J.L., Pien G.W. Fetal heart rate during maternal sleep. Dev. Psychobiol. 2021;63:945–959. doi: 10.1002/dev.22118. [DOI] [PubMed] [Google Scholar]
  25. DiPietro J.A., Bai J., Sgambati F.P., Henderson J.L., Watson H., Raghunathan R.S., Pien G.W. Fetal heart rate responses to maternal sleep-disordered breathing. Am. J. Obstet. Gynecol. 2023;228:459.e1–459.e8. doi: 10.1016/j.ajog.2022.09.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Edwards B.A., Nava-Guerra L., Kemp J.S., Carroll J.L., Khoo M.C., Sands S.A., Terrill P.I., Landry S.A., Amin R.S. Assessing ventilatory instability using the response to spontaneous sighs during sleep in preterm infants. Sleep. 2018;41 doi: 10.1093/sleep/zsy161. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. El-Dib M., Massaro A.N., Glass P., Aly H. Sleep wake cycling and neurodevelopmental outcome in very low birth weight infants. J. Matern Fetal Neonatal Med. 2014;27:892–897. doi: 10.3109/14767058.2013.845160. [DOI] [PubMed] [Google Scholar]
  28. Fantz R.L. Pattern vision in newborn infants. Science. 1963;140:296–297. doi: 10.1126/science.140.3564.296. [DOI] [PubMed] [Google Scholar]
  29. Fifer W.P., Byrd D.L., Kaku M., Eigsti I.-M., Isler J.R., Grose-Fifer J., Tarullo A.R., Balsam P.D. Newborn infants learn during sleep. Proc. Natl. Acad. Sci. 2010;107:10320–10323. doi: 10.1073/pnas.1005061107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Fleming P.J., Goncalves A.L., Levine M.R., Woollard S. The development of stability of respiration in human infants: changes in ventilatory responses to spontaneous sighs. J. Physiol. 1984;347:1–16. doi: 10.1113/jphysiol.1984.sp015049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Frank M.G., Issa N.P., Stryker M.P. Sleep enhances plasticity in the developing visual cortex. Neuron. 2001;30:275–287. doi: 10.1016/s0896-6273(01)00279-3. [DOI] [PubMed] [Google Scholar]
  32. Gazzolo D., Visser G.H.A., Santi F., Magliano C.P., Scopesi F., Russo A., Pittaluga C., Nigro M., Camoriano R., Bruschettini P.L. Behavioural development and Doppler velocimetry in relation to perinatal outcome in small for dates fetuses. Early Hum. Dev. 1995;43:185–195. doi: 10.1016/0378-3782(95)01676-7. [DOI] [PubMed] [Google Scholar]
  33. Georgoulas A., Jones L., Laudiano-Dray M.P., Meek J., Fabrizi L., Whitehead K. Sleep–wake regulation in preterm and term infants. Sleep. 2021;44 doi: 10.1093/sleep/zsaa148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Gordijn S.J., Beune I.M., Thilaganathan B., Papageorghiou A., Baschat A.A., Baker P.N., Silver R.M., Wynia K., Ganzevoort W. Consensus definition of fetal growth restriction: a Delphi procedure. Ultrasound Obstet. Gynecol. 2016;48:333–339. doi: 10.1002/uog.15884. [DOI] [PubMed] [Google Scholar]
  35. Gossé L.K., Pinti P., Wiesemann F., Elwell C.E.E., Jones E.J.H. Developing customized NIRS-EEG for infant sleep research: methodological considerations. Neurophotonics. 2023;10 doi: 10.1117/1.NPh.10.3.035010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Grigg-Damberger M.M. The visual scoring of sleep in infants 0 to 2 months of age. J. Clin. Sleep. Med. JCSM Publ. Am. Acad. Sleep. Med. 2016;12:429–445. doi: 10.5664/jcsm.5600. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Groome L.J., Singh K.P., Bentz L.S., Holland S.B., Atterbury J.L., Swiber M.J., Trimm III R.F. Temporal stability in the distribution of behavioral states for individual human fetuses. Early Hum. Dev. 1997;48:187–197. doi: 10.1016/s0378-3782(96)01853-1. [DOI] [PubMed] [Google Scholar]
  38. Groome L.J., Swiber M.J., Atterbury J.L., Bentz L.S., Holland S.B. Similarities and differences in behavioral state organization during sleep periods in the perinatal infant before and after birth. Child Dev. 1997;68:1–11. [PubMed] [Google Scholar]
  39. de Groot E.R., Bik A., Sam C., Wang X., Shellhaas R.A., Austin T., Tataranno M.L., Benders M.J.N.L., van den Hoogen A., Dudink J. Creating an optimal observational sleep stage classification system for very and extremely preterm infants. Sleep. Med. 2022;90:167–175. doi: 10.1016/j.sleep.2022.01.020. [DOI] [PubMed] [Google Scholar]
  40. de Groot E.R., Ryan M.-A., Sam C., Verschuren O., Alderliesten T., Dudink J., van den Hoogen A. Evaluation of sleep practices and knowledge in neonatal healthcare. Adv. Neonatal Care 23:499. 2023 doi: 10.1097/ANC.0000000000001102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Grunau R.E., Holsti L., Whitfield M.F., Ling E. Are twitches, startles, and body movements pain indicators in extremely low birth weight infants? Clin. J. Pain. 2000;16:37. doi: 10.1097/00002508-200003000-00007. [DOI] [PubMed] [Google Scholar]
  42. Hadders-Algra M., Van Eykern L.A., Klip-Van den Nieuwendijk A.W.J., Prechtl H.F.R. Developmental course of general movements in early infancy. II. EMG correlates. Early Hum. Dev. 1992;28:231–251. doi: 10.1016/0378-3782(92)90170-l. [DOI] [PubMed] [Google Scholar]
  43. Hadders-Algra M., Nakae Y., Van Eykern L.A., Klip-Van den Nieuwendijk A.W.J., Prechtl H.F.R. The effect of behavioural state on general movements in healthy full-term newborns. A polymyographic study. Early Hum. Dev. 1993;35:63–79. doi: 10.1016/0378-3782(93)90140-p. [DOI] [PubMed] [Google Scholar]
  44. Hellström-Westas L., Rosén I., Svenningsen N.W. Cerebral function monitoring during the first week of life in extremely small low birthweight (ESLBW) infants. Neuropediatrics. 1991;22:27–32. doi: 10.1055/s-2008-1071411. [DOI] [PubMed] [Google Scholar]
  45. Higgins L., Johnstone E., Heazell A. (2018): FEMINA2 1. 〈https://data.mendeley.com/datasets/vsxsjhp6n3/1〉.
  46. Holditch-Davis D., Barham L.N., O’Hale A., Tucker B. Effect of standard rest periods on convalescent preterm infants. J. Obstet. Gynecol. Neonatal Nurs. 1995;24:424–433. doi: 10.1111/j.1552-6909.1995.tb02499.x. [DOI] [PubMed] [Google Scholar]
  47. Hoppenbrouwers T., Hodgman J.E., Rybine D., Fabrikant G., Corwin M., Crowell D., Weese-Mayer D.E. Sleep architecture in term and preterm infants beyond the neonatal period: the influence of gestational age, steroids, and ventilatory support. Sleep. 2005;28:1428–1436. doi: 10.1093/sleep/28.11.1428. [DOI] [PubMed] [Google Scholar]
  48. Isler J.R., Thai T., Myers M.M., Fifer W.P. An automated method for coding sleep states in human infants based on respiratory rate variability. Dev. Psychobiol. 2016;58:1108–1115. doi: 10.1002/dev.21482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Jenni O.G., Deboer T., Achermann P. Development of the 24-h rest-activity pattern in human infants. Infant Behav. Dev. 2006;29:143–152. doi: 10.1016/j.infbeh.2005.11.001. [DOI] [PubMed] [Google Scholar]
  50. Jha S.K., Jones B.E., Coleman T., Steinmetz N., Law C.-T., Griffin G., Hawk J., Dabbish N., Kalatsky V.A., Frank M.G. Sleep-dependent plasticity requires cortical activity. J. Neurosci. 2005;25:9266–9274. doi: 10.1523/JNEUROSCI.2722-05.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Ji L., Majbri A., Hendrix C.L., Thomason M.E. Fetal behavior during MRI changes with age and relates to network dynamics. Hum. Brain Mapp. 2023;44:1683–1694. doi: 10.1002/hbm.26167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Jones L., Laudiano-Dray M.P., Whitehead K., Verriotis M., Meek J., Fitzgerald M., Fabrizi L. EEG, behavioural and physiological recordings following a painful procedure in human neonates. Sci. Data. 2018;5 doi: 10.1038/sdata.2018.248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Kaminska A., Delattre V., Laschet J., Dubois J., Labidurie M., Duval A., Manresa A., Magny J.-F., Hovhannisyan S., Mokhtari M., Ouss L., Boissel A., Hertz-Pannier L., Sintsov M., Minlebaev M., Khazipov R., Chiron C. Cortical auditory-evoked responses in preterm neonates: revisited by spectral and temporal analyses. Cereb. Cortex. 2018;28:3429–3444. doi: 10.1093/cercor/bhx206. [DOI] [PubMed] [Google Scholar]
  54. Keen A.E., Frasch M.G., Sheehan M.A., Matushewski B., Richardson B.S. Maturational changes and effects of chronic hypoxemia on electrocortical activity in the ovine fetus. Brain Res. 2011;1402:38–45. doi: 10.1016/j.brainres.2011.05.043. [DOI] [PubMed] [Google Scholar]
  55. Kohyama J. A quantitative assessment of the maturation of phasic motor inhibition during REM sleep. J. Neurol. Sci. 1996;143:150–155. doi: 10.1016/s0022-510x(96)00209-2. [DOI] [PubMed] [Google Scholar]
  56. Koskela T., Kendall G.S., Memon S., Sokolska M., Mabuza T., Huertas-Ceballos A., Mitra S., Robertson N.J., Meek J., Whitehead K. Prognostic value of neonatal EEG following therapeutic hypothermia in survivors of hypoxic-ischemic encephalopathy. Clin. Neurophysiol. 2021;132:2091–2100. doi: 10.1016/j.clinph.2021.05.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Lee C.W., Blanco B., Dempsey L., Chalia M., Hebden J.C., Caballero-Gaudes C., Austin T., Cooper R.J. Sleep state modulates resting-state functional connectivity in neonates. Front. Neurosci. 2020;14 doi: 10.3389/fnins.2020.00347. 〈https://www.frontiersin.org/articles/10.3389/fnins.2020.00347/full〉 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Lee H., Li B., DeForte S., Splaingard M.L., Huang Y., Chi Y., Linwood S.L. A large collection of real-world pediatric sleep studies. Sci. Data. 2022;9:421. doi: 10.1038/s41597-022-01545-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Lingam I., Okell J., Maksym K., Spencer R., Peebles D., Buquis G., Ambler G., Morsing E., Ley D., Singer D., Tenorio V., Dyer J., Ginsberg Y., Weissbach T., Huertas-Ceballos A., Marlow N., David A. (2023): Neonatal outcomes following early fetal growth restriction: a subgroup analysis of the EVERREST study. Arch Dis Child - Fetal Neonatal Ed. 〈https://fn.bmj.com/content/early/2023/04/25/archdischild-2022-325285〉. [DOI] [PubMed]
  60. Losito E., Eisermann M., Vignolo P., Hovhannisyan S., Magny J.F., Kaminska A. Benign neonatal sleep myoclonus evokes somatosensory responses. J. Clin. Neurophysiol. 2017;34:484. doi: 10.1097/WNP.0000000000000412. [DOI] [PubMed] [Google Scholar]
  61. Lucchini M., Shuffrey L.C., Nugent J.D., Pini N., Sania A., Shair M., Brink L., du Plessis C., Odendaal H.J., Nelson M.E., Friedrich C., Angal J., Elliott A.J., Groenewald C.A., Burd L.T., Myers M.M., Fifer W.P., Hankins G.D., Dukes K.A., Sullivan L.M., Tripp T., Robinson F., Raffo C., Petersen J.M., Young R.A., Mai C., Grillo E., Baker T., Toland G., Kinney Carmen M., Haynes H.C., Folkerth R.L., Holm R.D., Boyd I.A., Paterson T., Steen D.S., Markianos H., Roberts K., Broadbelt D., Goldstein K.G., Nelsen R.G., Cotton L.L., Jacobs J., Elliott P., Burd A.J., Angal L., Gromer J., Hoyme J., Jackson H.E., Mack M., Randall L., Sens B.B., Tobacco M.A., Eerden D., Odendaal P.V., Wright H., Geerts C., Jong L., de G., Schubert P., Wadee S., Dempers J., Burger E., Harbron J., Groenewald C., Fifer W., Myers M., Isler J., Sininger Y., Nugent J.D., Condon C., Shair M.C., Thai T., Willinger M., Hereld D., Hoffman H.J., Li C.-M. Effects of prenatal exposure to alcohol and smoking on fetal heart rate and movement regulation. Front. Physiol. 2021;12 doi: 10.3389/fphys.2021.594605. 〈https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.594605/full〉 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Mainous A.G., Hueston W.J. The effect of smoking cessation during pregnancy on preterm delivery and low birthweight. J. Fam. Pract. 1994;38:262–266. [PubMed] [Google Scholar]
  63. Maitre N.L., Key A.P., Chorna O.D., Slaughter J.C., Matusz P.J., Wallace M.T., Murray M.M. The dual nature of early-life experience on somatosensory processing in the human infant brain. Curr. Biol. 2017;27:1048–1054. doi: 10.1016/j.cub.2017.02.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Marshall P.J., Meltzoff A.N. Body maps in the infant brain. Trends Cogn. Sci. 2015;19:499–505. doi: 10.1016/j.tics.2015.06.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Milh M., Kaminska A., Huon C., Lapillonne A., Ben-Ari Y., Khazipov R. Rapid cortical oscillations and early motor activity in premature human neonate. Cereb. Cortex. 2007;17:1582–1594. doi: 10.1093/cercor/bhl069. [DOI] [PubMed] [Google Scholar]
  66. Miranda S.B. Visual abilities and pattern preferences of premature infants and full-term neonates. J. Exp. Child Psychol. 1970;10:189–205. doi: 10.1016/0022-0965(70)90071-8. [DOI] [PubMed] [Google Scholar]
  67. Montazeri S., Airaksinen M., Nevalainen P., Marchi V., Hellström-Westas L., Stevenson N.J., Vanhatalo S. An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation. Lancet Digit Health. 2022;4:e884–e892. doi: 10.1016/S2589-7500(22)00196-0. [DOI] [PubMed] [Google Scholar]
  68. Montazeri S., Nevalainen P., Stevenson N.J., Vanhatalo S. Sleep State Trend (SST), a bedside measure of neonatal sleep state fluctuations based on single EEG channels. Clin. Neurophysiol. 2022;143:75–83. doi: 10.1016/j.clinph.2022.08.022. [DOI] [PubMed] [Google Scholar]
  69. Nevalainen P., Lauronen L., Sambeth A., Wikström H., Okada Y., Pihko E. Somatosensory evoked magnetic fields from the primary and secondary somatosensory cortices in healthy newborns. NeuroImage. 2008;40:738–745. doi: 10.1016/j.neuroimage.2007.09.075. [DOI] [PubMed] [Google Scholar]
  70. Nijhuis J.G., Prechtl H.F.R., Martin C.B., Bots R.S.G.M. Are there behavioural states in the human fetus? Early Hum. Dev. 1982;6:177–195. doi: 10.1016/0378-3782(82)90106-2. [DOI] [PubMed] [Google Scholar]
  71. O’Toole J.M., Mathieson S.R., Magarelli F., Marnane W.P., Lightbody G., Boylan G.B. (2022): Neonatal EEG Graded for Severity of Background Abnormalities. Zenodo. 〈https://zenodo.org/records/7477575〉. [DOI] [PMC free article] [PubMed]
  72. Oller D.K., Caskey M., Yoo H., Bene E.R., Jhang Y., Lee C.-C., Bowman D.D., Long H.L., Buder E.H., Vohr B. Preterm and full term infant vocalization and the origin of language. Sci. Rep. 2019;9 doi: 10.1038/s41598-019-51352-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Peña M., Birch D., Uauy R., Peirano P. The effect of sleep state on electroretinographic (ERG) activity during early human development. Early Hum. Dev. 1999;55:51–62. doi: 10.1016/s0378-3782(99)00006-7. [DOI] [PubMed] [Google Scholar]
  74. Pihko E., Lauronen L., Wikström H., Taulu S., Nurminen J., Kivitie-Kallio S., Okada Y. Somatosensory evoked potentials and magnetic fields elicited by tactile stimulation of the hand during active and quiet sleep in newborns. Clin. Neurophysiol. 2004;115:448–455. doi: 10.1016/s1388-2457(03)00349-3. [DOI] [PubMed] [Google Scholar]
  75. Ranger M., Chau C.M.Y., Garg A., Woodward T.S., Beg M.F., Bjornson B., Poskitt K., Fitzpatrick K., Synnes A.R., Miller S.P., Grunau R.E. Neonatal pain-related stress predicts cortical thickness at age 7 years in children born very preterm. PLOS ONE. 2013;8 doi: 10.1371/journal.pone.0076702. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Roffwarg H.P., Muzio J.N., Dement W.C. Ontogenetic development of the human sleep-dream cycle. Science. 1966;152:604–619. doi: 10.1126/science.152.3722.604. [DOI] [PubMed] [Google Scholar]
  77. Saby J.N., Marshall P.J. The utility of EEG band power analysis in the study of infancy and early childhood. Dev. Neuropsychol. 2012;37:253–273. doi: 10.1080/87565641.2011.614663. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Sacchi C., O’Muircheartaigh J., Batalle D., Counsell S.J., Simonelli A., Cesano M., Falconer S., Chew A., Kennea N., Nongena P., Rutherford M.A., Edwards A.D., Nosarti C. Neurodevelopmental outcomes following intrauterine growth restriction and very preterm birth. J. Pedia. 2021;238:135–144.e10. doi: 10.1016/j.jpeds.2021.07.002. [DOI] [PubMed] [Google Scholar]
  79. Sahni R., Schulze K.F., Stefanski M., Myers M.M., Fifer W.P. Methodological issues in coding sleep states in immature infants. Dev. Psychobiol. 1995;28:85–101. doi: 10.1002/dev.420280203. [DOI] [PubMed] [Google Scholar]
  80. Scopes J.W., Ahmed I. Minimal rates of oxygen consumption in sick and premature newborn infants. Arch. Dis. Child. 1966;41:407–416. doi: 10.1136/adc.41.218.407. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Shellhaas R.A., Burns J.W., Wiggins S.A., Christensen M.K., Barks J.D.E., Chervin R.D. Sleep-wake cycling and cerebral oxygen metabolism among critically Ill neonates. J. Child Neurol. 2014;29:530–533. doi: 10.1177/0883073812470972. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Shiraki A., Kidokoro H., Watanabe H., Taga G., Ushida T., Narita H., Mitsumatsu T., Kumai S., Suzui R., Sawamura F., Ito Y., Yamamoto H., Nakata T., Sato Y., Hayakawa M., Takahashi Y., Natsume J. Sleep state-dependent development of resting-state functional connectivity during the preterm period. Sleep. 2024 doi: 10.1093/sleep/zsae225. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Shuffrey L.C., Myers M.M., Odendaal H.J., Elliott A.J., du Plessis C., Groenewald C., Burd L., Angal J., Nugent J.D., Isler J.R., Fifer W.P. Fetal heart rate, heart rate variability, and heart rate/movement coupling in the safe passage study. J. Perinatol. 2019;39:608–618. doi: 10.1038/s41372-019-0342-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Sokoloff G., Hickerson M.M., Wen R.Y., Tobias M.E., McMurray B., Blumberg M.S. Spatiotemporal organization of myoclonic twitching in sleeping human infants. Dev. Psychobiol. 2020;62:697–710. doi: 10.1002/dev.21954. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Sokoloff G., Dooley J.C., Glanz R.M., Wen R.Y., Hickerson M.M., Evans L.G., Laughlin H.M., Apfelbaum K.S., Blumberg M.S. Twitches emerge postnatally during quiet sleep in human infants and are synchronized with sleep spindles. Curr. Biol. 2021;31:3426–3432.e4. doi: 10.1016/j.cub.2021.05.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Sriram B., Mencer M.A., McKelvey S., Siegel E.R., Vairavan S., Wilson J.D., Preissl H., Eswaran H., Govindan R.B. Differences in the sleep states of IUGR and low-risk fetuses: An MCG study. Early Hum. Dev. 2013;89:815–819. doi: 10.1016/j.earlhumdev.2013.07.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Stabell U., Junge M., Fenner A. Metabolic rate and O2 consumption in newborns during different states of vigilance. Biol. Neonat. 1977;31:27–31. doi: 10.1159/000240939. [DOI] [PubMed] [Google Scholar]
  88. Stevens B.J., Gibbins S., Yamada J., Dionne K., Lee G., Johnston C., Taddio A. The premature infant pain profile-revised (PIPP-R): initial validation and feasibility. Clin. J. Pain. 2014;30:238. doi: 10.1097/AJP.0b013e3182906aed. [DOI] [PubMed] [Google Scholar]
  89. Stevenson N.J., Tapani K., Lauronen L., Vanhatalo S. A dataset of neonatal EEG recordings with seizure annotations. Sci. Data. 2019;6 doi: 10.1038/sdata.2019.39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  90. Stothers J.K., Warner R.M. Oxygen consumption and neonatal sleep states. J. Physiol. 1978;278:435–440. doi: 10.1113/jphysiol.1978.sp012314. [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Tamburro G., Jansen K., Lemmens K., Dereymaeker A., Naulaers G., De Vos M., Comani S. Automated detection and removal of flat line segments and large amplitude fluctuations in neonatal electroencephalography. PeerJ. 2022;10 doi: 10.7717/peerj.13734. [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Ten Hof J., Nijhuis I.J.M., Mulder E.J.H., Nijhuis J.G., Narayan H., Taylor D.J., Westers P., Visser G.H.A. Longitudinal study of fetal body movements: nomograms, intrafetal consistency, and relationship with episodes of heart rate patterns A and B. Pedia Res. 2002;52:568–575. doi: 10.1203/00006450-200210000-00017. [DOI] [PubMed] [Google Scholar]
  93. Thompson J.M.D., Wilson J., Bradford B.F., Li M., Cronin R.S., Gordon A., Raynes-Greenow C.H., Stacey T., Cullling V.M., Askie L.M., O’Brien L.M., Mitchell E.A., McCowan L.M.E., Heazell A.E.P. A better understanding of the association between maternal perception of foetal movements and late stillbirth—findings from an individual participant data meta-analysis. BMC Med. 2021;19:267. doi: 10.1186/s12916-021-02140-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  94. Tokariev A., Roberts J.A., Zalesky A., Zhao X., Vanhatalo S., Breakspear M., Cocchi L. Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms. Nat. Commun. 2019;10:2619. doi: 10.1038/s41467-019-10467-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  95. Vanhatalo S., Jousmäki V., Andersson S., Metsäranta M. An easy and practical method for routine, bedside testing of somatosensory systems in extremely low birth weight infants. Pedia Res. 2009;66:710–713. doi: 10.1203/PDR.0b013e3181be9d66. [DOI] [PubMed] [Google Scholar]
  96. Vasung L., Xu J., Abaci-Turk E., Zhou C., Holland E., Barth W.H., Barnewolt C., Connolly S., Estroff J., Golland P., Feldman H.A., Adalsteinsson E., Grant P.E. Cross-sectional observational study of typical in-utero fetal movements using machine learning. Dev. Neurosci. 2022 doi: 10.1159/000528757. 〈https://www.karger.com/Article/FullText/528757〉 [DOI] [PMC free article] [PubMed] [Google Scholar]
  97. de Vries J.I.P., Fong B.F. Normal fetal motility: an overview. Ultrasound Obstet. Gynecol. 2006;27:701–711. doi: 10.1002/uog.2740. [DOI] [PubMed] [Google Scholar]
  98. Weisman O., Magori-Cohen R., Louzoun Y., Eidelman A.I., Feldman R. Sleep-wake transitions in premature neonates predict early development. Pediatrics. 2011;128:706–714. doi: 10.1542/peds.2011-0047. [DOI] [PubMed] [Google Scholar]
  99. Whitehead K. (2024): OSF | Families and patient involvement in designing a project to analyse routine clinical paediatric EEG recordings for research purposes. 〈https://osf.io/epk4g/〉.
  100. Whitehead K., Fabrizi L. (2024): Sleep-wake resting EEG epochs in human neonates. Open Science Framework (OSF). 〈https://osf.io/〉.
  101. Whitehead K., Meek J., Fabrizi L. Developmental trajectory of movement-related cortical oscillations during active sleep in a cross-sectional cohort of pre-term and full-term human infants. Sci. Rep. 2018;8 doi: 10.1038/s41598-018-35850-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  102. Whitehead K., Laudiano-Dray M.P., Meek J., Fabrizi L. Emergence of mature cortical activity in wakefulness and sleep in healthy preterm and full-term infants. Sleep. 2018;41 doi: 10.1093/sleep/zsy096. 〈https://academic.oup.com/sleep/article/41/8/zsy096/4995737〉 [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Whitehead K., Papadelis C., Laudiano-Dray M.P., Meek J., Fabrizi L. The emergence of hierarchical somatosensory processing in late prematurity. Cereb. Cortex. 2019;29:2245–2260. doi: 10.1093/cercor/bhz030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  104. Whitehead K., Slobodina M., Meek J., Fabrizi L. Fronto-central slow cortical activity is attenuated during phasic events in rapid eye movement sleep at full-term birth. Early Hum. Dev. 2019;136:45–48. doi: 10.1016/j.earlhumdev.2019.07.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  105. Whitehead K., Jones L., Laudiano-Dray M.P., Meek J., Fabrizi L. Event-related potentials following contraction of respiratory muscles in pre-term and full-term infants. Clin. Neurophysiol. 2019;130:2216–2221. doi: 10.1016/j.clinph.2019.09.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  106. Whitehead K., Meek J., Fabrizi L., Smith B.A. Long-range temporal organisation of limb movement kinematics in human neonates. Clin. Neurophysiol. Pract. 2020;5:194–198. doi: 10.1016/j.cnp.2020.07.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  107. Whitehead K., Rupawala M., Laudiano-Dray M.P., Meek J., Olhede S., Fabrizi L. (2022): Spontaneous activation of cortical somatosensory networks depresses their excitability in preterm human neonates. bioRxiv. 〈https://www.biorxiv.org/content/10.1101/2022.12.08.519675v1〉.
  108. Wikström S., Pupp I.H., Rosén I., Norman E., Fellman V., Ley D., Hellström-Westas L. Early single-channel aEEG/EEG predicts outcome in very preterm infants. Acta Paediatr. 2012;101:719–726. doi: 10.1111/j.1651-2227.2012.02677.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  109. Wolff P.H. The development of attention in young infants. Ann. N. Y. Acad. Sci. 1965;118:815–830. doi: 10.1111/j.1749-6632.1965.tb40153.x. [DOI] [PubMed] [Google Scholar]
  110. Zamstein O., Wainstock T., Sheiner E. Decreased fetal movements: perinatal and long-term neurological outcomes. Eur. J. Obstet. Gynecol. Reprod. Biol. 2019;241:1–5. doi: 10.1016/j.ejogrb.2019.07.034. [DOI] [PubMed] [Google Scholar]
  111. Zavala J.H., Ecklund-Flores L., Myers M.M., Fifer W.P. Assessment of autonomic function in the late term fetus: the effects of sex and state. Dev. Psychobiol. 2020;62:224–231. doi: 10.1002/dev.21865. [DOI] [PMC free article] [PubMed] [Google Scholar]
  112. Zhang Y.S., Ghazanfar A.A. Perinatally influenced autonomic system fluctuations drive infant vocal sequences. Curr. Biol. 2016;26:1249–1260. doi: 10.1016/j.cub.2016.03.023. [DOI] [PubMed] [Google Scholar]

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Data Availability Statement

Open-access data were used to generate Fig. 3: please see Supplementary Methods and Supplementary Spreadsheet for details.

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