Abstract:Sleep architecture carries vital information about brain health across the lifespan. In particular, the ability to express distinct vigilance states is a key physiological marker of neurological wellbeing in the newborn infant although systems-level mechanisms remain elusive. Here, we demonstrate that the transition from quiet to active sleep in newborn infants is marked by a substantial reorganization of large-scale cortical activity and functional brain networks. This reorganization is attenuated in preterm … Show more
“…1b) capture brain patterns of global and slow variations along the main geometrical axes (e.g., anterior–posterior, left–right), while higher frequencies encode increasingly complex and localized patterns. This type of cortical decomposition is similar to results obtained with the same technique on different parcellations 20 , as well as with different approaches; e.g., neural field theory 24,25 .Fig. 1Method pipeline.…”
The brain is an assembly of neuronal populations interconnected by structural pathways. Brain activity is expressed on and constrained by this substrate. Therefore, statistical dependencies between functional signals in directly connected areas can be expected higher. However, the degree to which brain function is bound by the underlying wiring diagram remains a complex question that has been only partially answered. Here, we introduce the structural-decoupling index to quantify the coupling strength between structure and function, and we reveal a macroscale gradient from brain regions more strongly coupled, to regions more strongly decoupled, than expected by realistic surrogate data. This gradient spans behavioral domains from lower-level sensory function to high-level cognitive ones and shows for the first time that the strength of structure-function coupling is spatially varying in line with evidence derived from other modalities, such as functional connectivity, gene expression, microstructural properties and temporal hierarchy.
“…1b) capture brain patterns of global and slow variations along the main geometrical axes (e.g., anterior–posterior, left–right), while higher frequencies encode increasingly complex and localized patterns. This type of cortical decomposition is similar to results obtained with the same technique on different parcellations 20 , as well as with different approaches; e.g., neural field theory 24,25 .Fig. 1Method pipeline.…”
The brain is an assembly of neuronal populations interconnected by structural pathways. Brain activity is expressed on and constrained by this substrate. Therefore, statistical dependencies between functional signals in directly connected areas can be expected higher. However, the degree to which brain function is bound by the underlying wiring diagram remains a complex question that has been only partially answered. Here, we introduce the structural-decoupling index to quantify the coupling strength between structure and function, and we reveal a macroscale gradient from brain regions more strongly coupled, to regions more strongly decoupled, than expected by realistic surrogate data. This gradient spans behavioral domains from lower-level sensory function to high-level cognitive ones and shows for the first time that the strength of structure-function coupling is spatially varying in line with evidence derived from other modalities, such as functional connectivity, gene expression, microstructural properties and temporal hierarchy.
“…Quantitatively speaking, the spatial scale of a particle, its characteristic frequencies and Lyapunov exponents, all fit nicely with empirical observations of (dynamic) functional connectivity within and among large-scale intrinsic brain networks (Liegeois et al, 2019 ; Northoff, Wainio-Theberge, & Evers, 2019 ). The use of an eigen-decomposition of this sort is particularly interesting in relation to recent eigenmode-decompositions of structural connectivity (Atasoy, Donnelly, & Pearson, 2016 ), cortical geometry (Tokariev et al, 2019 ), and spatially embedded neural fields (Robinson et al, 2016 ). These related applications are slightly simpler than the current analysis because they can assume symmetric coupling—of one sort or another—and therefore need only deal with real variables and symmetric modes.…”
At the inception of human brain mapping, two principles of functional anatomy underwrote most conceptions—and analyses—of distributed brain responses: namely, functional segregation and integration. There are currently two main approaches to characterizing functional integration. The first is a mechanistic modeling of connectomics in terms of directed effective connectivity that mediates neuronal message passing and dynamics on neuronal circuits. The second phenomenological approach usually characterizes undirected functional connectivity (i.e., measurable correlations), in terms of intrinsic brain networks, self-organized criticality, dynamical instability, and so on. This paper describes a treatment of effective connectivity that speaks to the emergence of intrinsic brain networks and critical dynamics. It is predicated on the notion of Markov blankets that play a fundamental role in the self-organization of far from equilibrium systems. Using the apparatus of the renormalization group, we show that much of the phenomenology found in network neuroscience is an emergent property of a particular partition of neuronal states, over progressively coarser scales. As such, it offers a way of linking dynamics on directed graphs to the phenomenology of intrinsic brain networks.
“…Taken together, infants who experience nociceptive stimuli and stress spend excessive time awake at the expense of sleep, during a sensitive period in which sleep supports cortical development 94,95 , but this additional wakefulness may be of relatively little value [3][4][5] . For example, vigilance to a nociceptive stressor could be less useful when infants do not have the same capacity to ‗fight or flight' as an adult.…”
Study Objectives
In adults, wakefulness can be markedly prolonged at the expense of sleep, e.g. to stay vigilant in the presence of a stressor. These extra-long wake bouts result in a heavy-tailed distribution (highly right-skewed) of wake but not sleep durations. In infants, the relative importance of wakefulness and sleep are reversed, as sleep is necessary for brain maturation. Here we tested whether these developmental pressures are associated with unique regulation of sleep-wake states.
Methods
In 175 infants 28-40 weeks postmenstrual age (PMA), we monitored sleep-wake states using electroencephalography and behaviour. We constructed survival models of sleep-wake bout durations and the effect of PMA and other factors including stress (salivary cortisol), and examined whether sleep is resilient to nociceptive perturbations (a clinically necessary heel lance).
Results
Wake durations followed a heavy-tailed distribution as in adults, and lengthened with PMA and stress. However, differently from adults, active sleep durations also had a heavy-tailed distribution, and with PMA these shortened and became vulnerable to nociception-associated awakenings.
Conclusions
Sleep bouts are differently regulated in infants, with especially long active sleep durations which could consolidate this state’s maturational functions. Curtailment of sleep by stress and nociception may be disadvantageous, especially for pre-term infants given the limited value of wakefulness at this age. This could be addressed by environmental interventions in future.
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