Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture

Scarpetta, Silvia; Morisi, Niccolò; Mutti, Carlotta; Azzi, Nicoletta; Trippi, Irene; Ciliento, Rosario; Apicella, Ilenia; Messuti, Giovanni; Angiolelli, Marianna; Lombardi, Fabrizio; Parrino, Liborio; Vaudano, Anna Elisabetta

doi:10.1016/j.isci.2023.107840

Cited by 14 publications

(6 citation statements)

References 92 publications

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“…Under these conditions, the authors could show χ = 2 in vivo 2-photon imaging recordings of cellular activity with high signal-to-noise ratio for sensory evoked and spontaneous spike avalanches in frontal and sensory cortices of awake mice in line with their simulations 9 . This is in line with a recent EEG study 50 in humans that demonstrated χ = 2.…”

Section: Introductionsupporting

confidence: 93%

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Srinivasan,

Ribeiro,

Kells

et al. 2024

Preprint

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Scaling relationships characterize complex systems at criticality. In the brain, these relationships are evident in scale-invariant activity cascades, so-called neuronal avalanches, quantified by power laws in avalanche size and duration. At the cellular level, neuronal avalanches are identified in spatially distributed groups of neurons that participate in cascades of coincident action potential firing. Such spatiotemporal synchronization is central to theories on brain function, yet scaling relationships in avalanche synchronization have been challenging to study when only a fraction of neurons is observed, underestimating avalanche properties. Here, we study these biases from fractional sampling in an all-to-all, balanced network of excitatory and inhibitory neurons with critical branching process dynamics. We focus on the growth of mean avalanche size with avalanche duration. For parabolic avalanches, this growth is quadratic, quantified by the scaling exponent, χ = 2, which signifies rapid spatial expansion of coincident firing within a relatively short period of time. In contrast, χ << 2 for fractionally sampled networks. We show that temporal coarse-graining combined with a threshold for the minimally required coincident firing in the network recovers χ = 2, even when sampling as few as 0.1% of the neurons. In contrast, a commonly proposed ’crackling noise’ approach fails to recover χ under those conditions. Our approach robustly identifies χ = 2 for ongoing neuronal activity in frontal cortex of awake mice using cellular 2-photon imaging. Our findings demonstrate how to correct scaling bias from fractional sampling and identifies rapid, scale-invariant synchronization of cell assemblies in the brain.AUTHOR SUMMARYIn the brain, groups of neurons often fire together which is considered essential for normal brain function. A particular form of coincident firing has been identified for “neuronal avalanches” which are scale-invariant cascades of neuronal activity that rapidly engage large numbers of neurons. However, studying these avalanches when observing only a few neurons in the network is challenging. We used simulations and recordings from ongoing brain activity to explore how to overcome this challenge. We found that adjusting our temporal resolution and focusing on increasingly larger avalanches allows us to accurately detect rapid, parabolic expansions of these patterns even when examining a minuscule fraction of neurons. This identifies a general rule for how the brain operates best in engaging neurons to fire together, despite the limitations in our observations.

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Section: Introductionsupporting

confidence: 93%

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Srinivasan,

Ribeiro,

Kells

et al. 2024

Preprint

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“… 59 – 66 This further confirms that the AADs and the Omori law are related to the alpha rhythm dominating the awake resting state and suggests distinct generative mechanisms for the cascading process during NREM sleep. Despite the difference in avalanche dynamics between sleep and awake resting state reported here, neuronal avalanches during sleep show power-law size and duration distributions consistent with criticality, 67 , 68 as observed in the awake resting state. 36 , 37 …”

Section: Discussionsupporting

confidence: 62%

Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification of neural activity in the awake resting state

Lombardi,

Herrmann,

Parrino

et al. 2023

Cell Reports

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“…Previous claims about whether or not the brain operates close to criticality during sleep or active awake states are controversial. Some studies report deviation from criticality during sleep 5,36 , while others suggest the oppposite 31,37,38 or little difference between sleep and wake 39,40 . Another related line of work shows that prolonged lack of sleep results in deviation from criticality, while sleep tunes the brain back to criticality 41,42 .…”

Section: Resolved Controversy Limitations Future Prospectsmentioning

confidence: 99%

Cortex deviates from criticality during action and deep sleep: a temporal renormalization group approach

Sooter,

Fontenele,

et al. 2024

Preprint

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The hypothesis that the brain operates near criticality explains observations of complex, often scale-invariant, neural activity. However, the brain is not static, its dynamical state varies depending on what an organism is doing. Neurons often become more synchronized (ordered) during unconsciousness and more desynchronized (disordered) in highly active awake conditions. Are all these states equidistant from criticality; if not, which is closest? The fundamental physics of how systems behave near criticality came from renormalization group (RG) theory, but RG for neural systems remains largely undeveloped. Here we developed a temporal RG (tRG) theory for analysis of typical neuroscience data. We mathematically identified multiple types of criticality (tRG fixed points) and developed tRG-driven data analytic methods to assess proximity to each fixed point based on relatively short time series. Unlike traditional methods for studying criticality in neural systems, our tRG approach allows time-resolved measurements of distance from criticality in experiments at behaviorally relevant timescales. We apply our approach to recordings of spike activity in mouse visual cortex, showing that the relaxed, awake state is closest to criticality. When arousal shifts away from this state – either increasing in more active awake states or decreasing in deep sleep – cortical dynamics deviate from criticality.

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Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture

Cited by 14 publications

References 92 publications

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification of neural activity in the awake resting state

Cortex deviates from criticality during action and deep sleep: a temporal renormalization group approach

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