Tuning Neural Synchronization: The Role of Variable Oscillation Frequencies in Neural Circuits

Lowet, Eric; Weerd, Peter De; Roberts, Mark; Hadjipapas, Avgis

doi:10.3389/fnsys.2022.908665

Cited by 9 publications

(8 citation statements)

References 98 publications

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“…Self-organized, autonomous synchronization occurs because coupled oscillators either advance/accelerate or delay/decelerate each other until they maintain a common stable, intermediate frequency (a new dynamic setpoint) at stable phase relationships (Fig. 2A-C) (Tokuda et al, 2015(Tokuda et al, , 2020Ananthasubramaniam et al, 2018;Hahn et al, 2019;Lowet et al, 2022).…”

Section: General Properties Of Endogenous Oscillators and Clocksmentioning

confidence: 99%

Contribution of membrane-associated oscillators to biological timing at different timescales

Stengl¹,

Schneider²

2023

Preprint

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Environmental rhythms have selected for endogenous clocks that predict regular environmental changes like the daily light-dark cycle. Endogenous clocks are based on positive feedforward and negative feedback loops that generate rhythms even under constant conditions. Autonomous coupling of oscillators is the basis of self-organized timing that determines the repetitive sequence of events of physiology and behavior while mechanisms of homeostatic plasticity serve to maintain and stabilize physiological and behavioral homeostasis. The best studied biological clocks are circadian clock neurons of insects and mammals. Their molecular clockwork in the nucleus consists of transcriptional and translational feedback loops (TTFLs). This clockwork generates ~24 h rhythms in clock gene expression entrained to the light-dark cycle. It is assumed to drive all circadian oscillations in clock neurons such as rhythms in membrane potential, second messenger levels, and neurotransmitter release, thereby controlling circadian rhythms in physiology and behavior. It is not discerned yet whether the membrane-bound rhythms are mere outputs of the TTFL clockwork or whether instead they are driven by an autonomous posttranscriptional feedback loop (PTFL) clockwork in the plasma membrane. Furthermore, next to circadian rhythms the plasma membrane generates rhythms on much faster or slower timescales. It is not understood whether and how these multiscale rhythms are linked. Based on our work in peripheral and central insect multiscale clock neurons, we hypothesize that the excitable plasma membrane constitutes an adaptive endogenous PTFL clockwork at multiple timescales. Multiscale membrane-associated rhythms are suggested to be coupled to, but not driven by, the TTFL clockwork in the nucleus. Furthermore, we suggest that negative feedback loops via protein kinases and phosphatases on the one hand provide for mechanisms of homeostatic plasticity that maintain physiological homeostasis, keeping the period of cellular clocks stable. On the other hand, they also serve as coupling factors and links between cellular oscillators and clocks at multiple time scales controlling the temporal sequence and/or synchronization of physiological and behavioral processes. Our novel hypothesis is up for challenge in future experiments in different species.

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Section: General Properties Of Endogenous Oscillators and Clocksmentioning

confidence: 99%

Contribution of membrane-associated oscillators to biological timing at different timescales

Stengl¹,

Schneider²

2023

Preprint

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“…Autonomous synchronization happens because inputs into an oscillator do not cause runaway acceleration or runaway braking but have phase-dependent antagonistic effects ( Figures 2A, B ). Self-organized, autonomous synchronization occurs because coupled oscillators either advance/accelerate or delay/decelerate each other until they maintain a common stable, intermediate frequency (a new dynamic setpoint) at stable phase relationships ( Figure 2 ) ( Tokuda et al, 2015 ; 2020 ; Ananthasubramaniam et al, 2018 ; Hahn et al, 2019 ; Lowet et al, 2022 ). Dependent on the context some oscillators become dominant and impose their frequency on other oscillators.…”

Section: Introductionmentioning

confidence: 99%

“…The endogenous period of clocks is species-specific and genetically determined and maintains stable oscillations even under constant conditions. In addition to unilateral entrainment by a zeitgeber the mutual coupling of endogenous clocks ( Figure 2C ) allows for autonomous multilateral synchronization which adds dynamics on a higher level than unilateral entrainment ( Hardin, 2011 ; Hahn et al, 2019 ; Tokuda et al, 2020 ; Lowet et al, 2022 ; Jagannath et al, 2023 ; Kageyama et al, 2023 ; Kahn et al, 2023 ; Patton and Hastings, 2023 ; Wollmuth and Angert, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

“…Respective endogenous oscillations are not an unwanted artefact but a process that can couple and reconcile antagonistic mechanisms into a stable system. Autonomous synchronization/entrainment of endogenous oscillators underlies the autonomously generated robust sustainable order and homeostasis of biological systems and embed organisms into their environmental niche ( Schulz and Lane, 2017 ; Hahn et al, 2019 ; Liang et al, 2019 ; Rojas et al, 2019 ; Trujillo et al, 2019 ; Lowet et al, 2022 ; Jagannath et al, 2023 ; Kageyama et al, 2023 ; Kahn et al, 2023 ; Patton and Hastings, 2023 ; Wollmuth and Angert, 2023 ). The stable limit cycle oscillation frequency of a coupled system of endogenous oscillators can be viewed as dynamic setpoint of physiological homeostasis that the system bounces back to after perturbations.…”

Section: Introductionmentioning

confidence: 99%

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Contribution of membrane-associated oscillators to biological timing at different timescales

Stengl,

Schneider

2024

Front. Physiol.

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Environmental rhythms such as the daily light-dark cycle selected for endogenous clocks. These clocks predict regular environmental changes and provide the basis for well-timed adaptive homeostasis in physiology and behavior of organisms. Endogenous clocks are oscillators that are based on positive feedforward and negative feedback loops. They generate stable rhythms even under constant conditions. Since even weak interactions between oscillators allow for autonomous synchronization, coupling/synchronization of oscillators provides the basis of self-organized physiological timing. Amongst the most thoroughly researched clocks are the endogenous circadian clock neurons in mammals and insects. They comprise nuclear clockworks of transcriptional/translational feedback loops (TTFL) that generate ∼24 h rhythms in clock gene expression entrained to the environmental day-night cycle. It is generally assumed that this TTFL clockwork drives all circadian oscillations within and between clock cells, being the basis of any circadian rhythm in physiology and behavior of organisms. Instead of the current gene-based hierarchical clock model we provide here a systems view of timing. We suggest that a coupled system of autonomous TTFL and posttranslational feedback loop (PTFL) oscillators/clocks that run at multiple timescales governs adaptive, dynamic homeostasis of physiology and behavior. We focus on mammalian and insect neurons as endogenous oscillators at multiple timescales. We suggest that neuronal plasma membrane-associated signalosomes constitute specific autonomous PTFL clocks that generate localized but interlinked oscillations of membrane potential and intracellular messengers with specific endogenous frequencies. In each clock neuron multiscale interactions of TTFL and PTFL oscillators/clocks form a temporally structured oscillatory network with a common complex frequency-band comprising superimposed multiscale oscillations. Coupling between oscillator/clock neurons provides the next level of complexity of an oscillatory network. This systemic dynamic network of molecular and cellular oscillators/clocks is suggested to form the basis of any physiological homeostasis that cycles through dynamic homeostatic setpoints with a characteristic frequency-band as hallmark. We propose that mechanisms of homeostatic plasticity maintain the stability of these dynamic setpoints, whereas Hebbian plasticity enables switching between setpoints via coupling factors, like biogenic amines and/or neuropeptides. They reprogram the network to a new common frequency, a new dynamic setpoint. Our novel hypothesis is up for experimental challenge.

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“…Neural activity synchronization is crucial to neural function and cognitive processes [16][17][18][19]. Synchronization of different single neuron classes to periodic external stimuli [20,21] and coupled neurons [22][23][24][25] has been analyzed extensively, and can be measured both locally or over a global scale [26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Criticality and partial synchronization analysis in Wilson-Cowan and Jansen-Rit neural mass models

Kazemi,

Farokhniaee,

Jamali

2023

Preprint

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Synchronization is a phenomenon observed in neuronal networks involved in diverse brain activities. Neural mass models such as Wilson-Cowan (WC) and Jansen-Rit (JR) manifest synchronized states. Although they have been studied for decades, their ability to demonstrate second-order phase transition (SOPT) and criticality has not received enough attention, which serves as candidates for the development of healthy brain networks. In this study, two networks of coupled WC and JR nodes with small-world topologies were constructed and Kuramoto order parameter (KOP) was used to quantify the amount of synchronization. In addition, we investigated the presence of SOPT using the synchronization coefficient of variation. Both networks reached high synchrony by changing the coupling weight between their nodes. Moreover, they exhibited abrupt changes in the synchronization at certain values of the control parameter not necessarily related to a phase transition. While SOPT was observed only in JR model, neither WC nor JR model showed power-law behavior. Our study further investigated the global synchronization phenomenon that is known to exist in pathological brain states, such as seizure. JR model showed global synchronization, while WC model seemed to be more suitable in producing partially synchronized patterns.Corresponding author summaryYousef Jamali received his M.Sc. degree in physics from Sharif University, Tehran, Iran, in 2004, and his Ph.D. degree in physics from Sharif University, Tehran, Iran, in 2009. After finishing his Ph.D. thesis, in 2009, he got two years postdoctoral research associate position at the University of California at Berkeley, Department of Bioengineering. He is currently an Associate Professor in the Applied Mathematics Department (Biomathematics division), at Tarbiat Modares University, Tehran, Iran. His current research interests include the interdisciplinary area of the complex system especially on the modeling of brain. In fact, his interests are how the brain works at the critical state and how this complex system synchronized under different conditions.

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Tuning Neural Synchronization: The Role of Variable Oscillation Frequencies in Neural Circuits

Cited by 9 publications

References 98 publications

Contribution of membrane-associated oscillators to biological timing at different timescales

Contribution of membrane-associated oscillators to biological timing at different timescales

Contribution of membrane-associated oscillators to biological timing at different timescales

Criticality and partial synchronization analysis in Wilson-Cowan and Jansen-Rit neural mass models

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