Anticipated synchronization in neuronal circuits unveiled by a phase-response-curve analysis

Matias, Fernanda S.; Carelli, Pedro V.; Mirasso, Claudio R.; Copelli, Mauro

doi:10.1103/physreve.95.052410

Cited by 19 publications

(11 citation statements)

References 32 publications

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“…The PRC has been extensively shown to be important to explain different synchronization scenarios between coupled dynamical systems (see .e.g. [29,68]). It the case of delay-coupled neuronal populations, the PRC accurately reveals the efficacy and the direction of the information transfer.…”

Section: Role Of Collective Phase Response Functionsmentioning

confidence: 99%

Transmission delays and frequency detuning can regulate information flow between brain regions

Pariz

Fischer

Valizadeh

et al. 2020

Preprint

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Brain networks exhibit very variable and dynamical functional connectivity and flexible configurations of information exchange despite their overall fixed structure (connectome). Brain oscillations are hypothesized to underlie time-dependent functional connectivity by periodically changing the excitability of neural populations. In this paper, we investigate the role that the connection delay and the frequency detuning between different neural populations play in the transmission of signals. Based on numerical simulations and analytical arguments, we show that the amount of information transfer between two oscillating neural populations can be determined solely by their connection delay and the mismatch in their oscillation frequencies. Our results highlight the role of the collective phase response curve of the oscillating neural populations for the efficacy of signal transmission and the quality of the information transfer in brain networks.

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Section: Role Of Collective Phase Response Functionsmentioning

confidence: 99%

Transmission delays and frequency detuning can regulate information flow between brain regions

Pariz

Fischer

Valizadeh

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…For example, for a specific parameter mismatch between the sender and the receiver system that gives a first-order approximation to the delayed coupling (Corron et al, 2005). AS has also been reported in a chain consisting of a sender and two receivers with switching parameters (Pyragienè and Pyragas, 2015), between two Hodgkin-Huxley neurons with different depolarization parameters (Simonov et al, 2014) and in the presence of an inhibitory loop mediated by an interneuron with a free-running frequency greater than the others (Matias et al, 2017). It has also been shown that AS may appear between two neuron models directly coupled provided that the mean frequency of the free receiver is greater than the mean frequency of the sender with (Hayashi et al, 2016) and without the explicit time-delay (Pyragienè and Pyragas, 2013; Dima et al, 2018).…”

Section: Introductionmentioning

confidence: 93%

Exploring the Phase-Locking Mechanisms Yielding Delayed and Anticipated Synchronization in Neuronal Circuits

Porta

Matias

Santos

et al. 2019

Front. Syst. Neurosci.

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Synchronization is one of the brain mechanisms allowing the coordination of neuronal activity required in many cognitive tasks. Anticipated Synchronization (AS) is a specific type of out-of-phase synchronization that occurs when two systems are unidirectionally coupled and, consequently, the information is transmitted from the sender to the receiver, but the receiver leads the sender in time. It has been shown that the primate cortex could operate in a regime of AS as part of normal neurocognitive function. However it is still unclear what is the mechanism that gives rise to anticipated synchronization in neuronal motifs. Here, we investigate the synchronization properties of cortical motifs on multiple scales and show that the internal dynamics of the receiver, which is related to its free running frequency in the uncoupled situation, is the main ingredient for AS to occur. For biologically plausible parameters, including excitation/inhibition balance, we found that the phase difference between the sender and the receiver decreases when the free running frequency of the receiver increases. As a consequence, the system switches from the usual delayed synchronization (DS) regime to an AS regime. We show that at three different scales, neuronal microcircuits, spiking neuronal populations and neural mass models, both the inhibitory loop and the external current acting on the receiver mediate the DS-AS transition for the sender-receiver configuration by changing the free running frequency of the receiver. Therefore, we propose that a faster internal dynamics of the receiver system is the main mechanism underlying anticipated synchronization in brain circuits.

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“…A common brain signature of general anesthesia is the loss of global functional connectivity between specialized regions of the cortex while local populations show increases in neural synchrony [25,34,35]. Cellular and network mechanisms leading to neural synchrony have been studied extensively in the field of computational neuroscience [36][37][38]. A set of possible network wide mechanisms are the PING (pyramidal interneuron network gamma) class of mechanisms, where stable, synchronous activity patterns emerge when inhibition periodically shuts down excitation in the network [39][40][41][42][43].…”

Section: Anesthetic Effects On Spike Synchronymentioning

confidence: 99%

Modeling Synaptic Effects of Anesthesia and its Cortical Cholinergic Reversal

Enivaye

Booth

Hudetz

et al. 2021

Preprint

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General anesthetics work through a variety of molecular mechanisms while resulting in the common end point of sedation and loss of consciousness. Generally, the administration of common inhalation anesthetics induces decreases in synaptic excitation while promoting synaptic inhibition. Animal studies have shown that, during anesthesia, exogenously induced increases in acetylcholine-mediated effects in the brain can elicit wakeful-like behavior despite the continued presence of the anesthetic. Less investigated, however, is the question of whether the brain's electrophysiological activity is also restored to pre-anesthetic levels and quality by such interventions. Here we apply a computational model of a network composed of excitatory and inhibitory neurons to simulate the network effects of changes in synaptic inhibition and excitation due to anesthesia and its reversal by muscarinic receptor-mediated cholinergic effects. We use a differential evolution algorithm to fit model parameters to match measures of spiking activity, neuronal connectivity, and network dynamics recorded in the visual cortex of rodents during anesthesia with desflurane in vivo. We find that facilitating muscarinic receptor effects of acetylcholine on top of anesthetic-induced synaptic changes predicts reversal of the neurons’ spiking activity, functional connectivity, as well as pairwise and population interactions. Thus, our model results predict a possible neuronal mechanism for the induced reversal of the effects of anesthesia on post synaptic potentials, consistent with experimental behavioral observations.

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Anticipated synchronization in neuronal circuits unveiled by a phase-response-curve analysis

Cited by 19 publications

References 32 publications

Transmission delays and frequency detuning can regulate information flow between brain regions

Transmission delays and frequency detuning can regulate information flow between brain regions

Exploring the Phase-Locking Mechanisms Yielding Delayed and Anticipated Synchronization in Neuronal Circuits

Modeling Synaptic Effects of Anesthesia and its Cortical Cholinergic Reversal

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