Saeed Taghavi, Gianluca Susi, Fernando Maestú, Alireza Valizadeh
{"title":"Tuning the brain rhythms: How internal coherence influences network entrainment by tACS","authors":"Saeed Taghavi, Gianluca Susi, Fernando Maestú, Alireza Valizadeh","doi":"10.1016/j.chaos.2025.117421","DOIUrl":null,"url":null,"abstract":"Transcranial alternating current stimulation (tACS) is a promising tool for modulating brain activity, but its effects depend critically on the ongoing dynamics of the targeted networks. Here, we use a biophysically plausible model of a recurrent excitatory–inhibitory neuronal network to investigate how the endogenous coherence of neural oscillations modulates network response to external periodic inputs. By systematically varying the level of background excitation, we manipulate the synchrony and the amplitude of emergent rhythms. We then apply sinusoidal inputs with varying frequency and intensity to probe neuronal and network-level entrainment. At the single-neuron level, we assess phase locking of the spiking of the individual neurons to the stimulation; at the network level, we analyze the coherence between the population activity and the stimulation signal. Our results reveal increased phase locking in a subset of neurons, which is more pronounced in inhibitory neurons. Crucially, we observe that the Arnold tongue, which refers to the range of frequencies and intensities over which the network entrains to the external drive, broadens significantly when the network’s endogenous coherence is low. These findings suggest that the initial state of brain oscillations plays a key role in determining tACS efficacy, with implications for individualized stimulation protocols.","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"160 1","pages":""},"PeriodicalIF":5.6000,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos Solitons & Fractals","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1016/j.chaos.2025.117421","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Transcranial alternating current stimulation (tACS) is a promising tool for modulating brain activity, but its effects depend critically on the ongoing dynamics of the targeted networks. Here, we use a biophysically plausible model of a recurrent excitatory–inhibitory neuronal network to investigate how the endogenous coherence of neural oscillations modulates network response to external periodic inputs. By systematically varying the level of background excitation, we manipulate the synchrony and the amplitude of emergent rhythms. We then apply sinusoidal inputs with varying frequency and intensity to probe neuronal and network-level entrainment. At the single-neuron level, we assess phase locking of the spiking of the individual neurons to the stimulation; at the network level, we analyze the coherence between the population activity and the stimulation signal. Our results reveal increased phase locking in a subset of neurons, which is more pronounced in inhibitory neurons. Crucially, we observe that the Arnold tongue, which refers to the range of frequencies and intensities over which the network entrains to the external drive, broadens significantly when the network’s endogenous coherence is low. These findings suggest that the initial state of brain oscillations plays a key role in determining tACS efficacy, with implications for individualized stimulation protocols.
期刊介绍:
Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.