Frequency-dependent organization of the brain’s functional network through delayed-interactions

Ziaeemehr, Abolfazl; Zarei, Mina; Valizadeh, Alireza; Mirasso, Claudio R.

doi:10.1016/j.neunet.2020.08.003

Cited by 20 publications

(9 citation statements)

References 79 publications

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“…Stronger connections in this range can lead to anticorrelation of the nodes and longer delays can both result in positive and negative correlation. In an intermediate-range, around beta and low gamma, we observed that the pattern of the correlations and the distribution of the weights against distance has maximal similarity to each other, compatible with the recent results (Ziaeemehr et al, 2020b).…”

Section: Discussionsupporting

confidence: 91%

Frequency-Resolved Functional Connectivity: Role of Delay and the Strength of Connections

Ziaeemehr

Valizadeh

2021

Front. Neural Circuits

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The brain functional network extracted from the BOLD signals reveals the correlated activity of the different brain regions, which is hypothesized to underlie the integration of the information across functionally specialized areas. Functional networks are not static and change over time and in different brain states, enabling the nervous system to engage and disengage different local areas in specific tasks on demand. Due to the low temporal resolution, however, BOLD signals do not allow the exploration of spectral properties of the brain dynamics over different frequency bands which are known to be important in cognitive processes. Recent studies using imaging tools with a high temporal resolution has made it possible to explore the correlation between the regions at multiple frequency bands. These studies introduce the frequency as a new dimension over which the functional networks change, enabling brain networks to transmit multiplex of information at any time. In this computational study, we explore the functional connectivity at different frequency ranges and highlight the role of the distance between the nodes in their correlation. We run the generalized Kuramoto model with delayed interactions on top of the brain's connectome and show that how the transmission delay and the strength of the connections, affect the correlation between the pair of nodes over different frequency bands.

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Section: Discussionsupporting

confidence: 91%

Frequency-Resolved Functional Connectivity: Role of Delay and the Strength of Connections

Ziaeemehr

Valizadeh

2021

Front. Neural Circuits

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“…Second, we did not incorporate the transmission delay in our model. Indeed, the transmission delay between two brain regions is highly dependent upon their distance, which may range from several milliseconds to hundreds of milliseconds (Kringelbach et al, 2020;Ziaeemehr et al, 2020). In theory, introducing the distant-dependent time delay into a large-scale brain model will significantly enrich the model dynamics and influence SSVEP responses, a prediction that deserves to be examined in future studies.…”

Section: Discussionmentioning

confidence: 99%

Computational exploration of dynamic mechanisms of steady state visual evoked potentials at the whole brain level

Zhang

Cui

Zhang

et al. 2021

Preprint

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Periodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear resonance and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.

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“…To validate the KM for QIF neurons, in the next section we obtain the mean field model corresponding to Eqs. (19) and compare its predictions with those of the mean field model derived in Ref. 38 , which describes the dynamics of the QIF network Eq.…”

Section: Analysis Of the Kuramoto Model For Quadratic Integrate-and-f...mentioning

confidence: 99%

Kuramoto model for populations of quadratic integrate-and-fire neurons with chemical and electrical coupling

Clusella,

Pietras,

Montbrió

2021

Preprint

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We derive the Kuramoto model (KM) corresponding to a population of weakly coupled, nearly identical quadratic integrate-and-fire neurons (QIF) with both electrical and chemical coupling. The ratio of chemical to electrical coupling determines the phase lag of the characteristic sine coupling function of the KM, and critically determines the synchronization properties of the network. We apply our results to investigate chimera states in two coupled populations of identical QIF neurons. We find that the presence of both electrical and chemical coupling is a necessary condition for chimera states to exist. Finally, we numerically demonstrate that chimera states gradually disappear as coupling strengths cease to be weak.

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Frequency-dependent organization of the brain’s functional network through delayed-interactions

Cited by 20 publications

References 79 publications

Frequency-Resolved Functional Connectivity: Role of Delay and the Strength of Connections

Frequency-Resolved Functional Connectivity: Role of Delay and the Strength of Connections

Computational exploration of dynamic mechanisms of steady state visual evoked potentials at the whole brain level

Kuramoto model for populations of quadratic integrate-and-fire neurons with chemical and electrical coupling

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