Phase Synchronization in Neural Systems

Daffertshofer, Andreas; Pietras, Bastian

doi:10.1007/978-3-642-27737-5_693-1

Cited by 3 publications

(3 citation statements)

References 63 publications

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“…By sustaining communication among networks ( Fries, 2005 ), synchronization of neural activity mediates information processing in the brain ( Singer, 1993 ; Borisyuk et al, 1998 ; Fries, 2009 ). In other words, the correlated neurons’ behaviors, even though they are generated by spatially discrete and/or distant areas ( Gray et al, 1989 ), emerge from the integration of their signals that allow for sensory ( Gray, 1994 ), attentional ( Womelsdorf and Fries, 2007 ), or motor processing as well as for memory ( Axmacher et al, 2006 ), and for other fundamental cognitive processes ( Daffertshofer and Pietras, 2020 ). As a classical example, in visual areas, phase-locked oscillations of spatially segregated neuronal pools mediate binding of diverse visual features like motion, shape, and color into a coherent perception ( Singer and Gray, 1995 ).…”

Section: Introductionmentioning

confidence: 99%

Normalized compression distance to measure cortico-muscular synchronization

Pascarella

Gianni²,

Abbondanza³

et al. 2022

Front. Neurosci.

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The neuronal functional connectivity is a complex and non-stationary phenomenon creating dynamic networks synchronization determining the brain states and needed to produce tasks. Here, as a measure that quantifies the synchronization between the neuronal electrical activity of two brain regions, we used the normalized compression distance (NCD), which is the length of the compressed file constituted by the concatenated two signals, normalized by the length of the two compressed files including each single signal. To test the NCD sensitivity to physiological properties, we used NCD to measure the cortico-muscular synchronization, a well-known mechanism to control movements, in 15 healthy volunteers during a weak handgrip. Independently of NCD compressor (Huffman or Lempel Ziv), we found out that the resulting measure is sensitive to the dominant-non dominant asymmetry when novelty management is required (p = 0.011; p = 0.007, respectively) and depends on the level of novelty when moving the non-dominant hand (p = 0.012; p = 0.024). Showing lower synchronization levels for less dexterous networks, NCD seems to be a measure able to enrich the estimate of functional two-node connectivity within the neuronal networks that control the body.

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Section: Introductionmentioning

confidence: 99%

Normalized compression distance to measure cortico-muscular synchronization

Pascarella

Gianni²,

Abbondanza³

et al. 2022

Front. Neurosci.

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“…Research on the phase dynamics of cortical oscillatory activity is rather recent compared to amplitude modulations in the M/EEG. However, there are several reports indicating that the phase dynamics play a crucial role for information processing and intercortical communication [22,64,74,75,82,84].…”

Section: Introductionmentioning

confidence: 99%

Reduced Phase Models of Oscillatory Neural Networks

Pietras¹,

Daffertshofer

2021

Understanding Complex Systems

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“…Yet, an important theoretical achievement linking individual and global dynamics has been recently accomplished with the advent of the Ott-Antonsen theory [30], and with its application to populations of θ-neurons [31] and Quadratic Integrate-and-Fire (QIF) neurons [32]. Notably, these novel theoretical approaches readily apply to networks with electrical synapses [33][34][35][36].…”

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confidence: 99%

Exact mean-field theory explains the dual role of electrical synapses in collective synchronization

Montbrió,

Pazó

2020

Preprint

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Electrical synapses play a major role in setting up neuronal synchronization, but the precise mechanisms whereby these synapses contribute to synchrony are subtle and remain elusive. To investigate these mechanisms mean-field theories for quadratic integrate-and-fire neurons with electrical synapses have been recently put forward. Still, the validity of these theories is controversial since they assume that the neurons produce unrealistic, symmetric spikes, ignoring the well-known impact of spike shape on synchronization. Here we show that the assumption of symmetric spikes can be relaxed in such theories. The resulting mean-field equations reveal a dual role of electrical synapses: First, they equalize membrane potentials favoring the emergence of synchrony. Second, electrical synapses act as "virtual chemical synapses", which can be either excitatory or inhibitory depending upon the spike shape. Our results offer a precise mathematical explanation of the intricate effect of electrical synapses in collective synchronization. This reconciles previous theoretical and numerical works, and confirms the suitability of recent low-dimensional mean-field theories to investigate electrically coupled neuronal networks.

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Phase Synchronization in Neural Systems

Cited by 3 publications

References 63 publications

Normalized compression distance to measure cortico-muscular synchronization

Normalized compression distance to measure cortico-muscular synchronization

Reduced Phase Models of Oscillatory Neural Networks

Exact mean-field theory explains the dual role of electrical synapses in collective synchronization

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