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Vidaurre Arbizu, Carmen

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Vidaurre Arbizu

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Carmen

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Ingeniería Eléctrica y Electrónica

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0000-0003-3740-049X

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2475

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Now showing 1 - 2 of 2
  • PublicationEmbargo
    Canonical maximization of coherence: a novel tool for investigation of neuronal interactions between two datasets
    (Elsevier, 2019) Vidaurre Arbizu, Carmen; Nolte, Guido; Vries, I. E. J. de; Gómez Fernández, Marisol; Boonstra, Tjeerd W.; Müller, Klaus Robert; Villringer, Arno; Nikulin, Vadim V.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
    Synchronization between oscillatory signals is considered to be one of the main mechanisms through which neuronal populations interact with each other. It is conventionally studied with mass-bivariate measures utilizing either sensor-to-sensor or voxel-to-voxel signals. However, none of these approaches aims at maximizing syn-chronization, especially when two multichannel datasets are present. Examples include cortico-muscular coherence (CMC), cortico-subcortical interactions or hyperscanning (where electroencephalographic EEG/magnetoencephalographic MEG activity is recorded simultaneously from two or more subjects). For all of these cases, a method which could find two spatial projections maximizing the strength of synchronization would be desirable. Here we present such method for the maximization of coherence between two sets of EEG/MEG/EMG(electromyographic)/LFP (localfield potential) recordings. We refer to it as canonical Coherence (caCOH). caCOH maximizes the absolute value of the coherence between the two multivariate spaces in the frequency domain. Thisallows very fast optimization for many frequency bins. Apart from presenting details of the caCOH algorithm, we test its efficacy with simulations using realistic head modelling and focus on the application of caCOH to the detection of cortico-muscular coherence. For this, we used diverse multichannel EEG and EMG recordings and demonstrate the ability of caCOH to extract complex patterns of CMC distributed across spatial and frequency domains. Finally, we indicate other scenarios where caCOH can be used for the extraction of neuronal interactions.
  • PublicationOpen Access
    Novel multivariate methods to track frequency shifts of neural oscillations in EEG/MEG recordings
    (Elsevier, 2023) Vidaurre Arbizu, Carmen; Gurunandan, Kshipra; Jamshidi Idaji, Mina; Nolte, Guido; Gómez Fernández, Marisol; Villringer, Arno; Müller, Klaus Robert; Nikulin, Vadim V.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
    Instantaneous and peak frequency changes in neural oscillations have been linked to many perceptual, motor, and cognitive processes. Yet, the majority of such studies have been performed in sensor space and only occasionally in source space. Furthermore, both terms have been used interchangeably in the literature, although they do not reflect the same aspect of neural oscillations. In this paper, we discuss the relation between instantaneous frequency, peak frequency, and local frequency, the latter also known as spectral centroid. Furthermore, we propose and validate three different methods to extract source signals from multichannel data whose (instantaneous, local, or peak) frequency estimate is maximally correlated to an experimental variable of interest. Results show that the local frequency might be a better estimate of frequency variability than instantaneous frequency under conditions with low signal-to-noise ratio. Additionally, the source separation methods based on local and peak frequency estimates, called LFD and PFD respectively, provide more stable estimates than the decomposition based on instantaneous frequency. In particular, LFD and PFD are able to recover the sources of interest in simulations performed with a realistic head model, providing higher correlations with an experimental variable than multiple linear regression. Finally, we also tested all decomposition methods on real EEG data from a steady-state visual evoked potential paradigm and show that the recovered sources are located in areas similar to those previously reported in other studies, thus providing further validation of the proposed methods.