Phase shift invariant imaging of coherent sources (PSIICOS) from MEG data
| Autor: | Dmitrii Altukhov, Karim Jerbi, Alex Ossadtchi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
Cognitive Neuroscience Population Models Neurological Phase (waves) Electroencephalography 050105 experimental psychology Synchronization 03 medical and health sciences 0302 clinical medicine medicine Coherence (signal processing) Humans 0501 psychology and cognitive sciences Invariant (mathematics) education Cross-spectrum education.field_of_study Brain Mapping Quantitative Biology::Neurons and Cognition medicine.diagnostic_test 05 social sciences Detector Brain Magnetoencephalography Signal Processing Computer-Assisted Electrophysiology Amplitude Neurology Nerve Net Algorithm 030217 neurology & neurosurgery Algorithms Coherence (physics) |
| Zdroj: | NeuroImage. 183 |
| ISSN: | 1095-9572 |
| Popis: | Increasing evidence suggests that neuronal communication is a defining property of functionally specialized brain networks and that it is implemented through synchronization between population activities of distinct brain areas. The detection of long-range coupling in electroencephalography (EEG) and magnetoencephalography (MEG) data using conventional metrics (such as coherence or phase-locking value) is by definition contaminated by spatial leakage. Methods such as imaginary coherence, phase-lag index or orthogonalized amplitude correlations tackle spatial leakage by ignoring zero-phase interactions. Although useful, these metrics will by construction lead to false negatives in cases where true zero-phase coupling exists in the data and will underestimate interactions with phase lags in the vicinity of zero. Yet, empirically observed neuronal synchrony in invasive recordings indicates that it is not uncommon to find zero or close-to-zero phase lag between the activity profiles of coupled neuronal assemblies. Here, we introduce a novel method that allows us to mitigate the undesired spatial leakage effects and detect zero and near zero phase interactions. To this end, we propose a projection operation that operates on sensor-space cross-spectrum and suppresses the spatial leakage contribution but retains the true zero-phase interaction component. We then solve the network estimation task as a source estimation problem defined in the product space of interacting source topographies. We show how this framework provides reliable interaction detection for all phase-lag values and we thus refer to the method as Phase Shift Invariant Imaging of Coherent Sources (PSIICOS). Realistic simulations demonstrate that PSIICOS has better detector characteristics than existing interaction metrics. Finally, we illustrate the performance of PSIICOS by applying it to real MEG dataset recorded during a standard mental rotation task. Taken together, using analytical derivations, data simulations and real brain data, this study presents a novel source-space MEG/EEG connectivity method that overcomes previous limitations and for the first time allows for the estimation of true zero-phase coupling via non-invasive electrophysiological recordings. |
| Databáze: | OpenAIRE |
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