Evaluating phase synchronization methods in fMRI: a comparison study and new approaches

Autor: Hamed Honari, Ann S. Choe, Martin A. Lindquist
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Signal Processing (eess.SP)
FOS: Computer and information sciences
Computer Science - Machine Learning
Computer science
Synchronization
Machine Learning (cs.LG)
Functional connectivity
0302 clinical medicine
Sliding window protocol
Synchronization (computer science)
Image Processing
Computer-Assisted
Cortical Synchronization
Circular statistics
Brain Mapping
Time-varying phase synchronization
05 social sciences
Brain
Magnetic Resonance Imaging
Neurology
Metric (mathematics)
Instantaneous phase synchronization
Phase synchronization detection
Cognitive Neuroscience
Models
Neurological
Instantaneous phase
Statistics - Applications
Article
050105 experimental psychology
Hilbert–Huang transform
lcsh:RC321-571
Methodology (stat.ME)
03 medical and health sciences
FOS: Electrical engineering
electronic engineering
information engineering
Humans
Computer Simulation
Applications (stat.AP)
0501 psychology and cognitive sciences
Resting-state fMRI
Electrical Engineering and Systems Science - Signal Processing
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Statistics - Methodology
Resting state fMRI
business.industry
Pattern recognition
Filter (signal processing)
Phase synchronization
Artificial intelligence
Relative phase
business
030217 neurology & neurosurgery
Zdroj: NeuroImage, Vol 228, Iss, Pp 117704-(2021)
NeuroImage
Popis: In recent years there has been growing interest in measuring time-varying functional connectivity between different brain regions using resting-state functional magnetic resonance imaging (rs-fMRI) data. One way to assess the relationship between signals from different brain regions is to measure their phase synchronization (PS) across time. There are several ways to perform such analyses, and we compare methods that utilize a PS metric together with a sliding window, referred to here as windowed phase synchronization (WPS), with those that directly measure the instantaneous phase synchronization (IPS). In particular, IPS has recently gained popularity as it offers single time-point resolution of time-resolved fMRI connectivity. In this paper, we discuss the underlying assumptions required for performing PS analyses and emphasize the importance of band-pass filtering the data to obtain valid results. Further, we contrast this approach with the use of Empirical Mode Decomposition (EMD) to achieve similar goals. We review various methods for evaluating PS and introduce a new approach within the IPS framework denoted the cosine of the relative phase (CRP). We contrast methods through a series of simulations and application to rs-fMRI data. Our results indicate that CRP outperforms other tested methods and overcomes issues related to undetected temporal transitions from positive to negative associations common in IPS analysis. Further, in contrast to phase coherence, CRP unfolds the distribution of PS measures, which benefits subsequent clustering of PS matrices into recurring brain states.
Databáze: OpenAIRE
Externí odkaz: