A tutorial review of functional connectivity analysis methods and their interpretational pitfalls
Oscillatory neuronal activity may provide a mechanism for dynamic network coordination. Rhythmic neuronal interactions can be quantified using multiple metrics, each with their own advantages and disadvantages. This tutorial will review and summarize current analysis methods used in the field of inv...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-01-01
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| Series: | Frontiers in Systems Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnsys.2015.00175/full |
| _version_ | 1818766546707677184 |
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| author | Andre M Bastos Jan-Mathijs eSchoffelen Jan-Mathijs eSchoffelen |
| author_facet | Andre M Bastos Jan-Mathijs eSchoffelen Jan-Mathijs eSchoffelen |
| author_sort | Andre M Bastos |
| collection | DOAJ |
| description | Oscillatory neuronal activity may provide a mechanism for dynamic network coordination. Rhythmic neuronal interactions can be quantified using multiple metrics, each with their own advantages and disadvantages. This tutorial will review and summarize current analysis methods used in the field of invasive and non-invasive electrophysiology to study the dynamic connections between neuronal populations. First, we review metrics for functional connectivity, including coherence, phase synchronization, phase-slope index, and Granger causality, with the specific aim to provide an intuition for how these metrics work, as well as their quantitative definition. Next, we highlight a number of interpretational caveats and common pitfalls that can arise when performing functional connectivity analysis, including the common reference problem, the signal to noise ratio problem, the volume conduction problem, the common input problem, and the trial sample size bias problem. These pitfalls will be illustrated by presenting a set of MATLAB-scripts, which can be executed by the reader to simulate each of these potential problems. We discuss of how these issues can be addressed using current methods. |
| first_indexed | 2024-12-18T08:35:43Z |
| format | Article |
| id | doaj.art-348d125c98464edb8af5384253bcff3d |
| institution | Directory Open Access Journal |
| issn | 1662-5137 |
| language | English |
| last_indexed | 2024-12-18T08:35:43Z |
| publishDate | 2016-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Systems Neuroscience |
| spelling | doaj.art-348d125c98464edb8af5384253bcff3d2022-12-21T21:14:19ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372016-01-01910.3389/fnsys.2015.00175165147A tutorial review of functional connectivity analysis methods and their interpretational pitfallsAndre M Bastos0Jan-Mathijs eSchoffelen1Jan-Mathijs eSchoffelen2MITMax Planck Institute for PsycholinguisticsDonders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenOscillatory neuronal activity may provide a mechanism for dynamic network coordination. Rhythmic neuronal interactions can be quantified using multiple metrics, each with their own advantages and disadvantages. This tutorial will review and summarize current analysis methods used in the field of invasive and non-invasive electrophysiology to study the dynamic connections between neuronal populations. First, we review metrics for functional connectivity, including coherence, phase synchronization, phase-slope index, and Granger causality, with the specific aim to provide an intuition for how these metrics work, as well as their quantitative definition. Next, we highlight a number of interpretational caveats and common pitfalls that can arise when performing functional connectivity analysis, including the common reference problem, the signal to noise ratio problem, the volume conduction problem, the common input problem, and the trial sample size bias problem. These pitfalls will be illustrated by presenting a set of MATLAB-scripts, which can be executed by the reader to simulate each of these potential problems. We discuss of how these issues can be addressed using current methods.http://journal.frontiersin.org/Journal/10.3389/fnsys.2015.00175/fullElectrophysiologyoscillationsGranger causalityphase synchronizationcoherence analysisfunctional connectivity (FC) |
| spellingShingle | Andre M Bastos Jan-Mathijs eSchoffelen Jan-Mathijs eSchoffelen A tutorial review of functional connectivity analysis methods and their interpretational pitfalls Frontiers in Systems Neuroscience Electrophysiology oscillations Granger causality phase synchronization coherence analysis functional connectivity (FC) |
| title | A tutorial review of functional connectivity analysis methods and their interpretational pitfalls |
| title_full | A tutorial review of functional connectivity analysis methods and their interpretational pitfalls |
| title_fullStr | A tutorial review of functional connectivity analysis methods and their interpretational pitfalls |
| title_full_unstemmed | A tutorial review of functional connectivity analysis methods and their interpretational pitfalls |
| title_short | A tutorial review of functional connectivity analysis methods and their interpretational pitfalls |
| title_sort | tutorial review of functional connectivity analysis methods and their interpretational pitfalls |
| topic | Electrophysiology oscillations Granger causality phase synchronization coherence analysis functional connectivity (FC) |
| url | http://journal.frontiersin.org/Journal/10.3389/fnsys.2015.00175/full |
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