Literature DB >> 25599264

Detecting Functional Connectivity During Audiovisual Integration with MEG: A Comparison of Connectivity Metrics.

Tyler Ard1,2, Frederick W Carver1, Tom Holroyd1, Barry Horwitz3, Richard Coppola1.   

Abstract

In typical magnetoencephalography and/or electroencephalography functional connectivity analysis, researchers select one of several methods that measure a relationship between regions to determine connectivity, such as coherence, power correlations, and others. However, it is largely unknown if some are more suited than others for various types of investigations. In this study, the authors investigate seven connectivity metrics to evaluate which, if any, are sensitive to audiovisual integration by contrasting connectivity when tracking an audiovisual object versus connectivity when tracking a visual object uncorrelated with the auditory stimulus. The authors are able to assess the metrics' performances at detecting audiovisual integration by investigating connectivity between auditory and visual areas. Critically, the authors perform their investigation on a whole-cortex all-to-all mapping, avoiding confounds introduced in seed selection. The authors find that amplitude-based connectivity measures in the beta band detect strong connections between visual and auditory areas during audiovisual integration, specifically between V4/V5 and auditory cortices in the right hemisphere. Conversely, phase-based connectivity measures in the beta band as well as phase and power measures in alpha, gamma, and theta do not show connectivity between audiovisual areas. The authors postulate that while beta power correlations detect audiovisual integration in the current experimental context, it may not always be the best measure to detect connectivity. Instead, it is likely that the brain utilizes a variety of mechanisms in neuronal communication that may produce differential types of temporal relationships.

Entities:  

Keywords:  MEG; all-to-all; audiovisual integration; beta; coherence; functional connectivity; multimodal; oscillation

Mesh:

Year:  2015        PMID: 25599264      PMCID: PMC4533088          DOI: 10.1089/brain.2014.0296

Source DB:  PubMed          Journal:  Brain Connect        ISSN: 2158-0014


  37 in total

Review 1.  Spectral fingerprints of large-scale neuronal interactions.

Authors:  Markus Siegel; Tobias H Donner; Andreas K Engel
Journal:  Nat Rev Neurosci       Date:  2012-01-11       Impact factor: 34.870

Review 2.  Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs.

Authors:  Satu Palva; J Matias Palva
Journal:  Trends Cogn Sci       Date:  2012-03-20       Impact factor: 20.229

3.  Estimating complex cortical networks via surface recordings- a critical note.

Authors:  Lucas Antiqueira; Francisco A Rodrigues; Bernadette C M van Wijk; Luciano da F Costa; Andreas Daffertshofer
Journal:  Neuroimage       Date:  2010-06-11       Impact factor: 6.556

Review 4.  Multisensory processing in review: from physiology to behaviour.

Authors:  David Alais; Fiona N Newell; Pascal Mamassian
Journal:  Seeing Perceiving       Date:  2010

5.  Multisensory integration of dynamic faces and voices in rhesus monkey auditory cortex.

Authors:  Asif A Ghazanfar; Joost X Maier; Kari L Hoffman; Nikos K Logothetis
Journal:  J Neurosci       Date:  2005-05-18       Impact factor: 6.167

Review 6.  The relationship between spatial attention and saccades in the frontoparietal network of the monkey.

Authors:  Claire Wardak; Etienne Olivier; Jean-René Duhamel
Journal:  Eur J Neurosci       Date:  2011-06       Impact factor: 3.386

7.  Oscillatory synchronization in large-scale cortical networks predicts perception.

Authors:  Joerg F Hipp; Andreas K Engel; Markus Siegel
Journal:  Neuron       Date:  2011-01-27       Impact factor: 17.173

8.  Audiovisual synchrony enhances BOLD responses in a brain network including multisensory STS while also enhancing target-detection performance for both modalities.

Authors:  Jennifer L Marchant; Christian C Ruff; Jon Driver
Journal:  Hum Brain Mapp       Date:  2011-09-23       Impact factor: 5.038

9.  Measuring functional connectivity using MEG: methodology and comparison with fcMRI.

Authors:  Matthew J Brookes; Joanne R Hale; Johanna M Zumer; Claire M Stevenson; Susan T Francis; Gareth R Barnes; Julia P Owen; Peter G Morris; Srikantan S Nagarajan
Journal:  Neuroimage       Date:  2011-02-23       Impact factor: 6.556

10.  Good practice for conducting and reporting MEG research.

Authors:  Joachim Gross; Sylvain Baillet; Gareth R Barnes; Richard N Henson; Arjan Hillebrand; Ole Jensen; Karim Jerbi; Vladimir Litvak; Burkhard Maess; Robert Oostenveld; Lauri Parkkonen; Jason R Taylor; Virginie van Wassenhove; Michael Wibral; Jan-Mathijs Schoffelen
Journal:  Neuroimage       Date:  2012-10-06       Impact factor: 6.556

View more
  1 in total

1.  Permutation Statistics for Connectivity Analysis between Regions of Interest in EEG and MEG Data.

Authors:  Fahimeh Mamashli; Matti Hämäläinen; Jyrki Ahveninen; Tal Kenet; Sheraz Khan
Journal:  Sci Rep       Date:  2019-05-28       Impact factor: 4.379

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.