Non-linear canonical correlation for joint analysis of MEG signals from two subjects

 |  Login

Show simple item record

dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Campi, Cristina Parkkonen, Lauri Hari, Riitta Hyvärinen, Aapo 2017-05-11T07:29:54Z 2017-05-11T07:29:54Z 2013
dc.identifier.citation Campi , C , Parkkonen , L , Hari , R & Hyvärinen , A 2013 , ' Non-linear canonical correlation for joint analysis of MEG signals from two subjects ' FRONTIERS IN NEUROSCIENCE , vol 7 , 107 , pp. 1-7 . DOI: 10.3389/fnins.2013.00107 en
dc.identifier.issn 1662-4548
dc.identifier.other PURE UUID: 5d3fe33f-c036-4199-9b07-96cd8fc7b50e
dc.identifier.other PURE ITEMURL:
dc.identifier.other PURE LINK:
dc.identifier.other PURE FILEURL:
dc.description.abstract Traditional stimulus-based analysis methods of magnetoencephalography (MEG) data are often dissatisfactory when applied to naturalistic experiments where two or more subjects are measured either simultaneously or sequentially. To uncover the commonalities in the brain activity of the two subjects, we propose a method that searches for linear transformations that output maximally correlated signals between the two brains. Our method is based on canonical correlation analysis (CCA), which provides linear transformations, one for each subject, such that the temporal correlation between the transformed MEG signals is maximized. Here, we present a non-linear version of CCA which measures the correlation of energies and allows for a variable delay between the time series to accommodate, e.g., leader–follower changes. We test the method with simulations and with MEG data from subjects who received the same naturalistic stimulus sequence. The method may help analyse future experiments where the two subjects are measured simultaneously while engaged in social interaction. en
dc.format.extent 1-7
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries FRONTIERS IN NEUROSCIENCE en
dc.relation.ispartofseries Volume 7 en
dc.rights openAccess en
dc.subject.other 114 Physical sciences en
dc.subject.other 221 Nanotechnology en
dc.subject.other 214 Mechanical engineering en
dc.subject.other 218 Environmental engineering en
dc.title Non-linear canonical correlation for joint analysis of MEG signals from two subjects en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Neuroscience and Biomedical Engineering en
dc.subject.keyword canonical correlation anaysis (CCA)
dc.subject.keyword non-linear CCA
dc.subject.keyword magnetoencephalography (MEG)
dc.subject.keyword social interaction
dc.subject.keyword brain signal processing
dc.subject.keyword 114 Physical sciences
dc.subject.keyword 221 Nanotechnology
dc.subject.keyword 214 Mechanical engineering
dc.subject.keyword 218 Environmental engineering
dc.identifier.urn URN:NBN:fi:aalto-201705113922
dc.identifier.doi 10.3389/fnins.2013.00107
dc.type.version publishedVersion

Files in this item

Files Size Format View

There are no open access files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search archive

Advanced Search

article-iconSubmit a publication