Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists
NeuroImage, vol. 216, pp. 116745
Abstract
The 21st century marks the emergence of "big data" with a rapid increase in the availability of datasets with multiple measurements. In neuroscience, brain-imaging datasets are more commonly accompanied by dozens or hundreds of phenotypic subject descriptors on the behavioral, neural, and genomic level. The complexity of such "big data" repositories offer new opportunities and pose new challenges for systems neuroscience. Canonical correlation analysis (CCA) is a prototypical family of methods that is useful in identifying the links between variable sets from different modalities. Importantly, CCA is well suited to describing relationships across multiple sets of data, such as in recently available big biomedical datasets. Our primer discusses the rationale, promises, and pitfalls of CCA.
Authors 7
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Hao-Ting Wang corresponding
University of Sussex · University of York
Affiliation as printed
Department of Psychology, University of York, Heslington, York, United Kingdom; Sackler Center for Consciousness Science, University of Sussex, Brighton, United Kingdom. Electronic address: H.Wang@bsms.ac.uk
Department of Psychology, University of York, Heslington, York, United Kingdom
Sackler Center for Consciousness Science, University of Sussex, Brighton, United Kingdom
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Affiliation as printed
Department of Psychology, University of York, Heslington, York, United Kingdom
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Affiliation as printed
Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
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Affiliation as printed
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Affiliation as printed
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Affiliation as printed
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Physics & Astronomy, School of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
Department of Physics & Astronomy, School of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Danilo Bzdok corresponding Aachen Department of Psychiatry, Psychotherapy and Psychosomatics JARA-BRAIN
Montreal Neurological Institute and Hospital · Institut national de recherche en sciences et technologies du numérique · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Jülich Aachen Research Alliance · Mila - Quebec Artificial Intelligence Institute · McGill University · RWTH Aachen University
Affiliation as printed
Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany; JARA-BRAIN, Jülich-Aachen Research Alliance, Germany; Parietal Team, INRIA, Neurospin, Bat 145, CEA Saclay, 91191, Gif-sur-Yvette, France; Department of Biomedical Engineering, Montreal Neurological Institute, Faculty of Medicine, McGill University, Montreal, Canada; Mila - Quebec Artificial Intelligence Institute, Canada. Electronic address: danilo.bzdok@mcgill.ca
Department of Biomedical Engineering, Montreal Neurological Institute, Faculty of Medicine, McGill University, Montreal, Canada
Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany
JARA-BRAIN, Jülich-Aachen Research Alliance, Germany
Mila - Quebec Artificial Intelligence Institute, Canada
Parietal Team, INRIA, Neurospin, Bat 145, CEA Saclay, 91191, Gif-sur-Yvette, France
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