publication . Article . 2016

On the estimation of brain signal entropy from sparse neuroimaging data.

Grandy, T.; Garrett, D.; Schmiedek, F.; Werkle-Bergner, M.;
Open Access English
  • Published: 29 Mar 2016
  • Country: Germany
Multi-scale entropy (MSE) has been recently established as a promising tool for the analysis of the moment-to-moment variability of neural signals. Appealingly, MSE provides a measure of the predictability of neural operations across the multiple time scales on which the brain operates. An important limitation in the application of the MSE to some classes of neural signals is MSE’s apparent reliance on long time series. However, this sparse-data limitation in MSE computation could potentially be overcome via MSE estimation across shorter time series that are not necessarily acquired continuously (e.g., in fMRI block-designs). In the present study, using simulate...
free text keywords: ddc:150, Multidisciplinary, Data point, Accuracy and precision, Neuroimaging, Pattern recognition, Predictability, Electroencephalography, medicine.diagnostic_test, medicine, Cognitive neuroscience, Computer science, Artificial intelligence, business.industry, business, Computation, Neurophysiology, Article
45 references, page 1 of 3

Garrett D. al.Moment-to-moment brain signal variability: A next frontier in human brain mapping?Neurosci. Biobehav. Rev.37, 610–624; doi: 10.1016/j.neubiorev.2013.02.015 (2013).23458776 [OpenAIRE] [PubMed] [DOI]

Deco G., Jirsa V. K. & McIntosh A. R. Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat. Rev. Neurosci. 12, 43–56; doi: 10.1038/nrn2961 (2011).21170073 [OpenAIRE] [PubMed] [DOI]

Costa M., Goldberger A. L. & Peng C. K. Multiscale entropy analysis of complex physiologic time series. Phys. Rev. Lett. 89, 068102; doi: 10.1103/PhysRevLett.89.068102 (2002).12190613 [PubMed] [DOI]

Costa M., Goldberger A. L. & Peng C. K. Multiscale entropy analysis of biological signals. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71, 021906; doi: 10.1103/PhysRevE.71.021906 (2005).15783351 [PubMed] [DOI]

Richman J. S. & Moorman J. R. Physiological time-series analysis using approximate and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278, H2039–H2049 (2000).10843903 [OpenAIRE] [PubMed]

Heisz J. J., Shedden J. M. & McIntosh A. R. Relating brain signal variability to knowledge representation. Neuroimage 63, 1384–1392; doi: 10.1016/j.neuroimage.2012.08.018 (2012).22906786 [OpenAIRE] [PubMed] [DOI]

McDonough I. M. & Nashiro K. Network complexity as a measure of informat ion processing across resting-state networks: evidence from the Human Connectome Project. Front. Hum. Neurosci. 8; doi: 10.3389/fnhum.2014.00409 (2014). [OpenAIRE] [DOI]

McIntosh A. R., Kovacevic N. & Itier R. J. Increased brain signal variability accompanies lower behavioral variability in development. PLoS Comput. Biol. 4, e1000106; doi: 10.1371/journal.pcbi.1000106 (2008).18604265 [OpenAIRE] [PubMed] [DOI]

McIntosh A. al.Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability. Cereb. Cortex 24, 1806–1817; doi: 10.1093/cercor/bht030 (2014).23395850 [OpenAIRE] [PubMed] [DOI]

Yang A. al.Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis. Neurobiol. Aging 34, 428–438; doi: 10.1016/j.neurobiolaging.2012.05.004 (2013).22683008 [OpenAIRE] [PubMed] [DOI]

MišićB., Mills T., Taylor M. J. & McIntosh A. R. Brain Noise Is Task Dependent and Region Specific. J. Neurophysiol. 104, 2667–2676; doi: 10.1152/jn.00648.2010 (2010).20844116 [OpenAIRE] [PubMed] [DOI]

MišićB., Vakorin V. A., Paus T. & McIntosh A. R. Functional embedding predicts the variability of neural activity. Front. Hum. Neurosci. 5; doi: 10.3389/fnsys.2011.00090 (2011). [OpenAIRE] [DOI]

Buzsáki G.Rhythms of the Brain. (Oxford University Press, 2006).

Buzsáki G. & Draguhn A. Neuronal oscillations in cortical networks. Science 304, 1926–1929; doi: 10.1126/science.1099745 (2004).15218136 [OpenAIRE] [PubMed] [DOI]

Pincus S. M. & Goldberger A. L. Physiological time-series analysis: What does regularity quantify? Am. J. Physiol. Heart Circ. Physiol. 266, H1643–H1656 (1994). [OpenAIRE]

45 references, page 1 of 3
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