A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation

A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation

Fractal analysis of spontaneous cord dorsum potentials (CDPs) generated in the lumbosacral spinal segments has revealed that these potentials are generated by ongoing structured (non-random) neuronal activity. Studies aimed to disclose the changes produced by nociceptive stimulation on the funct...

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Bibliographic Details
Main Authors: Mario eMartin, Enrique eContreras-Hernàndez, Javier eBéjar, Gennaro eEsposito, Diógenes eChávez, Silvio eGlusman, Ulises eCortés, Pablo eRudomin
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-08-01
Series:Frontiers in Neuroinformatics
Subjects:
data analysis
spontaneous neuronal activity
Neural Signals Processing
Discovery and classification
Cord Dorsum Potentials
Online Access:http://journal.frontiersin.org/Journal/10.3389/fninf.2015.00021/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fninf.2015.00021/full

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