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Monitoring spike train synchrony
- Source :
- Journal of neurophysiology 109 (2013): 1457–1472. doi:10.1152/jn.00873.2012, info:cnr-pdr/source/autori:Thomas Kreuz (1); Daniel Chicharro (2); Conor Houghton (3); Ralph G. Andrzejak (4); Florian Mormann (5)/titolo:Monitoring spike train synchrony/doi:10.1152%2Fjn.00873.2012/rivista:Journal of neurophysiology/anno:2013/pagina_da:1457/pagina_a:1472/intervallo_pagine:1457–1472/volume:109
- Publication Year :
- 2012
- Publisher :
- arXiv, 2012.
-
Abstract
- Recently, the SPIKE-distance has been proposed as a parameter-free and time-scale independent measure of spike train synchrony. This measure is time-resolved since it relies on instantaneous estimates of spike train dissimilarity. However, its original definition led to spuriously high instantaneous values for event-like firing patterns. Here we present a substantial improvement of this measure which eliminates this shortcoming. The reliability gained allows us to track changes in instantaneous clustering, i.e., time-localized patterns of (dis)similarity among multiple spike trains. Additional new features include selective and triggered temporal averaging as well as the instantaneous comparison of spike train groups. In a second step, a causal SPIKE-distance is defined such that the instantaneous values of dissimilarity rely on past information only so that time-resolved spike train synchrony can be estimated in real-time. We demonstrate that these methods are capable of extracting valuable information from field data by monitoring the synchrony between neuronal spike trains during an epileptic seizure. Finally, the applicability of both the regular and the real-time SPIKE-distance to continuous data is illustrated on model electroencephalographic (EEG) recordings.<br />Comment: 16 pages, 10 figures, 35 references; 1 supplementary figure, 1 supplementary movie (see author's webpage http://www.fi.isc.cnr.it/users/thomas.kreuz/sourcecode.html)
- Subjects :
- FOS: Computer and information sciences
Time Factors
Physiology
Computer science
Spike train
Electroencephalography Phase Synchronization
Action Potentials
Electroencephalography
Synchronization
0302 clinical medicine
Spike trains
0303 health sciences
medicine.diagnostic_test
General Neuroscience
Brain
SPIKEdistance
Electrophysiology
Biological Physics (physics.bio-ph)
Train
Spike (software development)
Neurons and Cognition (q-bio.NC)
Data analysis
FOS: Physical sciences
Measure (mathematics)
Clustering
Methodology (stat.ME)
03 medical and health sciences
Seizures
medicine
Animals
Humans
Physics - Biological Physics
Cluster analysis
Statistics - Methodology
030304 developmental biology
Communication
Epilepsy
Quantitative Biology::Neurons and Cognition
business.industry
Pattern recognition
Physics - Medical Physics
Physics - Data Analysis, Statistics and Probability
Quantitative Biology - Neurons and Cognition
FOS: Biological sciences
Artificial intelligence
Medical Physics (physics.med-ph)
business
030217 neurology & neurosurgery
Data Analysis, Statistics and Probability (physics.data-an)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Journal of neurophysiology 109 (2013): 1457–1472. doi:10.1152/jn.00873.2012, info:cnr-pdr/source/autori:Thomas Kreuz (1); Daniel Chicharro (2); Conor Houghton (3); Ralph G. Andrzejak (4); Florian Mormann (5)/titolo:Monitoring spike train synchrony/doi:10.1152%2Fjn.00873.2012/rivista:Journal of neurophysiology/anno:2013/pagina_da:1457/pagina_a:1472/intervallo_pagine:1457–1472/volume:109
- Accession number :
- edsair.doi.dedup.....6177e396ff99bec3e7049fb25cfb4490
- Full Text :
- https://doi.org/10.48550/arxiv.1209.6604