Sample Entropy (SampEn) method (Neymotin et al. 2010)

Accession:137995
"... To determine the complexity of the EEG time series, we calculated the sample entropy (SampEn) .... SampEn is the negative natural logarithm of an estimate of the conditional probability that subseries (epochs) of length m-1 that match pointwise within a tolerance r also match at the mth point. ..."
Tool Information (Click on a link to find other Tools with that property)
Tool Type: Analysis; Statistics;
Simulation Environment: NEURON;
\
sampendemo
readme.txt
misc.mod
sampen.mod
vecst.mod
mosinit.hoc
misc.h
                            
NEURON Sample Entropy demo readme

"Sample Entropy is the negative natural logarithm of an estimate of
the conditional probability that subseries (epochs) of length m that
match pointwise within a tolerance r also match at the next point."

Files:
 sampen.mod - has the Sample Entropy (SampEn) Vector function, vsampen
 vecst.mod, misc.mod, misc.h - support code
 mosinit.hoc - sets up hoc GUI and starts demo

To compile:
 nrnivmodl *.mod

This should generate an architecture-specific directory containing
"special", a script to start NEURON and load the compiled-in
libraries. For example, on x86 64-bit systems, it will make x86_64
directory containing "special"

Then, to run :
 x86_64/special
that will start NEURON
To start the demo, use this command from the NEURON prompt:
 load_file("mosinit.hoc")
mosinit.hoc calls vsampen using its default parameters.

Note that mosinit.hoc calls install_sampen() in the beginning, to make
sure the Vector function, vsampen is available to NEURON.

vsampen Usage:
  Vec.vsampen([epoch length,error tolerance,normalize input,compute
  stdev,output vector])
Vec is a Vector with time-series data
all arguments to vsampen are optional 
epoch length: the number of points to use to match subseries, default:2
error tolerance: the factor * standard deviation of vector to use to
  consider points in subseries a match, default:0.2
normalize: sets Vector to have mean of 0 and standard deviation of 1
  before running sample entropy, default:0
compute stdev:- estimates standard deviation of Sample Entropy
  measure, default:0
output vector: should have size of 2 and stores SampEn and estimate of
  standard-deviation, default:empty
vsampen returns the sample entropy value, which should be >=0. returns
-1 on failure

The code in sampen.mod was used in:
 Interictal {EEG} Discoordination in a Rat Seizure Model by Neymotin,
 SA and Lee, H and Fenton, AA and Lytton, WW Journal of Clinical
 Neurophysiology 27(6):438-444, 2010.
The code in sampen.mod is a NEURON Vector function wrapper over code
written by Doug Lake. Original C code is available from
http://www.physionet.org/physiotools/sampen/
Sample Entropy was first described in:
 Physiological time-series analysis using approximate entropy and
 sample entropy by Richman, JS and Moorman, JR American Journal of
 Physiology- Heart and Circulatory Physiology 278(6):H2039--H2049,
 2000.

For questions/comments, email Sam Neymotin: samn at neurosim dot
  downstate dot edu