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InVivoR Package

Features

This package was developed to analyse electrophysiological data such as field potentials and unit activity. Features include:

  • loading .dat files and processing traces (filtering etc.)
  • extraction of event snippets from trace (ERPs)
  • Morlet wavelet transformation
  • Phase analysis of ERPs
  • Modulation-Index calculation for field potentials
  • Auto/Cross-Correlogram for unit activity
  • and more

Easy to use

Traces can be easily processed and analysed with only a few functions required. To analyse ERPs we can extract trace snippets using the ERPMat() function and later apply Morlet wavelet transforms.

To illustrate we can simply simulate several traces with different frequency components and write them to a matrix as ERPMat would do as well. Firstly we load the package and data.table and ggplot2 to further plot the data.

library(InVivoR)
library(data.table)
library(ggplot2)
trace <- sapply(X = 1:20, FUN = function(x){
  shiftOnset <- runif(n = 1, min = 0, max = pi)
  TraceOut <- sin(40*pi*seq(0,5,0.001))+sin(20*pi*seq(0,5,0.001))+sin(4*pi*seq(0,5,0.001))
  for(i in 1:40) {
    shiftOnset <- runif(n = 1, min = 0, max = pi)
    TraceOut <- TraceOut + 0.2*sin(runif(n = 1, min = 0.1, max = 100)*pi*seq(0+shiftOnset,5+shiftOnset,0.001))
  }
  TraceOut
  })

We can then provide the function WTbatch with the trace matrix and the frequencies we want to analyse. The package is also supports multiple cores which we can define as well.

Frequencies <- seq(0.1,40,0.1)
WaveletTransform <- WTbatch(ERPMat = t(trace), frequencies = Frequencies, SamplingRate = 1e3, CORES = 4, PhaseAnalysis = T, sigma = 6)
## finished ERP

PowerMat <- abs(WaveletTransform$Raw)^2
rownames(PowerMat) <- seq(0,5,0.001)
colnames(PowerMat) <- Frequencies

The function analyses all ERP snippets in one run and outputs a list with the transforms. However, it can also be specified to collapse all ERPs to an average to save memory. In practice we would like to average over several trials and see the average response to isolate the signal. This can be implemented manually or by using the

PowerAvg <- PowerMat(x = abs(WaveletTransform$Raw)^2)
rownames(PowerAvg) <- seq(0,5,0.001)
colnames(PowerAvg) <- Frequencies
## Warning in data.table::melt(PowerAvg): The melt generic in data.table has
## been passed a matrix and will attempt to redirect to the relevant reshape2
## method; please note that reshape2 is deprecated, and this redirection is now
## deprecated as well. To continue using melt methods from reshape2 while both
## libraries are attached, e.g. melt.list, you can prepend the namespace like
## reshape2::melt(PowerAvg). In the next version, this warning will become an
## error.