Barayeu_2023_IScience/README.md

P-unit data in nixio format for the paper 'Beat encoding at mistuned octaves within single electrosensory neurons'

Summary

We provide electrophysiological datasets of primary sensory afferents (P-Units) of the Apteronotus leptorhynchus (Barayeu et al., 2023). The datasets contain intracellular recordings sampled at 40 kHz. It also includes the timing of stimulus-related events recorded along with the electrophysiological data. The datasets also provide the metadata structured in a nixio format. The datasets address contain information and can be analysed with the questions in mind: How are beats at high difference frequencies encoded in the electrosensory system in primary sensory afferents?

Repository structure

The repository contains the P-unit data sets. They are provided in the nixio format (.nix).

Example code to load the data of a cell:

• import the nixo package

  import nixio as nix
  from matplotlib import pyplot as plt
  import numpy as np
  

• load cell (works if you are in the cell folder)

  file = nix.File.open('2019-05-07-aq-invivo-1.nix', nix.FileMode.ReadOnly)
  b = file.blocks[0]
  

• choice of a beat multi_tag

  mt_nr = 1
  mt = b.multi_tags[mt_nr]
  

• load the array of interest: here the EOD of the fish and the spike times

  EOD = b.data_arrays['LocalEOD-1']
  spikes_all = b.data_arrays['Spikes-1']
  voltage = b.data_arrays['V-1']
  

• slice the whole data array at the bignning and the extend of the multitag

  eod = EOD.get_slice([mt.positions[:][mt_nr]], [mt.extents[:][mt_nr]], nix.DataSliceMode.Data)[:]
  spikes = spikes_all.get_slice([mt.positions[:][mt_nr]], [mt.extents[:][mt_nr]], nix.DataSliceMode.Data)[:] - mt.positions[:][mt_nr]
  volt = voltage.get_slice([mt.positions[:][mt_nr]], [mt.extents[:][mt_nr]], nix.DataSliceMode.Data)[:]
  

• get the sampling

  sampling = len(EOD.get_slice([0], [0.1], nix.DataSliceMode.Data)[:]) * 10
  

• get the time array

  time_array = np.arange(0, mt.extents[:][mt_nr], 1 / sampling)
  

• example plot of a beat and the P-unit response

  fig, ax = plt.subplots(2, 1, sharex = True)
  ax[0].set_ylabel('mV')
  ax[0].plot(time_array, eod)
  ax[1].plot(time_array, volt)
  ax[1].set_ylabel('mV')
  ax[1].set_xlabel('Time [s]')
  ax[1].set_xlim(0,0.1)
  ax[1].scatter(spikes, np.ones(len(spikes))*np.max(volt))
  plt.show()
  

See https://nixio.readthedocs.io/en/latest/getting_started.html#tutorials for more documentation examples.