Dataset of cortical activity recorded with high spatial resolution from anesthetized rats (hdl:21.15109/ARP/0QRUQK)

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Part 1: Document Description
Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
Part 5: Other Study-Related Materials
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Dataset of cortical activity recorded with high spatial resolution from anesthetized rats

hdl:21.15109/ARP/0QRUQK

ARP

2021-07-19

3

Csaba, Horváth; Lili Fanni, Tóth; István, Ulbert; Fiáth, Richárd, 2021, "Dataset of cortical activity recorded with high spatial resolution from anesthetized rats", https://hdl.handle.net/21.15109/ARP/0QRUQK, ARP, V3, UNF:6:9YijdOOa6/UIjD4UOf8bhQ== [fileUNF]

Dataset of cortical activity recorded with high spatial resolution from anesthetized rats

hdl:21.15109/ARP/0QRUQK

https://doi.gin.g-node.org/10.12751/g-node.arf7ol/

Csaba, Horváth (Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary)

Lili Fanni, Tóth (Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary)

István, Ulbert (Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary)

Fiáth, Richárd (Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary)

2017-1.2.1-NKP-2017-00002

PD124175

PD134196

TUDFO/51757-1/2019-ITM

ARP

Fiáth, Richárd

Fiáth, Richárd

2021-07-08

https://hdl.handle.net/21.15109/ARP/0QRUQK

Medicine, Health and Life Sciences, Silicon probe, High density recording, High spatial resolution, Electrophysiology, Neurophysiology, Neural recording, Extracellular action potential, Single unit activity, Spike sorting, Slow oscillation, Slow wave activity, Ketamine/xylazine anesthesia, Neocortex, fakeDoiMigrationDone

Here, we present an electrophysiological dataset (~0.9 TB overall size) recorded from the neocortex of twenty rats anesthetized with ketamine/xylazine (<a href="https://doi.org/10.1038/s41597-021-00970-3">Horváth et al., 2021</a>). The wideband, spontaneous recordings (n = 109) were acquired with a single-shank silicon-based probe having 128 densely packed recording sites arranged in a 32x4 array (<a href="https://doi.org/10.1016/j.bios.2018.01.060">Fiáth et al., 2018</a>). The dataset contains the activity of a total of 7126 sorted single units extracted from all layers of the cortex. Here, we share raw neural recordings, as well as spike times, extracellular spike waveforms and several properties of units packaged in a standardized electrophysiological data format. For technical validation of our dataset, we provide the distributions of derived single unit properties along with various spike sorting quality metrics.

high-density electrophysiological recordings

experimental data

<h3>Repository structure</h3> <p>Each recording and corresponding metadata, single unit properties and quality metrics were packaged in the <a href="https://www.nwb.org/">Neurodata Without Borders: Neurophysiology version 2.0 (NWB:N 2.0) data format</a> using the <a href="https://github.com/NeurodataWithoutBorders/matnwb/">MatNWB API</a>. A single NWB file was created from each recording. NWB files were placed in folders based on the identifier of the animal (from Rat01 to Rat20), probe insertion sequence (Insertion1 or Insertion2) and cortical depth (from Depth1 to Depth3). The filename of the NWB file (identifier) was constructed by concatenating the above information (e.g., Rat01_Insertion2_Depth3).</p> <p>The CSV file named "Animal_characteristics_and_targeted_cortical_areas" contains information about the weight and sex of animals, as well as about the cortical area and stereotaxic coordinates corresponding to each probe insertion. The "Recording_characteristics" CSV file lists several useful properties for each NWB file including the file size, the duration of the recording, the cortical location, the single unit yield, the average signal-to-noise ratio of single units, the degree of power line (50 Hz) noise contamination (given by the power spectral density value measured at 50 Hz, and also by the ratio of the power spectral density measured at 50 Hz to the power spectral density measured at 49 Hz), the RMS noise and RMS signal levels.</p> <br> <h3>NWB file structure</h3> <p>Each NWB file contains several main groups which are similar to directories. The <i>acquisition</i> group contains the continuous wideband 128-channel data (‘wideband_multichannel_recording’) in a compressed form, as well as several parameters related to the raw data such as the measurement unit or the data conversion number. The <i>general</i> group contains metadata about the experiments and consists of several subgroups, related to the recording probe (‘general/devices’; ‘general/extracellular_ephys’) or the subjects of the experiments (‘general/subject’). Former subgroups carry information about the probe location (brain area and stereotaxic coordinates) and the relative positions and laminar location of recordings sites, while the latter contains metadata about the animal (e.g., sex, species, subject ID, or weight). Information about spike sorting and single units and corresponding data are available in the <i>units</i> group. For each unit, we included here the mean and standard deviation of their spike waveform on all channels, calculated both from the filtered (‘mean_waveform_all_channels_filt’; ’waveform_sd_all_channels_filt’) and the wideband data (‘mean_waveform_all_channels_raw’; ’ waveform_sd_all_channels_raw’). For an easier visualization of the multichannel spike waveform in two dimensions, we have also added an array which contains the mean spike waveform in the 32 x 4 shape of the electrode array (‘mean_waveform_all_channels_filt_32x4’; ’mean_waveform_all_channels_raw_32x4’). Furthermore, the spike waveform recorded on the channel with the largest spike (i.e., peak waveform channel) was saved separately (‘mean_waveform_peak_channel_filt’, ‘mean_waveform_peak_channel_raw’). Several single unit properties and cluster quality metrics, as well as the spike times and spike count of each unit were saved in the <i>units</i> group. Furthermore, to aid users in selecting and analyzing a subset of this dataset appropriate for their research goals, we also created an NWB file (‘allSingleUnits.nwb’) which contains all single units with all the properties listed above, along with the identifier of the recording (‘units/session_id’) and the cortical area (‘units/cortical_area’) they originate from. The structure of NWB files can be explored using the <a href="https://www.hdfgroup.org/downloads/hdfview/">HDFView</a> software.<p> <br> <h3>Interacting with the NWB files</h3> <p>Users can import data from NWB files using the <a href="https://github.com/NeurodataWithoutBorders/pynwb/">PyNWB</a> and <a href="https://github.com/NeurodataWithoutBorders/matnwb/">MatNWB</a> APIs, or using <a href="https://github.com/SpikeInterface">SpikeInterface</a>. Loaded samples of the raw data have to be multiplied by a conversion number (0.195) to get the amplitudes in microvolts. Here we provide some examples how users can import data from NWB files using the MATLAB-based MatNWB API.</p> <br> Loading a short segment (20.000 samples corresponding to 1 second of data) of the raw wideband recording on all (128) channels: <br> <br> <code> 1. nwb = nwbRead('Rat01_Insertion1_Depth1.nwb'); </code> <br> <code> 2. dataChunk=nwb.acquisition.get('wideband_multichannel_recording').data.load([1, 1], [128, 20000]); </code> <br> <br> It is important to note that TimeSeries data types in NWB files are stored with time in the first dimension and channels in the second, but dimensions are reversed in MatNWB. <br> Loading and plotting the mean spike waveform of a specific single unit on the peak waveform channel: <br> <br> <code> 3. peakChannels = nwb.units.vectordata.get('peak_waveform_channel').data.load(); </code> <br> <code> 4. meanWaveforms = nwb.units.vectordata.get('mean_waveform_all_channels_filt').data.load(); </code> <br> <code> 5. mySingleUnit = 11; </code> <br> <code> 6. singleUnitWaveform = meanWaveforms(peakChannels(mySingleUnit), :, mySingleUnit); </code> <br> <code> 7. plot(singleUnitWaveform); </code> <br> <br> Loading the isolation distance quality metric of all units found in a single NWB file: <br> <br> <code> 8. IDvalues = nwb.units.vectordata.get('isolation_distance').data.load(); </code> <br> <br> Spike times are stored in a special structure called ragged arrays consisting of two vectors. The spike_times vector contains all spike times of all single units concatenated one after the other, while the spike_times_index vector stores where the spike times of individual single units are located in the spike_index vector (see also <a href="https://neurodatawithoutborders.github.io/matnwb/tutorials/html/ecephys.html#H_97F533F8">https://neurodatawithoutborders.github.io/matnwb/tutorials/html/ecephys.html#H_97F533F8</a>). <br> We can load the spikes times of a specific single unit (in seconds) the following way: <br> <br> <code> 9. allSpikeTimes = nwb.units.spike_times.data.load(); </code> <br> <code> 10. spikeTimesIndex = nwb.units.spike_times_index.data.load(); </code> <br> <code> 11. spikesOfSingleUnit2 = allSpikeTimes(spikeTimesIndex(1)+1 : spikeTimesIndex(2)); </code> <br> <br> SpikeInterface can also be used to load the wideband data and single unit properties (in Python, works only with version 0.13): <br> <br> <code> 1. import spikeextractors as se </code> <br> <code> 2. nwbPath = 'Rat01_Insertion1_Depth1.nwb' </code> <br> <code> 3. recording = se.NwbRecordingExtractor(nwbPath) </code> <br> <code> 4. sorting = se.NwbSortingExtractor(nwbPath) </code> <br> <code> 5. mySingleUnit = 2 </code> <br> <code> 6. sorting.get_unit_property(mySingleUnit,'isolation_distance') </code> <br> <br> The dataset is also available at the G-Node GIN repository under the following link and DOI:<br> <a href="https://gin.g-node.org/UlbertLab/High_Resolution_Cortical_Spikes">https://gin.g-node.org/UlbertLab/High_Resolution_Cortical_Spikes</a><br> <a href="https://doi.gin.g-node.org/10.12751/g-node.arf7ol/">https://doi.gin.g-node.org/10.12751/g-node.arf7ol/</a> <br><br> We also provide a Matlab script ("NWB_tutorial_script.m") which can be used to load, visualize and preprocess (e.g., filter) files in the dataset using MatNWB.

Fiáth R, Raducanu BC, Musa S, Andrei A, Lopez CM, van Hoof C, Ruther P, Aarts A, Horváth D, Ulbert I. A silicon-based neural probe with densely-packed low-impedance titanium nitride microelectrodes for ultrahigh-resolution in vivo recordings. (2018) BIOSENSORS & BIOELECTRONICS 106: 86-92. <a href="https://doi.org/10.1016/j.bios.2018.01.060">doi: 10.1016/j.bios.2018.01.060</a> <br><br> Horváth C, Tóth LF, Ulbert I, Fiáth R. Dataset of cortical activity recorded with high spatial resolution from anesthetized rat (2021) SCIENTIFIC DATA 8:180. <a href="https://doi.org/10.1038/s41597-021-00970-3">doi: 10.1038/s41597-021-00970-3</a>

10.1038/s41597-021-00970-3

Fiáth R, Raducanu BC, Musa S, Andrei A, Lopez CM, van Hoof C, Ruther P, Aarts A, Horváth D, Ulbert I. A silicon-based neural probe with densely-packed low-impedance titanium nitride microelectrodes for ultrahigh-resolution in vivo recordings. (2018) BIOSENSORS & BIOELECTRONICS 106: 86-92. <a href="https://doi.org/10.1016/j.bios.2018.01.060">doi: 10.1016/j.bios.2018.01.060</a> <br><br> Horváth C, Tóth LF, Ulbert I, Fiáth R. Dataset of cortical activity recorded with high spatial resolution from anesthetized rat (2021) SCIENTIFIC DATA 8:180. <a href="https://doi.org/10.1038/s41597-021-00970-3">doi: 10.1038/s41597-021-00970-3</a>

• Number of cases: 20

• No. of variables per record: 9

• Type of File: text/tab-separated-values

UNF:6:xZZKbMKOGQoqMsQ0rAwr5A==

• Number of cases: 109

• No. of variables per record: 10

• Type of File: text/tab-separated-values

UNF:6:TdSCBxj7yCmd36nx24Uy2Q==

• Animal ID - Animal ID
• Weight (g) - Weight (g)
• Sex - Sex
• Cortical Area (Insertion1) - Cortical Area (Insertion1)
• AP coordinate (Insertion1) - AP coordinate (Insertion1)
• ML coordinate (Insertion1) -  ML coordinate (Insertion1)
• Cortical Area (Insertion2) -  Cortical Area (Insertion2)
• AP coordinate (Insertion2) -  AP coordinate (Insertion2)
• ML coordinate (Insertion2) -  ML coordinate (Insertion2)
• NWB file name - NWB file name
• NWB file size (GB) - NWB file size (GB)
• Recording duration (min) - Recording duration (min)
• Cortical area - Cortical area
• Single unit yield - Single unit yield
• Average signal-to-noise ratio of single units - Average signal-to-noise ratio of single units
• Power spectral density at 50 Hz (dB/Hz) - Power spectral density at 50 Hz (dB/Hz)
• 50 Hz/49 Hz ratio - 50 Hz/49 Hz ratio
• RMS noise level (300 - 6000 Hz) - RMS noise level (300 - 6000 Hz)
• RMS signal level (300 - 6000 Hz) - RMS signal level (300 - 6000 Hz)

f376 Location:

Variable Format: character

Notes: UNF:6:B9UEOIlDI7dKqzOjS+3Kkw==

f376 Location:

Summary Statistics: StDev 59.60174847311639; Min. 200.0; Valid 20.0; Mean 315.5; Max. 400.0

Variable Format: numeric

Notes: UNF:6:3Wy26x1d95hwxdYqS7SqAw==

f376 Location:

Variable Format: character

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f376 Location:

Variable Format: character

Notes: UNF:6:RCpD1Vjx55675cmKfwPXmQ==

f376 Location:

Summary Statistics: Min. -3.6; Valid 20.0; Mean -2.871; StDev 0.4822087340124552; Max. -1.95

Variable Format: numeric

Notes: UNF:6:s+2qS7UwmmwnKu3SxkWXoQ==

f376 Location:

Summary Statistics: Mean 2.378; Valid 20.0; Max. 2.96; Min. 1.95; StDev 0.2576942292514011;

Variable Format: numeric

Notes: UNF:6:J/RVbGkABi+gKGRLaiTNug==

f376 Location:

Variable Format: character

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f376 Location:

Variable Format: character

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f376 Location:

Variable Format: character

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f377 Location:

Variable Format: character

Notes: UNF:6:n27AEH6FbWee1lOCWNmcwA==

f377 Location:

Summary Statistics: Valid 109.0; Max. 13.45; StDev 2.411134393222711; Min. 3.14; Mean 8.135779816513761;

Variable Format: numeric

Notes: UNF:6:RHhSY5IKUftEh/673CfRPQ==

f377 Location:

Summary Statistics: Mean 37.55522935779816; Max. 61.94; Min. 15.13; Valid 109.0; StDev 11.28790171725416;

Variable Format: numeric

Notes: UNF:6:PbsJYJvnNsQsPZ/CWFBzEA==

f377 Location:

Variable Format: character

Notes: UNF:6:tlikml6icW1Bq7w+zkD2TA==

f377 Location:

Summary Statistics: Mean 65.37614678899082; Valid 109.0; Max. 159.0; Min. 2.0; StDev 40.984366710306986;

Variable Format: numeric

Notes: UNF:6:4zDjOqSr/8mQdRo207P0Bw==

f377 Location:

Summary Statistics: Max. 28.58; Valid 109.0; Min. 6.46; Mean 13.955412844036697; StDev 3.4722587194819865;

Variable Format: numeric

Notes: UNF:6:o+xKFHmP/HluoQW4mDUCRw==

f377 Location:

Summary Statistics: Min. 22.65; Mean 32.344954128440364; Valid 109.0; Max. 47.39; StDev 5.1343297416531835

Variable Format: numeric

Notes: UNF:6:RnwdjQdMRgMoowrxnNjJ/w==

f377 Location:

Summary Statistics: Min. 1.01; Max. 1.96; StDev 0.20883314154074398; Valid 109.0; Mean 1.2971559633027523;

Variable Format: numeric

Notes: UNF:6:6D0D/CPjThYw0u+60OArmA==

f377 Location:

Summary Statistics: Max. 9.9; Min. 3.41; Valid 109.0; StDev 1.2790951902053744; Mean 4.4722935779816515

Variable Format: numeric

Notes: UNF:6:rHLfFBVXa4WawwV8VobW7w==

f377 Location:

Summary Statistics: Valid 109.0; StDev 5.033242758972007; Mean 12.117339449541284; Max. 31.14; Min. 5.17;

Variable Format: numeric

Notes: UNF:6:xy1wh+XEFQxa4PphqF0TvQ==

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