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Description
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Dataset of the study "Propagating population activity patterns during spontaneous slow waves in the thalamus of rodents". The dataset contains raw high-density electrophysiological recordings obtained from the thalamus of anesthetized and freely moving rodents. Further details on the dataset (dataset and file structure, retrieving data from the files, etc.) are available below (see Notes).
Abstract of the study: Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus.
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Notes
| Dataset structure
Each recording and corresponding metadata were packaged in the Neurodata Without Borders: Neurophysiology version 2.0 (NWB:N 2.0) data format using the NeuroConv Python package. A single NWB file was created from each thalamic recording. NWB files were placed in folders based on the identifier of the animal (e.g., Rat1 or Mouse2), probe insertion sequence (e.g., Insertion1 or Insertion2) and thalamic depth (e.g., from Depth1 to Depth4). The filename of the NWB file (identifier) was constructed by concatenating the above information (e.g., Rat01_Insertion2_Depth3). For chronic recordings, each file identifier contains the day on which the data file was recorded.
The CSV/tab file named "Animal_characteristics_..." contains information about the weight, sex, species and strain of the animals used in the study. The "Recording_characteristics_..." CSV/tab file lists several useful properties for each NWB file including the file size, the duration of the recording, the thalamic location,the stereotaxic coordinates corresponding to each probe insertion, and whether population activity propagation in the thalamus was observed.
Directory structure of the dataset:
Rat/64_channel_multishank_recordings/Coronal_insertions (55 NWB files)
Rat/64_channel_multishank_recordings/Sagittal_insertions (27 NWB files)
Rat/Acute_Neuropixels_recordings (41 NWB files)
Rat/Chronic_Neuropixels_recordings (24 NWB files)
Rat/Simultaneous_thalamic_and_cortical_recordings (10 NWB files)
Mouse/128_channel_multishank_recordings (18 NWB files)
Mouse/Acute_Neuropixels_recordings (11 NWB files)
NWB file structure
Each NWB file contains several main groups (similar to directories). The acquisition group contains the continuous wideband data in a compressed form (in Neuropixels recordings, field potential and action potential recordings are separate), as well as several parameters related to the raw data such as the measurement unit or the data conversion number. The general 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’). The former subgroup carries information about the probe location (thalamic area and stereotaxic coordinates) and the relative positions of recordings sites, while the latter contains metadata about the animal (e.g., sex, species, subject ID, or weight).
Interacting with NWB files
After downloading, the structure of NWB files can be explored using the freely available HDFView software. Neurosift can be used to open NWB files in a browser and explore their contents using the download URL of the selected data file (e.g. https://science-data.hu/api/access/datafile/12193):
https://flatironinstitute.github.io/neurosift/?p=/nwb&url=FILE_URL
https://flatironinstitute.github.io/neurosift/?p=/nwb&url=https://science-data.hu/api/access/datafile/12193
Users can import data from NWB files offline using the PyNWB and MatNWB APIs, or using SpikeInterface. Loaded samples of the raw data have to be multiplied by a conversion number (e.g., 0.195 for 64-channel recordings) 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.
Loading a short segment (20.000 samples corresponding to 1 second of data) of the raw wideband recording on 64 channels:
1. nwb = nwbRead('Rat01_Insertion1_Depth1.nwb');
2. dataChunk=nwb.acquisition.get('ElectricalSeries').data.load([1, 1], [128, 20000]);
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.
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.
Channel-recording site layout
For Neuropixels recordings, channels 1, 2, 3, ... correspond to the most ventral thalamic positions, located closest to the probe tip, whereas channels ...383, 384 correspond to dorsal locations (located further away from the probe tip). For multishank recodings, the first 8 channels (or 16 channels for mouse recordings) correspond to the recording sites of the first shank, with channel 1 corresponding to the most dorsal site and channel 8 located at the most ventral position (site located closest to the shank tip). Similarly, the second 8 channels (or 16 channels for mice) correspond to the sites of the second shank, and so on. For the eight-shank, 64-channel Buzsaki probe recordings from the neocortex, the mapping is the same as described above (shank1: channels 1-8, shank2: channels 9-16, etc.) |
