DOI: 10.5061/dryad.x69p8czsr
title: Data from: Coincident development and synchronization of sleep-dependent delta in the cortex and medulla

description: In early development, active sleep is the predominant sleep state before
 it is supplanted by quiet sleep. In rats, the developmental increase in
 quiet sleep is accompanied by the sudden emergence of the cortical delta
 rhythm (0.5-4 Hz) around postnatal day 12 (P12). We sought to explain the
 emergence of cortical delta by assessing developmental changes in the
 activity of the parafacial zone (PZ), a medullary structure thought to
 regulate quiet sleep in adults. We recorded from PZ in P10 and P12 rats
 and predicted an age-related increase in neural activity during increasing
 periods of delta-rich cortical activity. Instead, during quiet sleep we
 discovered sleep-dependent rhythmic spiking activity—with intervening
 periods of total silence—phase-locked to a local delta rhythm. Moreover,
 PZ and cortical delta were coherent at P12, but not at P10. PZ delta was
 also phase-locked to respiration, suggesting sleep-dependent modulation of
 PZ activity by respiratory pacemakers in the ventral medulla.
 Disconnecting the main olfactory bulbs from the cortex did not diminish
 cortical delta, indicating that the influence of respiration on delta at
 this age is not mediated indirectly through nasal breathing. Finally, we
 observed an increase in parvalbumin-expressing terminals in PZ across
 these ages, supporting a role for local GABAergic inhibition in PZ’s
 rhythmicity. The unexpected discovery of delta-rhythmic neural activity in
 the medulla—when cortical delta is also emerging—provides a new
 perspective on the brainstem’s role in regulating sleep and promoting
 long-range functional connectivity in early development.
description: These files consist of all data required to recreate main figures
 and analyses from the manuscript, including: electrophysiological spiking
 and LFP data, respiratory data, as well as behavioral states.
 Electrophysioloical data were collected from a TDT Neural Data Acquisition
 System using NeuroNexus electrodes. Briefly, to analyze
 LFPs from PZ and cortex, raw neural activity was downsampled to ~1000 Hz,
 smoothed using a .005 s moving Gaussian kernel, and converted to binary
 files. For unit activity in PZ, raw neural activity was bandpass filtered
 (300-5000 Hz) and converted to binary files. Putative units were acquired
 from templates extracted using Kilosort and visualized and confirmed using
 Phy2. Waveforms and waveform autocorrelations were used to identify single
 units and multi-units. Sorted units, LFPs, movement data, and respiratory
 waveforms were imported into Spike2 (Cambridge Electronic Design,
 Cambridge, UK) or MATLAB for analysis.
description: # COINCIDENT DEVELOPMENT AND SYNCHRONIZATION OF SLEEP-DEPENDENT DELTA IN
 THE CORTEX AND MEDULLA
 [https://doi.org/10.5061/dryad.x69p8czsr](https://doi.org/10.5061/dryad.x69p8czsr) Below are descriptions of all MATLAB structures (i.e., "databases") in this Dryad repository. ## Data organization and file structure All files are MATLAB structures that are labelled as "age_ID_preproc.mat". Generally, files are divided by two rat ages: Postnatal day (P) 10 and P12. Each subject has its own ID (e.g., 7M2) and its own .mat data file. Each  datafile has a "preproc" structure which has multiple fields/variables containing all the recorded data from that subject. The description on all variables is as follows: slTime = sleep state time information for extracting/parsing, as determined by subject's behavior. tSpace = respiratory signal time values sResp = respiratory signal amplitude pzlfp = Parafacial zone (PZ) local field potential values m1lfp = cortical local field potential values pzDelta = PZ local field potential values, filtered for delta frequencies (0.5-4 Hz) pzDelta1Med = PZ local field potential values, filtered for delta frequencies (0.5-4 Hz), that are above the median amplitude calculated across the whole run m1Delta = cortical local field potential values, filtered for delta frequencies (0.5-4 Hz) m1Delta1Med = cortical local field potential values, filtered for delta frequencies (0.5-4 Hz), that are above the median amplitude calculated across the whole run pzMUA = all the times multiunit activity (MUA) in the parafacial zone (PZ) occured. Each row in the structure represents a single multiunit. pzSC  = all the times single units/cells (SC) in the parafacial zone (PZ) fired. Each row in the structure represents a single neuron. pzRasters = all the times a neuronal spike occurred in the PZ neuronal population, plottable as "rasters". pzIFR = the instantaneous firing rate of the PZ neuronal population.  resp2SD = Respiratory data that has been processed to remove any noise above 2 standard deviations of median respiratory waveform amplitude. \***Note for state definitions:** AS = active sleep WA = wake QS = quiet sleep The final behavioral state times were defined using multiple criterions, as described in the manuscript. You can access the time stamps for each state by combining the criterions. Here's an example MATLAB code for all the times the subject was in active sleep and quiet sleep: %for defining AS state AS_stateDef = [preproc.resp2SDraw ; preproc.midhaASraw ; preproc.islerASraw];    wherein resp2SDraw = raw respiratory signal times that has been processed to remove any noise above 2 standard deviations of median respiratory waveform amplitude. midhaASraw= active sleep periods that were marked by the observer based on behavioral data (e.g twitches) islerASraw = active sleep periods that were determined by irregular breathing, as previously demonstrated by Isler et al., 2016 (doi: 10.1002/dev.21482). %for defining QS state QS_stateDef = [preproc.resp2SDraw ; preproc.midhaQSraw ; preproc.islerQSraw ; preproc.pzDelta1MedRaw ; preproc.m1Delta1MedRaw];   wherein: midhaQSraw = quiet sleep periods that were marked by the observer based on behavioral data (e.g behavioral quiescence, absence of twitches/wake movements) islerQSraw = quiet sleep periods that were determined by regular breathing, as previously demonstrated by Isler et al., 2016 (doi: 10.1002/dev.21482). Other variables used in this sample code have been described above.  All variables/structures and how they were computed is described thoroughly in the relevant code script (e.g., PreProcessV0.m) #### **Sharing/Access information:**  Additional data (e.g., raw electrophysiological data, video files) can be requested by contacting the corresponding author of the manuscript (Midha Ahmad, [midha-ahmad@uiowa.edu](mailto:midha-ahmad@uiowa.edu)), although note that the full raw dataset is terabytes of data.  ## Code/Software All original code has been deposited at [https://github.com/Blumberg-Lab/Ahmad-et-al.-2024](https://github.com/Blumberg-Lab/Ahmad-et-al.-2024) and is publicly available.