Neuroexplorer 4

Extracellular single-unit and local field potentials (LFPs) recordings were obtained from an implanted intracranial multielectrode array structure. The 16-channel multielectrode array was connected to a wireless high-frequency headstage transmitter (W16; Triangle Biosystems, Durham, NC, USA) that sent continuous analog signals to a Multineuron Acquisition Processor system (16MAP, Plexon Inc., Dallas, TX, USA). Neural signals were preamplified (10,000–20,000X) and digitized at 40 kHz. Voltage-time threshold windows were used to identify single-unit waveforms online (SortClient 2.6; Plexon) and validated offline using automatic and manual sorting techniques (Offline Sorter 2.8; Plexon Inc., Dallas, TX, USA) according to the cumulative criteria described in detail previously [33 (link)]. Extracellular LFFs signals were obtained by low-frequency (0.2–200 Hz) filtering of the raw signals. LFPs were preamplified and digitized at a 0.5 kHz sampling rate. These data were subsequently processed offline using the NeuroExplorer 4 software (NEX 4, Plexon Inc., Dallas, TX, USA) and exported to MatLab (R17, MathWorks, Natick, MA, USA) to be further analyzed using custom routines.

The data were collected and processed randomly. All immunocytochemistry and behavioral tests were carried out blind. The electrophysiology experiments were not blind, but data collection and analyses were performed blind. Sample size was calculated according to the preliminary experiment results and the following formula: $\text{N}={\left[\frac{\left({\text{Z}}_{\text{α}/2}+{\text{Z}}_{\text{β}}\right)\text{σ}}{\text{δ}}\right]}^2\left({\text{Q}}_1^{-1}+{\text{Q}}_2^{-1}\right)$ , where α = 0.05 significant level, β = 0.2, power = 1-β, δ is the difference between the means of two samples, and Q is the sample fraction. The samples were randomly assigned to each group. The data were presented as mean ± SEM. One-way ANOVA was used for analysis of electrophysiological data in vitro. Two-tailed Student’s t-tests were performed after the normality test for the data from all groups in vivo. Variance was similar between groups being compared. We considered p < 0.05 to be statistically significant. The sleep patterns were determined by combined EEG, EMG, and video recordings. Data were presented as mean ± SEM. All data were analyzed using Origin8.0 (OriginLab), Clampfit 10.2 (Axon Instruments), NeuroExplorer4 (Plexon), and Microsoft Excel 2010. Data were exported into Illustrator CS6 (Adobe Systems) for preparation of figures.

A 4-shank probe with a total of 16 recording microelectrodes (A4 × 4–3mm-50-125-177-A16, NeuroNexus, Ann Arbor, MI, USA) was implanted at the L5 spinal level in the left DH. The array was oriented parallel to the rostrocaudal axis so that each electrode was at roughly the same mediolateral position. The depth of electrode insertion was monitored to estimate electrode position within the presumed Rexed lamina(e).
Electrode shank tips were lowered below the dorsal surface. Since the recording sites were spaced at 50 µm intervals up each shank of the electrode, we estimated the depth of the recorded neurons to be positioned within lamina II–III. Neurons that responded to limb displacement, indicating that they received proprioceptive input, were excluded. Measured extracellular signals of neuronal activity were amplified, and the band-pass was filtered between 500 Hz and 10 kHz, digitized at 40 kHz with the OmniPlex Data Acquisition System (Plexon, Dallas, TX, USA), and stored with stimulus markers on a disk. Single units were isolated using Offline Sorter v3 software (Plexon, Dallas, TX, USA) and analyzed with NeuroExplorer 4 (Plexon, Dallas, TX, USA).