DOI: 10.7272/q6p26wdc
title: A cognitive process occurring during sleep revealed by rapid eye movements

description: Since the discovery of REM sleep, the nature of the rapid eye movements
 that characterize this sleep phase has remained elusive. Do they reveal
 gaze shifts in the virtual environment of dreams or simply reflect random
 brainstem activity? We harnessed the head direction (HD) system of the
 mouse thalamus, a neuronal population whose activity reports, in awake
 mice, their actual HD as they explore their environment and, in sleeping
 mice, their virtual HD. We discovered that the direction and amplitude of
 rapid eye movements during REM sleep reveal the direction and amplitude of
 the ongoing changes in virtual HD. Thus, rapid eye movements disclose gaze
 shifts in the virtual world of REM sleep, thereby providing a window in
 the cognitive processes of the sleeping brain.
description: Extracellular
 electrophysiological recordings We recorded from the anteriodorsal nucleus of
 the thalamus (ADN) of mice, both in their home cage as well as while
 exploring the open field arena for food, for 60-120 min sessions. The
 entire recording amounted to a total of 6 to 12 hours per mouse.
 Electrophysiological data were acquired using an Intan RHD2000 system
 (Intan Technologies LLC) band passed filtered between 0.1 Hz and 7.5 kHz
 and digitized at 20 kHz. Spike sorting was performed semi-automatically,
 using Kilosort 2.0. This was followed by manual adjustment of the waveform
 clusters using the software Phy. For the local field potential (LFP), the
 wide-band signal was down-sampled to 1.25 kHz. Eye
 tracking We adopted the head-mounted eye
 tracking system described in Meyer et al. 2018. Light-weight camera
 modules (Arducam, with 5MP Omnivision OV5647 sensor) were used for eye
 tracking, one for each eye. Each camera was inserted into a 3D printed
 camera holder integrated in the head plate. Each eye was illuminated by an
 infrared LED (VSMB2943GX01, Vishay), also integrated in the head plate.
 Videos from the head mounted cameras were acquired at a frame rate of 90
 Hz using single-board computers (Raspberry Pi 3 model B, Raspberry Pi
 Foundation), one for each camera, and controlled using a software
 described in Meyer et al. 2018 and reposed in their github.
 Open field
 arena The
 rectangular open field arena (50 × 28 cm) was surrounded by 25 cm high
 walls displaying salient visual cues. The arena base and the walls were
 made from white plastic. The arena was illuminated by visible room lights
 as well as by infrared LED lights for video acquisition. The video (50 Hz
 sampling rate) was captured by a CMOS camera (Basler acA1300-200um) placed
 above the arena with infrared pass filter (Hoya) in front of the lens. The
 heading of the animal was detected based on the vector connecting the neck
 to the nose of the mouse. The extraction of the coordinates of the nose
 and the neck was performed by DeepLabCut. The heading was up-sampled to
 100Hz by linear interpolation and smoothing (running average with a 210 ms
 window size).
description: Matlab or Python can be used to open the data files. 
 Neuroscope (http://neurosuite.sourceforge.net/) can be also used to open the eeg files.