DOI: 10.5061/dryad.cnp5hqcfn
title: Extracellular recordings from mouse superior colliculus during the optokinetic reflex

description: This dataset contains extracellular recordings using Neuropixels 1.0
 probes of neurons from the superior colliculus of mice viewing a drifting
 grating stimulus. The drifting grating stimulus included a
 "probe" phase every 0.5 to 1 s in which the contrast of the
 grating was briefly (50 ms) increased from 40% to 100%. The electrode was
 inserted at an extreme angle tangential to the medial-lateral axis of the
 brain so that most of the contacts were positioned in the zonal layer, the
 superficial gray layer, the optic layer, or the intermediate gray layer of
 the superior colliculus. The goal of this experiment was to understand how
 resetting saccades produced via the optokinetic reflex modulate visual
 responses in the superior colliculus.
description: # Extracellular recordings from mouse superior colliculus during the
 optokinetic reflex Please use this digital object identifier to cite the
 dataset: [https://doi.org/10.5061/dryad.cnp5hqcfn](&lt;
 https://doi.org/10.5061/dryad.cnp5hqcfn&gt;) ## How to access data files
 Data are stored in a hierarchical data format (hdf) with each data file
 corresponding to a single experimental session. Files are named with the
 convention: `mlati_store.hdf`.
 "mlati" is an acronym that stands for medial (m)-lateral (l)
 axis (a) tangential (t) insertion (i). The animal number is a unique
 number associated with each animal used in the experiments. There are many
 free applications and software for accessing data stored as an hdf file
 including the graphical user interface
 [HDFView](https://www.hdfgroup.org/download-hdfview/) and the Python
 package [h5py](https://www.h5py.org/). ## Datasets contained within each
 data file Datasets within each data file are grouped by the type of data
 or the data processing module used to produce the dataset. Here are
 descriptions of each dataset which include the path to the dataset, the
 dataset shape, and a brief description of the dataset. Please note that
 not all datasets are populated in every data file. *Variability in the
 availability of datasets is indicated with italicized text*. ### Barcodes
 Datasets related to the periodic TTL pulse train encoding a 32-bit integer
 (i.e., barcode) recorded by all data acquisition systems. The barcode was
 used for synchronizing event timing across systems. *
 `barcodes/labjack/indices` (N) - The sample index from the LabJack
 recording that indicates the start of the barcode signal for each barcode
 recorded by the LabJack device * `barcodes/labjack/trains` (N x 100) - The
 sample from the LabJack recording for each rising edge in the TTL pulse
 train associated with each barcode recorded by the Labjack device *
 `barcodes/labjack/values` (N) - The integer value encoded by each barcode
 recorded by the LabJack device * `barcodes/neuropixels/indices` (N) - The
 sample index from the Neuropixels recording that indicates the start of
 the barcode signal for each barcode recorded by the Neuropixels data
 acquisition system * `barcodes/neuropixels/trains` (N x 100) - The sample
 from the Neuropixels recording for each rising edge in the TTL pulse train
 associated with each barcode recorded by the Neuropixels data acquisition
 system * `barcodes/neuropixels/values` (N) - The integer value encoded by
 each barcode recorded by the Neuropixels data acquisition system ###
 Epochs Manually-collected data used for segmenting the recording into
 distinct epochs based on visual stimuli. Please note, not all experiments
 included the same set of visual stimuli, *so some of these datasets may be
 empty*. For example, not all of the experiments included a sparse noise
 stimulus at the end of the recording, so the `epochs/sn/post` dataset is
 empty in these data files. * `epochs/bn/hr/hf` (2) - Start and stop sample
 from the LabJack recording for the epoch associated with the binary noise
 stimulus (high-resolution, high-frequency) * `epochs/bn/hr/lf` (2) - Start
 and stop sample from the LabJack recording for the epoch associated with
 the binary noise stimulus (high-resolution, low-frequency) *
 `epochs/bn/lr/hf` (2) - Start and stop sample from the LabJack recording
 for the epoch associated with the binary noise stimulus (low-resolution,
 high-frequency) * `epochs/bn/lr/lf` (2) - Start and stop sample from the
 LabJack recording for the epoch associated with the binary noise stimulus
 (low-resolution, low-frequency) * `epochs/dg` (2) - Start and stop sample
 from the LabJack recording for the epoch associated with the drifting
 grating stimulus * `epochs/fs` (2) - Start and stop sample from the
 LabJack recording for the epoch associated with the fictive saccades
 stimulus * `epochs/mb` (2) - Start and stop sample from the LabJack
 recording for the epoch associated with the moving bars stimulus *
 `epochs/sn/pre` (2) - Start and stop sample from the LabJack recording for
 the epoch associated with the sparse noise stimulus presented at the
 beginning of the experiment * `epochs/sn/post` (2) - Start and stop sample
 from the LabJack recording for the epoch associated with the sparse noise
 stimulus presented at the end of the experiment ### Frames Datasets
 related to video acquisition. * `frames/left/dropped` (N) - Mask which
 indicates frames missing from the left camera video recording *
 `frames/left/intervals` (N) - Inter-frame intervals between video frames
 from the left camera video recording * `frames/left/timestamps` (N) -
 Timestamps for each frame in the left camera video recording *
 `frames/right/dropped` (N) - Mask which indicates frames missing from the
 right camera video recording * `frames/right/intervals` (N) - Inter-frame
 intervals between video frames from the right camera video recording *
 `frames/right/timestamps` (N) - Timestamps for each frame in the right
 camera video recording ### LabJack Datasets associated with the LabJack
 data acquisition device. * `labjack/cameras/missing` (N) - Mask which
 indicates frames missing from the LabJack recording *
 `labjack/cameras/timestamps` (N) - Timestamp for each of N frames
 (including missing frames) from the LabJack recording * `labjack/matrix`
 (N x M) - Raw digital and analog signal recorded by the LabJack device
 where N is the number of samples and M is the number of channels (usually
 9) * `labjack/timespace` (N) - Timestamps associated with each sample in
 the LabJack recording ### Metrics Metrics and indices associated with each
 unit. * `metrics/ac` (N) - Amplitude cutoff metric for all units (N) *
 `metrics/dsi` (N) - Direction selectivity index for all units (N) *
 `metrics/fr` (N) - Mean firing rate for all units (N) * `metrics/lpi` (N)
 - Luminance polarity index for all units (N) * `metrics/pr` (N) - Presence
 ratio metric for all units (N) * `metrics/ql` (N) - Manually-curate
 quality label for all units (N) * `metrics/rpvr` (N) - Refractory period
 violation rate metric for all units (N) ### Pose Eye position datasets.
 Please note that for any of these datasets which have a second axis with a
 length of 4, the order of columns is x/horizontal eye position from the
 left eye, y/vertical eye position from the left eye, x/horizontal eye
 position from the right eye, y/vertical eye position from the right eye. *
 `pose/uncorrected` (N x 4) - Eye position (in pixels) estimated with
 DeepLabCut for each frame of the video recording not correcting for
 dropped frames * `pose/corrected` (N x 4) - Eye position (in pixels) after
 correcting for dropped frames * `pose/decomposed` (N x 4) - Eye position
 (in pixels) after using PCA to project eye position onto the horizontal
 (azimuth) and vertical (elevation) axes * `pose/filtered` (N x 4) - Eye
 position (in pixels) after smoothing the reoriented eye position data *
 `pose/interpolated` (N x 4) - Eye position (in pixels) after interpolating
 the values for missing and dropped frames * `pose/missing/left` (N) - Mask
 which indicates the missing and dropped frames from the left camera video
 recording * `pose/missing/right` (N) - Mask which indicates the missing
 and dropped frames from the right camera video recording *
 `pose/reoriented` (N x 4) Eye position (in pixels) after reorienting the
 decomposed eye position so that is positively correlated with the raw eye
 position data ### Prediction Datasets related to classifying eye movements
 as saccades or non-saccadic eye movements and estimating the start and
 stop of saccades. Training data wasn't collected from all
 experiments, *so it's possible some or all of these datasets will be
 empty in some data files.* * `prediction/saccades/direction/X` (N x M) -
 Putative saccade waveforms centered on the peak velocity where N is the
 number of saccades and M is the number of samples (i.e. video frames) *
 `prediction/saccades/direction/y` (N x 1) - Labels for putative saccades
 where -1 is temporal, +1 is nasal, and 0 is noise/non-saccadic eye
 movements * `prediction/saccades/epochs/X` (N x M) - Putative saccade
 waveforms centered on the peak velocity where N is the number of saccades
 and M is the number of samples (i.e. video frames) *
 `prediction/saccades/epochs/y` (N x 2) - Start (first column) and stop
 (second column) offsets that specify distance from the time of peak
 velocity for each saccade * `prediction/saccades/epochs/z` (N x 1) - The
 predicted label for each saccade ### Receptive fields Estimates of ON and
 OFF receptive fields using the sparse noise stimulus. * `rf/on` (N x M x
 P) - ON receptive fields for each unit where N is the number of units, M
 is the number of subregions along the vertical axis of the display, and P
 is the number of subregions along the horizontal axis of the display *
 `rf/off` (N x M x P) - OFF receptive fields for each unit where N is the
 number of units, M is the number of subregions along the vertical axis of
 the display, and P is the number of subregions along the horizontal axis
 of the display ### Saccades Datasets related to saccades. Please note that
 only datasets associated with saccades detected in the left eye are
 described here. Datasets associated with saccades detected in the right
 eye are also available. * `saccades/predicted/left/direction` (N) -
 Direction of saccades detected in the left eye *
 `saccades/predicted/left/dop` (N) - Direction of motion of the closest
 probe stimulus for each saccade detected in the left eye *
 `saccades/predicted/left/epochs` (N x 2) - Start (first column) and stop
 (second column) time (in frame indices) for each saccade detected in the
 left eye * `saccades/predicted/left/gmds` (N) - Direction of the drifting
 grating stimulus during each saccade detected in the left eye where -1 is
 counter-clockwise motion, +1 is clockwise motion, and 0 is no drifting
 grating * `saccades/predicted/left/indices` (N) - Time of peak velocity
 (in video frame indices) for each saccade detected in the left eye *
 `saccades/predicted/left/labels` (N) - Direction of each saccade detected
 in the left eye where -1 is temporal and +1 is nasal *
 `saccades/predicted/left/timestamps` (N x 2) - Start (first column) and
 stop (second column) time (in seconds) for each saccade detected in the
 left eye * `saccades/predicted/left/ttp` (N) - Distance (in seconds)
 between each saccade and the closest probe stimulus *
 `saccades/predicted/left/waveforms` (N x M) - Saccade waveforms for each
 saccade where N is the number of saccades and M is the number of samples
 (in video frames) * `saccades/putative/left/indices` (N) - Time of peak
 velocity (in video frame indices) for each putative saccade detected in
 the left eye * `saccades/putative/left/waveforms` (N x M) Saccade
 waveforms for each putative saccade where N is the number of putative
 saccades and M is the number of samples (in video frames) ### Spikes
 Datasets related to extracellular spikes. * `spikes/clusters` (N x 1) -
 Unit identity associated with each spike where N is the number of spikes *
 `spikes/timestamps` - (N x 1) - Timestamp (in seconds) associated with
 each spike where N is the number of spikes ### Stimuli Datasets related to
 visual stimuli. #### Binary noise stimulus Datasets associated with the
 binary noise stimulus. Please note that only the datasets associated with
 the high-spatial resolution (hr) x high-temporal frequency (hf) version of
 this stimulus are described here. Datasets associated with the other
 combinations of spatial resolution and temporal frequency are also
 available. Low-temporal frequency is abbreviated "lf" and
 low-spatial resolution is abbreviated "lr." *
 `stimuli/bn/hr/hf/fields` (N x M x P) - Matrix which indicates the field
 presented on each trial where N is the number of trials, M is the position
 along the vertical axis of the display, and P is the position along the
 horizontal axis of the display * `stimuli/bn/hr/hf/grids` (N x M x P x 2)
 - Matrix which indicates the location (in degrees of visual angle) for
 each subregion in the field where N is the number of trials, M is the
 position along the vertical axis of the display, and P is the position
 along the horizontal axis of the display * `stimuli/bn/hr/hf/missing` (N)
 - Mask which indicates which trials are missing where N is the number of
 trials * `stimuli/bn/hr/hf/timestamps` (N) - Timestamps (in seconds) for
 the onset of each trial * `stimuli/bn/hr/hf/length` (1) - Side length of
 each subregion in degrees of visual angle. All subregions have the same
 side length. #### Drifting grating stimulus Datasets associated with the
 drifting grating stimulus. * `stimuli/dg/grating/motion` (N) - Direction
 of motion for each block of the drifting grating stimulus where N is the
 number of blocks * `stimuli/dg/grating/timestamps` (N) - Timestamps (in
 seconds) for the onset of each block of the drifting grating stimulus
 where N is the number of blocks * `stimuli/dg/iti/timestamps` (N) -
 Timestamps (in seconds) for the end of each block of the drifting grating
 stimulus where N is the number of blocks * `stimuli/dg/motion/timestamps`
 (N) - Timestamps (in seconds) for the onset of motion of the drifting
 grating stimulus where N is the number of blocks *
 `stimuli/dg/probe/contrast` (N) - Contrast level (0 to 1) for each probe
 where N is the number of probes * `stimuli/dg/probe/dos` (N) - Direction
 of the closest saccade where -1 is temporal and +1 is nasal *
 `stimuli/dg/probe/motion` (N) - Direction of motion of the drifting
 grating stimulus for each probe where N is the number of probes *
 `stimuli/dg/probe/phase` (N) - Phase of the drifting grating stimulus for
 each probe where N is the number of probes * `stimuli/dg/probe/timestamps`
 (N) - Timestamp (in seconds) associated with each probe where N is the
 number of probes * `stimuli/dg/probe/tts` (N) - Latency from each probe to
 the closest saccade where N is the number of probes #### Fictive saccades
 stimulus Datasets associated with the fictive saccades stimulus. *
 `stimuli/fs/probe/motion` (N) - Direction of motion of the drifting
 grating stimulus for each probe presented during the fictive saccades
 stimulus where N is the number of probes * `stimuli/fs/probe/timestamps`
 (N) - Timestamp (in seconds) associated with each probe presented during
 the fictive saccades stimulus where N is the number of probes *
 `stimuli/fs/saccade/motion` (N) - Direction of each fictive saccade where
 -1 is counter-clockwise motion and +1 is clockwise motion *
 `stimuli/fs/saccade/timestamps` (N) - Timestamps (in seconds) for the
 start of each fictive saccade #### Moving bars stimulus Datasets
 associated with the moving bars stimulus. * `stimuli/mb/offset/timestamps`
 (N) - Timestamp (in seconds) for the onset of each moving bar where N is
 the number of trials * `stimuli/mb/onset/timestamps` (N) - Timestamp (in
 seconds) for the offset of each moving bar where N is the number of trials
 * `stimuli/mb/orientation` (N) - Orientation (in degrees) of the bar for
 each trial where N is the number of trials #### Sparse noise stimulus
 Datasets associated with the sparse noise stimulus. Please note only the
 datasets associated with the sparse noise stimulus presented at the
 beginning of the experiment (i.e., "pre"-experiment) are
 described here. Datasets associated with the sparse noise stimulus
 presented at the end of the experiment are also accessible by substituting
 "pre" with "post." For some experiments, the sparse
 noise stimulus was only presented at the beginning; there is no
 "post"-experiment presentation. *For these experiments the
 "post"-experiment datasets associated with the sparse noise
 stimulus will be empty.* * `stimuli/sn/pre/coords` (N x 2) - The
 horizontal and vertical position (in degrees of visual angle) for the
 active subregion on each trial of the sparse noise stimulus where N is the
 number of trials * `stimuli/sn/pre/fields` (N x M x P) - The field for
 each trial of the sparse noise stimulus where N is the number of trials, M
 is the position along the vertical axis of the display, and P is the
 position along the horizontal axis of the display *
 `stimuli/sn/pre/missing` (N) - Mask which indicates which trials of the
 sparse noise stimulus are missing * `stimuli/sn/pre/signs` (N) - Mask
 which indicates the sign of the active subregion on each trial of the
 sparse noise stimulus where True is maximum luminance (i.e., ON) and False
 is minimum luminance (i.e. OFF) * `stimuli/sn/pre/timestamps` (N) -
 Timestamps for the onset of each trial of the sparse noise stimulus ###
 Timestamping function parameters Parameters for the function used to
 timestamp events. The timestamping function takes sample indices from the
 LabJack recording and transforms them into sample indices from the
 Neuropixels recordings accounting for temporal drift between the two data
 acquisition systems. * `tfp/b` (1) - The slope of the timestamping
 function * `tfp/fp` (N) - The barcode indices where N is the number of
 barcodes * `tfp/m` (1) - The intercept of the timestamping function *
 `tfp/xp` (N) - The timestamps (in seconds) for the barcodes recorded by
 the LabJack device where N is the number of barcodes ### ZETA-test
 ZETA-test results associated with each unit. * `zeta/probe/left/latency`
 (N) - Latency from the probe to the response for probes presented during
 counter-clockwise motion of the drifting grating stimulus estimated with
 the ZETA-test for each unit * `zeta/probe/left/p` (N) - p-values from the
 ZETA-test for responses to probes presented during counter-clockwise
 motion of the drifting grating stimulus for each unit *
 `zeta/probe/right/latency` (N) - Latency from the probe to the response
 for probes presented during clockwise motion of the drifting grating
 stimulus estimated with the ZETA-test for each unit * `zeta/probe/right/p`
 (N) - p-values from the ZETA-test for responses to probes presented during
 clockwise motion of the drifting grating stimulus for each unit *
 `zeta/saccade/nasal/latency` (N) - Latency from the saccade onset to the
 response for nasal saccades estimated with the ZETA-test for each unit *
 `zeta/saccade/nasal/p` (N) - p-values from the ZETA-test for responses to
 nasal saccades for each unit * `zeta/saccade/temporal/latency` (N) -
 Latency from the saccade onset to the response for temporal saccades
 estimated with the ZETA-test for each unit * `zeta/saccade/temporal/p` (N)
 - p-values from the ZETA-test for responses to temporal saccades for each
 unit ### Other datasets There are other datasets that are leftover from
 the development of custom data analyses. For example, datasets keyed by
 paths starting with `curves`, `peths`, and `population` are intermediate
 outputs from data analyses, *may or may not be populated*, and can be
 ignored.