Reading an NWB File

After downloading an NWB file, you may want to view the data inside. You can do basic reading of the file with PyNWB. This is a package designed to utilize, modify, and process NWB files. The basic read functionality of PyNWB is shown below.

Environment Setup

⚠️Note: If running on a new environment, run this cell once and then restart the kernel⚠️

import warnings
warnings.filterwarnings('ignore')

try:
    from databook_utils.dandi_utils import dandi_stream_open
except:
    !git clone https://github.com/AllenInstitute/openscope_databook.git
    %cd openscope_databook
    %pip install -e .
    %cd ./docs/basics

import pandas as pd

from dandi import dandiapi
from pynwb import NWBHDF5IO

Downloading an NWB File

To read an NWB File, it must first be downloaded. dandiset_id and dandi_filepath may be changed to select a different file off of DANDI. If the file of interest is already downloaded, you don’t need to run the download cell again. When trying to download an embargoed file, refer to the code from the Downloading an NWB File notebook.

dandiset_id = "000021"
dandi_filepath = "sub-723627600/sub-723627600_ses-742951821.nwb"
download_loc = "."

filename = dandi_filepath.split("/")[-1]
filepath = f"{download_loc}/{filename}"

print(filename)
print(filepath)

sub-723627600_ses-742951821.nwb
./sub-723627600_ses-742951821.nwb

client = dandiapi.DandiAPIClient()
my_dandiset = client.get_dandiset(dandiset_id)
file = my_dandiset.get_asset_by_path(dandi_filepath)
# this may take awhile, especially if the file to download is large
file.download(filepath)

print(f"Downloaded file to {filepath}")

A newer version (0.62.2) of dandi/dandi-cli is available. You are using 0.61.2

Downloaded file to ./sub-723627600_ses-742951821.nwb

Reading an NWB File

You can read in a NWB file with PyNWB’s NWBHDF5IO method to retrieve an io object. You can use the .read method to actually read it in. From there, you can see the raw data of the NWB file and can print the fields you are interested in.

# takes relative or absolute filepath as first argument
io = NWBHDF5IO(f"{download_loc}/{filename}", mode="r", load_namespaces=True)
nwb = io.read()
nwb

root (NWBFile)

session_description: Data and metadata for an Ecephys session

identifier: 742951821

session_start_time

2018-10-26 12:47:04-07:00

timestamps_reference_time

2018-10-26 12:47:04-07:00

file_create_date

0

2020-05-26 00:53:26.959556-07:00

acquisition

raw_running_wheel_rotation

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: radians

data

timestamps

timestamps_unit: seconds

interval: 1

timestamp_link

0: acquisition/running_wheel_signal_voltage/timestamps

1: acquisition/running_wheel_supply_voltage/timestamps

running_wheel_signal_voltage

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: V

data

timestamps (link to acquisition/raw_running_wheel_rotation/timestamps)

timestamps_unit: seconds

interval: 1

running_wheel_supply_voltage

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: V

data

timestamps (link to acquisition/raw_running_wheel_rotation/timestamps)

timestamps_unit: seconds

interval: 1

processing

eye_tracking

description: Eye tracking processing module

data_interfaces

cr_ellipse_fits

description:

table

	center_x	center_y	height	phi	width	timestamps
id
0	327.339200	220.528876	7.122461	-0.046604	8.540818	3.15554
1	327.225841	220.183568	7.286199	-0.186530	8.163864	3.17849
2	327.171088	220.285960	7.290239	-0.267194	8.074097	3.18553
3	327.097132	220.502671	7.239620	-0.006504	8.026307	3.21892

... and 288127 more rows.

eye_ellipse_fits

description:

table

	center_x	center_y	height	phi	width	timestamps
id
0	310.748365	207.967287	124.601937	0.080571	158.078800	3.15554
1	311.049063	208.004817	124.397462	0.078970	157.795426	3.17849
2	311.266888	208.144224	124.609645	0.089244	157.970495	3.18553
3	311.164458	208.152664	124.450363	0.091454	157.778064	3.21892

... and 288127 more rows.

pupil_ellipse_fits

description:

table

	center_x	center_y	height	phi	width	timestamps
id
0	327.890593	192.698878	38.936052	-0.301362	42.041979	3.15554
1	NaN	NaN	NaN	NaN	NaN	3.17849
2	NaN	NaN	NaN	NaN	NaN	3.18553
3	329.518794	194.347578	41.306612	0.356213	45.434569	3.21892

... and 288127 more rows.

eye_tracking_rig_metadata

description: Eye tracking rig metadata module

data_interfaces

eye_tracking_rig_metadata

equipment: NP.1

monitor_position

monitor_position__unit: mm

camera_position

camera_position__unit: mm

led_position

led_position__unit: mm

monitor_rotation

monitor_rotation__unit: deg

camera_rotation

camera_rotation__unit: deg

filtered_gaze_mapping

description: Gaze mapping processing module filtered outputs

data_interfaces

eye_area

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Pixels ^ 2

data

timestamps

timestamps_unit: seconds

interval: 1

pupil_area

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Pixels ^ 2

data

timestamps

timestamps_unit: seconds

interval: 1

screen_coordinates

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Centimeters

data

timestamps

timestamps_unit: seconds

interval: 1

screen_coordinates_spherical

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Degrees

data

timestamps

timestamps_unit: seconds

interval: 1

optotagging

description: optogenetic stimulution data

data_interfaces

optotagging

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: seconds

data

timestamps

timestamps_unit: seconds

interval: 1

optogenetic_stimulation

description:

table

	start_time	condition	level	stop_time	stimulus_name	duration	tags	timeseries
id
0	9225.19538	a single square pulse	2.5	9225.20038	pulse	0.005	[optical_stimulation]	[(0, 1, optotagging pynwb.base.TimeSeries at 0x1601617791104\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (180,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (180,), type "<f8">\n timestamps_unit: seconds\n unit: seconds\n)]
1	9227.05495	a single square pulse	1.0	9227.05995	pulse	0.005	[optical_stimulation]	[(1, 1, optotagging pynwb.base.TimeSeries at 0x1601617791104\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (180,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (180,), type "<f8">\n timestamps_unit: seconds\n unit: seconds\n)]
2	9228.82508	half-period of a cosine wave	2.5	9229.82508	raised_cosine	1.000	[optical_stimulation]	[(2, 1, optotagging pynwb.base.TimeSeries at 0x1601617791104\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (180,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (180,), type "<f8">\n timestamps_unit: seconds\n unit: seconds\n)]
3	9230.66016	2.5 ms pulses at 10 Hz	2.5	9231.66016	fast_pulses	1.000	[optical_stimulation]	[(3, 1, optotagging pynwb.base.TimeSeries at 0x1601617791104\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (180,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (180,), type "<f8">\n timestamps_unit: seconds\n unit: seconds\n)]

... and 176 more rows.

raw_gaze_mapping

description: Gaze mapping processing module raw outputs

data_interfaces

eye_area

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Pixels ^ 2

data

timestamps

timestamps_unit: seconds

interval: 1

pupil_area

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Pixels ^ 2

data

timestamps

timestamps_unit: seconds

interval: 1

screen_coordinates

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Centimeters

data

timestamps

timestamps_unit: seconds

interval: 1

screen_coordinates_spherical

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: Degrees

data

timestamps

timestamps_unit: seconds

interval: 1

running

description: running speed data

data_interfaces

running_speed

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: cm/s

data

timestamps

timestamps_unit: seconds

interval: 1

timestamp_link

0: processing/running/running_wheel_rotation/timestamps

running_speed_end_times

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: cm/s

data

timestamps

timestamps_unit: seconds

interval: 1

running_wheel_rotation

resolution: -1.0

comments: no comments

description: no description

conversion: 1.0

offset: 0.0

unit: radians

data

timestamps (link to processing/running/running_speed/timestamps)

timestamps_unit: seconds

interval: 1

stimulus

description: Stimulus Times processing

data_interfaces

timestamps (link to processing/stimulus/timestamps/timestamps)

epoch_tags

set()

electrodes

description: metadata about extracellular electrodes

table

	x	y	z	imp	location	filtering	group	group_name	probe_vertical_position	probe_horizontal_position	probe_id	local_index	valid_data
id
850180720	NaN	NaN	NaN	NaN		AP band: 500 Hz high-pass; LFP band: 1000 Hz low-pass	probeE abc.EcephysElectrodeGroup at 0x1601617800992\nFields:\n description: Ecephys Electrode Group\n device: probeE abc.EcephysProbe at 0x1601617789856\nFields:\n probe_id: 769322720\n sampling_rate: 30000.0018391686\n\n has_lfp_data: True\n lfp_sampling_rate: 1250.000076632025\n location: See electrode locations\n probe_id: 769322720\n	probeE	3160	27	769322720	315	True
850180714	NaN	NaN	NaN	NaN		AP band: 500 Hz high-pass; LFP band: 1000 Hz low-pass	probeE abc.EcephysElectrodeGroup at 0x1601617800992\nFields:\n description: Ecephys Electrode Group\n device: probeE abc.EcephysProbe at 0x1601617789856\nFields:\n probe_id: 769322720\n sampling_rate: 30000.0018391686\n\n has_lfp_data: True\n lfp_sampling_rate: 1250.000076632025\n location: See electrode locations\n probe_id: 769322720\n	probeE	3140	43	769322720	312	True
850180154	NaN	NaN	NaN	NaN	VISal	AP band: 500 Hz high-pass; LFP band: 1000 Hz low-pass	probeE abc.EcephysElectrodeGroup at 0x1601617800992\nFields:\n description: Ecephys Electrode Group\n device: probeE abc.EcephysProbe at 0x1601617789856\nFields:\n probe_id: 769322720\n sampling_rate: 30000.0018391686\n\n has_lfp_data: True\n lfp_sampling_rate: 1250.000076632025\n location: See electrode locations\n probe_id: 769322720\n	probeE	340	43	769322720	32	True
850180600	NaN	NaN	NaN	NaN		AP band: 500 Hz high-pass; LFP band: 1000 Hz low-pass	probeE abc.EcephysElectrodeGroup at 0x1601617800992\nFields:\n description: Ecephys Electrode Group\n device: probeE abc.EcephysProbe at 0x1601617789856\nFields:\n probe_id: 769322720\n sampling_rate: 30000.0018391686\n\n has_lfp_data: True\n lfp_sampling_rate: 1250.000076632025\n location: See electrode locations\n probe_id: 769322720\n	probeE	2560	27	769322720	255	True

... and 2300 more rows.

electrode_groups

probeA

description: Ecephys Electrode Group

location: See electrode locations

device

sampling_rate: 29999.970280708

probe_id

769322712

has_lfp_data

True

probe_id

769322712

lfp_sampling_rate: 1249.99876169617

probeB

description: Ecephys Electrode Group

location: See electrode locations

device

sampling_rate: 29999.9198310558

probe_id

769322714

has_lfp_data

True

probe_id

769322714

lfp_sampling_rate: 1249.996659627325

probeC

description: Ecephys Electrode Group

location: See electrode locations

device

sampling_rate: 29999.9989851737

probe_id

769322716

has_lfp_data

True

probe_id

769322716

lfp_sampling_rate: 1249.99995771557

probeD

description: Ecephys Electrode Group

location: See electrode locations

device

sampling_rate: 29999.9256599708

probe_id

769322718

has_lfp_data

True

probe_id

769322718

lfp_sampling_rate: 1249.996902498785

probeE

description: Ecephys Electrode Group

location: See electrode locations

device

sampling_rate: 30000.0018391686

probe_id

769322720

has_lfp_data

True

probe_id

769322720

lfp_sampling_rate: 1250.000076632025

probeF

description: Ecephys Electrode Group

location: See electrode locations

device

sampling_rate: 30000.042175479

probe_id

769322722

has_lfp_data

True

probe_id

769322722

lfp_sampling_rate: 1250.001757311625

devices

probeA

sampling_rate: 29999.970280708

probe_id

769322712

probeB

sampling_rate: 29999.9198310558

probe_id

769322714

probeC

sampling_rate: 29999.9989851737

probe_id

769322716

probeD

sampling_rate: 29999.9256599708

probe_id

769322718

probeE

sampling_rate: 30000.0018391686

probe_id

769322720

probeF

sampling_rate: 30000.042175479

probe_id

769322722

intervals

drifting_gratings_presentations

description: Presentation times and stimuli details for 'drifting_gratings' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	temporal_frequency	color	mask	opacity	phase	size	units	stimulus_index	orientation	spatial_frequency	contrast	tags	timeseries
id
0	1586.006904	1588.008574	drifting_gratings	2.0	15.0	[1.0, 1.0, 1.0]	None	1.0	[10617.96666667, 10617.96666667]	[250.0, 250.0]	deg	2.0	315.0	0.04	0.8	[stimulus_time_interval]	[(3798, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	1589.009416	1591.011096	drifting_gratings	2.0	4.0	[1.0, 1.0, 1.0]	None	1.0	[10617.96666667, 10617.96666667]	[250.0, 250.0]	deg	2.0	135.0	0.04	0.8	[stimulus_time_interval]	[(3799, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	1592.011914	1594.013594	drifting_gratings	2.0	1.0	[1.0, 1.0, 1.0]	None	1.0	[10617.96666667, 10617.96666667]	[250.0, 250.0]	deg	2.0	225.0	0.04	0.8	[stimulus_time_interval]	[(3800, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	1595.014426	1597.016106	drifting_gratings	2.0	8.0	[1.0, 1.0, 1.0]	None	1.0	[10617.96666667, 10617.96666667]	[250.0, 250.0]	deg	2.0	180.0	0.04	0.8	[stimulus_time_interval]	[(3801, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 626 more rows.

flashes_presentations

description: Presentation times and stimuli details for 'flashes' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	color	mask	opacity	phase	size	units	stimulus_index	orientation	spatial_frequency	contrast	tags	timeseries
id
0	1285.739454	1285.989662	flashes	1.0	1.0	None	1.0	[0.0, 0.0]	[300.0, 300.0]	deg	1.0	0.0	[0.0, 0.0]	0.8	[stimulus_time_interval]	[(3647, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	1287.741164	1287.991365	flashes	1.0	1.0	None	1.0	[0.0, 0.0]	[300.0, 300.0]	deg	1.0	0.0	[0.0, 0.0]	0.8	[stimulus_time_interval]	[(3648, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	1289.742814	1289.993017	flashes	1.0	1.0	None	1.0	[0.0, 0.0]	[300.0, 300.0]	deg	1.0	0.0	[0.0, 0.0]	0.8	[stimulus_time_interval]	[(3649, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	1291.744504	1291.994702	flashes	1.0	1.0	None	1.0	[0.0, 0.0]	[300.0, 300.0]	deg	1.0	0.0	[0.0, 0.0]	0.8	[stimulus_time_interval]	[(3650, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 146 more rows.

gabors_presentations

description: Presentation times and stimuli details for 'gabors' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	temporal_frequency	x_position	y_position	color	mask	opacity	phase	size	units	stimulus_index	orientation	spatial_frequency	contrast	tags	timeseries
id
0	84.753134	84.986652	gabors	0.0	4.0	40.0	10.0	[1.0, 1.0, 1.0]	circle	1.0	[3644.93333333, 3644.93333333]	[20.0, 20.0]	deg	0.0	45.0	0.08	0.8	[stimulus_time_interval]	[(1, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	84.986652	85.236850	gabors	0.0	4.0	40.0	-40.0	[1.0, 1.0, 1.0]	circle	1.0	[3644.93333333, 3644.93333333]	[20.0, 20.0]	deg	0.0	0.0	0.08	0.8	[stimulus_time_interval]	[(2, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	85.236850	85.487048	gabors	0.0	4.0	-20.0	0.0	[1.0, 1.0, 1.0]	circle	1.0	[3644.93333333, 3644.93333333]	[20.0, 20.0]	deg	0.0	90.0	0.08	0.8	[stimulus_time_interval]	[(3, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	85.487048	85.737246	gabors	0.0	4.0	30.0	-40.0	[1.0, 1.0, 1.0]	circle	1.0	[3644.93333333, 3644.93333333]	[20.0, 20.0]	deg	0.0	0.0	0.08	0.8	[stimulus_time_interval]	[(4, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 3641 more rows.

invalid_times

description: experimental intervals

table

	start_time	stop_time	tags
id
0	996.94	1129.13	[EcephysProbe, 769322716, probeC]
1	3167.80	3226.30	[EcephysProbe, 769322716, probeC]
2	4122.34	4185.04	[EcephysProbe, 769322716, probeC]
3	5867.62	6115.02	[EcephysProbe, 769322716, probeC]

... and 3 more rows.

natural_movie_one_presentations

description: Presentation times and stimuli details for 'natural_movie_one' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	color	opacity	size	units	stimulus_index	orientation	frame	contrast	tags	timeseries
id
0	2847.060224	2847.093585	natural_movie_one	4.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	3.0	0.0	0.0	1.0	[stimulus_time_interval]	[(22000, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	2847.093585	2847.126945	natural_movie_one	4.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	3.0	0.0	1.0	1.0	[stimulus_time_interval]	[(22001, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	2847.126945	2847.160306	natural_movie_one	4.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	3.0	0.0	2.0	1.0	[stimulus_time_interval]	[(22002, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	2847.160306	2847.193667	natural_movie_one	4.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	3.0	0.0	3.0	1.0	[stimulus_time_interval]	[(22003, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 17996 more rows.

natural_movie_three_presentations

description: Presentation times and stimuli details for 'natural_movie_three' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	color	opacity	size	units	stimulus_index	orientation	frame	contrast	tags	timeseries
id
0	2216.533564	2216.566925	natural_movie_three	3.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	4.0	0.0	0.0	1.0	[stimulus_time_interval]	[(3999, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	2216.566925	2216.600287	natural_movie_three	3.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	4.0	0.0	1.0	1.0	[stimulus_time_interval]	[(4000, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	2216.600287	2216.633648	natural_movie_three	3.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	4.0	0.0	2.0	1.0	[stimulus_time_interval]	[(4001, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	2216.633648	2216.667010	natural_movie_three	3.0	[1.0, 1.0, 1.0]	1.0	[1920.0, 1080.0]	pix	4.0	0.0	3.0	1.0	[stimulus_time_interval]	[(4002, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 35996 more rows.

natural_scenes_presentations

description: Presentation times and stimuli details for 'natural_scenes' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	stimulus_index	frame	tags	timeseries
id
0	5909.618224	5909.868445	natural_scenes	9.0	5.0	104.0	[stimulus_time_interval]	[(51355, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	5909.868445	5910.118665	natural_scenes	9.0	5.0	66.0	[stimulus_time_interval]	[(51356, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	5910.118665	5910.368886	natural_scenes	9.0	5.0	36.0	[stimulus_time_interval]	[(51357, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	5910.368886	5910.619106	natural_scenes	9.0	5.0	61.0	[stimulus_time_interval]	[(51358, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 5946 more rows.

spontaneous_presentations

description: Presentation times and stimuli details for 'spontaneous' stimuli

table

	start_time	stop_time	stimulus_name	tags	timeseries
id
0	24.686364	84.753134	spontaneous	[stimulus_time_interval]	[(0, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	996.748081	1285.739454	spontaneous	[stimulus_time_interval]	[(3646, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	1584.255460	1586.006904	spontaneous	[stimulus_time_interval]	[(3797, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	2185.507656	2216.533564	spontaneous	[stimulus_time_interval]	[(3998, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 11 more rows.

static_gratings_presentations

description: Presentation times and stimuli details for 'static_gratings' stimuli

table

	start_time	stop_time	stimulus_name	stimulus_block	color	mask	opacity	phase	size	units	stimulus_index	orientation	spatial_frequency	contrast	tags	timeseries
id
0	5399.191914	5399.442125	static_gratings	8.0	[1.0, 1.0, 1.0]	None	1.0	0.5	[250.0, 250.0]	deg	6.0	0.0	0.08	0.8	[stimulus_time_interval]	[(49434, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
1	5399.442125	5399.692335	static_gratings	8.0	[1.0, 1.0, 1.0]	None	1.0	0.5	[250.0, 250.0]	deg	6.0	60.0	0.02	0.8	[stimulus_time_interval]	[(49435, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
2	5399.692335	5399.942546	static_gratings	8.0	[1.0, 1.0, 1.0]	None	1.0	0.0	[250.0, 250.0]	deg	6.0	90.0	0.16	0.8	[stimulus_time_interval]	[(49436, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]
3	5399.942546	5400.192756	static_gratings	8.0	[1.0, 1.0, 1.0]	None	1.0	0.75	[250.0, 250.0]	deg	6.0	120.0	0.08	0.8	[stimulus_time_interval]	[(49437, 1, timestamps pynwb.base.TimeSeries at 0x1601617792880\nFields:\n comments: no comments\n conversion: 1.0\n data: <HDF5 dataset "data": shape (70390,), type "<f8">\n description: no description\n interval: 1\n offset: 0.0\n resolution: -1.0\n timestamps: <HDF5 dataset "timestamps": shape (70390,), type "<f8">\n timestamps_unit: seconds\n unit: s\n)]

... and 5996 more rows.

subject

age: P120D

genotype: wt/wt

sex: M

species: Mus musculus

subject_id: 723627600

specimen_name: C57BL/6J-404571

age_in_days: 120.0

invalid_times

description: experimental intervals

table

	start_time	stop_time	tags
id
0	996.94	1129.13	[EcephysProbe, 769322716, probeC]
1	3167.80	3226.30	[EcephysProbe, 769322716, probeC]
2	4122.34	4185.04	[EcephysProbe, 769322716, probeC]
3	5867.62	6115.02	[EcephysProbe, 769322716, probeC]

... and 3 more rows.

units

description:

waveform_unit: volts

table

	snr	recovery_slope	cumulative_drift	waveform_halfwidth	cluster_id	amplitude_cutoff	l_ratio	isi_violations	d_prime	quality	velocity_below	spread	repolarization_slope	amplitude	peak_channel_id	PT_ratio	local_index	silhouette_score	presence_ratio	velocity_above	firing_rate	isolation_distance	max_drift	nn_miss_rate	waveform_duration	nn_hit_rate	spike_times	spike_amplitudes	waveform_mean
id
950961498	1.841796	-0.019077	271.43	0.206030	71	0.500000	0.034664	0.891168	2.686974	good	0.392438	110.0	0.328248	88.432305	850180154	0.418521	71	0.082570	0.99	0.480737	2.793710	41.556254	33.20	0.005581	0.439531	0.770202	[3.9744092642121345, 4.549875895599463, 5.759175821462583, 5.993375807104808, 6.206975794009929, 6.7112090964309274, 8.192109005643442, 8.691908975002896, 8.793608968768115, 8.83200896641398, 9.160642279600244, 11.537542133882928, 11.684675458196162, 11.845242115019191, 11.879775446235437, 12.154208762744465, 12.212875425814536, 13.693608668370603, 16.667208486072226, 22.354641470733963, 22.815141442502725, 23.10650809130698, 24.21087469026977, 24.312841350685307, 25.090874636320827, 25.43620794848329, 25.509541277320878, 25.561341274145246, 27.74087447386095, 28.369641101980687, 28.764874411083998, 30.626407630294885, 33.03534081594708, 33.558607450534566, 35.55980732784977, 38.41997381917216, 38.92894045463631, 42.095073593867895, 42.32287357990247, 44.54390677707399, 46.429139994831935, 47.78693991159117, 47.91770657024111, 48.05983989486087, 48.203239886069646, 48.31127321277993, 48.371006542451276, 48.85647317935611, 49.12490649623297, 49.32307315075091, 49.366206481439924, 49.4438398100139, 49.52783980486423, 49.65577313035453, 49.67600646244745, 51.56107301354894, 51.63700634222713, 52.6079396160368, 52.94190626222944, 53.41463956658156, 54.209172851205544, 54.21310618429774, 55.582206100364225, 55.90780608040311, 58.191572607062064, 59.389605866949225, 61.040405765745916, 61.10867242822745, 62.21000569404287, 64.34340556325347, 64.3551055625362, 64.58243888193272, 67.31967204745828, 68.21757199241196, 68.30390532045259, 69.720038566969, 70.2288052024454, 73.34697167795095, 74.40390494648832, 74.41933827887551, 75.70163820026333, 76.22697150139078, 76.23313816767939, 77.7615047406486, 78.16140471613248, 78.8190380091492, 81.64980450227398, 83.8021377036572, 85.8272375795072, 85.8553709111158, 85.87553757654614, 85.9832709032748, 86.00277090207935, 86.39783754452621, 86.48177087271395, 86.49183753876348, 87.03720417199611, 87.33027082069614, 87.59483747114339, 87.60137080407618, ...]	[0.00013284615614484466, 7.155759550312513e-05, 8.939943098470118e-05, 7.700851469753486e-05, 0.00011095208067655804, 9.029365072009522e-05, 8.262158543266691e-05, 8.201934636005223e-05, 8.435827603210274e-05, 7.879183893772323e-05, 0.00012424104360240826, 8.367359035809769e-05, 0.00011329268580875535, 7.306773723566603e-05, 7.532981786636207e-05, 7.770834297726059e-05, 9.337571677809022e-05, 9.52366706717469e-05, 8.349757184608462e-05, 7.536622739235519e-05, 7.499669323338691e-05, 7.157744082084876e-05, 0.0001384765399681603, 0.00011126323393442632, 7.626311263252822e-05, 7.405363129613772e-05, 7.310098623456404e-05, 7.392093992966326e-05, 8.219016713774625e-05, 9.068488970369246e-05, 8.235546651268378e-05, 8.438568630624676e-05, 7.359906753471943e-05, 9.099812459386434e-05, 8.207673087008007e-05, 7.481388403062735e-05, 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1.460745000000001, 5.329545000000003, 9.5238, 12.745200000000002, 8.975850000000017, -1.8413849999999987, -7.999485000000005, -6.363240000000003, -5.05869, -3.9306149999999986, -5.343, -5.391165000000003, 3.7026600000000047, 6.625515, 2.655119999999998, 3.41269499999999, 2.6391300000000038, 1.6097250000000014, 4.261529999999995, 4.567680000000005, 2.9253900000000033, 0.49959000000000175, -2.507504999999999, -1.9338149999999994, -1.3796249999999985, -0.9486749999999986, -0.40696499999999713, -0.777074999999998, 0.06454500000000163, -0.6526649999999987, -0.38570999999999644, 1.9037850000000085, 2.131740000000002, 1.4628899999999994, 0.808860000000001, 3.1599749999999944, 2.523105000000004, 1.9642349999999982, 2.1529949999999993, 1.9862699999999998, 2.336684999999999, 3.267810000000004, 4.179825000000005, 6.483749999999997, 8.659170000000007, 8.487569999999984, 10.706280000000012, 8.105955000000005, 10.38647999999999, 9.809475000000006, 8.081579999999999, 9.064379999999979, 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1.574234999999991], [0.0, -0.5208450000000298, 0.03724500000002351, 1.8493800000000036, 3.216719999999995, 1.8661500000000615, 1.4818049999999943, 3.200924999999998, 8.89785000000002, 4.648604999999996, -0.4738499999999952, -6.514949999999978, -9.39509999999999, -7.155134999999996, -6.834750000000026, -3.837209999999981, 2.1607949999999505, 5.5358549999999696, 3.548024999999953, -1.5613650000000234, -1.2296700000000342, 4.797389999999947, 0.9416549999999688, -4.090319999999995, 0.0027299999999677027, 2.797469999999965, 4.453215, 0.8675550000000385, -1.0920000000000059, 1.1265150000000475, 5.567640000000058, 10.72831500000007, 12.447435000000052, 14.518335000000047, 16.28113500000006, 14.1833250000001, 13.193115000000073, 11.48238000000006, 12.726870000000059, 13.59774000000009, 7.589790000000061, 7.928505000000076, 10.084620000000033, 11.213670000000068, 15.485340000000019, 16.711890000000043, 14.968785000000093, 11.118899999999993, 12.925575000000013, 12.581595000000018, 12.754365000000004, 16.089645000000058, 16.934580000000036, 11.313315000000063, 7.097220000000075, 6.5791050000000375, 6.711900000000011, 9.303840000000022, 12.148305000000033, 14.849250000000008, 13.409955000000043, 13.364909999999998, 10.235160000000011, 12.23527500000004, 15.521025000000026, 14.81902500000005, 11.40594000000004, 10.351185000000061, 5.003895000000032, 0.2735850000000468, 0.0450450000000302, -1.459379999999971, -1.3022099999999703, 1.9404449999999969, -0.5715449999999684, -1.6849949999999723, -5.03177999999998, -6.5845649999999765, -7.079474999999977, -9.070424999999986, -10.522589999999965, -10.81450499999999], [0.0, 0.7940399999999972, 1.6436550000000025, -1.0436400000000177, -0.8478600000000167, 1.8509399999999987, 2.104440000000001, 1.8070649999999953, 0.5381999999999998, 2.010645000000009, 5.656170000000026, 10.02046500000002, 10.949445000000017, 7.194135000000018, 7.9189500000000175, 7.892625000000019, 5.527665000000024, 6.314685000000022, 8.307780000000019, 11.883495000000025, 13.238745000000021, 10.241790000000018, 9.96391500000002, 12.612405000000019, 12.006150000000023, 9.913410000000018, 9.355515000000018, 9.07315500000002, 8.931975000000019, 8.36569500000002, 11.20957500000002, 12.283050000000022, 11.74836000000003, 10.973235000000019, 9.359805000000017, 7.358130000000015, 6.740955000000022, 4.432155000000025, 5.159700000000017, 6.081270000000024, 2.624700000000022, 1.260675000000015, 4.4157750000000275, 7.945665000000021, 8.571615000000019, 10.84843500000002, 6.961695000000018, 4.136535000000013, 3.401385000000018, 3.6320700000000246, 4.308525000000019, 6.318000000000023, 9.39705000000002, 7.648485000000016, 3.5222850000000214, 5.103540000000017, 3.3692100000000185, 9.390810000000018, 15.789345000000004, 12.726675000000023, 10.905570000000019, 10.246275000000018, 6.817590000000017, 7.252245000000022, 6.982560000000019, 11.660025000000026, 11.783265000000021, 12.597000000000032, 10.009545000000017, 6.775665000000026, 9.148620000000019, 7.537335000000016, 6.577545000000025, 8.71045500000002, 8.464950000000021, 7.062705000000017, 5.046210000000021, 5.3506050000000185, 6.204120000000021, 5.715060000000028, 5.790915000000026, 6.362460000000022], ...]

... and 3004 more rows.

session_id: 742951821

institution: Allen Institute for Brain Science

stimulus_notes: brain_observatory_1.1

### uncomment these to view aspects of the file

### not all of these exist for all NWB files (Key Errors will arise if the fields don't exist for this file)

# nwb.identifier
# nwb.processing
# nwb.acquisition["events"]
# nwb.intervals["trials"]
# nwb.stimulus["StimulusPresentation"]
# nwb.electrodes

OpenScope’s File Schemas

OpenScope works with two main types of brain data files for different experiments. There’s Extracellular Electrophysiology, Ecephys, which uses Neuropixels probes to gather electrical data, and Optical Physiology, Ophys, which uses 2-Photon Calcium imaging to gather fluorescence data. Since the NWB Standard is very flexible, and these files are used for different needs, there are several differences between these data types. These table schemas were made as comprehensive descriptions of what goes in our NWB files. Below, Pandas is used to display a general outline for each file type where every field within the NWB file is described. Note that NWB files or files from other institutions could vary from these significantly. These tables are just meant to be used as a reference, don’t be overwhelmed trying to understand all the fields!

# change pandas settings to show whole table
pd.set_option('display.max_rows', None)
pd.set_option('display.width', None)
pd.set_option('display.max_colwidth', -1)

Ecephys File

pd.read_csv("../../data/ecephys_schema.csv")

	Section	Field	Type	Path	Definition
0	NaN	Session Description	string	nwb.session_description	Description of the Session
1	NaN	Session Identifier	string	nwb.identifier	Unique identifier of the session
2	NaN	Session Start Time	datetime	nwb.session_start_time	Datetime start of the session
3	NaN	Reference Time	datetime	nwb.timestamps_reference_time	Time that all timestamps are in reference to
4	NaN	Experiment Description	string	nwb.experiment_description	Description of the experiment
5	NaN	Institution	string	nwb.institution	Name of the institution that produced these data
6	acquisition	Corneal Reflection Tracking Comments	string	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.comments	Comments
7	acquisition	Corneal Reflection Tracking Conversion	number	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.conversion	Scalar to multiply each element in data to convert it to the specified unit
8	acquisition	Corneal Reflection Tracking Description	string	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.description	Description
9	acquisition	Corneal Reflection Tracking Interval	number	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.interval	Unexplained
10	acquisition	Corneal Reflection Tracking Offset	number	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
11	acquisition	Corneal Reflection Tracking Reference Frame	string	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.reference_frame	Unexplained
12	acquisition	Corneal Reflection Tracking Resolution	number	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.resolution	The smallest meaningful difference (in specified unit) between values in data
13	acquisition	Corneal Reflection Tracking Unit	string	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.unit	Name of the unit for the data
14	acquisition	Corneal Reflection Tracking Angle	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.angle	Angle of the eye in degrees over time as calculated with corneal reflection tracking
15	acquisition	Corneal Reflection Tracking Height	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.height	Height of the cornea, in pixels, over time as calculated with corneal reflection tracking
16	acquisition	Corneal Reflection Tracking Width	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.width	Width of the cornea, in pixels, over time as calculated with corneal reflection tracking
17	acquisition	Corneal Reflection Tracking Area	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.area	Area of the cornea, in pixels, over time as calculated with corneal reflection tracking and with outliers removed. Should generally be equal to corneal reflection tracking height times corneal reflection tracking width
18	acquisition	Corneal Reflection Tracking Raw Area	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.area_raw	Area of the cornea, in pixels, over time as calculated with corneal reflection tracking. Should be equal to corneal reflection tracking height times corneal reflection tracking width.
19	acquisition	Corneal Reflection Tracking Data	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.data	2D array consisting of the X and Y locations of the eye, in pixels, over time as calculated by corneal reflection tracking
20	acquisition	Corneal Reflection Tracking Timestamps	array	nwb.acquisition["EyeTracking"].corneal_reflection_tracking.timestamps	Timestamps of the corneal reflection tracking arrays
21	acquisition	Eye Tracking Tracking Comments	string	nwb.acquisition["EyeTracking"].eye_tracking.comments	Comments
22	acquisition	Eye Tracking Conversion	number	nwb.acquisition["EyeTracking"].eye_tracking.conversion	Scalar to multiply each element in data to convert it to the specified unit
23	acquisition	Eye Tracking Description	string	nwb.acquisition["EyeTracking"].eye_tracking.description	Description
24	acquisition	Eye Tracking Interval	number	nwb.acquisition["EyeTracking"].eye_tracking.interval	Unexplained
25	acquisition	Eye Tracking Offset	number	nwb.acquisition["EyeTracking"].eye_tracking.offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
26	acquisition	Eye Tracking Reference Frame	string	nwb.acquisition["EyeTracking"].eye_tracking.reference_frame	Unexplained
27	acquisition	Eye Tracking Resolution	number	nwb.acquisition["EyeTracking"].eye_tracking.resolution	The smallest meaningful difference (in specified unit) between values in data
28	acquisition	Eye Tracking Unit	string	nwb.acquisition["EyeTracking"].eye_tracking.unit	Name of the unit for the data
29	acquisition	Eye Tracking Angle	array	nwb.acquisition["EyeTracking"].eye_tracking.angle	Angle of the eye in degrees over time as calculated with eye tracking
30	acquisition	Eye Tracking Height	array	nwb.acquisition["EyeTracking"].eye_tracking.height	Height of the eye, in pixels, over time as calculated with eye tracking
31	acquisition	Eye Tracking Width	array	nwb.acquisition["EyeTracking"].eye_tracking.width	Width of the eye, in pixels, over time as calculated with eye tracking
32	acquisition	Eye Tracking Area	array	nwb.acquisition["EyeTracking"].eye_tracking.area	Area of the eye, in pixels, over time as calculated with eye tracking with outliers removed. Should generally be equal to eye tracking height times eye tracking width
33	acquisition	Eye Tracking Raw Area	array	nwb.acquisition["EyeTracking"].eye_tracking.area_raw	Area of the eye, in pixels, over time as calculated with eye tracking. Should be equal to eye tracking height times eye tracking width
34	acquisition	Eye Tracking Data	array	nwb.acquisition["EyeTracking"].eye_tracking.data	2D array consisting of the X and Y locations of the eye, in pixels, over time as calculated by eye tracking
35	acquisition	Eye Tracking Timestamps	array	nwb.acquisition["EyeTracking"].eye_tracking.timestamps	Timestamps of the eye tracking arrays
36	acquisition	Eye Tracking Tracking Comments	string	nwb.acquisition["EyeTracking"].pupil_tracking.comments	Comments
37	acquisition	Eye Tracking Conversion	number	nwb.acquisition["EyeTracking"].pupil_tracking.conversion	Scalar to multiply each element in data to convert it to the specified unit
38	acquisition	Eye Tracking Description	string	nwb.acquisition["EyeTracking"].pupil_tracking.description	Description
39	acquisition	Eye Tracking Interval	number	nwb.acquisition["EyeTracking"].pupil_tracking.interval	Unexplained
40	acquisition	Eye Tracking Offset	number	nwb.acquisition["EyeTracking"].pupil_tracking.offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
41	acquisition	Eye Tracking Reference Frame	string	nwb.acquisition["EyeTracking"].pupil_tracking.reference_frame	Unexplained
42	acquisition	Eye Tracking Resolution	number	nwb.acquisition["EyeTracking"].pupil_tracking.resolution	The smallest meaningful difference (in specified unit) between values in data
43	acquisition	Eye Tracking Unit	string	nwb.acquisition["EyeTracking"].pupil_tracking.unit	Name of the unit for the data
44	acquisition	Pupil Tracking Angle	array	nwb.acquisition["EyeTracking"].pupil_tracking.angle	Angle of the pupil in degrees over time as calculated with pupil tracking
45	acquisition	Pupil Tracking Height	array	nwb.acquisition["EyeTracking"].pupil_tracking.height	Height of the pupil, in pixels, over time as calculated with pupil tracking
46	acquisition	Pupil Tracking Width	array	nwb.acquisition["EyeTracking"].pupil_tracking.width	Width of the pupil, in pixels, over time as calculated with pupil tracking
47	acquisition	Pupil Tracking Area	array	nwb.acquisition["EyeTracking"].pupil_tracking.area	Area of the pupil, in pixels, over time as calculated with pupil tracking and with outliers removed. Should generally be equal to pupil tracking height times pupil tracking width
48	acquisition	Pupil Tracking Raw Area	array	nwb.acquisition["EyeTracking"].pupil_tracking.area_raw	Area of the pupil, in pixels, over time as calculated with pupil tracking. Should be equal to pupil tracking height times pupil tracking width
49	acquisition	Pupil Tracking Data	array	nwb.acquisition["EyeTracking"].pupil_tracking.data	2D array consisting of the X and Y locations of the pupil, in pixels, over time as calculated by eye tracking
50	acquisition	Pupil Tracking Timestamps	array	nwb.acquisition["EyeTracking"].pupil_tracking.timestamps	Timestamps of the pupil tracking arrays
51	acquisition	Blink Times	array	nwb.acquisition["EyeTracking"].likely_blink.data	Array of booleans indicating probable blink times
52	acquisition	Blink Times Timestamps	array	nwb.acquisition["EyeTracking"].likely_blink.timestamps	Timestamps of the blink times array
53	acquisition	Running Wheel Rotation Comments	string	nwb.acquisition["raw_running_wheel_rotation"].comments	Comments
54	acquisition	Running Wheel Rotation Conversion	number	nwb.acquisition["raw_running_wheel_rotation"].conversion	Scalar to multiply each element in data to convert it to the specified unit
55	acquisition	Running Wheel Rotation Description	string	nwb.acquisition["raw_running_wheel_rotation"].description	Description
56	acquisition	Running Wheel Rotation Interval	number	nwb.acquisition["raw_running_wheel_rotation"].interval	Unexplained
57	acquisition	Running Wheel Rotation Offset	number	nwb.acquisition["raw_running_wheel_rotation"].offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
58	acquisition	Running Wheel Rotation Resolution	string	nwb.acquisition["raw_running_wheel_rotation"].resolution	The smallest meaningful difference (in specified unit) between values in data
59	acquisition	Running Wheel Rotation Timestamps Units	number	nwb.acquisition["raw_running_wheel_rotation"].timestamps_unit	Nameof the unit for the timestamps
60	acquisition	Running Wheel Rotation Unit	string	nwb.acquisition["raw_running_wheel_rotation"].unit	Name of the unit for the data
61	acquisition	Raw Running Wheel Rotation Data	array	nwb.acquisition["raw_running_wheel_rotation"].data	Speed of the running wheel, measured at each timestamps. The data is raw (cm/s).
62	acquisition	Raw Running Wheel Rotation Timestamps	array	nwb.acquisition["raw_running_wheel_rotation"].timestamps	Timestamps of the unfiltered running speed.
63	acquisition	Running Wheel Signal Voltage Conversion	string	nwb.acquisition["running_wheel_signal_voltage"].comments	Comments
64	acquisition	Running Wheel Signal Voltage Description	number	nwb.acquisition["running_wheel_signal_voltage"].conversion	Scalar to multiply each element in data to convert it to the specified unit
65	acquisition	Running Wheel Signal Voltage Interval	string	nwb.acquisition["running_wheel_signal_voltage"].description	Description
66	acquisition	Running Wheel Signal Voltage Offset	number	nwb.acquisition["running_wheel_signal_voltage"].interval	Unexplained
67	acquisition	Running Wheel Signal Voltage Resolution	number	nwb.acquisition["running_wheel_signal_voltage"].offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
68	acquisition	Running Wheel Signal Voltage Timestamps Units	string	nwb.acquisition["running_wheel_signal_voltage"].resolution	The smallest meaningful difference (in specified unit) between values in data
69	acquisition	Running Wheel Signal Voltage Unit	number	nwb.acquisition["running_wheel_signal_voltage"].timestamps_unit	Nameof the unit for the timestamps
70	acquisition	Running Wheel Signal Voltage Comments	string	nwb.acquisition["running_wheel_signal_voltage"].unit	Name of the unit for the data
71	acquisition	Running Wheel Signal Voltage Data	array	nwb.acquisition["running_wheel_signal_voltage"].data	Unused
72	acquisition	Running Wheel Signal Voltage Timestamps	array	nwb.acquisition["running_wheel_signal_voltage"].timestamps	Unused
73	acquisition	Running Wheel Supply Voltage Conversion	string	nwb.acquisition["running_wheel_supply_voltage"].comments	Comments
74	acquisition	Running Wheel Supply Voltage Description	number	nwb.acquisition["running_wheel_supply_voltage"].conversion	Scalar to multiply each element in data to convert it to the specified unit
75	acquisition	Running Wheel Supply Voltage Interval	string	nwb.acquisition["running_wheel_supply_voltage"].description	Description
76	acquisition	Running Wheel Supply Voltage Offset	number	nwb.acquisition["running_wheel_supply_voltage"].interval	Unexplained
77	acquisition	Running Wheel Supply Voltage Resolution	number	nwb.acquisition["running_wheel_supply_voltage"].offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
78	acquisition	Running Wheel Supply Voltage Timestamps Units	string	nwb.acquisition["running_wheel_supply_voltage"].resolution	The smallest meaningful difference (in specified unit) between values in data
79	acquisition	Running Wheel Supply Voltage Unit	number	nwb.acquisition["running_wheel_supply_voltage"].timestamps_unit	Nameof the unit for the timestamps
80	acquisition	Running Wheel Supply Voltage Comments	string	nwb.acquisition["running_wheel_supply_voltage"].unit	Name of the unit for the data
81	acquisition	Running Wheel Supply Voltage Data	array	nwb.acquisition["running_wheel_supply_voltage"].data	Unused
82	acquisition	Running Wheel Supply Voltage Timestamps	array	nwb.acquisition["running_wheel_supply_voltage"].timestamps	Unused
83	acquisition	LFP Comments	string	nwb.acquisition["probe_0_lfp"].electrical_series.comments	Comments
84	acquisition	LFP Conversion	number	nwb.acquisition["probe_0_lfp"].electrical_series.conversion	Scalar to multiply each element in data to convert it to the specified unit
85	acquisition	LFP Description	string	nwb.acquisition["probe_0_lfp"].electrical_series.description	Description
86	acquisition	LFP Interval	number	nwb.acquisition["probe_0_lfp"].electrical_series.interval	Unexplained
87	acquisition	LFP Offset	number	nwb.acquisition["probe_0_lfp"].electrical_series.offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
88	acquisition	LFP Resolution	string	nwb.acquisition["probe_0_lfp"].electrical_series.resolution	The smallest meaningful difference (in specified unit) between values in data
89	acquisition	LFP Timestamps Unit	number	nwb.acquisition["probe_0_lfp"].electrical_series.timestamps_unit	Nameof the unit for the timestamps
90	acquisition	LFP Unit	string	nwb.acquisition["probe_0_lfp"].electrical_series.unit	Name of the unit for the data
91	acquisition	Probe LFP Data	array	nwb.acquisition["lfp"].electrical_series[probe_name].data	n * t array of measured LFP values where n is the number of channels and t is the number of timestamps
92	acquisition	Probe LFP Timestamps	array	nwb.acquisition["lfp"].electrical_series[probe_name].timestamps	array of timestamps for LFP data
93	devices	Probe Description	string	nwb.devices[probe_name].description	Description of this probe
94	devices	Probe Manufacturer	string	nwb.devices[probe_name].manufacturer	Manufacturer of this probe
95	devices	Probe ID	number	nwb.devices[probe_name].probe_id	Unique identifier of the probe
96	devices	Probe Sampling Rate	number	nwb.devices[probe_name].sampling_rate	Sampling rate of the recording session with this probe
97	electrodes	Electrode Column Names	array	nwb.electrodes.colnames	Column names of the electrodes table
98	electrodes	Electrode IDs	array	nwb.electrodes.id	IDs column of the electrodes table
99	electrodes	Electrode X Coordinates	array	nwb.electrodes.x	CCF X coordinates column of the electrodes table. Represents the X location of electrodes along a probe.
100	electrodes	Electrode Y Coordinates	array	nwb.electrodes.y	CCF Y coordinates column of the electrodes table. Represents the Y location of electrodes along a probe.
101	electrodes	Electrode Z Coordinates	array	nwb.electrodes.z	CCF Z coordinates column of the electrodes table. Represents the Z location of electrodes along a probe.
102	electrodes	Impedance	array	nwb.electrodes.imp	Impedance column of the electrodes table. Unused in our data.
103	electrodes	Electrode Locations	array	nwb.electrodes.location	Brain region acronyms column of the electrodes table
104	electrodes	Electrode Filters	array	nwb.electrodes.filtering	Column of the electrodes table describing the list of filters applied to each electrode.
105	electrodes	Electrode Groups	array	nwb.electrodes.group	References to group object column of the electrodes table
106	electrodes	Electrode Group Names	array	nwb.electrodes.group_name	Group names (probe names) column of the electrodes table
107	electrodes	Electrode Probe Horizontal Position	array	nwb.electrodes.probe_vertical_position	Probe vertical positions column of the electrodes table
108	electrodes	Electrode Probe Vertical Position	array	nwb.electrodes.probe_horizontal_position	Probe horizontal positions column of the electrodes table
109	electrodes	Electrode Probe IDs	array	nwb.electrodes.probe_id	Probe IDs column of the electrodes table
110	electrodes	Electrode Local Indices	array	nwb.electrodes.local_index	Column of the electrodes table that contains local indices of electrodes within their own probe
111	electrodes	Electrode Valid Data Flags	array	nwb.electrodes.valid_data	Valid data flags column of the electrodes table
112	electrodes	Electrode Description	string	nwb.electrodes.description	Description of the electrodes table
113	electrode_groups	Electrode Group Description	string	nwb.electrode_groups[probeX].description	Description of this electrode group
114	electrode_groups	Electrode Group Device	Device	nwb.electrode_groups[probeX].device	Reference to the device information for this electrode group
115	electrode_groups	Electrode Group Has LFP Flag	boolean	nwb.electrode_groups[probeX].has_lfp	Flag indicating if this electrode group has LFP data
116	electrode_groups	Electrode Group Sampling Rate	number	nwb.electrode_groups[probeX].lfp_sampling_rate	Sampling rate of this group's LFP data
117	electrode_groups	Electrode Group Location	string	nwb.electrode_groups[probeX].location	Brain location acronym of this electrode group
118	electrode_groups	Electrode Group Probe ID	number	nwb.electrode_groups[probeX].probe_id	Probe Identifier of this electrode group
119	file_create_date	File Creation Date	number	nwb.file_create_date	Datetime time this file was created
120	intervals	Stimulus Interval IDs	array	nwb.intervals[stimulus].id	IDs column of the stimulus table
121	intervals	Stimulus Interval Start Times	array	nwb.intervals[stimulus].start_time	Column of start times of each interval in the stimulus table
122	intervals	Stimulus Interval Stop Times	array	nwb.intervals[stimulus].stop_time	Column of stop times of each interval in the stimulus table
123	intervals	Stimulus Interval Stimulus Names	array	nwb.intervals[stimulus].stimulus_name	Column of names of stimulus types for each interval of the stimulus table
124	intervals	Stimulus Interval Stimulus Blocks	array	nwb.intervals[stimulus].stimulus_block	Numbers representing stimulus blocks column of the stimulus table
125	intervals	Stimulus Interval Stimulus Frames	array	nwb.intervals[stimulus].frame	Column of the stimulus table consisting of frame numbers of the stimulus
126	intervals	Stimulus Interval Stimulus Indices	array	nwb.intervals[stimulus].stimulus_index	Column of the stimulus table which contains the stimulus index for each interval
127	intervals	Stimulus Interval Tags	array	nwb.intervals[stimulus].tags	Column of the stimulus table which contains a list of tags for each interval
128	intervals	Stimulus Interval Timeseries Link	array	nwb.intervals[stimulus].timeseries	Column of the stimulus table containing tuples of the form (i, c, r) where r is a reference to the complete timestamps array for the session, and i is the index within that array
129	intervals	Stimulus Intervals Description	string	nwb.intervals[stimulus].description	Description of the stimulus table
130	invalid_times	Invalid Times IDs	array	nwb.invalid_times.id	IDs column of the invalid times table
131	invalid_times	Invalid Times Start Times	array	nwb.invalid_times.start_time	Start times column of the invalid times table
132	invalid_times	Invalid Times Stop Times	array	nwb.invalid_times.stop_time	Stop times column of the invalid times table
133	invalid_times	Invalid Times Tags	array	nwb.invalid_times.tags	Tags column of the invalid times table
134	invalid_times	Invalid Times Description	string	nwb.invalid_times.description	Description of the invalid times table
135	processing	Optogenetic Stimulus Column Names	array	nwb.processing["optotagging"]["optogenetic_stimulation"].colname	Column names of the optogenetic stimulation table
136	processing	Optogenetic Stimulus IDs	array	nwb.processing["optotagging"]["optogenetic_stimulation"].id	IDs column of the optogenetic stimulation table
137	processing	Optogenetic Stimulus Start Times	array	nwb.processing["optotagging"]["optogenetic_stimulation"].start_time	Column of the stop times of the laser for each interval in the optogenetic stimulation table
138	processing	Optogenetic Stimulus Stop Times	array	nwb.processing["optotagging"]["optogenetic_stimulation"].stop_time	Column of the start times of the laser for each interval in the optogenetic stimulation table
139	processing	Optogenetic Stimulus Conditions	array	nwb.processing["optotagging"]["optogenetic_stimulation"].condition	Laser condition column of the optogenetic stimulation table
140	processing	Optogenetic Stimulus Levels	array	nwb.processing["optotagging"]["optogenetic_stimulation"].level	Laser voltage level column of the optogenetic stimulation table
141	processing	Optogenetic Stimulus Names	array	nwb.processing["optotagging"]["optogenetic_stimulation"].stimulus_name	Stimulus name column of the optogenetic stimulation table
142	processing	Optogenetic Stimulus Duration	array	nwb.processing["optotagging"]["optogenetic_stimulation"].duration	Laser duration column of the optogenetic stimulation table
143	processing	Optogenetic Stimulus Tags	array	nwb.processing["optotagging"]["optogenetic_stimulation"].tags	Tags column of the optogenetic stimulation table
144	processing	Optogenetic Stimulus Timeseries Links	array	nwb.processing["optotagging"]["optogenetic_stimulation"].timeseries	Timeseries reference column of the optogenetic stimulation table
145	processing	Optotagging Data	array	nwb.processing["optotagging"]["optotagging"].data	Period of the optotagging light oscilation (s)
146	processing	Optotagging Timestamps	array	nwb.processing["optotagging"]["optotagging"].timestamps	Array of timestamps for the optotagging pulses
147	processing	Running Speed Comments	string	nwb.processing["running"]["running_speed"].comments	Comments
148	processing	Running Speed Conversion	number	nwb.processing["running"]["running_speed"].conversion	Scalar to multiply each element in data to convert it to the specified unit
149	processing	Running Speed Description	string	nwb.processing["running"]["running_speed"].description	Description
150	processing	Running Speed Interval	number	nwb.processing["running"]["running_speed"].interval	Unexplained
151	processing	Running Speed Offset	number	nwb.processing["running"]["running_speed"].offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
152	processing	Running Speed Resolution	string	nwb.processing["running"]["running_speed"].resolution	The smallest meaningful difference (in specified unit) between values in data
153	processing	Running Speed Timestamps Units	number	nwb.processing["running"]["running_speed"].timestamps_unit	Nameof the unit for the timestamps
154	processing	Running Speed Unit	string	nwb.processing["running"]["running_speed"].unit	Name of the unit for the data
155	processing	Running Speed Data	array	nwb.processing["running"]["running_speed"].data	Speed of the running wheel, measured at each timestamps. The data is filtered with a low-pass filter to remove noise artifacts (cm/s).
156	processing	Running Speed Timestamps	array	nwb.processing["running"]["running_speed"].timestamps	Array of timestamps for the running_speed array
157	processing	Running Speed End Times Comments	string	nwb.processing["running"]["running_speed_end_times"].comments	Comments
158	processing	Running Speed End Times Conversion	number	nwb.processing["running"]["running_speed_end_times"].conversion	Scalar to multiply each element in data to convert it to the specified unit
159	processing	Running Speed End Times Description	string	nwb.processing["running"]["running_speed_end_times"].description	Description
160	processing	Running Speed End Times Interval	number	nwb.processing["running"]["running_speed_end_times"].interval	Unexplained
161	processing	Running Speed End Times Offset	number	nwb.processing["running"]["running_speed_end_times"].offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
162	processing	Running Speed End Times Resolution	string	nwb.processing["running"]["running_speed_end_times"].resolution	The smallest meaningful difference (in specified unit) between values in data
163	processing	Running Speed End Times Timestamps Units	number	nwb.processing["running"]["running_speed_end_times"].timestamps_unit	Nameof the unit for the timestamps
164	processing	Running Speed End Times Unit	string	nwb.processing["running"]["running_speed_end_times"].unit	Name of the unit for the data
165	processing	Running Speed End Times Data	array	nwb.processing["running"]["running_speed_end_times"].data	The times that each measurement period for the running speed end. Should be the same as Running Speed Timestamps but with indices offset by 1.
166	processing	Running Speed End Times Timestamps	array	nwb.processing["running"]["running_speed_end_times"].timestamps	Same as Running Speed End times Data
167	processing	Running Wheel Rotation Comments	string	nwb.processing["running"]["running_wheel_rotation"].comments	Comments
168	processing	Running Wheel Rotation Conversion	number	nwb.processing["running"]["running_wheel_rotation"].conversion	Scalar to multiply each element in data to convert it to the specified unit
169	processing	Running Wheel Rotation Description	string	nwb.processing["running"]["running_wheel_rotation"].description	Description
170	processing	Running Wheel Rotation Interval	number	nwb.processing["running"]["running_wheel_rotation"].interval	Unexplained
171	processing	Running Wheel Rotation Offset	number	nwb.processing["running"]["running_wheel_rotation"].offset	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.
172	processing	Running Wheel Rotation Resolution	string	nwb.processing["running"]["running_wheel_rotation"].resolution	The smallest meaningful difference (in specified unit) between values in data
173	processing	Running Wheel Rotation Timestamps Units	number	nwb.processing["running"]["running_wheel_rotation"].timestamps_unit	Nameof the unit for the timestamps
174	processing	Running Wheel Rotation Unit	string	nwb.processing["running"]["running_wheel_rotation"].unit	Name of the unit for the data
175	processing	Running Wheel Rotation Data	array	nwb.processing["running"]["running_wheel_rotation"].data	Position of the running wheel, measured at each timestamps.
176	processing	Running Wheel Rotation Timestamps	array	nwb.processing["running"]["running_wheel_rotation"].timestamps	Array of timestamps for the running_wheel_rotation array
177	processing	Stimulus Timestamps Data	array	nwb.processing["stimulus"]["timestamps"].data	Array of all the the stimulus timestamps during the session. Identical to Stimulus Timestamps Timestamps
178	processing	Stimulus Timestamps Timestamps	array	nwb.processing["stimulus"]["timestamps"].timestamps	Array of all the the stimulus timestamps during the session. Identical to Stimulus Timestamps Data
179	subject	Subject Age	number	nwb.subject.age	Age of the subject
180	subject	Subject Age in Days	number	nwb.subject.age_in_days	Age of the subject, in days
181	subject	Subject Genotype	string	nwb.subject.genotype	Genotype of the subject
182	subject	Subject Sex	string	nwb.subject.sex	Sex of the subject, M or F
183	subject	Subject Species	string	nwb.subject.species	Species of the subject
184	subject	Subject Specimen Name	string	nwb.subject.specimen_name	Specimen name of the subject
185	subject	Subject Strain	string	nwb.subject.strain	Strain of the subject
186	subject	Subject ID	string	nwb.subject.subject_id	Unique identifier of the subject
187	units	Unit Table Column Names	array	nwb.units.colnames	Column names of the units table
188	units	Unit IDs	array	nwb.units.id	IDs column of the units table
189	units	Unit Spreads	array	nwb.units.spread	Column of the units table consisting of the spread value for each unit
190	units	Unit PT Ratios	array	nwb.units.PT_ratio	Column of the units table consisting of the pt ratio for each unit
191	units	Unit Waveform Durations	array	nwb.units.waveform_duration	Column of the units table with the durations, in seconds, of a unit's waveform
192	units	Unit D-Primes	array	nwb.units.d_prime	Column of the units table containing the d_prime values for units.
193	units	Unit Cumulative Drifts	array	nwb.units.cumulative_drift	Column of the units table containing the cumulative drift values for units
194	units	Unit Silhouette Scores	array	nwb.units.silhouette_score	Column of the units table containing the silhouette score for units
195	units	Unit Cluster IDs	array	nwb.units.cluster_id	Column of the units table containing the cluster_id for units
196	units	Unit L Ratios	array	nwb.units.l_ratio	Column of the units table containing the l ratio for units
197	units	Unit Qualities	array	nwb.units.quality	Column of the units table with the quality, 'good' or 'noise' of each unit
198	units	Unit NN Miss Rates	array	nwb.units.nn_miss_rate	Column of the units table containing the nearest-neighbors miss rate for each unit
199	units	Unit Local Indices	array	nwb.units.local_index	Column of the units table containing the local index of each unit, where the local index is the order it was detected by kilosort
200	units	Unit Amplitude Recovery Slopes	array	nwb.units.amplitude_recovery_slope	Column of the units table containing the amplitude recovery slope for each unit
201	units	Unit SNRs	array	nwb.units.snr	Column of the units table containing the signal-to-noise ratio for each unit
202	units	Unit Velocities Above	array	nwb.units.velocity_above	Column of the units table containing the velocity above value for each unit
203	units	Unit Amplitude Cutoffs	array	nwb.units.amplitude_cutoff	Column of the units table containing the amplitude cutoff for each unit
204	units	Unit Isolation Distance	array	nwb.units.isolation_distance	Column of the units table containing the isolation distance for each unit
205	units	Unit Peak Channel IDs	array	nwb.units.peak_channel_id	Column of the units table consisting of the unique ID of the unit's peak channel that can be found in the electrodes table
206	units	Unit Velocities Below	array	nwb.units.velocity_below	Column of the units table containing the velocity below value for each unit
207	units	Unit NN Hit Rates	array	nwb.units.nn_hit_rate	Column of the units table containing the nearest-neighbors hit rate for each unit
208	units	Unit Firing Rates	array	nwb.units.firing_rate	Column of the units table containing the average firing rate for each unit
209	units	Unit ISI Violations	array	nwb.units.isi_violations	Column of the units table containing the inter-spike-interval violations for each unit
210	units	Unit Repolarization Slopes	array	nwb.units.repolarization_slope	Column of the units table containing the repolarization slope for each unit
211	units	Unit Presence Ratios	array	nwb.units.presence_ratio	Column of the units table containing the presence ratio for each unit
212	units	Unit Waveform Halfwidths	array	nwb.units.waveform_halfwidth	Column of the units table containing the average waveform halfwidth for each unit
213	units	Unit Max Drifts	array	nwb.units.max_drift	Column of the units table containing the maximum drift for each unit
214	units	Unit Spike Times	array	nwb.units.spike_times	Column of the units table consisting of the arrays of spike times for each unit. Should be same length as spikje amplitudes array
215	units	Unit Spike Amplitudes	array	nwb.units.spike_amplitudes	Column of the units table consisting of arrays of spike amplitudes for each unit. Should be same length as spike times array
216	units	Unit Waveform Means	array	nwb.units.waveform_mean	Column of mean waveforms for each unit. Each unit mean_waveform should be a 2D array with dimensions n*t where n is the number of channels and t is the time
217	units	Unit Waveform Halfwidths	array	nwb.units.waveform_halfwidth	Column of the units table containing the average waveform halfwidth for each unit
218	units	Unit Max Drifts	array	nwb.units.max_drift	Column of the units table containing the maximum drift for each unit
219	units	Unit Spike Times	array	nwb.units.spike_times	Column of the units table consisting of the arrays of spike times for each unit. Should be same length as spikje amplitudes array
220	units	Unit Spike Amplitudes	array	nwb.units.spike_amplitudes	Column of the units table consisting of arrays of spike amplitudes for each unit. Should be same length as spike times array
221	units	Unit Waveform Means	array	nwb.units.waveform_mean	Column of mean waveforms for each unit. Each unit mean_waveform should be a 2D array with dimensions n*t where n is the number of channels and t is the time

Ophys File

pd.read_csv("../../data/ophys_schema.csv")

	Section	Field	Type	Path	Definition	Unnamed: 5
0	NaN	Session Description	string	nwb.session_description	Description of the Session	NaN
1	NaN	Session Identifier	string	nwb.identifier	Unique identifier of the session	NaN
2	NaN	Session Start Time	datetime	nwb.session_start_time	Datetime start of the session	NaN
3	NaN	Reference Time	datetime	nwb.timestamps_reference_time	Time that all timestamps are in reference to	NaN
4	NaN	Experiment Description	string	nwb.experiment_description	Description of the experiment	NaN
5	NaN	Institution	string	nwb.institution	Name of the institution that produced these data	NaN
6	acquisition	Corneal Reflection Tracking Comments	string	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.comments"	Comments	NaN
7	acquisition	Corneal Reflection Tracking Conversion	number	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
8	acquisition	Corneal Reflection Tracking Description	string	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.description"	Description	NaN
9	acquisition	Corneal Reflection Tracking Interval	number	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.interval"	Unexplained	NaN
10	acquisition	Corneal Reflection Tracking Offset	number	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
11	acquisition	Corneal Reflection Tracking Reference Frame	string	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.reference_frame"	Unexplained	NaN
12	acquisition	Corneal Reflection Tracking Resolution	number	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
13	acquisition	Corneal Reflection Tracking Unit	string	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.unit"	Name of the unit for the data	NaN
14	acquisition	Corneal Reflection Tracking Angle	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.angle"	Angle of the eye in degrees over time as calculated with corneal reflection tracking	NaN
15	acquisition	Corneal Reflection Tracking Height	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.height"	Height of the cornea, in pixels, over time as calculated with corneal reflection tracking	NaN
16	acquisition	Corneal Reflection Tracking Width	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.width"	Width of the cornea, in pixels, over time as calculated with corneal reflection tracking	NaN
17	acquisition	Corneal Reflection Tracking Area	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.area"	Area of the cornea, in pixels, over time as calculated with corneal reflection tracking and with outliers removed. Should generally be equal to corneal reflection tracking height times corneal reflection tracking width	NaN
18	acquisition	Corneal Reflection Tracking Raw Area	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.area_raw"	Area of the cornea, in pixels, over time as calculated with corneal reflection tracking. Should be equal to corneal reflection tracking height times corneal reflection tracking width.	NaN
19	acquisition	Corneal Reflection Tracking Data	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.data"	2D array consisting of the X and Y locations of the eye, in pixels, over time as calculated by corneal reflection tracking	NaN
20	acquisition	Corneal Reflection Tracking Timestamps	array	nwb.acquisition[EyeTracking"].corneal_reflection_tracking.timestamps"	Timestamps of the corneal reflection tracking arrays	NaN
21	acquisition	Eye Tracking Tracking Comments	string	nwb.acquisition[EyeTracking"].eye_tracking.comments"	Comments	NaN
22	acquisition	Eye Tracking Conversion	number	nwb.acquisition[EyeTracking"].eye_tracking.conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
23	acquisition	Eye Tracking Description	string	nwb.acquisition[EyeTracking"].eye_tracking.description"	Description	NaN
24	acquisition	Eye Tracking Interval	number	nwb.acquisition[EyeTracking"].eye_tracking.interval"	Unexplained	NaN
25	acquisition	Eye Tracking Offset	number	nwb.acquisition[EyeTracking"].eye_tracking.offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
26	acquisition	Eye Tracking Reference Frame	string	nwb.acquisition[EyeTracking"].eye_tracking.reference_frame"	Unexplained	NaN
27	acquisition	Eye Tracking Resolution	number	nwb.acquisition[EyeTracking"].eye_tracking.resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
28	acquisition	Eye Tracking Unit	string	nwb.acquisition[EyeTracking"].eye_tracking.unit"	Name of the unit for the data	NaN
29	acquisition	Eye Tracking Angle	array	nwb.acquisition[EyeTracking"].eye_tracking.angle"	Angle of the eye in degrees over time as calculated with eye tracking	NaN
30	acquisition	Eye Tracking Height	array	nwb.acquisition[EyeTracking"].eye_tracking.height"	Height of the eye, in pixels, over time as calculated with eye tracking	NaN
31	acquisition	Eye Tracking Width	array	nwb.acquisition[EyeTracking"].eye_tracking.width"	Width of the eye, in pixels, over time as calculated with eye tracking	NaN
32	acquisition	Eye Tracking Area	array	nwb.acquisition[EyeTracking"].eye_tracking.area"	Area of the eye, in pixels, over time as calculated with eye tracking with outliers removed. Should generally be equal to eye tracking height times eye tracking width	NaN
33	acquisition	Eye Tracking Raw Area	array	nwb.acquisition[EyeTracking"].eye_tracking.area_raw"	Area of the eye, in pixels, over time as calculated with eye tracking. Should be equal to eye tracking height times eye tracking width	NaN
34	acquisition	Eye Tracking Data	array	nwb.acquisition[EyeTracking"].eye_tracking.data"	2D array consisting of the X and Y locations of the eye, in pixels, over time as calculated by eye tracking	NaN
35	acquisition	Eye Tracking Timestamps	array	nwb.acquisition[EyeTracking"].eye_tracking.timestamps"	Timestamps of the eye tracking arrays	NaN
36	acquisition	Eye Tracking Tracking Comments	string	nwb.acquisition[EyeTracking"].pupil_tracking.comments"	Comments	NaN
37	acquisition	Eye Tracking Conversion	number	nwb.acquisition[EyeTracking"].pupil_tracking.conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
38	acquisition	Eye Tracking Description	string	nwb.acquisition[EyeTracking"].pupil_tracking.description"	Description	NaN
39	acquisition	Eye Tracking Interval	number	nwb.acquisition[EyeTracking"].pupil_tracking.interval"	Unexplained	NaN
40	acquisition	Eye Tracking Offset	number	nwb.acquisition[EyeTracking"].pupil_tracking.offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
41	acquisition	Eye Tracking Reference Frame	string	nwb.acquisition[EyeTracking"].pupil_tracking.reference_frame"	Unexplained	NaN
42	acquisition	Eye Tracking Resolution	number	nwb.acquisition[EyeTracking"].pupil_tracking.resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
43	acquisition	Eye Tracking Unit	string	nwb.acquisition[EyeTracking"].pupil_tracking.unit"	Name of the unit for the data	NaN
44	acquisition	Pupil Tracking Angle	array	nwb.acquisition[EyeTracking"].pupil_tracking.angle"	Angle of the pupil in degrees over time as calculated with pupil tracking	NaN
45	acquisition	Pupil Tracking Height	array	nwb.acquisition[EyeTracking"].pupil_tracking.height"	Height of the pupil, in pixels, over time as calculated with pupil tracking	NaN
46	acquisition	Pupil Tracking Width	array	nwb.acquisition[EyeTracking"].pupil_tracking.width"	Width of the pupil, in pixels, over time as calculated with pupil tracking	NaN
47	acquisition	Pupil Tracking Area	array	nwb.acquisition[EyeTracking"].pupil_tracking.area"	Area of the pupil, in pixels, over time as calculated with pupil tracking and with outliers removed. Should generally be equal to pupil tracking height times pupil tracking width	NaN
48	acquisition	Pupil Tracking Raw Area	array	nwb.acquisition[EyeTracking"].pupil_tracking.area_raw"	Area of the pupil, in pixels, over time as calculated with pupil tracking. Should be equal to pupil tracking height times pupil tracking width	NaN
49	acquisition	Pupil Tracking Data	array	nwb.acquisition[EyeTracking"].pupil_tracking.data"	2D array consisting of the X and Y locations of the pupil, in pixels, over time as calculated by eye tracking	NaN
50	acquisition	Pupil Tracking Timestamps	array	nwb.acquisition[EyeTracking"].pupil_tracking.timestamps"	Timestamps of the pupil tracking arrays	NaN
51	acquisition	Blink Times	array	nwb.acquisition[EyeTracking"].likely_blink.data"	Array of booleans indicating probable blink times	NaN
52	acquisition	Blink Times Timestamps	array	nwb.acquisition[EyeTracking"].likely_blink.timestamps"	Timestamps of the blink times array	NaN
53	acquisition	2P Movie Data	array	nwb.acquisition[raw_suite2p_motion_corrected"].data"	3D array of the raw 2P movie where the dimensions are pixels height * pixels width * frame time	NaN
54	acquisition	2P Movie Timestamps	array	nwb.acquisition[raw_suite2p_motion_corrected"].timestamps"	Timestamps of the frames in the 2P movie	NaN
55	acquisition	2P Movie Rate	number	nwb.acquisition[raw_suite2p_motion_corrected"].rate"	Framerate of the 2P movie	NaN
56	acquisition	2P Movie Device	Device	nwb.acquisition[raw_suite2p_motion_corrected"].device"	Device that produced the 2P movie data	NaN
57	acquisition	2P Movie Imaging Plane	number	nwb.acquisition[raw_suite2p_motion_corrected"].imaging_plane"	Imaging Plane of the 2P movie	NaN
58	acquisition	Input Voltage Comments	string	nwb.acquisition[v_in"].comments"	Comments	NaN
59	acquisition	Input Voltage Conversion	number	nwb.acquisition[v_in"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
60	acquisition	Input Voltage Description	string	nwb.acquisition[v_in"].description"	Description	NaN
61	acquisition	Input Voltage Interval	number	nwb.acquisition[v_in"].interval"	Unexplained	NaN
62	acquisition	Input Voltage Offset	number	nwb.acquisition[v_in"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
63	acquisition	Input Voltage Resolution	number	nwb.acquisition[v_in"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
64	acquisition	Input Voltage Timestamps Unit	string	nwb.acquisition[v_in"].timestamps_unit"	Name of the unit for the timestamps	NaN
65	acquisition	Input Voltage Unit	string	nwb.acquisition[v_in"].unit"	Name of the unit for the data	NaN
66	acquisition	Input Voltage Data	array	nwb.acquisition[v_in"].data"	Unused	NaN
67	acquisition	Input Voltage Timestamps	array	nwb.acquisition[v_in"].timestamps"	Unused	NaN
68	acquisition	Signal Voltage Comments	string	nwb.acquisition[v_sig"].comments"	Comments	NaN
69	acquisition	Signal Voltage Conversion	number	nwb.acquisition[v_sig"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
70	acquisition	Signal Voltage Description	string	nwb.acquisition[v_sig"].description"	Description	NaN
71	acquisition	Signal Voltage Interval	number	nwb.acquisition[v_sig"].interval"	Unexplained	NaN
72	acquisition	Signal Voltage Offset	number	nwb.acquisition[v_sig"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
73	acquisition	Signal Voltage Resolution	number	nwb.acquisition[v_sig"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
74	acquisition	Signal Voltage Timestamps Unit	string	nwb.acquisition[v_sig"].timestamps_unit"	Name of the unit for the timestamps	NaN
75	acquisition	Signal Voltage Unit	string	nwb.acquisition[v_sig"].unit"	Name of the unit for the data	NaN
76	acquisition	Signal Voltage Data	array	nwb.acquisition[v_sig"].dat"	Unused	NaN
77	acquisition	Signal Voltage Timestamps	array	nwb.acquisition[v_sig"].timestamps"	Unused	NaN
78	devices	Device description	string	nwb.devices[device_name].description	Description of the device	NaN
79	file_create_date	File Creation Date	number	nwb.file_create_date	Datetime time this file was created	NaN
80	imaging_planes	Imaging Plane Description	string	nwb.imaging_planes[imaging_plane_name].description	Description of the instrument used.	NaN
81	imaging_planes	Imaging Plane Excitation Lambda	number	nwb.imaging_planes[imaging_plane_name].excitation_lambda	Peak wavelength of the light excitation given by the pulsed Ti:Sa laser (nm).	NaN
82	imaging_planes	Imaging Plane Imaging Rate	number	nwb.imaging_planes[imaging_plane_name].imaging_rate	Frame rate to record each imaged plane.	NaN
83	imaging_planes	Imaging Plane Indicator	string	nwb.imaging_planes[imaging_plane_name].indicator	Calcium indicator used to record neuronal activity.	NaN
84	imaging_planes	Imaging Plane Location	string	nwb.imaging_planes[imaging_plane_name].location	Brain area imaged during the experiemnt.	NaN
85	imaging_planes	Imaging Plane Optical Channel	OpticalChannel	nwb.imaging_planes[imaging_plane_name].optical_channel	Optical channel associated with this imaging plane. This provides a description of the fluorescence emission wavelength.	NaN
86	imaging_planes	Imaging Plane Unit	string	nwb.imaging_planes[imaging_plane_name].unit	Unit of this imaging plane	NaN
87	intervals	Stimulus Intervals Column Names	array	nwb.intervals[stimulus].colnames	Column names of the stimulus table	NaN
88	intervals	Stimulus Interval IDs	array	nwb.intervals[stimulus].id	IDs column of the stimulus table	NaN
89	intervals	Stimulus Interval Start Times	array	nwb.intervals[stimulus].start_time	Start times of the stimulus table	NaN
90	intervals	Stimulus Interval Stop Times	array	nwb.intervals[stimulus].stop_time	Stop times of the stimulus table	NaN
91	intervals	Stimulus Interval Stimulus Names	array	nwb.intervals[stimulus].stimulus_name	Names of stimulus types column of the stimulus table	NaN
92	intervals	Stimulus Interval Stimulus Blocks	array	nwb.intervals[stimulus].stimulus_block	Numbers representing stimulus blocks column of the stimulus table	NaN
93	intervals	Stimulus Interval Stimulus Frames	array	nwb.intervals[stimulus].frame	Column of the stimulus table consisting of frame numbers of the stimulus	NaN
94	intervals	Stimulus Interval Stimulus Indices	array	nwb.intervals[stimulus].stimulus_index	Column of the stimulus table which contains the stimulus index for each interval	NaN
95	intervals	Stimulus Interval Tags	array	nwb.intervals[stimulus].tags	Column of the stimulus table which contains a list of tags for each interval	NaN
96	intervals	Stimulus Interval Timeseries Link	array	nwb.intervals[stimulus].timeseries	Column of the stimulus table contain tuples of the form (i, c, r) where r is a reference to the complete timestamps array for the session, and i is the index within that array	NaN
97	intervals	Stimulus Intervals Description	string	nwb.intervals[stimulus].description	Description of the stimulus table	NaN
98	lab_meta_data	Experiment Container ID	number	nwb.lab_meta_data[metadata"].experiment_container_id"	unique id associated with all experiments that were cell-matched	NaN
99	lab_meta_data	FOV Width	number	nwb.lab_meta_data[metadata"].field_of_view_width"	Number of pixels in the horizontal direction	NaN
100	lab_meta_data	FOV Height	number	nwb.lab_meta_data[metadata"].field_of_view_height"	Number of pixels in the vertical direction	NaN
101	lab_meta_data	Imaging Depth	number	nwb.lab_meta_data[metadata"].imaging_depth"	Imaging depth from the surface of the brain in microns	NaN
102	lab_meta_data	Imaging Plane Group	number	nwb.lab_meta_data[metadata"].imaging_plane_group"	The Allen Institute mesoscope simultaneously acquire planes in pair. This number indicate which plane this experiment is associated with.	NaN
103	lab_meta_data	Imaging Plane Group Count	number	nwb.lab_meta_data[metadata"].imaging_plane_group_count"	Id of the imaging plane within the pair of simultateneously acquired planes.	NaN
104	lab_meta_data	Ophys Experiment ID	number	nwb.lab_meta_data[metadata"].ophys_experiment_id"	Unique id given to each imaging plane	NaN
105	lab_meta_data	Ophys Session ID	number	nwb.lab_meta_data[metadata"].ophys_session_id"	Unique id given to each experimental session. Multiple experiemntal ids can have the same session id.	NaN
106	processing	Fluorescence Trace Comments	string	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].comments"	Comments	NaN
107	processing	Fluorescence Trace Conversion	number	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
108	processing	Fluorescence Trace Description	string	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].description"	Description	NaN
109	processing	Fluorescence Trace Interval	number	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].interval"	Unexplained	NaN
110	processing	Fluorescence Trace Offset	number	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"]	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
111	processing	Fluorescence Trace Resolution	number	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
112	processing	Fluorescence Trace Timestamps Unit	string	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].timestamps_unit"	Name of the unit for the timestamps	NaN
113	processing	Fluorescence Trace Unit	string	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series["traces"].unit"	Name of the unit for the data	NaN
114	processing	Fluorescence Trace Data	array	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series.data"	Traces extracted from individual ROI, neuropil subtracted and demixed, but not normalized	NaN
115	processing	Fluorescence Trace Timestamps	array	nwb.processing[ophys"]["corrected_fluorescence"].roi_response_series.timestamps"	Timestamps of the corrected_fluorescence arrays	NaN
116	processing	DFF Trace Comments	string	nwb.processing[ophys"]["dff"].roi_response_series.comments"	Comments	NaN
117	processing	DFF Trace Conversion	number	nwb.processing[ophys"]["dff"].roi_response_series.conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
118	processing	DFF Trace Description	string	nwb.processing[ophys"]["dff"].roi_response_series.description"	Description	NaN
119	processing	DFF Trace Interval	number	nwb.processing[ophys"]["dff"].roi_response_series.interval"	Unexplained	NaN
120	processing	DFF Trace Offset	number	nwb.processing[ophys"]["dff"].roi_response_series.offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
121	processing	DFF Trace Resolution	number	nwb.processing[ophys"]["dff"].roi_response_series.resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
122	processing	DFF Trace Timestamps Unit	string	nwb.processing[ophys"]["dff"].roi_response_series.timestamps_unit"	Name of the unit for the timestamps	NaN
123	processing	DFF Trace Unit	string	nwb.processing[ophys"]["dff"].roi_response_series.unit"	Name of the unit for the data	NaN
124	processing	DFF Trace Data	array	nwb.processing[ophys"]["dff"].roi_response_series.data"	Traces extracted from individual ROI, baseline corrected, normalized fluorescence traces	NaN
125	processing	DFF Trace Timestamps	array	nwb.processing[ophys"]["dff"].roi_response_series.timestamps"	Timestamps of the dff arrays	NaN
126	processing	Event Detection Comments	string	nwb.processing[ophys"]["event_detection"].comments"	Comments	NaN
127	processing	Event Detection Conversion	number	nwb.processing[ophys"]["event_detection"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
128	processing	Event Detection Description	string	nwb.processing[ophys"]["event_detection"].description"	Description	NaN
129	processing	Event Detection Interval	number	nwb.processing[ophys"]["event_detection"].interval"	Unexplained	NaN
130	processing	Event Detection Offset	number	nwb.processing[ophys"]["event_detection"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
131	processing	Event Detection Resolution	number	nwb.processing[ophys"]["event_detection"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
132	processing	Event Detection Timestamps Unit	string	nwb.processing[ophys"]["event_detection"].timestamps_unit"	Name of the unit for the timestamps	NaN
133	processing	Event Detection Unit	string	nwb.processing[ophys"]["event_detection"].unit"	Name of the unit for the data	NaN
134	processing	Event Detection Data	array	nwb.processing[ophys"]["event_detection"].data"	Calcium events (detected with an L0 event detection algorithm)	NaN
135	processing	Event Detection Timestamps	array	nwb.processing[ophys"]["event_detection"].timestamps"	Timestamps of the events_detection arrays	NaN
136	processing	Event Detection Lambdas	array	nwb.processing[ophys"]["event_detection"].lambdas"	Lambda used in the event detection algorithm. lambda is chosen by finding smallest lambda such that the size of the smallest detected event is greater or equal to event_min_size*robust std of noise.	NaN
137	processing	Event Detection Standard Deviation	array	nwb.processing[ophys"]["event_detection"].noise_stds"	Estimates of the std of the noise for each trace	NaN
138	processing	ROI Table Column Names	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].colnames"	Column names of the ROI table	NaN
139	processing	ROI IDs	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].id"	Column of IDs in the ROI table	NaN
140	processing	ROI Cell Specimen IDs	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].cell_specimen_id"	Column of the ROI table consisting of the cell ID within a container for each ROI	NaN
141	processing	ROI Heights	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].height"	ROI heights, in pixels, column of the ROIs table	NaN
142	processing	ROI Mask Image Planes	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].mask_image_plane"	Column of the ROI table consisting of the index of ROIs that overlap	NaN
143	processing	ROI Max Corrections Down	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].max_correction_down"	Column of the ROI table consisting of the maximum motion correction downward for each ROI	NaN
144	processing	ROI Max Corrections Left	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].max_correction_left"	Column of the ROI table consisting of the maximum motion correction to the left for each ROI	NaN
145	processing	ROI Max Corrections Up	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].max_correction_up"	Maximum motion correction upward	NaN
146	processing	ROI Max Corrections Right	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].max_correction_right"	Maximum motion correction to the right	NaN
147	processing	ROI Valid Flags	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].valid_roi"	ROI validity flags column of the ROIs table, indicating if the ROI is classified as a cell	NaN
148	processing	ROI Widths	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].width"	ROI widths, in pixels, column of the ROI table	NaN
149	processing	ROI X Coordinates	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].x"	ROI X coordinates, in pixels, column of the ROI table	NaN
150	processing	ROI Y Coordinates	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].y"	ROI Y coordinates, in pixels, column of the ROI table	NaN
151	processing	ROI Image Masks	array	nwb.processing[ophys"]["image_segmentation"]["cell_specimen_table"].image_mask"	Column of the ROIs table consisting of the black/white segmentation mask image of each individual ROI	NaN
152	processing	2P Image Description	string	nwb.processing[ophys"]["images"].description"	Description of the Images	NaN
153	processing	2P Average Image	GrayscaleImage	nwb.processing[ophys"]["images"]["average_image"]"	Average Image of the movie from the session	NaN
154	processing	2P Max Projection	GrayscaleImage	nwb.processing[ophys"]["images"]["max_projection"]"	Maximum projection image of the movie from the session	NaN
155	processing	2P Segmentation Mask	GrayscaleImage	nwb.processing[ophys"]["images"]["segmentation_mask"]"	Black/white Segmentation mask image of all ROIs in the movie	NaN
156	processing	Ophys Motion Correction X Comments	string	nwb.processing[ophys"]["ophys_motion_correction_x"].comments"	Comments	NaN
157	processing	Ophys Motion Correction X Conversion	number	nwb.processing[ophys"]["ophys_motion_correction_x"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
158	processing	Ophys Motion Correction X Description	string	nwb.processing[ophys"]["ophys_motion_correction_x"].description"	Description	NaN
159	processing	Ophys Motion Correction X Interval	number	nwb.processing[ophys"]["ophys_motion_correction_x"].interval"	Unexplained	NaN
160	processing	Ophys Motion Correction X Offset	number	nwb.processing[ophys"]["ophys_motion_correction_x"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
161	processing	Ophys Motion Correction X Resolution	number	nwb.processing[ophys"]["ophys_motion_correction_x"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
162	processing	Ophys Motion Correction X Timestamps Unit	unit	nwb.processing[ophys"]["ophys_motion_correction_x"].timestamps_unit"	Name of the unit for the timestamps	NaN
163	processing	Ophys Motion Correction X Unit	string	nwb.processing[ophys"]["ophys_motion_correction_x"].unit"	Name of the unit for the data	NaN
164	processing	Motion Correction X Data	array	nwb.processing[ophys"]["ophys_motion_correction_x"].data"	horizontal correction applied to each frame of the two-photon raw movie using rigid-body motion correction	NaN
165	processing	Motion Correction X Timestamps	array	nwb.processing[ophys"]["ophys_motion_correction_x"].timestamps"	Array of timestamps for the motion correction arrays	NaN
166	processing	Ophys Motion Correction Y Comments	string	nwb.processing[ophys"]["ophys_motion_correction_y"].comments"	Comments	NaN
167	processing	Ophys Motion Correction Y Conversion	number	nwb.processing[ophys"]["ophys_motion_correction_y"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
168	processing	Ophys Motion Correction Y Description	string	nwb.processing[ophys"]["ophys_motion_correction_y"].description"	Description	NaN
169	processing	Ophys Motion Correction Y Interval	number	nwb.processing[ophys"]["ophys_motion_correction_y"].interval"	Unexplained	NaN
170	processing	Ophys Motion Correction Y Offset	number	nwb.processing[ophys"]["ophys_motion_correction_y"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
171	processing	Ophys Motion Correction Y Resolution	number	nwb.processing[ophys"]["ophys_motion_correction_y"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
172	processing	Ophys Motion Correction Y Timestamps Unit	string	nwb.processing[ophys"]["ophys_motion_correction_y"].timestamps_unit"	Name of the unit for the timestamps	NaN
173	processing	Ophys Motion Correction Y Unit	string	nwb.processing[ophys"]["ophys_motion_correction_y"].unit"	Name of the unit for the data	NaN
174	processing	Motion Correction Y Data	array	nwb.processing[ophys"]["ophys_motion_correction_y"].data"	Vertical correction applied to each frame of the two-photon raw movie using rigid-body motion correction	NaN
175	processing	Motion Correction Y Timestamps	array	nwb.processing[ophys"]["ophys_motion_correction_y"].timestamps"	Array of timestamps for the motion correction arrays	NaN
176	processing	Stimulus Timestamps Comments	string	nwb.processing[stimulus"]["timestamps"].comments"	Comments	NaN
177	processing	Stimulus Timestamps Conversion	number	nwb.processing[stimulus"]["timestamps"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
178	processing	Stimulus Timestamps Description	string	nwb.processing[stimulus"]["timestamps"].description"	Description	NaN
179	processing	Stimulus Timestamps Interval	number	nwb.processing[stimulus"]["timestamps"].interval"	Unexplained	NaN
180	processing	Stimulus Timestamps Offset	number	nwb.processing[stimulus"]["timestamps"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
181	processing	Stimulus Timestamps Resolution	number	nwb.processing[stimulus"]["timestamps"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
182	processing	Stimulus Timestamps Timestamps Unit	string	nwb.processing[stimulus"]["timestamps"].timestamps_unit"	Name of the unit for the timestamps	NaN
183	processing	Stimulus Timestamps Unit	string	nwb.processing[stimulus"]["timestamps"].unit"	Name of the unit for the data	NaN
184	processing	Stimulus Timestamps Data	array	nwb.processing[stimulus"]["timestamps"].data"	Array of all the screen refresh timestamps during the session. Identical to Stimulus Timestamps	NaN
185	processing	Stimulus Timestamps Timestamps	array	nwb.processing[stimulus"]["timestamps"].timestamps"	Array of all the screen refresh timestamps during the session. Identical to Stimulus Timestamps	NaN
186	processing	Ophys Stimulus Timestamps Comments	string	nwb.processing[ophys_stimulus"]["timestamps"].comments"	Comments	NaN
187	processing	Ophys Stimulus Timestamps Conversion	number	nwb.processing[ophys_stimulus"]["timestamps"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
188	processing	Ophys Stimulus Timestamps Description	string	nwb.processing[ophys_stimulus"]["timestamps"].description"	Description	NaN
189	processing	Ophys Stimulus Timestamps Interval	number	nwb.processing[ophys_stimulus"]["timestamps"].interval"	Unexplained	NaN
190	processing	Ophys Stimulus Timestamps Offset	number	nwb.processing[ophys_stimulus"]["timestamps"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
191	processing	Ophys Stimulus Timestamps Resolution	number	nwb.processing[ophys_stimulus"]["timestamps"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
192	processing	Ophys Stimulus Timestamps Timestamps Unit	string	nwb.processing[ophys_stimulus"]["timestamps"].timestamps_unit"	Name of the unit for the timestamps	NaN
193	processing	Ophys Stimulus Timestamps Unit	string	nwb.processing[ophys_stimulus"]["timestamps"].unit"	Name of the unit for the data	NaN
194	processing	Ophys Stimulus Timestamps Data	array	nwb.processing[stimulus_ophys"]["timestamps"].data"	Timestamps associated with all visual stimuli presented on the strimulation screen.	NaN
195	processing	Ophys Stimulus Timestamps Timestamps	array	nwb.processing[stimulus_ophys"]["timestamps"].timestamps"	Timestamps associated with all visual stimuli presented on the strimulation screen.	NaN
196	processing	Running DX Comments	string	nwb.processing[running"]["dx"].comments"	Comments	NaN
197	processing	Running DX Conversion	number	nwb.processing[running"]["dx"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
198	processing	Running DX Description	string	nwb.processing[running"]["dx"].description"	Description	NaN
199	processing	Running DX Interval	number	nwb.processing[running"]["dx"].interval"	Unexplained	NaN
200	processing	Running DX Offset	number	nwb.processing[running"]["dx"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
201	processing	Running DX Resolution	number	nwb.processing[running"]["dx"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
202	processing	Running DX Timestamps Unit	string	nwb.processing[running"]["dx"].timestamps_unit"	Name of the unit for the timestamps	NaN
203	processing	Running DX Unit	string	nwb.processing[running"]["dx"].unit"	Name of the unit for the data	NaN
204	processing	Running DX Data	array	nwb.processing[running"]["dx"].data"	Array of differences, in degrees, between current and last wheel position	NaN
205	processing	Running DX Timestamps	array	nwb.processing[running"]["dx"].timestamps"	Array of timestamps for the dx array	NaN
206	processing	Running Speed Comments	string	nwb.processing[running"]["speed"].comments"	Comments	NaN
207	processing	Running Speed Conversion	number	nwb.processing[running"]["speed"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
208	processing	Running Speed Description	string	nwb.processing[running"]["speed"].description"	Description	NaN
209	processing	Running Speed Interval	number	nwb.processing[running"]["speed"].interval"	Unexplained	NaN
210	processing	Running Speed Offset	number	nwb.processing[running"]["speed"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
211	processing	Running Speed Resolution	number	nwb.processing[running"]["speed"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
212	processing	Running Speed Timestamps Unit	string	nwb.processing[running"]["speed"].timestamps_unit"	Name of the unit for the timestamps	NaN
213	processing	Running Speed Unit	string	nwb.processing[running"]["speed"].unit"	Name of the unit for the data	NaN
214	processing	Running Speed Data	array	nwb.processing[running"]["speed"].data"	Speed of the running wheel, measured at each timestamps. The data is filtered with a low-pass filter to remove noise artifacts (cm/s).	NaN
215	processing	Running Speed Timestamps	array	nwb.processing[running"]["speed"].timestamps"	Timestamps of the running speed.	NaN
216	processing	Unfiltered Running Speed Comments	string	nwb.processing[running"]["speed_unfiltered"].comments"	Comments	NaN
217	processing	Unfiltered Running Speed Conversion	number	nwb.processing[running"]["speed_unfiltered"].conversion"	Scalar to multiply each element in data to convert it to the specified unit	NaN
218	processing	Unfiltered Running Speed Description	string	nwb.processing[running"]["speed_unfiltered"].description"	Description	NaN
219	processing	Unfiltered Running Speed Interval	number	nwb.processing[running"]["speed_unfiltered"].interval"	Unexplained	NaN
220	processing	Unfiltered Running Speed Offset	number	nwb.processing[running"]["speed_unfiltered"].offset"	Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.	NaN
221	processing	Unfiltered Running Speed Resolution	number	nwb.processing[running"]["speed_unfiltered"].resolution"	The smallest meaningful difference (in specified unit) between values in data	NaN
222	processing	Unfiltered Running Speed Timestamps Unit	string	nwb.processing[running"]["speed_unfiltered"].timestamps_unit"	Name of the unit for the timestamps	NaN
223	processing	Unfiltered Running Speed Unit	string	nwb.processing[running"]["speed_unfiltered"].unit"	Name of the unit for the data	NaN
224	processing	Unfiltered Running Speed Data	array	nwb.processing[running"]["speed_unfiltered"].data"	Speed of the running wheel, measured at each timestamps. The data is raw (cm/s).	NaN
225	processing	Unfiltered Running Speed Timestamps	array	nwb.processing[running"]["speed_unfiltered"].timestamps"	Timestamps of the unfiltered running speed.	NaN
226	subject	Subject Age	number	nwb.subject.age	Age of the subject	NaN
227	subject	Subject Age in Days	number	nwb.subject.age_in_days	Age of the subject, in days	NaN
228	subject	Subject Genotype	string	nwb.subject.genotype	Genotype of the subject	NaN
229	subject	Subject Sex	string	nwb.subject.sex	Sex of the subject, M or F	NaN
230	subject	Subject Species	string	nwb.subject.species	Species of the subject	NaN
231	subject	Subject Specimen Name	string	nwb.subject.specimen_name	Specimen name of the subject	NaN
232	subject	Subject Strain	string	nwb.subject.strain	Strain of the subject	NaN
233	subject	Subject ID	string	nwb.subject.subject_id	Unique identifier of the subject	NaN
234	subject	Subject Strain	string	nwb.subject.strain	Strain of the subject	NaN
235	subject	Subject ID	string	nwb.subject.subject_id	Unique identifier of the subject	NaN