Visual Stimuli#
Two possible stimulus sets were used in the Visual Coding - Neuropixels project, known as Brain Observatory 1.1 or Functional Connectivity. The former is largely similar to the visual stimuli used in the Visual Coding 2-photon dataset, with some key adaptations (described below). Each mouse only saw one of these two stimulus sets. It addition to these visual stimuli, an optotagging stimulus was also used in each of these sessions.
Brain Observatory 1.1#
These stimulus consisted of session A and session B from Visual Coding 2-photon merged together, with two additional stimuli: Gabor patches and flashes.
Below is a description of each stimulus family and the corresponding intervals tables in the NWB file.
First, import the necessary packages and load a single session file, unpacking only the intervals container.
import pynwb
import pandas as pd
import numpy as np
import matplotlib as plt
nwb_path = "/data/387858_2018-07-12_13-56-26_nwb_2026-08-19_07-52-55/387858_2018-07-12_13-56-26_nwb_2026-08-19_07-52-55.nwb.zarr"
nwbfile = pynwb.read_nwb(nwb_path)
nwbfile.intervals
{'drifting_gratings_presentations': drifting_gratings_presentations pynwb.epoch.TimeIntervals at 0x140078764992032
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'stimulus_block'
'temporal_frequency' 'color' 'mask' 'opacity' 'phase' 'size' 'units'
'stimulus_index' 'orientation' 'spatial_frequency' 'contrast' 'tags'
'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
temporal_frequency <class 'hdmf.common.table.VectorData'>,
color <class 'hdmf.common.table.VectorData'>,
mask <class 'hdmf.common.table.VectorData'>,
opacity <class 'hdmf.common.table.VectorData'>,
phase <class 'hdmf.common.table.VectorData'>,
size <class 'hdmf.common.table.VectorData'>,
units <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
orientation <class 'hdmf.common.table.VectorData'>,
spatial_frequency <class 'hdmf.common.table.VectorData'>,
contrast <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'drifting_gratings' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'flashes_presentations': flashes_presentations pynwb.epoch.TimeIntervals at 0x140078764992416
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'stimulus_block' 'color' 'mask'
'opacity' 'phase' 'size' 'units' 'stimulus_index' 'orientation'
'spatial_frequency' 'contrast' 'tags' 'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
color <class 'hdmf.common.table.VectorData'>,
mask <class 'hdmf.common.table.VectorData'>,
opacity <class 'hdmf.common.table.VectorData'>,
phase <class 'hdmf.common.table.VectorData'>,
size <class 'hdmf.common.table.VectorData'>,
units <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
orientation <class 'hdmf.common.table.VectorData'>,
spatial_frequency <class 'hdmf.common.table.VectorData'>,
contrast <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'flashes' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'gabors_presentations': gabors_presentations pynwb.epoch.TimeIntervals at 0x140078764993280
Fields:
colnames: ['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']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
temporal_frequency <class 'hdmf.common.table.VectorData'>,
x_position <class 'hdmf.common.table.VectorData'>,
y_position <class 'hdmf.common.table.VectorData'>,
color <class 'hdmf.common.table.VectorData'>,
mask <class 'hdmf.common.table.VectorData'>,
opacity <class 'hdmf.common.table.VectorData'>,
phase <class 'hdmf.common.table.VectorData'>,
size <class 'hdmf.common.table.VectorData'>,
units <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
orientation <class 'hdmf.common.table.VectorData'>,
spatial_frequency <class 'hdmf.common.table.VectorData'>,
contrast <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'gabors' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'invalid_times': invalid_times pynwb.epoch.TimeIntervals at 0x140078764990640
Fields:
colnames: ['start_time' 'stop_time' 'tags']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>
)
description: experimental intervals
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'natural_movie_one_presentations': natural_movie_one_presentations pynwb.epoch.TimeIntervals at 0x140078764992560
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'stimulus_block' 'color'
'opacity' 'size' 'units' 'stimulus_index' 'orientation' 'frame'
'contrast' 'tags' 'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
color <class 'hdmf.common.table.VectorData'>,
opacity <class 'hdmf.common.table.VectorData'>,
size <class 'hdmf.common.table.VectorData'>,
units <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
orientation <class 'hdmf.common.table.VectorData'>,
frame <class 'hdmf.common.table.VectorData'>,
contrast <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'natural_movie_one' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'natural_movie_three_presentations': natural_movie_three_presentations pynwb.epoch.TimeIntervals at 0x140078764995728
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'stimulus_block' 'color'
'opacity' 'size' 'units' 'stimulus_index' 'orientation' 'frame'
'contrast' 'tags' 'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
color <class 'hdmf.common.table.VectorData'>,
opacity <class 'hdmf.common.table.VectorData'>,
size <class 'hdmf.common.table.VectorData'>,
units <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
orientation <class 'hdmf.common.table.VectorData'>,
frame <class 'hdmf.common.table.VectorData'>,
contrast <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'natural_movie_three' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'natural_scenes_presentations': natural_scenes_presentations pynwb.epoch.TimeIntervals at 0x140078764997264
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'stimulus_block'
'stimulus_index' 'frame' 'tags' 'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
frame <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'natural_scenes' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'spontaneous_presentations': spontaneous_presentations pynwb.epoch.TimeIntervals at 0x140078764996880
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'tags' 'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'spontaneous' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>,
'static_gratings_presentations': static_gratings_presentations pynwb.epoch.TimeIntervals at 0x140078764997408
Fields:
colnames: ['start_time' 'stop_time' 'stimulus_name' 'stimulus_block' 'color' 'mask'
'opacity' 'phase' 'size' 'units' 'stimulus_index' 'orientation'
'spatial_frequency' 'contrast' 'tags' 'timeseries']
columns: (
start_time <class 'hdmf.common.table.VectorData'>,
stop_time <class 'hdmf.common.table.VectorData'>,
stimulus_name <class 'hdmf.common.table.VectorData'>,
stimulus_block <class 'hdmf.common.table.VectorData'>,
color <class 'hdmf.common.table.VectorData'>,
mask <class 'hdmf.common.table.VectorData'>,
opacity <class 'hdmf.common.table.VectorData'>,
phase <class 'hdmf.common.table.VectorData'>,
size <class 'hdmf.common.table.VectorData'>,
units <class 'hdmf.common.table.VectorData'>,
stimulus_index <class 'hdmf.common.table.VectorData'>,
orientation <class 'hdmf.common.table.VectorData'>,
spatial_frequency <class 'hdmf.common.table.VectorData'>,
contrast <class 'hdmf.common.table.VectorData'>,
tags_index <class 'hdmf.common.table.VectorIndex'>,
tags <class 'hdmf.common.table.VectorData'>,
timeseries_index <class 'hdmf.common.table.VectorIndex'>,
timeseries <class 'pynwb.base.TimeSeriesReferenceVectorData'>
)
description: Presentation times and stimuli details for 'static_gratings' stimuli
id: id <class 'hdmf.common.table.ElementIdentifiers'>}
All tables share a common set of timing columns and add a stimulus-specific set of parameter columns.
Common columns#
Column |
Description |
|---|---|
start_time |
Start time of the stimulus (s) |
stop_time |
Stop time of the stimulus (s) |
stimulus_name |
Name of the stimulus family |
stimulus_block |
Index of the contiguous block of trials this presentation belongs to |
stimulus_index |
Global index of the presentation within the session |
tags |
User-defined tags |
timeseries |
References to associated timeseries |
Drifting gratings#
The drifting gratings stimulus consists of a sinusoidal grating that is presented on the monitor that moves orthogonal to the orientation of the grating, moving in one of 8 directions (called orientation) and at one of 5 temporal frequencies. The directions are specified in units of degrees and temporal frequency in Hz. The grating has a spatial frequency of 0.04 cycles per degree and a contrast of 80%. Each trial is presented for 2 seconds with 1 second of mean luminance gray in between trials.
Column |
Description |
|---|---|
orientation |
Grating drift direction (deg) |
temporal_frequency |
Drift rate (Hz) |
spatial_frequency |
Grating spatial frequency (cyc/deg) |
contrast |
Stimulus contrast |
phase |
Spatial phase of the grating |
color |
Stimulus color |
mask |
Shape of mask applied to stimulus |
opacity |
Stimulus opacity [0-1] |
size |
Size of stimulus |
units |
Units of |
drifting_gratings = nwbfile.intervals["drifting_gratings_presentations"].to_dataframe()
drifting_gratings.head()
| 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 | 1591.133857 | 1593.135537 | drifting_gratings | 2.0 | 2.0 | [1.0, 1.0, 1.0] | None | 1.0 | [42423.86666667, 42423.86666667] | [250.0, 250.0] | deg | 2.0 | 315.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(3798, 1, timestamps pynwb.base.TimeSeries at... |
| 1 | 1594.136403 | 1596.138053 | drifting_gratings | 2.0 | 4.0 | [1.0, 1.0, 1.0] | None | 1.0 | [42423.86666667, 42423.86666667] | [250.0, 250.0] | deg | 2.0 | 135.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(3799, 1, timestamps pynwb.base.TimeSeries at... |
| 2 | 1597.138897 | 1599.140577 | drifting_gratings | 2.0 | 15.0 | [1.0, 1.0, 1.0] | None | 1.0 | [42423.86666667, 42423.86666667] | [250.0, 250.0] | deg | 2.0 | 225.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(3800, 1, timestamps pynwb.base.TimeSeries at... |
| 3 | 1600.141393 | 1602.143063 | drifting_gratings | 2.0 | 4.0 | [1.0, 1.0, 1.0] | None | 1.0 | [42423.86666667, 42423.86666667] | [250.0, 250.0] | deg | 2.0 | 270.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(3801, 1, timestamps pynwb.base.TimeSeries at... |
| 4 | 1603.143897 | 1605.145547 | drifting_gratings | 2.0 | 4.0 | [1.0, 1.0, 1.0] | None | 1.0 | [42423.86666667, 42423.86666667] | [250.0, 250.0] | deg | 2.0 | 90.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(3802, 1, timestamps pynwb.base.TimeSeries at... |
Static gratings#
The static gratings stimulus consists of a stationary sinusoidal grating that is flasshed on the monitor at one of 6 orientations, one of 5 spatial frequencies, and one of 4 phases. The grating has a contrast of 80%. Each trial is presented for 0.25 seconds and followed immediately by the next trial without any intertrial interval. There are blanksweeps, where the grating is replaced by the mean luminance gray, interleaved among the trials.
Column |
Description |
|---|---|
orientation |
Grating drift direction (deg) |
temporal_frequency |
Drift rate (Hz) |
spatial_frequency |
Grating spatial frequency (cyc/deg) |
contrast |
Stimulus contrast |
phase |
Spatial phase of the grating |
color |
Stimulus color |
mask |
Shape of mask applied to stimulus |
opacity |
Stimulus opacity [0-1] |
size |
Size of stimulus |
units |
Units of |
static_gratings = nwbfile.intervals["static_gratings_presentations"].to_dataframe()
static_gratings.head()
| start_time | stop_time | stimulus_name | stimulus_block | color | mask | opacity | phase | size | units | stimulus_index | orientation | spatial_frequency | contrast | tags | timeseries | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||
| 0 | 5398.313257 | 5398.563476 | static_gratings | 8.0 | [1.0, 1.0, 1.0] | None | 1.0 | 0.5 | [250.0, 250.0] | deg | 6.0 | 0.0 | 0.16 | 0.8 | [stimulus_time_interval] | [(49432, 1, timestamps pynwb.base.TimeSeries a... |
| 1 | 5398.563476 | 5398.813695 | static_gratings | 8.0 | [1.0, 1.0, 1.0] | None | 1.0 | 0.0 | [250.0, 250.0] | deg | 6.0 | 0.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(49433, 1, timestamps pynwb.base.TimeSeries a... |
| 2 | 5398.813695 | 5399.063914 | static_gratings | 8.0 | [1.0, 1.0, 1.0] | None | 1.0 | 0.5 | [250.0, 250.0] | deg | 6.0 | 90.0 | 0.02 | 0.8 | [stimulus_time_interval] | [(49434, 1, timestamps pynwb.base.TimeSeries a... |
| 3 | 5399.063914 | 5399.314133 | static_gratings | 8.0 | [1.0, 1.0, 1.0] | None | 1.0 | 0.75 | [250.0, 250.0] | deg | 6.0 | 150.0 | 0.04 | 0.8 | [stimulus_time_interval] | [(49435, 1, timestamps pynwb.base.TimeSeries a... |
| 4 | 5399.314133 | 5399.564339 | static_gratings | 8.0 | [1.0, 1.0, 1.0] | None | 1.0 | 0.0 | [250.0, 250.0] | deg | 6.0 | 30.0 | 0.02 | 0.8 | [stimulus_time_interval] | [(49436, 1, timestamps pynwb.base.TimeSeries a... |
What is the phase of the grating?
The phase refers to the relative position of the grating. Phase 0 and Phase 0.5 are 180° apart so that the peak of the grating of phase 0 lines up with the trough of phase 0.5.
Natural scenes#
The natural scenes stimulus consists of a 118 black and white images that are flashed on the monitor. Each trial is presented for 0.25 seconds and followed immediately by the next trial without any intertrial interval. There are blanksweeps, where the images are replaced by the mean luminance gray, interleaved in among the trials.
Column |
Description |
|---|---|
frame |
Index of the natural-scene image presented on this trial |
natural_scenes = nwbfile.intervals["natural_scenes_presentations"].to_dataframe()
natural_scenes.head()
| start_time | stop_time | stimulus_name | stimulus_block | stimulus_index | frame | tags | timeseries | |
|---|---|---|---|---|---|---|---|---|
| id | ||||||||
| 0 | 5908.739537 | 5908.989739 | natural_scenes | 9.0 | 5.0 | 34.0 | [stimulus_time_interval] | [(51353, 1, timestamps pynwb.base.TimeSeries a... |
| 1 | 5908.989739 | 5909.239940 | natural_scenes | 9.0 | 5.0 | 6.0 | [stimulus_time_interval] | [(51354, 1, timestamps pynwb.base.TimeSeries a... |
| 2 | 5909.239940 | 5909.490142 | natural_scenes | 9.0 | 5.0 | 28.0 | [stimulus_time_interval] | [(51355, 1, timestamps pynwb.base.TimeSeries a... |
| 3 | 5909.490142 | 5909.740343 | natural_scenes | 9.0 | 5.0 | 109.0 | [stimulus_time_interval] | [(51356, 1, timestamps pynwb.base.TimeSeries a... |
| 4 | 5909.740343 | 5909.990554 | natural_scenes | 9.0 | 5.0 | 105.0 | [stimulus_time_interval] | [(51357, 1, timestamps pynwb.base.TimeSeries a... |
Natural movies#
Short natural movie clips presented multiple times. natural_movie_one and natural_movie_three are two different clips. Each row corresponds to one frame of the movie.
Column |
Description |
|---|---|
frame |
Frame index within the movie clip |
natural_movie_one = nwbfile.intervals["natural_movie_one_presentations"].to_dataframe()
natural_movie_one.head()
| start_time | stop_time | stimulus_name | stimulus_block | color | opacity | size | units | stimulus_index | orientation | frame | contrast | tags | timeseries | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||
| 0 | 2852.187037 | 2852.220398 | 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 a... |
| 1 | 2852.220398 | 2852.253758 | 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 a... |
| 2 | 2852.253758 | 2852.287119 | 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 a... |
| 3 | 2852.287119 | 2852.320479 | 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 a... |
| 4 | 2852.320479 | 2852.353840 | natural_movie_one | 4.0 | [1.0, 1.0, 1.0] | 1.0 | [1920.0, 1080.0] | pix | 3.0 | 0.0 | 4.0 | 1.0 | [stimulus_time_interval] | [(22004, 1, timestamps pynwb.base.TimeSeries a... |
Gabor patches#
Small Gabor patches presented at a grid of positions on the monitor. Used to map each unit’s spatial receptive field.
Column |
Description |
|---|---|
x_position |
Horizontal position of the Gabor on the monitor (deg) |
y_position |
Vertical position of the Gabor on the monitor (deg) |
orientation |
Gabor orientation (deg) |
spatial_frequency |
Gabor spatial frequency (cyc/deg) |
temporal_frequency |
Gabor temporal frequency (Hz) |
contrast |
Stimulus contrast |
size |
Gabor patch size (deg) |
gabors = nwbfile.intervals["gabors_presentations"].to_dataframe()
gabors.head()
| 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 | 89.896827 | 90.130356 | gabors | 0.0 | 4.0 | 10.0 | -10.0 | [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] | [(1, 1, timestamps pynwb.base.TimeSeries at 0x... |
| 1 | 90.130356 | 90.380565 | gabors | 0.0 | 4.0 | -30.0 | 20.0 | [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] | [(2, 1, timestamps pynwb.base.TimeSeries at 0x... |
| 2 | 90.380565 | 90.630774 | gabors | 0.0 | 4.0 | 20.0 | -20.0 | [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] | [(3, 1, timestamps pynwb.base.TimeSeries at 0x... |
| 3 | 90.630774 | 90.880983 | gabors | 0.0 | 4.0 | 30.0 | 20.0 | [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] | [(4, 1, timestamps pynwb.base.TimeSeries at 0x... |
| 4 | 90.880983 | 91.131199 | gabors | 0.0 | 4.0 | 0.0 | -40.0 | [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] | [(5, 1, timestamps pynwb.base.TimeSeries at 0x... |
Flashes#
Full-field ON/OFF luminance flashes. Used to characterize ON/OFF responses.
flashes = nwbfile.intervals["flashes_presentations"].to_dataframe()
flashes.head()
| start_time | stop_time | stimulus_name | stimulus_block | color | mask | opacity | phase | size | units | stimulus_index | orientation | spatial_frequency | contrast | tags | timeseries | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||
| 0 | 1290.883097 | 1291.133309 | 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... |
| 1 | 1292.884817 | 1293.135016 | 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... |
| 2 | 1294.886487 | 1295.136691 | 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... |
| 3 | 1296.888137 | 1297.138344 | 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... |
| 4 | 1298.889787 | 1299.140004 | 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] | [(3651, 1, timestamps pynwb.base.TimeSeries at... |
Spontaneous activity#
Blocks of gray-screen activity presented between stimulus families. Used as a reference for baseline firing.
spontaneous = nwbfile.intervals["spontaneous_presentations"].to_dataframe()
spontaneous.head()
| start_time | stop_time | stimulus_name | tags | timeseries | |
|---|---|---|---|---|---|
| id | |||||
| 0 | 29.830107 | 89.896827 | spontaneous | [stimulus_time_interval] | [(0, 1, timestamps pynwb.base.TimeSeries at 0x... |
| 1 | 1001.891772 | 1290.883097 | spontaneous | [stimulus_time_interval] | [(3646, 1, timestamps pynwb.base.TimeSeries at... |
| 2 | 1589.382401 | 1591.133857 | spontaneous | [stimulus_time_interval] | [(3797, 1, timestamps pynwb.base.TimeSeries at... |
| 3 | 2190.634543 | 2221.660447 | spontaneous | [stimulus_time_interval] | [(3998, 1, timestamps pynwb.base.TimeSeries at... |
| 4 | 2822.161967 | 2852.187037 | spontaneous | [stimulus_time_interval] | [(21999, 1, timestamps pynwb.base.TimeSeries a... |
Invalid times#
Intervals during which the recording is considered unreliable and should be excluded from analysis.
invalid_times = nwbfile.intervals["invalid_times"].to_dataframe()
invalid_times.head()
| start_time | stop_time | tags | |
|---|---|---|---|
| id | |||
| 0 | 970.0 | 982.0 | [EcephysSession, 719161530, stimulus] |
Functional Connectivity#
Fig. 19 Neuropixels visual stimulus sets#