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Streaming an NWB file¶
This section demonstrates how to access the files on the DANDI Archive without downloading them. Based on the Streaming NWB files tutorial from PyNWB.
The dandi.dandiapi.DandiAPIClient can be used to get the S3 URL of the NWB file stored in the DANDI Archive.
from dandi.dandiapi import DandiAPIClient
client = DandiAPIClient.for_dandi_instance("dandi")
dandiset_id = "001084"
file_path = "sub-DL18/sub-DL18_ses-211110_image+ophys.nwb"
with DandiAPIClient() as client:
asset = client.get_dandiset(dandiset_id, 'draft').get_asset_by_path(file_path)
s3_url = asset.get_content_url(follow_redirects=1, strip_query=True)
We will use remfile for streaming the file. You can read more about remfile at this tutorial section.
import h5py
from pynwb import NWBHDF5IO
import remfile
# We stream the file using remfile and open it with h5py and pynwb
file = remfile.File(s3_url)
h5_file = h5py.File(file, "r")
io = NWBHDF5IO(file=h5_file, load_namespaces=True)
nwbfile = io.read()
/opt/hostedtoolcache/Python/3.13.15/x64/lib/python3.13/site-packages/hdmf/spec/namespace.py:620: UserWarning: Ignoring the following cached namespace(s) because another version is already loaded: core - cached version: 2.7.0, loaded version: 2.8.0 The loaded extension(s) may not be compatible with the cached extension(s) in the file. Please check the extension documentation and ignore this warning if these versions are compatible. self.warn_for_ignored_namespaces(ignored_namespaces)
nwbfile.subject
subject (Subject)
date_of_birth
2021-04-21 00:00:00-04:00Access raw imaging¶
This section demonstrates how to access the imaging data in the NWBFile.
NWB organizes data into different groups depending on the type of data. Groups can be thought of as folders within the file. Here are some of the groups within an NWBFile and the types of data they are intended to store:
acquisition: raw, acquired data that should never changeprocessing: processed data, typically the results of preprocessing algorithms and could change
Fiber array imaging¶
The fiber bundle imaging data was acquired using HCImage Live (Hamamatsu) at 30 Hz. It is stored in a pynwb.ophys.OnePhotonSeries object which is added to nwbfile.acquisition.
one_photon_series = nwbfile.acquisition["OnePhotonSeriesGreen"]
one_photon_series
OnePhotonSeriesGreen (OnePhotonSeries)
data
| Data type | uint16 |
|---|---|
| Shape | (40000, 376, 375) |
| Array size | 10.51 GiB |
| Chunk shape | (35, 376, 375) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 11280000000 |
| Compressed size (bytes) | 9213518925 |
| Compression ratio | 1.2242879286211483 |
dimension
| Data type | int64 |
|---|---|
| Shape | (2,) |
| Array size | 16.00 bytes |
| Chunk shape | None |
| Compression | None |
| Compression opts | None |
| Uncompressed size (bytes) | 16 |
| Compressed size (bytes) | 16 |
| Compression ratio | 1.0 |
[375 376]
imaging_plane (ImagingPlane)
optical_channel
0 (OpticalChannel)
device (Device)
The information about the imaging plane can accessed as nwbfile.acquisition["OnePhotonSeries"].imaging_plane or nwbfile.imaging_planes["ImagingPlane"].
nwbfile.imaging_planes["ImagingPlaneGreen"]
ImagingPlaneGreen (ImagingPlane)
optical_channel
0 (OpticalChannel)
device (Device)
# Visualize the imaging data.
from matplotlib import pyplot as plt
frame = one_photon_series.data[50]
plt.imshow(frame)
plt.title("Raw Fiber Array Imaging")
plt.show()
Fiber photometry traces¶
The raw fluorescence traces from the multi-fiber array are added to nwbfile.acquisition and are stored in a FiberPhotometryResponseSeries object using ndx-fiber-photometry. The fluorescence data during 470 nm excitation can be accessed as nwbfile.acquisition["FiberPhotometryResponseSeriesGreen"].
fiber_photometry_response_series = nwbfile.acquisition["FiberPhotometryResponseSeriesGreen"]
import pandas as pd
from matplotlib import pyplot as plt
# Prepare data for plotting
fiber_indices = [0, 4]
data = fiber_photometry_response_series.data[100:500, fiber_indices]
timestamps = fiber_photometry_response_series.get_timestamps()[100:500]
fig, axes = plt.subplots(nrows=data.shape[1], ncols=1, figsize=(8, 3), sharey=True, sharex=True, dpi=300)
for i, ax in enumerate(axes):
ax.plot(timestamps, data[:, i], linewidth=0.5, color="green")
ax.tick_params(axis='y', labelsize=8)
ax.tick_params(axis='x', labelsize=8)
ax.legend([f"Fiber {i+1}"], frameon=False, bbox_to_anchor=(.95, 1), loc='upper left', prop={'size': 8})
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
axes[0].spines['bottom'].set_visible(False)
axes[0].set_title("Raw fluorescence traces", fontsize=8)
plt.xlabel('Time (s)', fontsize=8)
plt.tick_params(axis='x', labelsize=8)
plt.tight_layout()
plt.show()
Fiber photometry metadata¶
The fiber photometry metadata includes the type of indicator(s), optical fiber(s), excitation source(s), photodector(s), dichroic mirror(s), and optical filter(s) that were used to construct a single fluorescence signal.
The metadata is stored in a FiberPhotometryTable object using ndx-fiber-photometry and is added to nwbfile.lab_meta_data. It can be accessed as nwbfile.lab_meta_data["FiberPhotometry"].fiber_photometry_table.
nwbfile.lab_meta_data["FiberPhotometry"].fiber_photometry_table[:]
| location | indicator | optical_fiber | excitation_source | photodetector | dichroic_mirror | allen_atlas_coordinates | included | coordinates | emission_filter | excitation_filter | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||
| 0 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [442, 644, 229] | False | [0.83, 0.74, 1.78] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 1 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [454, 642, 304] | False | [0.71, 0.72, 2.44] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 2 | Primary motor area Layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [460, 674, 180] | False | [0.65, 1.04, 1.35] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 3 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [495, 685, 260] | False | [0.3, 1.15, 2.05] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 4 | Primary motor area Layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [400, 686, 160] | False | [1.25, 1.16, 1.17] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 98 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [433, 775, 249] | False | [0.92, 2.05, 1.96] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 99 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [444, 815, 381] | True | [0.81, 2.45, 3.12] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 100 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [457, 833, 280] | False | [0.68, 2.63, 2.23] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 101 | Primary somatosensory area mouth layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [482, 821, 396] | False | [0.43, 2.51, 3.25] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 102 | Primary motor area Layer 2/3 | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [396, 791, 209] | False | [1.29, 2.21, 1.6] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
103 rows × 11 columns
The fiber_photometry_table_region attribute in the FiberPhotometryResponseSeries object references row(s) of this table:
fiber_photometry_table_region = nwbfile.acquisition["FiberPhotometryResponseSeriesGreen"].fiber_photometry_table_region[:]
fiber_photometry_table_region.head()
| location | indicator | optical_fiber | excitation_source | photodetector | dichroic_mirror | allen_atlas_coordinates | included | coordinates | emission_filter | excitation_filter | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||
| 0 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [442, 644, 229] | False | [0.83, 0.74, 1.78] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 1 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [454, 642, 304] | False | [0.71, 0.72, 2.44] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 2 | Primary motor area Layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [460, 674, 180] | False | [0.65, 1.04, 1.35] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 3 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [495, 685, 260] | False | [0.3, 1.15, 2.05] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
| 4 | Primary motor area Layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\... | FiberArray abc.OpticalFiber at 0x1406035293773... | ExcitationSource470 abc.ExcitationSource at 0x... | CMOSCamera pynwb.device.Device at 0x1406035301... | DichroicMirror1 abc.DichroicMirror at 0x140603... | [400, 686, 160] | False | [1.25, 1.16, 1.17] | OpticalFilter525 abc.BandOpticalFilter at 0x14... | OpticalFilter470 abc.BandOpticalFilter at 0x14... |
The metadata on the optical fiber used to record the GCaMP fluorescence is added to nwbfile.devices and can be accessed as nwbfile.devices["FiberArray"] or can be accessed from the referenced optical fiber in the fiber_photometry_table_region of the FiberPhotometryResponseSeries.
fiber_photometry_table_region["optical_fiber"][0]
FiberArray (OpticalFiber)
fiber_photometry_table_region["indicator"][0]
dLight1.3b (Indicator)
fiber_photometry_table_region["excitation_source"][0]
ExcitationSource470 (ExcitationSource)
fiber_photometry_table_region["photodetector"][0]
CMOSCamera (Device)
fiber_photometry_table_region["dichroic_mirror"][0]
DichroicMirror1 (DichroicMirror)
reflection_band_in_nm
| Data type | float64 |
|---|---|
| Shape | (2,) |
| Array size | 16.00 bytes |
[405. 532.]
transmission_band_in_nm
| Data type | float64 |
|---|---|
| Shape | (2,) |
| Array size | 16.00 bytes |
[545. 750.]
fiber_photometry_table_region["emission_filter"][0]
OpticalFilter525 (BandOpticalFilter)
fiber_photometry_table_region["excitation_filter"][0]
OpticalFilter470 (BandOpticalFilter)
Access processed fiber photometry data¶
This section demonstrates how to access the processed fiber photometry data in the NWBFile.
The processed fiber photometry data is stored in "processing/ophys" which can be accessed as nwbfile.processing["ophys"]. Within this processing module we can access the ∆F/F traces as nwbfile.processing["ophys"]["DfOverFFiberPhotometryResponseSeriesGreen"].
nwbfile.processing["ophys"]
ophys (ProcessingModule)
BaselineFiberPhotometryResponseSeriesGreen (FiberPhotometryResponseSeries)
data
| Data type | float64 |
|---|---|
| Shape | (40000, 103) |
| Array size | 31.43 MiB |
| Chunk shape | (21728, 56) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 32960000 |
| Compressed size (bytes) | 4678796 |
| Compression ratio | 7.044547357910027 |
fiber_photometry_table_region (DynamicTableRegion)
table (FiberPhotometryTable)
columns
location
indicator
optical_fiber
excitation_source
photodetector
dichroic_mirror
allen_atlas_coordinates
included
coordinates
emission_filter
excitation_filter
table
| location | indicator | optical_fiber | excitation_source | photodetector | dichroic_mirror | allen_atlas_coordinates | included | coordinates | emission_filter | excitation_filter | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||
| 0 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [442, 644, 229] | False | [0.83, 0.74, 1.78] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
| 1 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [454, 642, 304] | False | [0.71, 0.72, 2.44] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
| 2 | Primary motor area Layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [460, 674, 180] | False | [0.65, 1.04, 1.35] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
| 3 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [495, 685, 260] | False | [0.3, 1.15, 2.05] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
... and 99 more row(s).
DfOverFFiberPhotometryResponseSeriesGreen (FiberPhotometryResponseSeries)
data
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|---|---|
| Shape | (40000, 103) |
| Array size | 31.43 MiB |
| Chunk shape | (21728, 56) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 32960000 |
| Compressed size (bytes) | 29667458 |
| Compression ratio | 1.1109816014570577 |
fiber_photometry_table_region (DynamicTableRegion)
table (FiberPhotometryTable)
columns
location
indicator
optical_fiber
excitation_source
photodetector
dichroic_mirror
allen_atlas_coordinates
included
coordinates
emission_filter
excitation_filter
table
| location | indicator | optical_fiber | excitation_source | photodetector | dichroic_mirror | allen_atlas_coordinates | included | coordinates | emission_filter | excitation_filter | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||
| 0 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [442, 644, 229] | False | [0.83, 0.74, 1.78] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
| 1 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [454, 642, 304] | False | [0.71, 0.72, 2.44] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
| 2 | Primary motor area Layer 6a | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [460, 674, 180] | False | [0.65, 1.04, 1.35] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
| 3 | Caudoputamen | dLight1.3b abc.Indicator at 0x140603529377984\nFields:\n description: green dopamine sensor\n label: pAAV-CAG-dLight1.3b(AAV5)\n | FiberArray abc.OpticalFiber at 0x140603529377312\nFields:\n core_diameter_in_um: 34.0\n description: The optical fiber used in a multi-fiber arrays configuration, fabricated in-house to enable large scale measurements across deep brain volumes. Bare fibers were cut into pieces (ca. 3cm) then mounted under a microscope into 55-60μm diameter holes in a custom 3D printed grid (3mm W x 5mm L, Boston Micro Fabrication), measured under a dissection microscope to target a particular depth beneath the grid, and secured in place with UV glue (Norland Optical Adhesive 61). Each array contained between 30 and 103 fibers separated by a minimum of 220μm radially and 250μm axially. Separation was calculated to achieve maximal coverage of the striatum volume with no overlap in the collection fields of individual fibers. Fibers were cut with a fiber scribe, and the distal ends were inspected to ensure a uniform cut, and re-cut as necessary. Distal ends were then glued inside an 1cm ca. section of polyimide tube (0.8-1.3mm diameter, MicroLumen) then cut with a fresh razorblade. The bundled fibers inside the tube were then polished on fine grained polishing paper (ThorLabs,polished first with 6 μm, followed by 3 μm) to create a smooth, uniform fiber bundle surface for imaging. A larger diameter post was mounted on one side of the plastic grid to facilitate holding during implantation.\n manufacturer: Fiber Optics Tech\n model: not specified\n numerical_aperture: 0.66\n | ExcitationSource470 abc.ExcitationSource at 0x140603529376976\nFields:\n description: Blue excitation light (470 nm LED, Thorlabs, No. SOLIS-470C) and violet excitation light (for the isosbestic control)\nwere coupled into the optic fiber such that a power of 0.75 mW was delivered to the fiber tip.\nThen, 470 nm and 405 nm excitation were alternated at 100 Hz using a waveform generator,\neach filtered with a corresponding filter.\n\n excitation_wavelength_in_nm: 470.0\n illumination_type: LED\n manufacturer: Thorlabs\n model: SOLIS-470C\n | CMOSCamera pynwb.device.Device at 0x140603530107856\nFields:\n description: A tube lens in each path (Thor labs, No TTL165-A) focused emission light onto the CMOS sensors of the cameras to form an image of the fiber bundle.\n manufacturer: Hamamatsu Photonics, Orca Fusion BT Gen III\n | DichroicMirror1 abc.DichroicMirror at 0x140603529376640\nFields:\n cut_on_wavelength_in_nm: 532.0\n description: The dichroic mirror used to reflect green and pass red fluorescence\n manufacturer: Chroma Tech Corp\n model: ZT532rdc\n reflection_band_in_nm: [405. 532.]\n transmission_band_in_nm: [545. 750.]\n | [495, 685, 260] | False | [0.3, 1.15, 2.05] | OpticalFilter525 abc.BandOpticalFilter at 0x140603530113296\nFields:\n bandwidth_in_nm: 50.0\n center_wavelength_in_nm: 525.0\n description: The band-pass filter used to isolate the green emitted light after passing through a dichroic (Chroma, No. 532rdc) that reflected green and passed red fluorescence.\n filter_type: Bandpass\n manufacturer: Chroma\n model: 525/50m\n | OpticalFilter470 abc.BandOpticalFilter at 0x140603529377648\nFields:\n bandwidth_in_nm: 24.0\n center_wavelength_in_nm: 473.0\n description: The band-pass filter used to isolate the 470 nm excitation light.\n filter_type: Bandpass\n manufacturer: Chroma\n model: ET473/24\n |
... and 99 more row(s).
ImageSegmentation (ImageSegmentation)
PlaneSegmentation (PlaneSegmentation)
imaging_plane (ImagingPlane)
optical_channel
0 (OpticalChannel)
device (Device)
columns
image_mask
ROICentroids
Accepted
Rejected
table
| image_mask | ROICentroids | Accepted | Rejected | |
|---|---|---|---|---|
| id | ||||
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... and 99 more row(s).
OnePhotonSeriesMotionCorrectedGreen (OnePhotonSeries)
data
| Data type | uint16 |
|---|---|
| Shape | (40000, 381, 378) |
| Array size | 10.73 GiB |
| Chunk shape | (34, 381, 378) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 11521440000 |
| Compressed size (bytes) | 9143731733 |
| Compression ratio | 1.2600369670097362 |
dimension
| Data type | int64 |
|---|---|
| Shape | (2,) |
| Array size | 16.00 bytes |
| Chunk shape | None |
| Compression | None |
| Compression opts | None |
| Uncompressed size (bytes) | 16 |
| Compressed size (bytes) | 16 |
| Compression ratio | 1.0 |
[378 381]
imaging_plane (ImagingPlane)
optical_channel
0 (OpticalChannel)
device (Device)
df_over_f_traces = nwbfile.processing["ophys"]["DfOverFFiberPhotometryResponseSeriesGreen"]
# Visualize the DF/F traces.
from matplotlib import pyplot as plt
# Prepare data for plotting
data = df_over_f_traces.data[100:500, :5]
timestamps = df_over_f_traces.get_timestamps()[100:500]
fig, axes = plt.subplots(nrows=data.shape[1], ncols=1, figsize=(6, 4), sharey=True, sharex=True, dpi=300)
for i, ax in enumerate(axes):
ax.plot(timestamps, data[:, i], linewidth=0.5, color="green")
ax.tick_params(axis='y', labelsize=6)
ax.tick_params(axis='x', labelsize=6)
ax.legend([f"∆F/F Fiber {i+1}"], frameon=False, bbox_to_anchor=(.95, 1), loc='upper left', prop={'size': 6})
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
if i != data.shape[1] - 1:
ax.spines['bottom'].set_visible(False)
axes[0].set_title("DF/F Fluorescence traces", fontsize=6)
plt.xlabel('Time (s)', fontsize=6)
plt.tick_params(axis='x', labelsize=6)
plt.tight_layout()
plt.show()
Access motion corrected imaging data¶
This section demonstrates how to access the motion corrected imaging data in the NWBFile.
Similarly to the raw imaging data, the processed imaging data is stored in a pynwb.ophys.OnePhotonSeries object and is added to nwbfile.processing["ophys"].
motion_corrected = nwbfile.processing["ophys"]["OnePhotonSeriesMotionCorrectedGreen"]
motion_corrected
OnePhotonSeriesMotionCorrectedGreen (OnePhotonSeries)
data
| Data type | uint16 |
|---|---|
| Shape | (40000, 381, 378) |
| Array size | 10.73 GiB |
| Chunk shape | (34, 381, 378) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 11521440000 |
| Compressed size (bytes) | 9143731733 |
| Compression ratio | 1.2600369670097362 |
dimension
| Data type | int64 |
|---|---|
| Shape | (2,) |
| Array size | 16.00 bytes |
| Chunk shape | None |
| Compression | None |
| Compression opts | None |
| Uncompressed size (bytes) | 16 |
| Compressed size (bytes) | 16 |
| Compression ratio | 1.0 |
[378 381]
imaging_plane (ImagingPlane)
optical_channel
0 (OpticalChannel)
device (Device)
# Visualize the motion corrected imaging data.
from matplotlib import pyplot as plt
fig, axes = plt.subplots(nrows=1, ncols=2, sharex=True, sharey=True, dpi=300)
axes[0].imshow(one_photon_series.data[50])
axes[0].set_title("Raw Fiber Array Imaging", fontsize=6)
axes[0].tick_params(axis='x', labelsize=6)
axes[0].tick_params(axis='y', labelsize=6)
axes[1].imshow(motion_corrected.data[50])
axes[1].set_title("Motion Corrected Fiber Array Imaging", fontsize=6)
axes[1].tick_params(axis='x', labelsize=6)
axes[1].tick_params(axis='y', labelsize=6)
plt.tight_layout()
plt.show()
Access ROIs¶
This section demonstrates how to access the ROIs corresponding to fiber tops in the NWBFile.
The centroids and image masks of the ROIs are stored in a PlaneSegmentation added to an ImageSegmentation object in nwbfile.processing["ophys"].
rois_table = nwbfile.processing["ophys"]["ImageSegmentation"]["PlaneSegmentation"][:]
rois_table.head()
| image_mask | ROICentroids | Accepted | Rejected | |
|---|---|---|---|---|
| id | ||||
| 0 | [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,... | [166.47541258012367, 59.00562445763765] | 0 | 1 |
| 1 | [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,... | [163.1369152701555, 80.29428559091824] | 0 | 1 |
| 2 | [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,... | [144.14977970147507, 83.10331721340896] | 0 | 1 |
| 3 | [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,... | [123.4401911607665, 85.54001655461578] | 0 | 1 |
| 4 | [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,... | [111.00957492596739, 100.35934701854168] | 0 | 1 |
# Visualize the ROIs and the motion corrected imaging data.
from matplotlib import pyplot as plt
import numpy as np
plt.imshow(motion_corrected.data[50])
roi_masks = rois_table["image_mask"].values
roi_masks_combined = np.zeros(roi_masks[0].shape)
for i in range(roi_masks.shape[0]):
inds = np.where(roi_masks[i] != 0)
roi_masks_combined[inds] = 1
masked_roi_masks_combined = np.ma.masked_where(roi_masks_combined == 0, roi_masks_combined)
plt.imshow(masked_roi_masks_combined, cmap='gray', interpolation='none', alpha=0.5)
plt.title("ROIs on motion corrected image")
plt.show()
Access behavior data¶
This section demonstrates how to access the behavior data in the NWBFile.
The velocity for the roll and pitch (x, y) measured in m/s is added to nwbfile.processing["behavior"] stored in a pynwb.base.TimeSeries object. It can be accessed as nwbfile.processing["behavior"]["Velocity"].
The angular velocity from yaw (rotational) velocity is converted to radians/s and is also stored in a pynwb.base.TimeSeries object.
It can be accessed as nwbfile.processing["behavior"]["AngularVelocity"].
nwbfile.processing["behavior"]
behavior (ProcessingModule)
AngularVelocity (TimeSeries)
data
| Data type | float64 |
|---|---|
| Shape | (40000,) |
| Array size | 312.50 KiB |
| Chunk shape | (40000,) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 320000 |
| Compressed size (bytes) | 305498 |
| Compression ratio | 1.0474700325370379 |
timestamps
| Data type | float64 |
|---|---|
| Shape | (40000,) |
| Array size | 312.50 KiB |
| Chunk shape | (40000,) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 320000 |
| Compressed size (bytes) | 115444 |
| Compression ratio | 2.771906725338692 |
timestamp_link
0 (TimeSeries)
data
| Data type | float64 |
|---|---|
| Shape | (40000, 2) |
| Array size | 625.00 KiB |
| Chunk shape | (40000, 2) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 640000 |
| Compressed size (bytes) | 610953 |
| Compression ratio | 1.0475437554116274 |
timestamps (link to processing/behavior/AngularVelocity/timestamps)
| Data type | float64 |
|---|---|
| Shape | (40000,) |
| Array size | 312.50 KiB |
| Chunk shape | (40000,) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 320000 |
| Compressed size (bytes) | 115444 |
| Compression ratio | 2.771906725338692 |
Velocity (TimeSeries)
data
| Data type | float64 |
|---|---|
| Shape | (40000, 2) |
| Array size | 625.00 KiB |
| Chunk shape | (40000, 2) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 640000 |
| Compressed size (bytes) | 610953 |
| Compression ratio | 1.0475437554116274 |
timestamps (link to processing/behavior/AngularVelocity/timestamps)
| Data type | float64 |
|---|---|
| Shape | (40000,) |
| Array size | 312.50 KiB |
| Chunk shape | (40000,) |
| Compression | gzip |
| Compression opts | 4 |
| Uncompressed size (bytes) | 320000 |
| Compressed size (bytes) | 115444 |
| Compression ratio | 2.771906725338692 |
TimeIntervals (TimeIntervals)
columns
start_time
stop_time
event_type
table
| start_time | stop_time | event_type | |
|---|---|---|---|
| id | |||
| 0 | 10.21300 | 11.08000 | Light |
| 1 | 25.31550 | 26.18225 | Light |
| 2 | 36.25050 | 37.58400 | Tone |
| 3 | 69.78875 | 70.65550 | Light |
... and 159 more row(s).
velocity = nwbfile.processing["behavior"]["Velocity"]
# Visualize the DF/F traces and velocity for the roll in m/s.
import pandas as pd
from matplotlib import pyplot as plt
# Prepare data for plotting
data = df_over_f_traces.data[200:600, :2]
timestamps = df_over_f_traces.get_timestamps()[200:600]
velocity_x = velocity.data[200:600, 0]
fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(6, 4), sharey=False, sharex=True, dpi=300)
for i in range(len(axes)-1):
axes[i].plot(timestamps, data[:, i], linewidth=0.5, color="green")
axes[i].spines['top'].set_visible(False)
axes[i].spines['right'].set_visible(False)
axes[i].tick_params(axis='y', labelsize=6)
axes[i].tick_params(axis='x', labelsize=6)
axes[i].spines['bottom'].set_visible(False)
axes[i].set_ylim([-0.01, 0.09])
axes[i].legend([f"∆F/F Fiber {i+1}"], frameon=False, bbox_to_anchor=(.95, 1), loc='upper left', prop={'size': 6})
axes[i].spines['top'].set_visible(False)
axes[i].spines['right'].set_visible(False)
axes[-1].plot(timestamps, velocity_x, color="black", alpha=0.8, linewidth=0.5)
axes[-1].spines['top'].set_visible(False)
axes[-1].spines['right'].set_visible(False)
axes[-1].legend(["Roll velocity"], frameon=False, bbox_to_anchor=(.95, 1), loc='upper left', prop={'size': 6})
axes[-1].tick_params(axis='y', labelsize=6)
axes[-1].tick_params(axis='x', labelsize=6)
plt.xlabel('Time (s)', fontsize=6)
plt.tight_layout()
plt.show()
The onset times of the events (licking, tone, light or reward delivery) are added to nwbfile.processing["behavior"]["TimeIntervals"] table.
events = nwbfile.processing["behavior"]["TimeIntervals"][:]
events
| start_time | stop_time | event_type | |
|---|---|---|---|
| id | |||
| 0 | 10.21300 | 11.08000 | Light |
| 1 | 25.31550 | 26.18225 | Light |
| 2 | 36.25050 | 37.58400 | Tone |
| 3 | 69.78875 | 70.65550 | Light |
| 4 | 87.65825 | 88.99175 | Tone |
| ... | ... | ... | ... |
| 158 | 1312.37725 | 1312.54400 | Lick |
| 159 | 1313.64425 | 1313.74425 | Lick |
| 160 | 1318.24500 | 1319.07825 | Light |
| 161 | 1325.11250 | 1326.41275 | Tone |
| 162 | 1330.61350 | 1331.48025 | Light |
163 rows × 3 columns
from matplotlib import pyplot as plt
import matplotlib.lines as mlines
# Prepare data for plotting
data = df_over_f_traces.data[700:1200, 0]
timestamps = df_over_f_traces.get_timestamps()[700:1200]
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6, 2), dpi=300, sharex=True)
light_events = events[events["event_type"] == "Light"]
light_events = light_events[(light_events["start_time"] >= timestamps[0]) & (light_events["stop_time"] < timestamps[-1])]
tone_events = events[events["event_type"] == "Tone"]
tone_events = tone_events[(tone_events["start_time"] >= timestamps[0]) & (tone_events["stop_time"] < timestamps[-1])]
ax.plot(timestamps, data, color="green", linewidth=0.5)
for ind, row in light_events.iterrows():
ax.fill_between(timestamps, min(data), max(data), where=(timestamps >= row["start_time"]) & (timestamps <= row["stop_time"]), color='blue', edgecolor='none', alpha=0.1)
for ind, row in tone_events.iterrows():
ax.fill_between(timestamps, min(data), max(data), where=(timestamps >= row["start_time"]) & (timestamps <= row["stop_time"]), color='red', edgecolor='none', alpha=0.1)
# Create proxy lines for legend entries with corresponding colors and transparency
green_line = mlines.Line2D([], [], color='green', label='∆F/F from striatum', alpha=0.5)
blue_line = mlines.Line2D([], [], color='blue', label='Light', alpha=0.1)
red_line = mlines.Line2D([], [], color='red', label='Tone', alpha=0.1)
ax.legend(handles=[green_line, blue_line, red_line], frameon=False, bbox_to_anchor=(.95, 1), loc='upper left', prop={'size': 6})
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.tick_params(axis='y', labelsize=6)
ax.tick_params(axis='x', labelsize=6)
plt.xlabel('Time (s)', fontsize=6)
plt.show()