# report timestamp metadata on the version of interest
943)['time_stamp'] client.materialize.get_version_metadata(
datetime.datetime(2024, 1, 22, 8, 10, 1, 497934, tzinfo=datetime.timezone.utc)
Data Release v943 (January 22, 2024) is the first quarterly release of 2024.
This version ADDS the following tables
functional_properties_v3_bcm
: functional properties for each of the coregistered neurons
coregistration_manual_v4
: an update to the manual coregistration between functionally recorded units and EM cells
apl_functional_coreg_vess_fwd
, coregistration_auto_phase3_fwd
, and coregistration_auto_phase3_fwd_apl_vess_combined
: a set of tables that interact to build the automated coregistration model
A flat segmentation of the meshes is also available
The following tables from previous versions are included:
synapses_pni_2
( v117 )nucleus_detection_v0
( v117 )proofreading_status_public_release
( v343 )allen_v1_column_types_slanted_ref
( v661 )aibs_column_nonneuronal_ref
( v661 )baylor_log_reg_cell_type_coarse_v1
( v661 )coregistration_manual_v3
( v661 )nucleus_alternative_points
( v661 )nucleus_ref_neuron_svm
( v661 )allen_column_mtypes_v2
( v795 )aibs_metamodel_celltypes_v661
( v795 )aibs_metamodel_mtypes_v661_v2
( v795 )l5et_column
, bodor_pt_cells
, bodor_pt_target_proofread
, and pt_synapse_targets
( v795 )The following tables have been REMOVED (removed tables still available in version 795):
apl_functional_coreg_forward_v5
: removed and superseded by coregistration_auto_phase3_fwd_apl_vess_combined
aibs_soma_nuc_metamodel_preds_v117
: removed and superseded by aibs_metamodel_celltypes_v661
allen_minnie_extra_types
: a working table associated with v795
aibs_soma_nuc_exc_mtype_preds_v117
: removed and superseded by aibs_metamodel_mtypes_v661_v2
allen_column_mtypes_v1
: removed and superseded by allen_column_mtypes_v2
cell_edits_v661
: a working table associated with v795
Information about the version 943 release can be queried with the following:
# report timestamp metadata on the version of interest
client.materialize.get_version_metadata(943)['time_stamp']
datetime.datetime(2024, 1, 22, 8, 10, 1, 497934, tzinfo=datetime.timezone.utc)
Table name: functional_properties_v3_bcm
A summary of the functional properties for each of the coregistered neurons (as of coregistration_manual_v3
). For details, see (Ding et al. 2025)
The key columns are:
Column | Description |
---|---|
target_id |
Soma ID for the cell |
pt_position pt_supervoxel_id pt_root_id |
Bound spatial point columns associated with the centroid of the nucleus |
session |
The session index from functional imaging |
scan_idx |
The scan index from functional imaging |
unit_id |
The functional unit index from imaging. Only unique within scan and session |
pref_ori |
preferred orientation in radians (0 - pi), horizontal bar moving upward is 0 and orientation increases clockwise, extracted from model responses to oriented noise stimuli |
pref_dir |
preferred direction in radians (0 - 2pi), horizontal bar moving upward is 0 and orientation increases clockwise, extracted from model responses to oriented noise stimuli |
gOSI |
global orientation selectivity index |
gDSI |
global direction selectivity index |
cc_abs |
prediction performance of the model, higher is better |
This is a reference table on nucleus_detection_v0
, and can be indexed by the same nucleus id.
This table includes duplicate entries for the same ‘pt_root_id’ and nucleus id if the coregistered cell has multiple unit recordings
# Standard query
client.materialize.query_table('functional_properties_v3_bcm')
# Content-aware query
client.materialize.tables.functional_properties_v3_bcm(id=example_nucleus_id).query()
For more on how to interpret the table, see Annotation Tables.
Table name: coregistration_manual_v4
A table of EM nucleus centroids manually matched to Baylor functional units. A unique functional unit is identified by its session, scan_idx and unit_id. An EM nucleus centroid may have matched to more than one functional unit if it was scanned on more than one imaging field.
The key columns are:
Column | Description |
---|---|
id |
Soma ID for the cell |
pt_position pt_supervoxel_id pt_root_id |
Bound spatial point columns associated with the centroid of the cell nucleus |
session |
The session index from functional imaging |
scan_idx |
The scan index from functional imaging |
unit_id |
The functional unit index from imaging. Only unique within scan and session |
field |
The field index from functional imaging |
residual |
The residual distance between the functional and the assigned structural points after transformation, in microns |
score |
A separation score, measuring the difference between the residual distance to the assigned neuron and the distance to the nearest non-assigned neuron, in microns. This can be negative if the non-assigned neuron is closer than the assigned neuron. Larger values indicate fewer nearby neurons that could be confused with the assigned neuron. |
This is a reference table on nucleus_detection_v0
, and can be indexed by the same nucleus id.
This table includes duplicate entries for the same ‘pt_root_id’ and nucleus id if the coregistered cell has multiple unit recordings
# Standard query
client.materialize.query_table('coregistration_manual_v4')
# Content-aware query
client.materialize.tables.coregistration_manual_v4(id=example_nucleus_id).query()
This table coregistration_manual_v4
supercedes previous iterations of this table:
coregistration_manual_v3
coregistration_manual
For more on how to interpret the table, see Annotation Tables.
Table name: coregistration_auto_phase3_fwd_apl_vess_combined
A table of EM nucleus centroids automatically matched to Baylor functional units. This table reconciles the following two tables that both make a best match of the of registration using different techniques: coregistration_auto_phase3_fwd
and apl_functional_coreg_vess_fwd
. A unique functional unit is identified by its session, scan_idx and unit_id. An EM nucleus centroid may have matched to more than one functional unit if it was scanned on more than one imaging field.
The key columns are:
Column | Description |
---|---|
id |
Soma ID for the cell |
pt_position pt_supervoxel_id pt_root_id |
Bound spatial point columns associated with the centroid of the cell nucleus |
session |
The session index from functional imaging |
scan_idx |
The scan index from functional imaging |
unit_id |
The functional unit index from imaging. Only unique within scan and session |
field |
The field index from functional imaging |
residual |
The residual distance between the functional and the assigned structural points after transformation, in microns |
score |
A separation score, measuring the difference between the residual distance to the assigned neuron and the distance to the nearest non-assigned neuron, in microns. This can be negative if the non-assigned neuron is closer than the assigned neuron. Larger values indicate fewer nearby neurons that could be confused with the assigned neuron. |
This table remains available from materialization versions: 943, 1078, 1181
Use coregistration_auto_phase3_fwd_apl_vess_combined_v2
instead.
This table includes duplicate entries for the same pt_root_id
and nucleus id if the coregistered cell has multiple unit recordings
For more on how to interpret the table, see Annotation Tables.
Name | Volume | Cloudpath | Short Description | Type (size) |
---|---|---|---|---|
Proofread Segmentation (v943) | minnie65 | https://storage.googleapis.com/iarpa_microns/minnie/minnie65/seg_m943 |
Mulit-resolution flat / static cellular segmentation voxels and meshes from 8,8,40 nm and above | Precomputed Shareded Compressed Segmentation (12 TB) |
This contains the fixed state of the cellular segmentation at each version, where each voxel has been assigned an ID which is unique to each cellular object at 8,8,40, along with downsampled versions. Not all objects have been proofread, but a summary of the most focused efforts on cells can be found in the proofreading status metadata. In addition the mesh folder contains meshes of each object available at 3 different levels of downsampling. Folder contains many files, for download use cloud-volume, tensor-store, for bulk download use igneous, AWS CLI or gsutil CLI.