EM data acquisition: J. Kornfeld
Alignment: J. Kornfeld & A. Pope (V. Jain's team, Google Research)
SyConn processing: P. Schubert, A. Rother, H. Ahmad, J. Kornfeld
Cell & ultrastructure segmentation: M. Januszewski (V. Jain's team, Google Research)
EM data acquisition: J. Kornfeld
Alignment: J. Kornfeld & A. Pope (V. Jain's team, Google Research)
SyConn processing: P. Schubert, J. Kornfeld, S. Dorkenwald
Cell & ultrastructure segmentation: M. Januszewski (V. Jain's team, Google Research), S. Dorkenwald, P. Schubert
Please note that neuron reconstructions, synapse predictions, and cell-type classifications are best‑effort. We welcome feedback if you think you have discovered a systematic issue that deserves more attention. If you use this data in your work, please cite Rother et al., 2025 (see also songbird-connectomics.org/publications). The full connectome is available below as a public REST API and as direct downloads of the underlying arrays.
The currently available datasets, j0251 (256 × 256 × 384 µm) and j0126 (96 × 98 × 114 µm), were acquired from adult male zebra finch area X, a basal ganglia area responsible for song learning that contains striatal- and pallidal‑like cell types. Both datasets were acquired in the department of Winfried Denk at the MPI for Medical Research, Heidelberg.
The j0251 connectome (~18.36 M synapses, ~4.26 M neurons) can be queried in three ways: an interactive browser notebook, a public REST API, and direct downloads of the underlying NumPy arrays. For interactive analyses, see the API notebook; for programmatic access, the endpoints and downloads below.
Four endpoints. The two JSON endpoints accept rich filters (cell type, probability, synapse size, post-morphology, skeleton lengths) and tolerate concurrent clients. Skeleton and mesh fetches return binary blobs. Full parameter reference is in the API notebook and the agent guide (below).
GET /j0251/synapses/jsonmax_results is given.
curl "https://syconn.esc.mpcdf.mpg.de/j0251/synapses/json?pre_celltype=MSN&post_celltype=GPi&return_fields=x,y,z,size,prob&max_results=100"
GET /j0251/neurons/jsoncurl "https://syconn.esc.mpcdf.mpg.de/j0251/neurons/json?celltype=HVC&target_celltype=MSN&direction=outgoing&min_synapses=50"
GET /j0251/skeleton?neuron_id=<id>curl "https://syconn.esc.mpcdf.mpg.de/j0251/skeleton?neuron_id=930416054" -o skeleton.bin
GET /notebook/j0251/<version>/sv/<id>:0:<id>_meshcurl "https://syconn.esc.mpcdf.mpg.de/notebook/j0251/72_seg_20210127_agglo2_syn_20220811_celltypes_20230822/sv/930416054:0:930416054_mesh" -o mesh.bin
Note: HVC, LMAN, and DA are axon-only in
this dataset and cannot be used as post_celltype.
Default prob_min is 0.6.
The full filtered j0251 connectome as NumPy structured arrays, plus
the two label mappings. Loadable with
np.load(..., mmap_mode='r'); field schema is documented
in the agent guide.
All four files belong to dataset version
72_seg_20210127_agglo2_syn_20220811_celltypes_20230822.
j0251_…_filtered_synapses.npy
— 613 MB, 18,361,224 synapses
j0251_…_filtered_neurons.npy
— 94 MB, 4,261,298 neurons
j0251_…_filtered_celltype_mapping.txt
— cell-type name ↔ ID
j0251_…_filtered_post_morph_mapping.txt
— post-morphology code ↔ label (0=spine_neck, 1=spine_head, 2=shaft, 3=soma)
Cookbook-style markdown for AI coding agents (Claude and similar):
REST endpoint schemas with concrete curl examples, common filter
pitfalls, and how to load the raw .npy arrays in Python.
/connectome/connectome-guide.md