neuPrint¶

Neuprint is a service for presenting and analyzing connectomics data. It is used to host the Janelia EM reconstructions from a Drosophila hemibrain at https://neuprint.janelia.org/.

neuprint-python is a Python library that lets you query data directly from a neuprint server. You can install it from PyPI:

pip3 install neuprint-python

navis.interfaces.neuprint wraps neuprint-python and adds a few functions to fetch and convert data into navis objects.

# Import neuprint wrapper by navis
import navis.interfaces.neuprint as neu

First set up the connection: You can either pass your API token directly or store as NEUPRINT_APPLICATION_CREDENTIALS environment variable. We will use the latter option here:

client = neu.Client('https://neuprint.janelia.org/', dataset='hemibrain:v1.1')

You can use all of neuprint’s functions:

mbons, roi_info = neu.fetch_neurons(neu.SegmentCriteria(instance='.*MBON.*', regex=True))
mbons.head(3)

	bodyId	instance	type	pre	post	downstream	upstream	size	status	cropped	statusLabel	cellBodyFiber	somaRadius	somaLocation	roiInfo	notes	inputRois	outputRois
0	300972942	MBON14(a3)_R	MBON14	543	13634	4340	13634	1563154937	Traced	False	Roughly traced	None	NaN	None	{'MB(R)': {'pre': 17, 'post': 13295, 'downstre...	None	[MB(+ACA)(R), MB(R), SIP(R), SLP(R), SMP(R), S...	[MB(+ACA)(R), MB(R), SIP(R), SLP(R), SMP(R), S...
1	394225044	MBON14(a3)_L	MBON14	187	5172	768	5172	355138411	Traced	False	Roughly traced	None	NaN	None	{'MB(L)': {'pre': 185, 'post': 5143, 'downstre...	None	[MB(L), SIP(L), SNP(L), aL(L)]	[MB(L), SIP(L), SNP(L), aL(L)]
2	422725634	MBON06(B1>a)(AVM07)_L	MBON06	1356	21000	9584	21000	3118470391	Traced	False	Roughly traced	None	NaN	None	{'MB(R)': {'pre': 777, 'post': 20390, 'downstr...	None	[CRE(-ROB,-RUB)(R), CRE(R), INP, MB(+ACA)(R), ...	[CRE(-ROB,-RUB)(R), CRE(R), INP, MB(+ACA)(R), ...

NAVis has added three functions to neu:

navis.interfaces.neuprint.fetch_roi(): returns a navis.Volume from a ROI
navis.interfaces.neuprint.fetch_skeletons(): returns fully fledged navis.TreeNeuron - nodes, synapses, soma and all
navis.interfaces.neuprint.fetch_mesh_neuron(): returns navis.MeshNeuron - including synapses

mb = neu.fetch_roi('MB(R)')
mb

<navis.Volume(name=MB(R), color=(0.85, 0.85, 0.85, 0.2), vertices.shape=(57913, 3), faces.shape=(115856, 3))>

mbon_skeletons = neu.fetch_skeletons(neu.SegmentCriteria(instance='.*MBON.*_R', regex=True))
mbon_skeletons.head()

	type	name	id	n_nodes	n_connectors	n_branches	n_leafs	cable_length	soma	units
0	navis.TreeNeuron	MBON19(a2p3p)_R	423774471	6944	1783	549	561	246499.53125	1781.0	8 nanometer
1	navis.TreeNeuron	MBON14(a3)_R	300972942	22834	14177	2297	2369	758249.75000	NaN	8 nanometer
2	navis.TreeNeuron	MBON23(a2sp)_R	423382015	14190	5200	1195	1225	449662.18750	2364.0	8 nanometer
3	navis.TreeNeuron	MBON15-like(a'1a'2)_R	457175171	9051	2299	548	561	325558.90625	8810.0	8 nanometer
4	navis.TreeNeuron	MBON16-like(a'3a)_R	457196643	9769	4016	900	913	408057.59375	5974.0	8 nanometer

import navis

# Make a 3D plot
fig = navis.plot3d([mbon_skeletons[0], mb])