Connectomics

# Install all used libraries
!pip install -r ../../../requirements.txt --quiet
!pip install ../../../ --quiet

# Import libs and initialise API objects
from vfb_connect import vfb
import pandas as pd

import pymaid
import navis

navis.set_pbars(jupyter=False)
pymaid.set_pbars(jupyter=False)

# Connect to VFB's CATMAID server hosting the FAFB data
rm = pymaid.connect_catmaid(server="https://fafb.catmaid.virtualflybrain.org/", api_token=None, max_threads=10)

# Test call to see if connection works
print(f'Server is running CATMAID version {rm.catmaid_version}')

Welcome to the Virtual Fly Brain API
See the documentation at: https://virtualflybrain.org/docs/tutorials/apis/

Establishing connections to https://VirtualFlyBrain.org services...
Session Established!

Type vfb. and press tab to see available queries. You can run help against any query e.g. help(vfb.get_TermInfo)

INFO  : Global CATMAID instance set. Caching is ON. (pymaid)

Server is running CATMAID version 2020.02.15-102-gce1dee4

VFB provides a simple methods for exploring connectomics data

get_connected_neurons_by_type allows queries for connections between defined upstream and downstream neuron types/classes. This supports a level of abstraction not available without VFB, where grouping of neurons by higher level classifications is limited to extraction of classification from standardised names. The following examples take advantage of the abstract clasifications on VFB to explore direct synaptic connections.

vfb.get_terms_by_xref(['Trh-F-500041'], db='FlyCircuit')

	label	symbol	id	tags	description	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license
0	Trh-F-500041		VFB_00014110	[Entity, Adult, Anatomy, Cell, Expression_patt...	OutAge: Adult 5~15 days	[adult neuron, expression pattern fragment]	[FBbt_00047095, VFBext_0000004]	[FlyCircuit]	[Trh-F-500041]	[FlyCircuit:Trh-F-500041]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]

neurons_in_DA3 = vfb.get_instances("'neuron' that 'overlaps' some 'antennal lobe glomerulus DA3'")
neurons_in_DA3

	label	symbol	id	tags	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license	description
0	Uniglomerular mALT DA3 adPN#R2 (FAFB:65465)		VFB_00101240	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	[adult antennal lobe projection neuron DA3 adPN]	[FBbt_00100384]	[catmaid_fafb]	[65465]	[catmaid_fafb:65465]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....	NaN
1	Uniglomerular mALT DA3 adPN#R1 (FAFB:57349)		VFB_00101239	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	[adult antennal lobe projection neuron DA3 adPN]	[FBbt_00100384]	[catmaid_fafb]	[57349]	[catmaid_fafb:57349]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....	NaN
2	Uniglomerular mALT DA3 adPN#L2 (FAFB:2350853)		VFB_0010122u	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	[adult antennal lobe projection neuron DA3 adPN]	[FBbt_00100384]	[catmaid_fafb]	[2350853]	[catmaid_fafb:2350853]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....	NaN
3	Uniglomerular mALT DA3 adPN#L1 (FAFB:2449792)		VFB_0010123h	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	[adult antennal lobe projection neuron DA3 adPN]	[FBbt_00100384]	[catmaid_fafb]	[2449792]	[catmaid_fafb:2449792]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....	NaN
4	ORN_DA3_R (FlyEM-HB:1703683060)	ORN_DA3_R	VFB_jrchk183	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	[adult olfactory receptor neuron Or23a]	[FBbt_00067033]	[neuprint_JRC_Hemibrain_1point1]	[1703683060]	[neuronbridge:1703683060, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Orphan, cropped-None
...	...	...	...	...	...	...	...	...	...	...	...	...	...
153	lLN2T_a(Tortuous)_R (FlyEM-HB:5813055277)	lLN2T_a(Tortuous)_R	VFB_jrchk8bf	[Entity, Adult, Anatomy, Cell, Individual, Ner...	[adult antennal lobe local neuron lLN2T, adult...	[FBbt_00049816, FBbt_00049526]	[neuprint_JRC_Hemibrain_1point1]	[5813055277]	[neuprint_JRC_Hemibrain_1point1:5813055277, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
154	lLN2T_c(Tortuous)_R (FlyEM-HB:1671292719)	lLN2T_c(Tortuous)_R	VFB_jrchk8bo	[Entity, Adult, Anatomy, Cell, Individual, Ner...	[adult antennal lobe local neuron lLN2T]	[FBbt_00049816]	[neuprint_JRC_Hemibrain_1point1]	[1671292719]	[neuronbridge:1671292719, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
155	lLN2T_b(Tortuous)_R (FlyEM-HB:5813034493)	lLN2T_b(Tortuous)_R	VFB_jrchk8bm	[Entity, Adult, Anatomy, Cell, Individual, Ner...	[adult serotonergic neuron, adult antennal lob...	[FBbt_00049526, FBbt_00049816]	[neuprint_JRC_Hemibrain_1point1]	[5813034493]	[neuronbridge:5813034493, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
156	v2LN3b_R (FlyEM-HB:1888199872)	v2LN3b_R	VFB_jrchk8fg	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult antennal lobe local neuron v2LN3B, chol...	[FBbt_20003755, FBbt_00007403]	[neuprint_JRC_Hemibrain_1point1]	[1888199872]	[neuronbridge:1888199872, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
157	v2LN3b_R (FlyEM-HB:5813034455)	v2LN3b_R	VFB_jrchk8ff	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[cholinergic local interneuron of the adult an...	[FBbt_00007403, FBbt_20003755]	[neuprint_JRC_Hemibrain_1point1]	[5813034455]	[neuronbridge:5813034455, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False

158 rows × 13 columns

# Find all GABA-regic inputs onto descending neurons

vfb.get_connected_neurons_by_type(upstream_type='GABAergic neuron',
                                 downstream_type='adult descending neuron',
                                 weight=10).sort_values('weight', ascending=False, ignore_index=True)

	upstream_neuron_id	upstream_neuron_name	weight	downstream_neuron_id	downstream_neuron_name	upstream_class	downstream_class	up_data_source	up_accession	down_source	down_accession
0	VFB_jrchk79q	SMP594(SCB017)_R (FlyEM-HB:976934253)	492	VFB_jrchk70f	SMP454_R (FlyEM-HB:326253554)	adult superior medial protocerebrum neuron 594	adult superior medial protocerebrum neuron 454	None	None	None	None
1	VFB_jrchk79q	SMP594(SCB017)_R (FlyEM-HB:976934253)	393	VFB_jrchjsri	CL138_R (FlyEM-HB:707190304)	adult superior medial protocerebrum neuron 594	adult clamp neuron 138	None	None	None	None
2	VFB_jrchjrof	AVLP080_R (FlyEM-HB:5813027276)	373	VFB_jrchk4wd	PVLP136_R (FlyEM-HB:5813057178)	adult anterior ventrolateral protocerebrum neu...	adult posterior ventrolateral protocerebrum ne...	None	None	None	None
3	VFB_jrchjrek	AOTU019(ADM10)_L (FlyEM-HB:1605518663)	362	VFB_jrchk47t	PS017_R (FlyEM-HB:5813069484)	adult anterior optic tubercle neuron 019	adult posterior slope neuron 017	None	None	None	None
4	VFB_jrchjrob	AVLP076_R (FlyEM-HB:1135441187)	349	VFB_jrchk4wd	PVLP136_R (FlyEM-HB:5813057178)	adult anterior ventrolateral protocerebrum neu...	adult posterior ventrolateral protocerebrum ne...	None	None	None	None
...	...	...	...	...	...	...	...	...	...	...	...
1354	VFB_jrchk79p	SMP593(SCB014)_R (FlyEM-HB:549282467)	10	VFB_jrchk4a1	PS066(AVM08)_L (FlyEM-HB:1284675398)	adult superior medial protocerebrum neuron 593	adult posterior slope neuron 066	None	None	None	None
1355	VFB_jrchjrgi	AOTU053_R (FlyEM-HB:5813097142)	10	VFB_jrchk4a1	PS066(AVM08)_L (FlyEM-HB:1284675398)	adult anterior optic tubercle neuron 053	adult posterior slope neuron 066	None	None	None	None
1356	VFB_jrchjrej	AOTU019_R (FlyEM-HB:799868224)	10	VFB_jrchk0ve	MDN_R (FlyEM-HB:698016469)	adult anterior optic tubercle neuron 019	adult moonwalker descending neuron	None	None	None	None
1357	VFB_jrchjuut	IB060(PVL21)_L (FlyEM-HB:760806798)	10	VFB_jrchk7f7	VES029(AVM14)_L (FlyEM-HB:1099800130)	adult inferior bridge neuron 060	adult vest neuron 029	None	None	None	None
1358	VFB_jrchk4yr	SAD013_R (FlyEM-HB:5813024035)	10	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)	adult saddle neuron 013	descending neuron of the posterior brain DNp04	None	None	None	None

1359 rows × 11 columns

# Get connections between pacemaker neurons
clock_neuron_connectome = vfb.get_connected_neurons_by_type(upstream_type='pacemaker neuron',
                                 downstream_type='pacemaker neuron',
                                 weight=10).sort_values('weight', ascending=False)
clock_neuron_connectome

	upstream_neuron_id	upstream_neuron_name	weight	downstream_neuron_id	downstream_neuron_name	upstream_class	downstream_class	up_data_source	up_accession	down_source	down_accession
12	VFB_jrchjtex	DN1a_R (FlyEM-HB:264083994)	79	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	DN1a neuron	adult cholinergic neuron|LNd neuron	None	None	None	None
15	VFB_jrchjtey	DN1a_R (FlyEM-HB:5813022274)	75	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	DN1a neuron	adult cholinergic neuron|LNd neuron	None	None	None	None
25	VFB_jrchjtey	DN1a_R (FlyEM-HB:5813022274)	63	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	DN1a neuron	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
28	VFB_jrchjtex	DN1a_R (FlyEM-HB:264083994)	55	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	DN1a neuron	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
30	VFB_jrchk089	LPN_R (FlyEM-HB:480029788)	43	VFB_jrchk08a	LPN_R (FlyEM-HB:450034902)	adult LP neuron|adult dopaminergic neuron	adult LP neuron	None	None	None	None
16	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	40	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	adult cholinergic neuron|adult s-LNv neuron	adult cholinergic neuron|LNd neuron	None	None	None	None
24	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	37	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	adult cholinergic neuron|LNd neuron	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
19	VFB_jrchjtf0	DN1pA_R (FlyEM-HB:324846570)	37	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	ventro-contralateral-projecting DN1p neuron|ad...	adult cholinergic neuron|LNd neuron	None	None	None	None
18	VFB_jrchjtf2	DN1pA_R (FlyEM-HB:387944118)	34	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	adult glutamatergic neuron|ventro-contralatera...	adult cholinergic neuron|LNd neuron	None	None	None	None
26	VFB_jrchjtf1	DN1pA_R (FlyEM-HB:325529237)	33	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	adult glutamatergic neuron|ventro-contralatera...	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
13	VFB_jrchjtf1	DN1pA_R (FlyEM-HB:325529237)	30	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	adult glutamatergic neuron|ventro-contralatera...	adult cholinergic neuron|LNd neuron	None	None	None	None
31	VFB_jrchk08a	LPN_R (FlyEM-HB:450034902)	30	VFB_jrchk089	LPN_R (FlyEM-HB:480029788)	adult LP neuron	adult LP neuron|adult dopaminergic neuron	None	None	None	None
11	VFB_jrchjtf3	DN1pA_R (FlyEM-HB:387166379)	30	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	ventro-contralateral-projecting DN1p neuron|ad...	adult cholinergic neuron|LNd neuron	None	None	None	None
20	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	29	VFB_jrchjzxw	LNd_R (FlyEM-HB:5813056917)	adult cholinergic neuron|LNd neuron	adult cholinergic neuron|LNd neuron	None	None	None	None
8	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	25	VFB_jrchjzxx	LNd_R (FlyEM-HB:5813021192)	adult cholinergic neuron|adult s-LNv neuron	LNd neuron	None	None	None	None
29	VFB_jrchjtf3	DN1pA_R (FlyEM-HB:387166379)	25	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	ventro-contralateral-projecting DN1p neuron|ad...	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
27	VFB_jrchjtez	DN1pA_R (FlyEM-HB:5813010153)	25	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	adult glutamatergic neuron|ventro-contralatera...	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
22	VFB_jrchjtf0	DN1pA_R (FlyEM-HB:324846570)	25	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	ventro-contralateral-projecting DN1p neuron|ad...	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
23	VFB_jrchjtf2	DN1pA_R (FlyEM-HB:387944118)	22	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	adult glutamatergic neuron|ventro-contralatera...	adult cholinergic neuron|adult s-LNv neuron	None	None	None	None
9	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	21	VFB_jrchjzxx	LNd_R (FlyEM-HB:5813021192)	adult cholinergic neuron|LNd neuron	LNd neuron	None	None	None	None
21	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	17	VFB_jrchjzxw	LNd_R (FlyEM-HB:5813056917)	adult cholinergic neuron|adult s-LNv neuron	adult cholinergic neuron|LNd neuron	None	None	None	None
14	VFB_jrchjtez	DN1pA_R (FlyEM-HB:5813010153)	15	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	adult glutamatergic neuron|ventro-contralatera...	adult cholinergic neuron|LNd neuron	None	None	None	None
6	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	14	VFB_jrchjtf3	DN1pA_R (FlyEM-HB:387166379)	adult cholinergic neuron|adult s-LNv neuron	ventro-contralateral-projecting DN1p neuron|ad...	None	None	None	None
4	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	14	VFB_jrchjtf1	DN1pA_R (FlyEM-HB:325529237)	adult cholinergic neuron|LNd neuron	adult glutamatergic neuron|ventro-contralatera...	None	None	None	None
7	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	13	VFB_jrchjtf3	DN1pA_R (FlyEM-HB:387166379)	adult cholinergic neuron|LNd neuron	ventro-contralateral-projecting DN1p neuron|ad...	None	None	None	None
10	VFB_jrchjtf0	DN1pA_R (FlyEM-HB:324846570)	13	VFB_jrchjzxx	LNd_R (FlyEM-HB:5813021192)	ventro-contralateral-projecting DN1p neuron|ad...	LNd neuron	None	None	None	None
3	VFB_jrchk8e0	5th s-LNv (FlyEM-HB:511051477)	12	VFB_jrchjtf1	DN1pA_R (FlyEM-HB:325529237)	adult cholinergic neuron|adult s-LNv neuron	adult glutamatergic neuron|ventro-contralatera...	None	None	None	None
17	VFB_jrchjtf5	DN1pB_R (FlyEM-HB:5813071319)	11	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	anterior-projecting DN1p neuron|adult glutamat...	adult cholinergic neuron|LNd neuron	None	None	None	None
0	VFB_jrchjtey	DN1a_R (FlyEM-HB:5813022274)	11	VFB_jrchjtex	DN1a_R (FlyEM-HB:264083994)	DN1a neuron	DN1a neuron	None	None	None	None
1	VFB_jrchjtex	DN1a_R (FlyEM-HB:264083994)	10	VFB_jrchjtey	DN1a_R (FlyEM-HB:5813022274)	DN1a neuron	DN1a neuron	None	None	None	None
5	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	10	VFB_jrchjtez	DN1pA_R (FlyEM-HB:5813010153)	adult cholinergic neuron|LNd neuron	adult glutamatergic neuron|ventro-contralatera...	None	None	None	None
2	VFB_jrchjzxy	LNd_R (FlyEM-HB:5813069648)	10	VFB_jrchjtf2	DN1pA_R (FlyEM-HB:387944118)	adult cholinergic neuron|LNd neuron	adult glutamatergic neuron|ventro-contralatera...	None	None	None	None

# Get connections between visual projectsion neurons and descending neurons
visPN2DC = vfb.get_connected_neurons_by_type(upstream_type='visual projection neuron',
                                 downstream_type='adult descending neuron',
                                 weight=10).sort_values('weight', ascending=False)
visPN2DC

	upstream_neuron_id	upstream_neuron_name	weight	downstream_neuron_id	downstream_neuron_name	upstream_class	downstream_class	up_data_source	up_accession	down_source	down_accession
1701	VFB_jrchk09j	LT51(aSP29a)_R (FlyEM-HB:1282348408)	319	VFB_jrchjtfr	DNb01_R (FlyEM-HB:1566597156)	adult glutamatergic neuron|lobula tangential n...	descending neuron of the anterior ventral brai...	None	None	None	None
53	VFB_jrchk7g6	VES044_R (FlyEM-HB:5812979017)	262	VFB_jrchk7eb	VES009_R (FlyEM-HB:1140923511)	adult vest neuron 044	adult vest neuron 009	None	None	None	None
1332	VFB_jrchk09h	LT51_R (FlyEM-HB:5813069020)	238	VFB_jrchk7e7	VES006_R (FlyEM-HB:642728308)	lobula tangential neuron LT51|adult glutamater...	adult vest neuron 006	None	None	None	None
1668	VFB_jrchk0bu	LT86_R (FlyEM-HB:1285849916)	228	VFB_jrchk7g4	VES042_R (FlyEM-HB:1875284107)	lobula tangential neuron|adult cholinergic neuron	adult vest neuron 042	None	None	None	None
11	VFB_jrchk09c	LT51_R (FlyEM-HB:1444351896)	221	VFB_jrchjtfg	DNa03_R (FlyEM-HB:1139909038)	adult glutamatergic neuron|lobula tangential n...	descending neuron of the anterior dorsal brain...	None	None	None	None
...	...	...	...	...	...	...	...	...	...	...	...
1026	VFB_jrchjzoi	LLPC2a (FlyEM-HB:5813039328)	10	VFB_jrchjtfo	DNa10_R (FlyEM-HB:707116522)	lobula-lobula plate columnar neuron LLPC	descending neuron of the posterior brain DNp10	None	None	None	None
1020	VFB_jrchjwwh	LC10 (FlyEM-HB:5813016041)	10	VFB_jrchjtfo	DNa10_R (FlyEM-HB:707116522)	adult cholinergic neuron|lobula columnar neuro...	descending neuron of the posterior brain DNp10	None	None	None	None
1019	VFB_jrchjzul	LLPC3 (FlyEM-HB:1777956777)	10	VFB_jrchjtfo	DNa10_R (FlyEM-HB:707116522)	lobula-lobula plate columnar neuron LLPC	descending neuron of the posterior brain DNp10	None	None	None	None
1014	VFB_jrchjy7z	LC35_R (FlyEM-HB:1502364155)	10	VFB_jrchjtge	DNp10_R (FlyEM-HB:5813026936)	lobula columnar neuron|adult cholinergic neuron	descending neuron of the posterior brain DNp10	None	None	None	None
1706	VFB_jrchjuts	IB043_R (FlyEM-HB:883514695)	10	VFB_jrchjtfr	DNb01_R (FlyEM-HB:1566597156)	adult inferior bridge neuron 043	descending neuron of the anterior ventral brai...	None	None	None	None

1707 rows × 11 columns

visPN2DC['upstream_class'].value_counts(normalize=True).plot(kind = 'bar') # Excercise - sum up weights for each type.  Note - some types here subsume others

<Axes: xlabel='upstream_class'>

Get neurons downstream/downstream of a specific neuron

Starting from an individual neuron, in this case an individual neuron from hemibrain, find all neurons upstream or downstream, restricting to edges >= some specified wieght (synaptic connections) and optionally limiting the output by neuron type/class.

# Starting point - let's take one of the individual descending neurons from
# the previous exploratory queries and look for other inputs

upstream_of_DNp04 = vfb.get_neurons_upstream_of('DNp04_R (FlyEM-HB:1405231475)', weight = 20)
upstream_of_DNp04

	query_neuron_id	query_neuron_name	weight	target_neuron_id	target_neuron_name
0	VFB_jrchjy9x	LC4 (FlyEM-HB:1938544937)	98	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
1	VFB_jrchjy9p	LC4 (FlyEM-HB:1815070402)	97	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
2	VFB_jrchjyad	LC4 (FlyEM-HB:1908226457)	93	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
3	VFB_jrchjya0	LC4 (FlyEM-HB:5812998136)	92	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
4	VFB_jrchjyah	LC4 (FlyEM-HB:1938207942)	90	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
...	...	...	...	...	...
82	VFB_jrchk063	LPLC2_R (FlyEM-HB:5813034151)	24	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
83	VFB_jrchk4oy	PVLP023_R (FlyEM-HB:1598296804)	23	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
84	VFB_jrchjrof	AVLP080_R (FlyEM-HB:5813027276)	22	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
85	VFB_jrchk4p4	PVLP026_R (FlyEM-HB:1570565128)	21	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
86	VFB_jrchk4pd	PVLP031_R (FlyEM-HB:1630342124)	20	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)

87 rows × 5 columns

vfb.get_TermInfo(upstream_of_DNp04['query_neuron_id'])

	label	symbol	id	tags	description	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license
0	LPLC2_R (FlyEM-HB:5813034151)	LPLC2_R	VFB_jrchk063	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[lobula plate-lobula columnar neuron LPLC2]	[FBbt_00111763]	[neuprint_JRC_Hemibrain_1point1]	[5813034151]	[neuronbridge:5813034151, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
1	LC4 (FlyEM-HB:1625080038)	LC4	VFB_jrchjy9e	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1625080038]	[neuprint_JRC_Hemibrain_1point1:1625080038, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
2	LC4 (FlyEM-HB:1782668028)	LC4	VFB_jrchjy9o	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1782668028]	[neuronbridge:1782668028, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
3	LC4 (FlyEM-HB:1874035952)	LC4	VFB_jrchjy9z	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1874035952]	[neuprint_JRC_Hemibrain_1point1:1874035952, ne...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
4	LC4 (FlyEM-HB:1810956698)	LC4	VFB_jrchjy9j	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1810956698]	[neuprint_JRC_Hemibrain_1point1:1810956698, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
...	...	...	...	...	...	...	...	...	...	...	...	...	...
82	SAD017_R (FlyEM-HB:1630678915)	SAD017_R	VFB_jrchk4z0	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult saddle neuron 017]	[FBbt_20002226]	[neuprint_JRC_Hemibrain_1point1]	[1630678915]	[neuronbridge:1630678915, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
83	PVLP142_R (FlyEM-HB:1876565477)	PVLP142_R	VFB_jrchk4wk	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult cholinergic neuron, adult posterior ven...	[FBbt_00058205, FBbt_20002200]	[neuprint_JRC_Hemibrain_1point1]	[1876565477]	[neuronbridge:1876565477, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
84	PVLP151(SCB004)_L (FlyEM-HB:1628973439)	PVLP151(SCB004)_L	VFB_jrchk4x2	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult posterior ventrolateral protocerebrum n...	[FBbt_20002209]	[neuprint_JRC_Hemibrain_1point1]	[1628973439]	[neuronbridge:1628973439, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
85	PVLP100_R (FlyEM-HB:1375845363)	PVLP100_R	VFB_jrchk4u3	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult posterior ventrolateral protocerebrum n...	[FBbt_20002158]	[neuprint_JRC_Hemibrain_1point1]	[1375845363]	[neuronbridge:1375845363, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
86	PVLP094_R (FlyEM-HB:1503733177)	PVLP094_R	VFB_jrchk4tm	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult posterior ventrolateral protocerebrum n...	[FBbt_20002152]	[neuprint_JRC_Hemibrain_1point1]	[1503733177]	[neuprint_JRC_Hemibrain_1point1:1503733177, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...

87 rows × 13 columns

vfb.get_TermInfo(upstream_of_DNp04['query_neuron_id'])

	label	symbol	id	tags	description	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license
0	LPLC2_R (FlyEM-HB:5813034151)	LPLC2_R	VFB_jrchk063	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[lobula plate-lobula columnar neuron LPLC2]	[FBbt_00111763]	[neuprint_JRC_Hemibrain_1point1]	[5813034151]	[neuronbridge:5813034151, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
1	LC4 (FlyEM-HB:1625080038)	LC4	VFB_jrchjy9e	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1625080038]	[neuprint_JRC_Hemibrain_1point1:1625080038, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
2	LC4 (FlyEM-HB:1782668028)	LC4	VFB_jrchjy9o	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1782668028]	[neuronbridge:1782668028, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
3	LC4 (FlyEM-HB:1874035952)	LC4	VFB_jrchjy9z	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1874035952]	[neuprint_JRC_Hemibrain_1point1:1874035952, ne...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
4	LC4 (FlyEM-HB:1810956698)	LC4	VFB_jrchjy9j	[Entity, Adult, Anatomy, Cell, Cholinergic, Gl...	tracing status-Roughly traced, cropped-False	[lobula columnar neuron LC4]	[FBbt_00003874]	[neuprint_JRC_Hemibrain_1point1]	[1810956698]	[neuprint_JRC_Hemibrain_1point1:1810956698, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
...	...	...	...	...	...	...	...	...	...	...	...	...	...
82	SAD017_R (FlyEM-HB:1630678915)	SAD017_R	VFB_jrchk4z0	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult saddle neuron 017]	[FBbt_20002226]	[neuprint_JRC_Hemibrain_1point1]	[1630678915]	[neuronbridge:1630678915, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
83	PVLP142_R (FlyEM-HB:1876565477)	PVLP142_R	VFB_jrchk4wk	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult cholinergic neuron, adult posterior ven...	[FBbt_00058205, FBbt_20002200]	[neuprint_JRC_Hemibrain_1point1]	[1876565477]	[neuronbridge:1876565477, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
84	PVLP151(SCB004)_L (FlyEM-HB:1628973439)	PVLP151(SCB004)_L	VFB_jrchk4x2	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult posterior ventrolateral protocerebrum n...	[FBbt_20002209]	[neuprint_JRC_Hemibrain_1point1]	[1628973439]	[neuronbridge:1628973439, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
85	PVLP100_R (FlyEM-HB:1375845363)	PVLP100_R	VFB_jrchk4u3	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult posterior ventrolateral protocerebrum n...	[FBbt_20002158]	[neuprint_JRC_Hemibrain_1point1]	[1375845363]	[neuronbridge:1375845363, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
86	PVLP094_R (FlyEM-HB:1503733177)	PVLP094_R	VFB_jrchk4tm	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult posterior ventrolateral protocerebrum n...	[FBbt_20002152]	[neuprint_JRC_Hemibrain_1point1]	[1503733177]	[neuprint_JRC_Hemibrain_1point1:1503733177, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...

87 rows × 13 columns

Let’s try a similar query from one of the LC4 neurons to see what other descending neuron types are downstream of it.

vfb.get_neurons_downstream_of('LC4 (FlyEM-HB:1249932198)', classification="'adult descending neuron'", weight = 10)

	query_neuron_id	query_neuron_name	weight	target_neuron_id	target_neuron_name
0	VFB_jrchjy8y	LC4 (FlyEM-HB:1249932198)	78	VFB_jrchjtg7	DNp04_R (FlyEM-HB:1405231475)
1	VFB_jrchjy8y	LC4 (FlyEM-HB:1249932198)	65	VFB_jrchjtgf	DNp11_R (FlyEM-HB:1281324958)
2	VFB_jrchjy8y	LC4 (FlyEM-HB:1249932198)	30	VFB_jrchjup1	Giant Fiber_R (FlyEM-HB:2307027729)
3	VFB_jrchjy8y	LC4 (FlyEM-HB:1249932198)	11	VFB_jrchjtg6	DNp03_R (FlyEM-HB:1565846637)

More sophisticated connectomics queries require direct queries of connectomics DB APIs

CATMAID connectivity queries

Broadly speaking, using pymaid to query CATMAID servers lets you fetch connectivity data as either lists of up- and downstream partners or as whole adjacency matrices.

These examples use the VFB FAFB server.

# Using VFB to get neurons by type
DA1 = vfb.get_instances("'adult antennal lobe projection neuron DA1'")
len(DA1)
DA1

Warning: called a non existant id:VFB_00102294

	label	symbol	id	tags	description	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license
0	Gad1-F-400088		VFB_00009611	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[expression pattern fragment, adult antennal l...	[VFBext_0000004, FBbt_00067372]	[FlyCircuit]	[Gad1-F-400088]	[FlyCircuit:Gad1-F-400088]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
1	Uniglomerular mALT DA1 lPN#L1 (FAFB:4207871)		VFB_0010126e	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult fruitless aDT-e (female) neuron, adult ...	[FBbt_00110423, FBbt_00067363]	[catmaid_fafb]	[4207871]	[catmaid_fafb:4207871]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
2	Uniglomerular mALT DA1 lPN#L6 (FAFB:2381753)		VFB_0010123b	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[catmaid_fafb]	[2381753]	[catmaid_fafb:2381753]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
3	Uniglomerular mALT DA1 lPN#L3 (FAFB:2345089)		VFB_0010122p	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult fruitless aDT-e (female) neuron, adult ...	[FBbt_00110423, FBbt_00067363]	[catmaid_fafb]	[2345089]	[catmaid_fafb:2345089]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
4	Uniglomerular mlALT DA1 vPN#L1 (FAFB:2334841)		VFB_0010122m	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 vPN]	[FBbt_00067372]	[catmaid_fafb]	[2334841]	[catmaid_fafb:2334841]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
5	Uniglomerular mALT DA1 lPN#L2 (FAFB:2319457)		VFB_0010122k	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[catmaid_fafb]	[2319457]	[catmaid_fafb:2319457]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
6	Uniglomerular mALT DA1 lPN#L7 (FAFB:3239781)		VFB_0010124l	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult fruitless aDT-e (female) neuron, adult ...	[FBbt_00110423, FBbt_00067363]	[catmaid_fafb]	[3239781]	[catmaid_fafb:3239781]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
7	Uniglomerular mALT DA1 lPN#L5 (FAFB:2380564)		VFB_0010122z	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[catmaid_fafb]	[2380564]	[catmaid_fafb:2380564]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
8	Uniglomerular mlALT DA1 vPN#R1 (FAFB:1811442)		VFB_0010121x	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 vPN]	[FBbt_00067372]	[catmaid_fafb]	[1811442]	[catmaid_fafb:1811442]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
9	Uniglomerular mALT DA1 lPN#R5 (FAFB:2863104)		VFB_0010124e	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[catmaid_fafb]	[2863104]	[catmaid_fafb:2863104]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
10	Uniglomerular mALT DA1 lPN#L4 (FAFB:2379517)		VFB_0010122y	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[catmaid_fafb]	[2379517]	[catmaid_fafb:2379517]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
11	Uniglomerular mALT DA1 lPN#R4 (FAFB:755022)		VFB_00101205	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[755022]	[catmaid_fafb:755022]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
12	Uniglomerular mALT DA1 lPN#R7 (FAFB:57353)		VFB_00101202	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[57353]	[catmaid_fafb:57353]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
13	Uniglomerular mALT DA1 lPN#R1 (FAFB:57323)		VFB_00101201	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[57323]	[catmaid_fafb:57323]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
14	Uniglomerular mALT DA1 lPN#R3 (FAFB:61221)		VFB_00101204	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[61221]	[catmaid_fafb:61221]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
15	Uniglomerular mALT DA1 lPN#R2 (FAFB:57311)		VFB_00101200	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[57311]	[catmaid_fafb:57311]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
16	Uniglomerular mALT DA1 lPN#R8 (FAFB:57381)		VFB_00101203	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[57381]	[catmaid_fafb:57381]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
17	Multiglomerular mALT lvPN#R45 (FAFB:57035)		VFB_001011z3	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[catmaid_fafb]	[57035]	[catmaid_fafb:57035]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
18	Multiglomerular mALT lvPN#R46 (FAFB:57179)		VFB_001011zb	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[catmaid_fafb]	[57179]	[catmaid_fafb:57179]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
19	Multiglomerular mALT lvPN#R44 (FAFB:57158)		VFB_001011z9	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[catmaid_fafb]	[57158]	[catmaid_fafb:57158]	[JRC2018Unisex]	[BatesSchlegel2020]	[https://creativecommons.org/licenses/by-sa/4....
20	Uniglomerular mALT DA1 lPN#R6 (FAFB:27295)		VFB_00101199	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	NaN	[adult antennal lobe projection neuron DA1 lPN]	[FBbt_00067363]	[catmaid_fafb]	[27295]	[catmaid_fafb:27295]	[JRC2018Unisex]	[Zheng2018]	[https://creativecommons.org/licenses/by-sa/4....
21	Cha-F-300252		VFB_00005625	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[expression pattern fragment, adult ALl1 linea...	[VFBext_0000004, FBbt_00050025, FBbt_00067350,...	[FlyCircuit]	[Cha-F-300252]	[FlyCircuit:Cha-F-300252]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
22	VGlut-F-800329		VFB_00005957	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[antennal lobe projection neuron of ALl1 linea...	[FBbt_00067362, FBbt_00067350, VFBext_0000004,...	[FlyCircuit]	[VGlut-F-800329]	[FlyCircuit:VGlut-F-800329]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
23	VGlut-F-800317		VFB_00005913	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[antennal lobe projection neuron of ALl1 linea...	[FBbt_00067362, VFBext_0000004, FBbt_00050025,...	[FlyCircuit]	[VGlut-F-800317]	[FlyCircuit:VGlut-F-800317]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
24	VGlut-F-000655		VFB_00006552	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[adult antennal lobe projection neuron DA1, ad...	[FBbt_00048096, FBbt_00050025, FBbt_00067362, ...	[FlyCircuit]	[VGlut-F-000655]	[FlyCircuit:VGlut-F-000655]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
25	VGlut-F-200574		VFB_00006638	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[medial antennal lobe tract projection neuron,...	[FBbt_00067350, VFBext_0000004, FBbt_00048096,...	[FlyCircuit]	[VGlut-F-200574]	[FlyCircuit:VGlut-F-200574]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
26	fru-F-400149		VFB_00006344	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[medial antennal lobe tract projection neuron,...	[FBbt_00067350, VFBext_0000004, FBbt_00048096,...	[FlyCircuit]	[fru-F-400149]	[FlyCircuit:fru-F-400149]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
27	M_lvPNm45_R (FlyEM-HB:792023887)	M_lvPNm45_R	VFB_jrchk0xm	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[neuprint_JRC_Hemibrain_1point1]	[792023887]	[neuronbridge:792023887, neuprint_JRC_Hemibrai...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
28	M_lvPNm45_R (FlyEM-HB:757591093)	M_lvPNm45_R	VFB_jrchk0xl	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[neuprint_JRC_Hemibrain_1point1]	[757591093]	[neuprint_JRC_Hemibrain_1point1:757591093, neu...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
29	M_lvPNm45_R (FlyEM-HB:757258507)	M_lvPNm45_R	VFB_jrchk0xk	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[neuprint_JRC_Hemibrain_1point1]	[757258507]	[neuprint_JRC_Hemibrain_1point1:757258507, neu...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
30	Multiglomerular mALT lvPN#L3 (FAFB:4520615)		VFB_00102dvz	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	Multiglomerular mALT lvPN#L3, FBbt:00049785	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[catmaid_fafb]	[4520615]	[catmaid_fafb:4520615]	[JRC2018Unisex]	[TaiszGalili2022]	[https://creativecommons.org/licenses/by-sa/4....
31	Multiglomerular mALT lvPN#L2 (FAFB:7710838)		VFB_00102dw8	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	Multiglomerular mALT lvPN#L2, FBbt:00049785	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[catmaid_fafb]	[7710838]	[catmaid_fafb:7710838]	[JRC2018Unisex]	[TaiszGalili2022]	[https://creativecommons.org/licenses/by-sa/4....
32	Multiglomerular mALT lvPN#L1 (FAFB:4520197)		VFB_00102dvy	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	Multiglomerular mALT lvPN#L1, FBbt:00049785	[adult antennal lobe projection neuron DA1 lvPN]	[FBbt_20003824]	[catmaid_fafb]	[4520197]	[catmaid_fafb:4520197]	[JRC2018Unisex]	[TaiszGalili2022]	[https://creativecommons.org/licenses/by-sa/4....
33	DA1_lPN_R (FlyEM-HB:5813039315)	DA1_lPN_R	VFB_jrchjtdd	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult fruitless aDT-e (female) neuron, adult ...	[FBbt_00110423, FBbt_00067363]	[neuprint_JRC_Hemibrain_1point1]	[5813039315]	[neuronbridge:5813039315, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
34	DA1_lPN_R (FlyEM-HB:1734350908)	DA1_lPN_R	VFB_jrchjtdb	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[neuprint_JRC_Hemibrain_1point1]	[1734350908]	[neuprint_JRC_Hemibrain_1point1:1734350908, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
35	DA1_lPN_R (FlyEM-HB:754534424)	DA1_lPN_R	VFB_jrchjtde	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[neuprint_JRC_Hemibrain_1point1]	[754534424]	[neuronbridge:754534424, neuprint_JRC_Hemibrai...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
36	DA1_vPN_R (FlyEM-HB:733316908)	DA1_vPN_R	VFB_jrchjtdh	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 vPN]	[FBbt_00067372]	[neuprint_JRC_Hemibrain_1point1]	[733316908]	[neuronbridge:733316908, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
37	DA1_lPN_R (FlyEM-HB:1765040289)	DA1_lPN_R	VFB_jrchjtdc	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[neuprint_JRC_Hemibrain_1point1]	[1765040289]	[neuronbridge:1765040289, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
38	DA1_lPN_R (FlyEM-HB:722817260)	DA1_lPN_R	VFB_jrchjtda	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron DA1 lPN...	[FBbt_00067363, FBbt_00110423]	[neuprint_JRC_Hemibrain_1point1]	[722817260]	[neuprint_JRC_Hemibrain_1point1:722817260, neu...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
39	DA1_lPN_R (FlyEM-HB:1734350788)	DA1_lPN_R	VFB_jrchjtdf	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult fruitless aDT-e (female) neuron, adult ...	[FBbt_00110423, FBbt_00067363]	[neuprint_JRC_Hemibrain_1point1]	[1734350788]	[neuprint_JRC_Hemibrain_1point1:1734350788, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
40	DA1_lPN_R (FlyEM-HB:754538881)	DA1_lPN_R	VFB_jrchjtdg	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	tracing status-Roughly traced, cropped-False	[adult fruitless aDT-e (female) neuron, adult ...	[FBbt_00110423, FBbt_00067363]	[neuprint_JRC_Hemibrain_1point1]	[754538881]	[neuronbridge:754538881, neuprint_JRC_Hemibrai...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
41	Cha-F-500006		VFB_00010085	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[adult ALl1 lineage neuron, expression pattern...	[FBbt_00050025, VFBext_0000004, FBbt_00048096,...	[FlyCircuit]	[Cha-F-500006]	[FlyCircuit:Cha-F-500006]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
42	VGlut-F-000280		VFB_00010758	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[adult antennal lobe projection neuron DA1, me...	[FBbt_00048096, FBbt_00067350, FBbt_00067362, ...	[FlyCircuit]	[VGlut-F-000280]	[FlyCircuit:VGlut-F-000280]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
43	VGlut-F-600450		VFB_00010984	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[medial antennal lobe tract projection neuron,...	[FBbt_00067350, FBbt_00048096, FBbt_00067362, ...	[FlyCircuit]	[VGlut-F-600450]	[FlyCircuit:VGlut-F-600450]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
44	VGlut-F-700188		VFB_00010912	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[antennal lobe projection neuron of ALl1 linea...	[FBbt_00067362, FBbt_00050025, FBbt_00048096, ...	[FlyCircuit]	[VGlut-F-700188]	[FlyCircuit:VGlut-F-700188]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
45	Gad1-F-200064		VFB_00011249	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[antennal lobe projection neuron of ALl1 linea...	[FBbt_00067362, FBbt_00048096, FBbt_00050025, ...	[FlyCircuit]	[Gad1-F-200064]	[FlyCircuit:Gad1-F-200064]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
46	Gad1-F-200010		VFB_00012622	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[adult antennal lobe projection neuron DA1, ad...	[FBbt_00048096, FBbt_00050025, FBbt_00067362, ...	[FlyCircuit]	[Gad1-F-200010]	[FlyCircuit:Gad1-F-200010]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
47	VGlut-F-600326		VFB_00012155	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[expression pattern fragment, medial antennal ...	[VFBext_0000004, FBbt_00067350, FBbt_00050025,...	[FlyCircuit]	[VGlut-F-600326]	[FlyCircuit:VGlut-F-600326]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
48	VGlut-F-700040		VFB_00013061	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[expression pattern fragment, adult antennal l...	[VFBext_0000004, FBbt_00048096, FBbt_00067362,...	[FlyCircuit]	[VGlut-F-700040]	[FlyCircuit:VGlut-F-700040]	[adult brain template JFRC2, JRC2018Unisex]	[Chiang2010]	[]
49	fru-M-200319		VFB_00000323	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[antennal lobe projection neuron of ALl1 linea...	[FBbt_00067362, FBbt_00067350, VFBext_0000004,...	[FlyCircuit]	[fru-M-200319]	[FlyCircuit:fru-M-200319]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]
50	npf-M-300006		VFB_00001755	[Entity, Adult, Anatomy, Cell, Chemosensory_sy...	OutAge: Adult 5~15 days	[medial antennal lobe tract projection neuron,...	[FBbt_00067350, FBbt_00067362, FBbt_00050025, ...	[FlyCircuit]	[npf-M-300006]	[FlyCircuit:npf-M-300006]	[JRC2018Unisex, adult brain template JFRC2]	[Chiang2010]	[]

# Map neurons to CATMAID Skeleton IDs (skids)

da1_skids = vfb.vfb_id_2_xrefs(DA1['id'], db='catmaid_fafb', reverse_return=True)
da1_skids_int = list(map(int, da1_skids))
print(da1_skids_int)

# print is just used so we can see the list as a single line

33mWarning: The following IDs do not match DB &/or id_type constraints: {'VFB_00101200', 'VFB_00101201', 'VFB_jrchjtdf', 'VFB_00101202', 'VFB_0010122m', 'VFB_00005957', 'VFB_0010122z', 'VFB_00101204', 'VFB_00001755', 'VFB_00012155', 'VFB_0010123b', 'VFB_00010984', 'VFB_jrchk0xl', 'VFB_jrchjtdh', 'VFB_00009611', 'VFB_00102dvy', 'VFB_00010912', 'VFB_00010758', 'VFB_jrchk0xk', 'VFB_0010121x', 'VFB_00006344', 'VFB_00013061', 'VFB_00012622', 'VFB_00000323', 'VFB_00010085', 'VFB_00006638', 'VFB_jrchk0xm', 'VFB_00005913', 'VFB_jrchjtde', 'VFB_0010122y', 'VFB_jrchjtdb', 'VFB_001011z9', 'VFB_001011z3', 'VFB_jrchjtdc', 'VFB_00102dw8', 'VFB_00101205', 'VFB_jrchjtdd', 'VFB_0010124e', 'VFB_0010122k', 'VFB_001011zb', 'VFB_0010122p', 'VFB_00102dvz', 'VFB_0010126e', 'VFB_00101203', 'VFB_jrchjtda', 'VFB_00011249', 'VFB_00101199', 'VFB_0010124l', 'VFB_00005625', 'VFB_00006552', 'VFB_jrchjtdg'}
[2381753, 7710838, 4520197, 57179, 2379517, 3239781, 57158, 57035, 2345089, 57311, 27295, 2380564, 2319457, 4520615, 57323, 2334841, 755022, 1811442, 61221, 57353, 4207871, 57381, 2863104]

Generate a connectivity table for neurons downstream of DA1 neurons

da1 = pymaid.get_neurons(da1_skids_int)
da1_ds = pymaid.get_partners(da1_skids_int,
                             threshold=3,  # anything with >= 3 synapses
                             directions=['outgoing']  # downstream partners only
                            )

# Result is a pandas DataFrame
da1_ds.head()

INFO  : Fetching connectivity table for 23 neurons (pymaid)
INFO  : Done. Found 0 pre-, 301 postsynaptic and 0 gap junction-connected neurons (pymaid)

	neuron_name	skeleton_id	num_nodes	relation	2381753	7710838	4520197	57179	2379517	3239781	...	57323	2334841	755022	1811442	61221	57353	4207871	57381	2863104	total
0	Uniglomerular mlALT DA1 vPN mlALTed Milk 18114...	1811442	11769	downstream	0	0	0	0	0	0	...	20	0	32	0	26	3	0	4	30	152
1	Uniglomerular mlALT DA1 vPN mlALTed Milk 23348...	2334841	6362	downstream	32	0	0	0	28	26	...	0	0	0	0	0	0	17	0	0	139
2	LHAV4c1#1 488056 downstream DA1 GSXEJ	488055	12137	downstream	0	0	0	13	0	0	...	11	0	15	0	15	3	0	0	15	111
3	LHAV4a4#1 1911125 FML PS RJVR	1911124	6969	downstream	0	0	0	0	0	0	...	15	0	19	0	13	6	0	9	23	109
4	LHAV2a3#1 1870231 RJVR AJES PS	1870230	14820	downstream	0	0	0	0	0	0	...	7	0	19	1	7	23	0	28	5	105

5 rows × 28 columns

# Get an adjacency matrix between all Bates, Schlegel et al. neurons
bates = pymaid.find_neurons(annotations='Paper: Bates and Schlegel et al 2020')
adj = pymaid.adjacency_matrix(bates)
adj.head()

INFO  : Found 584 neurons matching the search parameters (pymaid)

targets	2863104	57349	57353	16	57361	15738898	57365	4182038	3813399	11524119	...	57323	4624362	1853423	2842610	57333	4624374	3080183	57337	4624378	57341
sources
2863104	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	2.0	0.0	12.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
57349	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
57353	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	5.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
16	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	0.0	1.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
57361	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

5 rows × 584 columns

import seaborn as sns

ax = sns.clustermap(adj, vmax=10, cmap='Greys')
# ax = sns.heatmap(adj, vmax=10, cmap='Greys')

/Users/robbiecourt/GIT/VFB_connect/.conda/lib/python3.10/site-packages/seaborn/matrix.py:560: UserWarning: Clustering large matrix with scipy. Installing `fastcluster` may give better performance.
  warnings.warn(msg)
/Users/robbiecourt/GIT/VFB_connect/.conda/lib/python3.10/site-packages/seaborn/matrix.py:560: UserWarning: Clustering large matrix with scipy. Installing `fastcluster` may give better performance.
  warnings.warn(msg)

# Axo-axonic connections between two different types of DA1 PNs
cn = pymaid.get_connectors_between(2863104, 1811442)
cn.head()

	connector_id	connector_loc	node1_id	source_neuron	confidence1	creator1	node1_loc	node2_id	target_neuron	confidence2	creator2	node2_loc
0	17870563	[363219.0, 169182.0, 153920.0]	6903652	2863104	5	NaN	[362894.0, 169511.0, 153920.0]	6546760	1811442	5	NaN	[363421.0, 168741.0, 153920.0]
1	6795747	[355030.0, 154048.0, 145800.0]	6795749	2863104	5	NaN	[355045.0, 154180.0, 145800.0]	6795745	1811442	5	NaN	[355024.0, 153946.0, 145760.0]
2	6826199	[358042.0, 160788.0, 147600.0]	6826200	2863104	5	NaN	[355948.0, 160126.0, 147600.0]	6826198	1811442	5	NaN	[358194.0, 160883.0, 147600.0]
3	6835037	[354306.0, 154100.0, 152320.0]	6835043	2863104	5	NaN	[354088.0, 153842.0, 152320.0]	6835033	1811442	5	NaN	[354400.0, 154346.0, 152360.0]
4	7032350	[355192.0, 167586.0, 158320.0]	7032356	2863104	5	NaN	[354814.0, 167861.0, 158320.0]	17870268	1811442	5	NaN	[356626.0, 167779.0, 158200.0]

import numpy as np

points = np.vstack(cn.connector_loc)

navis.plot3d([da1.idx[[1811442, 57353]],  # plot the two neurons
              points],  # plot the points of synaptic contacts as scatter
              scatter_kws=dict(name="synaptic contacts")
              )

Data type cannot be displayed: application/vnd.plotly.v1+json

neuprint connectivity queries

To programmatically interface with neuprint, we will use neuprint-python (link). It requires an API token which you can get via the website and is bound to the Google account that you use to log into neuprint. For this workshop we provide such a token as environment variable but you will need to start using your own token after the workshop is over.

These examples use the hemibrain v1.1 dataset.

neuprint-python

First we have to initialize the connection.

!pip install neuprint-python --quiet

import neuprint as neu
client = neu.Client('https://neuprint.janelia.org',
                    dataset='hemibrain:v1.1',
                    token='eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJlbWFpbCI6InZmYndvcmtzaG9wLm5ldXJvZmx5MjAyMEBnbWFpbC5jb20iLCJsZXZlbCI6Im5vYXV0aCIsImltYWdlLXVybCI6Imh0dHBzOi8vbGg2Lmdvb2dsZXVzZXJjb250ZW50LmNvbS8tWXFDN21NRXd3TlEvQUFBQUFBQUFBQUkvQUFBQUFBQUFBQUEvQU1adXVjbU5zaXhXZDRhM0VyTTQ0ODBMa2IzNDdvUlpfUS9zOTYtYy9waG90by5qcGc_c3o9NTA_c3o9NTAiLCJleHAiOjE3OTQwOTE4ODd9.ceg4mrj2o-aOhK0NHNGmBacg8R34PBPoLBwhCo4uOCQ')

Most functions in neuprint-python accept neu.NeuronCriteria which is effectively a filter for body IDs, types, cellbody fibers (~lineages), etc:

help(neu.NeuronCriteria)

Help on class NeuronCriteria in module neuprint.queries.neuroncriteria:

class NeuronCriteria(builtins.object)
 |  NeuronCriteria(matchvar='n', *, bodyId=None, type=None, instance=None, regex='guess', status=None, statusLabel=None, rois=None, inputRois=None, outputRois=None, roi_req='all', min_roi_inputs=1, min_roi_outputs=1, group=None, serial=None, cropped=None, birthtime=None, cellBodyFiber=None, class_=None, entryNerve=None, exitNerve=None, hemilineage=None, longTract=None, modality=None, origin=None, predictedNt=None, serialMotif=None, somaNeuromere=None, somaSide=None, subclass=None, synonyms=None, systematicType=None, target=None, label=None, min_pre=0, min_post=0, somaLocation=None, tosomaLocation=None, rootLocation=None, soma=None, client=None)
 |
 |  Neuron selection criteria.
 |
 |  Specifies which fields to filter by when searching for a Neuron (or Segment).
 |  This class does not send queries itself, but you use it to specify search
 |  criteria for various query functions.
 |
 |  Note:
 |      For simple queries involving only particular bodyId(s) or type(s)/instance(s),
 |      you can usually just pass the ``bodyId`` or ``type`` to the query function,
 |      without constructing a full ``NeuronCriteria``.
 |
 |      .. code-block:: python
 |
 |          from neuprint import fetch_neurons, NeuronCriteria as NC
 |
 |          # Equivalent
 |          neuron_df, conn_df = fetch_neurons(NC(bodyId=329566174))
 |          neuron_df, conn_df = fetch_neurons(329566174)
 |
 |          # Equivalent
 |          # (Criteria is satisfied if either type or instance matches.)
 |          neuron_df, conn_df = fetch_neurons(NC(type="OA-VPM3", instance="OA-VPM3"))
 |          neuron_df, conn_df = fetch_neurons("OA-VPM3")
 |
 |  Methods defined here:
 |
 |  __eq__(self, value)
 |      Implement comparison between criteria.
 |      Note: 'matchvar' is not considered during the comparison.
 |
 |  __init__(self, matchvar='n', *, bodyId=None, type=None, instance=None, regex='guess', status=None, statusLabel=None, rois=None, inputRois=None, outputRois=None, roi_req='all', min_roi_inputs=1, min_roi_outputs=1, group=None, serial=None, cropped=None, birthtime=None, cellBodyFiber=None, class_=None, entryNerve=None, exitNerve=None, hemilineage=None, longTract=None, modality=None, origin=None, predictedNt=None, serialMotif=None, somaNeuromere=None, somaSide=None, subclass=None, synonyms=None, systematicType=None, target=None, label=None, min_pre=0, min_post=0, somaLocation=None, tosomaLocation=None, rootLocation=None, soma=None, client=None)
 |      All criteria must be passed as keyword arguments.
 |
 |      .. note::
 |          Only ``bodyId``, ``type``, ``instance``, and ROI-related criteria are
 |          applicable to all datasets.  The applicability of all other criteria depends
 |          on the dataset being accessed (e.g. hemibrain,  manc, etc.).
 |
 |      .. note::
 |
 |          **Options for specifying ROI criteria**
 |
 |          The ``rois`` argument merely matches neurons that intersect the given ROIs at all
 |          (without distinguishing between inputs and outputs).
 |
 |          The ``inputRois`` and ``outputRois`` arguments allow you to put requirements
 |          on whether or not neurons have inputs or outputs in the listed ROIs.
 |          It produces a more expensive query, but it's more selective.
 |          It also enables you to require a minimum number of connections in the given
 |          ``inputRois`` or ``outputRois`` using the ``min_roi_inputs`` and ``min_roi_outputs``
 |          criteria.
 |
 |          In either case, use use ``roi_req`` to specify whether a neuron must match just
 |          one (``any``) of the listed ROIs, or ``all`` of them.
 |
 |      .. note::
 |
 |          **Matching against missing values (NULL)**
 |
 |          To search for neurons which are missing given property entirely,
 |          you can use a list containing ``None``, or the special value ``neuprint.IsNull``.
 |          For example, to find neurons with no `type`, use ``type=[None]`` or ``type=IsNull``.
 |
 |          **Matching against any value (NOT NULL)**
 |
 |          To search for any non-null value, you can use ``neuprint.NotNull``. For
 |          example, to find neurons that have a type (no matter what the
 |          type is), use ``type=NotNull``.
 |
 |      Args:
 |          matchvar (str):
 |              An arbitrary cypher variable name to use when this
 |              ``NeuronCriteria`` is used to construct cypher queries.
 |              Must begin with a lowercase letter.
 |
 |          bodyId (int or list of ints):
 |              List of bodyId values.
 |
 |          type (str or list of str):
 |              Cell type.  Matches depend on the the ``regex`` argument.
 |              If both ``type`` and ``instance`` criteria are supplied, any neuron that
 |              matches EITHER criteria will match the overall criteria.
 |
 |          instance (str or list of str):
 |              Cell instance (specific cell name).  Matches depend on the the ``regex`` argument.
 |              If both ``type`` and ``instance`` criteria are supplied, any neuron that
 |              matches EITHER criteria will match the overall criteria.
 |
 |          regex (bool):
 |              If ``True``, the ``instance`` and ``type`` arguments will be interpreted as
 |              regular expressions, rather than exact match strings.
 |              If ``False``, only exact matches will be found.
 |              By default, the matching method will be automatically chosen by inspecting the
 |              ``type`` and ``instance`` strings.  If they contain regex-like characters,
 |              then we assume you intend regex matching. (You can see which method was chosen by
 |              checking the ``regex`` field after the ``NeuronCriteria`` is constructed.)
 |
 |          status (str or list of str):
 |              Indicates the status of the neuron's reconstruction quality.
 |              Typically, named/annotated neurons have ``Traced`` status,
 |              the best quality.
 |          statusLabel (str or list of str):
 |             ``statusLabel`` is typically more fine-grained than ``status``,
 |             and mostly of interest during the construction of the connectome,
 |             not for end-users.  The possible values of ``statusLabel`` do not
 |             correspond one-to-one to those of ``status``.
 |
 |          rois (str or list of str):
 |              ROIs that merely intersect the neuron, without specifying whether
 |              they're intersected by input or output synapses.
 |              If not provided, will be auto-set from ``inputRois`` and ``outputRois``.
 |
 |          inputRois (str or list of str):
 |              Only Neurons which have inputs in EVERY one of the given ROIs will be matched.
 |              ``regex`` does not apply to this parameter.
 |
 |          outputRois (str or list of str):
 |              Only Neurons which have outputs in EVERY one of the given ROIs will be matched.
 |              ``regex`` does not apply to this parameter.
 |
 |          min_roi_inputs (int):
 |              How many input (post) synapses a neuron must have in each ROI to satisfy the
 |              ``inputRois`` criteria.  Can only be used if you provided ``inputRois``.
 |
 |          min_roi_outputs (int):
 |              How many output (pre) synapses a neuron must have in each ROI to satisfy the
 |              ``outputRois`` criteria.   Can only be used if you provided ``outputRois``.
 |
 |          roi_req (Either ``'any'`` or ``'all'``):
 |              Whether a neuron must intersect all of the listed input/output ROIs, or any of the listed input/output ROIs.
 |              When using 'any', each neuron must still match at least one input AND at least one output ROI.
 |
 |          group (int or list of int)
 |              In some datasets, the ``group`` ID is used to associate neurons morphological type,
 |              including left-right homologues. Neurons with the same group ID have matching morphology.
 |
 |          serial (int or list of int)
 |              Similar to ``group``, but used for associating neurons across segmental neuropils in the nerve cord.
 |              Neurons with the same ``serial`` ID are analogous to one another, but in different leg segments.
 |
 |          cropped (bool):
 |              If given, restrict results to neurons that are cropped or not.
 |
 |          birthtime (str or list of str):
 |          cellBodyFiber (str or list of str):
 |          class\_ (str or list of str):
 |              Matches for the neuron ``class`` field.
 |          entryNerve (str or list of str):
 |          exitNerve (str or list of str):
 |          hemilineage (str or list of str):
 |          longTract (str or list of str):
 |          modality (str or list of str):
 |          origin (str or list of str):
 |          predictedNt (str or list of str):
 |          serialMotif (str or list of str):
 |          somaNeuromere (str or list of str):
 |          somaSide  (str or list of str):
 |              Valid choices are 'RHS', 'LHS', 'Midline'
 |          subclass (str or list of str):
 |          synonyms (str or list of str):
 |          systematicType (str or list of str):
 |          target (str or list of str):
 |
 |          label (Either ``'Neuron'`` or ``'Segment'``):
 |              Which node label to match with.
 |              (In neuprint, all ``Neuron`` nodes are also ``Segment`` nodes.)
 |              By default, ``'Neuron'`` is used, unless you provided a non-empty ``bodyId`` list.
 |              In that case, ``'Segment'`` is the default. (It's assumed you're really interested
 |              in the bodies you explicitly listed, whether or not they have the ``'Neuron'`` label.)
 |
 |          min_pre (int):
 |              Exclude neurons that don't have at least this many t-bars (outputs) overall,
 |              regardless of how many t-bars exist in any particular ROI.
 |
 |          min_post (int):
 |              Exclude neurons that don't have at least this many PSDs (inputs) overall,
 |              regardless of how many PSDs exist in any particular ROI.
 |
 |          somaLocation:
 |              The ``somaLocation`` property of ``:Neuron`` objects contains
 |              the ``[X,Y,Z]`` coordinate (in voxels) of the cell body.
 |              ``NeuronCriteria`` does not allow you to match a specific coordinate,
 |              but you may set this argument to ``NotNull` (or ```IsNull``) to
 |              search for cells with (or without) a recorded cell body.
 |
 |          tosomaLocation:
 |              Neurons which could not be successfully attached to their cell body do not have
 |              a recorded ``somaLocation``.  Instead, they have an annotaiton on the cell body
 |              fiber, on the severed end extending out toward the cell body.
 |              Like ``somaLocation``, you can't match a specific coordinate using ``NeuronCriteria``,
 |              but you can use ``NotNull``/``IsNull``.
 |
 |          rootLocation:
 |              Some (but not all) Neurons which have no soma in the tissue sample are tagged with
 |              a ``rootLocation``, indicating where they enter/exit the sample.
 |              Like ``somaLocation``, you can't match a specific coordinate using ``NeuronCriteria``,
 |              but you can use ``NotNull``/``IsNull``.
 |
 |          soma (Either ``True``, ``False``, or ``None``)
 |              DEPRECATED.  Use ``somaLocation=NotNull`` or ``somaLocation=IsNull``.
 |
 |          client (:py:class:`neuprint.client.Client`):
 |              Used to validate ROI names.
 |              If not provided, the global default ``Client`` will be used.
 |
 |  __repr__(self)
 |      Return repr(self).
 |
 |  all_conditions(self, *vars, prefix=0, comments=True)
 |
 |  basic_conditions(self, prefix=0, comments=True)
 |      Construct a WHERE clause based on the basic conditions
 |      in this criteria (i.e. everything except for the "directed ROI" conditions.)
 |
 |  basic_exprs(self)
 |      Return the list of expressions that correspond
 |      to the members in this NeuronCriteria object.
 |      They're intended be combined (via 'AND') in
 |      the WHERE clause of a cypher query.
 |
 |  directed_rois_condition(self, *vars, prefix=0, comments=True)
 |      Construct the ```WITH...WHERE``` statements that apply the "directed ROI"
 |      conditions specified by this criteria's ``inputRois`` and ``outputRois``
 |      members.
 |
 |      These conditions are expensive to evaluate, so it's usually a good
 |      idea to position them LAST in your cypher query, once the result set
 |      has already been narrowed down by eariler filters.
 |
 |  global_vars(self)
 |
 |  global_with(self, *vars, prefix=0)
 |
 |  rois_expr(self)
 |
 |  typeinst_expr(self)
 |      Unlike all other fields, type and instance OR'd together.
 |      Either match satisfies the criteria.
 |
 |  ----------------------------------------------------------------------
 |  Class methods defined here:
 |
 |  combined_conditions(neuron_conditions, vars=[], prefix=0, comments=True) from builtins.type
 |      Combine the conditions from multiple NeuronCriteria into a single string,
 |      putting the "cheap" conditions first and the "expensive" conditions last.
 |      (That is, basic conditions first and the directed ROI conditions last.)
 |
 |  combined_global_with(neuron_conditions, vars=[], prefix=0) from builtins.type
 |
 |  ----------------------------------------------------------------------
 |  Data descriptors defined here:
 |
 |  __dict__
 |      dictionary for instance variables (if defined)
 |
 |  __weakref__
 |      list of weak references to the object (if defined)
 |
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 |
 |  MAX_LITERAL_LENGTH = 3
 |
 |  __hash__ = None

Fetching neurons

Let’s say we want to find all antennnal lobe projection neurons (PNs). Their type nomenclature adheres to {glomerulus}_{lineage}PN (e.g. DA1_lPN)for uniglomerular PNs and a M_{lineage}PN{tract}{type} (e.g. M_vPNml50 = “multiglomerular ventral lineage PN mediolateral tract type 50) for multiglomerular PNs.

To get them all, we need to use regex patterns (see this cheatsheet):

# Define the filter criteria
nc = neu.NeuronCriteria(type='.*?_.*?PN.*?', regex=True)

# Get general info for these neurons
pns, roi_info = neu.fetch_neurons(nc)

print(f'{pns.shape[0]} PNs found.')

pns.head()

/Users/robbiecourt/GIT/VFB_connect/.conda/lib/python3.10/site-packages/neuprint/client.py:609: FutureWarning:

Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`

337 PNs found.

	bodyId	instance	type	pre	post	downstream	upstream	size	status	cropped	statusLabel	cellBodyFiber	somaRadius	somaLocation	roiInfo	notes	inputRois	outputRois
0	294792184	M_vPNml53_R	M_vPNml53	92	344	730	344	420662445	Traced	False	Roughly traced	AVM04	336.5	[18923, 34319, 35424]	{'SNP(R)': {'pre': 70, 'post': 155, 'downstrea...	None	[AL(R), AL-D(R), AL-DA2(R), AL-DA4m(R), AL-DC1...	[AL(R), AL-DC1(R), LH(R), PLP(R), SIP(R), SLP(...
1	329599710	M_lvPNm32_R	M_lvPNm32	247	285	2052	285	343478957	Traced	False	Roughly traced	AVM06	NaN	None	{'SNP(R)': {'pre': 180, 'post': 93, 'downstrea...	None	[AL(R), AL-DC4(R), AL-DL2v(R), AL-DM1(R), AL-D...	[AL(R), AL-DL2v(R), AL-DM1(R), AL-DM4(R), AL-D...
2	417199910	M_lvPNm36_R	M_lvPNm36	162	347	1590	347	387058559	Traced	False	Roughly traced	AVM06	351.5	[13823, 33925, 34176]	{'SNP(R)': {'pre': 156, 'post': 95, 'downstrea...	None	[AL(R), AL-DL5(R), AL-DM4(R), AL-DP1m(R), AL-V...	[AL(R), AL-DL5(R), AL-DM4(R), AL-VP1d(R), AL-V...
3	480927537	M_vPNml70_R	M_vPNml70	82	276	692	276	240153322	Traced	False	Roughly traced	AVM04	NaN	None	{'SNP(R)': {'pre': 15, 'post': 18, 'downstream...	None	[AL(R), AL-DA2(R), AL-DA4l(R), AL-DA4m(R), AL-...	[LH(R), SLP(R), SNP(R)]
4	481268653	M_vPNml89_R	M_vPNml89	146	58	1614	58	265085609	Traced	False	Roughly traced	AVM04	NaN	None	{'SNP(R)': {'pre': 10, 'post': 2, 'downstream'...	None	[AL(R), AL-VC3l(R), AL-VC4(R), AL-VP1m(R), LH(...	[LH(R), SLP(R), SNP(R)]

# Check that the regex did not have any accidental by-catch
pns['type'].unique()

array(['M_vPNml53', 'M_lvPNm32', 'M_lvPNm36', 'M_vPNml70', 'M_vPNml89',
       'VP1l+_lvPN', 'M_vPNml69', 'DM1_lPN', 'DM4_vPN', 'M_vPNml79',
       'VP4+_vPN', 'DA4l_adPN', 'M_vPNml87', 'DM4_adPN', 'M_vPNml83',
       'VA5_lPN', 'DA4m_adPN', 'M_lvPNm24', 'M_vPNml85', 'VP1l+VP3_ilPN',
       'M_vPNml77', 'M_vPNml84', 'VC1_lPN', 'M_lvPNm39', 'M_vPNml50',
       'DM2_lPN', 'VC5_lvPN', 'M_vPNml88', 'M_vPNml58', 'VP4_vPN',
       'DP1m_vPN', 'DP1m_adPN', 'DM5_lPN', 'VC5_adPN', 'M_vPNml80',
       'M_lvPNm25', 'VC3m_lvPN', 'VP3+_vPN', 'VP1m+_lvPN', 'DA3_adPN',
       'V_l2PN', 'M_vPNml56', 'VC3l_adPN', 'VM7v_adPN', 'DL5_adPN',
       'VM4_adPN', 'VM2_adPN', 'M_lvPNm40', 'DC4_vPN', 'V_ilPN',
       'M_vPNml74', 'Z_lvPNm1', 'DA1_lPN', 'DP1l_adPN', 'VM4_lvPN',
       'M_vPNml71', 'DP1l_vPN', 'M_lvPNm41', 'M_spPN5t10', 'DA1_vPN',
       'VC4_adPN', 'DM3_adPN', 'M_lvPNm45', 'VL1_vPN', 'M_lvPNm44',
       'M_vPNml78', 'M_vPNml67', 'M_adPNm5', 'M_smPNm1', 'DM6_adPN',
       'DL2d_adPN', 'M_adPNm6', 'M_adPNm8', 'M_lvPNm43', 'Z_vPNml1',
       'M_vPNml59', 'DA2_lPN', 'M_lPNm11A', 'M_vPNml52', 'DL2d_vPN',
       'VL2p_vPN', 'VA1d_adPN', 'M_lPNm11B', 'M_lvPNm48', 'M_lPNm11C',
       'M_lvPNm42', 'VA1v_vPN', 'M_vPNml68', 'M_vPNml55', 'M_vPNml62',
       'VL2a_vPN', 'M_vPNml60', 'M_vPNml65', 'VM5d_adPN', 'M_l2PNm16',
       'M_vPNml61', 'M_vPNml57', 'M_vPNml64', 'M_lv2PN9t49',
       'VP2+VC5_l2PN', 'M_spPN4t9', 'M_vPNml66', 'M_vPNml75', 'M_vPNml63',
       'M_vPNml72', 'M_lvPNm38', 'D_adPN', 'M_vPNml76', 'M_vPNml54',
       'DM3_vPN', 'M_vPNml86', 'DL3_lPN', 'VA4_lPN', 'VP1d_il2PN',
       'DC1_adPN', 'M_l2PN3t18', 'M_lvPNm35', 'DL4_adPN', 'M_lvPNm28',
       'M_lvPNm27', 'M_ilPNm90', 'M_l2PNl20', 'M_lvPNm29', 'VA7l_adPN',
       'M_lPNm13', 'M_l2PNl21', 'DL1_adPN', 'M_imPNl92', 'M_vPNml73',
       'M_ilPN8t91', 'M_l2PNm14', 'VP1d+VP4_l2PN1', 'M_lvPNm26',
       'DL2v_adPN', 'VP3+VP1l_ivPN', 'M_lvPNm33', 'VA1v_adPN',
       'VP3+_l2PN', 'M_l2PN10t19', 'VP4+VL1_l2PN', 'M_l2PNl22',
       'M_l2PNm15', 'M_lPNm11D', 'MZ_lv2PN', 'DC2_adPN', 'M_lvPNm46',
       'VC2_lPN', 'VM1_lPN', 'VM3_adPN', 'VM7d_adPN', 'M_lvPNm47',
       'M_lPNm12', 'DC3_adPN', 'VP2+_adPN', 'VP1m+VP2_lvPN2',
       'VP1m+VP2_lvPN1', 'VA6_adPN', 'VA7m_lPN', 'M_adPNm7', 'M_adPNm4',
       'VA1d_vPN', 'VA3_adPN', 'VL1_ilPN', 'M_l2PNl23', 'M_lvPNm31',
       'VP1m+VP5_ilPN', 'VL2p_adPN', 'MZ_lvPN', 'VP2_adPN', 'VA2_adPN',
       'VM5v_adPN', 'VP5+VP2_l2PN', 'VP5+VP3_l2PN', 'VP5+_l2PN',
       'M_vPNml51', 'M_smPN6t2', 'M_lvPNm37', 'M_vPNml82', 'M_adPNm3',
       'VP1m_l2PN', 'DC4_adPN', 'VP5+Z_adPN', 'VL2a_adPN', 'VP2_l2PN',
       'M_lvPNm34', 'VP2+Z_lvPN', 'M_lvPNm30', 'M_l2PNm17', 'M_vPNml81',
       'VP1d+VP4_l2PN2'], dtype=object)

We can find the same neuron types using VFB instead. This allows curated neuron classes to be used and doesn’t depend on knowing naming conventions and using potentially error prone regex pattern matching.

#This will get all ALPNs from ALL datasets on VFB
ALPNs = vfb.get_instances("'adult antennal lobe projection neuron'")
# Explode the lists in the 'data_source' column into separate rows as each image can potentialy have multiple data sources. Note this can be done for any column with lists
exploded_ALPNs = ALPNs.explode('data_source')
#Select only rows from Hemibrain1.1 dataset
ALPNs=exploded_ALPNs[exploded_ALPNs['data_source'] == 'neuprint_JRC_Hemibrain_1point1']
ALPNs

Warning: called a non existant id:VFB_00102294

	label	symbol	id	tags	description	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license
896	OA-VUMa2_R (FlyEM-HB:1670265016)	OA-VUMa2_R	VFB_jrchk10i	[Entity, Adult, Anatomy, Cell, Individual, Ner...	tracing status-Roughly traced, cropped-False	[octopaminergic VUMa2 neuron]	[FBbt_00110157]	neuprint_JRC_Hemibrain_1point1	[1670265016]	[neuronbridge:1670265016, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
897	M_vPNml89_R (FlyEM-HB:1694850602)	M_vPNml89_R	VFB_jrchk100	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult GABAergic neuron, adult multiglomerular...	[FBbt_00058207, FBbt_20003864]	neuprint_JRC_Hemibrain_1point1	[1694850602]	[neuronbridge:1694850602, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
898	M_vPNml89_R (FlyEM-HB:1819326555)	M_vPNml89_R	VFB_jrchk101	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult multiglomerular antennal lobe projectio...	[FBbt_20003864, FBbt_00058207]	neuprint_JRC_Hemibrain_1point1	[1819326555]	[neuprint_JRC_Hemibrain_1point1:1819326555, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
899	OA-VUMa2_R (FlyEM-HB:638481581)	OA-VUMa2_R	VFB_jrchk10j	[Entity, Adult, Anatomy, Cell, Individual, Ner...	tracing status-Roughly traced, cropped-False	[octopaminergic VUMa2 neuron]	[FBbt_00110157]	neuprint_JRC_Hemibrain_1point1	[638481581]	[neuprint_JRC_Hemibrain_1point1:638481581, neu...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
900	M_lvPNm40_R (FlyEM-HB:1732313117)	M_lvPNm40_R	VFB_jrchk0xb	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult multiglomerular antennal lobe projectio...	[FBbt_20003819]	neuprint_JRC_Hemibrain_1point1	[1732313117]	[neuronbridge:1732313117, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
...	...	...	...	...	...	...	...	...	...	...	...	...	...
1237	VP2_l2PN(lALT)_R (FlyEM-HB:5813069447)	VP2_l2PN(lALT)_R	VFB_jrchk7ja	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult cholinergic neuron, adult antennal lobe...	[FBbt_00058205, FBbt_00049730]	neuprint_JRC_Hemibrain_1point1	[5813069447]	[neuronbridge:5813069447, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
1238	Z_vPNml1(noAL+SEZ)_R (FlyEM-HB:792364888)	Z_vPNml1(noAL+SEZ)_R	VFB_jrchk7zs	[Entity, Adult, Anatomy, Cell, GABAergic, Indi...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron, adult ...	[FBbt_00067123, FBbt_00058207]	neuprint_JRC_Hemibrain_1point1	[792364888]	[neuronbridge:792364888, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
1239	Z_vPNml1(noAL+SEZ)_R (FlyEM-HB:729608317)	Z_vPNml1(noAL+SEZ)_R	VFB_jrchk7zr	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron, adult ...	[FBbt_00067123, FBbt_00058205]	neuprint_JRC_Hemibrain_1point1	[729608317]	[neuprint_JRC_Hemibrain_1point1:729608317, neu...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
1240	Z_vPNml1(noAL+SEZ)_R (FlyEM-HB:698565676)	Z_vPNml1(noAL+SEZ)_R	VFB_jrchk7zq	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult cholinergic neuron, adult antennal lobe...	[FBbt_00058205, FBbt_00067123]	neuprint_JRC_Hemibrain_1point1	[698565676]	[neuronbridge:698565676, neuprint_JRC_Hemibrai...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
1241	Z_vPNml1(noAL+SEZ)_R (FlyEM-HB:698569832)	Z_vPNml1(noAL+SEZ)_R	VFB_jrchk7zp	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	tracing status-Roughly traced, cropped-False	[adult antennal lobe projection neuron, adult ...	[FBbt_00067123, FBbt_00058205]	neuprint_JRC_Hemibrain_1point1	[698569832]	[neuronbridge:698569832, neuprint_JRC_Hemibrai...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...

339 rows × 13 columns

Fetching synaptic partners

Looks good! Next: What’s downstream of those PNs?

exploded_ALPNs = ALPNs.explode('accession')
ds = neu.fetch_simple_connections(upstream_criteria=list(map(int, exploded_ALPNs['accession'])))
#using hemibrain regex
#ds = neu.fetch_simple_connections(upstream_criteria=neu.NeuronCriteria(bodyId=pns.bodyId.values))
ds

	bodyId_pre	bodyId_post	weight	type_pre	type_post	instance_pre	instance_post	conn_roiInfo
0	635062078	1671292719	390	DP1m_adPN	lLN2T_c	DP1m_adPN_R	lLN2T_c(Tortuous)_R	{'AL(R)': {'pre': 390, 'post': 390}, 'AL-DP1m(...
1	635062078	1704347707	326	DP1m_adPN	lLN2T_c	DP1m_adPN_R	lLN2T_c(Tortuous)_R	{'AL(R)': {'pre': 324, 'post': 324}, 'AL-DP1m(...
2	542634818	1704347707	322	DM1_lPN	lLN2T_c	DM1_lPN_R	lLN2T_c(Tortuous)_R	{'AL(R)': {'pre': 322, 'post': 322}, 'AL-DM1(R...
3	635062078	1640922516	320	DP1m_adPN	lLN2T_e	DP1m_adPN_R	lLN2T_e(Tortuous)_R	{'AL(R)': {'pre': 317, 'post': 316}, 'AL-DP1m(...
4	724816115	1670916819	318	DP1l_adPN	lLN2P_a	DP1l_adPN_R	lLN2P_a(Patchy)_R	{'AL(R)': {'pre': 318, 'post': 318}, 'AL-DP1l(...
...	...	...	...	...	...	...	...	...
101862	5901222910	5813086037	1	DM2_lPN	None	DM2_lPN_R	None	{'LH(R)': {'pre': 1, 'post': 1}}
101863	5901222910	5813095915	1	DM2_lPN	KCg-m	DM2_lPN_R	KCg-m_R	{'MB(R)': {'pre': 1, 'post': 1}, 'CA(R)': {'pr...
101864	5901222910	5813129316	1	DM2_lPN	LHAV6a1_b	DM2_lPN_R	LHAV6a1_b_R	{'LH(R)': {'pre': 1, 'post': 1}}
101865	5901222910	5901193783	1	DM2_lPN	LHAV4g4_a	DM2_lPN_R	LHAV4g4_a_R	{'LH(R)': {'pre': 1, 'post': 1}}
101866	5901222910	5901203780	1	DM2_lPN	LHAV4g11	DM2_lPN_R	LHAV4g11_R	{'LH(R)': {'pre': 1, 'post': 1}}

101867 rows × 8 columns

Each row is now a connections from a single up- to a single downstream neuron. The “weight” is the number of synapses between the pre- and the postsynaptic neuron. Let’s simplify by grouping by type:

by_type = ds.groupby(['type_pre', 'type_post'], as_index=False).weight.sum()
by_type.sort_values('weight', ascending=False, inplace=True)
by_type.reset_index(drop=True, inplace=True)
by_type

	type_pre	type_post	weight
0	DC3_adPN	KCg-m	3670
1	VM5d_adPN	KCg-m	3219
2	DC1_adPN	KCg-m	3215
3	VL2a_adPN	KCg-m	3096
4	DA1_lPN	KCg-m	3078
...	...	...	...
40631	M_vPNml50	WEDPN4	1
40632	M_vPNml50	WEDPN12	1
40633	M_vPNml50	V_ilPN	1
40634	M_vPNml50	VP4+VL1_l2PN	1
40635	Z_vPNml1	mALD2	1

40636 rows × 3 columns

The strongest connections are between PNs and Kenyon Cells (KCs). That’s not much of a surprise since there are thousands of KCs. For the sake of the argument let’s say we want to know where these connections occur:

#First find KCs in VFB
KCs = vfb.get_instances("'adult Kenyon cell'")
#Select only rows from Hemibrain1.1 dataset
exploded_KCs = KCs.explode('data_source')
KCs=exploded_KCs[exploded_KCs['data_source'] == 'neuprint_JRC_Hemibrain_1point1']
KCs

	label	symbol	id	tags	description	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license
909	KCa\'b\'-ap2_R (FlyEM-HB:5813020057)	KCa\'b\'-ap2_R	VFB_jrchjv6v	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[alpha'/beta' anterior-posterior type 2 Kenyon...	[FBbt_00049837, FBbt_00048138, FBbt_00058206]	neuprint_JRC_Hemibrain_1point1	[5813020057]	[neuprint_JRC_Hemibrain_1point1:5813020057, ne...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
910	KCa\'b\'-m_R (FlyEM-HB:579928928)	KCa\'b\'-m_R	VFB_jrchjv88	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[mushroom body dopaminergic neuron, alpha'/bet...	[FBbt_00048138, FBbt_00100253, FBbt_00058206]	neuprint_JRC_Hemibrain_1point1	[579928928]	[neuronbridge:579928928, neuprint_JRC_Hemibrai...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
911	KCa\'b\'-m_R (FlyEM-HB:5813062842)	KCa\'b\'-m_R	VFB_jrchjv9w	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[alpha'/beta' middle Kenyon cell, adult dopami...	[FBbt_00100253, FBbt_00058206, FBbt_00048138]	neuprint_JRC_Hemibrain_1point1	[5813062842]	[neuronbridge:5813062842, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
912	KCa\'b\'-ap2_R (FlyEM-HB:662409582)	KCa\'b\'-ap2_R	VFB_jrchjv6p	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[mushroom body dopaminergic neuron, adult dopa...	[FBbt_00048138, FBbt_00058206, FBbt_00049837]	neuprint_JRC_Hemibrain_1point1	[662409582]	[neuprint_JRC_Hemibrain_1point1:662409582, neu...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
913	KCa\'b\'-m_R (FlyEM-HB:5813056305)	KCa\'b\'-m_R	VFB_jrchjv82	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[adult dopaminergic neuron, mushroom body dopa...	[FBbt_00058206, FBbt_00048138, FBbt_00100253]	neuprint_JRC_Hemibrain_1point1	[5813056305]	[neuronbridge:5813056305, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
...	...	...	...	...	...	...	...	...	...	...	...	...	...
5094	KCg-m_R (FlyEM-HB:1141687352)	KCg-m_R	VFB_jrchjwch	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[gamma main Kenyon cell, mushroom body dopamin...	[FBbt_00111061, FBbt_00048138, FBbt_00058206]	neuprint_JRC_Hemibrain_1point1	[1141687352]	[neuronbridge:1141687352, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
5095	KCg-m_R (FlyEM-HB:693837780)	KCg-m_R	VFB_jrchjwcq	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[mushroom body dopaminergic neuron, gamma main...	[FBbt_00048138, FBbt_00111061, FBbt_00058206]	neuprint_JRC_Hemibrain_1point1	[693837780]	[neuronbridge:693837780, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
5096	KCg-m_R (FlyEM-HB:1101353948)	KCg-m_R	VFB_jrchjwe3	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[mushroom body dopaminergic neuron, adult dopa...	[FBbt_00048138, FBbt_00058206, FBbt_00111061]	neuprint_JRC_Hemibrain_1point1	[1101353948]	[neuronbridge:1101353948, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
5097	KCg-m_R (FlyEM-HB:540389646)	KCg-m_R	VFB_jrchjwcg	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[mushroom body dopaminergic neuron, adult dopa...	[FBbt_00048138, FBbt_00058206, FBbt_00111061]	neuprint_JRC_Hemibrain_1point1	[540389646]	[neuronbridge:540389646, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...
5098	KCg-m_R (FlyEM-HB:693841887)	KCg-m_R	VFB_jrchjwci	[Entity, Adult, Anatomy, Cell, Cholinergic, Do...	tracing status-Roughly traced, cropped-False	[adult dopaminergic neuron, mushroom body dopa...	[FBbt_00058206, FBbt_00048138, FBbt_00111061]	neuprint_JRC_Hemibrain_1point1	[693841887]	[neuronbridge:693841887, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...

1927 rows × 13 columns

# Fixes for conda environment to ensure full jupyterlab compatibility
import subprocess

# Check if conda is available
try:
    subprocess.run(["conda", "--version"], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    conda_available = True
except subprocess.CalledProcessError:
    conda_available = False

# Only run these commands if conda is available
if conda_available:
    try:
        # Update conda base environment
        subprocess.run(["conda", "update", "-n", "base", "-c", "defaults", "conda", "-y"], check=True)
        # Install jupyterlab_widgets
        subprocess.run(["conda", "install", "-n", "base", "-c", "conda-forge", "jupyterlab_widgets", "-y"], check=True)
        # Install ipywidgets
        subprocess.run(["conda", "install", "-n", "base", "-c", "conda-forge", "ipywidgets", "-y"], check=True)
        print("Conda packages updated successfully.")
    except subprocess.CalledProcessError as e:
        print(f"An error occurred while running a conda command: {e}")
else:
    print("Conda is not available in this environment.")

Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working...

The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:

  - defaults/osx-64::conda==23.1.0=py310hecd8cb5_0

done

==> WARNING: A newer version of conda exists. <==
  current version: 23.1.0
  latest version: 24.7.1

Please update conda by running

    $ conda update -n base -c defaults conda

Or to minimize the number of packages updated during conda update use

     conda install conda=24.7.1

## Package Plan ##

  environment location: /usr/local/Caskroom/miniconda/base

  added / updated specs:
    - conda


The following NEW packages will be INSTALLED:

  brotli-python      pkgs/main/osx-64::brotli-python-1.0.9-py310hcec6c5f_8
  libcxx             pkgs/main/osx-64::libcxx-14.0.6-h9765a3e_0
  lz4-c              pkgs/main/osx-64::lz4-c-1.9.4-hcec6c5f_1
  pip                pkgs/main/osx-64::pip-24.2-py310hecd8cb5_0
  pluggy             pkgs/main/osx-64::pluggy-1.0.0-py310hecd8cb5_1
  zstd               pkgs/main/osx-64::zstd-1.5.5-hc035e20_2

The following packages will be UPDATED:

  bzip2                                    1.0.8-h1de35cc_0 --> 1.0.8-h6c40b1e_6
  cffi                               1.15.1-py310h6c40b1e_3 --> 1.16.0-py310h6c40b1e_1
  charset-normalizer                     2.0.4-pyhd3eb1b0_0 --> 3.3.2-pyhd3eb1b0_0
  conda-package-han~                  2.0.2-py310hecd8cb5_0 --> 2.3.0-py310hecd8cb5_0
  conda-package-str~                  0.7.0-py310hecd8cb5_0 --> 0.10.0-py310hecd8cb5_0
  cryptography                       38.0.4-py310hf6deb26_0 --> 42.0.5-py310h30e54ef_1
  idna                                  3.4-py310hecd8cb5_0 --> 3.7-py310hecd8cb5_0
  libffi                                   3.4.2-hecd8cb5_6 --> 3.4.4-hecd8cb5_1
  openssl            conda-forge::openssl-1.1.1w-h8a1eda9_0 --> pkgs/main::openssl-3.0.14-h46256e1_0
  pycosat                             0.6.4-py310hca72f7f_0 --> 0.6.6-py310h6c40b1e_1
  pyopenssl          pkgs/main/noarch::pyopenssl-22.0.0-py~ --> pkgs/main/osx-64::pyopenssl-24.2.1-py310hecd8cb5_0
  python                                  3.10.9-h218abb5_0 --> 3.10.14-h5ee71fb_1
  requests                           2.28.1-py310hecd8cb5_0 --> 2.32.3-py310hecd8cb5_0
  sqlite                                  3.40.1-h880c91c_0 --> 3.45.3-h6c40b1e_0
  tk                                      8.6.12-h5d9f67b_0 --> 8.6.14-h4d00af3_0
  tqdm                               4.64.1-py310hecd8cb5_0 --> 4.66.4-py310h20db666_0
  tzdata                                   2022g-h04d1e81_0 --> 2024a-h04d1e81_0
  urllib3                           1.26.14-py310hecd8cb5_0 --> 2.2.2-py310hecd8cb5_0
  xz                                      5.2.10-h6c40b1e_1 --> 5.4.6-h6c40b1e_1
  zlib                                    1.2.13-h4dc903c_0 --> 1.2.13-h4b97444_1
  zstandard                          0.18.0-py310hca72f7f_0 --> 0.22.0-py310h2d76c9a_0

The following packages will be SUPERSEDED by a higher-priority channel:

  ca-certificates    conda-forge::ca-certificates-2024.7.4~ --> pkgs/main::ca-certificates-2024.7.2-hecd8cb5_0
  certifi            conda-forge/noarch::certifi-2024.7.4-~ --> pkgs/main/osx-64::certifi-2024.7.4-py310hecd8cb5_0



Downloading and Extracting Packages

Preparing transaction: ...working... done
Verifying transaction: ...working... failed

RemoveError: 'pluggy' is a dependency of conda and cannot be removed from
conda's operating environment.

An error occurred while running a conda command: Command '['conda', 'update', '-n', 'base', '-c', 'defaults', 'conda', '-y']' returned non-zero exit status 1.

exploded_KCs = KCs.explode('accession')
adj, roi_info2 = neu.fetch_adjacencies(sources=list(map(int, exploded_ALPNs['accession'][:300])), targets=list(map(int, exploded_KCs['accession'][:300])))
roi_info2.head()

	bodyId_pre	bodyId_post	roi	weight
0	542634818	477900945	CA(R)	21
1	542634818	487160828	CA(R)	31
2	542634818	508599194	CA(R)	17
3	542634818	508616471	CA(R)	9
4	542634818	508616471	NotPrimary	2

# Group by region of interest (ROI)
by_roi = roi_info2.groupby('roi').weight.sum()
by_roi.head()

roi
CA(R)         34060
NotPrimary      359
SCL(R)           20
SLP(R)          135
Name: weight, dtype: int64

ax = by_roi.plot.bar()
ax.set_xlabel('')
ax.set_ylabel('PN to KC synapses')

Text(0, 0.5, 'PN to KC synapses')

adj = roi_info2[roi_info2.roi == 'CA(R)'].pivot(columns="bodyId_pre",
                                          index="bodyId_post",
                                          values="weight").fillna(0)

sns.clustermap(adj, cmap='Greys')

/Users/robbiecourt/GIT/VFB_connect/.conda/lib/python3.10/site-packages/seaborn/matrix.py:560: UserWarning:

Clustering large matrix with scipy. Installing `fastcluster` may give better performance.

/Users/robbiecourt/GIT/VFB_connect/.conda/lib/python3.10/site-packages/seaborn/matrix.py:560: UserWarning:

Clustering large matrix with scipy. Installing `fastcluster` may give better performance.

<seaborn.matrix.ClusterGrid at 0x7fe3d3f45540>

Querying paths

Let’s say we want to find out how to go from a PN (second order olfactory neurons) all the way to a descending neuron (presumably leading to motor neurons in the VNC).

#First find DNs in VFB
DNs = vfb.get_instances("'adult descending neuron'")
#Select only rows from Hemibrain1.1 dataset
exploded_DNs = DNs.explode('data_source')
DNs=exploded_DNs[exploded_DNs['data_source'] == ('neuprint_JRC_Hemibrain_1point1')]
DNs

	label	symbol	id	tags	parents_label	parents_id	data_source	accession	xrefs	templates	dataset	license	description
15	NPFP1_R (FlyEM-HB:1043117106)	NPFP1_R	VFB_jrchk103	[Entity, Adult, Anatomy, Cell, Individual, Ner...	[adult octopaminergic neuron, adult NPF P1 neu...	[FBbt_00058203, FBbt_00048120]	neuprint_JRC_Hemibrain_1point1	[1043117106]	[neuronbridge:1043117106, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
16	NPFP1(PDM12)_L (FlyEM-HB:5813068915)	NPFP1(PDM12)_L	VFB_jrchk104	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult NPF P1 neuron, adult cholinergic neuron]	[FBbt_00048120, FBbt_00058205]	neuprint_JRC_Hemibrain_1point1	[5813068915]	[neuronbridge:5813068915, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
17	MDN(PDM13)_L (FlyEM-HB:5813021079)	MDN(PDM13)_L	VFB_jrchk0vf	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult moonwalker descending neuron]	[FBbt_00111308]	neuprint_JRC_Hemibrain_1point1	[5813021079]	[neuprint_JRC_Hemibrain_1point1:5813021079, ne...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
18	MDN(PDM13)_L (FlyEM-HB:729742221)	MDN(PDM13)_L	VFB_jrchk0vc	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult moonwalker descending neuron]	[FBbt_00111308]	neuprint_JRC_Hemibrain_1point1	[729742221]	[neuronbridge:729742221, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
19	MDN_R (FlyEM-HB:698016469)	MDN_R	VFB_jrchk0ve	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult moonwalker descending neuron]	[FBbt_00111308]	neuprint_JRC_Hemibrain_1point1	[698016469]	[neuronbridge:698016469, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
...	...	...	...	...	...	...	...	...	...	...	...	...	...
263	WED105_R (FlyEM-HB:1375284097)	WED105_R	VFB_jrchk7rz	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult wedge neuron 105]	[FBbt_20003655]	neuprint_JRC_Hemibrain_1point1	[1375284097]	[neuronbridge:1375284097, neuprint_JRC_Hemibra...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
264	oviDNb(PDM15)_L (FlyEM-HB:642763374)	oviDNb(PDM15)_L	VFB_jrchk8dn	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[oviposition descending neuron oviDNb]	[FBbt_00049921]	neuprint_JRC_Hemibrain_1point1	[642763374]	[neuprint_JRC_Hemibrain_1point1:642763374, neu...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
265	oviDNa_R (FlyEM-HB:550655668)	oviDNa_R	VFB_jrchk8dm	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[oviposition descending neuron oviDNa]	[FBbt_00049920]	neuprint_JRC_Hemibrain_1point1	[550655668]	[neuronbridge:550655668, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
266	oviDNb_R (FlyEM-HB:519949044)	oviDNb_R	VFB_jrchk8do	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[oviposition descending neuron oviDNb]	[FBbt_00049921]	neuprint_JRC_Hemibrain_1point1	[519949044]	[neuronbridge:519949044, neuprint_JRC_Hemibrai...	[JRC_FlyEM_Hemibrain, JRC2018Unisex]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Roughly traced, cropped-False
267	vpoDN_R (FlyEM-HB:5813057864)	vpoDN_R	VFB_jrchk8rz	[Entity, Adult, Anatomy, Cell, Cholinergic, In...	[adult doublesex pMN2 (female) neuron]	[FBbt_00048405]	neuprint_JRC_Hemibrain_1point1	[5813057864]	[neuronbridge:5813057864, neuprint_JRC_Hemibra...	[JRC2018Unisex, JRC_FlyEM_Hemibrain]	[Xu2020NeuronsV1point1]	[https://creativecommons.org/licenses/by/4.0/l...	tracing status-Traced, cropped-False

249 rows × 13 columns

# First fetch the DNs
exploded_DNs = DNs.explode('accession')
dns, _ = neu.fetch_neurons(list(map(int, exploded_DNs['accession'])))
#with regex
#dns, _ = neu.fetch_neurons(neu.NeuronCriteria(type='(.*DN[^1]{0,}.*|Giant Fiber)', regex=True))
dns

	bodyId	instance	type	pre	post	downstream	upstream	size	status	cropped	statusLabel	cellBodyFiber	somaRadius	somaLocation	roiInfo	notes	inputRois	outputRois
0	297925719	SMP478_R	SMP478	11	514	33	514	887352389	Traced	False	Roughly traced	PDM15	301.0	[18670, 15472, 12256]	{'SNP(R)': {'pre': 8, 'post': 411, 'downstream...	pMP1 candidates	[INP, SCL(R), SIP(R), SLP(R), SMP(L), SMP(R), ...	[SIP(R), SMP(R), SNP(R)]
1	298961895	SMP478_R	SMP478	8	569	38	569	862856817	Traced	False	Roughly traced	PDM15	301.0	[17329, 15560, 10624]	{'SNP(R)': {'pre': 5, 'post': 317, 'downstream...	pMP1 candidates	[INP, SCL(R), SMP(L), SMP(R), SNP(L), SNP(R)]	[SMP(L), SMP(R), SNP(L), SNP(R)]
2	299298593	SMP478(PDM15)_L	SMP478	5	289	16	289	613001071	Traced	False	Roughly traced	None	NaN	None	{'SNP(R)': {'pre': 1, 'post': 80, 'downstream'...	pMP1 candidates	[SMP(L), SMP(R), SNP(L), SNP(R)]	[SMP(L), SMP(R), SNP(L), SNP(R)]
3	326253554	SMP454_R	SMP454	2613	9756	21869	9756	8166517062	Traced	False	Roughly traced	PDM12	465.5	[22142, 20149, 5600]	{'SNP(R)': {'pre': 1374, 'post': 3627, 'downst...	None	[ATL(R), AVLP(R), CAN(R), CRE(-ROB,-RUB)(R), C...	[AOTU(R), AVLP(R), CRE(-ROB,-RUB)(R), CRE(-RUB...
4	327255181	SMP290_R	SMP290	147	455	1028	455	816661754	Traced	False	Roughly traced	PDM05	396.0	[23064, 11810, 14912]	{'SNP(R)': {'pre': 63, 'post': 390, 'downstrea...	pMP5 candidates	[FLA(R), PENP, SMP(L), SMP(R), SNP(L), SNP(R),...	[FLA(R), PENP, SMP(R), SNP(R), mALT(R)]
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
244	5813078352	PS133_R	PS133	9	1041	30	1041	1572727885	Traced	False	Roughly traced	PDM17	351.0	[26154, 14795, 14256]	{'INP': {'post': 252, 'upstream': 252}, 'SCL(R...	None	[CAN(R), EPA(L), EPA(R), GNG, GOR(L), GOR(R), ...	[CAN(R), GOR(R), IPS(R), PENP, SPS(L), SPS(R),...
245	5813082237	PS212_R	PS212	77	5047	299	5047	2290180209	Traced	False	Roughly traced	PVM02	456.5	[20933, 11422, 19304]	{'INP': {'pre': 14, 'post': 613, 'downstream':...	None	[EPA(R), GNG, GOR(R), IB, ICL(R), INP, IPS(R),...	[GNG, IB, ICL(R), INP, IPS(R), PLP(R), SPS(R),...
246	5813095193	DNp16_R	DNp16	70	683	429	683	292910198	Traced	False	Roughly traced	PVM02	276.0	[25941, 10730, 20000]	{'INP': {'post': 34, 'upstream': 34}, 'IB': {'...	None	[CAN(R), GNG, IB, INP, IPS(R), PENP, SPS(R), V...	[CAN(R), GNG, IPS(R), PENP, SPS(R), VMNP]
247	5813096489	VES081_R	VES081	14	1321	71	1321	928031787	Traced	False	Roughly traced	PVM15	451.0	[15106, 10109, 20144]	{'VMNP': {'pre': 5, 'post': 1190, 'downstream'...	None	[AL(R), GNG, IPS(R), LAL(-GA)(R), LAL(R), LX(R...	[GNG, VES(R), VMNP]
248	5813108230	DNp16/17_R	DNp16/17	5	177	16	177	304268206	Traced	False	Roughly traced	PVM02	321.5	[23677, 10111, 18544]	{'INP': {'post': 2, 'upstream': 2}, 'IB': {'po...	None	[GNG, IB, INP, IPS(R), SPS(R), VMNP]	[IPS(R), SPS(R), VMNP]

249 rows × 18 columns

Neuprint lets you query paths from a single source to a single target. For multi-source or -target queries, your best bet is to download the entire graph and run the queries locally using networkx or igraph.

# Find all paths from A PN to A DNs
paths = neu.fetch_shortest_paths(upstream_bodyId=list(map(int, exploded_ALPNs['accession']))[0],
                                 downstream_bodyId=list(map(int, exploded_DNs['accession']))[0],
                                 min_weight=10)
paths

	path	bodyId	type	weight
0	0	1670265016	OA-VUMa2	0
1	0	328533761	PPL201	14
2	0	360259229	LHAV3h1	11
3	0	1043117106	NPFP1	13
4	1	1670265016	OA-VUMa2	0
5	1	328533761	PPL201	14
6	1	329225149	LHCENT10	12
7	1	1043117106	NPFP1	10
8	2	1670265016	OA-VUMa2	0
9	2	574688051	LHPV12a1	23
10	2	360259229	LHAV3h1	17
11	2	1043117106	NPFP1	13
12	3	1670265016	OA-VUMa2	0
13	3	577542489	M_lvPNm24	10
14	3	456847100	SLP130	10
15	3	1043117106	NPFP1	10
16	4	1670265016	OA-VUMa2	0
17	4	1700307582	M_l2PNl21	12
18	4	360259229	LHAV3h1	15
19	4	1043117106	NPFP1	13
20	5	1670265016	OA-VUMa2	0
21	5	1700307582	M_l2PNl21	12
22	5	329897255	LHCENT10	15
23	5	1043117106	NPFP1	16

So it looks like there are three separate 7-hop paths to go from M_vPNml53 to DN1a. Let’s visualize the neurons involved!

Fetching meshes & skeletons

You can fetch skeletons as SWCs directly via neuprint-python. For visualization however it’s easiest to load neuron morphologies via navis. For that navis wraps neuprint-python and adds some convenience functions (see also the tutorial):

# Import the wrapped neuprint-python
# -> this exposes ALL base functions plus a couple navis-specific extras
import navis
import navis.interfaces.neuprint as neu

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

# Fetch neurons in the first path
bodyIDS = paths.loc[(paths.path == 0), 'bodyId']
# nl = neu.fetch_skeletons(paths.loc[(paths.path == 0), 'bodyId'])
# nl

xrefs = ['neuprint_JRC_Hemibrain_1point1:' + str(id) for id in bodyIDS]

nl_terms = vfb.terms(xrefs)
nl_terms.load_skeletons(template='JRC_FlyEM_Hemibrain')
nl = [term.skeleton for term in nl_terms]
nl_terms.summary

INFO: Resolved xref neuprint_JRC_Hemibrain_1point1:1670265016 to VFB_jrchk10i
INFO: Resolved xref neuprint_JRC_Hemibrain_1point1:328533761 to VFB_jrchk45u
INFO: Resolved xref neuprint_JRC_Hemibrain_1point1:360259229 to VFB_jrchjyu5
INFO: Resolved xref neuprint_JRC_Hemibrain_1point1:1043117106 to VFB_jrchk103

	ID	Name	Description	URL	Related Terms	Parents	License	Cross References	Datasets
0	VFB_jrchk10i	OA-VUMa2_R	tracing status-Roughly traced, cropped-False	https://n2t.net/vfb:VFB_jrchk10i	[Rel(relation=MinimalEdgeInfo(label=capable of...	[OA-VUMa2]	CC-BY_4.0	[https://neuronbridge.janelia.org/search?q=167...	[JRC_FlyEM_Hemibrain neurons Version 1.1]
1	VFB_jrchk45u	PPL201_R	tracing status-Roughly traced, cropped-False	https://n2t.net/vfb:VFB_jrchk45u	[Rel(relation=MinimalEdgeInfo(label=capable of...	[PPL201]	CC-BY_4.0	[https://neuronbridge.janelia.org/search?q=328...	[JRC_FlyEM_Hemibrain neurons Version 1.1]
2	VFB_jrchjyu5	LHAV3h1_R	tracing status-Roughly traced, cropped-False	https://n2t.net/vfb:VFB_jrchjyu5	[Rel(relation=MinimalEdgeInfo(label=capable of...	[LHAV3h1, adult cholinergic neuron]	CC-BY_4.0	[https://neuprint.janelia.org/results?dataset=...	[JRC_FlyEM_Hemibrain neurons Version 1.1]
3	VFB_jrchk103	NPFP1_R	tracing status-Roughly traced, cropped-False	https://n2t.net/vfb:VFB_jrchk103	[Rel(relation=MinimalEdgeInfo(label=capable of...	[adult octopaminergic neuron, NPFP1]	CC-BY_4.0	[https://neuronbridge.janelia.org/search?q=104...	[JRC_FlyEM_Hemibrain neurons Version 1.1]

# Let's also get some ROI meshes

# al = neu.fetch_roi('AL(R)')
# lh = neu.fetch_roi('LH(R)')
# ca = neu.fetch_roi('CA(R)')

# If the neuprint server fails to return the meshes (often due to capacity issues), we can use the VFB API to get the meshes instead
[al,lh,ca] = [term.mesh for term in vfb.terms(['AL(R) on JRC_FlyEM_Hemibrain','LH(R) on JRC_FlyEM_Hemibrain','CA(R) on JRC_FlyEM_Hemibrain'])]

# Plot
navis.plot3d([nl, lh, al, ca])

Data type cannot be displayed: application/vnd.plotly.v1+json

Plotting graphs

There are various ways of plotting static graphs. In theory Jupyter notebooks lend themselves to interactive graphs too but unfortunately DeepNote does not yet support the required libraries (e.g. ipywidgets). That being said: if you want to run this locally or on Google colab, check out ipycytoscape.

There are numerous options to do this but we will use networkx to plot a static graph:

import networkx as nx
import numpy as np

# Initialize the graph
G = nx.DiGraph()

# Generate edges from the paths
edges = []
for p in paths.path.unique():
    this_path = paths.loc[(paths.path == p)]
    this_edges = list(zip(this_path.values[:-1], this_path.values[1:]))

    for i in range(this_path.shape[0] - 1):
        edges.append([this_path.bodyId.values[i], this_path.bodyId.values[i + 1], this_path.weight.values[i + 1]])

# Add the edges
G.add_weighted_edges_from(edges)

# Add some names to the nodes
nx.set_node_attributes(G, paths.set_index('bodyId')['type'].to_dict(), name='name')

import matplotlib.pyplot as plt

# Draw using a simple force-directed layout
pos = nx.kamada_kawai_layout(G)

# We could draw everything in one step but this way we have more control over the plot
fig, ax = plt.subplots(figsize=(10, 10))

# Draw nodes
nx.draw_networkx_nodes(G, pos=pos, ax=ax)

# Draw edges
weights = np.array([e[2]['weight'] for e in G.edges(data=True)])
nx.draw_networkx_edges(G, pos=pos, width=(weights / 12).tolist())

# Add node labels
nx.draw_networkx_labels(G, pos=pos, labels=dict(G.nodes('name')), font_size=14)

# Turn axes of
ax.set_axis_off()

In general, I recommend exporting your graph to e.g. graphml and importing it into e.g. cytoscape if you want to explore an interactive network graph. see nx.write_gml