Wondering whether this type of summary might be useful.
Queried for connections between neurons of types in the set
L2, L3, Mi1, TM2, Tm4, T4 & T5
| upstream_type |
weight |
downstream_type |
Robustness |
downstream neurons |
| L2 |
21 |
Tm4 |
93.95 |
2.37 |
| L2 |
104 |
Tm2 |
54.54 |
1.11 |
| L3 |
18 |
Mi1 |
40.25 |
1.03 |
| Mi1 |
16 |
T4 |
99.77 |
7.25 |
| Mi1 |
13 |
Tm3 |
93.58 |
2.42 |
| Tm2 |
13 |
T5 |
99.55 |
4.5 |
| Tm3 |
9 |
T4 |
99.32 |
4.38 |
| Tm3 |
6 |
Tm3 |
64.32 |
1.48 |
| Tm4 |
8 |
T5 |
97.84 |
3.64 |
Weight: mean number of synapses per pairwise connection. Robustness: percentage of cells of the upstream type connected to cells of the downstream type - the number connected to a neuron of the downstream type/number of neurons of the upstream type for which we have connectomic data. Downstream neurons: mean number of neurons of the downstream type that each neuron of the upstream type connects to (dividing the number of pairwise connections by the number of upstream neurons.)
Visualisations - connectivity matrix - could use something fancier than a heat map to allow a couple of values in each square. e.g. see visualisations from transcriptomics of %expressing cells + levels using colors and bars
queries used:
MATCH (up:Class:Neuron)<-[:SUBCLASSOF*0..2]-(upsub:Class:Neuron)<-[:INSTANCEOF]-
(n1:Neuron:Individual:has_neuron_connectivity)-[st:synapsed_to]->(n2:Individual:Neuron:has_neuron_connectivity)-
[:INSTANCEOF]->(downsub:Class:Neuron)-[:SUBCLASSOF*0..2]->(down:Class)
WHERE st.weight[0] >= 5
AND up.short_form in ["FBbt_00003720", "FBbt_00003721", "FBbt_00003731", "FBbt_00003736",
"FBbt_00003776", "FBbt_00003790", "FBbt_00003791", "FBbt_00003792"]
AND down.short_form in ["FBbt_00003720", "FBbt_00003721", "FBbt_00003731", "FBbt_00003736",
"FBbt_00003776", "FBbt_00003790", "FBbt_00003791", "FBbt_00003792"]
RETURN DISTINCT count(distinct n1) as upstream_count, count(distinct n2) as downstream_count,
up.symbol[0] as upstream_type, round(avg(st.weight[0])) as weight,
count(st) as pairwise_connections, down.symbol[0] as downstream_type
order by pairwise_connections desc, weight desc
MATCH (up:Class:Neuron)<-[:SUBCLASSOF*0..2]-(upsub:Class:Neuron)<-[:INSTANCEOF]-
(n1:Neuron:Individual:has_neuron_connectivity)
WHERE up.short_form in ["FBbt_00003720", "FBbt_00003721", "FBbt_00003731", "FBbt_00003736", "FBbt_00003776", "FBbt_00003790", "FBbt_00003791", "FBbt_00003792"]
RETURN DISTINCT up.symbol[0], count(n1) as upstream_count
Wondering whether this type of summary might be useful.
Queried for connections between neurons of types in the set
L2, L3, Mi1, TM2, Tm4, T4 & T5
Weight: mean number of synapses per pairwise connection. Robustness: percentage of cells of the upstream type connected to cells of the downstream type - the number connected to a neuron of the downstream type/number of neurons of the upstream type for which we have connectomic data. Downstream neurons: mean number of neurons of the downstream type that each neuron of the upstream type connects to (dividing the number of pairwise connections by the number of upstream neurons.)
Visualisations - connectivity matrix - could use something fancier than a heat map to allow a couple of values in each square. e.g. see visualisations from transcriptomics of %expressing cells + levels using colors and bars
queries used: