connectivity matrices

Explore the connectivity of different neuronal cell types in our dataset

Render by Alexandra Rother

what?

The connectomic dataset allows us to examine either individual synapses or all of the synapses connected to a single cell. To better understand common connectivity motifs, we have grouped cells by neuronal cell type. Further information about these cell types can be found on the Cell Types page. We focused on three matrices that are useful for analysing connectivity from different perspectives. Each matrix element therefore contains the total synaptic area of all the synapses from one presynaptic cell type to a postsynaptic cell type. We focused on synaptic areas as these provide an estimate of synaptic strength.

why?

To help you visualise the contents of these matrices more easily, we have created an interactive version for the website. You can find the original version in the Rother et al. (2025) paper (see the Publications page). Clicking on certain elements in the matrix allows you to view an example synapse and renderings of the pre- and postsynaptic cells. Not all matrix elements are interactive: we focused on connections that we deemed to be the most important for the circuit motifs explained in our publications.

how?

Explore the matrices by clicking on different elements. Hovering over an element will cause the pre- and postsynaptic cell types to light up, and the elements that can be clicked on will become larger. To see examples of the synapses included, click on the matrix element to open a pop-up window.

Matrix and Lightbox

postsynaptic cell type

presynaptic cell type
MSN
STN
TAN
GPe
GPi
LTS
INT1
INT2
INT3
DA
1.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
LMAN
12.1
0.4
0.0
0.1
0.3
0.0
0.3
0.2
0.1
HVC
52.9
0.5
0.1
1.0
2.0
0.1
0.2
0.5
2.1
MSN
0.3
0.1
0.2
1.6
4.7
0.1
0.0
0.1
0.4
STN
0.2
0.1
0.0
0.1
0.9
0.0
0.0
0.0
0.0
TAN
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
GPe
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.4
0.3
GPi
0.2
0.8
0.0
0.0
0.7
0.1
0.2
0.3
0.3
LTS
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
INT1
0.1
0.1
0.0
0.6
0.8
0.1
0.3
0.0
0.0
INT2
2.5
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
INT3
7.4
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.3
50403020100
percentage [%]

globally normalised

×

globally normalised

what is “globally normalised”?

“Globally normalised” means that the synaptic area is shown in relation to the total synaptic area in the dataset. Therefore, the sum of all elements of the matrix is 100%. This visualisation helps to identify the most frequent connections across the dataset.

Matrix and Lightbox

postsynaptic cell type

presynaptic cell type
MSN
STN
TAN
GPe
GPi
LTS
INT1
INT2
INT3
DA
2.3
1.8
3.5
0.4
0.2
1.8
3.2
0.6
0.6
LMAN
15.6
16.3
6.7
3.8
2.8
7.0
25.4
11.3
3.1
HVC
68.2
20.7
36.8
28.7
20.7
16.1
13.9
31.9
59.4
MSN
0.4
5.7
46.3
45.8
49.9
14.8
2.5
4.2
12.3
STN
0.2
5.3
3.5
3.0
9.8
3.7
1.5
1.1
0.6
TAN
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
GPe
0.0
6.9
1.1
0.4
0.8
8.6
0.9
23.0
7.5
GPi
0.3
34.2
0.2
0.3
6.9
29.6
14.7
16.2
8.0
LTS
0.1
0.3
0.2
0.1
0.0
0.1
0.4
0.0
0.0
INT1
0.1
6.2
1.4
17.3
8.9
14.8
22.8
2.0
0.0
INT2
3.2
0.9
0.1
0.1
0.0
0.5
14.1
0.3
0.1
INT3
9.6
1.6
0.3
0.0
0.0
2.8
0.6
9.3
8.3
60504030200
percentage [%]

incoming normalised

×

incoming normalised

what is “incoming normalised”?

“Incoming normalised” means that the synaptic area is shown in relation to the total synaptic area received by one cell type. Therefore, the sum of each column is 100%. This visualisation helps us to see which inputs each cell type receives on the soma or dendrites of its cells.

Matrix and Lightbox

postsynaptic cell type

presynaptic cell type
MSN
STN
TAN
GPe
GPi
LTS
INT1
INT2
INT3
DA
91.5
2.2
0.6
0.8
0.9
0.4
2.1
0.5
1.1
LMAN
89.2
2.8
0.2
1.0
2.0
0.2
2.4
1.4
0.8
HVC
89.2
0.8
0.2
1.7
3.3
0.1
0.3
0.9
3.5
MSN
4.4
1.8
2.1
21.1
62.9
0.8
0.4
1.0
5.6
STN
13.4
8.7
0.8
7.2
64.9
1.0
1.3
1.3
1.4
TAN
96.2
1.1
0.0
0.7
0.0
0.0
2.1
0.0
0.0
GPe
1.5
16.8
0.4
1.4
7.5
3.5
1.2
40.8
26.9
GPi
8.9
31.4
0.0
0.4
25.5
4.6
7.3
10.9
10.9
LTS
68.1
12.0
0.9
7.6
1.5
0.8
8.1
0.9
0.2
INT1
3.7
7.1
0.2
29.2
41.2
2.8
14.1
1.6
0.1
INT2
92.0
0.8
0.0
0.1
0.1
0.1
6.6
0.2
0.1
INT3
93.7
0.5
0.0
0.0
0.1
0.1
0.1
2.0
3.6
806040200
percentage [%]

outgoing normalised

×

outgoing normalised

what is “outgoing normalised”?

“Outgoing normalised” means that the synaptic area is shown in relation to the total synaptic area that one cell type makes to all its targets. Therefore, the sum of each row is 100%. This visualisation helps to show the output target of each cell type.