Network Viewer¶
The Network Viewer tab interactively explores the functional connectivity
network from a completed MEA-NAP run, including optional cell-type overlays.
It’s the Python equivalent of MATLAB’s runMEANAPviewer.m.
Using the Network Viewer tab¶
Click Browse… and select a MEA-NAP output
.matfile from theExperimentMatFiles/subfolder of an output directory, e.g.OutputData.../ExperimentMatFiles/<recording>_OutputData....mat.The network renders immediately. Recording metadata (name, DIV, group, active node count) appears in the left panel.
Adjust settings to update the plot in real time:
Lag — which functional connectivity lag value to view (e.g.
1000 ms,2500 ms,5000 ms).Edge threshold — minimum correlation weight required to draw an edge.
Node color metric — color nodes by any node-level metric present in the file (betweenness centrality, node strength, z-score, …), or leave as None for flat cyan nodes.
(Optional) Click Load cell types from file… to overlay cell-type information — see below.
Node size is always proportional to node degree (ND). Node color uses the viridis colormap, with a colorbar legend on the right.
Cell-type overlay¶
Cell types are rendered as concentric rings on each node, one line style per type, mirroring the MATLAB viewer.
Loading cell types:
Prepare (or locate) a cell-type spreadsheet: each column is one cell type, each cell contains the 1-indexed channel number of a cell belonging to that type. Columns with no cells for a given type should be left blank. The
PutativeCellType_*.xlsxfiles produced alongside MEA-NAP runs use this format.NeuN+
PV+
SST+
68
25
110
78
42
216
117
In the Cell types group, click Load cell types from file… and select the
.xlsxor.csvfile.A listbox appears with every cell type found — select one or more to filter the displayed network.
Filtering by cell type:
Selecting one type shows only nodes of that type.
Selecting multiple types shows only nodes belonging to all selected types (intersection — consistent with the MATLAB viewer).
Deselecting everything returns to showing all active nodes.
The concentric-circle legend at the bottom of the plot identifies which ring style corresponds to which cell type.
Note on .mat cell-type data
MEA-NAP stores Info.CellTypes inside output .mat files as a MATLAB MCOS
table object, which scipy.io can’t decode. When the viewer detects this, it
logs a message and prompts you to load the cell-type spreadsheet directly —
the same .xlsx file originally supplied to the MATLAB pipeline.
Using the network plotting API from Python¶
The plotting code underneath this tab is a standalone module,
meanap.network_plot, usable independently of the GUI. See the
network-plotting notebook tutorial
for a runnable, end-to-end walkthrough with real output baked in, or the
API reference for the full function/class list.