meanap.pipeline

MEA-NAP Python pipeline — spike detection and analysis steps.

Modules

burst_detection

cancellation

Cooperative cancellation for pipeline runs.

channel_layout

Electrode channel-ID -> spatial coordinate lookup, port of getCoordsFromLayout.m.

example_data

Download the shared example dataset used by the MATLAB and Python test pipelines.

firing_rates

io

I/O helpers for MEA-NAP pipeline files.

louvain

Louvain modularity optimization, port of community_louvain.m (BCT).

modularity

Consensus-clustering modularity, port of mod_consensus_cluster_iterate.m.

network_metrics

Network metrics, ported from the Brain Connectivity Toolbox (Functions/2019_03_03_BCT/*.m) as called by ExtractNetMet.m.

nmf

Non-negative matrix factorization dimensionality metrics, port of calNMF.m (called from ExtractNetMet.m for the num_nnmf_components /nComponentsRelNS/nnmf_residuals/nnmf_var_explained fields).

null_models

Degree/strength-preserving network randomization, ports of randmio_und_signed.m, null_model_und_sign.m, randmio_und_v2.m and latmio_und_v2.m (BCT / Functions/CC_PL_SW/).

output_folders

Create the MEA-NAP output folder tree, mirroring CreateOutputFolders.m.

parula

plotting

plotting_step2

plotting_step4

Step 4 check plots: plotConnectivityProperties.m, StandardisedNetworkPlot.m (base + betweenness-centrality-colored variants), NodeCartography.m, StandardisedNetworkPlotNodeColourMap.m (circular/module variant), electrodeSpecificMetrics.m (half-violin panel of all node metrics), and StandardisedNetworkPlotNodeCartography.m (circular/cartography variant).

probabilistic_threshold

Probabilistic edge thresholding, port of adjM_thr_parallel.m.

report

Self-contained HTML output viewer for a MEA-NAP pipeline run.

runner

Top-level pipeline runner, orchestrating steps to mirror MEApipeline.m.

spike_detection

MEA spike detection algorithms — Python port of MATLAB WATERS.

spreadsheet

Read the recording list spreadsheet, mirroring pipelineReadCSV.m.

step2

step3

Step 3: functional connectivity (adjacency matrices), port of the generateAdjMs.m / adjM_thr_parallel.m portion of MEApipeline.m.

step4

Step 4: network activity metrics, port of ExtractNetMet.m (see network_metrics.py for exactly which metrics are and aren't in scope, and which are deterministic vs.

sttc

Spike Time Tiling Coefficient (STTC), port of get_sttc.m / sttc_m.m.