Nicholas Tolley

Agreed, could plan to do it after SfN! (it ends November 16th). Before may work depending on how much last minute poster making me and @rythorpe have to do

@JBruce32 the default parameter file comes from the parameter tuned network used in [Jones et al. 2009](https://pubmed.ncbi.nlm.nih.gov/20149881/) It's broadly the same structure as the `.param` files from HNN-GUI (however a...

Hi @JBruce32, unfortunately this function is not used for writing the details of the `Network` to a file (internally this function is useful for testing purposes). For context, the `.params`...

@samadpls this could be something to consider for your project!

> Looks good so far! Let's see how it shapes when you have it working Agreed! Also @mjpelah I added the tag "WIP" before the title to indicate the PR...

Small nitpick, the `_plot_cell()` function is a bit confusingly named as there is a `plot_cells()` function which is called from the `Network` and plots the soma positions. Perhaps the next...

This can be saved for another PR, but two things that would be really nice to have in `plot_cell_morhology` is the ability to specify different colors for each section, as...

Following up on our conversation about the connectivity. I think we can avoid using the hardcoded values referencing the params file through a combination of the attribute [`net.connectivity`](https://jonescompneurolab.github.io/hnn-core/stable/generated/hnn_core.Network.html#hnn_core.Network) and [`pick_connection()`](https://jonescompneurolab.github.io/hnn-core/stable/generated/hnn_core.pick_connection.html#hnn_core.pick_connection)...

[Here](https://github.com/ntolley/hnn-core/blob/9db8532e7935367e0535b52b26c10295645f3664/hnn_core/network.py#L1182-L1197) is an example of the logic I've recently implemented in #419 that allows you to see if a given `receptor` and `loc` combination is valid. You could loop through...

As for modifying connections directly, here's an example of how it'd be done: ```py new_weight = 0.1 new_prob = 0.5 conn_indices = pick_connection(net, src_gids='L2_pyramidal', target_gids='L5_pyramidal', loc='proximal', receptor='ampa') assert len(conn_indices) ==...