From 4b56a52ccebcaa3630d2e7fe5efd10de726aa1cd Mon Sep 17 00:00:00 2001 From: jschepers Date: Thu, 7 Nov 2024 10:38:23 +0100 Subject: [PATCH] minor changes --- joss_paper/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/joss_paper/paper.md b/joss_paper/paper.md index 42f4cac7..4475850b 100644 --- a/joss_paper/paper.md +++ b/joss_paper/paper.md @@ -72,7 +72,7 @@ Few toolboxes for simulating EEG data exist, most being proprietary MATLAB tools In the following, we highlight two actively developed MATLAB-based tools: `Brainstorm` [@tadel2011brainstorm] which especially excels at visualizing the forward model and generating ERPs from phase-aligned oscillations, and `SEREEGA` [@krol2018sereega], which offers comprehensive simulation capabilities with a focus on ERP-component simulation, tools for benchmarking like signal-to-noise specification and more realistic noise simulation (e.g. via random sources). -In Python, `MNE-Python` [@GramfortEtAl2013a] provides some tutorials to simulate EEG data, but the functionality is very basic. `HNN-Core` [@Jas2023] can simulate realistic EEG data but requires detailed knowledge of neurocortical column models. +In Python, `MNE-Python` [@GramfortEtAl2013a] provides some tutorials to simulate EEG data, but the functionality is very basic. `HNN-Core` [@Jas2023] can simulate realistic EEG data by parameterising the neuronal activity in cortical columns. In contrast to these tools, `UnfoldSim.jl` has a higher-level perspective, uniquely focusing on the regression-ERP aspect. It provides functions to simulate multi-condition experiments, uniquely allows for modelling multi-subject EEG datasets, and offers support to model continuous EEG data with overlapping events. Further, the implementation in Julia offers a platform that is free, actively encourages research software engineering methods, makes it easy to add custom expansions via the `AbstractTypes`, and allows easy access from Python and R.