Reference to paper on spike inference for spinal cord

Author: PTRRupprecht

README.md

@@ -41,6 +41,8 @@ You will get started within few minutes.
 
 ## Updates to ground truth datasets and pretrained models:
 
+***2025-05-01*** - Our study of spike inference for **calcium imaging data from spinal cord** is now published in the Journal of Neuroscience. Check out the [openly accessible manuscript](https://doi.org/10.1523/JNEUROSCI.1187-24.2025), which also includes the reviewer reports and rebuttal letters. Cascade models pretrained on spinal cord ground truth are already available, and the ground truth with both excitatory and inhibitory spinal cord neurons is already part of this repository's ground truth database (datasets #40 and #41).
+
 ***2025-04-25*** - New [blog post](https://gcamp6f.com/2025/04/25/accuaretly-computing-noise-levels-for-calcium-imaging-data/) about the standardized noise level $\nu$ that can be used to compare shot noise levels across calcium imaging recordings. The blog post investigas the effect of true noise levels, imaging rates and true neuronal spike rates on the measured noise metric.
 
 ***2025-04-10*** - First models for spike inference with interneurons, primarily based on GCaMP8 data, are now available. The models are described in our recent [preprint](https://www.biorxiv.org/content/10.1101/2025.03.03.641129v1) in Figure 6. Please check out this [FAQ section](https://github.com/HelmchenLabSoftware/Cascade?tab=readme-ov-file#can-i-apply-cascade-to-data-recorded-with-interneurons) for more details about these models and their potential limitations.