gin commit from UX410UAK

Modified files: 2

README.md

@@ -6,7 +6,7 @@ This dataset contains the binned activity times series of intracranial recording
 For each patient, the dataset contains one 10-minute reference recording (interictal), obtained in a seizure-free interval, as well as several pre-ictal recordings, spanning 10 minutes prior to seizure onset. Pre-ictal recordings end at seizure onset.
 
 The binned activity is defined as the number of recorded active neurons in a certain brain area in discrete time bins of 4 ms. For each recording, we provide the binned activities in left and right hippocampus (LH/RH), amygdala (LA/RA), parahippocampal cortex (LPHC/RPHC), entorhinal cortex (LEC/REC), and the full medial temporal lobe (left/right).
-For more details on the data acquisition and pre-processing, see [ref].
+For more details on the data acquisition and pre-processing, see [1].
 
 
 ## Repository structure
@@ -16,17 +16,19 @@ For more details on the data acquisition and pre-processing, see [ref].
 * preIct_recordings_patients.txt contains a list of all preictal recordings and the corresponding patientID
 * interictal/* contains all interictal (reference) recordings
 * preictal/* contains all preictal recordings
+* all recordings are provided as pickle files (.pkl) and as textfiles (.txt)
 
 
 ### Python Code
-Python scripts to estimate the distance to criticality using the Multistep Regression estimator [ref] and to reproduce the results shown in [ref].
+* Example code to read the data (python_code/reading_data/*)
+* Scripts to estimate the distance to criticality using the Multistep Regression estimator [2] and to reproduce the results shown in [1] (python_code/analysis_PlosCB/*)
 
 ## Cite as
 Reference: Assessing criticality in pre-seizure single neuron activity of human epileptic cortex.
 
 ## Related Publications
-* Reference: Assessing criticality in pre-seizure single neuron activity of human epileptic cortex.
-* Reference: MR estimator
+* [1] Assessing criticality in pre-seizure single neuron activity of human epileptic cortex.
+* [2] Spitzner, F. P., Dehning, J., Wilting, J., Hagemann, A., Neto, J. P., Zierenberg, J., & Priesemann, V. (2020). MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity. arXiv preprint arXiv:2007.03367.
 
 ## Licensing
-See `LICENSE.txt` for the full license.
+See `LICENSE.txt` for the full license.

python_code/analysis_PlosCB/readme_code.md

@@ -4,17 +4,17 @@
 ## Running the Multistep Regression Analysis
 
 * run_analysis_fullrecs.py (Analysis of full recordings from all brain areas)
-* run_analysis_timeresolved.py (Timeresolved analysis, including the 2-part analysis and the sliding window analysis. Note that the sliding window analysis of all recordings is computationally expensive.)
+* run_analysis_timeresolved.py (Timeresolved analysis, including the 2-part analysis and the sliding window analysis. Note that the sliding window analysis of all recordings will be computationally expensive.)
 
 
-## Creating the figures
+## Creating the figures (after running the analysis)
 
 * create_figure_1.py
 * create_figure_2.py
 * create_supp_figures.py
 
 
-## Other functions / utilities called by the above mentioned scipts
+## Other functions / utilities called by the scripts
 
 * mr_epilepsy_fullrecs.py
 * mr_epilepsy_timeresolved.py