diff --git a/multiarea_model/data_multiarea/SLN_logdensities.R b/multiarea_model/data_multiarea/SLN_logdensities.R
deleted file mode 100644
index 38fbe8a3e19f9e74bf85d53324c96f160d69a8a3..0000000000000000000000000000000000000000
--- a/multiarea_model/data_multiarea/SLN_logdensities.R
+++ /dev/null
@@ -1,13 +0,0 @@
-library('aod')
-source(paste(Sys.getenv('HOME'),'/model-june/data_multi_area/bbAlt.R', sep=""))
-f <- file(paste(Sys.getenv('HOME'),'/model-june/data_multi_area/raw_data/RData_prepared_logdensities.txt', sep=""),'r')
-x <- read.table(f)
-close(f)
-
-
-dens <- data.matrix(x)[,7]
-
-m2.bb <- betabin(cbind(S, I) ~ dens , ~ 1, data = x, "probit", control = list(maxit = 100000))
-h2.bb <- c(coef(m2.bb))
-
-print(h2.bb)
diff --git a/multiarea_model/data_multiarea/VisualCortex_Data.py b/multiarea_model/data_multiarea/VisualCortex_Data.py
index 37ef027f82519e5a3083dc0781d91cc3d1842d79..047ca4a4f7791ac4ebf56fd9db8ad5330dfca80c 100644
--- a/multiarea_model/data_multiarea/VisualCortex_Data.py
+++ b/multiarea_model/data_multiarea/VisualCortex_Data.py
@@ -1328,16 +1328,11 @@ def process_raw_data():
         return res
 
     # Call R script to perform SLN fit
-    try:
-        proc = subprocess.Popen(["Rscript",
-                                 os.path.join(basepath, 'SLN_logdensities.R')],
-                                stdout=subprocess.PIPE)
-        out = proc.communicate()[0].decode('utf-8')
-        R_fit = [float(out.split('\n')[1].split(' ')[1]),
-                 float(out.split('\n')[1].split(' ')[3])]
-    except OSError:
-        print("No R installation, taking hard-coded fit parameters.")
-        R_fit = [-0.1516142, -1.5343200]
+    print("We currently cannot publish the R code because of "
+          "copyright issues, there taking hard-coded fit parameters. "
+          "See Schmidt et al. (2018) for a full explanation "
+          "of the procedure.")
+    R_fit = [-0.1516142, -1.5343200]
 
     """
     4. Fill missing data with fitted values.