ALMOST finished the methods section.

2026-05-15 16:45:51 +02:00
parent cbd0af7a5f
commit 155fb1eecf
46 changed files with 561 additions and 450 deletions
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--- a/main.aux
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@@ -166,13 +166,13 @@
 \abx@aux@segm{0}{0}{bauer1987separate}
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 \newlabel{sec:intensity_measures}{{2.2.3}{12}{}{}{}}
 \newlabel{eq:input_ratio}{{14}{13}{}{}{}}
-\@writefile{toc}{\contentsline {subsection}{\numberline {2.3}Field data-based analysis of the model pathway}{13}{}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {2.3}Field data-based analysis of the model pathway}{14}{}\protected@file@percent }
 \@writefile{toc}{\contentsline {section}{\numberline {3}Results}{14}{}\protected@file@percent }
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.1}Mechanisms driving the emergence of intensity invariance}{14}{}\protected@file@percent }
 \@writefile{toc}{\contentsline {subsubsection}{\numberline {3.1.1}Full-wave rectification \& lowpass filtering}{14}{}\protected@file@percent }
--- a/main.blg
+++ b/main.blg
@@ -1,71 +1,71 @@
 [0] Config.pm:307> INFO - This is Biber 2.19
 [0] Config.pm:310> INFO - Logfile is 'main.blg'
-[36] biber:340> INFO - === Do Mai 14, 2026, 14:31:13
+[36] biber:340> INFO - === Fr Mai 15, 2026, 16:11:10
-[43] Biber.pm:419> INFO - Reading 'main.bcf'
+[45] Biber.pm:419> INFO - Reading 'main.bcf'
-[72] Biber.pm:979> INFO - Found 55 citekeys in bib section 0
+[73] Biber.pm:979> INFO - Found 55 citekeys in bib section 0
-[78] Biber.pm:4419> INFO - Processing section 0
+[79] Biber.pm:4419> INFO - Processing section 0
-[82] Biber.pm:4610> INFO - Looking for bibtex file 'cite.bib' for section 0
+[83] Biber.pm:4610> INFO - Looking for bibtex file 'cite.bib' for section 0
-[84] bibtex.pm:1713> INFO - LaTeX decoding ...
+[85] bibtex.pm:1713> INFO - LaTeX decoding ...
-[114] bibtex.pm:1519> INFO - Found BibTeX data source 'cite.bib'
+[116] bibtex.pm:1519> INFO - Found BibTeX data source 'cite.bib'
-[292] UCollate.pm:68> INFO - Overriding locale 'en-US' defaults 'variable = shifted' with 'variable = non-ignorable'
+[289] UCollate.pm:68> INFO - Overriding locale 'en-US' defaults 'variable = shifted' with 'variable = non-ignorable'
-[292] UCollate.pm:68> INFO - Overriding locale 'en-US' defaults 'normalization = NFD' with 'normalization = prenormalized'
+[289] UCollate.pm:68> INFO - Overriding locale 'en-US' defaults 'normalization = NFD' with 'normalization = prenormalized'
-[292] Biber.pm:4239> INFO - Sorting list 'nyt/global//global/global' of type 'entry' with template 'nyt' and locale 'en-US'
+[289] Biber.pm:4239> INFO - Sorting list 'nyt/global//global/global' of type 'entry' with template 'nyt' and locale 'en-US'
-[292] Biber.pm:4245> INFO - No sort tailoring available for locale 'en-US'
+[289] Biber.pm:4245> INFO - No sort tailoring available for locale 'en-US'
-[316] bbl.pm:660> INFO - Writing 'main.bbl' with encoding 'UTF-8'
+[312] bbl.pm:660> INFO - Writing 'main.bbl' with encoding 'UTF-8'
-[328] bbl.pm:763> INFO - Output to main.bbl
+[322] bbl.pm:763> INFO - Output to main.bbl
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 10, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 10, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 21, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 21, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 38, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 38, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 49, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 49, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 58, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 58, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 73, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 73, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 82, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 82, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 91, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 91, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 100, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 100, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 109, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 109, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 118, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 118, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 127, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 127, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 136, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 136, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 157, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 157, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 178, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 178, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 187, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 187, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 196, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 196, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 207, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 207, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 218, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 218, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 229, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 229, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 240, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 240, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 249, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 249, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 258, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 258, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 269, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 269, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 278, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 278, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 289, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 289, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 300, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 300, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 309, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 309, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 328, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 328, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 337, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 337, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 400, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 400, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 419, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 419, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 428, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 428, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 437, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 437, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 456, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 456, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 491, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 491, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 526, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 526, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 535, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 535, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 556, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 556, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 565, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 565, warning: 6 characters of junk seen at toplevel
-[328] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 576, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 576, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 587, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 587, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 619, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 619, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 648, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 648, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 658, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 658, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 667, warning: 6 characters of junk seen at toplevel
+[322] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 667, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 688, warning: 6 characters of junk seen at toplevel
+[323] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 688, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 709, warning: 6 characters of junk seen at toplevel
+[323] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 709, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 720, warning: 6 characters of junk seen at toplevel
+[323] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 720, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 729, warning: 6 characters of junk seen at toplevel
+[323] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_2sRz/347c261ec4135a5723bef5c751f5078f_24870.utf8, line 729, warning: 6 characters of junk seen at toplevel
-[329] Biber.pm:131> WARN - BibTeX subsystem: /tmp/biber_tmp_CAWg/347c261ec4135a5723bef5c751f5078f_89475.utf8, line 749, warning: 6 characters of junk seen at toplevel
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-Output written on main.pdf (42 pages, 33581775 bytes).
+Output written on main.pdf (42 pages, 33586366 bytes).
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--- a/main.pdf
+++ b/main.pdf
--- a/main.synctex.gz
+++ b/main.synctex.gz
--- a/main.tex
+++ b/main.tex
@@ -79,18 +79,14 @@
 \newcommand{\kf}{\omega} % Unspecific Gabor kernel frequency
 \newcommand{\kp}{\phi} % Unspecific Gabor kernel phase
 \newcommand{\kn}{n} % Unspecific Gabor kernel lobe number
 % \newcommand{\ks}{s} % Unspecific Gabor kernel sign
 \newcommand{\kwi}{\kw_i} % Specific Gabor kernel width
 \newcommand{\kfi}{\kf_i} % Specific Gabor kernel frequency
 \newcommand{\kpi}{\kp_i} % Specific Gabor kernel phase
 \newcommand{\kni}{\kn_i} % Specific Gabor kernel lobe number
 % \newcommand{\ksi}{\ks_i} % Specific Gabor kernel sign
 % Math shorthands - Auxiliary kernel parameters:
-\newcommand{\fsin}{f_{\text{sin}}} % Carrier frequency
+\newcommand{\fdrm}{\text{FDRM}} % Gaussian full duration relative to maximum
-\newcommand{\rh}{h_{\text{rel}}} % Relative Gaussian height for FWRH
+\newcommand{\rh}{h_{\text{rel}}} % Relative Gaussian height for FDRM calculation
 \newcommand{\fwrh}{\text{FWRH}} % Gaussian full-width at relative height
 \newcommand{\off}{\beta_0} % Offset for linear frequency approximation
 % Math shorthands - Thresholding nonlinearity:
 \newcommand{\thr}{\Theta_i} % Step function threshold value
@@ -287,6 +283,20 @@ approximation by basic mathematical operations. We then elaborate on the key
 mechanisms that drive the emergence of intensity-invariant song representations
 within the auditory pathway.
 % RIPPED FROM RESULTS, MAYBE INTEGRATE SOMEWHERE HERE:
 % The robustness of song recognition is tied to the degree of intensity
 % invariance of the finalized feature representation. Ideally, the values of each
 % feature should depend only on the relative amplitude dynamics of the song
 % pattern but not on the overall intensity of the song. In the grasshopper, the
 % emergence of intensity-invariant representations along the song recognition
 % pathway likely is a distributed process that involves different neuronal
 % populations, which raises the question of what the essential computational
 % mechanisms are that drive this process. Within the model pathway, we identified
 % two key mechanisms that render the song representation more invariant to
 % intensity variations. The two mechanisms each comprise a nonlinear signal
 % transformation followed by a linear signal transformation but differ in the
 % specific operations involved, as outlined in the following sections.
 % SCRAPPED UNTIL FURTHER NOTICE:
 % Multi-species, multi-individual communally inhabited environments\\
 % - Temporal overlap: Simultaneous singing across individuals/species common\\
@@ -328,43 +338,38 @@ on PyPi.
 \subsection{Functional model of the grasshopper song recognition pathway}
-% Too long (no splitting, only pruning).
+The anatomical organisation of the grasshopper song recognition pathway can be
-The essence of constructing a functional model of a given system is to gain a
+outlined as a feed-forward network of three consecutive neuronal
-sufficient understanding of the system's essential structural components and
+populations~(Fig.\,\ref{fig:pathway}a-c): Peripheral auditory receptor neurons,
-their presumed functional roles; and to then build a formal framework of
+whose axons enter the ventral nerve cord (VNC) at the level of the metathoracic
-manageable complexity around these two aspects. Anatomically, the organization
+ganglion; local interneurons that remain exclusively within the thoracic region
-of the grasshopper song recognition pathway can be outlined as a feed-forward
+of the VNC; and ascending neurons projecting from the thoracic region towards
-network of three consecutive neuronal
+the supraesophageal ganglion (SEG), or central
-populations~(Fig.\,\mbox{\ref{fig:pathway}a-c}): Peripheral auditory receptor
+brain~(\bcite{rehbein1974structure}; \bcite{rehbein1976auditory};
 neurons, whose axons enter the ventral nerve cord at the level of the
 metathoracic ganglion; local interneurons that remain exclusively within the
 thoracic region of the ventral nerve cord; and ascending neurons projecting
 from the thoracic region towards the supraesophageal
 ganglion~(\bcite{rehbein1974structure}; \bcite{rehbein1976auditory};
 \bcite{eichendorf1980projections}). The input to the network originates at the
 tympanal membrane, which acts as acoustic receiver and is coupled to the
 dendritic endings of the receptor neurons~(\bcite{gray1960fine}). The outputs
-from the network converge in the supraesophageal ganglion, which is presumed to
+from the network converge in the SEG, which presumably harbors the neuronal
-harbor the neuronal substrate for conspecific song recognition and response
+substrate for conspecific song recognition and response
 initiation~(\bcite{ronacher1986routes}; \bcite{bauer1987separate};
-\bcite{bhavsar2017brain}). Functionally, the ascending neurons are the most
+\bcite{bhavsar2017brain}).
 diverse of the three populations along the pathway. Individual ascending
 neurons possess highly specific response properties that contrast with the
 rather homogeneous response properties of the preceding receptor neurons and
 local interneurons~(\bcite{clemens2011efficient}), indicating a transition from
 a uniform population-wide processing stream into several parallel branches.
 Based on these anatomical and physiological considerations, the overall
 structure of the model pathway is divided into two distinct
 stages~(Fig.\,\ref{fig:pathway}d). The preprocessing stage incorporates the
 known physiological processing steps at the levels of the tympanal membrane,
 the receptor neurons, and the local interneurons; and operates on
 one-dimensional signal representations. The feature extraction stage
 corresponds to the processing within the ascending neurons and further
 downstream towards the supraesophageal ganglion; and operates on
 high-dimensional signal representations. The details of each physiological
 processing step and its functional approximation within the two stages are
 outlined in the following sections.
 Functionally, the ascending neurons are the most diverse of the three neuronal
 populations. Individual ascending neurons possess highly specific response
 properties that contrast with the rather homogeneous response properties of the
 preceding receptor neurons and local
 interneurons~(\bcite{clemens2011efficient}), which indicates a transition from
 a uniform population-wide processing stream into several parallel branches.
 Accordingly, the model pathway is divided into two distinct
 stages~(Fig.\,\ref{fig:pathway}d): The preprocessing stage incorporates the
 processing steps at the levels of the tympanal membrane, the receptor neurons,
 and the local interneurons; and operates on one-dimensional signal
 representations~(Fig.\,\ref{fig:stages_pre}). The feature extraction stage
 corresponds to the processing within the ascending neurons and further
 downstream towards the SEG; and operates on high-dimensional signal
 representations~(Fig.\,\ref{fig:stages_feat}). The details of each
 physiological processing step and its functional approximation are described in
 the following sections.
 \begin{figure}[!ht]
    \centering
    \includegraphics[width=\textwidth]{figures/fig_auditory_pathway.pdf}
@@ -389,53 +394,54 @@ outlined in the following sections.
 \subsubsection{Population-driven signal preprocessing}
-Grasshoppers receive airborne sound waves by a tympanal organ at either side of
+Grasshoppers receive airborne sound waves by a tympanal organ at each side of
 the body. The tympanal membrane acts as a mechanical resonance filter for
 sound-induced vibrations~(\bcite{windmill2008time}; \bcite{malkin2014energy}).
 Vibrations that fall within specific frequency bands are focused on different
 membrane areas, while others are attenuated. This processing step can be
-approximated by an initial bandpass filter
+approximated by an initial bandpass filter~(Fig.\,\ref{fig:stages_pre}a)
 applied to the acoustic input signal $\raw(t)$:
 \begin{equation}
    \filt(t)\,=\,\raw(t)\,*\,\bp, \qquad \fc\,=\,5\,\text{kHz},\,30\,\text{kHz}
    \label{eq:bandpass}
 \end{equation}
-applied to the acoustic input signal $\raw(t)$. The auditory receptor neurons
+The receptor neurons transduce the vibrations of the tympanal membrane into
-transduce the vibrations of the tympanal membrane into sequences of action
+sequences of action potentials. They thereby encode the amplitude modulation,
-potentials. Thereby, they encode the amplitude modulation, or envelope, of the
+or envelope, of the signal~(\bcite{machens2001discrimination}), which likely
-signal~(\bcite{machens2001discrimination}), which likely involves a rectifying
+involves a rectifying nonlinearity~(\bcite{machens2001representation}). The
-nonlinearity~(\bcite{machens2001representation}). This can be modelled as
+extraction of the signal envelope~(Fig.\,\ref{fig:stages_pre}b) can be modelled
-full-wave rectification followed by lowpass filtering
+as full-wave rectification followed by lowpass filtering of the tympanal signal
 $\filt(t)$:
 \begin{equation}
    \env(t)\,=\,|\filt(t)|\,*\,\lp, \qquad \fc\,=\,250\,\text{Hz}
    \label{eq:env}
 \end{equation}
-of the tympanal signal $\filt(t)$. Furthermore, the receptors exhibit a
+Furthermore, the receptors exhibit a sigmoidal response curve over
-sigmoidal response curve over logarithmically compressed intensity
+logarithmically compressed stimulus intensities~(\bcite{suga1960peripheral};
-levels~(\bcite{suga1960peripheral}; \bcite{gollisch2002energy}). In the model
+\bcite{gollisch2002energy}). In the model pathway, logarithmic
-pathway, logarithmic compression is achieved by conversion to decibel scale
+compression~(Fig.\,\ref{fig:stages_pre}c) is achieved by conversion to decibel
 scale
 \begin{equation}
    \db(t)\,=\,20\,\cdot\,\dec \frac{\env(t)}{\dbref}, \qquad \dbref\,=\,1
    \label{eq:log}
 \end{equation}
-relative to the common reference intensity $\dbref$.
+relative to the common reference intensity $\dbref$. Both the receptor
-Both the receptor neurons~(\bcite{romer1976informationsverarbeitung};
+neurons~(\bcite{romer1976informationsverarbeitung}; \bcite{gollisch2004input};
-\bcite{gollisch2004input}; \bcite{fisch2012channel}) and, on a larger scale,
+\bcite{fisch2012channel}) and, on a larger scale, the subsequent local
-the subsequent local interneurons~(\bcite{hildebrandt2009origin};
+interneurons~(\bcite{hildebrandt2009origin}; \bcite{clemens2010intensity})
-\bcite{clemens2010intensity}) adapt their firing rates in response to sustained
+adapt their firing rates in response to sustained stimulus intensities, which
-stimulus intensity levels, which allows for the robust encoding of faster
+allows for the robust encoding of faster amplitude modulations against a slowly
-amplitude modulations against a slowly changing overall baseline intensity.
+changing overall baseline intensity. Functionally, the adaptation mechanism
-Functionally, the adaptation mechanism resembles a highpass filter
+resembles a highpass filter~(Fig.\,\ref{fig:stages_pre}d) over the
 logarithmically compressed envelope $\db(t)$:
 \begin{equation}
    \adapt(t)\,=\,\db(t)\,*\,\hp, \qquad \fc\,=\,10\,\text{Hz}
    \label{eq:highpass}
 \end{equation}
-over the logarithmically scaled envelope $\db(t)$. This processing step
+This processing step concludes the preprocessing stage of the model pathway.
-concludes the preprocessing stage of the model pathway. The resulting
+The resulting intensity-adapted envelope $\adapt(t)$ is then passed on from the
-intensity-adapted envelope $\adapt(t)$ is then passed on from the local
+local interneurons to the ascending neurons, where it serves as the basis for
-interneurons to the ascending neurons, where it serves as the basis for the
+the following feature extraction stage.
 following feature extraction stage.
 % Cite somewhere:
 \begin{figure}[!ht]
    \centering
    \includegraphics[width=\textwidth]{figures/fig_pre_stages.pdf}
@@ -453,59 +459,71 @@ following feature extraction stage.
 \subsubsection{Feature extraction by individual neurons}
 The ascending neurons extract and encode a number of different features of the
-preprocessed signal. As a population, they hence represent the signal in a
+preprocessed signal, and hence represent the signal in a higher-dimensional
-higher-dimensional space than the preceding receptor neurons and local
+space than the preceding receptor neurons and local interneurons. Each
-interneurons. Each ascending neuron is assumed to scan the signal for a
+ascending neuron is assumed to scan the signal for a specific template pattern,
-specific template pattern, which can be thought of as a kernel of a particular
+which can be thought of as a kernel of a particular structure and on a
-structure and on a particular time scale. This process, known as template
+particular time scale. This process, known as template matching, can be
-matching, can be modelled as a convolution
+modelled as a convolution of the intensity-adapted envelope $\adapt(t)$ with a
 kernel $k_i(t)$ specific to the $i$-th ascending neuron:
 \begin{equation}
    c_i(t)\,=\,\adapt(t)\,*\,k_i(t)
    = \infint \adapt(\tau)\,\cdot\,k_i(t\,-\,\tau)\,d\tau
    \label{eq:conv}
 \end{equation}
-of the intensity-adapted envelope $\adapt(t)$ with a kernel $k_i(t)$ per
+We use Gabor kernels as basis functions for creating different template
-ascending neuron. We use Gabor kernels as basis functions for creating
+patterns. An arbitrary one-dimensional, real Gabor kernel is generated by
-different template patterns. An arbitrary one-dimensional, real Gabor kernel is
+multiplication of a Gaussian envelope with standard deviation or kernel width
-generated by multiplication of a Gaussian envelope and a sinusoidal carrier
+$\kwi$ and a sinusoidal carrier with frequency $\kfi$ and phase $\kpi$:
 \begin{equation}
-    k_i(t,\,\kwi,\,\kfi,\,\kpi)\,=\,e^{-\frac{t^{2}}{2{\kwi}^{2}}}\,\cdot\,\sin(\kfi\,t\,+\,\kpi), \qquad \kfi\,=\,2\pi\fsin
+    k_i(t,\,\kwi,\,\kfi,\,\kpi)\,=\,e^{-\frac{t^{2}}{2{\kwi}^{2}}}\,\cdot\,\sin(\kfi\,t\,+\,\kpi), \qquad \kfi\,=\,2\pi f_{\text{sin}_i}
    \label{eq:gabor}
 \end{equation}
-with Gaussian standard deviation or kernel width $\kwi$, carrier frequency
+Different combinations of $\kwi$ and $\kfi$ result in Gabor kernels with
-$\kfi$, and carrier phase $\kpi$. Different combinations of $\kw$ and $\kf$
+different lobe number $\kni$, which is the number of half-periods of the
-result in Gabor kernels with different lobe number $\kn$, which is the number
+carrier that fit under the Gaussian envelope within reasonable limits of
-of half-periods of the carrier that fit under the Gaussian envelope within
+attenuation. The time window under the Gaussian envelope that contains the
-reasonable limits of attenuation. The interval under the Gaussian envelope that
+relevant lobes of the kernel can be defined as Gaussian full duration at height
-contains the relevant lobes of the kernel can be defined as Gaussian full-width
+$\rh$ relative to the maximum of the Gaussian:
 measured at relative peak height $\rh$
 \begin{equation}
-    \fwrh(\kw,\,\rh)\,=\,2\,\cdot\,\sqrt{-2\,\cdot\,\ln \rh}\cdot\,\kw, \qquad \rh\,\in\,(0,\,1]
+    \fdrm(\kwi,\,\rh)\,=\,2\,\cdot\,\sqrt{-2\,\cdot\,\ln \rh}\cdot\,\kwi, \qquad \rh\,\in\,(0,\,1]
    \label{eq:fdrm}
 \end{equation}
 % Yes, FDRM is a hideous acronym. Based on the common "full width at half
 % maximum" (FWHM) and adjusted because "full duration at half maximum" (FDHM)
 % is apparently preferred in a temporal context. Alternatively, "w_\text{gauss}"?
 With this, an appropriate carrier frequency $\kfi$ for obtaining a Gabor kernel
 with width $\kwi$ and desired lobe number $\kni$ can be approximated as
 \begin{equation}
    \kfi(\kni,\,\kwi,\,\rh)\,=\,\frac{0.5\,\cdot\,(\kni\,+\,\beta_0)}{\fdrm(\kwi,\,\rh)}, \qquad \kni\,\geq\,2\enspace\forall\enspace \kni\,\in\,\mathbb{Z}
    \label{eq:gabor_freq}
 \end{equation}
 With this, an appropriate carrier frequency $\kf$ for obtaining a Gabor kernel
 with width $\kw$ and desired lobe number $\kn$ can be approximated as
 % \begin{equation}
-%     \kf(\kn,\,\fwrh)\,=\,\frac{0.5\,\cdot\,\kn\,+\,\off}{\fwrh}, \qquad \kn\,\geq\,2\enspace\forall\enspace \kn\,\in\,\mathbb{Z}
+%     \kfi(\kni,\,\kwi,\,\rh)\,=\,\frac{0.5\,\cdot\,(\kni\,+\,\beta_0)}{2\,\cdot\,\sqrt{-2\,\cdot\,\ln \rh}\cdot\kwi}, \qquad \kni\,\geq\,2\enspace\forall\enspace \kni\,\in\,\mathbb{Z}
 % \end{equation}
-\begin{equation}
+The relationship between $\kfi$ and $\kni$ is approximately linear except for
-    \kf(\kn,\,\kw,\,\rh)\,=\,\frac{\kn\,+\,\off}{4\,\cdot\,\sqrt{-2\,\cdot\,\ln \rh}}, \qquad \kn\,\geq\,2\enspace\forall\enspace \kn\,\in\,\mathbb{Z}
+small $\kni$. The offset term $\beta_0\approx0.5$ was added to balance the
-\end{equation}
+amplitudes of the $\kni$ desired lobes of the kernel --- which should be
-where $\off$ is a small positive offset to the near-linear relationship between
+maximized --- against the amplitudes of the next-outer lobes, which should not
-$\kf$ and $\kn$ to balance the amplitude of the $\kn$ desired lobes of the
+exceed the threshold value determined by $\rh$. Note that simple Gaussian
-kernel --- which should be maximized --- against the amplitude of the
+kernels with $\kni=1$ can be obtained by setting the carrier frequency to
-next-outer lobes, which should not exceed the threshold value determined by
+$\kfi=0$ and are hence not covered by Eq.\,\ref{eq:gabor_freq}.
-$\rh$. For $\kn=1$, carrier frequency $\kf$ is set to zero, which results in a
+
-simple Gaussian kernel. Carrier phase $\kp$ determines the position of the
+Carrier phase $\kpi$ determines the position of the kernel lobes relative to
-kernel lobes relative to the kernel center. By setting $\kp$ to one of only
+the kernel center. We restrict the Gabor kernels to be either even or odd
-four specific phase values~(Tab.\,\ref{tab:gabor_phases}), we restrict the
+functions by setting $\kpi$ to one of only four specific phase
-Gabor kernels to be either even functions~(mirror-symmetric, uneven $\kn$) or
+values~(Tab.\,\ref{tab:gabor_phases}). Even Gabor kernels are mirror-symmetric
-odd functions~(point-symmetric, even $\kn$) with either positive or negative
+with uneven $\kni$, whereas odd Gabor kernels are point-symmetric with even
-sign, which refers to the sign of the kernel's central lobe (even kernels) or
+$\kni$. Both even and odd kernels can have either positive or negative sign,
-the left of the two central lobes (odd kernels).
+which refers to the sign of the kernel's central lobe (even kernels) or the
 left of the two central lobes (odd kernels). These four major groups of Gabor
 kernels allow for the extraction of different types of signal features, such as
 the presence of peaks (even, $+$), troughs (even, $-$), onsets (odd, $+$), and
 offsets (odd, $-$) at various time scales.
 \FloatBarrier
 \begin{table}[!ht]
    \centering
-    \captionsetup{width=.46\textwidth}
+    \captionsetup{width=.45\textwidth}
    \caption{Values of phase $\kp$ that are specific for the four major groups
             of Gabor kernels.}
    \begin{tabular}{|ccc|}
@@ -519,13 +537,10 @@ the left of the two central lobes (odd kernels).
    \label{tab:gabor_phases}
 \end{table}
 \FloatBarrier
-These four major groups of Gabor kernels allow for the extraction of different
+Following the convolutional template matching~(Fig.\,\ref{fig:stages_feat}a),
-types of signal features, such as the presence of peaks (even, $+$), troughs
+each kernel-specific response $c_i(t)$ is passed through a shifted Heaviside
-(even, $-$), onsets (odd, $+$), and offsets (odd, $-$) at various time scales.
+step-function $\nl$ with threshold value $\thr$ to obtain a binary
-% Add kernel normalization here.
+response~(Fig.\,\ref{fig:stages_feat}b):
 Following the convolutional template matching, each kernel-specific response
 $c_i(t)$ is passed through a shifted Heaviside step-function $\nl$ with
 threshold value $\thr$ to obtain a binary response
 \begin{equation}
    b_i(t,\,\thr)\,=\,\begin{cases}
        \;1, \quad c_i(t)\,>\,\thr\\
@@ -533,12 +548,12 @@ threshold value $\thr$ to obtain a binary response
    \end{cases}
    \label{eq:binary}
 \end{equation}
-which can be thought of as a categorization into "relevant" and "irrelevant"
+The thresholding of $c_i(t)$ into $b_i(t)$ can be thought of as a
-response values. In the grasshopper, these thresholding nonlinearities might
+categorization into "relevant" and "irrelevant" response values.
-either be part of the processing within the ascending neurons or take place
+% It is unclear whether such a thresholding nonlinearity is actually implemented
-further downstream~(SOURCE). Finally, the responses of the ascending neurons
+% either by the ascending neurons or at some point further downstream in the SEG.
-are assumed to be integrated somewhere in the supraesophageal
+Finally, the responses of the ascending neurons are assumed to be integrated
-ganglion~(\bcite{ronacher1986routes}; \bcite{bauer1987separate};
+somewhere in the SEG~(\bcite{ronacher1986routes}; \bcite{bauer1987separate};
 \bcite{bhavsar2017brain}). This processing step can be approximated as temporal
 averaging of the binary responses $b_i(t)$ by a lowpass filter
 \begin{equation}
@@ -752,26 +767,23 @@ array was moved as close to the grasshopper as possible without interrupting
 its song production, which amounts to an approximate offset distance of 10\,cm
 between the animal and the leading microphone. Care was taken to maintain a
 stable position and height of the microphone array during recording. The
-resulting recordings were then processed through the model pathway and analysed
+resulting recordings were then processed through the model pathway and analyzed
 according to the procedure described in Section~\ref{sec:intensity_measures}.
 \section{Results}
 \subsection{Mechanisms driving the emergence of intensity invariance}
-% Still missing the SNR analysis. Should be able to write around it for now.
+It is not necessary to test each processing step along the model pathway for
-The robustness of song recognition is tied to the degree of intensity
+intensity invariance. Instead, we can focus on those steps that involve
-invariance of the finalized feature representation. Ideally, the values of each
+nonlinear transformations, since these are the only steps that can potentially
-feature should depend only on the relative amplitude dynamics of the song
+change the dependency on scale $\sca$ between the input and output
-pattern but not on the overall intensity of the song. In the grasshopper, the
+representations. Overall, there are three nonlinear transformations along the
-emergence of intensity-invariant representations along the song recognition
+model pathway: Full-wave rectification during envelope extraction, logarithmic
-pathway likely is a distributed process that involves different neuronal
+compression, and the thresholding nonlinearity during feature extraction. In
-populations, which raises the question of what the essential computational
+the following, we analyze the effects of each of these transformations on the
-mechanisms are that drive this process. Within the model pathway, we identified
+intensity and SNR of the resulting representations as well as their potential
-two key mechanisms that render the song representation more invariant to
+contribution to intensity invariance.
 intensity variations. The two mechanisms each comprise a nonlinear signal
 transformation followed by a linear signal transformation but differ in the
 specific operations involved, as outlined in the following sections.
 \subsubsection{Full-wave rectification \& lowpass filtering}
--- a/python/save_figure_texts.py
+++ b/python/save_figure_texts.py
@@ -79,7 +79,7 @@ texts = {
    'model_titles_logarithm': ('Logarithmic\nCompression', title_props),
    'model_titles_adaptation': ('Intensity\nAdaptation', title_props),
    'model_titles_convolution': ('Convolutional\nFiltering', title_props),
-    'model_titles_nonlinear': ('Threshold\nNonlinearity', title_props),
+    'model_titles_nonlinear': ('Thresholding\nNonlinearity', title_props),
    'model_titles_integration': ('Temporal\nAveraging', title_props),
    'model_titles_readout': ('Weighted\nReadout', title_props),
@@ -94,7 +94,7 @@ texts = {
    # ELEMENT LABELS (MODEL CIRCUIT):
    'model_elements_filt': (r'$x_{\text{filt}}$', element_props),
    'model_elements_env': (r'$x_{\text{env}}$', element_props),
-    'model_elements_log': (r'$x_{\text{dB}}$', element_props),
+    'model_elements_log': (r'$x_{\text{log}}$', element_props),
    'model_elements_adapt': (r'$x_{\text{adapt}}$', element_props),
    'model_elements_c1': (r'$c_1$', element_props),
    'model_elements_c2': (r'$c_2$', element_props),
@@ -109,7 +109,7 @@ texts = {
    # LINE LABELS (MODEL CIRCUIT):
    'model_lines_env': (r'$\lvert\cdot\lvert,h_{\text{LP}}$', line_props),
-    'model_lines_log': (r'$\text{log}$', line_props),
+    'model_lines_log': (r'$\text{dB}$', line_props),
    'model_lines_hp': (r'$h_{\text{HP}}$', line_props),
    'model_lines_k1': (r'$k_1$', line_props),
    'model_lines_k2': (r'$k_2$', line_props),