First methods paragraph (WIP).

main.tex

@@ -109,11 +109,11 @@ conspicuous acoustic signals of grasshoppers are their species-specific calling
 songs, which broadcast the presence of the singing individual --- mostly the
 males of the species --- to potential mates within range. These songs are
 usually more characteristic of a species than morphological
-traits~(\bcite{tishechkin2016acoustic}, \bcite{tarasova2021eurasius}), which
-can vary greatly within species~(\bcite{rowell1972variable},
+traits~(\bcite{tishechkin2016acoustic}; \bcite{tarasova2021eurasius}), which
+can vary greatly within species~(\bcite{rowell1972variable};
 \bcite{kohler2017morphological}). The reliance on songs to mediate reproduction
 represents a strong evolutionary driving force, that resulted in a massive
-species diversification~(\bcite{vedenina2011speciation},
+species diversification~(\bcite{vedenina2011speciation};
 \bcite{sevastianov2023evolution}), with over 6800 recognized grasshopper
 species in the \textit{Acrididae} family~(\bcite{cigliano2024orthoptera}). It
 is this diversity of species, and the crucial role of acoustic communication in
@@ -122,7 +122,7 @@ candidate for attempting to construct a functional model framework. As a
 necessary reduction, the model we propose here focuses on the pathway
 responsible for the recognition of species-specific calling songs, disregarding
 other essential auditory functions such as directional
-hearing~(\bcite{helversen1984parallel}, \bcite{ronacher1986routes},
+hearing~(\bcite{helversen1984parallel}; \bcite{ronacher1986routes};
 \bcite{helversen1988interaural}).
 
 % What are the signals the auditory system is supposed to recognize?
@@ -133,7 +133,7 @@ system, one has to understand the properties of the songs it is designed to
 recognize. Grasshopper songs are amplitude-modulated broad-band acoustic
 signals. Most songs are produced by stridulation, during which the animal pulls
 the serrated stridulatory file on its hindlegs across a resonating vein on the
-forewings~(\bcite{helversen1977stridulatory}, \bcite{stumpner1994song},
+forewings~(\bcite{helversen1977stridulatory}; \bcite{stumpner1994song};
 \bcite{helversen1997recognition}). Every tooth that strikes the vein generates
 a brief pulse of sound. Multiple pulses make up a syllable; and the alternation
 of syllables and relatively quiet pauses forms a characteristic, through noisy,
@@ -141,7 +141,7 @@ waveform pattern. Song recognition depends on certain temporal and structural
 parameters of this pattern, such as the duration of syllables and
 pauses~(\bcite{helversen1972gesang}), the slope of pulse
 onsets~(\bcite{helversen1993absolute}), and the accentuation of syllable onsets
-relative to the preceeding pause~(\bcite{balakrishnan2001song},
+relative to the preceeding pause~(\bcite{balakrishnan2001song};
 \bcite{helversen2004acoustic}). The amplitude modulation, or envelope, of the
 song is sufficient for recognition~(\bcite{helversen1997recognition}). However,
 the essential recognition cues can vary considerably with external physical
@@ -150,7 +150,7 @@ in order to reliably recognize songs under different conditions. For instance,
 the temporal structure of grasshopper songs warps with
 temperature~(\bcite{skovmand1983song}). The auditory system can compensate for
 this variability by reading out relative temporal relationships rather than
-absolute time intervals~(\bcite{creutzig2009timescale},
+absolute time intervals~(\bcite{creutzig2009timescale};
 \bcite{creutzig2010timescale}), as those remain relatively constant across
 different temperatures~(\bcite{helversen1972gesang}). Another, perhaps even
 more fundamental external source of song variability lays in the attenuation of
@@ -167,13 +167,13 @@ This neccessitates that the auditory system achieves a certain degree of
 intensity invariance --- a time scale-selective sensitivity to faster amplitude
 dynamics and simultaneous insensitivity to slower, more sustained amplitude
 dynamics. Intensity invariance in different auditory systems is often
-associated with neuronal adaptation~(\bcite{benda2008spike},
-\bcite{barbour2011intensity}, \bcite{ozeri2018fast}, more
+associated with neuronal adaptation~(\bcite{benda2008spike};
+\bcite{barbour2011intensity}; \bcite{ozeri2018fast}; more
 general:~\bcite{benda2021neural}). In the grasshopper auditory system, a number
 of neuron types along the processing chain exhibit spike-frequency adaptation
 in response to sustained stimulus
-intensities~(\bcite{romer1976informationsverarbeitung},
-\bcite{gollisch2002energy}, \bcite{hildebrandt2009origin},
+intensities~(\bcite{romer1976informationsverarbeitung};
+\bcite{gollisch2002energy}; \bcite{hildebrandt2009origin};
 \bcite{clemens2010intensity}) and thus likely contribute to the emergence of
 intensity-invariant song representations. This means that intensity invariance
 is not the result of a single processing step but rather a gradual process, in
@@ -196,8 +196,8 @@ informative features of the song pattern and then integrate the gathered
 information into a final categorical percept. Previous authors have proposed a
 functional model framework that describes this process --- feature extraction,
 evidence accumulation, and categorical decision making --- in both
-crickets~(\bcite{clemens2013computational}, \bcite{hennig2014time}) and
-grasshoppers~(\bcite{clemens2013feature}, review on
+crickets~(\bcite{clemens2013computational}; \bcite{hennig2014time}) and
+grasshoppers~(\bcite{clemens2013feature}; review on
 both:~\bcite{ronacher2015computational}). Their framework provides a
 comprehensible and biologically plausible account of the computational
 mechanisms required for species-specific song recognition, which has served as
@@ -219,7 +219,7 @@ larger, generic set of unfitted Gabor basis functions in order to cover a wide
 range of possible song features across different species. Gabor functions
 approximate the general structure of the filters used in the existing framework
 as well as the filter functions found in various auditory
-neurons~(\bcite{rokem2006spike}, \bcite{clemens2011efficient},
+neurons~(\bcite{rokem2006spike}; \bcite{clemens2011efficient};
 \bcite{clemens2012nonlinear}). The fitted sigmoidal nonlinearities in the
 existing framework consistently exhibited very steep slopes and are therefore
 replaced by shifted Heaviside step-functions, which results in a binarization
@@ -233,23 +233,23 @@ after a certain delay following the onset of a song, which emphasizes the
 temporal dynamics of evidence accumulation towards a final categorical
 decision. The most notable difference between our model pathway and the
 existing framework, however, lays in the addition of a physiologically inspired
-preprocessing portion, whose starting point corresponds to the initial
-reception of airborne sound waves. This allows the model to operate on
-unmodified recordings of natural grasshopper songs instead of condensed pulse
-train approximations, which widens its scope towards more realistic,
-ecologically relevant scenarios. For instance, we were able to investigate the
-contribution of different processing stages to the emergence of
-intensity-invariant song representations based on actual field recordings of
-songs at different distances from the sender.
+preprocessing stage, whose starting point corresponds to the initial reception
+of airborne sound waves. This allows the model to operate on unmodified
+recordings of natural grasshopper songs instead of condensed pulse train
+approximations, which widens its scope towards more realistic, ecologically
+relevant scenarios. For instance, we were able to investigate the contribution
+of different processing stages to the emergence of intensity-invariant song
+representations based on actual field recordings of songs at different
+distances from the sender.
 % Forgive me, it's friday.
 In the following, we outline the structure of the proposed model of the
-grasshopper auditory pathway, from the initial sound reception at the tympanal
-membrane up to the generation of a high-dimensional, time-varying feature
-representation that is suitable for species-specific song recognition. We
-provide a side-by-side account of the known physiological processing steps and
-their functional approximation by basic mathematical operations. We then
-elaborate on two key mechanisms that drive the emergence of intensity-invariant
-song representations within the auditory pathway.
+grasshopper auditory pathway, from the initial reception of sound waves up to
+the generation of a high-dimensional, time-varying feature representation that
+is suitable for species-specific song recognition. We provide a side-by-side
+account of the known physiological processing steps and their functional
+approximation by basic mathematical operations. We then elaborate on two key
+mechanisms that drive the emergence of intensity-invariant song representations
+within the auditory pathway.
 
 % SCRAPPED UNTIL FURTHER NOTICE:
 % Multi-species, multi-individual communally inhabited environments\\
@@ -280,30 +280,38 @@ song representations within the auditory pathway.
 % - How to integrate the available knowledge on anatomy, physiology, ethology?\\
 % $\rightarrow$ Abstract, simplify, formalize $\rightarrow$ Functional model framework
 
-\section{Developing a functional model of\\the grasshopper auditory pathway}
+\section{Developing a functional model of the\\grasshopper song recognition pathway}
 
-% Either pick up in intro and/or discussion, or move entirely:
-The grasshopper auditory system has been studied extensively over the past
-decades; and a corresponding number of involved neuron types has been
-described~(\bcite{rehbein1974structure}; \bcite{kalmring1975afferent};
-\bcite{rehbein1976auditory}; \bcite{eichendorf1980projections}). The functional
-model we propose here focuses on the pathway responsible for song recognition
-and assumes a strict feed-forward organization of three consecutive neuronal
-populations: Peripheral auditory receptor neurons~\mbox{(1st order)}, local
-interneurons of the metathoracic ganglion~\mbox{(2nd order)}, and ascending
-neurons~\mbox{(3rd order)} projecting towards the supraesophageal ganglion.
+The essence of constructing a functional model of a sensory processing system
+is to gain a sufficient understanding of the system's essential structural
+components and the functional roles they might fulfill; and to then build a
+formal framework of manageable complexity around these two aspects.
+Anatomically, the organization of the grasshopper song recognition pathway can
+be outlined as a hierarchical feed-forward network of three consecutive
+neuronal populations~(Fig.\,\ref{fig:pathway}a-c): Peripheral auditory receptor
+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 from
 
-Previous authors have reported a marked increase in response heterogenity
-within the population of ascending neurons compared to receptors and local
-interneurons, which exhibit almost identical filter characteristics,
-respectively~(\bcite{clemens2011efficient}). Based on these findings, the model
-pathway can be divided into two distinct portions~(Fig.\,\ref{fig:pathway}c+d).
-In the preprocessing portion, generated 
 
-The preprocessing portion comprises the tympanal membrane, receptors, and
-local interneurons. The different signal representations 
 
-Due to the similar response properties within the involved
+The input to the network originates from
+sound-induced vibrations of the tympanal membrane on each side of the thorax,
+which are transduced into electro-chemical signals by the receptor neurons. The
+output from the network converges somewhere in the supraesophageal ganglion,
+where the recognition of conspecific songs is presumed to take
+place~(\bcite{romer1985responses}; \bcite{ronacher1986routes};
+\bcite{bauer1987separate}; \bcite{bhavsar2017brain}). Functionally, the
+ascending neuron population is characterized by a marked increase in response
+heterogenity compared to the preceding receptor neurons and local interneurons,
+which exhibit relatively homogeneous response properties across their
+respective populations~(\bcite{clemens2011efficient}). Based on these
+considerations, the organisation of the model
+pathway~(Fig.\,\ref{fig:pathway}d) comprises two distinct overall stages:
+
 
 
 1) "Pre-split portion" of the auditory pathway:\\
@@ -324,13 +332,26 @@ $\rightarrow$ Individual neuron-specific response traces from this stage onwards
     \centering
     \def\svgwidth{\textwidth}
     \import{figures/}{fig_auditory_pathway.pdf_tex}
-    \caption[Grasshopper auditory system]{\textbf{The auditory system of
-    grasshoppers.}}
+    \caption{\textbf{Schematic organisation of the song recognition pathway in
+                     grasshoppers compared to the structure of the model pathway.}
+                     \textbf{a}:~Course of the pathway in the grasshopper, from
+                     the tympanal membrane over receptor neurons (1st order),
+                     local interneurons (2nd order) of the metathoracic
+                     ganglion, and ascending neurons (3rd order) further
+                     towards the central brain.
+                     \textbf{b}:~Connections between the three neuronal
+                     populations within the metathoracic ganglion.
+                     \textbf{c}:~Network representation of neuronal connectivity.
+                     \textbf{d}:~Flow diagram of the different signal
+                     representations (boxes) and transformations (arrows) along
+                     the model pathway. The pathway consists of a
+                     population-wide preprocessing stream followed by several
+                     parallel feature extraction streams.
+                     }
     \label{fig:pathway}
 \end{figure}
-\FloatBarrier
 
-\subsection{Population-driven signal pre-processing}
+\subsection{Population-driven signal preprocessing}
 
 Grasshoppers receive airborne sound waves by a tympanal organ at each side of
 the thorax~(Fig.\,\ref{fig:pathway}a). The tympanal membrane acts as a