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Added some (older) papers on neuronal types, structure, and connectivity to the literature archive.

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Expanded cite.bib accordingly.
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2025-12-11 11:30:10 +01:00
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@@ -134,6 +134,25 @@ $\rightarrow$ More general, simpler, unfitted formalized Gabor filter bank
\section{Developing a functional model of\\the grasshopper auditory pathway}
The auditory pathway of grasshoppers comprises a number of neuronal stages and
identified cell types~(\bcite{rehbein1974structure}; \bcite{rehbein1976auditory}).
Along the auditory pathway of grasshoppers (Fig.\,\ref{fig:pathway}a+b),
1) "Pre-split portion" of the auditory pathway:\\
Tympanal membrane $\rightarrow$ Receptor neurons $\rightarrow$ Local interneurons
Similar response/filter properties within receptor/interneuron populations (\cite{clemens2011efficient})\\
$\rightarrow$ One population-wide response trace per stage (no "single-cell resolution")
2) "Post-split portion" of the auditory pathway:\\
Ascending neurons (AN) $\rightarrow$ Central brain neurons
Diverse response/filter properties within AN population (\cite{clemens2011efficient})\\
- Pathway splitting into several parallel branches\\
- Expansion into a decorrelated higher-dimensional sound representation\\
$\rightarrow$ Individual neuron-specific response traces from this stage onwards
\begin{figure}[!ht]
\centering
\def\svgwidth{\textwidth}
@@ -148,9 +167,9 @@ $\rightarrow$ More general, simpler, unfitted formalized Gabor filter bank
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
mechanical resonance filter, that focuses vibrations of specific frequencies on
different membrane areas while attenuating
others~(\bcite{michelsen1971frequency}; \bcite{windmill2008time};
mechanical resonance filter: Vibrations that fall within specific frequency
bands are focused on different membrane areas, while others are
attenuated~(\bcite{michelsen1971frequency}; \bcite{windmill2008time};
\bcite{malkin2014energy}). This processing step can be approximated by an
initial bandpass filter
\begin{equation}
@@ -158,10 +177,10 @@ initial bandpass filter
\label{eq:bandpass}
\end{equation}
applied to the acoustic input signal $\raw(t)$. The auditory receptor neurons
connect directly to the tympanal membrane. Besides performing the
mechano-electrical transduction, the receptor population further is substrate
to several known processing steps. First, the receptors extract the signal
envelope~(\bcite{machens2001discrimination}), which likely involves a
connect directly to the tympanal membrane~(Fig.\,\ref{fig:pathway}a). Besides
performing the mechano-electrical transduction, the receptor population is
substrate to several known processing steps. First, the receptors extract the
signal envelope~(\bcite{machens2001discrimination}), which likely involves a
rectifying nonlinearity~(\bcite{machens2001representation}). This can be
modelled as full-wave rectification followed by lowpass filtering
\begin{equation}
@@ -177,52 +196,25 @@ logarithmic compression is achieved by conversion to decibel scale
\label{eq:log}
\end{equation}
relative to the maximum intensity $\dbref$ of the signal envelope $\env(t)$.
The axons of the receptor neurons project into the metathoracic ganglion, where
they synapse onto local interneurons~(Fig.\,\ref{fig:pathway}b). Both the local
interneurons~(\bcite{hildebrandt2009origin}; \bcite{clemens2010intensity}) and,
to a lesser extent, the receptors themselves~(\bcite{fisch2012channel}) display
spike-frequency adaptation in response to sustained stimulation.
This behavior is crucial to render subsequent signal representations invariant
to variations in sound intensity.
"Pre-split portion" of the auditory pathway:\\
Tympanal membrane $\rightarrow$ Receptor neurons $\rightarrow$ Local interneurons
Similar response/filter properties within receptor/interneuron populations (\cite{clemens2011efficient})\\
$\rightarrow$ One population-wide response trace per stage (no "single-cell resolution")
\textbf{Stage-specific processing steps and functional approximations:}
Initial: Continuous acoustic input signal $x(t)$
Filtering of behaviorally relevant frequencies by tympanal membrane\\
$\rightarrow$ Bandpass filter 5-30 kHz
Extraction of signal envelope (AM encoding) by receptor population\\
$\rightarrow$ Full-wave rectification, then lowpass filter 500 Hz
Logarithmically compressed intensity tuning curve of receptors\\
$\rightarrow$ Decibel transformation
Spike-frequency adaptation in receptor and interneuron populations\\
$\rightarrow$ Highpass filter 10 Hz
%
Next, the axons of the receptor neurons project into the metathoracic ganglion,
where they synapse onto local interneurons~(Fig.\,\ref{fig:pathway}b). Both the
local interneurons~(\bcite{hildebrandt2009origin};
\bcite{clemens2010intensity}) and, to a lesser extent, the receptors
themselves~(\bcite{fisch2012channel}) display spike-frequency adaptation in
response to sustained stimulus intensity levels. This mechanism allows for the
robust encoding of faster amplitude modulations against a slowly changing
overall baseline intensity. Functionally, this processing step resembles a
highpass filter
\begin{equation}
\adapt(t)\,=\,\db(t)\,*\,\hp, \qquad \fc\,=\,10\,\text{Hz}
\label{eq:highpass}
\end{equation}
%
over the logarithmically scaled envelope $\db(t)$. The projections of the local
interneurons remain within the metathoracic ganglion and synapse onto a small
number of ascending neurons~(Fig.\,\ref{fig:pathway}b).
\subsection{Feature extraction by individual neurons}
"Post-split portion" of the auditory pathway:\\
Ascending neurons (AN) $\rightarrow$ Central brain neurons
Diverse response/filter properties within AN population (\cite{clemens2011efficient})\\
- Pathway splitting into several parallel branches\\
- Expansion into a decorrelated higher-dimensional sound representation\\
$\rightarrow$ Individual neuron-specific response traces from this stage onwards
\textbf{Stage-specific processing steps and functional approximations:}
Template matching by individual ANs\\
@@ -267,6 +259,20 @@ $\rightarrow$ Lowpass filter 1 Hz
%
\section{Two mechanisms driving the emergence of intensity-invariant song representation}
\textbf{Definition of invariance (general, systemic):}\\
Invariance = Property of a system to maintain a stable output with respect to a
set of relevant input parameters (variation to be represented) but irrespective
of one or more other parameters (variation to be discarded)
$\rightarrow$ Selective input-output decorrelation
\textbf{Definition of intensity invariance (context of neurons and songs):}\\
Intensity invariance = Time scale-selective sensitivity to certain faster
amplitude dynamics (song waveform, small-scale AM) and simultaneous
insensitivity to slower, more sustained amplitude dynamics (transient baseline,
large-scale AM, current overall intensity level)\\
$\rightarrow$ Without time scale selectivity, any fully intensity-invariant
output will be a flat line
\subsection{Logarithmic scaling \& spike-frequency adaptation}
Envelope $\env(t)$ $\xrightarrow{\text{dB}}$ Logarithmic $\db(t)$ $\xrightarrow{\hp}$ Adapted $\adapt(t)$