j_hartling/paper_2025
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Syncing to work.

Browse Source
This commit is contained in:
j-hartling
2026-05-25 22:10:33 +02:00
parent 2b0978ac32
commit 6cd56b82b0
2 changed files with 21 additions and 38 deletions
Download Patch File Download Diff File Expand all files Collapse all files

59
main.tex
View File

@@ -1542,45 +1542,28 @@ acoustic environment.
Our understanding of sensory processing systems is based on the distributed
accumulation of anatomical, physiological, and ethological evidence. Functional
modelling provides a powerful tool to integrate the available knowledge
fragments into a coherent whole, which greatly fasciliates systematic
investigations and allows us to address questions of increasingly broader
scope. For instance, we were able to investigate the interaction between the
two mechanisms of intensity invariance because we can relate the output of the
first mechanism to the input of the second mechanism, which would not be
possible if both are treated as separate entities. We can also use the model
pathway as a general basis for comparing song representations across different
species without building a specific model for each species. However, the
potential of a functional modelling approach also depends directly on the
amount of available knowledge on the sensory system and the stimuli it operates
on. The grasshopper auditory system is a comparably simple and well-understood
system and is therefore a particularly suitable candidate for functional
modelling.
modelling provides a powerful tool to integrate the available fragments into a
coherent whole. It fasciliates systematic, reproducible investigations of
relevant parameters such as scale $\sca$ or threshold value $\thr$. Moreover,
it allows to address questions of broader scope by generalizing from concrete
evidence. For instance, the interaction between the two mechanisms of intensity
invariance is most assessible if both mechanisms can be treated as consecutive
stages along the pathway --- where the output of the first stage relates
directly to the input of the second stage --- rather than separate entities.
The model pathway also provides a general basis for comparing song
representations across different species without the need for species-specific
models. However, the potential of functional modelling for research on sensory
systems depends entirely on the amount of available knowledge about the system.
The grasshopper song recognition pathway is a comparably simple and very
well-understood system and is therefore a particularly suitable candidate for
functional modelling. Other sensory systems that are either more complex or
have not been subject to decades of study will likely not be suitable for this
approach yet.
that has been studied extensively over the past decades. This makes it
a particularly suitable candidate for functional modelling.
functional
modelling is not without limitations.
However, building a
framework that captures the essential functional aspects of a sensory system is
a challenging task.
It requires comprehensive information on the system and the
stimuli it operates on as well as careful abstraction of the underlying
structures and mechanisms. The grasshopper auditory system is a comparably
simple, well-understood system that has been studied extensively over the past
decades.
and is therefore a
particularly suitable candidate for functional modelling. Many other sensory
systems
\textbf{Song recognition pathway: Grasshopper vs. model:}\\
The model pathway includes a rather large number of Gabor kernels compared to
the 15 to 20 ascending neurons in the grasshopper auditory
system~(\bcite{stumpner1991auditory}).
% \textbf{Song recognition pathway: Grasshopper vs. model:}\\
% The model pathway includes a rather large number of Gabor kernels compared to
% the 15 to 20 ascending neurons in the grasshopper auditory
% system~(\bcite{stumpner1991auditory}).
\subsection{Interplay of song representation and song design}