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