Schwach-nichtlineare Interaktionen in einem elektrosensorischen Cocktailparty-Problem

01/07/2020 to 30/06/2023

The cocktail party problem emphasizes the amazing capabilities of
the auditory system to separate one source of acoustic information
from many other jamming signals. Particularly challenging for neural
systems is the detection of faint signals close to threshold on a
background of much stronger distractors. We propose to study the
latter scenario both theoretically in populations of integrate-and-fire
neurons and electrophysiologically as well as behaviorally in the
active electrosensory system in two species of weakly electric fish. In
field studies we recently observed male fish attacking a distant
intruder while courting a close-by female. Here, the faint intruder
signal is detected despite the presence of the more than a thousand
fold stronger, ongoing female signal. The intruder and the female
signal are both periodic but differ in their frequency. In contrast to the
mammalian auditory system there are no frequency filter banks in the
peripheral electrosensory system and all signals are processed by the
same population of neurons. We hypothesize the enhancement of
neuronal responses through weakly nonlinear interactions with the
jamming signal, to be at the core of this impressive detection
performance. We propose to characterize possible nonlinear
interactions between two periodic signals in the first two stages of
electrosensory processing in the gymnotiform fish Apteronotus
leptorhynchus and A. albifrons. Guided by theoretical predictions we
quantify the responses evoked by combinations of frequencies in
electroreceptors and their targets, pyramidal cells that are organized
in three maps. Across these maps the pyramidal cells differ in their
cellular and functional properties and in their receptive field sizes.
This rich parameter space allows to compare several evolutionary
adaptations of a basic neural circuit design. In parallel we extend the
theory of weakly nonlinear interactions to leaky integrate-and-fire
neurons with adaptation currents. In addition we will consider the
more natural case of a non-static signals. The electroreceptor
population is heterogeneous with respect to baseline firing rates and
response variability. We explore how heterogeneity might be
opitmized for the representation of faint signals based on readout
strategies of target neurons using various signal detection
approaches. Additional operand conditioning experiments will quantify
detection thresholds and integration times in controlled lab conditions
and will provide important benchmarks for both the theoretical and
electrophysiological work. Our work will provide solid and fundamental
insights as to how weakly nonlinear interactions are involved in
encoding faint signals in the presence of strong jamming stimuli. We
will understand how evolutionary adaptations of a convergent network
of neurons provide the basis for solving this difficult cocktail party
problem.