Biology subjects

Seidenbecher, S. E.

Publications and source records attributed to Seidenbecher, S. E..

2 recordsLinked to original sources

bioRxiv2023

Altered reactivity to threatening stimuli in Drosophila models of Parkinson's disease, revealed by a trial-based assay

The fruit fly Drosophila melanogaster emerges as an affordable, genetically tractable model of behavior and brain diseases. However, despite the surprising level of evolutionary conservation from flies to humans, significant genetic, circuit-level and behavioral differences hinder the interpretability of fruit fly models for human disease. Therefore, to allow a more direct fly-versus-human comparison, we surveyed the rarely exploited, rich behavioral repertoire of fruit flies with genetic alterations relevant to Parkinsons disease (PD), including overexpression of human mutant Parkin or -synuclein proteins and mutations in dopamine receptors. Flies with different genetic backgrounds displayed variable behaviors, including freezing, slowing and running, in response to predator-mimicking passing shadows used as threatening stimuli in a single-animal trial-based assay. We found that the expression of human mutant Parkin in flies resulted in reduced walking speed and decreased reactivity to passing shadows. Flies with dopamine receptor mutations showed similar alterations, consistent with the motor and cognitive deficits typical in humans with PD. We also found age-dependent trends in behavioral choice during the fly lifespan, while dopamine receptor mutant flies maintained their decreased general reactivity throughout all age groups. Our data demonstrate that single-trial behavioral analysis can reveal subtle behavioral changes in mutant flies that can be used to further our understanding of disease pathomechanisms and help gauge the validity of genetic Drosophila models of neurodegeneration, taking us one step closer to bridging the gap in fly-to-human translation.

neuroscience↗

bioRxiv2019

Foraging fruit flies mix navigational and learning-based decision-making strategies

Animals often navigate environments that are uncertain, volatile and complex, making it challenging to locate reliable food sources. Therefore, it is not surprising that many species evolved multiple, parallel and complementary foraging strategies to survive. Current research on animal behavior is largely driven by a reductionist approach and attempts to study one particular aspect of behavior in isolation. This is justified by the huge success of past and current research in understanding neural circuit mechanisms of behaviors. But focusing on only one aspect of behaviors obscures their inherent multidimensional nature. To fill this gap we aimed to identify and characterize distinct behavioral modules using a simple reward foraging assay. For this we developed a single-animal, trial-based probabilistic foraging task, where freely walking fruit flies experience optogenetic sugar-receptor neuron stimulation. By carefully analyzing the walking trajectories of flies, we were able to dissect the animals foraging decisions into multiple underlying systems. We show that flies perform local searches, cue-based navigation and learn task relevant contingencies. Using probabilistic reward delivery allowed us to bid several competing reinforcement learning (RL) models against each other. We discover that flies accumulate chosen option values, forget unchosen option values and seek novelty. We further show that distinct behavioral modules -learning and navigation-based systems-cooperate, suggesting that reinforcement learning in flies operates on dimensionality reduced representations. We therefore argue that animals will apply combinations of multiple behavioral strategies to generate foraging decisions.

neuroscience↗