Project Details
Projekt
Robust network states from variable ion channel composition and connectivity: a mathematical approach in a Drosophila motocircuit
Applicant
Professorin Dr. Susanne Schreiber
Subject Area
Experimental and Theoretical Network Neuroscience
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 453877723
Motor control of complex behavior relies on the generation of specific activation patterns in specialized neuronal circuits. Mature motocircuits, therefore, require a well-orchestrated combination of intrinsic neuronal properties, such as morphology, ion channel composition, and network structure. In some cases, precision of these properties can be important for function, although variability in circuit components is tolerated to some extent. In other cases, variability of intrinsic neuronal properties or circuit components may be advantageous in the context of trade-offs (like the cost required for more precision) or in fact be directly beneficial for robust circuit function. The goal of P7 is to distinguish between these possibilities within the framework of a simple central pattern generator that provides data constraints and testability of a computational modeling approach (together with P6). Specifically, we seek to understand how imprecisions in the development of the central pattern generator underlying fly wing beat oscillation (at the levels of intrinsic properties of the constituent neurons as well as network connectivity) affect the robust function of the mature circuit. In preliminary experiments for RobustCircuit we have identified specific instances for each of the two beneficial roles for variability of intrinsic neuronal properties or circuit components: (i) we hypothesize that imprecise neuronal function (based on ion channel noise) benefits re-establishment of a preferred network mode after perturbation, and (ii) we hypothesize that developmental imprecisions (including gap junctions between motoneurons) facilitate the self-organization of robust network motifs by lowering the ‘regulatory cost’ compared to a more precise genetic specification. Taken together, this project aims to uncover beneficial roles of variability based on mechanistic principles that are likely to generalize beyond the system at hand.
DFG Programme
Research Units
