Overview: The Research Unit RobustCircuit
From Imprecision to Robustness in Neural Circuit Assembly
Why imprecision and robustness? The specificity of innumerable synaptic contacts is of central importance to the study of brain development and function. In contrast, terms like ‘imprecision’ and ‘noise’ are more commonly used in association with faulty development and reduced function. In most studies of neuronal development and function, imprecision only features as error bars and in the hope for significance between control and experimental averages. Yet, the development of neural circuits is in many aspects imprecise, and mature circuitry is often highly flexible and error-tolerant, i.e. robust.
The core hypothesis of RobustCircuit is that imprecisions of distinct processes at lower scales (from molecules to cells) enable robustness of circuit assembly and function at higher scales (from cells to behavior).
Our 13 research teams pursue this idea in eight projects, ranging from molecular to behavioral scales:
Our initiative is motivated by our common realization that imprecision in neural circuit assembly can play important roles for flexible development and robust function. Yet, studies on neural circuit assembly more often focus on the remarkable precision of connectivity, rather than the importance of its imprecision.
We want to understand when and how developmental imprecision can lead to robustness in the outcome.
Loss of robustness and increased variability play important, yet poorly understood roles in neural circuit wiring and consequently for brain function. Possible roles of noise range from irrelevant to necessary for robustness:
Why are some outcomes highly precise and others inherently variable, even if both encounter imprecision during development?
The RobustCircuit teams tackle this question using the fly’s neural circuitry as a model system. Advanced Drosophila tools and experimental advantages allow for the quantitative study of imprecisions on scales ranging from molecules to subcellular structures, neurons and circuits. At the same time, the system permits quantitative measurements of robust output at scales from cells to circuit function and behavior. However, the question of how precise or variable, robust and flexible neural circuits arise from imprecise assembly is not specific to Drosophila and has general relevance.
Why focus on live dynamics?
The RobustCircuit teams want to understand common principles underlying the requirements of imprecise processes at lower scales (from molecules to cells) to yield robust outcomes at higher scales (from cells to behavior) in neural circuit assembly. Live imaging is the principle means to obtain quantitative data on imprecise and robust processes at the levels of molecular, subcellular and cellular dynamics. Seven of the eight projects utilize intravital and ex vivo live imaging to obtain statistically powerful data on imprecisions, including noise, in subcellular dynamics. Based on such quantitative data, computational modeling allows one to make predictions for the roles imprecisions play in creating robust systems. The Z1 integration project is therefore designed to tackle the challenges resulting from our collaborative project design.