The Zimmer Lab

Prof. Manuel Zimmer

Head of Department

Division Neural Network Dynamics and Behaviour

Data sharing
Code sharing

In the Zimmer lab, we are interested in how neural network dynamics in the brain represent sensory information and perform computations to generate decisions and subsequent behaviors. Moreover, we aim to explain fundamental properties of neuronal circuits, for example the need to sleep. 

These are key problems in neuroscience, each of which have alone challenged worldwide communities of experts for decades. We, however, propose that a holistic approach should be undertaken to understand these functions in their full context. To make this goal achievable, we take advantage of the uniquely experimentally tractable model organism C. elegans, a 1mm long nematode worm that can be found dwelling in soil. C. elegans has a small nervous system of only 302 neurons with a completely mapped connectivity map. Nevertheless, it can produce sophisticated behaviors. In recent years, we developed new approaches to quantify C. elegans behavior in unprecedented detail and to record the activity of all neurons simultaneously in real time. These new technologies, together with the rich and efficient genetic toolkit available for the worm, will allow the first complete understanding of any nervous system’s operational principles. In the long term our holistic approach will enable us to generate a realistic in silico simulation of the brain’s properties and behaviors. We will provide a basic proof of principle working model to guide the study of higher nervous systems and the design of brain inspired computational devices.

Research Interests


Neuronal population dynamics in C. elegans orchestrate hierarchies of motor actions
From connectome to function: connectivity features underlying neuronal population dynamics
Functions of brain wide motor representations
Control of sleep and wakefulness
Quantitative behavior

Current and Future Research

In our current and future work, we combine advanced microscopy techniques for whole brain and whole nervous system imaging with quantitative behavior, molecular genetics and computational neuroscience. Our research objectives remain focused on brain dynamics crucial for nervous system function. We aim to understand the information flow from sensory inputs via decision making to behavioral output, and why these processing stages occur in such a distributed (as opposed to sequential) manner. We also aim to solve why such a system requires a sleep-wake cycle. Finally, our findings will be recapitulated in a realistic in silico simulation of brain dynamics and behavior. This holistic approach will enable us for the first time to understand the operational principles of the worm’s nervous system, which we propose are generalizable to larger animals. We are focusing on a few major objectives:

  • To develop new light-sheet microscopy approaches for whole nervous system imaging in freely behaving worms.
  • Using whole brain imaging combined with complex sensory stimulation protocols, we are studying how sensory circuits represent features of the environment and interact with brain dynamics to control behavior. This approach will uncover the neural basis of computations and decision making as well as all functions of brain wide motor representations.
  • Using graph theory, we are analyzing the worm’s connectome to inform targeted circuit manipulations of its nervous system. Here we aim to further uncover the crucial features in anatomical wiring architecture that serve neuronal function.
  • While neuronal population dynamics in worms represent a global framework for long timescale action sequences, it remains to be addressed how these action commands are transformed into individual actions and movement patterns at the motor periphery. 
  • How are whole brain dynamics affected by sleep deprivation and subsequent rebound sleep? Studying sleep homeostasis will shed light on a major mystery: why do animals need to sleep?
  • We will reverse engineer the brain in a faithful comprehensive network simulation; the first one available for any complete nervous system. In collaboration with computer scientists, we will leverage this computational platform to design novel brain inspired robotics algorithms and devices.