MoCoTi - Motor Control and Timing in the Cerebellum: Spatio-Temporal Integration in Complex Neuronal Networks

 

About MoCoti

 

Thanks to the ever improving temporal and spatial resolution of modern functional brain imaging techniques there is a growing body of experimental data relating different temporal tasks like sensory motor synchronization (SMS) or interval estimation (IE) to specific brain regions. For IE and SMS the two main important regions are the cerebellum and the striatum, respectively [1]. Unfortunately, functional imaging cannot help to elucidate on the way in which clocking signals are created by those regions, let alone the way in which they are integrated into our thoughts, emotions, and actions.

Lesion studies and functional imaging both find the cerebellum to play a key role in human timing, especially for sub-second time intervals. The cerebellum connects our brain to our mechanical periphery, which is inherently linked to the physical world via its mass, its inertia; but how does the cerebellum measure time? Is it deterministically driven by internal oscillators like a quartz clock? Or are our limbs to the cerebellum what a pendulum is to a mechanical clock? Does the cerebellum need that mechanical feedback loop as a driver, for intermittent calibration, or not at all? What in the end does it take to estimate time intervals or tap your toe to a beat?

These are questions we are addressing with theoretical analysis and simulations on the SpiNNaker [2] platform. We are starting from a bare bones model of cerebellar micro-zones [3] connected to robotic limbs [4]. We will augment and extend our model step-by-step and thereby thoroughly test its temporal features and characteristics at each stage. With our bottom-up approach of building relevant circuitry piece-by-piece, we hope to identify the essential ingredients for different aspects of time in the cerebellum.

 

Principal Investigators

Jörg Conradt (TUM)

Research Interests

  • Neuronal-Style Information Processing in Closed-Control-Loop Systems
  • Event Based Neuromorphic Vision
  • Self-Construction and Organization of Neuronal Circuits
  • Information Processing in Distributed Neuronal Circuits
  • Neuromorphic Real-Time Computing and Control

 

Florian Röhrbein (TUM)

Florian Röhrbein is senior lecturer at the research group “Robotics and Embedded Systems” in TUM’s Informatics Department. He is managing director of the Neurorobotics subproject of the Human Brain Project flagship. He has international work experience in various projects on brain-inspired cognitive systems. Research stays include the MacKay Institute of Communication and Neuroscience (UK), the HONDA Research Institute Europe (Germany) and the Albert Einstein College of Medicine (New York). He received his Diploma (with honors) and PhD (magna cum laude) from TU München. In 2011 he received the venia legendi for computer science from Universität Bremen.

 

Christoph Richter (TUM)

Research Interests

  • Distributed and adaptive information processing
  • Neuromorphic hardware, sensors and computing
  • Electronic devices and computing architectures for the post-Moore era

 

References

[1]: Teki, S., Grube, M., Kumar, S., and Griffiths, T. (2011) "Distinct Neural Substrates of Duration-Based and Beat-Based Auditory Timing". The Journal of Neuroscience, 31(10): 3805-3812.
[2]: Furber, S., Galluppi, F., Temple, S., and Plana, L. (2014), "The SpiNNaker Project". The Proceedings of the IEEE 102(5): 652-665.
[3]: Carrillo, R.C., Ros, E., Boucheny, C., Coenen O. (2008), "A real-time spiking cerebellum model for learning robot control". BioSystems 94, 18-27
[4]: Marques, H.M., et al., and MYOROBOTICS Project Team, (2013) "MYOROBOTICS: a modular toolkit for legged locomotion research using musculoskeletal designs". In Proc. 6th International Symposium on Adaptive Motion of Animals and Machines (AMAM'13).