Core Faculty Profile

Matthew Tresch

Assistant Professor, Joint appointment with
the Department of Physical Medicine and Rehabilitation
PhD, Neuroscience, Massachusetts Institute of Technology

Phone:  (312) 503-1373
E-mail: m-tresch@northwestern.edu

Research Interests

Research in our lab focuses on the mechanisms and strategies responsible for the coordination of movement by spinal motor systems. We examine these issues by using a range of neurophysiological, behavioral, and computational approaches, attempting to integrate between investigations across a number of different levels of analysis and obtain a holistic understanding of spinal cord function.

There are several reasons for why the spinal cord is an especially exciting model to examine basic issues of motor coordination. The most obvious and fundamental reason is its critical role in the production of movement. This importance is clear from the profound loss of function following spinal cord injury, and an important goal of our research is to provide information that might help guide rehabilitation and regeneration strategies. Second, spinal motor systems make significant contributions to the production of movement, and are not simple passive conduits of commands from higher brain areas. Finally, the spinal cord can be studied using a range of different experimental techniques and preparations. These include both in vitro preparations, allowing for detailed neurophysiological investigations, and in vivo preparations, allowing for investigations of higher level aspects of behavior.

It is our hope that by exploiting these advantages, we can come to a better understanding of the role of this critical structure within the neural control of movement, as well as providing insights into the more general process of motor coordination.

Current projects:

Are behaviors produced through the combination of muscle synergies?

Many investigators have proposed that movements might be produced through combinations of a small number of muscle groupings, or muscle synergies. We address this hypothesis using a set of novel computational tools, assessing the extent to which behaviors can be described in terms of such combinations. We are also currently performing neurophysiological experiments, using multi-unit and single unit recordings in rats and frogs to assess whether a signature of this organization can be observed in the details of spinal cord organization. Additional work aims at understanding the biomechanical function of these muscle groupings, investigating how they can be used to produce a range of behaviors, and how they relate to the details of the biomechanics of the limb.

The role of synchronization in spinal cord function

We have shown in previous experiments that motor units in developing animals are strongly synchronized during walking. We are currently examining the detailed patterns of synchronization between different muscles to assess whether it might play a role in establishing the patterns of muscle coordination seen in adult behaviors. We will also examine potential roles of synchronization directly, investigating whether manipulation of motor neuron synchronization can affect behaviors produced by spinal motor systems.

Neurophysiological substrates of motor coordination

We are also interested in understanding the neurophysiological implementation of motor coordination in the spinal cord. How do spinal interneuronal systems pool together the muscles in the appropriate balances and temporal sequences underlying basic behaviors? We are examining these questions by identifying spinal interneurons which might be involved in the coupling of different motor pools during behavior. These experiments involve intracellular and extracellular recordings of neurons in in vitro preparations during the production of behaviors, combined with anatomical and functional studies of these same neurons.

Selected Publications

1. Tresch, M.C., Saltiel P., and Bizzi E. (1999) The construction of movement by the spinal cord. Nature Neurosci., 2:162-167.

2. Tresch, M.C. and Kiehn O. (1999) The coding of the locomotor phase by neuronal populations in rostral and caudal spinal segments of the neonatal rat. J. Neurophys. 82: 3563-3574.

3. Tresch, M.C. and Kiehn O. (2000) Population reconstruction of the locomotor cycle from interneuron activity in the mammalian spinal cord. J. Neurophys. 83: 1972-1978.

4. Tresch, M.C. and Kiehn O. (2000) Motor coordination without action potentials in the mammalian spinal cord. Nature Neurosci. 3: 593-599.

5. Bizzi, E., Tresch MC, Saltiel P, and d'Avella A. (2000) New perspectives on spinal motor systems. Nat. Rev. Neurosci. 1:101-108.

6. d'Avella A. and Tresch M.C. (2002) Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies. In Advances in Neural Information Processing Systems 14, Dietterich T.G., Becker S., and Ghahramani Z. (eds.), MIT Press.

7. Kiehn O., and Tresch M.C. (2002) Gap junctions and motor behavior. Trends Neurosci. 25:108-115.

8. Tresch M.C. and Kiehn O. (2002) Synchronization of motor neurons during locomotion in the neonatal rat: predictors and mechanisms. J. Neurosci., 22:9997-10008.

9. Tresch M.C., Saltiel P., d'Avella A., and Bizzi E. (2002) Coordination and localization in spinal motor systems. Brain Res. Rev. 40:66-79.

10. Perrier J.-F. and Tresch, M.C. (2004) Recruitment of motor neuronal persistent inward currents shapes withdrawal reflexes in the frog. J Physiol. 562:507-20.

11. Richardson A., Slotine J.-J., Bizzi E., and Tresch M.C. (2005) Intrinsic musculoskeletal properties stabilize wiping movements in the spinalized frog. J. Neurosci 25:3181-3191.

12. Cheung V.C.K., d'Avella A., Tresch M.C., and Bizzi E. (2005) Central and sensory contributions to the activation and organization of muscle synergies during natural motor behaviors. J Neurosci. 25:6419-34.

13. Cheung V.C.K. and Tresch M.C. (2005) . Proc 27th IEEE Eng Med Biol Soc.

14. Tresch MC, Cheung VC, d'Avella A. (2006) Matrix factorization algorithms for the identification of muscle synergies: evaluation on simulated and experimental data sets. J Neurophysiol 95(4):2199-212