14
Mathematical Modeling of Brain Circuitry
during Cerebellar Movement Control*
Henrik Jörntell, Per-Ola Forsberg, Fredrik
Bengtsson, and Rolf Johansson
Lund University
Lund, Sweden
CONTENTS
14.1 Introduction ................................................................................................ 264
14.2 Problem Formulation................................................................................. 265
14.3 Materials and Methods.............................................................................. 266
14.4 Results .......................................................................................................... 266
14.4 Discussion ................................................................................................... 273
14.5 Conclusions ................................................................................................. 274
References ............................................................................................................. 275
Abstract
Reconstruction of movement control properties of the brain could result
in many potential advantages for application in robotics. However, a
hampering factor so far has been the lack of knowledge of the structure and function of brain circuitry in vivo during movement control.
Much more detailed information has recently become available for the
area of the cerebellum that controls arm–hand movements. In addition
to previously obtained extensive background knowledge of the overall
connectivity of the controlling neuronal network, recent studies have
provided detailed characterizations of local microcircuitry connectivity and physiology in vivo. In the present study, we study one component of this neuronal network, the cuneate nucleus, and characterize its
mathematical properties using system identification theory. The cuneate
nucleus is involved in the processing of the sensory feedback evoked by
movements. As a substrate for our work, we use a characterization of
* © 2009 IEEE. Reprinted, with permission, from Proceedings of the 2009 IEEE International
Conference on Robotics and Biomimetics (ROBIO2009), December 19–23, 2009, Guilin, China,
pp. 98–103.
263
Mathematical Modeling of Brain Circuitry
during Cerebellar Movement Control*
Henrik Jörntell, Per-Ola Forsberg, Fredrik
Bengtsson, and Rolf Johansson
Lund University
Lund, Sweden
CONTENTS
14.1 Introduction ................................................................................................ 264
14.2 Problem Formulation................................................................................. 265
14.3 Materials and Methods.............................................................................. 266
14.4 Results .......................................................................................................... 266
14.4 Discussion ................................................................................................... 273
14.5 Conclusions ................................................................................................. 274
References ............................................................................................................. 275
Abstract
Reconstruction of movement control properties of the brain could result
in many potential advantages for application in robotics. However, a
hampering factor so far has been the lack of knowledge of the structure and function of brain circuitry in vivo during movement control.
Much more detailed information has recently become available for the
area of the cerebellum that controls arm–hand movements. In addition
to previously obtained extensive background knowledge of the overall
connectivity of the controlling neuronal network, recent studies have
provided detailed characterizations of local microcircuitry connectivity and physiology in vivo. In the present study, we study one component of this neuronal network, the cuneate nucleus, and characterize its
mathematical properties using system identification theory. The cuneate
nucleus is involved in the processing of the sensory feedback evoked by
movements. As a substrate for our work, we use a characterization of
* © 2009 IEEE. Reprinted, with permission, from Proceedings of the 2009 IEEE International
Conference on Robotics and Biomimetics (ROBIO2009), December 19–23, 2009, Guilin, China,
pp. 98–103.
263