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Mathematical Modeling of Brain Circuitry during Cerebellar Movement Control

Jörntell, Henrik LU ; Forsberg, Per-Ola LU ; Bengtsson, Fredrik LU and Johansson, Rolf LU (2009) 2009 IEEE International Conference on Robotics and Biomimetics In [Host publication title missing] p.98-103
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... (More)
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 incoming and outgoing signals of individual neurons during sensory activation as well as a recently obtained microcircuitry characterization for this structure. We find that system identification is a useful way to find suitable mathematical models that capture the properties and transformation capabilities of the neuronal microcircuitry that constitute the cuneate nucleus. Future work will show whether specific aspects of the mathematical properties can be ascribed to a specific microcircuitry and/or neuronal property. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
pages
98 - 103
conference name
2009 IEEE International Conference on Robotics and Biomimetics
external identifiers
  • WOS:000285530500017
  • Scopus:77951478439
DOI
10.1109/ROBIO.2009.5420640
project
LCCC
Cerebellum
language
English
LU publication?
yes
id
25268fd4-4be1-420a-80a4-e59ffeacf439 (old id 1627104)
date added to LUP
2010-07-05 10:00:08
date last changed
2017-01-01 08:16:37
@inproceedings{25268fd4-4be1-420a-80a4-e59ffeacf439,
  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 incoming and outgoing signals of individual neurons during sensory activation as well as a recently obtained microcircuitry characterization for this structure. We find that system identification is a useful way to find suitable mathematical models that capture the properties and transformation capabilities of the neuronal microcircuitry that constitute the cuneate nucleus. Future work will show whether specific aspects of the mathematical properties can be ascribed to a specific microcircuitry and/or neuronal property.},
  author       = {Jörntell, Henrik and Forsberg, Per-Ola and Bengtsson, Fredrik and Johansson, Rolf},
  booktitle    = {[Host publication title missing]},
  language     = {eng},
  pages        = {98--103},
  title        = {Mathematical Modeling of Brain Circuitry during Cerebellar Movement Control},
  url          = {http://dx.doi.org/10.1109/ROBIO.2009.5420640},
  year         = {2009},
}