title: Major remaining gaps in models of sensorimotor systems.
abstract: Experimental descriptions of the anatomy and physiology of individual components of sensorimotor systems have revealed substantial complexity, making it difficult to intuit how complete systems might work. This has led to increasing efforts to develop and employ mathematical models to study the emergent properties of such systems. Conversely, the development of such models tends to reveal shortcomings in the experimental database upon which models must be constructed and validated. In both cases models are most useful when they point up discrepancies between what we think we know and possibilities that we may have overlooked. This overview considers those components of complete sensorimotor systems that currently appear to be potentially important but poorly understood. These are generally omitted completely from modeled systems or buried in implicit assumptions that underlie the design of the model.
authors.affiliation: Department of Biomedical Engineering, University of Southern California Los Angeles, CA, USA.
authors.forename: Gerald E
authors.initials: GE
authors.lastname: Loeb
authors.affiliation: L-3 Applied Technologies Inc., HEM Division San Diego, CA, USA.
authors.forename: George A
authors.initials: GA
authors.lastname: Tsianos
keywords: biological neural networks; sensorimotor control; sensorimotor integration; sensorimotor learning; sensorimotor systems modeling