title: Neural control of interlimb oscillations. I. Human bimanual coordination.
abstract: How do humans and other animals accomplish coordinated movements? How are novel combinations of limb joints rapidly assembled into new behavioral units that move together in in-phase or anti-phase movement patterns during complex movement tasks? A neural central pattern generator (CPG) model simulates data from human bimanual coordination tasks. As in the data, anti-phase oscillations at low frequencies switch to in-phase oscillations at high frequencies, in-phase oscillations occur at both low and high frequencies, phase fluctuations occur at the anti-phase in-phase transition, a "seagull effect" of larger errors occurs at intermediate phases, and oscillations slip toward in-phase and anti-phase when driven at intermediate phases. These oscillations and bifurcations are emergent properties of the CPG model in response to volitional inputs. The CPG model is a version of the Ellias-Grossberg oscillator. Its neurons obey Hodgkin-Huxley type equations whose excitatory signals operate on a faster time scale than their inhibitory signals in a recurrent on-center off-surround anatomy. When an equal command or GO signal activates both model channels, the model CPG can generate both in-phase and anti-phase oscillations at different GO amplitudes. Phase transitions from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases.
authors.affiliation: Center for Adaptive Systems, Boston University, MA 02215, USA.
authors.forename: S
authors.initials: S
authors.lastname: Grossberg
authors.forename: C
authors.initials: C
authors.lastname: Pribe
authors.forename: M A
authors.initials: MA
authors.lastname: Cohen
mesh_terms: D005121:Extremities / Q000502:physiology*; D006801:Humans; D009068:Movement / Q000502:physiology*; D009424:Nervous System Physiological Phenomena; D016571:Neural Networks, Computer