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Having its basis in an empirically derived theory of human coordination, VPI offers a principled approach to human-machine interaction and opens up new ways to understand how humans interact with human-like machines including identification of underlying neural mechanisms.
In this proof of concept study, human subjects coordinate hand movements with a virtual partner, an avatar of a hand whose movements are driven by a computerized version of the Haken-Kelso-Bunz (HKB) equations that have been shown to govern basic forms of human coordination.
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Many researchers seek to fit dynamical models to human coordination of simple motor tasks.
In this paper we take inspiration from the "dynamic clamp" of cellular and computational neuroscience in order to probe essential properties of human social coordination.
Analogous to the dynamic clamp [1], [3] VPI allows the experimenter to explore a range of control parameters and coupling manipulations not typically accessible in experimental studies of human social coordination.
In like fashion, but now scaled up from the level of neuronal behavior to the level of behaving humans, we introduce VPI as a surrogate system to systematically investigate the essentially nonlinear dynamics of human social coordination (see [8] [10] for recent reviews].
The theory of dynamic patterns can also be employed to describe human coordination with external agents, which we describe next.
It was never intended as a human coordination tool.
Contribution of the subcortical nuclei to the coordination of human behavior is dependent on the existence of appropriate anatomical architecture.
In an important recent study of Chinese archaeo-astronomy, David Pankenier (2013, 5) traces the Chinese coordination of human activities with the observation and positions of the sun, moon, and stars as far back as the Neolithic cultures of the fifth millennium BCE.
Efficient care processes demand appropriate coordination of human and material resources to meet patients' needs in critical care.
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