How is human locomotion visually controlled? Fifty years ago, it was proposed that we steer to a goal using optic flow, the pattern of motion at the eye that specifies the direction of locomotion. However, we might also simply walk in the perceived direction of a goal. These two hypotheses normally predict the same behavior, but we tested them in an immersive virtual environment by displacing the optic flow from the direction of walking, violating the laws of optics. We found that people walked in the visual direction of a lone target, but increasingly relied on optic flow as it was added to the display. The visual control law for steering toward a goal is a linear combination of these two variables weighted by the magnitude of flow, thereby allowing humans to have robust locomotor control under varying environmental conditions.

How do space and time relate m rhythmical tasks that reqmre the hmbs to move singly or together m various modes of coordination ? And what kind of minimal theoretical model could account for the observed data9 Ead~er findings for human cychcal movements were consistent w~th a nonhnear, limit cycle oscdlator model (Kelso, Holt, Rubm, & Kugler, 198 l) although no detailed modehng was performed at that Ume In the present study, lonemauc data were sampled at 200 samples/second, and a detmled analysis of movement amphtude, frequency, peak velooty, and relative phase (for the blmanual modes, m phase and anuphase) was performed As frequency was scaled from l to 6 Hz (m steps of l Hz) using a pacing metronome, amphtude dropped reversely and peak veiooty m-creased WRhm a frequency condmon, the movement's amphtude scaled &rectly with lls peak veloc-Ry These &verse lonematlc behaviors were modeled exphotly m terms oflow-&menslonal (nonhn-ear) dlsslpaUve dynamics, wRh hnear stiffness as the only control parameter Data and model are shown to compare favorably The abstract, dynamical model offers a umfied treatment of a number of fundamental aspects of movement coordination and control How do space and time relate m rhythmical tasks that require the hands to move singly or together in various modes of coordi-nation9 And what kind of minimal theoretical model could account for the observed data? The present article addresses these fundamental questions that are of longstanding interest to experimental psychology and movement science (e g, von Hoist, 1937/1973; Scripture, 1899; Stetson & Bouman, 1935) It is well known, for example, that discrete and repetitive movements of different amplitude vary systematically in movement duration (provided accuracy requirements are held constant, e g, Cralk, 1947a, 1947b) This and related facts were later for-mahzed into F~tts's Law (1954), a relation among movement time, movement amplitude, and target accuracy, whose under-pmnmgs have been extensively studied (and debated upon) quite recently (e g.

The departure point of the present paper is our effort to characterize and understand the spatiotemporal structure of articulatory patterns in speech. To do so, we removed segmental variation as much as possible while retaining the spoken act's stress and prosodic structure. Subjects produced two sentences from the "rainbow passage" using reiterant speech in which normal syllables were replaced by /ba/ or /ma/. This task was performed at two self-selected rates, conversational and fast. Infrared LEDs were placed on the jaw and lips and monitored using a modified SELSPOT optical tracking system. As expected, when pauses marking major syntactic boundaries were removed, a high degree of rhythmicity within rate was observed, characterized by well-defined periodicities and small coefficients of variation. When articulatory gestures were examined geometrically on the phase plane, the trajectories revealed a scaling relation between a gesture's peak velocity and displacement. Further quantitative analysis of articulator movement as a function of stress and speaking rate was indicative of a language-modulated dynamical system with linear stiffness and equilibrium (or rest) position as key control parameters. Preliminary modeling was consonant with this dynamical perspective which, importantly, does not require that time per se be a controlled variable.