Quick manual following response induced by large-field visual motion: what drives the response and how is it driven? Hiroaki Gomi, Naoki Saijo, Naotoshi Abekawa, Ikuya Murakami, Shin’ya Nishida NTT Communication Science Labs. Nippon Telegraph and Telephone, Japan

Voluntary reaching movement requires several computational processes, such as trajectory planning, kinematics, and dynamics, for which certain duration is needed after target is shown. In contrast to such planned movement, humans also have several kinds of fast visuomotor controls: large-field visual motion induces leg muscle activation with very short latency for stabilizing posture (Nashner and Berthoz, 1978) and smooth eye movements (ocular following response: OFR) for stabilizing retinal images (Miles et al., 1986; Gellman et al., 1990), and reaching-target jump induces a quick adjustment during arm movement (Goodale et al., 1986; Prablanc and Martin, 1992; Pisella et al., 1998; Day and Lyon, 2000; Desmurget and Grafton, 2000; Pisella et al., 2000). In addition to these fast motor controls, we recently found a quick manual motor response induced by large-field visual motion (Fig.1), which we named “manual following response (MFR)” (Saijo et al., 2003). When subject was asked to make a manual response opposite to the visual motion, a rapid pro-directional response was observed before anti-movement and initiation of the voluntary anti-directional movement was greatly delayed by this pro-directional response, suggesting an involuntary mechanism of the MFR. What information drives this response? A potential interpretation is that MFR is not directly generated by visual motion, but by target miss-localization induced by visual motion (Brenner and Smeets, 1997; Whitney et al., 2003). To answer this question, we performed a series of experiments. We found that the abrupt visual motion induced the MFR without affecting perceptual target localization, and that the magnitude of MFR was changed nearly in proportion to the strength of visual motion (in terms of motion coherence of random-dot kinematogram). Additionally, the MFR was observed even when the visual motion was confined to the follow-through phase of a hitting movement, in which no target existed. These results suggest that the MFR is driven by visual “motion” information, rather than by target “position” information. Moreover, the arm response was systematically modulated by hand bias forces, which could be interpreted as a result of reflexive visuomotor control. To explore the sensory processing involved in the MFR, we next examined the effect of image contrast and spatiotemporal frequency with using sinusoidal grating patterns as visual inputs. As the image contrast was increased, the MFR amplitude increased, and its latency decreased, up to the image contrast of ~10 %, and almost levelled off thereafter. As the temporal frequency was increased, the MFR amplitude increased up to 15-20 Hz, and then decreased (Fig.2) (Gomi et al., 2004). The spatiotemporal-frequency tuning of the MFR differed from that of the perceptual contrast sensitivity for visual motion (Burr & Ross, 1982), but coincided well with that of the OFR (Miles et al. 1986). This suggests that MFR and OFR share a common visual motion processing mechanism.

Fig.1 Large-field visual motion in leftward (green) or rightward (blue) direction induces MFR during arm movement. (a) Experimental setup. (b) x-acceleration (c) normalized and rectified EMGs of shoulder flexor and elbow extensor muscles.

Fig.2 MFR amplitude variation surface as a function of image spatiotemporal frequency. Data points colored by magenta were fitted by a Gaussian surface.

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