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Chapter 2. Prehension

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<strong>Chapter</strong> 4 - Planning of <strong>Prehension</strong> 75<br />

riphery is fed back to cortical areas for further planning and com-<br />

mands.<br />

As a simplified view of the CNS, it is a useful model for localizing<br />

some of the functions that task plans must perform. Motivations,<br />

emerging from limbic structures, are converted to goal-directed, sen-<br />

ally-ordered movements, using cortical and subcortical mechanisms.<br />

Cortical areas include the parietal association cortex, involved in the<br />

precise visual guidance of goal-directed arm and hand movements,<br />

and the frontal association cortex, involved in the processing of per-<br />

ceptual cues and memory stores. Subcortically, the basal ganglia,<br />

converging on secondary motor areas (SMA and dorsomedial area 6),<br />

are involved in strategy selection in accordance with goals and the<br />

context for the actions. The role of motor cortex is more part of<br />

movement execution, that of advanced tactile and proprioceptive<br />

adjustment of the fingers and hand.<br />

One way to study planning at the CNS level is to delay the signal<br />

to initiate the movement. In monkey studies where the direction of<br />

intended movement is given, but the GO signal is delayed (Wise,<br />

1985), neurons in the dorsal premotor area show directionally tuned<br />

activity during the delay period. Hocherman and Wise (1991) find<br />

that these responses vary with both target location and degree and in-<br />

tended curvature of the hand path.<br />

Research has shown that CNS processing is different when<br />

processing object property information for object recognition and<br />

naming, compared to manual interactions with the object. For<br />

example, after processing by the visual cortex, the parietal lobes are<br />

involved more extensively in visuomotor processing for reaching and<br />

grasping objects, whereas the temporal lobes are more involved in<br />

processing information for object recognition. (Wise & Desimone,<br />

1988; Goodale, Milner, Jakobson & Carey, 1991).<br />

While neural models are a gross simplification of the brain, they<br />

are useful for making important observations. The brain consists of<br />

billions of neurons, each making thousands of connections on other<br />

neurons. Information is processed to convert motivations into motor<br />

activity through the help of sensory information. Information, goals,<br />

control, and commands are distributed somehow across these arrays<br />

of processors. Yet, studies on the primate brain suggest conflicting<br />

evidence as to the nature of the information: there can be body-space<br />

or world-space reference frames, the language can be kinematic or<br />

dynamic, control can be feedforward or feedback, and commands can<br />

be at the movement or muscle level. There is likely a separation of<br />

neural computation for planning (frontal and parietal association areas,

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