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Review
. 2010 Aug;204(4):475-91.
doi: 10.1007/s00221-010-2315-2. Epub 2010 Jun 8.

The cognitive neuroscience of prehension: recent developments

Affiliations
Review

The cognitive neuroscience of prehension: recent developments

Scott T Grafton. Exp Brain Res. 2010 Aug.

Abstract

Prehension, the capacity to reach and grasp, is the key behavior that allows humans to change their environment. It continues to serve as a remarkable experimental test case for probing the cognitive architecture of goal-oriented action. This review focuses on recent experimental evidence that enhances or modifies how we might conceptualize the neural substrates of prehension. Emphasis is placed on studies that consider how precision grasps are selected and transformed into motor commands. Then, the mechanisms that extract action relevant information from vision and touch are considered. These include consideration of how parallel perceptual networks within parietal cortex, along with the ventral stream, are connected and share information to achieve common motor goals. On-line control of grasping action is discussed within a state estimation framework. The review ends with a consideration about how prehension fits within larger action repertoires that solve more complex goals and the possible cortical architectures needed to organize these actions.

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Figures

Fig. 1
Fig. 1
Anatomic connections of areas V6A and AIP based on tract tracing in non-human primates. These are hubs that define superior and inferior networks within the parietal cortex. The superior network has strong connections to superior parietal lobule and dorsal premotor cortex. The inferior network has strong connections with temporal cortex, SII and the posterior portion of area F5. Anatomic labeling is approximate
Fig. 2
Fig. 2
Schematic showing the functional modularity supporting prehensile behavior. Arrows indicate main sources of information sharing. A motor command can be selected and programmed in advanced and adjusted on-line based on state estimation and internal models that also track object information

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