Sensorimotor transformations in cortical motor areas

Kakei, Shinji; Hoffman, Donna S.; Strick, Peter L.

doi:10.1016/s0168-0102(03)00031-2

Cited by 146 publications

(106 citation statements)

References 36 publications

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“…The discrepancy in PD shifts between motor cortex and muscles is not necessarily at odds with direct cortical control of movement, because of the posturedependent modulation in firing rates (Andersen et al, 1985;Kakei et al, 2003) (see example of polar plots computed for spinal neuron in Fig. 1 B).…”

Section: Resultsmentioning

confidence: 99%

Coordinate Transformation is First Completed Downstream of Primary Motor Cortex

Yanai¹,

Adamit²,

Israel³

et al. 2008

J. Neurosci.

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It was suggested previously that the transformation of action to muscle-based coding is completed in the primary motor cortex (M1). This is consistent with a predominant direct pathway leading from M1 to motoneurons. Accordingly, spinal segmental interneurons that are located downstream to M1 are expected to show muscle-like coding properties. We addressed this hypothesis using simultaneous recording of cortical and spinal activity in primates performing an isometric wrist task with multiple targets and two hand postures. Here we show that while the motor cortex follows an intermediate coordinate frame, spinal interneurons already follow a muscle-like coordinate frame. We thus suggest that the final steps in coordinate transformation of motor commands take place downstream of M1 via corticospinal interactions.

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Section: Resultsmentioning

confidence: 99%

Coordinate Transformation is First Completed Downstream of Primary Motor Cortex

Yanai¹,

Adamit²,

Israel³

et al. 2008

J. Neurosci.

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show abstract

“…For ventral PM, a series of recent studies in monkeys point to extrinsic-like rather than intrinsic-like coding (Kakei et al, 1999(Kakei et al, , 2001(Kakei et al, , 2003. Moreover, the representation of the fingers has been located within ventral PM rather than in dorsal PM (Godschalk et al, 1995;Preuss et al, 1996).…”

Section: Discussionmentioning

confidence: 99%

“What” Becoming “Where”: Functional Magnetic Resonance Imaging Evidence for Pragmatic Relevance Driving Premotor Cortex

2004

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Previous studies using the serial prediction task (SPT) have shown that attending to the locations of objects activates the dorsal part of premotor cortex more than attending to the sizes of objects. The opposite holds for the ventral part of the premotor cortex. The present study used functional magnetic resonance imaging to investigate whether the learning of arbitrary stimulus-response mappings influences this functional dissociation. One experimental group learned to assign stimuli to response buttons based on stimulus size; another group did so based on stimulus location. More specifically, one-half of the participants in both experimental groups learned to assign stimuli to finger movements of their right hand, whereas the other half assigned stimuli to finger movements of their left hand. During scanning, all participants performed both size SPT and location SPT. Thus, we investigated the effects of the attended stimulus property (size or location), the motor effector assigned to it (fingers of left or right hand), and the spatial arrangement of the targets (the same in all groups). As expected, without motor training, the dorsal premotor cortex was less activated during size SPT compared with location SPT. The opposite held for ventral premotor cortex. With motor training, however, this differential activity pattern vanished. Activity in dorsal premotor cortex reflected neither the attended stimulus property nor the motor effector assigned to it. Instead, its activity may be related to the spatial properties of the response targets once some object property, such as size, takes on the "pragmatic relevance" of a spatially directed response.

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“…AIP neurons represent grasping movements in terms of visual properties of target objects and contain context-related information for the appropriate selection of actions (Taira et al, 1990;Sakata et al, 1995;Murata et al, 2000;Baumann et al, 2009 Fluet et al, 2010). The representation of hand movements in these areas is therefore based on the overall motor goal, instead of a more intrinsic (muscle-like) representation as in M1 (Kakei et al, 1999(Kakei et al, , 2003Morrow et al, 2007), which makes these signals interesting potential targets for prosthetic applications (Shenoy et al, 2003).…”

Section: Nature Of Decoded Signalsmentioning

confidence: 99%

Grasp Movement Decoding from Premotor and Parietal Cortex

Townsend¹,

Subasi²,

Scherberger³

2011

J. Neurosci.

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Despite recent advances in harnessing cortical motor-related activity to control computer cursors and robotic devices, the ability to decode and execute different grasping patterns remains a major obstacle. Here we demonstrate a simple Bayesian decoder for real-time classification of grip type and wrist orientation in macaque monkeys that uses higher-order planning signals from anterior intraparietal cortex (AIP) and ventral premotor cortex (area F5). Real-time decoding was based on multiunit signals, which had similar tuning properties to cells in previous single-unit recording studies. Maximum decoding accuracy for two grasp types (power and precision grip) and five wrist orientations was 63% (chance level, 10%). Analysis of decoder performance showed that grip type decoding was highly accurate (90.6%), with most errors occurring during orientation classification. In a subsequent off-line analysis, we found small but significant performance improvements (mean, 6.25 percentage points) when using an optimized spike-sorting method (superparamagnetic clustering). Furthermore, we observed significant differences in the contributions of F5 and AIP for grasp decoding, with F5 being better suited for classification of the grip type and AIP contributing more toward decoding of object orientation. However, optimum decoding performance was maximal when using neural activity simultaneously from both areas. Overall, these results highlight quantitative differences in the functional representation of grasp movements in AIP and F5 and represent a first step toward using these signals for developing functional neural interfaces for hand grasping.

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Sensorimotor transformations in cortical motor areas

Cited by 146 publications

References 36 publications

Coordinate Transformation is First Completed Downstream of Primary Motor Cortex

Coordinate Transformation is First Completed Downstream of Primary Motor Cortex

“What” Becoming “Where”: Functional Magnetic Resonance Imaging Evidence for Pragmatic Relevance Driving Premotor Cortex

Grasp Movement Decoding from Premotor and Parietal Cortex

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