Information Analysis on Neural Tuning in Dorsal Premotor Cortex for Reaching and Grasping

Previous studies have shown that the dorsal premotor cortex (PMd) neurons are relevant to reaching as well as grasping. In order to investigate their specific contribution to reaching and grasping, respectively, we design two experimental paradigms to separate these two factors. Two monkeys are instructed to reach in four directions but grasp the same object and grasp four different objects but reach in the same direction. Activities of the neuron ensemble in PMd of the two monkeys are collected while performing the tasks. Mutual information (MI) is carried out to quantitatively evaluate the neurons' tuning property in both tasks. We find that there exist neurons in PMd that are tuned only to reaching, tuned only to grasping, and tuned to both tasks. When applied with a support vector machine (SVM), the movement decoding accuracy by the tuned neuron subset in either task is quite close to the performance by full ensemble. Furthermore, the decoding performance improves significantly by adding the neurons tuned to both tasks into the neurons tuned to one property only. These results quantitatively distinguish the diversity of the neurons tuned to reaching and grasping in the PMd area and verify their corresponding contributions to BMI decoding.

[1]  P. Strick,et al.  Frontal Lobe Inputs to the Digit Representations of the Motor Areas on the Lateral Surface of the Hemisphere , 2005, The Journal of Neuroscience.

[2]  J. Tanji,et al.  Functional specialization in dorsal and ventral premotor areas. , 2004, Progress in brain research.

[3]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[4]  S. Wise,et al.  Learning-dependent neuronal activity in the premotor cortex: activity during the acquisition of conditional motor associations , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[5]  Shaomin Zhang,et al.  Decoding grasp movement from monkey premotor cortex for real-time prosthetic hand control , 2013 .

[6]  M. Nicolelis,et al.  Reconstructing the Engram: Simultaneous, Multisite, Many Single Neuron Recordings , 1997, Neuron.

[7]  Vittorio Gallese,et al.  Somatotopic organization of the lateral part of area F2 (dorsal premotor cortex) of the macaque monkey. , 2003, Journal of neurophysiology.

[8]  Dawn M. Taylor,et al.  Direct Cortical Control of 3D Neuroprosthetic Devices , 2002, Science.

[9]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[10]  M. Arbib,et al.  Dorsal Premotor Cortex and Conditional Movement Selection: A PET Functional Mapping Study , 1998 .

[11]  E. Stark,et al.  Encoding of reach and grasp by single neurons in premotor cortex is independent of recording site. , 2007, Journal of neurophysiology.

[12]  Michael J. Black,et al.  Decoding Complete Reach and Grasp Actions from Local Primary Motor Cortex Populations , 2010, The Journal of Neuroscience.

[13]  Jon A. Mukand,et al.  Neuronal ensemble control of prosthetic devices by a human with tetraplegia , 2006, Nature.

[14]  T Brochier,et al.  Simultaneous recording of macaque premotor and primary motor cortex neuronal populations reveals different functional contributions to visuomotor grasp. , 2007, Journal of neurophysiology.

[15]  Michael J. Black,et al.  Decoding grasp aperture from motor-cortical population activity , 2007, 2007 3rd International IEEE/EMBS Conference on Neural Engineering.

[16]  N. Hatsopoulos,et al.  Encoding of Coordinated Reach and Grasp Trajectories in Primary Motor Cortex , 2012, The Journal of Neuroscience.

[17]  Miriam Zacksenhouse,et al.  Cortical Ensemble Adaptation to Represent Velocity of an Artificial Actuator Controlled by a Brain-Machine Interface , 2005, The Journal of Neuroscience.

[18]  L. Fogassi,et al.  Functional properties of grasping-related neurons in the dorsal premotor area F2 of the macaque monkey. , 2004, Journal of neurophysiology.

[19]  Yaoyao Hao,et al.  Development of an invasive brain-machine interface with a monkey model , 2012, Chinese Science Bulletin.

[20]  J. Kalaska,et al.  Covariation of primate dorsal premotor cell activity with direction and amplitude during a memorized-delay reaching task. , 2000, Journal of neurophysiology.

[21]  Jerald D. Kralik,et al.  Real-time prediction of hand trajectory by ensembles of cortical neurons in primates , 2000, Nature.

[22]  Scott T. Grafton,et al.  Dorsal premotor cortex and conditional movement selection: A PET functional mapping study. , 1998, Journal of neurophysiology.

[23]  Nicolas Y. Masse,et al.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm , 2012, Nature.

[24]  David M. Santucci,et al.  Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates , 2003, PLoS biology.

[25]  D. Deng,et al.  Differentiation and adaptation epigenetic networks: Translational research in gastric carcinogenesis , 2013 .

[26]  Paul B. Johnson,et al.  Visuomotor transformations underlying arm movements toward visual targets: a neural network model of cerebral cortical operations , 1992, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[27]  Jose C. Principe,et al.  2009 Special Issue: Ascertaining neuron importance by information theoretical analysis in motor Brain-Machine Interfaces , 2009 .

[28]  J. Tanji,et al.  Distinctions between dorsal and ventral premotor areas: anatomical connectivity and functional properties , 2007, Current Opinion in Neurobiology.

[30]  Yiwen Wang,et al.  Instantaneous estimation of motor cortical neural encoding for online brain–machine interfaces , 2010, Journal of neural engineering.

[31]  W. Marsden I and J , 2012 .

[32]  Erk Subasi,et al.  Grasp Movement Decoding from Premotor and Parietal Cortex , 2011, The Journal of Neuroscience.

[33]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[34]  Andrew S. Whitford,et al.  Cortical control of a prosthetic arm for self-feeding , 2008, Nature.