Hirak Parikh et al 2009 J. Neural Eng. 6 026004 doi:10.1088/1741-2560/6/2/026004
Hirak Parikh1, Timothy C Marzullo2 and Daryl R Kipke1,2
Show affiliationsImproving cortical prostheses requires the development of recording neural interfaces that are efficient in terms of providing maximal control information with minimal interface complexity. While the typical approaches have targeted neurons in the motor cortex with multiple penetrating shanks, an alternative approach is to determine an efficient distribution of electrode sites within the layers of the cortex with fewer penetrating shanks. The objective of this study was to compare unit activity in the upper and lower layers of the cortex with respect to movement and direction in order to inform the design of penetrating microelectrodes. Four rats were implanted bilaterally with multi-site single-shank silicon microelectrode arrays in the neck/shoulder region of the motor cortex. We simultaneously recorded unit activity across all layers of the motor cortex while the animal was engaged in a movement direction task. Localization of the electrode array within the different layers of the cortex was determined by histology. We denoted units from layers 2 and 3 and units as upper layer units, and units from layers 5 and 6 as lower layer units. Analysis of unit spiking activity demonstrated that both the upper and lower layers encode movement and direction information. Unit responses in either cortical layer of the cortex were not preferentially associated with contralateral or ipsilateral movement. Aggregate analysis (633 neurons) and best session analysis (75 neurons) indicated that units in the lower layers (layers 5, 6) are more likely to encode direction information when compared to units in the upper layers (layers 2, 3) (p< 0.05). These results suggest that electrode sites clustered in the lower layers provide access to more salient control information for cortical neuroprostheses.
87.19.R- Mechanical and electrical properties of tissues and organs
Issue 2 (April 2009)
Received 19 September 2008, accepted for publication 3 February 2009
Published 2 March 2009
Hirak Parikh et al 2009 J. Neural Eng. 6 026004
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