A wireless transmission neural interface system for unconstrained non-human primates.
OBJECTIVE
Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications.


METHODS
To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation.


RESULTS
We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm.


CONCLUSIONS
We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.
Department of Neurobiology and Anatomy, University of Texas-Houston Medical School, 6431 Fannin St., Houston, TX 77030, USA. Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton BN1 9QG, UK.
Jose A
JA
Fernandez-Leon
Arun
A
Parajuli
Robert
R
Franklin
Michael
M
Sorenson
Daniel J
DJ
Felleman
Bryan J
BJ
Hansen
Ming
M
Hu
Valentin
V
Dragoi
D000818:Animals; D003195:Computer Communication Networks / Q000295:instrumentation; D011211:Electric Power Supplies; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008252:Macaca fascicularis; D008253:Macaca mulatta; D008297:Male; D008904:Miniaturization; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D019579:Neocortex / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D059015:Wireless Technology / Q000295:instrumentation*