Wireless Multimodal Neural Interface Device for Neural Control Studies

We present a wireless multimodal neural interface device to record neural activities of neurons in dorsal root ganglia (DRG) and muscle electrical activities (EMG) of the selected muscles of 4 limbs, while selectively manipulating neural activities in DRGs of freely locomoting cats via optogenetic stimulation. The neural interface device has 4 identical 8-channel analog front-end (AFE) circuits for DRG recording with the mid-band gain of 60 dB within 9 Hz - 500 Hz, as well as a 16-channel AFE for EMG recording with the mid-band gain of 40 dB within 0.7 Hz -105 Hz. To effectively stimulate target neurons by optogenetic neuromodulation, the neural interface device has 4 identical 4-channel programmable stimulation drivers that can deliver pulsating current up to 65 mA to the selected LED. To eliminate tethering effects, the neural interface device uses Bluetooth Low Energy radio to receive user-defined stimulation parameters (i.e., stimulation frequency, pulse width, LED current) and send the recording data. The neural interface is built in a form factor of a head-mounted device, or headstage device, which has a plug-in structure formed by two vertical functional boards and one horizontal substrate board, resulting in dimensions of 3 x 3 x 3.3 cm³and a weight of 6.5 g.

I. Introduction

When animals move, the receptors in moving limbs inform the central nervous system (CNS) with somatosensory feedback from muscle spindle afferents [1]. The CNS integrates the feedback information at various levels and shapes locomotor output to adapt locomotion to the constantly changing environment [1]. Thus, motion-dependent somatosensory feedback is critical in the control of functional and dynamically stable locomotion. Neural interface devices, providing accurate modification and measurement of target analytes in animals and humans, have always been important in investigating the mechanisms of somatosensory feedback in the control of locomotion [2]–[4]. Over the past years, there have been exciting advancements in the development of neural interface devices, involving the development of new flexible sensing materials, low power and high-density circuits, wireless telemetry, integrated implantable and wearable form factors, etc.