Wireless gigabit data telemetry for large-scale neural recording

Yen-Cheng Kuan, Yi Kai Lo*, Yanghyo Kim, Mau-Chung Chang, Wentai Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Implantable wireless neural recording from a large ensemble of simultaneously acting neurons is a critical component to thoroughly investigate neural interactions and brain dynamics from freelymoving animals. Recent researches have shown the feasibility of simultaneously recording from hundreds of neurons and suggested that the ability of recording a larger number of neurons results in better signal quality. This massive recording inevitably demands a large amount of data transfer. For example, recording 2000 neuronswhile keeping the signal fidelity (> 12 bit,> 40 KS/s per neuron) needs approximately a 1-Gb/s data link. Designing a wireless data telemetry system to support such (or higher) data rate while aiming to lower the power consumption of an implantable device imposes a grand challenge on neuroscience community. In this paper, we present a wireless gigabit data telemetry for future large-scale neural recording interface. This telemetry comprises of a pair of low-power gigabit transmitter and receiver operating at 60 GHz, and establishes a short-distance wireless link to transfer the massive amount of neural signals outward from the implanted device. The transmission distance of the received neural signal can be further extended by an externally rendezvous wireless transceiver, which is less power/heat-constraint since it is not at the immediate proximity of the cortex and its radiated signal is not seriously attenuated by the lossy tissue. The gigabit data link has been demonstrated to achieve a high data rate of 6 Gb/s with a bit-error-rate of 10-12 at a transmission distance of 6 mm, an applicable separation between transmitter and receiver. This high data rate is able to support thousands of recording channels while ensuring a low energy cost per bit of 2.08 pJ/b.

Original languageEnglish
Article number2416202
Pages (from-to)949-957
Number of pages9
JournalIEEE Journal of Biomedical and Health Informatics
Volume19
Issue number3
DOIs
StatePublished - 1 May 2015

Keywords

  • Brain-machine interface
  • Data telemetry
  • Implant
  • Large-scale
  • Neural interface
  • Prosthetics
  • Transceiver
  • Wireless neural recording

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