One of the goals of the Neural Engineering System Design (NESD) program in the United States and of similar programs around the world is to develop an interface able to read from one million neurons in parallel. This is well beyond the capabilities of traditional multi-electrode arrays (MEAs), which are inherently limited in both spatial resolution and number of channels, due to issues with power dissipation and wiring.1, 2 To overcome these roadblocks our group has proposed a novel optrode array that measures electrical activity and uses light for both signal transduction and transmission, thus decoupling the bio-potentials from the signal acquisition circuitry.3 The technology relies on the sensitivity of a particular class of liquid crystals (LCs) to small electric fields and is analogous to a LC display, where the intensity of each pixel (optrode, in our case) is controlled by the electrical activity of the biological tissue. Here, we present the first use of such a transduction mechanism to record from cardiac tissue and investigate stimulus artifact suppression in rabbit sciatic nerve. Our results pave the way to the development of high-density high-channel-count optrode arrays for electrophysiology studies and brain-machine interfaces.
This paper presents an investigation into a novel electro-optic device for bi-directional brain-machine interface (BMI) by using both a chiral smectic C* liquid crystal to sense neuronal signals and the photovoltaic effect to stimulate neuronal tissues. By leveraging both the optical and electrical domains, this new electro-optic device can achieve high density of channel count and we have so far demonstrated up to 323 such channels. We focus here on tissue stimulation by adding a photovoltaic PN junction into the LC sensing structure described elsewhere to achieve a full bi-directional neuronal interface.
Nerve conduction and activity is a marker of disease and wellness and provides insight into the complex way the nervous system encodes information. We propose an electro-optical detection system and show the recordings from an electrically stimulated in-vitro nerve preparation. The system converts the action potential at the probing position to light intensity before any amplification and detection. Thence the light signal is detected by a photodetector. The new detection system has the ability of isolating the probing point and the amplification circuits, which reduces the electrical interference from the circuit. Moreover, the sampled signal transmitted via optical fibres rather than cables or wires makes it more robust to environmental noise. From the experiment, we demonstrated that the electro-optical detection system is able to detect and amplify the nerve response. By analysing the data, we can distinguish the response from the stimulus artifact and calculate CAP (compound action potential) propagation speed.
We report on the latest development of our photonics-based brain-machine interface. This work done in collaboration between UNSW and Macquarie University – and supported by the US Office of Naval Research – directly addresses the long-term DARPA challenge of producing implantable chips with 1 million neural connections. To the best of our knowledge, no technology has demonstrated the potential so far to scale up to such a massive number of channels.
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