optrode-array-for-simultaneous-optogenetic-modulation-electrical

Optrode Array for Simultaneous Optogenetic Modulation and Electrical Neural Recording

During the last decade, optogenetics has become an essential tool for the investigation of neural signaling due to its unique capability of selective ...

Ewha Womans University

We present an electromagnetic linear vibration energy harvester with an array of rectangular permanent magnets as a springless proof mass. Instead of supporting the magnet assembly with spring element, ferrofluid has been used as a lubricating material. When external vibration is applied laterally to the harvester, magnet assembly slides back and forth on the channel with reduced friction and wear due to ferrofluid, which significantly improves the long-term reliability of the device. Electric power is generated across an array of copper windings formed at the bottom of the aluminum housing. A proof-of-concept harvester has been fabricated and tested with a vibration exciter at various input frequencies and accelerations. For the device where 5 μL of ferrofluid was used for lubrication, maximum output power of 493 μW has been generated, which was 4.37% higher than that without ferrofluid. Long-term reliability improvement due to ferrofluid lubrication has also been verified. For the device with ferrofluid, 1.02% decrease of output power has been observed, in contrast to 59.73% decrease of output power without ferrofluid after 93,600 cycles.

Electromagnetic Linear Vibration Energy Harvester Using Sliding Permanent Magnet Array and Ferrofluid as a Lubricant.

We present a light emitting diode (LED)-based optical waveguide array that can optogenetically modulate genetically targeted neurons in the brain. The reusable part of the system consists of control electronics and conventional multi-wavelength LED. The disposable part comprises optical fibers assembled with microlens array fabricated on a silicon die. Both parts can be easily assembled and separated by snap fit structure. Measured light intensity is 3.35 mW/mm at 469 nm and 0.29 mW/mm at 590 nm when the applied current is 80 mA. In all the tested conditions, the light-induced temperature rise is under 0.5°C and over 90% of the relative light intensity is maintained at 2 mm-distance from the fiber tips. We further tested the efficiency of the optical array in vivo at 469 nm. When the optical array delivers light stimulation on to the visual cortex of a mouse expressing channelrhodopsin-2, the neural activity is significantly increased. The light-driven neural activity is successfully transformed into a percept of the mouse, showing significant learning of the task detecting the cortical stimulation. Our results demonstrate that the proposed optical array interfaces well with the neural circuits in vivo and the system is applicable to guide animal behaviors.

Multi-wavelength light emitting diode-based disposable optrode array for in vivo optogenetic modulation.

In this paper, we look into the fundamental mechanism to retrieve the power from physical vibrations by using microelectromechanical systems (MEMS) energy harvesters. An analytical model is presented for the velocity-damped resonant generator (VDRG) that delivers electrical power through the power enhancement mechanism using the mechanical resonance of a suspended mass. Deliverable power is also analytically discussed with respect to the theoretical limit, and a view to understand the VDRG behaviors is presented in association with the impedance matching condition and the quality factors. Mechano-electric power conversions including electrostatic induction, electromagnetic induction, and piezoelectric effect are discussed to study the scaling effect. Recent examples of MEMS VDRGs are reviewed and evaluated in terms of the power density.

MEMS vibrational energy harvesters.

Due to a limited lifetime of a battery, energy harvesters have been studied as alternative energy sources for implantable biomedical devices such as an implantable stimulator for epileptic seizure suppression. However, energy harvesters have weakness in providing stable power. We designed a neural recording circuit powered solely by a piezoelectric energy harvester, and applied its output to a seizure detector to analyze the reliability of the recorded signal. Performance of the seizure detector was evaluated. We found that the average time differences between with and without voltage variances were about 0.05 s under regular vibrations and about 0.07 s under irregular vibrations, respectively. The ratio of average true positive alarm period varied within about 0.02% under regular vibrations and 0.029% under irregular vibrations, respectively. The ratio of average false positive alarm period varied within about 0.004% under regular vibrations and 0.014% under irregular vibrations, respectively. This paper presents a reliability analysis of an epileptic seizure detector with a neural signal recording circuit powered by a piezoelectric energy harvester. The results showed that a supply voltage variance within ±10% could be acceptable for reliable operation of a seizure detector.

Reliability Analysis of an Epileptic Seizure Detector Powered by an Energy Harvester.

During the last decade, optogenetics has become an essential tool for neuroscience research due to its unrivaled feature of cell-type-specific neuromodulation. There have been several technological advances in light delivery devices. Among them, the combination of optogenetics and electrophysiology provides an opportunity for facilitating optogenetic approaches. In this study, a novel design of an optrode array was proposed for realizing optical modulation and electrophysiological recording. A 4 × 4 optrode array and five-channel recording electrodes were assembled as a disposable part, while a reusable part comprised an LED (light-emitting diode) source and a power line. After the characterization of the intensity of the light delivered at the fiber tips, in vivo animal experiment was performed with transgenic mice expressing channelrhodopsin, showing the effectiveness of optical activation and neural recording.

Implantable Optrode Array for Optogenetic Modulation and Electrical Neural Recording.

. This paper presents a conventional light emitting diode (LED) and polymer waveguide coupled silicon optrode array.. Unique lens design at the waveguide inlet enables a high light coupling efficiency with a single LED light source, and provides small power consumption compatible with a wireless optogenetic neuromodulation system. To increase the light intensity at the waveguide tip, a lensed waveguide is fabricated with epoxy-based photoresist SU-8, which has a plano-convex lens shape at the waveguide inlet to focus the light in the horizontal direction. In addition, a cylindrical lens is assembled in front of the waveguide inlet to focus the source light in the vertical direction.. The glass cylindrical lens and SU-8 plano-convex lens increased the light coupling efficiency by 6.7 dB and 6.6 dB, respectively. The fabricated 1 × 4 array of optrodes is assembled with a single LED with 465 nm wavelength, which produces a light intensity of approximately 2.7 mW mmat the SU-8 waveguide outlet when 50 mA input current is applied to the LED. Each optrode has four recording electrodes at the SU-8 waveguide outlet. The average impedance of the iridium oxide (IrO) electroplated recording electrodes is 43.6 kΩ..experiment at the hippocampus region CA1 and CA2 demonstrated the capability of optical stimulation and neural signal recording through the LED and SU-8 waveguide coupled silicon optrode array.

Chang-Hyeon Ji

Department of Electronic and Electrical Engineering,
Graduate Program in Smart Factory

Ewha Womans University

Optrode Array for Simultaneous Optogenetic Modulation and Electrical Neural Recording

Chang-Hyeon Ji

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Electronic and Electrical Engineering,Graduate Program in Smart Factory

Ewha Womans University

Optrode Array for Simultaneous Optogenetic Modulation and Electrical Neural Recording

Department of Electronic and Electrical Engineering,
Graduate Program in Smart Factory