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      High Density, Double-Sided, Flexible Optoelectronic Neural Probes With Embedded μLEDs

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          Abstract

          Optical stimulation and imaging of neurons deep in the brain require implantable optical neural probes. External optical access to deeper regions of the brain is limited by scattering and absorption of light as it propagates through tissue. Implantable optoelectronic probes capable of high-resolution light delivery and high-density neural recording are needed for closed-loop manipulation of neural circuits. Micro-light-emitting diodes (μLEDs) have been used for optical stimulation, but predominantly on rigid silicon or sapphire substrates. Flexible polymer neural probes would be preferable for chronic applications since they cause less damage to brain tissue. Flexible μLED neural probes have been recently implemented by flip-chip bonding of commercially available μLED chips onto flexible substrates. Here, we demonstrate a monolithic design for flexible optoelectronic neural interfaces with embedded gallium nitride μLEDs that can be microfabricated at wafer-scale. Parylene C is used as the substrate and insulator due to its biocompatibility, compliance, and optical transparency. We demonstrate one-dimensional and two-dimensional individually-addressable μLED arrays. Our μLEDs have sizes as small as 22 × 22 μm in arrays of up to 32 μLEDs per probe shank. These devices emit blue light at a wavelength of 445 nm, suitable for stimulation of channelrhodopsin-2, with output powers greater than 200 μW at 2 mA. Our flexible optoelectronic probes are double-sided and can illuminate brain tissue from both sides. Recording electrodes are co-fabricated with μLEDs on the front- and backside of the optoelectronic probes for electrophysiology recording of neuronal activity from the volumes of tissue on the front- and backside simultaneously with bi-directional optical stimulation.

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          Most cited references41

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          Fully integrated silicon probes for high-density recording of neural activity

          Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal–oxide–semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.
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            Going deeper than microscopy: the optical imaging frontier in biology.

            Optical microscopy has been a fundamental tool of biological discovery for more than three centuries, but its in vivo tissue imaging ability has been restricted by light scattering to superficial investigations, even when confocal or multiphoton methods are used. Recent advances in optical and optoacoustic (photoacoustic) imaging now allow imaging at depths and resolutions unprecedented for optical methods. These abilities are increasingly important to understand the dynamic interactions of cellular processes at different systems levels, a major challenge of postgenome biology. This Review discusses promising photonic methods that have the ability to visualize cellular and subcellular components in tissues across different penetration scales. The methods are classified into microscopic, mesoscopic and macroscopic approaches, according to the tissue depth at which they operate. Key characteristics associated with different imaging implementations are described and the potential of these technologies in biological applications is discussed.
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              Large-scale recording of neuronal ensembles.

              How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron-electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                09 August 2019
                2019
                : 13
                : 745
                Affiliations
                [1] 1Department of Electrical and Computer Engineering, Carnegie Mellon University , Pittsburgh, PA, United States
                [2] 2Department of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA, United States
                [3] 3Carnegie Mellon Neuroscience Institute, Carnegie Mellon University , Pittsburgh, PA, United States
                Author notes

                Edited by: Ulrich G. Hofmann, Freiburg University Medical Center, Germany

                Reviewed by: Eric Klein, Albert Ludwigs Universität Freiburg, Germany; Patrick Degenaar, Newcastle University, United Kingdom

                *Correspondence: Maysamreza Chamanzar mchamanzar@ 123456cmu.edu

                This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2019.00745
                6699515
                31456654
                af0d45a0-a0c5-41e5-9e18-9fdd51d2102e
                Copyright © 2019 Reddy, Kimukin, Stewart, Ahmed, Barth, Towe and Chamanzar.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 February 2019
                : 05 July 2019
                Page count
                Figures: 6, Tables: 1, Equations: 4, References: 50, Pages: 15, Words: 10862
                Categories
                Neuroscience
                Original Research

                Neurosciences
                neural probe,micro-led,parylene c,microfabrication,optogenetics
                Neurosciences
                neural probe, micro-led, parylene c, microfabrication, optogenetics

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