Presentation on theme: "Optically Switched Planar Microelectrode Arrays Hardware, Software & Algorithms Tom Manuccia Professor Department of Electrical & Computer Engineering."— Presentation transcript:
Optically Switched Planar Microelectrode Arrays Hardware, Software & Algorithms Tom Manuccia Professor Department of Electrical & Computer Engineering George Washington University (202) GWU homepage August 14, 2004
Chick cardiac myocytes beating on a conventional 32 electrode, non-multiplexed array in our lab (Jan. 2002) Because of the limited number of recording sites, it is rare that a beating cluster of cells will be in registry with an electrode. Three problems limit scaling: (a) The use of a single metal layer severely constrains the routing of traces and electrode packing density; (b) One contact pad per electrode required; (c) One pre-amp and filter per electrode required.
Conventional MEA (MicroElectrodeArray) Technology One Amplifier & Signal Processing Chain per Electrode
Multi-Layer Fabrication Solves the Routing & Other Problems
Multi-layer Fabrication Using BCB Presently used MEA dielectrics / encapsulants: Polyimide, Polysiloxane –Absorb water, swell, delaminate upon reuse –Poor hydrophilicity requires awkward “flaming” procedure for cell adhesion –Fabrication by laser ablation of individual vias is slow and non-reproducible BCB / Cyclotene (B-staged bis(benzocyclobutene di-methyl siloxane) ) –Well known planarizing, photodefinable, dielectric resin for semicon fabrication –New to MEAs, probably new to bioengineering –Hydrophilic but no water absorption, no delamination, no “flaming” required, non-toxic to neurons –Fabrication by conventional lithography (fast, high yield, etc.) BCB allows multiple layer MEA designs –Dramatically increases total electrode count & packing density –Allows for shielding layers to do stimulation and recording on one chip –Vertical stacking of traces allows optical access to cells from below for microscopy, absorption, florescence, etc.
Accelerated aging tests: delamination, water permeation, R, C, etc. Major problem in field solved - ML-MEA sample (similar construction to OSMA) after 2 weeks in boiling saturated brine. We observed no delamination or measurable decrease in resistance (from many hundreds of Gigohms) between electrodes. Other tests included adhesion (pull) tests, strain (polarized light), pinhole inspection, trace continuity, specific test structures (traces crossing, interdigitated electrodes, interlayer C, long term biocompatability, unwanted bulk or surface chemisorption, surface hydrophilicity / hydrophobicity, interface Z, etc.
Drop-In, Pin-Compatible OEM Replacement MEA Fabricated by Manuccia’s group using Multi-layer MEA technology
Rat Cortical Neurons Growing on our ML-MEA This micrograph was taken 6 days post-seeding. This particular culture continued to thrive out to 30 days, at which point, we recycled the plate for durability / reuse testing. A rat hippocampal culture continued to thrive at 52 days, with 55 out of the 64 electrodes showing active units and S/N as large as 17:1. Courtesy: Ed Keefer, Neuroscience Institute, La Jolla.
Action Potentials Recorded with an ML - MEA Twenty five superimposed AP’s from the rat cortical neuron culture show excellent reproducibility in amplitude, timing and shape. Courtesy: Ed Keefer, Neuroscience Institute, La Jolla
Optically Controlled Electrical Switches Solves the Connector and Parallel Electronics Problems
Conventional Electrical Multiplexers Cannot Be Used Conventional electrical multiplexing not adequate for high impedance, low voltage analog signals such as in this application –charge injection –voltage offsets –Major problem of RF interference from the 5 V control lines in electrical multiplexers at high Z’s With (e.g.) 10,000 on-plate, matched, low-noise, high gain amps, conventional analog multiplexers could be used, but this is cost prohibitive and requires opaque substrates, and/or sophisticated packaging. Optically controlled electrical multiplexing –Lower charge injection artifact –Lower voltage offset artifact –Noise immunity at high switching rates –Optical switching completely circumvents RF EMI –Adaptable to extremely high packing densities
Optically Switched Microelectrode Array (OSMA) Concept - I One optically controlled electrical switch for each electrode Large numbers of electrodes are connected to the same output bus Individual electrodes are selected via low power laser illumination For each bus, only one pad, one connector and one signal amplification and signal processing chain is needed
OSMA Array Concept - II
Early OSMA array An early prototype OSMA 16x16 array connected to a single output bus
Electrical Performance - OSMA switches Raw data (1 mV, 1 kHz, 1 Mohm source Z) from tests of one of our early a-Si optically controlled switches being used to sample sine and square waves. For many applications, slow switches such as this would be used to select and route only the “interesting” electrodes to the output buses, and thus would stay “on” for the duration of a pharmacology or other experiment. After settling, ultimate on/off switching ratios are in excess of 1000:1.
Noise Measurements - OSMA switches Experimental setup and raw data: Inside a Faraday cage, an 80 microvolt simulated action potential with 1 Megohm source impedance was injected into one of our GaAs optically controlled switches, and thence to a high quality amplifier with 1 Megohm input impedance and ,000 Hz bandwidth. The lower trace shows the resulting signal (20 uV/div) with the laser “ON”. With the laser off, the AP’s disappear completely ( > 1000:1), and the noise drops slightly from 5 uV (RMS) to 4 uV (RMS). Thus, the switches are essentially noise free when on, and an open circuit when off. Other measurements (not shown) included I-V curve tracing to detect non-ohmic contacts and other effects, photovoltaic artifacts, switching R’s and C’s, photolinearity, time constant measurements (carrier lifetimes/trapping), physical adhesion, lift-off & other fab flaws, etc.
Complete single well 10k pixel OSMA wafer Quadrant of an 3" wafer showing test structures (left edge) and one complete, encapsulated OSMA device. Contact pads are for 3 signal buses, 1 electrochemical reference bus & 1 ground plane. Structure consists of several insulating & metal layers. Because the switches are directly under the electrodes in this design, the electrophysiologist would use three small lasers mounted on micropositioners as “virtual pipettes”, directing them at the cells of interest.
Small portion of 10k pixel OSMA Due to lighting, the gold electrodes appear clear in this microphotograph of the pixels are reference electrodes and are hard-wired to one bus. The remaining 7500 are wired through the switches to three signal buses.
Multi-well MEA Plate with OSMA Multiplexers (12 Wells, 768 electrodes) The large wells of this plate are suitable for slice preparations.
96 Well Plate Optically Switched Microelectrode Array (6144 electrodes) Entire electrode plateMicrograph of one of the 96 8x8 electrode arrays The relatively narrow wells of this plate are suitable for cell culture work
Hardware Summary: Multiple Generations of Microelectrode Arrays From the P.I.’s lab Single layer, multiple layer, non-switched, switched, amorphous-Si, GaAs, horizontal and vertical geometry switches: 64 electrode OEM drop-in array, 768 electrodes in 12 wells, 6144 electrodes in 96 wells, 10,000 electrodes in one large (1 cm 2 ) contiguous area, etc.
Environmental Chamber for 10 kPixel array OSMA mounted in a temperature controlled perfusion chamber on the microscope stage for wet electrical testing. The red color is from the pH indicator in the growth medium.
10 kPixel OSMA Flow / Perfusion System
Data Analysis and Simulation
Data Analysis Software - Ensembles Designed to analyze data from large electrode count MEA’s in real or near real time. Detects and quantifies small changes in 1st and 2nd order statistics of the firing patterns. Detects and enumerates membership in correlationally defined neural ensembles. Detects subtle phase changes in firing patterns without any change in rates, ISI’s, etc.. Left - Color coded cross correlogram in a simulated 100 neuron network exhibiting chaotic firing. The weights of all connections crossing a cut plane have been reduced. Right - Correlogram of the same data after re-indexing of the neuron ID’s by Ensembles The presence of two distinct ensembles is obvious (i.e., two diagonal blocks).
Example of Another Use of Ensembles: Detecting the Change Between 1 and 2 Ensemble Behavior In a Network With a Soft Cut-Plane A quasi-chaotically firing, randomly connected network was modified by multiplying the synaptic weights of all processes crossing a “cut-plane”. The resulting spike time data was fed to Ensembles for analysis. With weak coupling, the two sub-nets fire independently. As the coupling increases, activity in the sub-nets becomes more correlated. The above graph shows the variation of the firing similarity metric for numerous pairs of neurons as a function of coupling strength. With weak coupling, the similarities clearly cluster into two groups, same-side and opposite-side, but start to merge at coupling strengths as low as For stronger coupling, the networks effectively act as one.
Data Simulation Software - NeuroSpike Can simulate 100,000 biologically realistic neurons on a desktop PC. Includes neuron level rate adaptation, spike timing dependent synaptic plasticity, statistical distribution of neuron location, orientation, and many other parameters. Used to simulate streaming data from high electrode count MEA’s for input to Ensembles. May also have AI / ANN interest. Uses an optimistic discrete event simulation kernel.
Data Simulation Software - NeuroSpike Typical data generated by NeuroSpike. This shows the activity of the inhibitory neurons in a simulation of 1000 randomly connected, randomly located simple integrate and fire neurons (900 excitatory, 100 inhibitory). Different parameters can generate a rich variety of behaviors including epileptic-like spatio-temporal waves of activity, clusters of cells (ie, ensembles) acting in concert, but only weakly connected to other clusters, network wide bursting behavior, etc.
Major Achievements First microelectrode arrays with multiple layer construction –Overcomes trace routing problems. Allows for 10X - 100X increase in electrode count Introduction of a new, biocompatible insulating material with vastly improved physical and chemical properties. –Overcomes previous durability and cell adhesion problems. First microelectrode array incorporating an optically controlled electrical multiplexer –Overcomes previous scaling limitations. Allows reasonable number of connections and amplifier chains. Can select only those electrodes of interest. Glass substrate. First microelectrode array with more than 1 or 2 wells –MEA’s no longer just for basic research. Sequential experiments & washout no longer required. First software simulator of biologically realistic neuronal networks that can handle networks of 10^5 neurons on a desktop machine at reasonable speed –Important as “gold-standard” data source for data analysis programs designed to handle the data from large numbers of neurons simultaneously (ie, advanced MEA’s) First data analysis software to detect changes in ensemble firing behavior in data streamed from large electrode count MEA’s. –Critical to high throughput, high sensitivity, high selectivity assays
Selected formal and collegial relationships - Academia Neuroscience Institute (La Jolla) – Dr. Ed Keefer – performing tests on our arrays; will use them in his ongoing research efforts, probable joint grant applications, joint papers. Univ. North Texas – Prof.. Guenter Gross – performing tests on our arrays, supplied field potential data from his cell culture work for our data analysis efforts. Case Western Reserve Univ. Medical School – Prof. Bryan Roth – head of NIMH psychoactive drug screening program – committed to use of our system, possible joint grant applications. Pittsburgh Supercomputing Center – Discussions with facility director in regards to parallelizing Ensembles for very large on-line data analysis tasks (i.e., High Throughput Screening). Suggested that obtaining grant support would be easy. Penn State – Dr. Jeffrey Catchmark – Associate director, co-author of one patent application. The NSF Nanofabrication Facility at Penn State was used for most fabrication tasks. Howard Univ. – Dr. Gary Harris – The NSF Nanofabrication Facility at Howard was used for occasional fabrication tasks.
Selected formal and collegial relationships - Government NIMH – Drs. Mike Huerta, Dennis Glanzman – Program managers for our efforts for many years NIMH – Dr. Linda Brady – Head NIMH psychoactive drug screening program - Strongly supports the potential HTS application of our technologies. NINDS –Dr. Bill Heetderks (now NIBIB) – Program manager for our multi-layer fabrication advance. Naval Research Laboratory – Dr. Joe Pancrazio – Performed initial testing on our arrays, probable collaborator in future joint efforts, papers. Wants to use our arrays. DARPA – Dr. Alan Rudolph – DoD’s Tissue Based Biosensors Program – interested in HTS applications of this technology
Selected formal and collegial relationships - Commercial Merck – Drs. Jeff Conn – head of Neuroscience – Setting requirements for HTS system, possible R&D support, collaborative efforts. Lilly - Dr. Gary Tollifson - head of Neuroscience products - Interested in our system for slice preparations. Tranzyme, Inc. – Dr. Ramabhadran – Collaboration / system purchase for studies of transfected neurons Applied Neuronal Network Dynamics, Inc. – Mr. Daron Evans – Customer for drop-in replacement arrays Research International – Dr. Elric Saaski – Teaming partner to engineer the environmental and thermal control subsystems. Tensor Biosciences – Dr. Miro Pastrnak – Possible teaming partner – slice preps Loftstrand, Inc. – Dr. Pat Manos – Performed tests with cardiac myocytes in our lab. SAIC – Dr. Paul Schaudies – Possible chem/bio warfare applications. NeuraLynx, Inc. – C. Stengel – Teaming partner to supply data acquisition hardware, possible distributor of our software for basic neuroscience users, independent of HTS - drug discovery & neurotoxicology applications.
Related Grant Support (taken from NIH CRISP) Grant NumberPI NameProject Title 1r43dc Manuccia, ThomasNeuroSpike Software For The Simulation Of Neuronal Networks 1r43mh Manuccia, ThomasInitiated-Event Model Of Statistical Point Processes 1r43mh Manuccia, ThomasProcessing And Display Of Correlations In Multineuron Events 1r43mh a1Manuccia, ThomasOptically Switched Microelectrode Array 1r43mh Manuccia, ThomasSoftware For The Detection Of Neural Ensembles 1r43ns Manuccia, ThomasTechnology for Ultra-dense Microelectrode Arrays 2r44mh a1Manuccia, ThomasInitiated Event Models Of Stochastic Point Processes 5r44mh Manuccia, ThomasInitiated Event Models Of Stochastic Point Processes 2r44mh Manuccia, ThomasOptically Switched Microelectrode Array 5r44mh Manuccia, ThomasOptically Switched Microelectrode Array 5r44mh Manuccia, ThomasOptically Switched Microelectrode Array 3r44mh s1Manuccia, ThomasOptically Switched Microelectrode Array 2r44mh a2Manuccia, ThomasSystem For The Detection Of Neural Ensembles 5r44mh Manuccia, ThomasSystem For The Detection Of Neural Ensembles
Sampling of Other Biomedical Engineering and Sensing Projects From the Lab of the P.I. 1. Coherent Anti-Stokes Raman Microscopy - Allows chemical species selective spatial visualization - e.g., the distribution of lipids, deuterated lipids, etc. within cells. Essentially a mid-IR microscope with the spatial resolution of a visible light microscope. 2. Laser Electron Microscope - Similar to #1. Essentially a mid-IR microscope with the spatial resolution of a scanning electron microscope. 3. Mass transport to/from coated droplets acoustically levitated in a free-jet wind tunnel. Possible chem/bio warfare utility. 4. Ultrasensitive and selective (ie, sub-ppt) detection of NO by Zeman modulated acousto-optic detection. Application to explosives detection. 5. Production and imaging of ultrasound by pulsed RF in tissue - Contrast production by spatially varying dielectric material properties not acoustic properties. Application to the detection of breast malignancies.
Staff of the Schafer BioEngineering Group - Dec. 20, 2002 (Missing: Pat Manos, & Ingrid Mahogony --- Includes the P.I.’s wife and daughter)