Close-Packed Silicon Microelectrodes for Scalable Spatially Oversampled Neural Recording

Objective: Neural recording electrodes are important tools for understanding neural codes and brain dynamics. Neural electrodes that are closely packed, such as in tetrodes, enable spatial oversampling of neural activity, which facilitates data analysis. Here we present the design and implementation of close-packed silicon microelectrodes to enable spatially oversampled recording of neural activity in a scalable fashion. Methods: Our probes are fabricated in a hybrid lithography process, resulting in a dense array of recording sites connected to submicron dimension wiring. Results: We demonstrate an implementation of a probe comprising 1000 electrode pads, each 9 × 9 μm, at a pitch of 11 μm. We introduce design automation and packaging methods that allow us to readily create a large variety of different designs. Significance: We perform neural recordings with such probes in the live mammalian brain that illustrate the spatial oversampling potential of closely packed electrode sites.Massachusetts Institute of Technology. Simons Center for the Social BrainNational Institutes of Health (U.S.) (NIH Director’s Pioneer Award DP1NS087724)National Institutes of Health (U.S.) (NIH Grant R01NS067199)National Institutes of Health (U.S.) (NIH grant Grant 2R44NS070453- 03A1)National Institutes of Health (U.S.) (NIH Grant R01DA029639)National Science Foundation (U.S.) (Cognitive Rhythms Collaborative, NSF DMS 1042134)Institution of Engineering and Technology (IET) (Harvey Prize)New York Stem Cell FoundationNational Institutes of Health (U.S.) (NIH grant CBET 1053233)United States. Defense Advanced Research Projects Agency (DARPA Grant HR0011-14-2-0004)Paul G. Allen Family Foundatio

IEEE Trans Biomed Eng

ObjectiveNeural recording electrodes are important tools for understanding neural codes and brain dynamics. Neural electrodes that are close-packed, such as in tetrodes, enable spatial oversampling of neural activity, which facilitates data analysis. Here we present the design and implementation of close-packed silicon microelectrodes, to enable spatially oversampled recording of neural activity in a scalable fashion.MethodsOur probes are fabricated in a hybrid lithography process, resulting in a dense array of recording sites connected to submicron dimension wiring.ResultsWe demonstrate an implementation of a probe comprising 1000 electrode pads, each 9 \uc3\u2014 9 \uce\ubcm, at a pitch of 11 \uce\ubcm. We introduce design automation and packaging methods that allow us to readily create a large variety of different designs.SignificanceFinally, we perform neural recordings with such probes in the live mammalian brain that illustrate the spatial oversampling potential of closely packed electrode sites.R44 NS070453/NS/NINDS NIH HHS/United StatesR01 NS067199/NS/NINDS NIH HHS/United StatesR01 DA029639/DA/NIDA NIH HHS/United StatesDP1NS087724/DP/NCCDPHP CDC HHS/United StatesR01DA029639/DA/NIDA NIH HHS/United StatesDP1 NS087724/NS/NINDS NIH HHS/United StatesR01NS067199/NS/NINDS NIH HHS/United States2R44NS070453-03A1/NS/NINDS NIH HHS/United States2016-01-01T00:00:00Z26699649PMC469219

Hybrid multisite silicon neural probe with integrated flexible connector for interchangeable packaging

Multisite neural probes are a fundamental tool to study brain function. Hybrid silicon/polymer neural probes combine rigid silicon and flexible polymer parts into one single device and allow, for example, the precise integration of complex probe geometries, such as multishank designs, with flexible biocompatible cabling. Despite these advantages and benefiting from highly reproducible fabrication methods on both silicon and polymer substrates, they have not been widely available. This paper presents the development, fabrication, characterization, and in vivo electrophysiological assessment of a hybrid multisite multishank silicon probe with a monolithically integrated polyimide flexible interconnect cable. The fabrication process was optimized at wafer level, and several neural probes with 64 gold electrode sites equally distributed along 8 shanks with an integrated 8 µm thick highly flexible polyimide interconnect cable were produced. The monolithic integration of the polyimide cable in the same fabrication process removed the necessity of the postfabrication bonding of the cable to the probe. This is the highest electrode site density and thinnest flexible cable ever reported for a hybrid silicon/polymer probe. Additionally, to avoid the time-consuming bonding of the probe to definitive packaging, the flexible cable was designed to terminate in a connector pad that can mate with commercial zero-insertion force (ZIF) connectors for electronics interfacing. This allows great experimental flexibility because interchangeable packaging can be used according to experimental demands. High-density distributed in vivo electrophysiological recordings were obtained from the hybrid neural probes with low intrinsic noise and high signal-to-noise ratio (SNR).This work has been funded by: national funds through the Foundation for Science and Technology (FCT)—projects UIDB/50026/2020 and UIDP/50026/2020; the projects NORTE-01-0145- FEDER-000013 (“PersonalizedNOS—New avenues for the development of personalized medical interventions for neurological, oncologic and surgical disorders”) and NORTE-01-0145-FEDER-000023 (“FROnTHERA—Frontiers of technology for theranostics of cancer, metabolic and neurodegenerative diseases”), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF); ICVS Scientific Microscopy Platform, member of the national infrastructure PPBI— Portuguese Platform of Bioimaging (PPBI-POCI-01-0145-FEDER-022122); FCT project PTDC/MEDNEU/ 28073/2017 (POCI-01-0145-FEDER-028073); and The Branco Weiss fellowship—Society in Science, (ETH Zurich)

A direct-to-drive neural data acquisition system

Driven by the increasing channel count of neural probes, there is much effort being directed to creating increasingly scalable electrophysiology data acquisition (DAQ) systems. However, all such systems still rely on personal computers for data storage, and thus are limited by the bandwidth and cost of the computers, especially as the scale of recording increases. Here we present a novel architecture in which a digital processor receives data from an analog-to-digital converter, and writes that data directly to hard drives, without the need for a personal computer to serve as an intermediary in the DAQ process. This minimalist architecture may support exceptionally high data throughput, without incurring costs to support unnecessary hardware and overhead associated with personal computers, thus facilitating scaling of electrophysiological recording in the future.National Institutes of Health (U.S.) (Grant 1DP1NS087724)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Institutes of Health (U.S.) (Grant 2R44NS070453)National Institutes of Health (U.S.) (Grant R43MH101943)New York Stem Cell FoundationPaul Allen FoundationMassachusetts Institute of Technology. Media LaboratoryGoogle (Firm)United States. Defense Advanced Research Projects Agency (HR0011-14-2-0004)Hertz Foundation (Myhrvold Family Fellowship

Extracellular electrophysiology with close-packed recording sites: spike sorting and characterization

Advances in recording technologies now allow us to record populations of neurons simultaneously, data necessary to understand the network dynamics of the brain. Extracellular probes are fabricated with ever greater numbers of recording sites to capture the activity of increasing numbers of neurons. However, the utility of this extracellular data is limited by an initial analysis step, spike sorting, that extracts the activity patterns of individual neurons from the extracellular traces. Commonly used spike sorting methods require manual processing that limits their scalability, and errors can bias downstream analyses. Leveraging the replication of the activity from a single neuron on nearby recording sites, we designed a spike sorting method consisting of three primary steps: (1) a blind source separation algorithm to estimate the underlying source components, (2) a spike detection algorithm to find the set of spikes from each component best separated from background activity and (3) a classifier to evaluate if a set of spikes came from one individual neuron. To assess the accuracy of our method, we simulated multi-electrode array data that encompass many of the realistic variations and the sources of noise in in vivo neural data. Our method was able to extract individual simulated neurons in an automated fashion without any errors in spike assignment. Further, the number of neurons extracted increased as we increased recording site count and density. To evaluate our method in vivo, we performed both extracellular recording with our close-packed probes and a co-localized patch clamp recording, directly measuring one neuron’s ground truth set of spikes. Using this in vivo data we found that when our spike sorting method extracted the patched neuron, the spike assignment error rates were at the low end of reported error rates, and that our errors were frequently the result of failed spike detection during bursts where spike amplitude decreased into the noise. We used our in vivo data to characterize the extracellular recordings of burst activity and more generally what an extracellular electrode records. With this knowledge, we updated our spike detector to capture more burst spikes and improved our classifier based on our characterizations

Materials and neuroscience: validating tools for large-scale, high-density neural recording

Extracellular recording remains the only technique capable of measuring the activity of many neurons simultaneously with a sub-millisecond precision, in multiple brain areas, including deep structures. Nevertheless, many questions about the nature of the detected signal and the limitations/capabilities of this technique remain unanswered. The general goal of this work is to apply the methodology and concepts of materials science to answer some of the major questions surrounding extracellular recording, and thus take full advantage of this seminal technique. We start out by quantifying the effect of electrode impedance on the amplitude of measured extracellular spikes and background noise. Can we improve data quality by lowering electrode impedance? We demonstrate that if the proper recording system is used, then the impedance of a microelectrode, within the range typical of standard polytrodes (~ 0.1 to 2 MΩ), does not significantly affect a neural spike amplitude or the background noise, and therefore spike sorting. In addition to improving the performance of each electrode, increasing the number of electrodes in a single neural probe has also proven advantageous for simultaneously monitoring the activity of more neurons with better spatiotemporal resolution. How can we achieve large-scale, highdensity extracellular recordings without compromising brain tissue? Here we report the design and in vivo validation of a complementary metal–oxide–semiconductor (CMOS)-based scanning probe with 1356 electrodes arranged along approximately 8 mm of a thin shaft (50 μm thick and 100 μm wide). Additionally, given the ever-shrinking dimensions of CMOS technology, there is a drive to fabricate sub-cellular electrodes (< 10 μm). Therefore, to evaluate electrode configurations for future probe designs, several recordings from many different brain regions were performed with an ultra-dense probe containing 255 electrodes, each with a geometric area of 5 x 5 μm and a pitch of 6 μm. How can we validate neural probes with different electrode materials/configurations and different sorting algorithms? We describe a new procedure for precisely aligning two probes for in vivo “paired-recordings” such that the spiking activity of a single neuron is monitored with both a dense extracellular silicon polytrode and a juxtacellular micro-pipette. We gathered a dataset of paired-recordings, which is available online. The “ground truth” data, for which one knows exactly when a neuron in the vicinity of an extracellular probe generates an action potential, has been used for several groups to validate and quantify the performance of new algorithms to automatically detect/sort single-units

Technological challenges in the development of optogenetic closed-loop therapy approaches in epilepsy and related network disorders of the brain

Epilepsy is a chronic, neurological disorder affecting millions of people every year. The current available pharmacological and surgical treatments are lacking in overall efficacy and cause side-effects like cognitive impairment, depression, tremor, abnormal liver and kidney function. In recent years, the application of optogenetic implants have shown promise to target aberrant neuronal circuits in epilepsy with the advantage of both high spatial and temporal resolution and high cell-specificity, a feature that could tackle both the efficacy and side-effect problems in epilepsy treatment. Optrodes consist of electrodes to record local field potentials and an optical component to modulate neurons via activation of opsin expressed by these neurons. The goal of optogenetics in epilepsy is to interrupt seizure activity in its earliest state, providing a so-called closed-loop therapeutic intervention. The chronic implantation in vivo poses specific demands for the engineering of therapeutic optrodes. Enzymatic degradation and glial encapsulation of implants may compromise long-term recording and sufficient illumination of the opsin-expressing neural tissue. Engineering efforts for optimal optrode design have to be directed towards limitation of the foreign body reaction by reducing the implant’s elastic modulus and overall size, while still providing stable long-term recording and large-area illumination, and guaranteeing successful intracerebral implantation. This paper presents an overview of the challenges and recent advances in the field of electrode design, neural-tissue illumination, and neural-probe implantation, with the goal of identifying a suitable candidate to be incorporated in a therapeutic approach for long-term treatment of epilepsy patients