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Journal ArticleDOI

An implantable 455-active-electrode 52-channel CMOS neural probe

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TLDR
The main tradeoff in neural probe design is between minimizing the probe dimensions and achieving high spatial resolution using large arrays of small recording sites.
Abstract
Neural probes have become the most important tool for enabling neuroscientists to place microelectrode sensors close to individual neurons and to monitor their activity in vivo. With such devices, it is possible to perform acute or chronic extracellular recordings of electrical activity from a single neuron or from groups of neurons. After the many developments in neural implants, it has become clear that large arrays of electrodes are desirable to further investigate the activity performed by complex neural networks. Therefore, in this paper, we propose a CMOS neural probe containing 455 active electrodes in the probe shank (100 μm wide, 10 mm long, and 50 μm thick) and 52 simultaneous readout channels in the probe body (2.9 × 3.3 mm2). In situ amplification under each electrode enables low-impedance interconnection lines, regardless of the electrode impedance, with a residual crosstalk of -44.8 dB. This design has been implemented in a 0.18-μm standard CMOS technology, with additional CMOS-compatible post-processing performed at wafer level to define the electrodes and the probe outline. In this architecture, the analog front-end achieves an input-referred noise of 3.2 μVrms and an NEF of 3.08. The power consumption of the core circuit is 949.8 μW, while the total power consumption is 1.45 mW. The high-density active-electrode array in this neural probe allows for the massive recording of neural activity. In vivo measurements demonstrate successful simultaneous recordings from many individual cells.

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Citations
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Journal ArticleDOI

Revealing neuronal function through microelectrode array recordings

TL;DR: The ongoing advancements in microelectrode technology are introduced, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry.
Journal ArticleDOI

Materials for flexible bioelectronic systems as chronic neural interfaces.

TL;DR: This Review provides an overview of the advances in materials and device design that are enabling the realization of implantable electronic interfaces for long-term, multiplexed recording and stimulation of the brain and nervous system.
Journal ArticleDOI

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels

TL;DR: A CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks, and is demonstrated for large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.
Journal ArticleDOI

Close-Packed Silicon Microelectrodes for Scalable Spatially Oversampled Neural Recording

TL;DR: The design and implementation of close-packed silicon microelectrodes to enable spatially oversampled recording of neural activity in a scalable fashion are presented and performed in the live mammalian brain to illustrate the spatial oversampling potential of closely packed electrode sites.
Journal ArticleDOI

State-of-the-art MEMS and microsystem tools for brain research

TL;DR: The state-of-the-art in recording and stimulation tools for brain research is reviewed, and some of the most significant technology trends shaping the field of neurotechnology are discussed.
References
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Book

Design of Analog CMOS Integrated Circuits

Behzad Razavi
TL;DR: The analysis and design techniques of CMOS integrated circuits that practicing engineers need to master to succeed can be found in this article, where the authors describe the thought process behind each circuit topology, but also consider the rationale behind each modification.
Journal ArticleDOI

Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering

TL;DR: A new method for detecting and sorting spikes from multiunit recordings that combines the wave let transform with super paramagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions is introduced.
Journal ArticleDOI

Large-scale recording of neuronal ensembles

TL;DR: Large-scale recordings from neuronal ensembles now offer the opportunity to test competing theoretical frameworks and 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.
Journal ArticleDOI

A low-power low-noise CMOS amplifier for neural recording applications

TL;DR: In this article, a low-noise low-power biosignal amplifiers capable of amplifying signals in the millihertz-to-kilohertz range while rejecting large dc offsets generated at the electrode-tissue interface is presented.
Journal ArticleDOI

Accuracy of Tetrode Spike Separation as Determined by Simultaneous Intracellular and Extracellular Measurements

TL;DR: It is hypothesized that automatic spike-sorting algorithms have the potential to significantly lower error rates, and implementation of a semi-automatic classification system confirms this suggestion, reducing errors close to the estimated optimum, in the range 0-8%.
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