Literature DB >> 25904712

Generalized analog thresholding for spike acquisition at ultralow sampling rates.

Bryan D He1, Alex Wein2, Lav R Varshney3, Julius Kusuma4, Andrew G Richardson5, Lakshminarayan Srinivasan6.   

Abstract

Efficient spike acquisition techniques are needed to bridge the divide from creating large multielectrode arrays (MEA) to achieving whole-cortex electrophysiology. In this paper, we introduce generalized analog thresholding (gAT), which achieves millisecond temporal resolution with sampling rates as low as 10 Hz. Consider the torrent of data from a single 1,000-channel MEA, which would generate more than 3 GB/min using standard 30-kHz Nyquist sampling. Recent neural signal processing methods based on compressive sensing still require Nyquist sampling as a first step and use iterative methods to reconstruct spikes. Analog thresholding (AT) remains the best existing alternative, where spike waveforms are passed through an analog comparator and sampled at 1 kHz, with instant spike reconstruction. By generalizing AT, the new method reduces sampling rates another order of magnitude, detects more than one spike per interval, and reconstructs spike width. Unlike compressive sensing, the new method reveals a simple closed-form solution to achieve instant (noniterative) spike reconstruction. The base method is already robust to hardware nonidealities, including realistic quantization error and integration noise. Because it achieves these considerable specifications using hardware-friendly components like integrators and comparators, generalized AT could translate large-scale MEAs into implantable devices for scientific investigation and medical technology.
Copyright © 2015 the American Physiological Society.

Keywords:  brain initiative; finite rate of innovation; multielectrode arrays; spike acquisition; sub-Nyquist

Mesh:

Year:  2015        PMID: 25904712      PMCID: PMC4518723          DOI: 10.1152/jn.00623.2014

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  18 in total

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Authors:  Wilson Truccolo; Uri T Eden; Matthew R Fellows; John P Donoghue; Emery N Brown
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4.  A systems approach for data compression and latency reduction in cortically controlled brain machine interfaces.

Authors:  Karim G Oweiss
Journal:  IEEE Trans Biomed Eng       Date:  2006-07       Impact factor: 4.538

5.  An energy-efficient micropower neural recording amplifier.

Authors:  W Wattanapanitch; M Fee; R Sarpeshkar
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2007-06       Impact factor: 3.833

Review 6.  Multi-electrode array technologies for neuroscience and cardiology.

Authors:  Micha E Spira; Aviad Hai
Journal:  Nat Nanotechnol       Date:  2013-02       Impact factor: 39.213

7.  Multi-neuronal signals from the retina: acquisition and analysis.

Authors:  M Meister; J Pine; D A Baylor
Journal:  J Neurosci Methods       Date:  1994-01       Impact factor: 2.390

8.  Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex.

Authors:  C M Gray; P E Maldonado; M Wilson; B McNaughton
Journal:  J Neurosci Methods       Date:  1995-12       Impact factor: 2.390

9.  A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging.

Authors:  Jon Oñativia; Simon R Schultz; Pier Luigi Dragotti
Journal:  J Neural Eng       Date:  2013-07-17       Impact factor: 5.379

10.  Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys.

Authors:  David A Schwarz; Mikhail A Lebedev; Timothy L Hanson; Dragan F Dimitrov; Gary Lehew; Jim Meloy; Sankaranarayani Rajangam; Vivek Subramanian; Peter J Ifft; Zheng Li; Arjun Ramakrishnan; Andrew Tate; Katie Z Zhuang; Miguel A L Nicolelis
Journal:  Nat Methods       Date:  2014-04-28       Impact factor: 28.547

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