Literature DB >> 19427545

Large-scale electrophysiology: acquisition, compression, encryption, and storage of big data.

Benjamin H Brinkmann1, Mark R Bower, Keith A Stengel, Gregory A Worrell, Matt Stead.   

Abstract

The use of large-scale electrophysiology to obtain high spatiotemporal resolution brain recordings (>100 channels) capable of probing the range of neural activity from local field potential oscillations to single-neuron action potentials presents new challenges for data acquisition, storage, and analysis. Our group is currently performing continuous, long-term electrophysiological recordings in human subjects undergoing evaluation for epilepsy surgery using hybrid intracranial electrodes composed of up to 320 micro- and clinical macroelectrode arrays. DC-capable amplifiers, sampling at 32kHz per channel with 18-bits of A/D resolution are capable of resolving extracellular voltages spanning single-neuron action potentials, high frequency oscillations, and high amplitude ultra-slow activity, but this approach generates 3 terabytes of data per day (at 4 bytes per sample) using current data formats. Data compression can provide several practical benefits, but only if data can be compressed and appended to files in real-time in a format that allows random access to data segments of varying size. Here we describe a state-of-the-art, scalable, electrophysiology platform designed for acquisition, compression, encryption, and storage of large-scale data. Data are stored in a file format that incorporates lossless data compression using range-encoded differences, a 32-bit cyclically redundant checksum to ensure data integrity, and 128-bit encryption for protection of patient information.

Entities:  

Mesh:

Year:  2009        PMID: 19427545      PMCID: PMC2720128          DOI: 10.1016/j.jneumeth.2009.03.022

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  20 in total

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2.  A simple format for exchange of digitized polygraphic recordings.

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3.  Time-frequency spectral estimation of multichannel EEG using the Auto-SLEX method.

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Review 4.  Large-scale recording of neuronal ensembles.

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5.  European data format 'plus' (EDF+), an EDF alike standard format for the exchange of physiological data.

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6.  EEG data compression techniques.

Authors:  G Antoniol; P Tonella
Journal:  IEEE Trans Biomed Eng       Date:  1997-02       Impact factor: 4.538

7.  Extensible biosignal (EBS) file format: simple method for EEG data exchange.

Authors:  G Hellmann; M Kuhn; M Prosch; M Spreng
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8.  High-frequency oscillations and seizure generation in neocortical epilepsy.

Authors:  Greg A Worrell; Landi Parish; Stephen D Cranstoun; Rachel Jonas; Gordon Baltuch; Brian Litt
Journal:  Brain       Date:  2004-05-20       Impact factor: 13.501

9.  Internally generated reactivation of single neurons in human hippocampus during free recall.

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Authors: 
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  38 in total

1.  Synchrony in normal and focal epileptic brain: the seizure onset zone is functionally disconnected.

Authors:  Christopher P Warren; Sanqing Hu; Matt Stead; Benjamin H Brinkmann; Mark R Bower; Gregory A Worrell
Journal:  J Neurophysiol       Date:  2010-10-06       Impact factor: 2.714

2.  Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

Authors:  Yogatheesan Varatharajah; Brent Berry; Jan Cimbalnik; Vaclav Kremen; Jamie Van Gompel; Matt Stead; Benjamin Brinkmann; Ravishankar Iyer; Gregory Worrell
Journal:  J Neural Eng       Date:  2018-06-01       Impact factor: 5.379

3.  An Enhanced Visualization Method to Aid Behavioral Trajectory Pattern Recognition Infrastructure for Big Longitudinal Data.

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Journal:  IEEE Trans Big Data       Date:  2017-01-16

Review 4.  Recording and analysis techniques for high-frequency oscillations.

Authors:  G A Worrell; K Jerbi; K Kobayashi; J M Lina; R Zelmann; M Le Van Quyen
Journal:  Prog Neurobiol       Date:  2012-03-07       Impact factor: 11.685

5.  A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task.

Authors:  N Chandravadia; D Liang; A G P Schjetnan; A Carlson; M Faraut; J M Chung; C M Reed; B Dichter; U Maoz; S K Kalia; T A Valiante; A N Mamelak; U Rutishauser
Journal:  Sci Data       Date:  2020-03-04       Impact factor: 6.444

6.  Network oscillations modulate interictal epileptiform spike rate during human memory.

Authors:  Joseph Y Matsumoto; Matt Stead; Michal T Kucewicz; Andrew J Matsumoto; Pierce A Peters; Benjamin H Brinkmann; Jane C Danstrom; Stephan J Goerss; W Richard Marsh; Fred B Meyer; Gregory A Worrell
Journal:  Brain       Date:  2013-06-25       Impact factor: 13.501

7.  Chaos based encryption system for encrypting electroencephalogram signals.

Authors:  Chin-Feng Lin; Shun-Han Shih; Jin-De Zhu
Journal:  J Med Syst       Date:  2014-04-15       Impact factor: 4.460

8.  Metadata and annotations for multi-scale electrophysiological data.

Authors:  Mark R Bower; Matt Stead; Benjamin H Brinkmann; Kevin Dufendach; Gregory A Worrell
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

9.  A low-cost multielectrode system for data acquisition enabling real-time closed-loop processing with rapid recovery from stimulation artifacts.

Authors:  John D Rolston; Robert E Gross; Steve M Potter
Journal:  Front Neuroeng       Date:  2009-07-23

10.  Intravenous recording of intracranial, broadband EEG.

Authors:  Mark R Bower; Matt Stead; Jamie J Van Gompel; Regina S Bower; Vlastimil Sulc; Samuel J Asirvatham; Gregory A Worrell
Journal:  J Neurosci Methods       Date:  2013-01-08       Impact factor: 2.390

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