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

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

Research output: Contribution to journalArticlepeer-review

85 Scopus citations


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 32 kHz 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.

Original languageEnglish (US)
Pages (from-to)185-192
Number of pages8
JournalJournal of Neuroscience Methods
Issue number1
StatePublished - May 30 2009


  • Cyclic redundancy codes
  • Data compression
  • Data encryption
  • EEG analysis
  • Multiscale electrophysiology format
  • Quantitative analysis
  • Range encoding

ASJC Scopus subject areas

  • Neuroscience(all)


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