QSpike tools: a generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays

Abstract

Micro-Electrode Arrays (MEAs) have emerged as a mature technique to investigate brain (dys)functions in vivo and in in vitro animal models. Often referred to as "smart" Petri dishes, MEAs have demonstrated a great potential particularly for medium-throughput studies in vitro, both in academic and pharmaceutical industrial contexts. Enabling rapid comparison of ionic/pharmacological/genetic manipulations with control conditions, MEAs are employed to screen compounds by monitoring non-invasively the spontaneous and evoked neuronal electrical activity in longitudinal studies, with relatively inexpensive equipment. However, in order to acquire sufficient statistical significance, recordings last up to tens of minutes and generate large amount of raw data (e.g., 60 channels/MEA, 16 bits A/D conversion, 20 kHz sampling rate: approximately 8 GB/MEA,h uncompressed). Thus, when the experimental conditions to be tested are numerous, the availability of fast, standardized, and automated signal preprocessing becomes pivotal for any subsequent analysis and data archiving. To this aim, we developed an in-house cloud-computing system, named QSpike Tools, where CPU-intensive operations, required for preprocessing of each recorded channel (e.g., filtering, multi-unit activity detection, spike-sorting, etc.), are decomposed and batch-queued to a multi-core architecture or to a computers cluster. With the commercial availability of new and inexpensive high-density MEAs, we believe that disseminating QSpike Tools might facilitate its wide adoption and customization, and inspire the creation of community-supported cloud-computing facilities for MEAs users.

α-Synuclein strains cause distinct synucleinopathies after local and systemic administration

“…This allowed us to monitor simultaneously, chronically, and non-invasively the neuronal electrical activity from up to 60 locations within the very same culture. MEA recordings were analysed off-line by QSpikeTools 36 . Briefly, the extracellular electric fields were monitored from the 59 independent electrodes in each MEAs were sampled at 25 kHz per channel, 1,2003 amplified, bandpass-filtered (200-3,000 Hz), and digitally recorded for 30 min every day, up to 6 days following the bath application of a-SYN, dissolved in culture medium with distinct concentrations (that is, 0.1, 0.5, and 1 mM).…”

Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays

“…The objective of the new tool is not to re-create completely new analysis frameworks but rather to complement and speed-up existing ones. For this reason the processing steps performed here match closely the ones from the QSpike tools [2], a previously released and freely available software package. The results from the pre-processing stages of both tools are interchangeable, so that the available report generating facilities provided by the QSpike tools can be used without major modifications with the output data from the new tool.…”

“…2 shows the different data processing steps performed by the tool. Except by the generalised concept of input and output streams and block processing (described above), these steps are exactly the same as the ones performed by the original QSpike tools implementation in Matlab [2]. When a single data block is used the results of both tools is exactly the same.…”

“…Typical processing pipelines of MEA data recordings usually involve a filtering step followed by a spike detection and artefact removal algorithm [2]. These pre-processing steps are then typically followed by a spike sorting algorithm and/or other post-processing steps, such as burst-detection in the case of cultured cells [3].…”

“…These pre-processing steps are then typically followed by a spike sorting algorithm and/or other post-processing steps, such as burst-detection in the case of cultured cells [3]. In order to simplify and automatise these processing steps different software packages were proposed over the years [4], [5], [2]. These pioneering tools, however, were designed primarily with ease of use and not performance in mind, or were designed during a time were parallel hardware was not so prevalent as it is today.…”