Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays

Abstract

Abstract-Technological advances of Multielectrode Arrays (MEAs) used for multi-site, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future.In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs or GPUs.Our tool builds on and complements existing MEA data analysis packages. It can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.

A Brief History of Simulation Neuroscience

“…About 60 years ago, implantable microelectrodes were developed to record from single neurons in a freely behaving ground squirrel during 4 days (Strumwasser, 1958). Nowadays, penetrating multi-electrode arrays (MEAs) can record from individual neurons simultaneously at multiple sites to study distributed neural circuits (Gehring et al, 2015; Maccione et al, 2015), and mesh nanoelectronics, which are tissue-like electronics consisting of a macroporous mesh structure with addressable electronic devices, have achieved stable single-neuron level chronic recording and stimulation in freely behaving animals for at least 8 months (Fu et al, 2016). Yet, even so, the huge number of neurons and the complexity of neural interactions preclude the high-density parallel recordings of the whole mammalian brain.…”