Microelectronics, bioinformatics and neurocomputation for massive neuronal recordings in brain circuits with large scale multielectrode array probes

Deciphering neural network function in health and disease requires recording from many active
neurons simultaneously. Developing approaches to increase their numbers is a major
neurotechnological challenge. Parallel to recent advances in optical Ca 2+ imaging, an emerging
approach consists in adopting complementary-metal-oxide-semiconductor (CMOS) technology to
realize MultiElectrode Array (MEA) devices. By implementing signal conditioning and multiplexing
circuits, these devices allow nowadays to record from several thousands of single neurons at sub-
millisecond temporal resolution. At the same time, these recordings generate very large data
streams which become challenging to analyze.
Here, at first we shortly review the major approaches developed for data management and analysis
for conventional, low-resolution MEAs. We highlight how conventional computational tools cannot
be easily up-scaled to very large electrode array recordings, and custom bioinformatics tools are an
emerging need in this field. We then introduce a novel approach adapted for the acquisition,
compression and analysis of extracellular signals acquired simultaneously from 4096 electrodes
with CMOS MEAs. Finally, as a case study, we describe how this novel large scale recording platform
was used to record and analyze extracellular spikes from the ganglion cell layer in the wholemount
retina at pan-retinal scale following patterned light stimulation.