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Extracellular Recording of Entire Neural Networks Using a Dual-Mode Microelectrode Array With 19 584 Electrodes and High SNR

Xinyue Yuan, Andreas Hierlemann, Urs Frey

2021IEEE Journal of Solid-State Circuits50 citationsDOIOpen Access PDF

Abstract

Electrophysiological research on neural networks and their activity focuses on the recording and analysis of large data sets that include information of thousands of neurons. CMOS microelectrode arrays (MEAs) feature thousands of electrodes at a spatial resolution on the scale of single cells and are, therefore, ideal tools to support neural-network research. Moreover, they offer high spatio-temporal resolution and signal-to-noise ratio (SNR) to capture all features and subcellular-resolution details of neuronal signaling. Here, we present a dual-mode (DM) MEA, which enables simultaneous: 1) full-frame readout from all electrodes and 2) high-SNR readout from an arbitrarily selectable subset of electrodes. The DM-MEA includes 19 584 electrodes, 19 584 full-frame recording channels with noise levels of 10.4 μV <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> in the action potential (AP) frequency band (300 Hz-5 kHz), 246 low-noise recording channels with noise levels of 3.0 μV <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> in the AP band and eight stimulation units. The capacity to simultaneously perform full-frame and high-SNR recordings endows the presented DM-MEA with great flexibility for various applications in neuroscience and pharmacology.

Topics & Concepts

MicroelectrodeNoise (video)Multielectrode arrayComputer scienceElectrodeFrame (networking)ElectrophysiologyArtificial intelligencePhysicsNeuroscienceTelecommunicationsBiologyQuantum mechanicsImage (mathematics)Neuroscience and Neural EngineeringAdvanced Memory and Neural ComputingNeural dynamics and brain function