High-density microelectrode array recordings and real-time spike sorting for closed-loop experiments: an emerging technology to study neural plasticity

Abstract

Understanding plasticity of neural networks is a key to comprehending their development and function. A powerful technique to study neural plasticity includes recording and control of pre- and post-synaptic neural activity, e.g., by using simultaneous intracellular recording and stimulation of several neurons. Intracellular recording is, however, a demanding technique and has its limitations in that only a small number of neurons can be stimulated and recorded from at the same time. Extracellular techniques offer the possibility to simultaneously record from larger numbers of neurons with relative ease, at the expenses of increased efforts to sort out single neuronal activities from the recorded mixture, which is a time consuming and error prone step, referred to as spike sorting. In this mini-review, we describe recent technological developments in two separate fields, namely CMOS-based high-density microelectrode arrays, which also allow for extracellular stimulation of neurons, and real-time spike sorting. We argue that these techniques, when combined, will provide a powerful tool to study plasticity in neural networks consisting of several thousand neurons in vitro.

Conferring flexibility and reconfigurability to a 26,400 microelectrode CMOS array for high throughput neural recordings

“…Once an area of interest has been identified, as for example the one marked with a red dashed square in Figure 4a, a high-density configuration of electrodes (529) has been recruited in this area to perform subcellular-resolution recording on a 400×400 µm 2 patch (2% of sensor area). This facilitates the assignment of different APs to the respective neurons in this area through the application of spike sorting methods [11]. For Figure 4: Two electrode configurations used for recordings from cultured rat cortical neurons.…”

Highly integrated CMOS microsystems to interface with neurons at subcellular resolution

“…Figure 5 shows network recordings. 2000 individual single cells were identified through spike sorting of HD-MEA data (25)(26)(27), and the color-coding indicates the action potential spike amplitudes. The fluorescence image of transfected cells of the same culture shows clusters of neurons and tracks of neurite bundles.…”

Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials

“…Recently, more advanced high density arrays were used to study the network activity [48,64] . Network variabilities during circuit functions were studied using multiple-electrode array recordings [13] .…”