Accurate signal-source localization in brain slices by means of high-density microelectrode arrays

Abstract

Extracellular recordings by means of high-density microelectrode arrays (HD-MEAs) have become a powerful tool to resolve subcellular details of single neurons in active networks grown from dissociated cells. To extend the application of this technology to slice preparations, we developed models describing how extracellular signals, produced by neuronal cells in slices, are detected by microelectrode arrays. The models help to analyze and understand the electrical-potential landscape in an in vitro HD-MEA-recording scenario based on point-current sources. We employed two modeling schemes, (i) a simple analytical approach, based on the method of images (MoI), and (ii) an approach, based on finite-element methods (FEM). We compared and validated the models with large-scale, high-spatiotemporal-resolution recordings of slice preparations by means of HD-MEAs. We then developed a model-based localization algorithm and compared the performance of MoI and FEM models. Both models provided accurate localization results and a comparable and negligible systematic error, when the point source was in saline, a condition similar to cell-culture experiments. Moreover, the relative random error in the x-y-z-localization amounted only up to 4.3% for z-distances up to 200 μm from the HD-MEA surface. In tissue, the systematic errors of both, MoI and FEM models were significantly higher, and a pre-calibration was required. Nevertheless, the FEM values proved to be closer to the tissue experimental results, yielding 5.2 μm systematic mean error, compared to 22.0 μm obtained with MoI. These results suggest that the medium volume or “saline height”, the brain slice thickness and anisotropy, and the location of the reference electrode, which were included in the FEM model, considerably affect the extracellular signal and localization performance, when the signal source is at larger distance to the array. After pre-calibration, the relative random error of the z-localization in tissue was only 3% for z-distances up to 200 μm. We then applied the model and related detailed understanding of extracellular recordings to achieve an electrically-guided navigation of a stimulating micropipette, solely based on the measured HD-MEA signals, and managed to target spontaneously active neurons in an acute brain slice for electroporation.

Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level

“…Cerebellar Purkinje cells, which become GABAergic upon maturation, likely represented the main source of the extracellularly detected APs here. Using the DM-MEA, we recorded from the full brain slice simultaneously including all Purkinje cells, which has not yet been shown with other HD-MEAs 6,35 at such high spatial resolution. Moreover, we could map the Purkinje cell layer and cerebellar lobules across the full brain slice at high spatiotemporal resolution.…”

Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies

“…In a first approach, we quantified the spatial averaging in dependence of the electrode size under controlled conditions by using a stimulating point-current source or micropipette close to the electrode as model signal-source, as shown in Figure 5A,B (Supplementary Figure S1a shows the electric field of the point-current source). By using the micropipette approach, the signal source is well-defined, and we were able to examine parameters, such as the precise location of the signal source and the lateral and vertical distance between electrode and source (Obien et al, 2019). The micropipette (point-current-source) recordings were done for two electrode sizes el1 (86 μm 2 ) and el4 (11 μm 2 ) and are shown in Figure 5C.…”

“…The mathematical model used here was adapted from Obien et al (2019). The model assumed a point-current source located above an HD-MEA in a homogeneous and isotropic extracellular medium.…”

Plasticity and Adaptation in Neuromorphic Biohybrid Systems

“…Here continuous perfusion of the slice ( Panuccio et al., 2018 ) ensures osmolarity conditions. Typically, slices are held in place by a nylon mesh attached to a platinum Ω-wire, which improves tissue adhesion and mechanical stability ( Mapelli and D'Angelo, 2007 ; Obien et al., 2019 ), further aided by inducing coagulation with thrombin ( Hutzler et al., 2006 ). This arrangement is compatible with combined patch-clamp recordings where viable cells are identified for their smoothness and clear outline ( Gibb and Edwards, 1994 ).…”