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Abstract Intracellular access with high spatiotemporal resolution can enhance the understanding of how neurons or cardiomyocytes regulate and orchestrate network activity and how this activity can be affected with pharmacology or other interventional modalities. Nanoscale devices often employ electroporation to transiently permeate the cell membrane and record intracellular potentials, which tend to decrease rapidly with time. Here, one reports innovative scalable, vertical, ultrasharp nanowire arrays that are individually addressable to enable long‐term, native recordings of intracellular potentials. One reports electrophysiological recordings that are indicative of intracellular access from 3D tissue‐like networks of neurons and cardiomyocytes across recording days and that do not decrease to extracellular amplitudes for the duration of the recording of several minutes. The findings are validated with cross‐sectional microscopy, pharmacology, and electrical interventions. The experiments and simulations demonstrate that the individual electrical addressability of nanowires is necessary for high‐fidelity intracellular electrophysiological recordings. This study advances the understanding of and control over high‐quality multichannel intracellular recordings and paves the way toward predictive, high‐throughput, and low‐cost electrophysiological drug screening platforms.
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This content will become publicly available on May 1, 2025
Error Function Optimization to Compare Neural Activity and Train Blended Rhythmic Networks
We present a novel set of quantitative measures for “likeness” (error function) designed to alleviate the time-consuming and subjective nature of manually comparing biological recordings from electrophysiological experiments with the outcomes of their mathematical models. Our innovative “blended” system approach offers an objective, high-throughput, and computationally efficient method for comparing biological and mathematical models. This approach involves using voltage recordings of biological neurons to drive and train mathematical models, facilitating the derivation of the error function for further parameter optimization. Our calibration process incorporates measurements such as action potential (AP) frequency, voltage moving average, voltage envelopes, and the probability of post-synaptic channels. To assess the effectiveness of our method, we utilized the sea slug Melibe leonina swim central pattern generator (CPG) as our model circuit and conducted electrophysiological experiments with TTX to isolate CPG interneurons. During the comparison of biological recordings and mathematically simulated neurons, we performed a grid search of inhibitory and excitatory synapse conductance. Our findings indicate that a weighted sum of simple functions is essential for comprehensively capturing a neuron’s rhythmic activity. Overall, our study suggests that our blended system approach holds promise for enabling objective and high-throughput comparisons between biological and mathematical models, offering significant potential for advancing research in neural circuitry and related fields.
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- Award ID(s):
- 1455527
- PAR ID:
- 10577614
- Publisher / Repository:
- Brain Sciences
- Date Published:
- Journal Name:
- Brain Sciences
- Volume:
- 14
- Issue:
- 5
- ISSN:
- 2076-3425
- Page Range / eLocation ID:
- 468
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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