AIMC Topic: Electrophysiological Phenomena

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A Machine Learning-Driven Electrophysiological Platform for Real-Time Tumor-Neural Interaction Analysis and Modulation.

Nature communications
Neural-tumor electrophysiology-marked by pathological membrane potentials and ion channel dysregulation-emerges as actionable targets to curb tumor aggression. Yet, how neural-driven bioelectrical crosstalk dynamically regulates tumors within functio...

Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex.

Neuroinformatics
Accurate classification of neuronal cell types is essential for understanding brain organization, but multimodal neuron datasets are scarce and strongly imbalanced across subclasses. We present a benchmark of synthetic data augmentation methods for p...

An electrical pulse artifact signal for estimating arterial blood pressure: a proof-of-concept study.

Physiological measurement
Hypertension is a leading cause of mortality worldwide, for which myriad treatment options are available. It is widely considered that continuous measurement of arterial blood pressure (BP) could improve the treatment of hypertension; however, chroni...

Advances in large-scale electrophysiology with high-density microelectrode arrays.

Lab on a chip
A detailed functional characterization of electrogenic cells, such as neurons and cardiomyocytes, by means of high-density microelectrode arrays (HD-MEAs) has emerged as a powerful approach for inferring cellular phenotypes and elucidating fundamenta...

Enhanced electrophysiological recordings in acute brain slices, spheroids, and organoids using 3D high-density multielectrode arrays.

PloS one
Recent advances in three-dimensional (3D) biological brain models in vitro and ex vivo are creating new opportunities to understand the complexity of neural networks but pose the technological challenge of obtaining high-throughput recordings of elec...

Determination of intrinsic cellular electrical and mechanical properties using micro/nano manipulation techniques.

Soft matter
Single-mode biophysical fingerprints have specific overlap when cell heterogeneity is analyzed. The cross-sensitivity between these parameters results in significant fuzzy intervals in cell phenotype classification based on one-dimensional features, ...

Intelligent in-cell electrophysiology: Reconstructing intracellular action potentials using a physics-informed deep learning model trained on nanoelectrode array recordings.

Nature communications
Intracellular electrophysiology is essential in neuroscience, cardiology, and pharmacology for studying cells' electrical properties. Traditional methods like patch-clamp are precise but low-throughput and invasive. Nanoelectrode Arrays (NEAs) offer ...

Machine learning-assisted implantable plant electrophysiology microneedle sensor for plant stress monitoring.

Biosensors & bioelectronics
Plant electrical signals serve as a medium for long-distance signal transmission and are intricately linked to plant stress responses. High-fidelity acquisition and analysis of plant electrophysiological signals contribute to early stress identificat...

The evolution of patch-clamp electrophysiology: Robotic, multiplex, and dynamic.

Molecular pharmacology
The patch-clamp technique has been the gold standard for analysis of excitable cells. Since its development in the 1980s, it has contributed immensely to our understanding of neurons, muscle cells, and cardiomyocytes and the ion channels and receptor...

Sensorimotor control of robots mediated by electrophysiological measurements of fungal mycelia.

Science robotics
Living tissues are still far from being used as practical components in biohybrid robots because of limitations in life span, sensitivity to environmental factors, and stringent culture procedures. Here, we introduce fungal mycelia as an easy-to-use ...