AIMC Topic: Microelectrodes

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Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data.

Scientific reports Apr 30, 2025
Biosensors, such as microelectrode arrays that record in vitro neuronal activity, provide powerful platforms for studying neuroactive substances. This study presents a machine learning workflow to analyze drug-induced changes in neuronal biosensor da...
Machine Learning Animals Bicuculline Neurons Nerve Net Microelectrodes Biosensing Techniques Rats Action Potentials
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Repetitive training enhances the pattern recognition capability of cultured neural networks.

PLoS computational biology Apr 22, 2025
Cultured neural networks in vitro have demonstrated the biocomputing capability to recognize patterns. However, the underlying mechanisms behind information processing and pattern recognition remain less understood. Here, we developed an in vitro neu...
Pattern Recognition, Physiological Pattern Recognition, Automated Nerve Net Microelectrodes Neural Networks, Computer Rats Animals Neurons Cells, Cultured Computational Biology
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A hybrid bioelectronic retina-probe interface for object recognition.

Biosensors & bioelectronics Mar 24, 2025
Retina converts light stimuli into spike firings, encoding abundant visual information critical for both fundamental studies of the visual system and therapies for visual diseases. However, probing these spikes directly from the retina is hindered by...
Humans Machine Learning Light Retina Neurons Animals Microelectrodes Biosensing Techniques Equipment Design
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Intelligent in-cell electrophysiology: Reconstructing intracellular action potentials using a physics-informed deep learning model trained on nanoelectrode array recordings.

Nature communications Jan 14, 2025
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 ...
Animals Deep Learning Action Potentials Humans Microelectrodes Electrophysiological Phenomena Nanotechnology Myocytes, Cardiac Electrophysiology
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Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signaling in a Model of Niemann-Pick Disease Type C.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Sep 28, 2024
Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle su...
Microelectrodes Niemann-Pick Disease, Type C Algorithms Animals Rats Graphite Hippocampus Neurons Microscopy Machine Learning
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Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Journal of neural engineering Jul 29, 2024
Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupli...
Humans Action Potentials Parkinson Disease Neurons Male Deep Brain Stimulation Neural Networks, Computer Middle Aged Microelectrodes Models, Neurological Female Aged
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Generalisation capabilities of machine-learning algorithms for the detection of the subthalamic nucleus in micro-electrode recordings.

International journal of computer assisted radiology and surgery Jul 1, 2024
PURPOSE: Micro-electrode recordings (MERs) are a key intra-operative modality used during deep brain stimulation (DBS) electrode implantation, which allow for a trained neurophysiologist to infer the anatomy in which the electrode is placed. As DBS t...
Electrodes, Implanted Subthalamic Nucleus Algorithms Deep Brain Stimulation Microelectrodes Humans Machine Learning
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Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains.

PLoS computational biology Apr 29, 2024
Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large...
Action Potentials Neurons Neural Networks, Computer Synapses Computational Biology Machine Learning Patch-Clamp Techniques Nerve Net Rats Algorithms Microelectrodes Animals Models, Neurological
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Robot-assisted implantation of a microelectrode array in the occipital lobe as a visual prosthesis: technical note.

Journal of neurosurgery Oct 27, 2023
The prospect of direct interaction between the brain and computers has been investigated in recent decades, revealing several potential applications. One of these is sight restoration in profoundly blind people, which is based on the ability to elici...
Humans Animals Visual Cortex Robotics Prosthesis Implantation Electrodes, Implanted Microelectrodes Visual Prosthesis
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Raster plots machine learning to predict the seizure liability of drugs and to identify drugs.

Scientific reports Feb 10, 2022
In vitro microelectrode array (MEA) assessment using human induced pluripotent stem cell (iPSC)-derived neurons holds promise as a method of seizure and toxicity evaluation. However, there are still issues surrounding the analysis methods used to pre...
Induced Pluripotent Stem Cells Forecasting Humans Adult Cells, Cultured Neural Networks, Computer Drug-Related Side Effects and Adverse Reactions Pharmaceutical Preparations Male Female Machine Learning Toxicity Tests Liability, Legal Middle Aged Dose-Response Relationship, Drug Microelectrodes Seizures
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