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Microelectrodes

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Information sparseness in cortical microelectrode channels while decoding movement direction using an artificial neural network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Implanted microelectrode arrays can directly pick up electrode signals from the primary motor cortex (M1) during movement, and brain-machine interfaces (BMIs) can decode these signals to predict the directions of contemporaneous movements. However, i...

Robot-assisted implantation of a microelectrode array in the occipital lobe as a visual prosthesis: technical note.

Journal of neurosurgery
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...

Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains.

PLoS computational biology
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...

Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Journal of neural engineering
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...

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
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...

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)
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...

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

Scientific reports
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...

Repetitive training enhances the pattern recognition capability of cultured neural networks.

PLoS computational biology
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...

Virtual white matter: a novel system for cross-dish neural interaction and modulation.

Journal of neural engineering
. Biological neural networks (BNNs) are characterized by complex interregional connectivity, allowing for seamless communication between different brain regions.models traditionally consist of single-dish neural cultures that cannot recapitulate the ...