A machine learning-based approach for vital node identification in complex networks
Vital node identification is the problem of finding nodes of highest importance in complex
networks. This problem has crucial applications in various contexts such as viral marketing …
networks. This problem has crucial applications in various contexts such as viral marketing …
Signal Processing for Brain–Computer Interfaces: A review and current perspectives
Brain–computer interfaces (BCIs) employ neurophysiological signals derived from the brain
to control computers or external devices. By enhancing or replacing human peripheral …
to control computers or external devices. By enhancing or replacing human peripheral …
From end to end: Gaining, sorting, and employing high-density neural single unit recordings
The meaning behind neural single unit activity has constantly been a challenge, so it will
persist in the foreseeable future. As one of the most sourced strategies, detecting neural …
persist in the foreseeable future. As one of the most sourced strategies, detecting neural …
A study of autoencoders as a feature extraction technique for spike sorting
Spike sorting is the process of grouping spikes of distinct neurons into their respective
clusters. Most frequently, this grouping is performed by relying on the similarity of features …
clusters. Most frequently, this grouping is performed by relying on the similarity of features …
A fully automatic multichannel neural spike sorting algorithm with spike reduction and positional feature
Objective: The sorting of neural spike data recorded by multichannel and high channel
neural probes such as Neuropixels, especially in real-time, remains a significant technical …
neural probes such as Neuropixels, especially in real-time, remains a significant technical …
Technical survey of end-to-end signal processing in BCIs using invasive MEAs
A Erbslöh, L Buron, Z Ur-Rehman… - Journal of Neural …, 2024 - iopscience.iop.org
Modern brain-computer interfaces and neural implants allow interaction between the tissue,
the user and the environment, where people suffer from neurodegenerative diseases or …
the user and the environment, where people suffer from neurodegenerative diseases or …
DualSort: online spike sorting with a running neural network
Objective. Spike sorting, ie the detection and separation of measured action potentials from
different extracellularly recorded neurons, remains one of the bottlenecks in deciphering the …
different extracellularly recorded neurons, remains one of the bottlenecks in deciphering the …
Vital node identification in complex networks using a machine learning-based approach
Vital node identification is the problem of finding nodes of highest importance in complex
networks. This problem has crucial applications in various contexts such as viral marketing …
networks. This problem has crucial applications in various contexts such as viral marketing …
Deep learning-based spike sorting: a survey
Objective. Deep learning is increasingly permeating neuroscience, leading to a rise in signal-
processing applications for extracellular recordings. These signals capture the activity of …
processing applications for extracellular recordings. These signals capture the activity of …
NeuSort: an automatic adaptive spike sorting approach with neuromorphic models
Objective. Spike sorting, a critical step in neural data processing, aims to classify spiking
events from single electrode recordings based on different waveforms. This study aims to …
events from single electrode recordings based on different waveforms. This study aims to …