Papers Spike Sorting
“Spike Sorting” 태그가 달린 논문 51편 · 필터 해제
Scalable 49-Channel Neural Recorder with an Event-Driven Ramp ADC and PCA Compression in 28 nm CMOS
Neural interfaces advance neuroscience research and therapeutic innovations by accurately measuring neuronal activity. However, recording raw data from numerous neurons results in substantial amount of data and poses cha…
Spike SortingA Real-time and Hardware Efficient Artfecat-free Spike Sorting Using Deep Spike Detection
Spike sorting is a valuable tool in understanding brain regions. It assigns detected spike waveforms to their origins, helping to research the mechanism of the human brain and the development of implantable brain-machine…
channel selectionSpike SortingSpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm
Objective: Spike sorting is a fundamental step in analysing extracellular recordings, enabling the isolation of single-neuron activity. However, it remains a challenging problem because extracellular traces mix overlappi…
ClusteringComputational EfficiencySpike SortingFS-SS: Few-Shot Learning for Fast and Accurate Spike Sorting of High-channel Count Probes
There is a need for fast adaptation in spike sorting algorithms to implement brain-machine interface (BMIs) in different applications. Learning and adapting the functionality of the sorting process in real-time can signi…
Few-Shot LearningMeta-LearningSpike SortingPulse Processing -- Overview and Challenges
The detection of irregularly spaced pulses of non-negligible width is a fascinating yet under-explored topic in signal processing. It sits adjacent to other core topics such as radar and symbol detection yet has its own …
compressed sensingDiagnosticPositionSpike SortingSimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation
Spike sorting is an essential process in neural recording, which identifies and separates electrical signals from individual neurons recorded by electrodes in the brain, enabling researchers to study how specific neurons…
Spike SortingZero-shot GeneralizationL-Sort: On-chip Spike Sorting with Efficient Median-of-Median Detection and Localization-based Clustering
Spike sorting is a critical process for decoding large-scale neural activity from extracellular recordings. The advancement of neural probes facilitates the recording of a high number of neurons with an increase in chann…
ClusteringSpike SortingInferring collective synchrony observing spiking of one or several neurons
We tackle a quantification of synchrony in a large ensemble of interacting neurons from the observation of spiking events. In a simulation study, we efficiently infer the synchrony level in a neuronal population from a p…
Spike SortingE-Sort: Empowering End-to-end Neural Network for Multi-channel Spike Sorting with Transfer Learning and Fast Post-processing
Decoding extracellular recordings is a crucial task in electrophysiology and brain-computer interfaces. Spike sorting, which distinguishes spikes and their putative neurons from extracellular recordings, becomes computat…
Few-Shot LearningSpike SortingTransfer Learning68-Channel Highly-Integrated Neural Signal Processing PSoC with On-Chip Feature Extraction, Compression, and Hardware Accelerators for Neuroprosthetics in 22nm FDSOI
Multi-channel electrophysiology systems for recording of neuronal activity face significant data throughput limitations, hampering real-time, data-informed experiments. These limitations impact both experimental neurobio…
Spike SortingL-Sort: An Efficient Hardware for Real-time Multi-channel Spike Sorting with Localization
Spike sorting is essential for extracting neuronal information from neural signals and understanding brain function. With the advent of high-density microelectrode arrays (HDMEAs), the challenges and opportunities in mul…
Brain Computer InterfaceClusteringSpike SortingNeuromorphic Online Clustering and Classification
The bottom two layers of a neuromorphic architecture are designed and shown to be capable of online clustering and supervised classification. An active spiking dendrite model is used, and a single dendritic segment perfo…
Brain Computer InterfaceClassificationClusteringOnline Clustering+1NeuSort: 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 develop a novel online spike sorter, …
Spike SortingTemplate MatchingAdaptive SpikeDeep-Classifier: Self-organizing and self-supervised machine learning algorithm for online spike sorting
Objective. Research on brain-computer interfaces (BCIs) is advancing towards rehabilitating severely disabled patients in the real world. Two key factors for successful decoding of user intentions are the size of implant…
channel selectionSpike SortingEdge computing on TPU for brain implant signal analysis
The ever-increasing number of recording sites of silicon-based probes imposes a great challenge for detecting and evaluating single-unit activities in an accurate and efficient manner. Currently separate solutions are av…
Contrastive LearningDeep LearningEdge-computingSpike Sorting+1Zydeco-Style Spike Sorting Low Power VLSI Architecture for IoT BCI Implants
Brain Computer Interface (BCI) has great potential for solving many brain signal analysis limitations, mental disorder resolutions, and restoring missing limb functionality via neural-controlled implants. However, there …
Brain Computer InterfaceSpike SortingAn Adaptive Contrastive Learning Model for Spike Sorting
Brain-computer interfaces (BCIs), is ways for electronic devices to communicate directly with the brain. For most medical-type brain-computer interface tasks, the activity of multiple units of neurons or local field pote…
Binary ClassificationBrain Computer InterfaceClassificationContrastive Learning+2Toward A Formalized Approach for Spike Sorting Algorithms and Hardware Evaluation
Spike sorting algorithms are used to separate extracellular recordings of neuronal populations into single-unit spike activities. The development of customized hardware implementing spike sorting algorithms is burgeoning…
Spike SortingEfficient Approximation of Action Potentials with High-Order Shape Preservation in Unsupervised Spike Sorting
This paper presents a novel approximation unit added to the conventional spike processing chain which provides an appreciable reduction of complexity of the high-hardware cost feature extractors. The use of the Taylor po…
Spike SortingThree-dimensional spike localization and improved motion correction for Neuropixels recordings
Neuropixels (NP) probes are dense linear multi-electrode arrays that have rapidly become essential tools for studying the electrophysiology of large neural populations. Unfortunately, a number of challenges remain in an…
DenoisingSpike Sorting