Cover Image

SimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Yimu, Han, Dongqi, Wang, Yansen, Lv, Zhenning, Gu, Yu, Li, Dongsheng
Format:	Preprint
Published:	2025
Subjects:	Neurons and Cognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting
by: Minnick, John R., et al.
Published: (2026)

Latent Diffusion for Neural Spiking Data
by: Kapoor, Jaivardhan, et al.
Published: (2024)

SpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm
by: Georgiadis, Vasileios, et al.
Published: (2025)

Implicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale
by: Minnick, John R., et al.
Published: (2026)

EEGFormer: Towards Transferable and Interpretable Large-Scale EEG Foundation Model
by: Chen, Yuqi, et al.
Published: (2024)

Cross-Species Transfer Learning for Electrophysiology-to-Transcriptomics Mapping in Cortical GABAergic Interneurons
by: Schwider, Theo, et al.
Published: (2026)

A Data-Driven Method to Map the Functional Organisation of Human Brain White Matter
by: Sun, Yifei, et al.
Published: (2026)

HetSyn: Versatile Timescale Integration in Spiking Neural Networks via Heterogeneous Synapses
by: Deng, Zhichao, et al.
Published: (2025)

Bridging Theory and Practice in Crafting Robust Spiking Reservoirs
by: Freddi, Ruggero, et al.
Published: (2026)

Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment
by: Yu, Chengting, et al.
Published: (2025)

Toward Efficient Spiking Transformers: Synapse Pruning Meets Synergistic Learning-Based Compensation
by: Sun, Hongze, et al.
Published: (2025)

REVE: A Foundation Model for EEG -- Adapting to Any Setup with Large-Scale Pretraining on 25,000 Subjects
by: Ouahidi, Yassine El, et al.
Published: (2025)

A Global Data-Driven Model for The Hippocampus and Nucleus Accumbens of Rat From The Local Field Potential Recordings (LFP)
by: Sadeghi, Maedeh, et al.
Published: (2024)

Spiking Neural Models for Decision-Making Tasks with Learning
by: Jaffard, Sophie, et al.
Published: (2025)

Visual Large Language Models Exhibit Human-Level Cognitive Flexibility in the Wisconsin Card Sorting Test
by: Hao, Guangfu, et al.
Published: (2025)

Power-Law Scaling in the Classification Performance of Small-Scale Spiking Neural Networks
by: Zhang, Zhengdi, et al.
Published: (2026)

Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex
by: Vasques, Xavier, et al.
Published: (2025)

Functional Classification of Spiking Signal Data Using Artificial Intelligence Techniques: A Review
by: Sharifrazi, Danial, et al.
Published: (2024)

Place Cells as Multi-Scale Position Embeddings: Random Walk Transition Kernels for Path Planning
by: Zhao, Minglu, et al.
Published: (2025)

State Space Models Naturally Produce Time Cell and Oscillatory Behaviors and Scale to Abstract Cognitive Functions
by: Lu, Sen, et al.
Published: (2025)

Comparing and Scaling fMRI Features for Brain-Behavior Prediction
by: Sieler, Mikkel Schöttner, et al.
Published: (2025)

NeuralBench: A Unifying Framework to Benchmark NeuroAI Models
by: Banville, Hubert, et al.
Published: (2026)

Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
by: Silva, Santiago, et al.
Published: (2018)

Scaling and context steer LLMs along the same computational path as the human brain
by: Raugel, Joséphine, et al.
Published: (2025)

Modeling Visual Hallucination: A Generative Adversarial Network Framework
by: Zareh, Masoumeh, et al.
Published: (2021)

A Framework for Standardizing Similarity Measures in a Rapidly Evolving Field
by: Cloos, Nathan, et al.
Published: (2024)

Training Large Neural Networks With Low-Dimensional Error Feedback
by: Hanut, Maher, et al.
Published: (2025)

Criticality Analysis: Bio-inspired Nonlinear Data Representation
by: Scheper, Tjeerd V. olde
Published: (2023)

Probabilistic Geometric Principal Component Analysis with application to neural data
by: Hsieh, Han-Lin, et al.
Published: (2025)

Multi-Scale Graph Theoretical Analysis of Resting-State fMRI for Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Healthy Controls
by: Khazaee, Ali, et al.
Published: (2024)

A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning across Broad Atlases and Disorders
by: Wei, Xinxu, et al.
Published: (2025)

Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience
by: Liu, Zinan, et al.
Published: (2025)

Meta-Dynamical State Space Models for Integrative Neural Data Analysis
by: Vermani, Ayesha, et al.
Published: (2024)

Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
by: Gondur, Rabia, et al.
Published: (2023)

STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC
by: Wang, Jiyao, et al.
Published: (2024)

Latent Variable Double Gaussian Process Model for Decoding Complex Neural Data
by: Ziaei, Navid, et al.
Published: (2024)

SpikeFit: Towards Optimal Deployment of Spiking Networks on Neuromorphic Hardware
by: Kartashov, Ivan, et al.
Published: (2025)

Omni-iEEG: A Large-Scale, Comprehensive iEEG Dataset and Benchmark for Epilepsy Research
by: Duan, Chenda, et al.
Published: (2026)

DCHO: A Decomposition-Composition Framework for Predicting Higher-Order Brain Connectivity to Enhance Diverse Downstream Applications
by: Li, Weibin, et al.
Published: (2025)

Integrated Brain Connectivity Analysis with fMRI, DTI, and sMRI Powered by Interpretable Graph Neural Networks
by: Qu, Gang, et al.
Published: (2024)