[HTML][HTML] Continuing progress of spike sorting in the era of big data

D Carlson, L Carin - Current opinion in neurobiology, 2019 - Elsevier
Highlights•Novel devices are posing challenges to existing spike sorting pipelines.•Spike
sorting methodology is expanding to handle thousands to millions of neurons.•Multi-stage …

A fully automated approach to spike sorting

JE Chung, JF Magland, AH Barnett, VM Tolosa… - Neuron, 2017 - cell.com
Understanding the detailed dynamics of neuronal networks will require the simultaneous
measurement of spike trains from hundreds of neurons (or more). Currently, approaches to …

Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels

M Pachitariu, N Steinmetz, S Kadir, M Carandini… - BioRxiv, 2016 - biorxiv.org
Advances in silicon probe technology mean that in vivo electrophysiological recordings from
hundreds of channels will soon become commonplace. To interpret these recordings we …

Spike sorting for large, dense electrode arrays

C Rossant, SN Kadir, DFM Goodman, J Schulman… - Nature …, 2016 - nature.com
Developments in microfabrication technology have enabled the production of neural
electrode arrays with hundreds of closely spaced recording sites, and electrodes with …

Computational neuroscience: Mathematical and statistical perspectives

RE Kass, SI Amari, K Arai, EN Brown… - Annual review of …, 2018 - annualreviews.org
Mathematical and statistical models have played important roles in neuroscience, especially
by describing the electrical activity of neurons recorded individually, or collectively across …

Mixture models with a prior on the number of components

JW Miller, MT Harrison - Journal of the American Statistical …, 2018 - Taylor & Francis
ABSTRACT A natural Bayesian approach for mixture models with an unknown number of
components is to take the usual finite mixture model with symmetric Dirichlet weights, and …

High-dimensional cluster analysis with the masked EM algorithm

SN Kadir, DFM Goodman, KD Harris - Neural computation, 2014 - ieeexplore.ieee.org
Cluster analysis faces two problems in high dimensions: the “curse of dimensionality” that
can lead to overfitting and poor generalization performance and the sheer time taken for …

SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters

J Magland, JJ Jun, E Lovero, AJ Morley, CL Hurwitz… - Elife, 2020 - elifesciences.org
Spike sorting is a crucial step in electrophysiological studies of neuronal activity. While many
spike sorting packages are available, there is little consensus about which are most …

To sort or not to sort: the impact of spike-sorting on neural decoding performance

S Todorova, P Sadtler, A Batista… - Journal of neural …, 2014 - iopscience.iop.org
Objective. Brain–computer interfaces (BCIs) are a promising technology for restoring motor
ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical …

Learning a common dictionary for subject-transfer decoding with resting calibration

H Morioka, A Kanemura, J Hirayama, M Shikauchi… - NeuroImage, 2015 - Elsevier
Brain signals measured over a series of experiments have inherent variability because of
different physical and mental conditions among multiple subjects and sessions. Such …