Literature DB >> 25282542

Challenges in the quantification and interpretation of spike-LFP relationships.

Supratim Ray1.   

Abstract

Brain signals often show fluctuations in particular frequency bands, which are highly conserved across species and are associated with specific behavioural states. Such rhythmic patterns can be captured in the local field potential (LFP), which is obtained by low-pass filtering the extracellular signal recorded from microelectrodes. However, LFP also captures other neural processes that are associated with spikes, such as synaptic events preceding a spike, low-frequency component of the action potential ("spike bleed-through") and spike afterhyperpolarization, which pose difficulties in the estimation of the amplitude and phase of the rhythm with respect to spikes. Here we discuss these issues and different techniques that have been used to dissociate the rhythm from other neural events in the LFP.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2014        PMID: 25282542     DOI: 10.1016/j.conb.2014.09.004

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  21 in total

1.  Stimulus-dependent spiking relationships with the EEG.

Authors:  Adam C Snyder; Matthew A Smith
Journal:  J Neurophysiol       Date:  2015-06-24       Impact factor: 2.714

2.  Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability.

Authors:  Brian D Allen; Caroline Moore-Kochlacs; Jacob G Bernstein; Justin P Kinney; Jorg Scholvin; Luís F Seoane; Chris Chronopoulos; Charlie Lamantia; Suhasa B Kodandaramaiah; Max Tegmark; Edward S Boyden
Journal:  J Neurophysiol       Date:  2018-07-11       Impact factor: 2.714

3.  Adaptive spike-artifact removal from local field potentials uncovers prominent beta and gamma band neuronal synchronization.

Authors:  Kianoush Banaie Boroujeni; Paul Tiesinga; Thilo Womelsdorf
Journal:  J Neurosci Methods       Date:  2019-11-06       Impact factor: 2.390

4.  Primary sensorimotor cortex exhibits complex dependencies of spike-field coherence on neuronal firing rates, field power, and behavior.

Authors:  F I Arce-McShane; B J Sessle; C F Ross; N G Hatsopoulos
Journal:  J Neurophysiol       Date:  2018-03-28       Impact factor: 2.714

Review 5.  A Tutorial Review of Functional Connectivity Analysis Methods and Their Interpretational Pitfalls.

Authors:  André M Bastos; Jan-Mathijs Schoffelen
Journal:  Front Syst Neurosci       Date:  2016-01-08

6.  Decoding of Attentional State Using High-Frequency Local Field Potential Is As Accurate As Using Spikes.

Authors:  Surya S Prakash; Aritra Das; Sidrat Tasawoor Kanth; J Patrick Mayo; Supratim Ray
Journal:  Cereb Cortex       Date:  2021-07-29       Impact factor: 5.357

7.  Sensory feedback-dependent coding of arm position in local field potentials of the posterior parietal cortex.

Authors:  Paul VanGilder; Ying Shi; Gregory Apker; Christopher A Buneo
Journal:  Sci Rep       Date:  2021-04-27       Impact factor: 4.379

8.  Detection of transient synchrony across oscillating receptors by the central electrosensory system of mormyrid fish.

Authors:  Alejandro Vélez; Bruce A Carlson
Journal:  Elife       Date:  2016-06-21       Impact factor: 8.140

Review 9.  Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals.

Authors:  Subhash Chandran K S; Ashutosh Mishra; Vinay Shirhatti; Supratim Ray
Journal:  J Neurosci       Date:  2016-03-23       Impact factor: 6.167

10.  Effect of Cross-Orientation Normalization on Different Neural Measures in Macaque Primary Visual Cortex.

Authors:  Aritra Das; Supratim Ray
Journal:  Cereb Cortex Commun       Date:  2021-02-10
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