Literature DB >> 33499330

Transcranial Evoked Potentials Can Be Reliably Recorded with Active Electrodes.

Marco Mancuso1, Valerio Sveva1, Alessandro Cruciani2, Katlyn Brown3, Jaime Ibáñez4, Vishal Rawji3, Elias Casula5, Isabella Premoli6, Sasha D'Ambrosio7,8, John Rothwell3, Lorenzo Rocchi3.   

Abstract

Electroencephalographic (EEG) signals evoked by transcranial magnetic stimulation (TMS) are usually recorded with passive electrodes (PE). Active electrode (AE) systems have recently become widely available; compared to PE, they allow for easier electrode preparation and a higher-quality signal, due to the preamplification at the electrode stage, which reduces electrical line noise. The performance between the AE and PE can differ, especially with fast EEG voltage changes, which can easily occur with TMS-EEG; however, a systematic comparison in the TMS-EEG setting has not been made. Therefore, we recorded TMS-evoked EEG potentials (TEPs) in a group of healthy subjects in two sessions, one using PE and the other using AE. We stimulated the left primary motor cortex and right medial prefrontal cortex and used two different approaches to remove early TMS artefacts, Independent Component Analysis and Signal Space Projection-Source Informed Recovery. We assessed statistical differences in amplitude and topography of TEPs, and their similarity, by means of the concordance correlation coefficient (CCC). We also tested the capability of each system to approximate the final TEP waveform with a reduced number of trials. The results showed that TEPs recorded with AE and PE do not differ in amplitude and topography, and only few electrodes showed a lower-than-expected CCC between the two methods of amplification. We conclude that AE are a viable solution for TMS-EEG recording.

Entities:  

Keywords:  EEG artefacts; TMS-EEG; active electrodes; electroencephalography; independent component analysis; motor evoked potentials; neurophysiology; transcranial evoked potentials; transcranial magnetic stimulation

Year:  2021        PMID: 33499330      PMCID: PMC7912161          DOI: 10.3390/brainsci11020145

Source DB:  PubMed          Journal:  Brain Sci        ISSN: 2076-3425


  37 in total

1.  Nonparametric permutation tests for functional neuroimaging: a primer with examples.

Authors:  Thomas E Nichols; Andrew P Holmes
Journal:  Hum Brain Mapp       Date:  2002-01       Impact factor: 5.038

2.  Nonparametric statistical testing of EEG- and MEG-data.

Authors:  Eric Maris; Robert Oostenveld
Journal:  J Neurosci Methods       Date:  2007-04-10       Impact factor: 2.390

3.  High frequency somatosensory stimulation in dystonia: Evidence fordefective inhibitory plasticity.

Authors:  Roberto Erro; Lorenzo Rocchi; Elena Antelmi; Rocco Liguori; Michele Tinazzi; Alfredo Berardelli; John Rothwell; Kailash P Bhatia
Journal:  Mov Disord       Date:  2018-10-30       Impact factor: 10.338

Review 4.  TMS-EEG: A window into the neurophysiological effects of transcranial electrical stimulation in non-motor brain regions.

Authors:  Aron T Hill; Nigel C Rogasch; Paul B Fitzgerald; Kate E Hoy
Journal:  Neurosci Biobehav Rev       Date:  2016-03-06       Impact factor: 8.989

5.  Effects of pulse width, waveform and current direction in the cortex: A combined cTMS-EEG study.

Authors:  E P Casula; L Rocchi; R Hannah; J C Rothwell
Journal:  Brain Stimul       Date:  2018-04-24       Impact factor: 8.955

6.  Somatosensory Temporal Discrimination Threshold Involves Inhibitory Mechanisms in the Primary Somatosensory Area.

Authors:  Lorenzo Rocchi; Elias Casula; Pierluigi Tocco; Alfredo Berardelli; John Rothwell
Journal:  J Neurosci       Date:  2016-01-13       Impact factor: 6.167

Review 7.  Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography.

Authors:  Faranak Farzan; Marine Vernet; Mouhsin M D Shafi; Alexander Rotenberg; Zafiris J Daskalakis; Alvaro Pascual-Leone
Journal:  Front Neural Circuits       Date:  2016-09-22       Impact factor: 3.492

Review 8.  Analysing connectivity with Granger causality and dynamic causal modelling.

Authors:  Karl Friston; Rosalyn Moran; Anil K Seth
Journal:  Curr Opin Neurobiol       Date:  2012-12-21       Impact factor: 6.627

9.  Controllable Pulse Parameter TMS and TMS-EEG As Novel Approaches to Improve Neural Targeting with rTMS in Human Cerebral Cortex.

Authors:  Ricci Hannah; Lorenzo Rocchi; Sara Tremblay; John C Rothwell
Journal:  Front Neural Circuits       Date:  2016-11-29       Impact factor: 3.492

10.  The effects of NMDA receptor blockade on TMS-evoked EEG potentials from prefrontal and parietal cortex.

Authors:  Nigel C Rogasch; Carl Zipser; Ghazaleh Darmani; Tuomas P Mutanen; Mana Biabani; Christoph Zrenner; Debora Desideri; Paolo Belardinelli; Florian Müller-Dahlhaus; Ulf Ziemann
Journal:  Sci Rep       Date:  2020-02-21       Impact factor: 4.379

View more
  3 in total

1.  Feeling of Ownership over an Embodied Avatar's Hand Brings About Fast Changes of Fronto-Parietal Cortical Dynamics.

Authors:  Elias Paolo Casula; Gaetano Tieri; Lorenzo Rocchi; Rachele Pezzetta; Michele Maiella; Enea Francesco Pavone; Salvatore Maria Aglioti; Giacomo Koch
Journal:  J Neurosci       Date:  2021-12-03       Impact factor: 6.709

2.  The effect of stimulation frequency on transcranial evoked potentials.

Authors:  Giorgio Leodori; Lorenzo Rocchi; Marco Mancuso; Maria Ilenia De Bartolo; Viola Baione; Matteo Costanzo; Daniele Belvisi; Antonella Conte; Giovanni Defazio; Alfredo Berardelli
Journal:  Transl Neurosci       Date:  2022-08-05       Impact factor: 1.264

3.  Preconditioning Stimulus Intensity Alters Paired-Pulse TMS Evoked Potentials.

Authors:  Vishal Rawji; Isabella Kaczmarczyk; Lorenzo Rocchi; Po-Yu Fong; John C Rothwell; Nikhil Sharma
Journal:  Brain Sci       Date:  2021-03-04
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.