Mapping dynamical properties of cortical microcircuits using robotized TMS and EEG: Towards functional cytoarchitectonics

Harquel, Sylvain; Bacle, Thibault; Beynel, Lysianne; Marendaz, Christian; Chauvin, Alan; David, Olivier

doi:10.1016/j.neuroimage.2016.05.009

Cited by 48 publications

(69 citation statements)

References 66 publications

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“…The log mean magnitudes of different time windows are computed to capture the decay artifact and various TEP peaks. The time windows considered in ARTIST are 0–60, 60–140, and 140–220 ms:

f_{14} = normall normalo normalg (|||, normalm normale normala normaln (|, (|||, Y_{i, t}))), t \in ([]|, 0 normalm normals, 60 normalm normals)

f_{15} = normall normalo normalg (|||, normalm normale normala normaln (|, (|||, Y_{i, t}))), t \in ([]|, 60 normalm normals, 140 normalm normals)

f_{16} = normall normalo normalg (|||, normalm normale normala normaln (|, (|||, Y_{i, t}))), t \in ([]|, 140 normalm normals, 220 normalm normals)

These are designed to capture TEP peaks that are typically present when different brain areas are stimulated (Harquel et al, ; Rosanova et al, ), such as n45, p60, n100, and p200 (see neural IC4 and IC5 in Figure for examples). They can also be used to capture the artifacts that are time‐locked to the TMS (e.g., the decay artifact).…”

Section: Methodsmentioning

confidence: 99%

“…iv If the number of peaks is greater than a preset threshold J (empirically determined to be 0.8ÁNÁT in ARTIST, where N is f 14 5logjmean jY i;t j À Á j; t 2 0 ms; 60 ms ½ f 15 5logjmean jY i;t j À Á j; t 2 60 ms; 140 ms ½ f 16 5logjmean jY i;t j À Á j; t 2 140 ms; 220 ms ½ These are designed to capture TEP peaks that are typically present when different brain areas are stimulated (Harquel et al, 2016;Rosanova et al, 2009), such as n45, p60, n100, and p200 (see neural IC4 and IC5 in Figure 1 for examples). They can also be used to capture the artifacts that are time-locked to the TMS (e.g., the decay artifact).…”

Section: Blink/vertical Eye Movement Fmentioning

confidence: 99%

“…However, these findings provide only an observational view of how brain activity and function are related, and importantly lack the causal inference that is often necessary to dissect circuits and guide therapeutic interventions. Single‐pulse transcranial magnetic stimulation (spTMS) coupled with electroencephalogram (EEG) provides the causal probe and measurement tools, respectively, that can be utilized to study systems‐level causal brain dynamics in both healthy and clinical populations (Ferrarelli et al, ; Harquel et al, ; Massimini et al, ; Morishima et al, ; Premoli et al, ; Sun et al, ). However, in addition to the conventional EEG artifacts (Fisch, & Spehlmann, ), spTMS‐EEG suffers from multiple stimulation‐related artifacts including those derived from the stimulation pulse itself (Veniero, Bortoletto, & Miniussi, ), scalp muscle activation (Mutanen, Mäki, & Ilmoniemi, ), electrode movement or polarization, sensory system activation (Massimini et al, ), eye blinks, coil clicks (Nikouline, Ruohonen, & Ilmoniemi, ; Ter Braack, de Vos, & van Putten, ), and coil recharge (see Figure for examples of main types of artifacts and neural signals) (Ilmoniemi, & Kičić, ).…”

Section: Introductionmentioning

confidence: 99%

“…clinical populations (Ferrarelli et al, 2008;Harquel et al, 2016;Massimini et al, 2005;Morishima et al, 2009;Premoli et al, 2014;Sun et al, 2016). However, in addition to the conventional EEG artifacts (Fisch, & Spehlmann, 1999), spTMS-EEG suffers from multiple stimulation-related artifacts including those derived from the stimulation pulse itself (Veniero, Bortoletto, & Miniussi, 2009), scalp muscle activation (Mutanen, Mäki, & Ilmoniemi, 2013), electrode movement or polarization, sensory system activation (Massimini et al, 2005), eye blinks, coil clicks (Nikouline, Ruohonen, & Ilmoniemi, 1999;Ter Braack, de Vos, & van Putten, 2015), and coil recharge (see Figure 1 for examples of main types of artifacts and neural signals) (Ilmoniemi, & Kičić, 2010).…”

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confidence: 99%

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ARTIST: A fully automated artifact rejection algorithm for single‐pulse TMS‐EEG data

Wu¹,

Keller

Rogasch

et al. 2018

Human Brain Mapping

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Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.

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“…The log mean magnitudes of different time windows are computed to capture the decay artifact and various TEP peaks. The time windows considered in ARTIST are 0–60, 60–140, and 140–220 ms:

f_{14} = normall normalo normalg (|||, normalm normale normala normaln (|, (|||, Y_{i, t}))), t \in ([]|, 0 normalm normals, 60 normalm normals)

f_{15} = normall normalo normalg (|||, normalm normale normala normaln (|, (|||, Y_{i, t}))), t \in ([]|, 60 normalm normals, 140 normalm normals)

f_{16} = normall normalo normalg (|||, normalm normale normala normaln (|, (|||, Y_{i, t}))), t \in ([]|, 140 normalm normals, 220 normalm normals)

Section: Methodsmentioning

confidence: 99%

Section: Blink/vertical Eye Movement Fmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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ARTIST: A fully automated artifact rejection algorithm for single‐pulse TMS‐EEG data

Wu¹,

Keller

Rogasch

et al. 2018

Human Brain Mapping

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show abstract

“…The analysis of brain modes showed that a cortical area distribution pattern that had similar intrinsic dynamic properties was similar to the resting-state networks. 99 Further, Casali et al investigated significant current density, phase-locking, and significant current scattering of TEP and indicated a reproducible profile of excitability and connectivity from the occipital to ipsilateral frontal areas. 18 In addition, Amico et al recently explored the directed functional connectivity interactions between cortical areas based on the source-reconstructed TMS/high-density-EEG recordings and found that sp-TMS elicited specific frequency band modulations in beta band for the precuneus and gamma band for the premotor according to each stimulated region.…”

Section: Cortical Plasticity Indexed By Tep Pasmentioning

confidence: 99%

Toward the establishment of neurophysiological indicators for neuropsychiatric disorders using transcranial magnetic stimulation‐evoked potentials: A systematic review

Noda

2019

Psychiatry Clin Neurosci

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Transcranial magnetic stimulation (TMS) can depolarize the neurons directly under the coil when applied to the cerebral cortex, and modulate the neural circuit associated with the stimulation site, which makes it possible to measure the neurophysiological index to evaluate excitability and inhibitory functions. Concurrent TMS and electroencephalography (TMS-EEG) has been developed to assess the neurophysiological characteristics of cortical regions other than the motor cortical region noninvasively. The aim of this review is to comprehensively discuss TMS-EEG research in the healthy brain focused on excitability, inhibition, and plasticity following neuromodulatory TMS paradigms from a neurophysiological perspective. A search was conducted in PubMed to identify articles that examined humans and that were written in English and published by September 2018. The search terms were as follows: (TMS OR 'transcranial magnetic stimulation') AND (EEG OR electroencephalog*) NOT (rTMS OR 'repetitive transcranial magnetic stimulation' OR TBS OR 'theta burst stimulation') AND (healthy). The study presents an overview of TMS-EEG methodology and neurophysiological indices and reviews previous findings from TMS-EEG in healthy individuals. Furthermore, this review discusses the potential application of TMS-EEG neurophysiology in the clinical setting to study healthy and diseased brain conditions in the future. Combined TMS-EEG is a powerful tool to probe and map neural circuits in the human brain noninvasively and represents a promising approach for determining the underlying pathophysiology of neuropsychiatric disorders.

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Neuromodulation Management of Chronic Neuropathic Pain in the Central Nervous System

2020

Adv Funct Materials

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Neuromodulation is a clinical tool used for treating chronic neuropathic pain by transmitting controlled physical energy to the pre‐identified neural targets in the central nervous system. Its drug‐free, nonaddictive, and improved targeting characteristics have attracted increasing attention among neuroscience research and clinical practices. This article provides a brief overview of the neuropathic pain and pharmacological routines for treatment, summarizes both the invasive and noninvasive neuromodulation modalities for pain management, and highlights an emerging brain stimulation technology, transcranial focused ultrasound (tFUS), with a focus on ultrasound transducer devices and the achieved neuromodulation effects and applications on pain management. Practical considerations of spatial guidance for tFUS are discussed for clinical applications. The safety of transcranial ultrasound neuromodulation and its future prospectives on pain management are also discussed.

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Mapping dynamical properties of cortical microcircuits using robotized TMS and EEG: Towards functional cytoarchitectonics

Cited by 48 publications

References 66 publications

ARTIST: A fully automated artifact rejection algorithm for single‐pulse TMS‐EEG data

ARTIST: A fully automated artifact rejection algorithm for single‐pulse TMS‐EEG data

Toward the establishment of neurophysiological indicators for neuropsychiatric disorders using transcranial magnetic stimulation‐evoked potentials: A systematic review

Neuromodulation Management of Chronic Neuropathic Pain in the Central Nervous System

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