We would like to thank David Pitcher for his valuable contribution to this TMS experiment. This research was funded&#160;by a fellowship from the Levie-Edersheim-Gitter Institute for Brain Mapping&#160;to B.S, a grant from the Wolfson Foundation; grants 65/08 and 1657/08 from the Israeli Science Foundation&#160;and a travel grant from the British Council Researcher Exchange&#160;Programme to G.Y.&#160;The experiment was conducted at the Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center.

The experiment is conducted in two separate sessions. During the first session a functional MRI experiment (e.g. a functional localizer) is carried out in order to define the desired TMS target areas on an individual subject basis. The fMRI results are then fed into a stereotactic navigation system for an accurate TMS targeting. The second session is held following the analysis of the fMRI data, during which EEG is recorded concurrently with TMS. The protocol described here was approved by the ethics committee o...

<ol>
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Having the unique ability to momentarily disrupt normal neuronal activity in selected cortical areas, in precise time points and with a relatively good spatial accuracy, TMS allows to causally link a stimulated brain area with a behavioral or a neurophysiological measure. In this paper we described a method for measuring EEG during concurrent TMS application, targeting functionally defined cortical areas, and applying an analysis that enables a reliable measuring of ERP responses. We gave an example from the literature i...

Transcranial Magnetic Stimulation (TMS) generates momentary interference to the normal neural activity in target areas of the brain. By creating this transitory neural interference and measuring a behavioral or physiological change, we can draw a causal link between the target area and the measured experimental effect (for a review see Pascual-Leone et al. and Taylor et al.1,2). Such an experimental effect may be, for example, a performance on a cognitive task or a change in electrophysiological (EEG) activity. Indeed, in recent years researchers have started using TMS in combination with EEG to directly relate cortical areas with event-related potentials (ERP) or oscillatory activity patterns (e.g.2-7). In this methodological paper we will describe a particular and useful framework for combining TMS and EEG: fMRI-guided TMS during an ERP experiment. First, we will detail how to apply TMS to areas predefined by fMRI, while recording EEG data. We will then describe an experimental design that allows extraction of reliable ERP. The goal of such an experiment is to causally link brain areas revealed with functional MRI to ERP components of interest. Lastly, we will give a specific example of a study relating face and body selective ERPs with face and body selective areas that are revealed with fMRI.
What is the benefit of linking EEG signals with fMRI activations? EEG and fMRI are commonly used tools to measure cortical responses to visual input. For example, category-selectivity in the visual pathway was assessed for different visual object categories such as faces, body parts, and written words, both by means of ERP extracted from EEG data8,9, and functional MRI10-12. The signals measured by these two common research tools are, however, of fundamentally different nature. EEG carries information about neural electrical activity with great temporal precision, but very low spatial resolution and may reflect a mixture of many separate underlying sources. The fMRI provides an indirect measure of neuronal activity relying on the slow hemodynamic changes occurring during stimulus presentation or/and task execution, but presents this activity with a higher spatial resolution. Establishing a correlation between the two measures can thus be of great interest, but is limited in that it does not imply a causal link between the scalp-recorded electrophysiological response and the areas revealed with functional MRI. Even when measured simultaneously (e.g.13-15), a directional causal relation between EEG and activity in functionally defined cortical areas cannot be determined. TMS is a tool that can assist achieving the establishment of such a causal relationship.
A simultaneous EEG-TMS study is methodologically challenging, mostly due to the high voltage artifact introduced to the EEG signal by the magnetic stimulation (see Figure 1, for a review see Ilmoniemi et al.16). This artifact consists of a transient short living pulse-related disturbance, often followed by a slower secondary (or residual) artifact that may last a few hundreds of milliseconds after the pulse is delivered Figure 2A, thus overriding most ERP components of interest. This secondary artifact may include mechanical sources such as currents induced by the magnetic pulse into the wiring and the slow decay of these currents in the skin, and physiological sources such as muscular activity over the scalp and auditory or somatosensory evoked potentials elicited by the operation of the coil17-20. Although the mechanical sources of interference probably produce larger amplitude artifacts than the physiological ones, these different artifacts cannot be separated, and the existence of any of them in the signal can confound the results. One possible solution is the application of repetitive TMS pulses prior to EEG recording (&#34;offline TMS&#34;), as opposed to simultaneous EEG-TMS. The inhibitory effect of such a protocol on cortical activity persists for several minutes (and up to half an hour) after the stimulation, and EEG can be measured during this effective time window and compared with baseline, pre-TMS, EEG data. Repetitive stimulation, however, is by definition lacking the high temporal resolution that online TMS may offer, where pulses can be administered at a precise timing relative to trial onset at the millisecond resolution. The effect of repetitive stimulation may also propagate via cortical connections across a wider area than desired and therefore significantly reduce the spatial resolution as well.
To take advantage of both the spatial and temporal resolution that TMS can provide, a simultaneous EEG-TMS combination can be applied. However, this requires methods for removal of artifacts generated by the magnetic stimulation on the EEG signal. Very few offline mathematical solutions for TMS artifact removal have been proposed16,21,22, although no method is agreed upon, and no one method may be optimal for all experimental designs. A &#34;clipping&#34; system, consisting of a sample-and-hold circuitry, was also developed to momentarily stop EEG acquisition during TMS pulse delivery 20. This technique not only requires specialized hardware, but may not completely remove the residual TMS artifact. In this paper we will describe an adaptation of an EEG-TMS methodology developed by Thut and colleagues19, particularly suitable for ERP studies. This technique allows reliable extraction of ERP while eliminating all the residual noise components caused by the TMS pulse Figure 2. We will further provide general guidance towards a successful EEG-TMS experimental setup.
Another challenge in TMS studies addressed in this methodological paper is finding the best coil position and angle for an accurate targeting of the desired cortical area. We will describe the use of a stereotactic navigation system to coregister the subject&#39;s head with the pre-acquired functional MRI images. Although the navigation system can be used to localize anatomically-defined brain structures, an fMRI-guided targeting is particularly useful since for many functions and experimental effects the precise location of activation cannot be inferred from anatomical markers alone. For such functional regions of interest (ROI), the definition of an area is made for each participant individually.
To illustrate all of the above, we will provide an example of a study we conducted previously, in which EEG was recorded concurrently with TMS guided by fMRI activations7. In this study, a double dissociation was made between face-selective and body-selective ERPs: although face and body ERPs peak around the same latency and electrode sites, targeting individually defined face-selective and body-selective areas in the lateral occipital lobe enabled us to dissociate the neural networks underlying each ERP response. Finally, we will try to give more general advise for optimizing EEG recording during TMS application.

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			<td height="43" style="height:43px;width:209px;">3.0T Signa MRI scanner</td>
			<td style="width:107px;">General Electric</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="42">
			<td height="63" rowspan="2" style="height:63px;width:209px;">BrainAmp&#160; amplifier&#160;</td>
			<td rowspan="2" style="width:107px;"><a name="RANGE!B3">Brain Products GmbH</a></td>
			<td rowspan="2" style="width:113px;">BP-01300</td>
			<td rowspan="2" style="width:167px;"></td>
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		<tr height="21">
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			<td height="64" style="height:64px;width:209px;">Electrode input box</td>
			<td style="width:107px;">Brain Products GmbH</td>
			<td style="width:113px;"></td>
			<td style="width:167px;">Optional</td>
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		<tr height="64">
			<td height="64" style="height:64px;width:209px;">PowerPack - battery for amplifier</td>
			<td style="width:107px;">Brain Products GmbH</td>
			<td style="width:113px;">BP-02615</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="146">
			<td height="167" rowspan="2" style="height:167px;width:209px;">BrainCap - 32 flat electrodes on a flexible cap&#160;</td>
			<td rowspan="2" style="width:107px;">Brain Products GmbH</td>
			<td rowspan="2" style="width:113px;">BP-0300MR</td>
			<td rowspan="2" style="width:167px;">Flat electrodes should be used to assure a shorter distance beween coil and scalp. If larger (e.g. pin type) electrodes are used, remove the ones under the coil</td>
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			<td height="43" style="height:43px;width:209px;">TMS Super Rapid2 stimulator</td>
			<td style="width:107px;">Magstim</td>
			<td style="width:113px;"></td>
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			<td height="22" style="height:22px;width:209px;">50mm double coil</td>
			<td style="width:107px;">Magstim</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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			<td height="169" style="height:169px;width:209px;">Coil holder&#160;</td>
			<td style="width:107px;"></td>
			<td style="width:113px;"></td>
			<td style="width:167px;">Any mechanical arm or tripod that can hold the coil, be adjusted to the right angle and location, and keep the coil steady during stimulation</td>
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			<td height="22" style="height:22px;width:209px;">Chinrest</td>
			<td style="width:107px;"></td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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		<tr height="43">
			<td height="43" style="height:43px;width:209px;">Polaris infrared camera</td>
			<td style="width:107px;">Rogue Research Inc</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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		<tr height="43">
			<td height="43" style="height:43px;width:209px;">Polaris trackers and pointer tool</td>
			<td style="width:107px;">Rogue Research Inc</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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		<tr height="43">
			<td height="43" style="height:43px;width:209px;">BrainSight workstation and software</td>
			<td style="width:107px;">Rogue Research Inc</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
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		<tr height="64">
			<td height="64" style="height:64px;width:209px;">BrainVision Recorder software</td>
			<td style="width:107px;">Brain Products GmbH</td>
			<td style="width:113px;">BP-00010</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:209px;">MATLAB software</td>
			<td style="width:107px;">The MathWorks Icn.</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="106">
			<td height="106" style="height:106px;width:209px;">SPM for Matlab</td>
			<td style="width:107px;">Wellcome Department of Imaging Neuroscience, London, UK&#160;</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:209px;">MarsBar region of interest toolbox for SPM</td>
			<td style="width:107px;"></td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="211">
			<td height="211" style="height:211px;width:209px;">Psychtoolbox for MATLAB</td>
			<td style="width:107px;"></td>
			<td style="width:113px;"></td>
			<td style="width:167px;">This toolbox and the E-prime software (below) are examples for stimulus presentation software capable of delivering commands to the TMS stimulator and to the EEG recorder with reliable timing</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:209px;">E-Prime software</td>
			<td style="width:107px;">Psychology Software Tools, Inc.</td>
			<td style="width:113px;"></td>
			<td style="width:167px;"></td>
		</tr>
	</tbody>
</table>

extracting visual evoked potentials from eeg data recorded during fmri-guided transcranial magnetic stimulation

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator&#39;s coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes.

A concurrent EEG-TMS investigation was used to reveal whether the ERP responses to faces and bodies recorded over the occipito-temporal scalp are dissociated. When visual stimuli are presented, a prominent N1 component is recorded at posterior-lateral electrode sites. In particular, the N1 component is typically larger for faces and bodies than to other stimulus categories8,33. By assessing the effect of stimulation on face and body-selective brain areas defined with fMRI on their respective face and body N1 c...

Watch this Scientific Journal Video about Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation at JoVE.com

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

This paper describes a method for collecting and analyzing electroencephalography (EEG) data during concurrent transcranial magnetic stimulation (TMS) guided by activations revealed with functional magnetic resonance imaging (fMRI). A method for TMS artifact removal and extraction of event related potentials is described as well as considerations in paradigm design and experimental setup.

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological ...

extracting-visual-evoked-potentials-from-eeg-data-recorded-during

Research

JoVE Journal

Neuroscience

13.7K ビュー.  Tel-Aviv University. 本稿では、機能的磁気共鳴画像法（fMRI）を用いて明らかにした活性化によって案内同時経頭蓋磁気刺激（TMS）中に（EEG）データを収集し、脳波を分析するための方法が記載されている。事象関連電位のTMSアーチファクト除去や抽出のための方法は、パラダイムの設計と実験で説明しただけでなく、配慮されている。 