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 of the Tel-Aviv Sourasky Medical Center.
In the example given in this paper, data were analyzed with MATLAB version 7.7 (R2008b). The Statistical Parametric Mapping (SPM 5) software for MATLAB and MarsBar toolbox for SPM 23 were used for fMRI data processing.
1. fMRI Session and fMRI Data Analysis
2. Preparing a Paradigm for the EEG-TMS Experiment that will allow ERP Extraction
Described in the section below is a method for collecting EEG data during TMS application in a way that allows extraction of reliable and replicable ERPs19. The advantage of this technique is that it easily handles the secondary, long lasting, TMS artifact, and is robust enough even to allow restoration of data at electrodes located right under the TMS coil, where the artifact is of the highest voltage and longest duration.
3. Setting up the EEG and the Neuronavigation System, and Conducting the Experiment
Accurate TMS targeting of individually defined ROIs is possible with the use of a stereotactic navigation system, comprised of an infrared camera, infrared sensors mounted on the participant's head, and a specialized software.
4. Analyzing the EEG Data and Computing ERP
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 component, we attempted to reveal whether the face and body N1 responses reflect (at least partially) non-overlapping sources, or rather the same network activity with quantitatively different activation levels.
We applied a double-pulse stimulation at 60 msec and 100 msec after image onset (see for example Pitcher et al.34,35), to the face-selective and body-selective areas in the lateral occipital cortex – the Occipital-Face Area (OFA) and the Extrastriate Body Area (EBA) (Figure 4A, see section 1.3 above for definition of the relevant fMRI contrasts). The two areas were stimulated in separate blocks, while subjects viewed images of faces and headless bodies. Results show that stimulation to the OFA enhance the N1 amplitude to faces but not to bodies, whereas stimulation to the EBA enhance the N1 to bodies but not to faces. Figure 2B depicts the face N1 before and after TMS residual artifact subtraction, and Figure 4B shows the specific effect of TMS on the N1 component as a function of stimulated area.
These findings show how fMRI-guided TMS during concurrent EEG recording can be applied to assess whether two (or more) neural networks are dissociated, as well as to establish a causal link between a functionally defined brain area and an electrophysiological signal.
Figure 1. Data processing. Raw and processed data of a representative subject, at the lateral-occipital electrode PO8. (A) Raw EEG data including two trials, each containing two TMS pulses separated by 40 msec (red arrows); (B) Zoom into the data after pulse removal. The two pulses at each trial are removed from the data by cutting a window around the double-pulse (2 msec before first pulse to 16 msec after second pulse). The cut edges are then connected by interpolation (red arrows) as explained in 4.1.2; (C) The interpolated segment allows filtering without creating edge artifacts. In this figure, a 40 Hz low-pass filtered ERP (red) is plotted against its non-filtered version (grey); (D) As an alternative to interpolation, the free ends that are remained after pulse removal can be joined together (see for example Fugetta et al26, and point 4.1.2 in the text). Here, both methods are compared and show highly similar waveforms (blue and red traces mostly overlap), after low-pass filtering at 40 Hz. Red trace: linear interpolation method; blue trace: no interpolation (connected edges are taken apart for plotting purpose only, to keep consistency of time axis). Please click here to view a larger version of this figure.
Figure 2. TMS artifacts and the subtraction technique. (A) Left – ERP time-locked to the presentation of an image of a face, with a double-pulse TMS at 60 msec and 100 msec after image onset. Each line represents an electrode. Note that for some electrodes the immediate TMS artifact is followed by a longer residual artifact. Right – Approximate coil location is symbolized by the two red circles, and a few electrodes are labeled for orientation; (B) Artifact-subtraction procedure. The immediate pulse artifact is removed (concealed), a template of the residual noise is measured based on "TMS only" trials and subtracted from full trials. Adapted with permission from Sadeh et al7. Please click here to view a larger version of this figure.
Figure 3. Stereotactic Navigation System. Top: Setting landmarks for corregistration. In order to corregister the structural scan of the head with the actual head position during the experiment, anatomical landmarks are marked on the image as shown by arrows. Then, the locations in space of the same landmarks on the subject's head are provided to the system with the aid of a specialized tracker that is detected by the camera. Bottom: Functional brain areas can be precisely targeted. Activations are overlaid on the anatomical image, and desired areas are marked and saved. During the session the experimenter can load a pre-defined area to target with TMS. Please click here to view a larger version of this figure.
Figure 4. Representative results. Double-pulse TMS was applied either to the right OFA or to the right EBA, at 60 msec and 100 msec after the onset of a face or a headless-body image. A dissociation between the face-N1 and the body-N1 responses was made. (A) The two target areas in a representative subject; (B) Left – double dissociation between the face and the body networks. TMS to the OFA enhanced the N1 response to faces, but not to bodies, relatively to TMS to the EBA. The opposite pattern is shown for headless-body stimuli. Right – N1 peak amplitude for faces and bodies, following OFA stimulation, EBA stimulation, and without TMS stimulation. Error bars denote the SEM. This figures was adapted with permission from Sadeh et al7. Please click here to view a larger version of this figure.
3.0T Signa MRI scanner | General Electric | ||
BrainAmp amplifier | Brain Products GmbH | BP-01300 | |
Electrode input box | Brain Products GmbH | Optional | |
PowerPack – battery for amplifier | Brain Products GmbH | BP-02615 | |
BrainCap – 32 flat electrodes on a flexible cap | Brain Products GmbH | BP-0300MR | 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 |
TMS Super Rapid2 stimulator | Magstim | ||
50mm double coil | Magstim | ||
Coil holder | 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 | ||
Chinrest | |||
Polaris infrared camera | Rogue Research Inc | ||
Polaris trackers and pointer tool | Rogue Research Inc | ||
BrainSight workstation and software | Rogue Research Inc | ||
BrainVision Recorder software | Brain Products GmbH | BP-00010 | |
MATLAB software | The MathWorks Icn. | ||
SPM for Matlab | Wellcome Department of Imaging Neuroscience, London, UK | ||
MarsBar region of interest toolbox for SPM | |||
Psychtoolbox for MATLAB | 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 | ||
E-Prime software | Psychology Software Tools, Inc. |
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'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.
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'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.
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'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.