Contact heat evoked potentials using simultaneous EEG and fMRI and their correlation with evoked pain
© Roberts et al; licensee BioMed Central Ltd. 2008
Received: 07 February 2008
Accepted: 17 December 2008
Published: 17 December 2008
The Contact Heat Evoked Potential Stimulator (CHEPS) utilises rapidly delivered heat pulses with adjustable peak temperatures to stimulate the differential warm/heat thresholds of receptors expressed by Aδ and C fibres. The resulting evoked potentials can be recorded and measured, providing a useful clinical tool for the study of thermal and nociceptive pathways. Concurrent recording of contact heat evoked potentials using electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has not previously been reported with CHEPS. Developing simultaneous EEG and fMRI with CHEPS is highly desirable, as it provides an opportunity to exploit the high temporal resolution of EEG and the high spatial resolution of fMRI to study the reaction of the human brain to thermal and nociceptive stimuli.
In this study we have recorded evoked potentials stimulated by 51°C contact heat pulses from CHEPS using EEG, under normal conditions (baseline), and during continuous and simultaneous acquisition of fMRI images in ten healthy volunteers, during two sessions. The pain evoked by CHEPS was recorded on a Visual Analogue Scale (VAS).
Analysis of EEG data revealed that the latencies and amplitudes of evoked potentials recorded during continuous fMRI did not differ significantly from baseline recordings. fMRI results were consistent with previous thermal pain studies, and showed Blood Oxygen Level Dependent (BOLD) changes in the insula, post-central gyrus, supplementary motor area (SMA), middle cingulate cortex and pre-central gyrus. There was a significant positive correlation between the evoked potential amplitude (EEG) and the psychophysical perception of pain on the VAS.
The results of this study demonstrate the feasibility of recording contact heat evoked potentials with EEG during continuous and simultaneous fMRI. The combined use of the two methods can lead to identification of distinct patterns of brain activity indicative of pain and pro-nociceptive sensitisation in healthy subjects and chronic pain patients. Further studies are required for the technique to progress as a useful tool in clinical trials of novel analgesics.
Functional magnetic resonance imaging (fMRI) has developed into a tool that is extensively used in non-invasive brain imaging. It provides information about cerebro-vascular activity throughout the whole brain with excellent spatial localisation, yet it is limited by the poor temporal resolution it offers, which is in the order of seconds. On the other hand, electroencephalogram (EEG) is recorded directly from the scalp of the subject and can provide information about neurophysiological activity with a very precise temporal resolution, in the order of milliseconds. The disadvantage of EEG however, is that localisation of the source of electrical activity within the brain is quite difficult.
Therefore the integration of these two techniques is highly desirable, and would allow the exploitation of the advantages of both techniques – high spatial resolution of fMRI and high temporal resolution of EEG. The technique would be widely applicable in all areas of neurophysiological research, but particularly in pain studies, where combined use of the two techniques could lead to the identification of distinct patterns of brain activity indicative of pain and pro-nociceptive sensitisation in healthy subjects and chronic pain patients. These patterns could prove useful in the assessment of the analgesic efficacy of novel analgesic compounds, adding to the desirability of co-registration of pain evoked potentials (such as those stimulated by contact heat) with EEG and fMRI.
Objective markers of pain could be less variable and/or more sensitive to analgesic treatments (i.e. EPs, fMRI). The present study enables the use of these markers to simultaneously assess pharmacodynamic-pharmacokinetic relationships and antihyperalgesic activity in single dose studies in experimental pain models in humans, and in pain patients (e.g. of novel agents that block TRPV1, the heat and capsaicin receptor). Pain biomarkers are needed to provide early pivotal information on efficacy, dose-response and time-course of TRPV1 antagonists, for strategic rapid and cost-effective drug development. Further, neuropathic pain patients would be expected to have reduced pain-evoked potential amplitudes but increased fMRI activation, different from volunteer or inflammatory models/conditions.
The use of simultaneous EEG and fMRI in pharmacological studies of novel analgesics would allow (i) measurement of the combined response to the same pharmacological intervention when the plasma concentration of the analgesic is at its peak (i.e. at the same time-course); (ii) recordings can be analysed at the single subject level, reducing inter-session variability, which is well recognised with regard to pain scores, and (iii) selection of the parameter which enables possible reduction in dose in clinical trials.
Simultaneous EEG and fMRI has already been utilised in studies of epilepsy , sleep , studies of human alpha activity [3, 4] and the study of auditory [5, 6], visual [7, 8], and motor activity . In the field of pain research, laser and electrically stimulated pain evoked potentials have been successfully co-registered using EEG and fMRI [10, 11], but CHEPS has the advantages of a larger area of stimulation, the ability to apply repetitive stimuli to the same cutaneous area without inducing erythema, and simplicity of use in the clinic (i.e. no eye protection required, easy to move location); however, one disadvantage of CHEPS is that in order to avoid habituation the thermode must be physically moved between stimuli.
Simultaneous EEG/fMRI is a readily feasible application yet the MR environment poses a number of technical challenges, limitations and safety issues (for a review of technical and safety issues see [12, 13]). The gradient switching fields and radiofrequency (RF) pulses of the MR scanner can create currents in conducting loops that can potentially cause heating of the electrodes and burns at the point of contact with the scalp of the subject. Therefore it is recommended to avoid loops and crossing over of electrode wires, and introduce current limiting resistors to electrode wires.
The gradient fields and RF pulses of the MR scanner can lead to artefacts that can obscure the signal recorded from the EEG, as can movements within the static magnetic field; movement of the head, talking, swallowing and even the pulsatile motion of the heart (ballistocardiogram artefact). The magnet's helium cold pump and gradient coils also produce mechanical vibrations that can be picked up by the EEG wires in the static magnetic field and converted to electrical noise. All these issues need to be addressed and overcome during experimental set-up and processing of EEG and fMRI data, in terms of patient safety and also preserving the quality of the data collected.
Until recently, quantifiable contact heat evoked potentials in EEG had been hard to elicit, due to technical limitations i.e. slow temperature rise and fall times. However, the contact heat evoked potential stimulator (CHEPS) has been designed with a maximum (adjustable) temperature rise time of 70°C/s. CHEPS can stimulate the differential thermal thresholds of receptors innervated by Aδ and C nociceptive nerve fibres, and has been shown to selectively excite these fibre subtypes in human hairy and glabrous skin . The latencies and amplitudes of heat evoked Aδ potentials stimulated by CHEPS have been shown to be robust and reproducible [15, 16], despite the disadvantage posed by the slow temperature rise time of the heat stimuli produced by CHEPS (70°C/s compared to a rise time of greater than 1000°C/s reported with lasers) which may lead to a reduction in temporal summation and thus a less synchronous afferent volley .
The compatibility of CHEPS with fMRI further widens its scope of application both in healthy volunteers for research purposes and in chronic pain patients. Reproducibility of blood oxygen level dependent (BOLD) responses and pain scores to CHEPS stimulation have already been illustrated in healthy volunteers .
In this human volunteer study we have assessed the feasibility of monitoring contact heat evoked Aδ potentials with simultaneous EEG and fMRI, and determined their relationship to the ratings of evoked pain.
Ten healthy volunteers were recruited to take part in this feasibility study (6 female, 4 male). The average age of participants was 27.7 years (range 22 – 35 years). Informed consent was taken from all subjects prior to commencement of the study and the study itself was approved by Hammersmith and Queen Charlotte's & Chelsea Research Ethics Committee (REC reference 06/Q0404/9).
Contact heat stimulation was performed using CHEPS (Medoc Ltd, Ramat Yishai, Israel) with a thermode area of 572.5 mm2, and a heating thermo-foil (Minco Products, Inc., Minneapolis, MN) covered with a 25 μm layer of thermo conductive plastic (Kapton®, thermal conductivity at 23°C of 0.1 – 0.35 W/m/K). The thermode heating rate was up to 70°C/s, the cooling rate up to 40°C/s and the baseline temperature was 32°C.
Baseline recording of evoked potentials was undertaken with the subject lying on the scanner table (outside the magnet) without any scanning taking place. Ten 51°C stimuli of approximately 800 ms duration (approximately 271 ms to reach peak temperature of 51°C and approximately 475 ms to return to baseline [total 746 ms]) and 7 s inter-stimulus interval were applied to the left volar forearm of the subject, and the thermode moved after each stimulus to avoid habituation.
Baseline and fMRI protocols were repeated on two occasions on all subjects to assess reproducibility.
After completion of baseline and fMRI protocols, subjects were asked to rate the pain of contact heat stimulation by CHEPS on a visual analogue scale (VAS), by placing a mark on a line 10 cm in length that was graded from 0 to 10, 0 being not painful at all, and 10 being the worst pain imaginable. The distance of the mark from 0 (in cm) was measured and noted as the pain score.
Electroencephalogram (EEG) recording
EEG was acquired from a 32 electrode cap using MRI compatible equipment (BrainCap MR, BrainAmp MR Plus 32 Amplifier, BrainProducts GmbH, Munich, Germany) with the subject relaxed and eyes opened. Electrodes were contacted with Abralyt 2000 electrode gel and impedance maintained below 5 k Ω (when the value of the 5 k Ω current limiting safety resistors [in place as standard on each electrode lead, close to the electrode itself] was subtracted). The data was acquired in a mono-polar fashion, which avoids the disadvantages of average reference recordings and allows for re-montaging of data after acquisition. The reference electrode was located in the FCz position, and the ground electrode in the Iz position. Vertical electro-oculogram (EOG) and electro-cardiogram (ECG) were monitored to allow exclusion of traces contaminated by eye blinks and to enable pulse artefact subtraction. EEG signals were digitised and transmitted to acquisition equipment outside the scanner room by optical fibre. For the baseline recording (outside the scanner) a sampling rate of 250 Hz was applied, and for fMRI recording (inside the scanner) a sampling rate of 5000 Hz was applied. Online low and high pass filters (10 s and 250 Hz respectively) were also applied to the EEG data recorded during baseline and fMRI protocols. CHEPS stimulation and scan events were registered on a trigger channel connected to the acquisition equipment.
EEG data was analysed using a dedicated software package (BrainVision Analyser Version 1.05.0002, BrainProducts GmbH, Munich, Germany). The baseline EEG data was filtered (low pass 0.5305 Hz, high pass 40 Hz), segmented around the trigger input from CHEPS, corrected for blinks using the Gratton and Coles correction algorithm, averaged (10 segments), and re-referenced to an average reference. A baseline correction was applied from -200 to 0 ms pre-stimulus.
The EEG data recorded during fMRI was corrected for scan artefacts using an MRI correction solution provided with the analysis software, using subtraction algorithms based on methods originally developed by Allen and colleagues . Scan start points were detected and marked (using average gradient and criterion for continuous scans) and corrected (using template drift correction). Pulse artefacts were also removed using a solution provided with the analysis software (correction by R peaks – demeaned amplitude algorithm used for R peak detection). Independent component analysis (ICA) was carried out on all data sets, and trials contaminated by subject movement or ocular artefacts were identified visually and removed in the ICA back transform. The data was segmented, averaged (33 segments), re-referenced and a baseline correction applied (as above for the baseline recorded data).
All EEG data is reported from the Cz electrode, with an average reference. The latency of heat evoked Aδ potentials was measured from the first definitive negative peak (N2) and the amplitude measured peak to peak – N2 to P2 (the N2 to P2 component was defined as the peak within a time window of 250 – 550 ms).
Graphs were created and statistical tests performed on EEG data using GraphPad Prism (Version 3.02 for Windows, GraphPad Software, San Diego California USA).
In each scanning session, 275 fMRI scans were acquired on a 1.5 T Siemens Avanto magnetic resonance scanner (Siemens Medical Systems, Erlangen, Germany) with a standard head array coil. 19 slices parallel to the anterior commisure and the posterior commisure (AC/PC line) were acquired using a gradient echo EPI (Echo Planar Imaging) sequence (Repetition time/Echo time (TR/TE) = 2.3 s/53 ms, flip angle = 90°, field-of-view (FOV) = 23 cm, matrix = 64 × 64, voxel size = 3.6 mm × 3.6 mm × 5 mm). A high resolution T1-MP-RAGE anatomical scan was also obtained (TR/TE = 11 ms/5.2 ms, flip angle = 15°, FOV = 23 cm, matrix = 256 × 256, voxel size = 0.9 mm × 0.9 mm × 1 mm).
To achieve synchronization, the trigger output of the scanner was used to initialize the fMRI paradigm and triggers from CHEPS stimulation and the scanner were recorded together with the EEG signals.
Processing of fMRI images was performed using SPM5 (Functional Imaging Laboratory, London, UK). Due to T1 saturation effects, the first 5 volumes of each acquisition were discarded, leaving 270 volumes. Each dataset was realigned to correct for any motion during the acquisition, time corrected due to differences in image acquisition time between slices, followed by normalisation to transform the data to match the SPM template. The template images supplied with SPM conform to the space defined by the ICBM, NIH P-20 project, and approximate that of the space described in the atlas of . Finally, images were smoothed using an isotropic Gaussian Kernel (8 mm full-width-at-half-maximum).
Statistical analysis was based on the General Linear Model (GLM). For within subject analysis the scanning paradigm was specified in SPM and a first level model estimation was performed. The event responses were modelled onto a design matrix by specifying their onset times and their duration. For the group analysis of the ten subjects, a canonical, random effects model (RFX) was used to make a population inference (corrected p < 0.05). Spatial extend thresholding (voxel threshold = 135 mm3) was carried out to exclude isolated voxels or small groups and only show clusters of activation. An average brain, representative of all 10 subjects was determined by averaging the normalised structural brain volumes. Significantly activated regions resulting from the group analysis were superimposed on the average brain. The location of the activated regions was assessed using SPM Anatomy toolbox.
To assess correlation between fMRI activation and evoked potential amplitude (or VAS scores), values collected for each subject were entered as covariates using simple regression analysis in SPM5.
Contact heat evoked potentials
The average evoked potential latencies for the first baseline protocol were (mean ± SEM) N2: 0.316 ± 0.009 s, P2: 0.429 ± 0.015 s, and for the second baseline protocol repeated on a separate occasion were N2: 0.322 ± 0.010 s, P2: 0.432 ± 0.013 s. The latencies for the first fMRI protocol were N2: 0.314 ± 0.008 s, P2 0.446 ± 0.017 s, and for the second, N2: 0.317 ± 0.009 s, P2: 0.443 ± 0.015 s. These latencies were approximately 0.100 s longer than those reported in LEP studies, and this is most likely due to the slower temperature rise time of CHEPS (and thus longer stimulus duration) in comparison to laser stimuli, which may lead to slower activation of nociceptors and a reduction of temporal summation [17, 22].
Evoked potentials and pain scores recorded during baseline and fMRI protocols in healthy volunteers.
N2 latency (s)
0.319 ± 0.006
24.87 ± 2.15
5.30 ± 0.53
0.317 ± 0.006
24.49 ± 2.77
5.97 ± 0.57
ns (p = 0.4183)
ns (p = 0.3402)
ns (p = 0.1918)
Mean ± SEM
ns = not significant
Differences in overall averages for evoked responses were noted between males and females, with evoked potentials recorded from females having a faster latency (F 0.302 ± 0.004 s vs. M 0.345 ± 0.009 s, p = 0.0003) and a larger amplitude (F 27.62 ± 2.87 μV vs. M 18.47 ± 1.78 μV, p = 0.0286).
No significant correlation between subject age and overall evoked potential latency or amplitude was observed (rs = 0.2298, p = 0.2567; rs = 0.1043, p = 0.3925 respectively).
Areas of BOLD fMRI activation after stimulation using CHEPS.
Cluster 1 (501 vox)
Right Superior Frontal Gyrus
Right Precentral Gyrus
Right Middle Cingulate Cortex
Cluster 2 (366 vox)
Right SupraMarginal Gyrus
Right Postcentral Gyrus
Right Heschls Gyrus
Cluster 3 (357 vox)
Left SupraMarginal Gyrus
Left Postcentral Gyrus
Cluster 4 (221 vox)
Left Insula Lobe
Left Rolandic Operculum
Left Precentral Gyrus
Left Inferior Frontal Gyrus
Cluster 5 (208 vox)
Right Postcentral Gyrus
Right Inferior Parietal Lobule
Cluster 6 (7 vox)
Right Insula Lobe
Although the thermode was moved randomly, it is possible that there could be some contribution of the touch sensation to the measured BOLD response. To avoid this, the movement of the thermode should be modelled as a nuisance covariate in future experiments.
Stimulation at 51°C with the CHEPS probe elicited a painful sensation in all ten subjects. There was no significant difference between reported VAS ratings for baseline and fMRI protocols (Table 1).
Female subjects were noted to have a significantly higher VAS than males for CHEPS stimulation (p = 0.0416). No correlation between age and average reported VAS was observed (rs = 0.1534, p = 0.3410).
The regression analysis in SPM showed no correlation between BOLD signal and evoked potential amplitudes or VAS scores.
In this study we have demonstrated that it is feasible to record brain activity in response to noxious thermal stimulation (51°C contact heat) with CHEPS, using simultaneous EEG and fMRI. The EEG recorded during fMRI acquisition was unaffected by the additional processing steps required to remove MRI related artefacts. These artefacts can contaminate the raw data and their removal can compromise the quality of the EEG signal. However, our simultaneously acquired EEG revealed heat evoked Aδ potentials that were reproducible across the two separate fMRI sessions. Although the aim of this feasibility study was not to directly compare the measurements inside and outside the scanner, the amplitudes and latencies recorded inside the scanner were consistent with those recorded in two baseline (control) sessions (Figure 3, Table 1), suggesting there was no signal degradation or reduction of signal to noise ratio caused by conditions in the MRI environment or additional processing requirements. This is in agreement with a similar study using laser-evoked pain conducted by Iannetti and colleagues in 2005, which also showed no variation in amplitude or latency of Aδ evoked potentials inside and outside the scanner. A study of auditory evoked potentials with concurrent fMRI has shown a difference in the latency and amplitude of the N1 component of the event related potential, with longer latencies and higher amplitudes recorded outside the scanner, however no difference in latency or amplitude of the P300 component of the response .
To avoid MRI induced artefacts contaminating EEG data, some groups have recorded EEG and fMRI separately , or employed an "interleaved" approach, where EEG is recorded during gaps in fMRI image acquisition to avoid artefacts in the EEG data, or short "burst" or "sparse" fMRI protocols are used, avoiding EEG data collection during image acquisition [11, 20, 24–28]. Despite avoiding most of the technical issues of using truly simultaneous EEG and fMRI, these interleaved protocols have theoretical drawbacks – the two methods are not monitoring the same neurophysiological event when they are recorded separately from one another, which is a disadvantage when the brain activity being studied is in any way unpredictable (such as spike activity in epilepsy, or sleep studies) or changeable (effects of habituation or learning).
Our contact heat evoked potential data has also highlighted a possible gender related difference in the latencies and amplitudes of responses – with female volunteers exhibiting an earlier latency and larger amplitude of response than male volunteers, and also a higher reported VAS score after CHEPS stimulation, an effect that has previously been noted . However, in contrast to this study (which was also conducted in volunteers), there is no effect of subject age upon the latency and amplitude of evoked responses in our data set, or the VAS reported after contact heat stimulation. This may be due to the limited age range in our study, or the small number of subjects recruited. If the number of subjects was increased and the age range broadened, then an age dependent effect may be observed.
Prior to scanning volunteers we used phantom QA tests to assess whether the EEG recording equipment and the CHEPS stimulation device affected the quality of the fMRI images. This included signal-to-noise, ghosting measurements and visual inspection of any artefacts. Our results showed that the fMRI images acquired alongside evoked potential recordings were unaffected by the simultaneous EEG acquisition, and were not impaired by the presence of the EEG recording and CHEPS equipment inside the scanner.
The results we obtained agree with previously published data showing patterns of brain activation after nociceptive and noxious thermal stimulation [10, 11, 18, 30–34], with BOLD changes apparent in the insula, post-central gyrus, SMA, middle cingulate cortex and pre-central gyrus (Figure 4). Cooling of the CHEPS thermode back to baseline temperature will activate cool sensitive-fibres and this could potentially affect the BOLD response; however, the fMRI changes we observed were similar to those obtained with other methods of stimulation with noxious stimuli (these would be primarily related to the initial upstroke of the heat stimulus).
In accord with other studies of pain-evoked potentials, our data has revealed a significant positive correlation between evoked potential amplitude and reported pain scores or pain intensity [15, 29, 32, 35, 36] (Figure 6a, b). However, this simple positive relationship with subjective pain scores was not present in the fMRI signal change data, even when regions of interest were analysed separately. This is unlike a recent study of painful electrical stimulation, which showed a positive correlation between stimulus correlated BOLD responses in a network of cortical and cerebellar areas and reported pain intensity , and other studies using fMRI that have shown signal changes to correlate with pain intensity, or subjective experience of pain [37, 38]. However these studies have either grouped subjects according to their sensitivity to heat stimuli , set stimuli according to individual thresholds , or used various stimulus intensities . Our fMRI protocol used a stimulus at only one intensity for all subjects in the study, which may explain why no correlation with pain scores could be seen in our fMRI data. In protocols that lead on from this feasibility study stimuli at or just above the pain threshold for each individual will be used. While correlations were made with VAS scores as they are widely used in clinical trials of analgesics, these must be regarded with caution, as VAS scores are ordinal and not linear measures of pain perception – further studies and analyses using an interval scale (Rasch model) would be of interest ).
This study demonstrates the feasibility of recording contact heat evoked potentials with simultaneous EEG and fMRI. Evoked potentials monitored inside the MRI scanner were similar to those recorded under baseline conditions and were highly reproducible on two occasions. We have also demonstrated a linear relationship between evoked potential amplitude and VAS score, as shown in previous volunteer studies. fMRI group analysis showed BOLD activation in areas shown to be associated with nociception in previous publications, but there was no simple correlation of regional fMRI signal changes with individual pain scores – suggesting changes in BOLD signal may reflect later processing in cerebral pathways rather than encoding pain intensity in a linear fashion. Further studies are in progress to demonstrate that simultaneous CHEPS-evoked potentials and fMRI is a useful tool in clinical trials of novel analgesics.
The authors would like to thank the BBSRC and also GlaxoSmithKline PLC for financial assistance, and in particular Dr Boris Chizh, Dr Zahid Ali, and Dr David Stephens of GlaxoSmithKline for helpful discussions.
- Stern JM: Simultaneous electroencephalography and functional magnetic resonance imaging applied to epilepsy. Epilepsy Behav. 2006, 8 (4): 683-692. 10.1016/j.yebeh.2006.03.002.View ArticlePubMedGoogle Scholar
- Czisch M, Wetter TC, Kaufmann C, Pollmacher T, Holsboer F, Auer DP: Altered processing of acoustic stimuli during sleep: reduced auditory activation and visual deactivation detected by a combined fMRI/EEG study. Neuroimage. 2002, 16 (1): 251-258. 10.1006/nimg.2002.1071.View ArticlePubMedGoogle Scholar
- Goncalves SI, de Munck JC, Pouwels PJ, Schoonhoven R, Kuijer JP, Maurits NM, Hoogduin JM, Van Someren EJ, Heethaar RM, Lopes da Silva FH: Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: inter-subject variability. Neuroimage. 2006, 30 (1): 203-213. 10.1016/j.neuroimage.2005.09.062.View ArticlePubMedGoogle Scholar
- Laufs H, Kleinschmidt A, Beyerle A, Eger E, Salek-Haddadi A, Preibisch C, Krakow K: EEG-correlated fMRI of human alpha activity. Neuroimage. 2003, 19 (4): 1463-1476. 10.1016/S1053-8119(03)00286-6.View ArticlePubMedGoogle Scholar
- Mulert C, Jager L, Schmitt R, Bussfeld P, Pogarell O, Moller HJ, Juckel G, Hegerl U: Integration of fMRI and simultaneous EEG: towards a comprehensive understanding of localization and time-course of brain activity in target detection. Neuroimage. 2004, 22 (1): 83-94. 10.1016/j.neuroimage.2003.10.051.View ArticlePubMedGoogle Scholar
- Scarff CJ, Reynolds A, Goodyear BG, Ponton CW, Dort JC, Eggermont JJ: Simultaneous 3-T fMRI and high-density recording of human auditory evoked potentials. Neuroimage. 2004, 23 (3): 1129-1142. 10.1016/j.neuroimage.2004.07.035.View ArticlePubMedGoogle Scholar
- Comi E, Annovazzi P, Silva AM, Cursi M, Blasi V, Cadioli M, Inuggi A, Falini A, Comi G, Leocani L: Visual evoked potentials may be recorded simultaneously with fMRI scanning: A validation study. Hum Brain Mapp. 2005, 24 (4): 291-298. 10.1002/hbm.20087.View ArticlePubMedGoogle Scholar
- Henning S, Merboldt KD, Frahm J: Simultaneous recordings of visual evoked potentials and BOLD MRI activations in response to visual motion processing. NMR Biomed. 2005, 18 (8): 543-552. 10.1002/nbm.988.View ArticlePubMedGoogle Scholar
- Lazeyras F, Zimine I, Blanke O, Perrig SH, Seeck M: Functional MRI with simultaneous EEG recording: feasibility and application to motor and visual activation. J Magn Reson Imaging. 2001, 13 (6): 943-948. 10.1002/jmri.1135.View ArticlePubMedGoogle Scholar
- Iannetti GD, Niazy RK, Wise RG, Jezzard P, Brooks JC, Zambreanu L, Vennart W, Matthews PM, Tracey I: Simultaneous recording of laser-evoked brain potentials and continuous, high-field functional magnetic resonance imaging in humans. Neuroimage. 2005, 28 (3): 708-719. 10.1016/j.neuroimage.2005.06.060.View ArticlePubMedGoogle Scholar
- Christmann C, Koeppe C, Braus DF, Ruf M, Flor H: A simultaneous EEG-fMRI study of painful electric stimulation. Neuroimage. 2007, 34 (4): 1428-1437. 10.1016/j.neuroimage.2006.11.006.View ArticlePubMedGoogle Scholar
- Lemieux L, Allen PJ, Franconi F, Symms MR, Fish DR: Recording of EEG during fMRI experiments: patient safety. Magn Reson Med. 1997, 38 (6): 943-952. 10.1002/mrm.1910380614.View ArticlePubMedGoogle Scholar
- Lemieux L, Allen P, Krakow K, Symms MR, Fish DR: Methodological Issues in EEG-correlated Functional MRI Experiments. IJBEM. 1999, 1 (1): 87-95.Google Scholar
- Granovsky Y, Matre D, Sokolik A, Lorenz J, Casey KL: Thermoreceptive innervation of human glabrous and hairy skin: a contact heat evoked potential analysis. Pain. 2005, 115 (3): 238-247.View ArticlePubMedGoogle Scholar
- Chen AC, Niddam DM, Arendt-Nielsen L: Contact heat evoked potentials as a valid means to study nociceptive pathways in human subjects. Neurosci Lett. 2001, 316 (2): 79-82. 10.1016/S0304-3940(01)02374-6.View ArticlePubMedGoogle Scholar
- Le Pera D, Valeriani M, Niddam D, Chen AC, Arendt-Nielsen L: Contact heat evoked potentials to painful and non-painful stimuli: effect of attention towards stimulus properties. Brain Topogr. 2002, 15 (2): 115-123. 10.1023/A:1021472524739.View ArticlePubMedGoogle Scholar
- Iannetti GD, Zambreanu L, Tracey I: Similar nociceptive afferents mediate psychophysical and electrophysiological responses to heat stimulation of glabrous and hairy skin in humans. J Physiol. 2006, 577 (Pt 1): 235-248. 10.1113/jphysiol.2006.115675.View ArticlePubMedPubMed CentralGoogle Scholar
- Howard M, Coen S, Buchanan T, Smart T, Gregory S, Williams S, Huggins J, Hanna M: Test-retest Reproducibility of Cerebral and Subjective Responses to Painful and Non-painful Contact-Heat Evoked Potential Stimulation (CHEPS) [abstract]. Eur J Pain. 2006, 10 (S1): S82-10.1016/S1090-3801(06)60308-X.View ArticleGoogle Scholar
- Greffrath W, Baumgartner U, Treede RD: Peripheral and central components of habituation of heat pain perception and evoked potentials in humans. Pain. 2007Google Scholar
- Portas CM, Krakow K, Allen P, Josephs O, Armony JL, Frith CD: Auditory processing across the sleep-wake cycle: simultaneous EEG and fMRI monitoring in humans. Neuron. 2000, 28 (3): 991-999. 10.1016/S0896-6273(00)00169-0.View ArticlePubMedGoogle Scholar
- Talairach J, Tournoux P: Co-planar stereotaxic atlas of the human brain. 1988, Thieme Publishing Group, New YorkGoogle Scholar
- Truini A, Galeotti F, Romaniello A, Virtuoso M, Iannetti GD, Cruccu G: Laser-evoked potentials: normative values. Clin Neurophysiol. 2005, 116 (4): 821-826. 10.1016/j.clinph.2004.10.004.View ArticlePubMedGoogle Scholar
- Ball T, Schreiber A, Feige B, Wagner M, Lucking CH, Kristeva-Feige R: The role of higher-order motor areas in voluntary movement as revealed by high-resolution EEG and fMRI. Neuroimage. 1999, 10 (6): 682-694. 10.1006/nimg.1999.0507.View ArticlePubMedGoogle Scholar
- Bonmassar G, Schwartz DP, Liu AK, Kwong KK, Dale AM, Belliveau JW: Spatiotemporal brain imaging of visual-evoked activity using interleaved EEG and fMRI recordings. Neuroimage. 2001, 13 (6 Pt 1): 1035-1043. 10.1006/nimg.2001.0754.View ArticlePubMedGoogle Scholar
- Garreffa G, Bianciardi M, Hagberg GE, Macaluso E, Marciani MG, Maraviglia B, Abbafati M, Carni M, Bruni I, Bianchi L: Simultaneous EEG-fMRI acquisition: how far is it from being a standardized technique?. Magn Reson Imaging. 2004, 22 (10): 1445-1455. 10.1016/j.mri.2004.10.013.View ArticlePubMedGoogle Scholar
- Kruggel F, Herrmann CS, Wiggins CJ, von Cramon DY: Hemodynamic and electroencephalographic responses to illusory figures: recording of the evoked potentials during functional MRI. Neuroimage. 2001, 14 (6): 1327-1336. 10.1006/nimg.2001.0948.View ArticlePubMedGoogle Scholar
- Muller BW, Stude P, Nebel K, Wiese H, Ladd ME, Forsting M, Jueptner M: Sparse imaging of the auditory oddball task with functional MRI. Neuroreport. 2003, 14 (12): 1597-1601. 10.1097/00001756-200308260-00011.View ArticlePubMedGoogle Scholar
- Nebel K, Stude P, Wiese H, Muller B, de Greiff A, Forsting M, Diener HC, Keidel M: Sparse imaging and continuous event-related fMRI in the visual domain: a systematic comparison. Hum Brain Mapp. 2005, 24 (2): 130-143. 10.1002/hbm.20075.View ArticlePubMedGoogle Scholar
- Cheng SS, Liu JY, Hsui YR, Chang ST: Chemical polymorphism and antifungal activity of essential oils from leaves of different provenances of indigenous cinnamon (Cinnamomum osmophloeum). Bioresour Technol. 2006, 97 (2): 306-312. 10.1016/j.biortech.2005.02.030.View ArticlePubMedGoogle Scholar
- Peyron R, Laurent B, Garcia-Larrea L: Functional imaging of brain responses to pain. A review and meta-analysis (2000). Neurophysiol Clin. 2000, 30 (5): 263-288. 10.1016/S0987-7053(00)00227-6.View ArticlePubMedGoogle Scholar
- Ingvar M: Pain and functional imaging. Philos Trans R Soc Lond B Biol Sci. 1999, 354 (1387): 1347-1358. 10.1098/rstb.1999.0483.View ArticlePubMedPubMed CentralGoogle Scholar
- Qiu Y, Noguchi Y, Honda M, Nakata H, Tamura Y, Tanaka S, Sadato N, Wang X, Inui K, Kakigi R: Brain Processing of the Signals Ascending Through Unmyelinated C Fibers in Humans: An Event-Related Functional Magnetic Resonance Imaging Study. Cereb Cortex. 2006, 16 (9): 1289-1295. 10.1093/cercor/bhj071.View ArticlePubMedGoogle Scholar
- Brooks JC, Nurmikko TJ, Bimson WE, Singh KD, Roberts N: fMRI of thermal pain: effects of stimulus laterality and attention. Neuroimage. 2002, 15 (2): 293-301. 10.1006/nimg.2001.0974.View ArticlePubMedGoogle Scholar
- Moulton EA, Keaser ML, Gullapalli RP, Greenspan JD: Regional intensive and temporal patterns of functional MRI activation distinguishing noxious and innocuous contact heat. J Neurophysiol. 2005, 93 (4): 2183-2193. 10.1152/jn.01025.2004.View ArticlePubMedGoogle Scholar
- Ohara S, Crone NE, Weiss N, Treede RD, Lenz FA: Amplitudes of laser evoked potential recorded from primary somatosensory, parasylvian and medial frontal cortex are graded with stimulus intensity. Pain. 2004, 110 (1–2): 318-328. 10.1016/j.pain.2004.04.009.View ArticlePubMedGoogle Scholar
- Granovsky Y, Granot M, Nir RR, Yarnitsky D: Objective Correlate of Subjective Pain Perception by Contact Heat-Evoked Potentials. J Pain. 2007Google Scholar
- Bornhovd K, Quante M, Glauche V, Bromm B, Weiller C, Buchel C: Painful stimuli evoke different stimulus-response functions in the amygdala, prefrontal, insula and somatosensory cortex: a single-trial fMRI study. Brain. 2002, 125 (Pt 6): 1326-1336. 10.1093/brain/awf137.View ArticlePubMedGoogle Scholar
- Coghill RC, McHaffie JG, Yen YF: Neural correlates of interindividual differences in the subjective experience of pain. Proc Natl Acad Sci USA. 2003, 100 (14): 8538-8542. 10.1073/pnas.1430684100.View ArticlePubMedPubMed CentralGoogle Scholar
- Decruynaere C, Thonnard JL, Plaghki L: Measure of experimental pain using Rasch analysis. Eur J Pain. 2007, 11 (4): 469-474. 10.1016/j.ejpain.2006.07.001.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2253/8/8/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.