- Email: [email protected]
EEG sources of the 170-ms response to faces are co-localized in the fusiform gyrus
www.elsevier.com/locate/ynimg NeuroImage 35 (2007) 1495 – 1501
Technical Note
MEG/EEG sources of the 170-ms response to faces are co-localized in the fusiform gyrus Iris Deffke, a,⁎ Tilmann Sander, b Jens Heidenreich, d Werner Sommer, c Gabriel Curio, a Lutz Trahms, b and Andreas Lueschow a a
Department of Neurology, Campus Benjamin Franklin, Charité-University-Medicine-Berlin, Hindenburgdamm 30, 12200, Berlin, Germany Physikalisch–Technische Bundesanstalt, Berlin, Germany c Biological Psychology, Humboldt-University, Berlin, Germany d Department of Radiology and Nuclear Medicine, Campus Benjamin Franklin, Charité-University-Medicine-Berlin, Berlin, Germany b
Received 26 September 2005; revised 24 January 2007; accepted 25 January 2007 Available online 13 February 2007 The 170-ms electrophysiological processing stage (N170 in EEG, M170 in MEG) is considered an important computational step in face processing. Hence its neuronal sources have been modelled in several studies. The current study aimed to specify the relation of the dipolar sources underlying N170 and M170. Whole head EEG and MEG were measured simultaneously during the presentation of unfamiliar faces. An Independent Component Analysis (ICA) was applied to the data prior to localization. N170 and M170 were then modelled with a pair of dipoles in a four-shell ellipse (EEG)/ homogeneous sphere (MEG) arranged symmetrically across midline. The dipole locations were projected onto the individual structural MR brain images. Dipoles were localized in fusiform gyri in ten out of eleven individuals for EEG and in seven out of eleven for MEG. N170 and M170 were co-localized in the fusiform gyrus in six individuals. The ICA shifted some of the single-subject dipoles up from cerebellum to fusiform gyrus mainly due to the removal of cardiac activity. The group mean dipole locations were also found in posterior fusiform gyri, and did not differ significantly between EEG and MEG. The result was replicated in a repeated measurement 3 months later. © 2007 Elsevier Inc. All rights reserved. Keywords: Face processing; N170; M170; Equivalent current dipole (ECD); Source localization; Fusiform gyrus
Introduction Perceiving and recognizing faces is considered one of the most complex and demanding visual processes. Electroencephalographic (EEG) studies have reported a positive face-specific event-related potential (ERP) at the vertex around 150 ms after face presentation onset (the vertex positive potential, VPP) (Botzel and ⁎ Corresponding author. Fax: +49 030 8445 4264. E-mail address: [email protected] (I. Deffke). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2007.01.034
Grusser, 1989; Jeffreys, 1989; Jeffreys and Tukmachi, 1992). Further, a negative deflection at right and left posterior electrodes can be recorded around 170 ms after face presentations (N170, e.g. Bentin et al., 1996). The N170 has been related to the configural processing of face features and their integration into a holistic face percept (Bentin and Deouell, 2000; Schweinberger et al., 2002; Carbon et al., 2005). N170 and VPP depend on the same neural generator, a main factor contributing to apparent functional differences between both components being the choice of the reference electrode (Joyce and Rossion, 2005). Using magnetoencephalography (MEG), face-specific eventrelated magnetic fields (ERFs) have been recorded at posterior sensors around the same latency as the N170 (e.g. Lu et al., 1991; Sato et al., 1999; Watanabe et al., 1999; Halgren et al., 2000; Liu et al., 2002; Hoshiyama et al., 2003; Lewis et al., 2003). These ERFs have been related to configural face encoding and to the identification of faces (Halgren et al., 2000; Liu et al., 2002). Several studies have modelled the cortical sources underlying N170 and M170 as equivalent current dipoles (ECDs). N170 sources have been localized to the fusiform gyri (FG) (Rossion et al., 2003), or to the FG and additional structures such as the lingual gyri (Mnatsakanian and Tarkka, 2004). Other EEG studies found entirely different generators such as the lateral occipitotemporal cortex (Schweinberger et al., 2002) or the superior temporal sulci (Itier and Taylor, 2004). In contrast, the M170 source has been consistently localized in or close to the FG (Linkenkaer-Hansen et al., 1998; Sato et al., 1999; Watanabe et al., 1999; Lewis et al., 2003; Halgren et al., 2000; Hoshiyama et al., 2003). The reason for the larger heterogeneity of results in localization studies of the N170 than the M170 is unclear. Critical factors may be task and stimulus as well as recording technique. MEG has become more widely used over the last years in the study of face processing. The current study aimed at a specification of the relation between face-related N170 and M170 sources by localizing them on simultaneously recorded EEG and MEG data. The data quality was improved by removing noise with the help of
1496
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
Independent Component Analysis (ICA). To account for individual differences in functional neuroanatomy, dipoles were localized on single-subject data. The robustness of the localizations was examined by repeating the experiment after 3 months with the same participants.
where reaction time and error rate were measured. This procedure was introduced to enhance the familiarity of the face stimuli. In Session 2, we did not find any effects of prior exposure to the face stimuli on the N170 or M170, and again no priming effects for N/ M170. We thus used the data to examine the robustness of the dipole localizations.
Material and methods EEG and MEG measurement The recent study is part of a broader research project on electrophysiological correlates of face priming processes. Its design will be described here as long as it is relevant for the reported results. Subjects Eleven right-handed healthy persons (7 women; mean age = 25.9, S.D. = 3.8, range 19 to 35 years) participated in the study. All persons had normal or corrected to normal vision. The ethics committee of the Charité, Campus Benjamin Franklin, approved of the study design. All participants gave their written informed consent. Stimuli and experimental paradigm 380 black and white photographs of unfamiliar faces taken from a front perspective were shown (300 adults, 80 children; see Fig. 1 for an example of the face stimuli and their presentation sequence). None of the persons depicted wore glasses, a beard, or other additional items. The experimental task consisted of an age classification. Subjects had to decide as fast as possible whether a child (8– 9 years) or an adult (20–30 years) face was shown. In a continuous repetition priming paradigm, all faces were repeated four times. The effect of the lag between repetitions was studied by repeating one half of the faces after 3 intervening faces (6 s) and the other half after 90 intervening faces (3 min). During the interstimulus interval (ISI), a fixation cross was shown. The length of the ISI varied between 500 and 1100 ms (mean 800 ms). Face repetition had no effect on the N170 and M170 amplitudes [all ANOVA main effects of repetition: F < 0.9, p > .44; see Fig. 2 for the short lag repetitions]. Taking advantage of the absence of priming effects, trials were averaged across all four repetitions. After eliminating ∼ 20% of EOG-artefact contaminated trials, app. 1000 trials per subject could be used for averaging. To test the impact of familiarity on priming effects the identical experiment was repeated 3 months later (Session 2) in ten of the eleven participants. On 2 consecutive days before Session 2, they performed different behavioural face tasks (e.g. a one-back task)
Fig. 1. Example of successive face presentations in the experiment.
EEG and MEG were measured simultaneously in an electrically and magnetically shielded room. EEG was recorded from 27 electrodes attached to a cap (positions: O1, O2, PO9, PO10, T5, T6, T1, T2, T3, T4, Pz, P3, P4, CP5, CP6, Cz, C3, C4, Fz, Fc1, Fc2, Fc5, Fc6, F3, F4, F7, F8) using a reference electrode on the nose. The magnetic fields were recorded with a 93-channel wholehead MEG system (Eagle Technology™, ET160). Axial gradiometers with a baseline of 5 cm were employed. Vertical and horizontal electrooculograms (EOG) were recorded. EEG and EOG electrode impedances below 50 kΩ were found to be sufficient. This was due to the high input impedance of 20 mΩ of the EEG amplifier used and its low noise of 6.5 nV Hz− 1/2 (Scheer et al., 2006). EEG and MEG were digitized with a sampling rate of 500 Hz and a bandpass filter of 0.1–200 Hz. Offline, the data were downsampled to 250 Hz and bandpass-filtered between 0.5 and 40 Hz. To remove eye artefacts (EOG) in the data and artefacts caused by the magnetic field of the heart, the MEG data were submitted to an Independent Component Analysis (ICA) before averaging (Sander et al., 2002). Likewise, an ICA was computed on the EEG data, which served mainly to remove EOG. In addition to the ICA correction EOG-artefact contaminated epochs were excluded in the conventional fashion. ERPs and ERFs were calculated over 1200 ms with a pre-stimulus baseline of 200 ms. We report results with and without ICA correction to compare the effects of ICA on the localization results. Acquisition of structural magnetic resonance brain images (MRI) and co-registration of EEG/MEG sensor positions In 9 participants, we acquired a coronally orientated highresolution T1-weighted multiplanar three-dimensional reconstruction of MR (MPR) (TR 15 ms, TE 7 ms, flip angle 8°, 148 partitions, slab thickness 220 mm, 1.49 × 0.98 × 0.98 mm nominal pixel resolution). A 1.5 T MRI scanner (Magnetom Vision™, Siemens, Erlangen) was used. In Brain Voyager 2000™, voxel size was spatially resampled to 1.0 × 1.0 × 1.0 mm. The resulting images were standardized to Talairach space (Talairach and Tournaux, 1988). The head position in the MEG system was measured with the help of five magnetic marker coils. One coil was attached close to the nasion (∼1 cm distance), two on the left and right forehead, and the two remaining coils close to the left and right preauricular points (∼ 1 cm away). The possibility of detecting head tilts in all directions was ensured by the large spatial separation between the coils at the preauricular points and the ones at the front of the head. After EEG/MEG acquisition, the positions of the EEG electrodes, MEG markers, and the standard anatomical landmarks (fiducials) were measured in three-dimensional space. This was done with the help of an ultrasonic system (Zebris 3D Measurement of Movement CSM20S). The head coordinate system was defined by the fiducials nasion and left and right preauricular
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
1497
Fig. 2. Grand-averaged ERPs, ERFs and EOGs recorded to the face repetitions with short lag. ERP grand averages comprise single-subject responses at electrodes PO9 and PO10. ERF grand averages were based upon spatial averages of single-subject responses. Spatial averages represent the mean of the channel with the largest M170 amplitude and neighbouring channels showing at least 70% of the highest response. Note the absence of priming effects on the N170 and M170.
points. The magnetic marker positions were used to make the coordinate transformation of the MEG sensors into the head coordinate system. The EEG electrode positions were given directly in the head coordinate system. Dipole localization for single subjects The dipole localizations were calculated with the program Brain Electrical Source Analysis (BESA 2000™, MEGIS Software, Gräfelfing, Germany). N170/M170 were defined as event-related potential/field with maximal strength at posterior channel locations between 120 and 200 ms after face onset. The dipole fit time intervals covered the peak of the N170/M170 and a time interval around the peak comprising data points from 100% to approx. 70% of the peak amplitude. We used a four-shell (brain, cerebrospinal fluid, bone, scalp) ellipsoidal head model for EEG (Berg and Scherg, 1994) and a single-layer spherical head model for MEG modelling. N170 and M170 were each modelled by two single dipoles. A symmetry constraint was introduced. The two dipoles had to lie symmetrically in the right and left hemisphere. This was due to the observation that without the use of a symmetry constraint, we had neither obtained physiologically plausible EEG nor MEG localization results for a considerable number of subjects. For example, the sources were located in the middle between both hemispheres, with one source in the frontal and one in the occipital cortex. In other cases sources were located outside of the cortex. Despite being a strong a priori constraint the assumption of symmetric sources underlying N170 and M170 has physiological plausibility. fMRI studies (e.g. Kanwisher et al., 1997; Horovitz et al., 2004) found symmetric face-related activations in the occipitotemporal cortex.
In intracranial recordings (Allison et al., 1999), N200 locations (the N200 being a likely analogue of the surface-recorded N/M170) clustered symmetrically in the fusiform gyrus with the tendency for a stronger right hemispherical source. The dipole locations and orientations were projected onto the individual MR images in Brain Voyager™. The dipole coordinates of the two subjects for whom no individual MRI could be taken were projected onto a standard MRI (average of 27 T1-weighted images of the same individual; source: www.bic.mni.mcgill.ca/cgi/ icbm_view). The anatomic substrate corresponding to the dipole coordinates was determined with the help of a brain atlas (Duvernoy, 1999). Determination of the mean dipole localization and comparison between N170 and M170 localizations The x-, y- and z-values of the dipole coordinates were averaged across subjects and the mean coordinates projected onto a standard MRI. Wilcoxon-signed rank tests were used for all statistical comparisons. Two-tailed significance level for all tests was α < .05. Results MEG and EEG were recorded from 11 subjects in Session 1 and from 10 subjects in Session 2. The error rate for the age decisions was relatively high (mean value = 21%, S.D. = 12%), indicating that the task was difficult. Indeed, this was reported by the majority of participants after the experiment. There was no change of the error rate across the face repetitions [ANOVA main effect for repetitions with short lag: F(3,30) = 0.71, p = .45; long lag: F(3,30) = 1.27, p = .30].
1498
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
Latencies and amplitudes of N170 and M170 and single-subject dipole locations in Session 1 The latencies and amplitudes of the N170 parameters were calculated for PO9 and PO10. The M170 parameters were obtained from the channel with the highest amplitude in each hemisphere. All mean amplitude and latency values are given in Table 1. For group mean time curves of MEG, EEG data and EOG data see Fig. 2. Neither latencies nor amplitudes showed significant hemispherical differences (see Table 1). There was also no difference between EEG and MEG peak latencies for the right [Z = −0.96, p = .34] or left [Z = − 1.43, p = .15] hemisphere. For six of the eleven individuals, the ECDs corresponding to N170 and M170 were co-localized in the fusiform gyri or on the border between fusiform gyri and adjacent structures. The dipoles were mostly localized in the middle and posterior parts (around y = − 55 mm to − 77 mm). In four other individuals, only the N170 dipole was localized in fusiform gyri (y = −64 mm to − 77 mm), while the M170 sources were localized in other structures of the occipital or temporal cortex such as the inferior occipital gyri. In one participant, only the M170 was localized to the FG, whereas the N170 source was located in the inferior lingual gyri. Fig. 3 displays an example of a N/M170 co-localization in fusiform gyri for one participant. Overall, there was a high consistency of N170 dipole localizations across the individuals, while the M170 showed more variability. In ten of eleven subjects the N170 dipoles were localized in the fusiform gyri, whereas the M170 dipoles were localized in the fusiform gyri in seven participants. Group mean localization results for N170 and M170 The group mean sources of the N170 and the M170 were located in the fusiform gyri. Post-hoc computed values of Goodness of Fit (GOF, mean of 93% for N170 and 84% for M170) indicated a good explanation of the data variance by the two-source dipole model. Table 2 (upper part) summarizes the localization results. It should be noted that the intraindividual comparison between the localization results of N170 and M170 revealed no significant differences. Comparison of N170 and M170 localization results between Sessions 1 and 2 data The dipolar sources of the Session 2 M170 in one individual were grossly mislocalized outside the cerebral cortex, and Table 1 Latencies and amplitudes of N170 and M170 and results of statistical tests for hemispherical differences Left hemisphere, mean (S.D.)
Latencies N170 M170 Amplitudes N170 M170 Note. p < .05.
158 (11) ms 158 (15) ms − 5.0 (3.7) μv − 160.4 (39.6) fT
Right hemisphere, mean (S.D.)
159 (16) ms 158 (15) ms −6.5 (3.3) μv − 160.3 (76.1) fT
Wilcoxon's test for hemispherical difference Z
p
− 0.43 − 0.62
.72 .53
− 1.5 0.00
.14 .99
consequently rejected as non-physiological outliers. Across sessions no significant intraindividual differences were observed for EEG and MEG localizations. N170 and M170 sources were again localized in the fusiform gyrus. All numerical results are given in Table 2. Effect of Independent Component Analysis (ICA) on the localization results To estimate the effect of the ICA on EEG and MEG source localization, we localized N170 and M170 dipoles for Session 1 without any prior ICA correction. The effect of ICA on EEG source localization consisted of significantly more inferior and posterior localization results [y-coordinate: Z = − 2.13, p = .03; z-coordinate: Z = − 1.95, p = .05; x-coordinate: Z = − 0.62, p = .58]. The dipole coordinates of the ICA-corrected EEG localizations were x = ±36 ± 5 mm, y = −57 ± 14 mm and z = − 16 ± 7 mm. The shift to a more posterior locus could be due to the additional removal of eye artefacts by ICA. These eye artefacts mainly show up as ERP deflections at frontal electrodes. For ICA-corrected MEG data, the group mean M170 coordinates were x = ± 24 ± 14 mm, y = − 64 ± 20 mm and z = − 21 ± 7 mm. The dipole projection onto the standard MRI showed an M170 location in the cerebellum, just inferior to the FG. A statistical comparison with the localization results of the ICA-corrected data displayed no significant differences [x-coordinate: Z = − 1.4, p = .18, y-coordinate: Z = −0.16, p = .90, z-coordinate: Z = − 0.78, p = .47]. Nevertheless, the shift of the mean dipole localization of the ICA results to a physiologically plausible cortical locus that can be explained by a substantial effect of the ICA correction on some of the individual subject data. Here, the localization on ICA data resulted in much more superior dipole locations. This shift can be explained by the ICA removal of cardiac activity which is strongest at the most inferior MEG sensors. The heart artefact ICA correction will be illustrated for the MEG data in the following part. Elimination of cardiac artefacts by ICA Magnetocardiographic activity (MCG) can be superimposed onto the MEG, as described by Jousmäki and Hari (1996). The MCG influence on the visually evoked fields in our experiments can be ascertained in Fig. 4A which shows one raw data channel located in the region of the M170 activation pattern. The MCG R-peak with 1 pT peak amplitude has a width at half maximum of about 20 ms. The relation between the R-peak frequency and the stimulation frequency is decisive to estimate the influence of the R-peak on an evoked field obtained by averaging. In our case the faces are presented at a rate of 0.5 Hz and the heartbeat occurs more frequently at a rate of about 1 Hz. Furthermore, the heartbeat is not synchronised with the face presentations. Therefore, the average over 1000 face presentations accumulates 20 superimposed R-peaks in each 20 ms window. The cumulative field of the R-peaks divided by the number of epochs in the average yields an estimate of 10–20 fT as the contribution of the R-peak to the M170. Fig. 4B shows the R-peak ICA map obtained by applying the time-delayed decorrelation ICA algorithm (SOBI/TDSEP) (Belouchrani et al., 1997; Ziehe and Müller, 1998) to MEG data as described by Sander et al. (2002). In eight out of eleven subjects similar R-peak maps were obtained. Almost all basal channels of the MEG sensor are activated by the R-peak. Therefore the global field power of the
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
1499
Fig. 3. N170 and M170 localization results for one individual where both N170 and M170 were localized in the fusiform gyrus. In the first row, N170 (EEG) potential distributions and M170 (MEG) field patterns at the point of maximal global field power of N170/M170 peaks are shown in two-dimensional head views. In EEG, dotted areas and in MEG solid lines indicate positivity. Contour step is 1 μV for EEG and 20 fT for MEG. R is right, L is left. EEG electrode positions are represented as points; MEG sensors are represented as crosses. On the right of each head view, the corresponding time curves of global field power (GFP, grey) and goodness of fit (GOF, black) are shown. The lower part of the figure displays the dipole locations of N170 and M170 as black and white circles in the individual MR image in coronal (COR) view on the left and transversal (TRA) view on the right side. The attached lines show the direction of the dipolar current flow. The y- and z-values indicate the Talairach slice coordinates.
R-peak residual is not negligible and its removal improves the M170 localization. Similar arguments can be put forward for the EEG data with respect to the eye blink artefact.
results was examined. In addition, the re-test-reliability of the localizations was tested in a repeated measurement design. The ECDs corresponding to N170 and M170 were localized in the middle to posterior fusiform gyri for a high proportion of single subjects (N170: ten out of eleven, M170: seven out of eleven). The group mean dipoles were also localized to the FG, this source being found for EEG and MEG in both measurement sessions. Several fMRI studies (e.g. Kanwisher et al., 1997; Horovitz et al., 2004) as well as intracranial recordings (McCarthy et al., 1999) have isolated a part of the fusiform gyri as a face-specific processing area. The proximity of the N170 and M170 localiza-
Discussion The aim of the present study was to compare on a single subject and on a group level the neuronal sources of face processing in the 170-ms latency range as measured by EEG and MEG in a simultaneous recording. Furthermore, the impact of artefact reduction by Independent Component Analysis on the localization
Table 2 Results of the N170 and M170 dipole localizations for Sessions 1 and 2: GOF values, Talairach dipole coordinates, parameters of Wilcoxon's test, and absolute differences between the dipole locations GOF, mean (S.D.) Session 1 N170 M170 Session 2 N170 M170
Dipole location, mean (S.D.)
Statistical comparison of dipole locations, Wilcoxon Z (p)
x
y
z
93 (6) 85 (4)
±35 (7), ±29 (11)
− 65 (11) − 62 (16)
− 11 (6) − 15 (11)
95 (4) 85 (7)
±35 (5) ±29 (12)
− 58 (15) − 64 (14)
− 5 (10) − 19 (15)
x Session 1 N/M170 − 1.15 (.28) Session 2 N/M170 − 1.72 (.10) Session 1/2 N170 − 0.7 (.55) Session 1/2 M170 − 0.65 (.57)
Absolute distance between dipoles, mean (S.D.)
y
z
− 0.88 (.41)
− 0.89 (.36)
20 (9)
− 1.13 (.30)
− 1.95 (.06)
29 (13)
− 1.13 (.30)
− 1.6 (.13)
21 (7)
− 0.65 (.57)
− 0.42 (.73)
19 (7)
Notes. GOF values are given in %. Dipole locations are given in x-, y-, and z-Talairach coordinates in mm. p < .05. Absolute distances between dipole locations are displayed in mm.
1500
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
despite the high signal to noise ratio of the data. The mislocalizations may have occurred due to the relatively small number of electrodes – this applies to EEG – and also to the activity of sources not directly related to face processing. Such sources can be removed by subtracting non-face stimuli (Rossion et al., 2003 for EEG). In the absence of non-face stimuli, the application of the symmetry constraint can have a comparable effect. It stabilizes the dipole fit with respect to noise and task-unrelated sources (Scherg and Berg, 1991) by reducing the number of parameters to be modelled from 6 to 3 per dipole pair. Our high rate of colocalizations of N170 and M170 can be taken as evidence for the plausibility of the chosen dipole model. Fig. 4. (A) Single raw data channel showing signal peaks due to the heartbeat. The channel is from the location indicated by X in panel B. (B) Two-dimensional map representation of the cardiac artifact pattern identified by ICA. The map is a view onto the head from above with front and back indicated. The map corresponds to the field distribution of the peaks (R-peak of the cardiac QRS complex) visible in the single channel data in panel A. The R-peak is strongest in the channels closest to the heart muscle. These channels are at the periphery of the two-dimensional map.
tions to this area underlines the physiological plausibility of our results. Relation of the present results to other N170 and M170 localization studies Our M170 localization results are in accordance with other MEG studies that also localized the M170 in the posterior fusiform gyrus (e.g. Watanabe et al., 1999; Halgren et al., 2000; Hoshiyama et al., 2003). The FG source was found consistently across studies, although they differed in their localization approaches. For example, Halgren et al. (2000) localized on difference curves between faces and other stimuli, whereas we localized on data acquired to face presentations alone. In contrast to M170, our N170 localization results correspond with only one other study (Rossion et al., 2003). This study used a similar localization procedure. Rossion et al. (2003) also modelled the N170 by a pair of dipoles with a symmetry constraint. Interestingly, they found a fusiform gyrus (FG) localization not only for faces, but also for the difference curve between faces and cars. However, our results are in disagreement with a number of studies finding several other N170 sources (Schweinberger et al., 2002; Watanabe et al., 2003; Itier and Taylor, 2004; cf. Introduction). One reason for the disparity can lie in the kind of stimuli used. Schweinberger et al. (2002) also modelled the N170 by a symmetric dipole pair. Employing famous faces as stimuli, they found an N170 source in the lateral occipitotemporal cortex. Their famous faces may have evoked different processing at the 170-ms stage than our initially unfamiliar face stimuli. Other obvious reasons for disparity can be the number of dipoles and the localization constraints introduced, as well as the number of recording sites. Having recorded a 128-electrode EEG, Mnatsakanian and Tarkka (2004) chose a dipole model without symmetry constraints and found four dipoles mainly accounting for the activity around 170 ms. Two dipoles were localized in the right and left FG, and two dipoles in the lingual gyri. They found nearly symmetric locations for both dipole pairs, although they did not use a symmetry constraint. We would not have found plausible (cortical) source localizations for a number of individuals without the use of a symmetry constraint (see Material and methods). This problem occurred
Reasons for a predominant activation of the fusiform gyrus in the current study We hypothesize that one reason for co-localization of the N170 and M170 to the fusiform gyrus was that the age classification task strongly activated this area. The small age difference between the face stimulus classes – children 8 to 9 versus young adults 20 to 30 – made the task difficult. A part-based evaluation, e.g. the processing of different skin texture or wrinkles as would have been possible for faces of older adults, could not be used here. Instead, we assume that the performance was primarily based on the evaluation of configurational differences. Different lines of evidence indicate that the fusiform gyrus is indeed involved in the analysis of facial configuration. Intracranial recordings (McCarthy et al., 1999) revealed that recording sites in the fusiform gyrus responded more to full faces whereas sites in the lateral occipitotemporal cortex responded more to face parts. Involvement of the fusiform gyrus in configural processing is also indicated by a significant reduction of the M170 amplitude to faces with the basic configuration distorted (eyes, mouth and nose scrambled; Halgren et al., 2000). Based on a series of experiments with EEG scalp recordings, Bentin et al. (1996) and Sagiv and Bentin (2001) proposed a 2source model of the N170 in which the source in lateral occipitotemporal cortex is responsible for the analysis of face components, whereas the fusiform source analyzes the canonic configuration (the “Gestalt”) of a face. The authors (Sagiv and Bentin, 2001) further suggested that the two processes are not hierarchically connected, but that depending on task requirements one or the other is predominantly active. Consequently, if a certain task requires the analysis of the overall facial configuration the fusiform gyrus would be the dominant source, whereas the activity of lateral parts of occipitotemporal cortex would dominate the activity in part-based processing tasks. Recent fMRI work (e.g. Rotshtein et al., 2005) corroborates the proposal that the fusiform gyrus is primarily involved in configural face processing and face identification. In accordance with this argument we suggest that the nature (configural processing) and difficulty of the present task led to a main activation of the source in fusiform gyrus, which then dominated both N170 and M170. Conclusion In the current study sources of N and M170 were co-localized in the fusiform gyrus. This result was not only obtained for mean source locations, but more importantly in a considerable number of single subjects. Moreover, the result was replicated within the same group. Possible explanations for the high quality of the co-
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
localization are a high number of trials, sufficient artefact reduction by the use of ICA and a predominant activation of the fusiform gyrus by the task used. The necessity of applying a symmetry constraint might limit physiological conclusions to be drawn. On the other hand the good correspondence of the present localization results with other studies justifies its application. A future study has to probe whether contrasting different face tasks in combination with a refined localization approach can disentangle multiple sources and their interplay in early face processing. Acknowledgments We thank Walter Endl, Vienna, for the face photographs. We also thank C. Carbon, T. Bengner, B. Pelzer, and both anonymous reviewers for their detailed comments on earlier versions of the manuscript. This work is supported by DFG grant number GRK 432/2 and BMBF grant number 01GO0208 BNIC. References Allison, T., Puce, A., Spencer, D., McCarthy, G., 1999. Electrophysiological studies of human face perception: I. Potentials generated in occipitotemporal cortex by face and non-face stimuli. Cereb. Cortex 9, 415–430. Belouchrani, A., Abed-Meraim, K., Cardoso, J.-F., Moulines, E., 1997. A blind source separation technique based on second-order statistics. IEEE Trans. Signal Process. 45, 434–444. Bentin, S., Deouell, L., 2000. Structural encoding and identification in face processing: ERP evidence for separate mechanisms. Cogn. Neuropsychol. 17, 35–54. Bentin, S., Allison, T., Puce, A., Perez, E., McCarthy, G., 1996. Electrophysiological studies of face perception in humans. J. Cogn. Neurosci. 8, 551–565. Berg, P., Scherg, M., 1994. A fast method for forward computation of multiple-shell spherical head models. Electroencephalogr. Clin. Neurophysiol. 90, 58–64. Botzel, K., Grusser, OJ., 1989. Electric brain potentials evoked by pictures of faces and non-faces: a search for “face-specific” EEG-potentials. Exp. Brain Res. 77, 349–360. Carbon, CC., Schweinberger, SR., Kaufmann, J., Leder, H., 2005. Early face processing in normal and Thatcher faces: an event-related brain potentials study. Cogn. Brain Res. 24, 544–555. Duvernoy, H., 1999. The Human Brain. Surface, Blood Supply, and ThreeDimensional Sectional Anatomy, 2nd ed. Springer Verlag, Wien. Halgren, E., Raij, T., Marinkovic, K., Jousmäki, V., Hari, R., 2000. Cognitive response profile of the human fusiform face area as determined by MEG. Cereb. Cortex 10, 69–81. Horovitz, S., Rossion, B., Skudlarski, P., Gore, J., 2004. Parametric design and correlational analyses help integrating fMRI and electrophysiological data during face processing. NeuroImage 22, 1587–1595. Hoshiyama, M., Kakigi, R., Watanabe, S., Miki, K., Takeshima, Y., 2003. Brain responses for the subconscious recognition of faces. Neurosci. Res. 46, 435–442. Itier, R., Taylor, M., 2004. Source analysis of the N170 to faces and objects. NeuroReport 15, 1261–1265. Jeffreys, DA., 1989. A face-responsive potential recorded from the human scalp. Exp. Brain Res. 78, 193–202. Jeffreys, DA., Tukmachi, ES., 1992. The vertex-positive scalp potential evoked by faces and objects. Exp. Brain Res. 91, 340–350.
1501
Jousmäki, V., Hari, R., 1996. Cardiac artifacts in magnetoencephalogram. J. Clin. Neurophysiol. 13, 172–176. Joyce, C., Rossion, B., 2005. The face-sensitive N170 and VPP components manifest the same brain processes: the effect of reference electrode site. Clin. Neurophysiol. 116, 2613–2631. Kanwisher, N., McDermott, J., Chun, M., 1997. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302–4311. Lewis, S., Thoma, R., Lanoue, M., Miller, G., Heller, W., Edgar, C., Huang, M., Weisend, M., Irwin, J., Paulson, K., Canive, J., 2003. Visual processing of facial affect. NeuroReport 14, 1841–1845. Linkenkaer-Hansen, K., Palva, J., Sams, M., Hietanen, J., Ilmoniemi, R., 1998. Face-selective processing in human extrastriate cortex around 120 ms after stimulus onset revealed by magnetoencephalography. Neurosci. Lett. 253, 147–150. Liu, J., Harris, A., Kanwisher, N., 2002. Stages of processing in face perception: an MEG study. Nat. Neurosci. 5, 910–916. Lu, S., Hamalainen, M., Hari, R., Ilmoniemi, R., Lounasmaa, O., Sams, N., Vilkman, V., 1991. Seeing faces activates three separate areas outside the occipital visual cortex in man. Neuroscience 43, 287–290. McCarthy, G., Puce, A., Belger, A., Allison, T., 1999. Electrophysiological studies of human face perception: II. Response properties of face-specific potentials generated in occipitotemporal cortex. Cereb. Cortex 9, 431–444. Mnatsakanian, E., Tarkka, I., 2004. Familiar-face recognition and comparison: source analysis of scalp-recorded event-related potentials. Clin. Neurophysiol. 115, 880–886. Rossion, B., Joyce, C., Cottrell, G., Tarr, M., 2003. Early lateralization and orientation tuning for face, word, and object processing in the visual cortex. NeuroImage 20, 1609–1924. Rotshtein, P., Henson, R., Treves, A., Driver, J., Dolan, R., 2005. Morphing Marilyn into Maggie dissociates physical and identity face representations in the brain. Nat. Neurosci. 8, 107–113. Sagiv, N., Bentin, S., 2001. Structural encoding of human and schematic faces: holistic and part-based processes. J. Cogn. Neurosci. 13, 651–937. Sander, T.H., Wubbeler, G., Lueschow, A., Curio, G., Trahms, L., 2002. Cardiac artifact subspace identification and elimination in cognitive MEG data using time-delayed decorrelation. IEEE Trans. Biomed. Eng. 49, 345–354. Sato, N., Nakamura, K., Nakamura, A., Suguira, M., Ito, K., Fukuda, H., Kawashima, R., 1999. Different time course between scene processing and face processing. A MEG study. NeuroReport 26, 3633–3637. Scheer, HJ., Sander, T., Trahms, L., 2006. The influence of amplifier, interface and biological noise on signal quality in high-resolution EEG. Physiol. Meas. 27, 109–117. Scherg, M., Berg, P., 1991. Use of prior knowledge in brain electromagnetic source analysis. Brain Topogr. 4, 143–150. Schweinberger, S., Pickering, E., Jentzsch, I., Burton, A., Kaufmann, J., 2002. Event-related brain potential evidence for a response of inferior temporal cortex to familiar face repetitions. Cogn. Brain Res. 14, 398–409. Talairach, J., Tournaux, P., 1988. Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, New York. Watanabe, S., Kakigi, R., Koyama, S., Kirino, E., 1999. Human face perception traced by magneto- and electroencephalography. Cogn. Brain Res. 8, 125–142. Watanabe, S., Kakigi, R., Puce, A., 2003. The spatiotemporal dynamics of the face inversion effect: a magneto- and electroencephalographic study. Neuroscience 116, 879–895. Ziehe, A., Müller, K.-R., 1998. TDSEP – an efficient algorithm for blind separation using time structure. In: Niklasson, L., Bodén, M., Ziemke, T. (Eds.), Proceedings of the 8th ICANN. Springer Verlag, New York, pp. 675–680.
Technical Note
MEG/EEG sources of the 170-ms response to faces are co-localized in the fusiform gyrus Iris Deffke, a,⁎ Tilmann Sander, b Jens Heidenreich, d Werner Sommer, c Gabriel Curio, a Lutz Trahms, b and Andreas Lueschow a a
Department of Neurology, Campus Benjamin Franklin, Charité-University-Medicine-Berlin, Hindenburgdamm 30, 12200, Berlin, Germany Physikalisch–Technische Bundesanstalt, Berlin, Germany c Biological Psychology, Humboldt-University, Berlin, Germany d Department of Radiology and Nuclear Medicine, Campus Benjamin Franklin, Charité-University-Medicine-Berlin, Berlin, Germany b
Received 26 September 2005; revised 24 January 2007; accepted 25 January 2007 Available online 13 February 2007 The 170-ms electrophysiological processing stage (N170 in EEG, M170 in MEG) is considered an important computational step in face processing. Hence its neuronal sources have been modelled in several studies. The current study aimed to specify the relation of the dipolar sources underlying N170 and M170. Whole head EEG and MEG were measured simultaneously during the presentation of unfamiliar faces. An Independent Component Analysis (ICA) was applied to the data prior to localization. N170 and M170 were then modelled with a pair of dipoles in a four-shell ellipse (EEG)/ homogeneous sphere (MEG) arranged symmetrically across midline. The dipole locations were projected onto the individual structural MR brain images. Dipoles were localized in fusiform gyri in ten out of eleven individuals for EEG and in seven out of eleven for MEG. N170 and M170 were co-localized in the fusiform gyrus in six individuals. The ICA shifted some of the single-subject dipoles up from cerebellum to fusiform gyrus mainly due to the removal of cardiac activity. The group mean dipole locations were also found in posterior fusiform gyri, and did not differ significantly between EEG and MEG. The result was replicated in a repeated measurement 3 months later. © 2007 Elsevier Inc. All rights reserved. Keywords: Face processing; N170; M170; Equivalent current dipole (ECD); Source localization; Fusiform gyrus
Introduction Perceiving and recognizing faces is considered one of the most complex and demanding visual processes. Electroencephalographic (EEG) studies have reported a positive face-specific event-related potential (ERP) at the vertex around 150 ms after face presentation onset (the vertex positive potential, VPP) (Botzel and ⁎ Corresponding author. Fax: +49 030 8445 4264. E-mail address: [email protected] (I. Deffke). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2007.01.034
Grusser, 1989; Jeffreys, 1989; Jeffreys and Tukmachi, 1992). Further, a negative deflection at right and left posterior electrodes can be recorded around 170 ms after face presentations (N170, e.g. Bentin et al., 1996). The N170 has been related to the configural processing of face features and their integration into a holistic face percept (Bentin and Deouell, 2000; Schweinberger et al., 2002; Carbon et al., 2005). N170 and VPP depend on the same neural generator, a main factor contributing to apparent functional differences between both components being the choice of the reference electrode (Joyce and Rossion, 2005). Using magnetoencephalography (MEG), face-specific eventrelated magnetic fields (ERFs) have been recorded at posterior sensors around the same latency as the N170 (e.g. Lu et al., 1991; Sato et al., 1999; Watanabe et al., 1999; Halgren et al., 2000; Liu et al., 2002; Hoshiyama et al., 2003; Lewis et al., 2003). These ERFs have been related to configural face encoding and to the identification of faces (Halgren et al., 2000; Liu et al., 2002). Several studies have modelled the cortical sources underlying N170 and M170 as equivalent current dipoles (ECDs). N170 sources have been localized to the fusiform gyri (FG) (Rossion et al., 2003), or to the FG and additional structures such as the lingual gyri (Mnatsakanian and Tarkka, 2004). Other EEG studies found entirely different generators such as the lateral occipitotemporal cortex (Schweinberger et al., 2002) or the superior temporal sulci (Itier and Taylor, 2004). In contrast, the M170 source has been consistently localized in or close to the FG (Linkenkaer-Hansen et al., 1998; Sato et al., 1999; Watanabe et al., 1999; Lewis et al., 2003; Halgren et al., 2000; Hoshiyama et al., 2003). The reason for the larger heterogeneity of results in localization studies of the N170 than the M170 is unclear. Critical factors may be task and stimulus as well as recording technique. MEG has become more widely used over the last years in the study of face processing. The current study aimed at a specification of the relation between face-related N170 and M170 sources by localizing them on simultaneously recorded EEG and MEG data. The data quality was improved by removing noise with the help of
1496
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
Independent Component Analysis (ICA). To account for individual differences in functional neuroanatomy, dipoles were localized on single-subject data. The robustness of the localizations was examined by repeating the experiment after 3 months with the same participants.
where reaction time and error rate were measured. This procedure was introduced to enhance the familiarity of the face stimuli. In Session 2, we did not find any effects of prior exposure to the face stimuli on the N170 or M170, and again no priming effects for N/ M170. We thus used the data to examine the robustness of the dipole localizations.
Material and methods EEG and MEG measurement The recent study is part of a broader research project on electrophysiological correlates of face priming processes. Its design will be described here as long as it is relevant for the reported results. Subjects Eleven right-handed healthy persons (7 women; mean age = 25.9, S.D. = 3.8, range 19 to 35 years) participated in the study. All persons had normal or corrected to normal vision. The ethics committee of the Charité, Campus Benjamin Franklin, approved of the study design. All participants gave their written informed consent. Stimuli and experimental paradigm 380 black and white photographs of unfamiliar faces taken from a front perspective were shown (300 adults, 80 children; see Fig. 1 for an example of the face stimuli and their presentation sequence). None of the persons depicted wore glasses, a beard, or other additional items. The experimental task consisted of an age classification. Subjects had to decide as fast as possible whether a child (8– 9 years) or an adult (20–30 years) face was shown. In a continuous repetition priming paradigm, all faces were repeated four times. The effect of the lag between repetitions was studied by repeating one half of the faces after 3 intervening faces (6 s) and the other half after 90 intervening faces (3 min). During the interstimulus interval (ISI), a fixation cross was shown. The length of the ISI varied between 500 and 1100 ms (mean 800 ms). Face repetition had no effect on the N170 and M170 amplitudes [all ANOVA main effects of repetition: F < 0.9, p > .44; see Fig. 2 for the short lag repetitions]. Taking advantage of the absence of priming effects, trials were averaged across all four repetitions. After eliminating ∼ 20% of EOG-artefact contaminated trials, app. 1000 trials per subject could be used for averaging. To test the impact of familiarity on priming effects the identical experiment was repeated 3 months later (Session 2) in ten of the eleven participants. On 2 consecutive days before Session 2, they performed different behavioural face tasks (e.g. a one-back task)
Fig. 1. Example of successive face presentations in the experiment.
EEG and MEG were measured simultaneously in an electrically and magnetically shielded room. EEG was recorded from 27 electrodes attached to a cap (positions: O1, O2, PO9, PO10, T5, T6, T1, T2, T3, T4, Pz, P3, P4, CP5, CP6, Cz, C3, C4, Fz, Fc1, Fc2, Fc5, Fc6, F3, F4, F7, F8) using a reference electrode on the nose. The magnetic fields were recorded with a 93-channel wholehead MEG system (Eagle Technology™, ET160). Axial gradiometers with a baseline of 5 cm were employed. Vertical and horizontal electrooculograms (EOG) were recorded. EEG and EOG electrode impedances below 50 kΩ were found to be sufficient. This was due to the high input impedance of 20 mΩ of the EEG amplifier used and its low noise of 6.5 nV Hz− 1/2 (Scheer et al., 2006). EEG and MEG were digitized with a sampling rate of 500 Hz and a bandpass filter of 0.1–200 Hz. Offline, the data were downsampled to 250 Hz and bandpass-filtered between 0.5 and 40 Hz. To remove eye artefacts (EOG) in the data and artefacts caused by the magnetic field of the heart, the MEG data were submitted to an Independent Component Analysis (ICA) before averaging (Sander et al., 2002). Likewise, an ICA was computed on the EEG data, which served mainly to remove EOG. In addition to the ICA correction EOG-artefact contaminated epochs were excluded in the conventional fashion. ERPs and ERFs were calculated over 1200 ms with a pre-stimulus baseline of 200 ms. We report results with and without ICA correction to compare the effects of ICA on the localization results. Acquisition of structural magnetic resonance brain images (MRI) and co-registration of EEG/MEG sensor positions In 9 participants, we acquired a coronally orientated highresolution T1-weighted multiplanar three-dimensional reconstruction of MR (MPR) (TR 15 ms, TE 7 ms, flip angle 8°, 148 partitions, slab thickness 220 mm, 1.49 × 0.98 × 0.98 mm nominal pixel resolution). A 1.5 T MRI scanner (Magnetom Vision™, Siemens, Erlangen) was used. In Brain Voyager 2000™, voxel size was spatially resampled to 1.0 × 1.0 × 1.0 mm. The resulting images were standardized to Talairach space (Talairach and Tournaux, 1988). The head position in the MEG system was measured with the help of five magnetic marker coils. One coil was attached close to the nasion (∼1 cm distance), two on the left and right forehead, and the two remaining coils close to the left and right preauricular points (∼ 1 cm away). The possibility of detecting head tilts in all directions was ensured by the large spatial separation between the coils at the preauricular points and the ones at the front of the head. After EEG/MEG acquisition, the positions of the EEG electrodes, MEG markers, and the standard anatomical landmarks (fiducials) were measured in three-dimensional space. This was done with the help of an ultrasonic system (Zebris 3D Measurement of Movement CSM20S). The head coordinate system was defined by the fiducials nasion and left and right preauricular
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
1497
Fig. 2. Grand-averaged ERPs, ERFs and EOGs recorded to the face repetitions with short lag. ERP grand averages comprise single-subject responses at electrodes PO9 and PO10. ERF grand averages were based upon spatial averages of single-subject responses. Spatial averages represent the mean of the channel with the largest M170 amplitude and neighbouring channels showing at least 70% of the highest response. Note the absence of priming effects on the N170 and M170.
points. The magnetic marker positions were used to make the coordinate transformation of the MEG sensors into the head coordinate system. The EEG electrode positions were given directly in the head coordinate system. Dipole localization for single subjects The dipole localizations were calculated with the program Brain Electrical Source Analysis (BESA 2000™, MEGIS Software, Gräfelfing, Germany). N170/M170 were defined as event-related potential/field with maximal strength at posterior channel locations between 120 and 200 ms after face onset. The dipole fit time intervals covered the peak of the N170/M170 and a time interval around the peak comprising data points from 100% to approx. 70% of the peak amplitude. We used a four-shell (brain, cerebrospinal fluid, bone, scalp) ellipsoidal head model for EEG (Berg and Scherg, 1994) and a single-layer spherical head model for MEG modelling. N170 and M170 were each modelled by two single dipoles. A symmetry constraint was introduced. The two dipoles had to lie symmetrically in the right and left hemisphere. This was due to the observation that without the use of a symmetry constraint, we had neither obtained physiologically plausible EEG nor MEG localization results for a considerable number of subjects. For example, the sources were located in the middle between both hemispheres, with one source in the frontal and one in the occipital cortex. In other cases sources were located outside of the cortex. Despite being a strong a priori constraint the assumption of symmetric sources underlying N170 and M170 has physiological plausibility. fMRI studies (e.g. Kanwisher et al., 1997; Horovitz et al., 2004) found symmetric face-related activations in the occipitotemporal cortex.
In intracranial recordings (Allison et al., 1999), N200 locations (the N200 being a likely analogue of the surface-recorded N/M170) clustered symmetrically in the fusiform gyrus with the tendency for a stronger right hemispherical source. The dipole locations and orientations were projected onto the individual MR images in Brain Voyager™. The dipole coordinates of the two subjects for whom no individual MRI could be taken were projected onto a standard MRI (average of 27 T1-weighted images of the same individual; source: www.bic.mni.mcgill.ca/cgi/ icbm_view). The anatomic substrate corresponding to the dipole coordinates was determined with the help of a brain atlas (Duvernoy, 1999). Determination of the mean dipole localization and comparison between N170 and M170 localizations The x-, y- and z-values of the dipole coordinates were averaged across subjects and the mean coordinates projected onto a standard MRI. Wilcoxon-signed rank tests were used for all statistical comparisons. Two-tailed significance level for all tests was α < .05. Results MEG and EEG were recorded from 11 subjects in Session 1 and from 10 subjects in Session 2. The error rate for the age decisions was relatively high (mean value = 21%, S.D. = 12%), indicating that the task was difficult. Indeed, this was reported by the majority of participants after the experiment. There was no change of the error rate across the face repetitions [ANOVA main effect for repetitions with short lag: F(3,30) = 0.71, p = .45; long lag: F(3,30) = 1.27, p = .30].
1498
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
Latencies and amplitudes of N170 and M170 and single-subject dipole locations in Session 1 The latencies and amplitudes of the N170 parameters were calculated for PO9 and PO10. The M170 parameters were obtained from the channel with the highest amplitude in each hemisphere. All mean amplitude and latency values are given in Table 1. For group mean time curves of MEG, EEG data and EOG data see Fig. 2. Neither latencies nor amplitudes showed significant hemispherical differences (see Table 1). There was also no difference between EEG and MEG peak latencies for the right [Z = −0.96, p = .34] or left [Z = − 1.43, p = .15] hemisphere. For six of the eleven individuals, the ECDs corresponding to N170 and M170 were co-localized in the fusiform gyri or on the border between fusiform gyri and adjacent structures. The dipoles were mostly localized in the middle and posterior parts (around y = − 55 mm to − 77 mm). In four other individuals, only the N170 dipole was localized in fusiform gyri (y = −64 mm to − 77 mm), while the M170 sources were localized in other structures of the occipital or temporal cortex such as the inferior occipital gyri. In one participant, only the M170 was localized to the FG, whereas the N170 source was located in the inferior lingual gyri. Fig. 3 displays an example of a N/M170 co-localization in fusiform gyri for one participant. Overall, there was a high consistency of N170 dipole localizations across the individuals, while the M170 showed more variability. In ten of eleven subjects the N170 dipoles were localized in the fusiform gyri, whereas the M170 dipoles were localized in the fusiform gyri in seven participants. Group mean localization results for N170 and M170 The group mean sources of the N170 and the M170 were located in the fusiform gyri. Post-hoc computed values of Goodness of Fit (GOF, mean of 93% for N170 and 84% for M170) indicated a good explanation of the data variance by the two-source dipole model. Table 2 (upper part) summarizes the localization results. It should be noted that the intraindividual comparison between the localization results of N170 and M170 revealed no significant differences. Comparison of N170 and M170 localization results between Sessions 1 and 2 data The dipolar sources of the Session 2 M170 in one individual were grossly mislocalized outside the cerebral cortex, and Table 1 Latencies and amplitudes of N170 and M170 and results of statistical tests for hemispherical differences Left hemisphere, mean (S.D.)
Latencies N170 M170 Amplitudes N170 M170 Note. p < .05.
158 (11) ms 158 (15) ms − 5.0 (3.7) μv − 160.4 (39.6) fT
Right hemisphere, mean (S.D.)
159 (16) ms 158 (15) ms −6.5 (3.3) μv − 160.3 (76.1) fT
Wilcoxon's test for hemispherical difference Z
p
− 0.43 − 0.62
.72 .53
− 1.5 0.00
.14 .99
consequently rejected as non-physiological outliers. Across sessions no significant intraindividual differences were observed for EEG and MEG localizations. N170 and M170 sources were again localized in the fusiform gyrus. All numerical results are given in Table 2. Effect of Independent Component Analysis (ICA) on the localization results To estimate the effect of the ICA on EEG and MEG source localization, we localized N170 and M170 dipoles for Session 1 without any prior ICA correction. The effect of ICA on EEG source localization consisted of significantly more inferior and posterior localization results [y-coordinate: Z = − 2.13, p = .03; z-coordinate: Z = − 1.95, p = .05; x-coordinate: Z = − 0.62, p = .58]. The dipole coordinates of the ICA-corrected EEG localizations were x = ±36 ± 5 mm, y = −57 ± 14 mm and z = − 16 ± 7 mm. The shift to a more posterior locus could be due to the additional removal of eye artefacts by ICA. These eye artefacts mainly show up as ERP deflections at frontal electrodes. For ICA-corrected MEG data, the group mean M170 coordinates were x = ± 24 ± 14 mm, y = − 64 ± 20 mm and z = − 21 ± 7 mm. The dipole projection onto the standard MRI showed an M170 location in the cerebellum, just inferior to the FG. A statistical comparison with the localization results of the ICA-corrected data displayed no significant differences [x-coordinate: Z = − 1.4, p = .18, y-coordinate: Z = −0.16, p = .90, z-coordinate: Z = − 0.78, p = .47]. Nevertheless, the shift of the mean dipole localization of the ICA results to a physiologically plausible cortical locus that can be explained by a substantial effect of the ICA correction on some of the individual subject data. Here, the localization on ICA data resulted in much more superior dipole locations. This shift can be explained by the ICA removal of cardiac activity which is strongest at the most inferior MEG sensors. The heart artefact ICA correction will be illustrated for the MEG data in the following part. Elimination of cardiac artefacts by ICA Magnetocardiographic activity (MCG) can be superimposed onto the MEG, as described by Jousmäki and Hari (1996). The MCG influence on the visually evoked fields in our experiments can be ascertained in Fig. 4A which shows one raw data channel located in the region of the M170 activation pattern. The MCG R-peak with 1 pT peak amplitude has a width at half maximum of about 20 ms. The relation between the R-peak frequency and the stimulation frequency is decisive to estimate the influence of the R-peak on an evoked field obtained by averaging. In our case the faces are presented at a rate of 0.5 Hz and the heartbeat occurs more frequently at a rate of about 1 Hz. Furthermore, the heartbeat is not synchronised with the face presentations. Therefore, the average over 1000 face presentations accumulates 20 superimposed R-peaks in each 20 ms window. The cumulative field of the R-peaks divided by the number of epochs in the average yields an estimate of 10–20 fT as the contribution of the R-peak to the M170. Fig. 4B shows the R-peak ICA map obtained by applying the time-delayed decorrelation ICA algorithm (SOBI/TDSEP) (Belouchrani et al., 1997; Ziehe and Müller, 1998) to MEG data as described by Sander et al. (2002). In eight out of eleven subjects similar R-peak maps were obtained. Almost all basal channels of the MEG sensor are activated by the R-peak. Therefore the global field power of the
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
1499
Fig. 3. N170 and M170 localization results for one individual where both N170 and M170 were localized in the fusiform gyrus. In the first row, N170 (EEG) potential distributions and M170 (MEG) field patterns at the point of maximal global field power of N170/M170 peaks are shown in two-dimensional head views. In EEG, dotted areas and in MEG solid lines indicate positivity. Contour step is 1 μV for EEG and 20 fT for MEG. R is right, L is left. EEG electrode positions are represented as points; MEG sensors are represented as crosses. On the right of each head view, the corresponding time curves of global field power (GFP, grey) and goodness of fit (GOF, black) are shown. The lower part of the figure displays the dipole locations of N170 and M170 as black and white circles in the individual MR image in coronal (COR) view on the left and transversal (TRA) view on the right side. The attached lines show the direction of the dipolar current flow. The y- and z-values indicate the Talairach slice coordinates.
R-peak residual is not negligible and its removal improves the M170 localization. Similar arguments can be put forward for the EEG data with respect to the eye blink artefact.
results was examined. In addition, the re-test-reliability of the localizations was tested in a repeated measurement design. The ECDs corresponding to N170 and M170 were localized in the middle to posterior fusiform gyri for a high proportion of single subjects (N170: ten out of eleven, M170: seven out of eleven). The group mean dipoles were also localized to the FG, this source being found for EEG and MEG in both measurement sessions. Several fMRI studies (e.g. Kanwisher et al., 1997; Horovitz et al., 2004) as well as intracranial recordings (McCarthy et al., 1999) have isolated a part of the fusiform gyri as a face-specific processing area. The proximity of the N170 and M170 localiza-
Discussion The aim of the present study was to compare on a single subject and on a group level the neuronal sources of face processing in the 170-ms latency range as measured by EEG and MEG in a simultaneous recording. Furthermore, the impact of artefact reduction by Independent Component Analysis on the localization
Table 2 Results of the N170 and M170 dipole localizations for Sessions 1 and 2: GOF values, Talairach dipole coordinates, parameters of Wilcoxon's test, and absolute differences between the dipole locations GOF, mean (S.D.) Session 1 N170 M170 Session 2 N170 M170
Dipole location, mean (S.D.)
Statistical comparison of dipole locations, Wilcoxon Z (p)
x
y
z
93 (6) 85 (4)
±35 (7), ±29 (11)
− 65 (11) − 62 (16)
− 11 (6) − 15 (11)
95 (4) 85 (7)
±35 (5) ±29 (12)
− 58 (15) − 64 (14)
− 5 (10) − 19 (15)
x Session 1 N/M170 − 1.15 (.28) Session 2 N/M170 − 1.72 (.10) Session 1/2 N170 − 0.7 (.55) Session 1/2 M170 − 0.65 (.57)
Absolute distance between dipoles, mean (S.D.)
y
z
− 0.88 (.41)
− 0.89 (.36)
20 (9)
− 1.13 (.30)
− 1.95 (.06)
29 (13)
− 1.13 (.30)
− 1.6 (.13)
21 (7)
− 0.65 (.57)
− 0.42 (.73)
19 (7)
Notes. GOF values are given in %. Dipole locations are given in x-, y-, and z-Talairach coordinates in mm. p < .05. Absolute distances between dipole locations are displayed in mm.
1500
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
despite the high signal to noise ratio of the data. The mislocalizations may have occurred due to the relatively small number of electrodes – this applies to EEG – and also to the activity of sources not directly related to face processing. Such sources can be removed by subtracting non-face stimuli (Rossion et al., 2003 for EEG). In the absence of non-face stimuli, the application of the symmetry constraint can have a comparable effect. It stabilizes the dipole fit with respect to noise and task-unrelated sources (Scherg and Berg, 1991) by reducing the number of parameters to be modelled from 6 to 3 per dipole pair. Our high rate of colocalizations of N170 and M170 can be taken as evidence for the plausibility of the chosen dipole model. Fig. 4. (A) Single raw data channel showing signal peaks due to the heartbeat. The channel is from the location indicated by X in panel B. (B) Two-dimensional map representation of the cardiac artifact pattern identified by ICA. The map is a view onto the head from above with front and back indicated. The map corresponds to the field distribution of the peaks (R-peak of the cardiac QRS complex) visible in the single channel data in panel A. The R-peak is strongest in the channels closest to the heart muscle. These channels are at the periphery of the two-dimensional map.
tions to this area underlines the physiological plausibility of our results. Relation of the present results to other N170 and M170 localization studies Our M170 localization results are in accordance with other MEG studies that also localized the M170 in the posterior fusiform gyrus (e.g. Watanabe et al., 1999; Halgren et al., 2000; Hoshiyama et al., 2003). The FG source was found consistently across studies, although they differed in their localization approaches. For example, Halgren et al. (2000) localized on difference curves between faces and other stimuli, whereas we localized on data acquired to face presentations alone. In contrast to M170, our N170 localization results correspond with only one other study (Rossion et al., 2003). This study used a similar localization procedure. Rossion et al. (2003) also modelled the N170 by a pair of dipoles with a symmetry constraint. Interestingly, they found a fusiform gyrus (FG) localization not only for faces, but also for the difference curve between faces and cars. However, our results are in disagreement with a number of studies finding several other N170 sources (Schweinberger et al., 2002; Watanabe et al., 2003; Itier and Taylor, 2004; cf. Introduction). One reason for the disparity can lie in the kind of stimuli used. Schweinberger et al. (2002) also modelled the N170 by a symmetric dipole pair. Employing famous faces as stimuli, they found an N170 source in the lateral occipitotemporal cortex. Their famous faces may have evoked different processing at the 170-ms stage than our initially unfamiliar face stimuli. Other obvious reasons for disparity can be the number of dipoles and the localization constraints introduced, as well as the number of recording sites. Having recorded a 128-electrode EEG, Mnatsakanian and Tarkka (2004) chose a dipole model without symmetry constraints and found four dipoles mainly accounting for the activity around 170 ms. Two dipoles were localized in the right and left FG, and two dipoles in the lingual gyri. They found nearly symmetric locations for both dipole pairs, although they did not use a symmetry constraint. We would not have found plausible (cortical) source localizations for a number of individuals without the use of a symmetry constraint (see Material and methods). This problem occurred
Reasons for a predominant activation of the fusiform gyrus in the current study We hypothesize that one reason for co-localization of the N170 and M170 to the fusiform gyrus was that the age classification task strongly activated this area. The small age difference between the face stimulus classes – children 8 to 9 versus young adults 20 to 30 – made the task difficult. A part-based evaluation, e.g. the processing of different skin texture or wrinkles as would have been possible for faces of older adults, could not be used here. Instead, we assume that the performance was primarily based on the evaluation of configurational differences. Different lines of evidence indicate that the fusiform gyrus is indeed involved in the analysis of facial configuration. Intracranial recordings (McCarthy et al., 1999) revealed that recording sites in the fusiform gyrus responded more to full faces whereas sites in the lateral occipitotemporal cortex responded more to face parts. Involvement of the fusiform gyrus in configural processing is also indicated by a significant reduction of the M170 amplitude to faces with the basic configuration distorted (eyes, mouth and nose scrambled; Halgren et al., 2000). Based on a series of experiments with EEG scalp recordings, Bentin et al. (1996) and Sagiv and Bentin (2001) proposed a 2source model of the N170 in which the source in lateral occipitotemporal cortex is responsible for the analysis of face components, whereas the fusiform source analyzes the canonic configuration (the “Gestalt”) of a face. The authors (Sagiv and Bentin, 2001) further suggested that the two processes are not hierarchically connected, but that depending on task requirements one or the other is predominantly active. Consequently, if a certain task requires the analysis of the overall facial configuration the fusiform gyrus would be the dominant source, whereas the activity of lateral parts of occipitotemporal cortex would dominate the activity in part-based processing tasks. Recent fMRI work (e.g. Rotshtein et al., 2005) corroborates the proposal that the fusiform gyrus is primarily involved in configural face processing and face identification. In accordance with this argument we suggest that the nature (configural processing) and difficulty of the present task led to a main activation of the source in fusiform gyrus, which then dominated both N170 and M170. Conclusion In the current study sources of N and M170 were co-localized in the fusiform gyrus. This result was not only obtained for mean source locations, but more importantly in a considerable number of single subjects. Moreover, the result was replicated within the same group. Possible explanations for the high quality of the co-
I. Deffke et al. / NeuroImage 35 (2007) 1495–1501
localization are a high number of trials, sufficient artefact reduction by the use of ICA and a predominant activation of the fusiform gyrus by the task used. The necessity of applying a symmetry constraint might limit physiological conclusions to be drawn. On the other hand the good correspondence of the present localization results with other studies justifies its application. A future study has to probe whether contrasting different face tasks in combination with a refined localization approach can disentangle multiple sources and their interplay in early face processing. Acknowledgments We thank Walter Endl, Vienna, for the face photographs. We also thank C. Carbon, T. Bengner, B. Pelzer, and both anonymous reviewers for their detailed comments on earlier versions of the manuscript. This work is supported by DFG grant number GRK 432/2 and BMBF grant number 01GO0208 BNIC. References Allison, T., Puce, A., Spencer, D., McCarthy, G., 1999. Electrophysiological studies of human face perception: I. Potentials generated in occipitotemporal cortex by face and non-face stimuli. Cereb. Cortex 9, 415–430. Belouchrani, A., Abed-Meraim, K., Cardoso, J.-F., Moulines, E., 1997. A blind source separation technique based on second-order statistics. IEEE Trans. Signal Process. 45, 434–444. Bentin, S., Deouell, L., 2000. Structural encoding and identification in face processing: ERP evidence for separate mechanisms. Cogn. Neuropsychol. 17, 35–54. Bentin, S., Allison, T., Puce, A., Perez, E., McCarthy, G., 1996. Electrophysiological studies of face perception in humans. J. Cogn. Neurosci. 8, 551–565. Berg, P., Scherg, M., 1994. A fast method for forward computation of multiple-shell spherical head models. Electroencephalogr. Clin. Neurophysiol. 90, 58–64. Botzel, K., Grusser, OJ., 1989. Electric brain potentials evoked by pictures of faces and non-faces: a search for “face-specific” EEG-potentials. Exp. Brain Res. 77, 349–360. Carbon, CC., Schweinberger, SR., Kaufmann, J., Leder, H., 2005. Early face processing in normal and Thatcher faces: an event-related brain potentials study. Cogn. Brain Res. 24, 544–555. Duvernoy, H., 1999. The Human Brain. Surface, Blood Supply, and ThreeDimensional Sectional Anatomy, 2nd ed. Springer Verlag, Wien. Halgren, E., Raij, T., Marinkovic, K., Jousmäki, V., Hari, R., 2000. Cognitive response profile of the human fusiform face area as determined by MEG. Cereb. Cortex 10, 69–81. Horovitz, S., Rossion, B., Skudlarski, P., Gore, J., 2004. Parametric design and correlational analyses help integrating fMRI and electrophysiological data during face processing. NeuroImage 22, 1587–1595. Hoshiyama, M., Kakigi, R., Watanabe, S., Miki, K., Takeshima, Y., 2003. Brain responses for the subconscious recognition of faces. Neurosci. Res. 46, 435–442. Itier, R., Taylor, M., 2004. Source analysis of the N170 to faces and objects. NeuroReport 15, 1261–1265. Jeffreys, DA., 1989. A face-responsive potential recorded from the human scalp. Exp. Brain Res. 78, 193–202. Jeffreys, DA., Tukmachi, ES., 1992. The vertex-positive scalp potential evoked by faces and objects. Exp. Brain Res. 91, 340–350.
1501
Jousmäki, V., Hari, R., 1996. Cardiac artifacts in magnetoencephalogram. J. Clin. Neurophysiol. 13, 172–176. Joyce, C., Rossion, B., 2005. The face-sensitive N170 and VPP components manifest the same brain processes: the effect of reference electrode site. Clin. Neurophysiol. 116, 2613–2631. Kanwisher, N., McDermott, J., Chun, M., 1997. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302–4311. Lewis, S., Thoma, R., Lanoue, M., Miller, G., Heller, W., Edgar, C., Huang, M., Weisend, M., Irwin, J., Paulson, K., Canive, J., 2003. Visual processing of facial affect. NeuroReport 14, 1841–1845. Linkenkaer-Hansen, K., Palva, J., Sams, M., Hietanen, J., Ilmoniemi, R., 1998. Face-selective processing in human extrastriate cortex around 120 ms after stimulus onset revealed by magnetoencephalography. Neurosci. Lett. 253, 147–150. Liu, J., Harris, A., Kanwisher, N., 2002. Stages of processing in face perception: an MEG study. Nat. Neurosci. 5, 910–916. Lu, S., Hamalainen, M., Hari, R., Ilmoniemi, R., Lounasmaa, O., Sams, N., Vilkman, V., 1991. Seeing faces activates three separate areas outside the occipital visual cortex in man. Neuroscience 43, 287–290. McCarthy, G., Puce, A., Belger, A., Allison, T., 1999. Electrophysiological studies of human face perception: II. Response properties of face-specific potentials generated in occipitotemporal cortex. Cereb. Cortex 9, 431–444. Mnatsakanian, E., Tarkka, I., 2004. Familiar-face recognition and comparison: source analysis of scalp-recorded event-related potentials. Clin. Neurophysiol. 115, 880–886. Rossion, B., Joyce, C., Cottrell, G., Tarr, M., 2003. Early lateralization and orientation tuning for face, word, and object processing in the visual cortex. NeuroImage 20, 1609–1924. Rotshtein, P., Henson, R., Treves, A., Driver, J., Dolan, R., 2005. Morphing Marilyn into Maggie dissociates physical and identity face representations in the brain. Nat. Neurosci. 8, 107–113. Sagiv, N., Bentin, S., 2001. Structural encoding of human and schematic faces: holistic and part-based processes. J. Cogn. Neurosci. 13, 651–937. Sander, T.H., Wubbeler, G., Lueschow, A., Curio, G., Trahms, L., 2002. Cardiac artifact subspace identification and elimination in cognitive MEG data using time-delayed decorrelation. IEEE Trans. Biomed. Eng. 49, 345–354. Sato, N., Nakamura, K., Nakamura, A., Suguira, M., Ito, K., Fukuda, H., Kawashima, R., 1999. Different time course between scene processing and face processing. A MEG study. NeuroReport 26, 3633–3637. Scheer, HJ., Sander, T., Trahms, L., 2006. The influence of amplifier, interface and biological noise on signal quality in high-resolution EEG. Physiol. Meas. 27, 109–117. Scherg, M., Berg, P., 1991. Use of prior knowledge in brain electromagnetic source analysis. Brain Topogr. 4, 143–150. Schweinberger, S., Pickering, E., Jentzsch, I., Burton, A., Kaufmann, J., 2002. Event-related brain potential evidence for a response of inferior temporal cortex to familiar face repetitions. Cogn. Brain Res. 14, 398–409. Talairach, J., Tournaux, P., 1988. Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, New York. Watanabe, S., Kakigi, R., Koyama, S., Kirino, E., 1999. Human face perception traced by magneto- and electroencephalography. Cogn. Brain Res. 8, 125–142. Watanabe, S., Kakigi, R., Puce, A., 2003. The spatiotemporal dynamics of the face inversion effect: a magneto- and electroencephalographic study. Neuroscience 116, 879–895. Ziehe, A., Müller, K.-R., 1998. TDSEP – an efficient algorithm for blind separation using time structure. In: Niklasson, L., Bodén, M., Ziemke, T. (Eds.), Proceedings of the 8th ICANN. Springer Verlag, New York, pp. 675–680.