1 Department of Psychiatry, , 2 Department of Neurology II, Otto-von-Guericke University of Magdeburg, , 3 Leibnitz Institute for Neurobiology, Magdeburg and , 4 Center of Anatomy and Brain Research at Heinrich-Heine University of Düsseldorf, Düsseldorf, Germany
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Abstract |
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Introduction |
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Several imaging studies have demonstrated the importance of medial orbitofrontal/prefrontal and lateral orbitofrontal/ prefrontal cortex during negative and positive emotional stimulation (Pardo et al., 1993; George et al., 1995
; Baker et al., 1997
; Irwin et al., 1997
; Lane et al., 1997a
,b
,c
; Paradiso et al., 1997
; Phillips et al., 1997
; Reimann et al., 1997
; LaBar et al., 1998
; Beauregard et al., 1998
; Büchel et al., 1998
; Morris et al., 1998
). Some authors argue for valence specifity (George et al., 1995
; Imaizumi et al., 1997
; Irwin et al., 1997
; Lane et al., 1997a
,b
,c
; Paradiso et al., 1997
; Phillips et al., 1997
; Pihan et al., 1997
; Aftanas et al., 1998
; Lang et al., 1998
; Morris et al., 1998
), others rather support the hypothesis of non-specific activation pattern in negative and positive emotions (Naumann et al., 1992
, 1993
; Schneider et al., 1995
; Breiter et al., 1996
; Schupp et al., 1997
; Beauregard et al., 1998
; Phelps et al., 1998
). In addition it would be helpful to know the time-course of negative and positive emotional processing in orbitofrontal and prefrontal cortex. Even if negative and positive emotions are processed in similar neural structures they may differ in time-course (early or later orbitofrontal activation) and/or in functional connectivity (distinct functional connections between orbitofrontal cortex and other prefrontal cortical areas in negative and positive emotions).
According to Damasio (Damasio, 1994, 1995
, 1997
), emotions signify somatic and cognitive events before they are transformed into action. One may assume that distinct kinds of signification, either negative or positive, may be processed in different spatial and/or temporal ways from orbitofrontal to premotor/motor cortex. We therefore investigated spatial and temporal activation patterns in orbitofrontal, prefrontal and premotor/motor cortex during emotional-motor (positive and negative pictures associated with a motor response) and non-emotional-motor control (gray and neutral pictures associated with a motor response) conditions in healthy subjects combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG).
Techniques with high spatial (positron emission tomography or fMRI) and temporal (MEG) resolution have been advantangeously combined before (Heinze et al., 1994), particularly in activation with movements (Sanders et al., 1996
; Joliot et al., 1998
; Stippich et al., 1998
), but, to our knowledge, have never been combined in relation to emotional activation. Although there are several methodological problems in applying two techniques with different neurophysiological substrates, hemodynamic (fMRI) and electromagnetic (MEG) activity, the above-cited studies have nevertheless yielded high coincidence between both kinds of signals and thus afford complementary information (Heinze et al., 1994
; Sanders et al., 1996
; Joliot et al., 1998
; Stippich et al., 1998
). Consequently combining spatial and temporal measures with fMRI and MEG during emotional activation may further reveal similarities and differences in physiological mechanisms in neural processing of negative and positive emotions.
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Materials and Methods |
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Healthy subjects (age 25.9 ± 6.1 years, mean ± SD; all right-handed) included 10 persons (5 women and 5 men). Subjects with a history of psychiatric, neurological or other serious physical illness; drug or alcohol abuse; or first-degree relatives with a history of major psychiatric or neurological disorders (as evaluated with the semistructured interview according to DSM IV) were excluded. No subject was taking regular medication.
Ethics approval and permission were obtained from the Ethics Committee of the University of Magdeburg. After complete and detailed description of the study to the subjects, written informed consent was obtained.
Paradigm
Affective Stimulation
Affective stimulation was performed with pictures from the International Affective Picture System (IAPS) (Lang et al., 1997) which was validated also on a German population (Hamm and Vaitl, 1993
). Based on the large-sample valence (positivenegative) ratings, pictures were selected as negative (e.g. a mutilated face) or positive (e.g. smiling baby). Neutral (e.g. a book) pictures served as a control condition in order to control for potentially confounding features of the emotion-generating pictures such as emotionally irrelevant visual stimulation related to objects, scenes, etc., as well as attentional and arousal effects. In addition, gray pictures without any contours, patterns and content, showing only the colour gray homogenously, served as a second control condition in order to control for arousal effects as elicited by visual contents, contours and patterns. Slide sets were matched for content/properties (colours, scenery, objects, people, close-ups of faces, animals), dominance (according to subjective ratings provided by IAPS) and arousal (according to subjective ratings provided by IAPS). Although such matching of contents/properties is not available by the IAPS itself, we nevertheless tried to match pictures as much as possible in orientation using the method of Irwin et al. (Irwin et al., 1997
). Even if the same content or scenery were not exactly available in another valence we nevertheless tried to match the respective picture with a picture containing a somehow related content, property or scenery. For example, a book was not matched with a picture that included people or animals, and vice versa. A picture with predominantly blue content was not mached with a rather red picture. Subsequently pictures differed only in emotional valence (positive, neutral, negative) but neither in dominance nor in arousal.
We employed 100 pictures from each condition (100 negative, 100 positive, 100 neutral, 100 gray) and presented them under computer control. Pictures were presented for 6 s respectively in blocks with 10 valence constant pictures (positive, negative, neutral and gray blocks); between the blocks there was a break of 3 s. The order of blocks was counterbalanced with regard to emotional valence in order to control for potential order effects. Subsequently 40 blocks, each consisting of 10 valence-constant pictures, were presented in a counterbalanced order so that positive, negative, neutral and gray blocks were alternating. Blocks were counterbalanced between subjects as well as across fMRI/MEG investigations. Each picture was presented for 6 s and appeared on a screen with a central fixation point (in both fMRI and MEG in order to avoid eye movements; see also below), and was switched automatically to the next picture. Subjects (all right-handed) had to press a touch switch by means of abduction of the right index finger as soon as a new picture appeared.
Paradigm Implementation
For both MRI and MEG, the visual stimuli were projected automatically via a computer and a back-projection television system.
MRI. In MRI these projected stimuli were then focused via a biconvex lens so that subjects wearing a binocular could see the pictures inside the scanner. The heads of the subjects were restrained using a vacuum-compressed surgical pillow. Subjects were instructed not to move their eyes or other parts of their body. Optimal position of the binocular with fixation (in order to avoid eye movements) as well as of the head and the body were adjusted individually in order to avoid eye and head movements.
MEG. The subject was sitting in a wooden chair in a magnetically shielded room (Low Temperature Laboratory, University of Magdeburg), with the forearm pronated on the armrest. Pictures were presented on a normal screen located 1 m in front of the subject. The optimal position of the subject with regard to the screen was adjusted individually such that they were not forced to move their eyes either horizontally or vertically in order to watch the pictures. The subjects were requested to keep their eyes open and to fixate the middle of the screen in front of them. They were asked not to move either their eyes or other parts of the body before, during and after their finger movements.
Instructions Given to Subjects
The experiment took place in four sessions. Session 1 acquainted fMRI and MEG subjects with the scanner and the experimental procedure. Sessions 2 and 3 were the actual scanning sessions. The order of investigations (first MEG then MRI or inverse) was counterbalanced for subjects within each group, controlling for potential order effects. In session 4, subjects made ratings of the pictures to which they were exposed.
Prior to all sessions, subjects were told that they will view various pictures with different emotional contents. Furthermore, subjects were informed they (all subjects) would receive an i.v. injection of saline before fMRI/MEG since the subjects of the current study were used as a placebo-control group as part of an ongoing study.
Subjects were further asked to remain as motionless as possible to minimize MEG and fMRI movement artifacts. They were told to avoid eye movements before, during and after their finger movements and to fixate a central fixation point on the screen in MEG and the binocular in fMRI. If they had the urge to move either their body or their eyes they were instructed to do this during the 3 s break between the blocks. All subjects understood they could terminate the experiment at any time without explanation. Before actual fMRI and MEG scanning (i.e. before session 2), subjects were given the opportunity to practise prior to the experiment with 20 test pictures.
Behavioral and Psychological Monitoring
Reaction time the time from the appearance of a new picture to the execution of the finger movement (i.e. press on the touch switch) was registered. For analysis we calculated the means of reaction time for each condition (i.e. positive, negative, neutral, gray) and compared them statistically using Friedman tests for dependent samples. We choosed reaction time as a behavioral measure of emotional valence since it is known that the time necessary for movement preparation and initiation depends on the respective functional context (other movements, concomittant visual stimuli, etc.); the more complex the content (and the movement), the longer the reaction time (Kristeva et al., 1991; Kristeva-Feige et al., 1997
; Naito et al., 1998
). Hence we expected differences in reaction times between negative, positive and neutral (i.e. more complex) pictures on the one hand, and gray (i.e. less complex) pictures on the other hand. Assuming different correlation patterns between both emotional conditions we in addition performed correlational analysis between subjective ratings of the pictures and reaction times for each condition (negative, positive, neutral, gray) using Spearman correlation analysis with Bonferroni correction (significance level of P = 0.0042).
In order to control for pre-experimental psychological states, which might influence emotional induction, all subjects had to fill out the Bf-s, the Befindlichkeitsskala (Zerssen, 1976), a well-validated instrument for self-evaluation of actual psychological state. Furthermore each subject was retrospectively asked whether the injection had any influence on their psychological state; all subjects denied that it had.
Pictures from the IAPS were subjectively rated for valence, dominance and arousal with the Self-Assessment Manikin (SAM) (Lang, 1980). IAPS ratings of were done after fMRI/MEG investigations. Subjective ratings of the different conditions were compared with those obtained by Hamm and Vaitl, who validated the IAPS for a German population (Hamm and Vaitl, 1993
). Due to the influence of the magnetic field we were unfortunately unable to obtain vegetative measures of emotional responses (skin resistance, etc.) during scanning.
Functional MRI
Data Acquisition
The images were acquired in a Bruker Biospec 3T/60cm head scanner equipped with a quadrupolar birdcage head coil. Before scanning, the nasion and the right and left preauricular points were marked with paramagnetic markers in order to project dipoles from MEG on anatomical and fMR images. The subjects heads were immobilized with a vacuum cushion with attached earmuffs. An imaging session started with low-noise [sound pressure level (SPL) 62 dBA], low-contrast FLASH images in mediosagittal directions. The use of a FLASH sequence offers the possibility to slow down the gradient switching. Together with an optimized excitation pulse and modified spoiler gradients the final low-noise imaging sequence, focused on a few slices, produced a noise peak level of 58 dB SPL at the position of the ear.
Five contiguous axial planes of the whole frontal lobe including the medial and lateral frontal cortex, the motor and premotor cortex, the orbitofrontal cortex and the anterior cingulate (i.e. from orbitofrontal cortex and ventricles up to central sulcus) were chosen for functional imaging (i.e. thickness of 8 mm, 160 mm field of view, and 64 x 64 matrix size) (see Fig. 1).
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High T1-contrast imaging (MDEFT) was used to obtain anatomical landmarks with high three-dimensional resolution and immediately followed fMRI with the following parameters: field of view 256 mm, slice thickness 2.25 mm, 64 slices, in-plane matrix size 256 x 256. On the basis of these anatomical images, localization of slices/activity in fMRI and dipoles from MEG were determined.
Image and Statistical Analysis
Data were analyzed as follows. First, subject movement was monitored using the AIR package. Data were selected for further analysis on the basis of the absence of motion artifacts. In orientation on the standard (Bandettini et al., 1993, Sanders et al., 1996
) subjects with head movements >2 mm and or >1° were excluded from initial analysis (n = 2). Since both subjects showed only slightly increased movements (2.4 mm and 1.2°; 2.0 mm and 0.9°) we first ran an analysis without them and then included them into the analysis in order to increase the number of subjects; this did not result in any changes in the results. Moreover, we compared the subjects below the artifact rejection rate (n = 8) with those above the artifact rejection rate (n = 2) and could not found any differences. In agreement with previous methods used (Irwin et al., 1997
; Lang et al., 1998
) we finally checked all subjects (n = 10) for presence/ absence of eye movement artifacts in vertical and horizontal EOG as measured in MEG (see below). None of the subjects included into final analysis (n = 10) showed any alterations in EOG as can be seen in Figure 3
. Hence the results reported are the ones from the second analysis with 10 subjects, which included the two subjects initially excluded.
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Activity in these ROIs in both hemispheres was analyzed by correlation analysis (Bandettini et al., 1993) to obtain a statistical parametric map. Such a map displays the spatial distribution of the Z-score for each of the differences or constrasts positivenegative, positiveneutral, positivegray, negativeneutral, negativegray and neutralgray. These maps were thresholded (P < 0.001) (P < 0.05 for the spatial extent of the activation foci) and overlaid onto our anatomical template image to attribute each activation focus to an anatomical area. To orientate standards with regard to thresholds, two kinds of analysis were performed: one without correction for multiple comparisons (P < 0.001), and one with correction for multiple comparisons (P < 0.01), in agreement with Lang et al. (Lang et al., 1998
) who used a similar procedure. Since both kinds of analysis revealed similar results, activated voxels seem to represent true activations rather than artifacts of multiple comparison. Percentages of significantly activated voxels and intensity-weighted volumes (IWVs) (the product of the absolute number of voxels and the average signal change in each region in all slices) were determined for positively and negatively correlated activations (Gaschler-Markewski et al., 1997
). In addition to absolute numbers of positive and negative IWVs (see Table 1
), we determined the relative activation (positive IWVs)/deactivation (negative IWVs) strength of prefrontal cortical regions with highest, intermediate and lowest activity within the respective contrast (see Table 2
). The right and left side of each region were added and divided by two and compared to the other regions so that finally distribution of activity across the various prefrontal cortical regions within that particular contrast was obtained; comparisons of relative activation strength across the various contrasts remain impossible. For interpretation of results for each contrast separately one should thus put both kinds of presentations absolute number of positive/negative IWVs in each prefrontal region (Table 1
) and relative activation strength across prefrontal regions (Table 2
) together. Correlation analyses using Spearman rank correlation tests were performed to calculate relations between fMRI signal (IWV) in the various ROIs and reaction times (Naito et al., 1998
).
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In order to corroborate on anatomical grounds the emerging results (see below) of a dissociation of primate prefrontal cortex into medial and lateral groups, we statistically investigated the connectivity patterns of the prefrontal areas. In analogy to Young et al.'s analysis of the visual streams (Young et al., 1995), we characterized the dichotomization of prefrontal cortical areas into two groups by a two-sided criterion: (i) areas should be significantly more connected within the groups than between the groups, and (ii) areas should be significantly more disconnected between the groups than within the groups.
This standard criterion for anatomical dissociation of two areal groups can easily be evaluated by performing a chi-squared test on the respective connectivity data. As data on human cortical connectivity are not available, we addressed this issue generally for primate prefrontal cortex by using macaque connectivity data from the database CoCoMac (http://www.hirn.uni-duesseldorf.de/~rk/Cx/CoCoMac.htm). This relational database currently contains almost 5000 experimental findings on corticocortical connectivity collated in a standardized manner from published tracing studies. Using objective relational transformation (ORT), CoCoMac is able to convert data between different parcellation schemes independent of spatial coordinates (Stephan and Kötter, 1999; Stephan et al., 1999). In order to control for potential influences of the resolution of the chosen parcellation scheme on the result of our statistical test, we used CoCoMac to transform the data into two different maps, the traditional (and rather coarse) map of Walker (Walker, 1940
), and the scheme of Carmichael and Price (Carmichael and Price, 1994
), which is considerably more fine-grained for orbital and medial parts of prefrontal cortex. For both maps, we assigned each area either to a lateral or a medial group. An area was assigned to the lateral group if it was entirely situated on or encroached substantially onto the lateral convexity, i.e. for Walker's map the lateral group comprised areas 8A, 8B, 9, 12, 45, 46, whereas for the scheme of Carmichael and Price it contained areas 12r, 12l, 10o, 45, 46, 8 and 9. All other prefrontal areas were assigned to the medial group.
Magnetencephalography (MEG)
Experimental Procedure
A 148-channel (i.e. arranged in a helmet-like configuration) DC-SQUID neuromagnetometer (Magnes 2500 WH, Biomagnetic Technologies, San Diego, CA), covering the whole scalp, recorded the brain's magnetic fields. This device employs 74 pairs of two orthogonal figure-of-eight planar first-order gradiometers, measuring at each location the two orthogonal derivatives, one along the latitudes and the other along the longitudes, of the radial magnetic field component Bz. With this configuration, the largest signal can be detected just above the source current.The electro-oculogram (EOG) was recorded using Ag/AgCl electrodes. To monitor eye movements and the possible spread of brain activity below the orbit, one measurement between the right/left infraorbital and the right/left mastoid was adopted in addition to the conventional vertical and horizontal electro-oculograms from both eyes. Surface EMG associated with abduction of the index finger was recorded from two electrodes placed ~2 cm apart over the right first dorsal interosseus muscle.
A subset of MEG channels, EOG and EMG were displayed on a screen continuously, so that the task performance and the vigilance of the subject could be monitored.
A three-dimensional Cartesian head coordinate system was defined for each subject based on three anatomical landmarks: left and right preauricular points as well as nasion. In this three-dimensional head coordinate system the positive x-axis passed through the nasion (anteriorposterior direction) and the positive y-axis through the left preauricular point (mediallateral direction), whereas the z-axis (representing the inferiorsuperior direction) was perpendicular to the point of bisection between the xand y-axes. Position and orientation of the sensor as well as the head shape with respect to this coordinate system were measured with a three-diemsional digitizer before and after each recording session.
Signal Analysis. The recording passband was 050 Hz for MEG, 0.01100 Hz for EOG (6 dB points) and 303000 Hz for EMG. The signals were digitized at 254.31 Hz and afterwards segmented into stimulus-locked epochs of 2.0 s duration (1800 ms pretrigger interval). Off-line reduction of environmental noise was performed through subtraction of the weighted signals from three reference channels. Automatic rejection level of field amplitudes >3 pT/cm was used to exclude magnetic artifacts; for EOG the rejection level was 100 µV. Spontaneous activity was continuously stored on a magneto-optical disk for later off-line analysis. The averaged epochs were finally filtered with a 45 Hz low pass in combination with a 50 Hz Notzh filter.
Off-line Analysis. The spontaneous signals were analyzed off-line to obtain precise alignment with the EMG onset. Signals associated with each EMG burst were reviewed visually, and the epochs containing eye motion artifacts, ambigous EMG bursts or other artifacts were omitted from the analysis. Only those trials without any eye motion artifacts containing movements with the same abrupt onset rise time and the same shape as seen in the rectified EMG were utilized for further analysis. A total of at least 70 artifact-free trials were averaged for each experimental condition (positive, negative, neutral, gray), otherwise (<70 artifact-free trials per condition) the subject was excluded from the study (see above: Exclusion criteria). There were neither significant differences nor any trends in number of eye artifacts between the four conditions (negative, positive, neutral, gray); hence emotional conditions did not induce more eye artifacts than non-emotional conditions. Subjects whose head positions differed by >1 cm between the beginning and the end of the session, as measured with the three head positions (nasion, preauricular left and right; see above) were excluded (n = 1). After digital low-pass filtering at 45 Hz and a 50 Hz Notzh filter, the signals were subjected to amplitude measurements within epochs of 50 ms within a time window of analysis of 2200 ms (2000 to +200 ms), of which the first 200 ms were used for determining the baseline. The processed data were also utilized for construction of isocontour maps, and, finally, for source identification. Occipital channels were excluded for analysis of amplitudes and source identification in order to avoid interference between visual processing in occipital regions and early emotional processing in frontal areas.
Isocontour Maps and Source Identification. Isocontour maps of the field amplitude were constructed from the measured data at selected latencies (200 ms epochs within the time window of analysis) using linear interpolation.
To identify sources underlying the measured signals, the signal distributions were modeled using the model of a moving dipole (MD) embedded in a homogenous spherical volume conductor. The centre of the volume conductor was evaluated by approximating the surface of the scalp underneath the gradiometer system by the above-mentioned sphere. The model (strength, position, orientation) parameters were optimized by means of an iterative least-squares procedure. The MD analysis was performed for each 50 ms epoch within the time window of analysis. Only MDs accounting for >60% of the field variance and with a goodness-of-fit value >8590% were accepted. For each 50 ms epoch within the window of time analysis, the MD with the best goodness-of-fit value was taken as the representative one.
MRIMEG Integration.
(i) Dipole locations were projected onto the corresponding three-dimensional anatomical MRI scan (see above for further details of anatomical MRI scan). To identify the nasion and the two preauricular points in the MRI, paramagnetic markers (Nitro capsules) centered on these points were fixed on the scalp. The markers were easily identified in the MR images and served as reference points for localizing the estimated dipole locations in the MRI data sets. Prefrontal, premotor and motor cortical areas were identified in anatomical MRI as described in the TalairachTournoux atlas (Talairach and Tournoux, 1993). (ii) Functional MR images were matched and projected on the respective individual three-dimensional anatomical MRI scan with the respective dipole locations in order to compare anatomical localizations between dipoles and fMRI signals. (iii) The ROI in fMRI, within which the dipole could be localized, and its nearest local maximum of activation in the slice indicated by MEG, were determined in agreement with the method applied by Sanders et al. (Sanders et al., 1996), which compared to other methods of comparison between MEG and FMRI signals proved to be the most valid one. However, interpretation remains limited since, firstly, both kinds of signals must be physiologically distinguished; and secondly, comparison reflects only anatomical closeness or distance, and any physiological interpretation should be avoided. Hence, interpretation is limited and rather relative. (iv) Talairach coordinates of both estimated dipoles and corresponding regional activation clusters in fMRI were determined in reference to three-dimensional anatomical MRI. (v) Talairach coordinates for dipoles and corresponding fMRI signals were compared with each other to measure differences in anatomical localization in millimeters (see Table 4
). Although these values seem to be a quite exact interpretation, due to the above-mentioned reasons, the results do, however, remain limited and rather relative, as they only reflect anatomical closeness or distance within one or several regions between both kinds of signals.
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Results |
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Mean reaction times were lowest during gray pictures (443.10 ± 139.23 ms) and higher during negative (520.95 ± 160.40 ms), positive (520.01 ± 178.31 ms) and neutral (529.29 ± 184.36 ms) conditions. Variance analysis, however, did not show any significant difference (P = 0.731) between the four conditions.
Pre-experimental psychological states as measured with the Befindlichkeitsskala (BFs) (see Materials and Methods) revealed a value of 13.42 ± 5.05, indicating no major stress in current psychological state. Ratings of valence, dominance and arousal of pictures from IAPS (see Materials and Methods) in healthy subjects did not differ from ratings in the already investigated healthy population (Hamm and Vaitl, 1993; Lang et al., 1997
). The heart rate as a physiological measure, which could be obtained in MEG only, showed no significant differences between the four conditions (73.3 ± 4.5 min in negative emotions; 69.5 ± 3.6 in positive emotions; 68.8 ± 3.8 min in neutral pictures; 62.3 ± 3.6 min in gray pictures).
Cortical Activation in fMRI
Activation signals in fMRI showed clusters of activation in orbitofrontal, lateral prefrontal and premotor cortical areas, corresponding to BA 11 and 12 (orbitofrontal), BA 9, 45, 46 and 47 (lateral prefrontal), and BA 6 (premotor), whereas the other prefrontal/frontal areas such as cingulate cortex (BA 24, 32), medial prefrontal cortex (BA 8, 9,10) and motor cortex (BA 4) were less activated (see Table 1 and Fig. 2
). In general, activation was much stronger in contrasts involving positive or/and negative emotional pictures than in non-emotional contrasts (grayneutral) (see Table 1
). We did not observe differences in lateralization between the four experimental conditions (gray, neutral, positive, negative) (see Fig. 3
) or different activation patterns in women and men.
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Contrasts involving positive emotional pictures (positive gray, positiveneutral, positivenegative) showed strong activation clusters, particularly in lower lateral prefrontal cortex (BA 46, 47), and less strong clusters in medial orbitofrontal cortex (BA 11, 12). In addition, positive emotional stimulation led to quite strong activation in premotor cortex which was not found in negative emotions (see Tables 1 and 2 as well as Fig. 2
). Negatively correlated activity in contrasts involving positive pictures (positivegray, positiveneutral) was strongest in orbitofrontal cortex (BA 11, 12) and less marked in lateral prefrontal cortex (BA 9, 46) (see Tables 1 and 2
as well as Fig. 2
).
The negativepositive contrast showed the strongest positively and negatively correlated IWVs in orbitofrontal and lateral prefrontal cortex as well as in premotor cortex (only negatively correlated IWVs) (see Tables 1 and 2), further underlining the importance of these cortical regions in neural processing of positive and negative emotions.
In summary, negative and positive emotional pictures led to different activation patterns in orbitofrontal, lateral prefrontal and premotor cortex. Negative emotional pictures induced strong activation (i.e. positively correlated IWVs) in medial orbitofrontal cortex and marked negatively correlated activity in lateral prefrontal cortex, whereas positive emotional stimulation showed an inverse pattern with strong activation in lateral prefrontal cortex and marked negatively correlated activity in orbitofrontal cortex (see Table 2).
Structural Connectivity in Primate Prefrontal Cortex
The CoCoMac database delivered 474 published reports on connectivity between the prefrontal areas of the map of Carmichael and Price (Carmichael and Price, 1994) (351 existing connections, 123 connections explicitly stated to be absent) and 104 reports for the respective areas of Walker's map (Walker, 1940
) (74 existing connections, 30 connections absent). Performing a chi-squared-test for each dataset according to the criterion of Young et al. (Young et al., 1995
) (see Materials and Methods), the null hypothesis was significantly rejected in both cases (P < 0.01). Therefore, the anatomical connectivity corroborates the view that the primate prefrontal cortex is effectively dissociated into distinct lateral and medial groups of areas.
Electromagnetic Signals in MEG
A representative magnetoencephalographic curve during index finger movement with emotional stimulation can be seen in Figure 3. All subjects typically showed a readiness field (RF), starting 500 ms prior to the movement, and a motor field (MF) (50 to 50 ms) before and during movement execution. Both RF and MF were seen mainly over the left somatomotor area, followed by the movement-evoked fields MEFI (80150 ms) and MEFII (150200 ms), peaking at 100 and 180200 ms respectively. The complete MEFII as well as MEFIII and PMF (postmovement field) could not be recorded because recording time was limited to 200 ms after movement onset (see Materials and Methods). The largest signal was reproducible over the left somatomotor area. This pattern of movement-related magnetic fields was observed in all subjects and showed no major differences between conditions (gray, neutral, positive, negative) (see Tables 3 and 4
).
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In summary, MEG signal analysis revealed the typical pattern of movement-related magnetic fields with a readiness field (RF), starting about 500 ms prior to movement onset, and motor fields (MF, MEFI) during and after movement onset. Dipoles of movement-related magnetic fields could be anatomically localized in anterior and posterior parts of primary motor cortex. In addition to movement-related magnetic fields, an EMF in early time windows (1700 to 1100 ms) was observed only in positive and negative emotions but not in either of the control conditions (neutral, gray). Onset, strength and anatomical location of EMF differed between negative and positive emotions. EMF showed an earlier onset, a higher strength and a more medially oriented orbitofrontal location in negative emotions than in positive emotions. Single ECDs for EMF were anatomically localized either in medial orbitofrontal cortex (negative emotions) or in lateral orbitofrontal/lower lateral prefrontal cortex (positive emotions), corresponding quite well to activation signals in the respective cortical area in fMRI.
Correlations between MRI/MEG Signals and Behavioral Measures
We correlated reaction times with subjective ratings and regional activation signals in fMRI/MEG using the Spearman rank correlation test with Bonferroni correction (significance level of P = 0.0042 which is here equated with P = 0.05). We obtained significant correlations between reaction times and subjective ratings only in negative emotions (r = 0.771; P = 0.033) but neither in positive emotions nor in the other two conditions (neutral, gray).
Concerning fMRI, regional activation signals were correlated with differences in reaction times between corresponding conditions. In the grayneutral contrast marginally significant correlations were found between reaction time and right lateral prefrontal (r = 0.711; P = 0.079), right medial prefrontal (r = 0.676; P = 0.095), and left premotor (r = 0.713; P = 0,070) cortical activity. In addition, significant correlations were found only in negative emotions but not in contrasts involving positive emotions. Both contrasts, negativegray and negativeneutral, showed significant/marginally significant correlations between reaction time and right medial prefrontal (r = 0.713/0.755; P = 0.047/0.069) and right motor (r = 0.677/0.874; P = 0.013/0.096) cortical activation signals.
Reaction time in negative emotions correlated significantly (r = 0.935/0.876; P = 0.023/0.032) with magnetic field strength (RMS/dipole RMS) in EMF, whereas no significant correlations were found with late magnetic fields (RF, MF, MEFI). No significant correlations between reaction times and magnetic fields were found in the other three conditions (positive, neutral, gray).
In summary, subjects showed significant correlations of reaction time with subjective experience, right medial prefrontal/motor cortical fMRI signals and early magnetic field strength only in negative emotions but neither in positive emotions nor in both control conditions (neutral, gray).
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Discussion |
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The results of the present study confirm our initial hypothesis of spatial and temporal differences between negative and positive emotional processing from medial/lateral orbitofrontal to premotor/motor cortex, which, in addition, lend further support to the assumption of a functional subdivision of the orbitofrontal cortex into a medial and a lateral part showing distinct temporal and connectional patterns. Negative and positive emotional processing led to almost inverse alterations (positively or negatively correlated activity) in medial and lateral orbitofrontal cortex, showed distinct temporal patterns, and could be characterized by differences in effective connectivity between medial and lateral prefrontal cortical structures. Consequently, negative and positive signification of somatic and cognitive events may be subserved by different prefrontal cortical neural networks, which can be distinguished by their spatial, temporal and connectional properties.
Spatial, Temporal and Connectional Differences in Orbitofrontal Cortex during Negative and Positive Emotional Processing
In accordance with previous studies we found strong activation in orbitofrontal, lateral prefrontal and premotor cortex during emotional stimulation (Pardo et al., 1993; George et al., 1995
; Morris et al., 1996
, 1998
; Baker et al., 1997
; Imaizumi et al., 1997
; Irwin et al., 1997
; Lane et al., 1997a
,b
,c
; Paradiso et al., 1997
; Phillips et al., 1997
; Büchel et al., 1998
; LaBar et al., 1998
). Most studies report activation of different cortical regions during negative and positive emotional stimulation (George et al., 1995
; Morris et al., 1996
, 1998
; Baker et al., 1997
; Imaizumi et al., 1997
; Irwin et al., 1997
; Lane et al., 1997a
,b
,c
; Lang et al., 1998
), whereas only some authors postulate similar neuro-anatomical substrates for negative and positive emotional processing in prefrontal cortex (Beauregard et al., 1998
) and/or amygdala (Breiter et al., 1996
, Phelps et al., 1998
).
We found dissimiliar extents of activity in medial orbitofrontal and ventral lateral orbitofrontal cortex during negative and positive emotional processing (see Table 2). Similar to other authors, we found activation (i.e. positively correlated activity) in orbitofrontal cortex during negative emotional stimulation and in lateral prefrontal cortex during positive emotional stimulation (Pardo et al., 1993
; George et al., 1995
; Baker et al., 1997
; Irwin et al., 1997
; Paradiso et al., 1997
; Philipps et al., 1997; Morris et al., 1998
; Mayberg et al., 1999
). In addition, we found a high proportion of negatively correlated activity in orbitofrontal cortex during positive emotional processing and in lateral prefrontal cortex during negative emotional stimulation, which, depending on the interpretation of negatively correlated activity (see Methodological limitations), would be in accordance with PET studies reporting increases and decreases of activity in similar regions. Baker and co-workers (Baker et al., 1997
) found increased orbitofrontal and decreased lateral prefrontal cortical activity during negative emotional stimulation, which, with regard to orbitofrontal increase, is further supported by similar findings in other studies (George et al., 1995
; Paradiso et al., 1997
; Mayberg et al., 1999
). In contrast, positive emotional stimulation led to decreased orbitofrontal (Paradiso et al., 1997
) and increased lateral prefrontal (Baker et al., 1997
) cortical activity. Concerning laterality, we could not find any significant differences in right/left activation between negative and positive emotional processing in orbitofrontal cortex or in lateral prefrontal or other prefrontal cortical areas. Such a finding is in agreement with some studies (George et al., 1995
; Baker et al., 1997
; Gainotti et al., 1997
; Lane et al., 1997a
,b
,c
; Reimann et al., 1997
; Beauregard et al., 1998
), but it disagrees with other studies that find differential lateralization patterns in negative (right frontal cortex) and positive (left frontal cortex) emotions (Morris et al., 1996
, 1998
; Imaizumi et al., 1997
; Irwin et al., 1997
; Paradiso et al., 1997
; Sutton et al., 1997
). In addition, we did not find any strong tendencies of lateralization of the early underlying dipole in MEG. However, due to the fact that the issue of lateralization in emotional processing cannot currently be resolved, interpretation of our finding of nonlateralization has to remain open.
Such spatial patterns in neural processing of negative and positive emotional stimulation are further underlined by consideration of temporal aspects as investigated with MEG. Similar to other authors (Kristeva et al., 1991; Salmelin and Hari, 1994
; Nagamine et al., 1996
; Hoshiyama et al., 1997
; Joliot et al., 1998
; Kristeva-Feige et al., 1997
, 1994
; Stippich et al., 1998
), we found movement-related magnetic fields in all four conditions (i.e. which did not differ in the movement required) and, in addition, an EMF only in emotional (negative and positive) but not in non-emotional (neutral, gray) conditions. Since similar early changes in magnetic fields have never been observed in MEG studies investigating movements only (see above), such early magnetic activity must somehow be related to emotional processing, though other effects cannot be excluded entirely (see Methodological limitations). Similar to investigations with EEG (Naumann et al., 1992
, 1993
; Cuthbert et al., 1993
; Pihan et al., 1997
; Schupp et al., 1997
; Aftanas et al., 1998
), magnetic activity differed considerably between negative and positive emotional conditions. In negative emotional stimulation, both the early magnetic field and its corresponding dipoles showed an earlier onset (1700 ms), a higher strength and a more medially oriented orbitofrontal location than in the positive emotional condition, which was characterized by a later onset (1200 ms), a lower strength and a rather laterally oriented orbitofrontal location (see Tables 3 and 4
as well as Figs 2
and 5). Such differences in magnetic fields are in accordance with results from fMRI where the orbitofrontal cortex was strongly activated in negative emotional stimulation and the lateral prefrontal cortex in positive emotional stimulation (see above).
Considering spatial and temporal differences during negative and positive emotional stimulation, one may thus assume distinct neural pathways in prefrontal cortex for negative and positive emotions. Negative emotional stimulation is processed early with strong activation from medial orbitofrontal cortex to premotor/motor cortex via the cingulate cortex. In contrast, prefrontal activation in positive emotional stimulation is generated later and weaker in lateral orbitofrontal and lateral prefrontal cortex continuing to premotor/motor cortex via cingulate cortex and medial prefrontal cortex. Such a differential role of medial and lateral orbitofrontal cortex in negative and positive emotional processing is further supported by consideration of cytoarchitectonical, connectional and functional differences (Morecraft et al., 1992; Bates and Goldman-Rakic, 1993
; Carmichael and Price, 1994
, 1995a
, Carmichael and Price, b
, 1996
; Barbas, 1995
; Morecraft and Van Hoesen, 1998
). The medial orbitofrontal cortex shows an agranular or dysgranular cytoarchitetconic; is connected with hippocampal formation, ventrolateral parts of the basal nucleus of the amygdala, dorsolateral prefrontal cortex (area 9 and rostral 46), dorsomedial parts of mediodorsal thalamic nucleus and anterior cingulate cortex; and is functionally involved in negative emotional processing and affective reactivity to alien stimuli (Morecraft et al., 1992
; Baker et al., 1997
; Drevets and Raichle, 1998
; Morecraft and Van Hoesen, 1998
). In contrast, the lateral orbitofrontal cortex shows a granular cytoarchitetconic, and is connected with ento/perirhinal cortex, ventromedial parts of the basal nucleus of amygdala, dorsolateral prefrontal cortex (area 45 and caudoventral 46), ventromedial parts of mediodorsal thalamic nucleus, premotor and parietal cortex, and posterior cingulate cortex. One may thus hypothesize that, functionally, the lateral orbitofrontal cortex may be related to the formation of assocations between emotions and thoughts (Morecraft et al., 1992
; Bates and Goldman-Rakic, 1993
; Baker et al., 1997
; Drevets and Raichle, 1998
; Morecraft and Van Hoesen, 1998
). Consequently, negative emotional stimulation may be processed in medial prefrontal cortical areas, whereas positive emotional stimulation uses lateral prefrontal cortical structures.
Such a functional dissociation between medial and lateral prefrontal cortex with distinct temporal properties is further supported by our analysis of structural connectivity in primate prefrontal cortex showing a clear connectional differentiation between medial and lateral prefrontal cortical pathways, which would be in full accordance with the present fMRI/MEG data as measured in humans.This distinction between medial and lateral prefrontal cortical pathways may account for the process of negative and positive signification of somatic and cognitive events. According to Damasio (Damasio, 1994, 1995
, 1997
), somatic and cognitive events become signified by emotions either negatively or positively before they are transformed into actions. The activation paradigm in the present study consisted in concomitant emotional (negative and positive visual pictures) and motor (finger extension with a mouse click after the appearance of each picture) stimulation, thus requiring transformation of negative and positive emotional experience into (motor) action, and therefore investigated the spatial and temporal course of emotionalmotor activation from orbitofrontal to premotor/motor cortex via the various prefrontal cortical regions. Spatial and temporal differences between negative and positive emotional processing may be interpreted as a support for the assumption that the process of transformation of negatively and positively signified events into actions may be subserved by distinct prefrontal cortical networks.
Methodological Limitations
Conclusions
The role of medial and lateral orbitofrontal cortex, as well as temporal properties of prefrontal cortical activation during negative and positive emotional stimulation, remains unclear. According to Damasio, negatively and positively signified events may be transformed into action using distinct prefrontal cortical networks. We therefore investigated spatiotemporal activation patterns in orbitofrontal and prefrontal cortex during concomitant emotional-motor stimulation in a combined MEG/fMRI study.
Negative emotional processing could be characterized by increased orbitofrontal activation and early (1700 ms), strong and more medially oriented orbitofrontal dipoles, whereas positive emotional stimulation led to lateral prefrontal activation with later (1500 ms), weaker and more laterally oriented orbito/prefrontal dipoles.
It is concluded that negative emotional processing can be characterized by early and strong medial orbitofrontal cortical activation, whereas positive emotional processing generates later and weaker activation in lateral orbitofrontal and lateral prefrontal cortex. Thus the present results confirm the assumption of a functional dissociation between medial and lateral orbitofrontal cortex in negative and positive emotional processing. In addition, negatively and positively signified events may be transformed into action using distinct, i.e. medial and lateral prefrontal, cortical networks.
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Notes |
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Address correspondence to G. Northoff MD, Ph.D., Department of Psychiatry, Otto-von-Guericke University of Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany. Email: Georg.Northoff{at}Medizin.Uni-Magdeburg.de.
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