Max-Planck-Institute of Cognitive Neuroscience, Leipzig, Germany
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Abstract |
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Introduction |
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Studies investigating novelty processing in the brain usually include two varieties of novel information, namely generic and episodic novelty. Generic novelty is provided by stimuli that have never before been experienced by the subjects. A traditional index of the response to such stimuli is the autonomic galvanic skin response (van Engeland et al., 1991; Knight, 1996
). The same kinds of stimuli that elicit autonomic skin responses cause an involuntary attentional shift when they occur outside the current focus of attention because of their potential behavioral significance [orienting response (Knight, 1984
; Näätänen, 1990
)]. Converging evidence suggests that the neurophysiological mechanisms underlying the orienting response are reflected in the event-related potentials (ERPs) as a frontally distributed, positive-going deflection that peaks around 300 ms, the so-called novel P3 (Courchesne et al., 1975
; Woods, 1990
). This ERP component is usually elicited by unexpected non-tonal environmental sounds that are embedded in a train of frequent standard and rare deviant stimuli. When novel events are repeated and thus are categorizable into a discrete group of events there is a change from a frontal to a more posterior scalp distribution of the novel P3 (Priedman et al., 1998).
Several divergent methods have been employed to delineate the sources of late positivities in the ERP (Rogers et al., 1993; Mecklinger et al., 1998
). Electroas well as magnetoencephalographic scalp recordings have shown that the scalp novel P3 reflects the activity of a widespread neuronal network including frontal and parietal lobes as well as lateral and medial temporal lobe structures (Mecklinger and Ullsperger, 1995
; Alho et al., 1998
). Additionally, research on stroke patients with focal brain lesions (Knight, 1984
, 1996
) and on epileptic patients undergoing depth electrode measurements (Baudena et al., 1995
; Halgren et al., 1995a
,b
) also suggested that the novel P3 reflects the activity of a distributed network, with major components in the hippocampus, the temporal lobes and dorsolateral prefrontal cortex.
Conversely, episodic novelty is provided by stimuli that are familiar in general but occur in a specific task situation for the first time. This is the situation in recognition paradigms in which subjects are required to decide whether or not a given stimulus has occurred previously in the experimental setting. In positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies, the difference in brain activation between new stimuli and previously presented, i.e. old stimuli (NEW minus OLD subtraction) allows the brain regions involved in novelty processing to be examined. There is converging evidence from these studies that novelty processing activates a large cortical and subcortical network including temporal, parietal and frontal regions, irrespective of whether visual words (Kapur et al., 1995), pictures (Tulving et al., 1996
) or auditory sentences (Tulving et al., 1994
) are used as stimulus materials. Tulving et al. (Tulving et al., 1996
) assume that this transmodal novelty network realizes two subprocesses: novelty assessment, subserved by subcortical and temporal as well as parietal cortical regions, and novelty encoding, subserved by the frontal lobes.
These studies show that novelty is a broad concept that embraces a number of separable processes and brain regions. In a recent study, brain responses to two forms of auditory generic novelty namely meaningful and non-meaningful novel sounds under attend and unattend conditions were examined (Mecklinger et al., 1997). This study revealed that only meaningful novel events for which a conceptual semantic representation can be assumed elicited a negative ERP component subsequent to the novel P3. In light of the topographical and functional similarities of this negative component with N4 components evoked by lexical-semantic aspects of language processes (Kutas and Hillyard, 1983
) it was suggested that it reflects conceptual-semantic processes, i.e. the retrieval of semantic concepts expressed by the sounds.
The present study aims at identifying the spatialtemporal characteristics of brain activation underlying the processing of identifiable (meaningful) and non-identifiable (non-meaningful) novel events by combining ERP and fMRI measures. The ERP approach to novelty processing is necessarily approximate in its capability of identifying functionally relevant brain regions, because neuronal sources can only be estimated from the two-dimensional scalp topography using inverse methods like dipole fitting algorithms [for an overview see Scherg (Scherg, 1990)]. Conversely, neuroimaging methods, despite their capability of localizing brain structures underlying cognitive functions with a high spatial resolution, in most cases do not provide the temporal resolution required to make inferences about the subprocesses involved in novelty processing that operate in the millisecond range.
In an effort to overcome the intrinsic limitations of both approaches, in the present study parallel ERP and fMRI recordings were conducted in separate sessions using the same subjects and stimulus materials, i.e. identifiable and non-identifiable novels sounds embedded in a train of tonal events. Because some aspects of novelty processing are considered as an automatic, biological response that operate independently of attentional processes, the experiments included two attentional conditions in which the subjects either attended to or ignored the stimulus train. Both the electrophysiological and hemodynamic measures were integrated by means of a neuroanatomically constrained source analysis. The fMRI provides the number and locations of possible generators of scalp-recorded ERP components that are active in specific time intervals. Therefore, equivalent current dipoles were kept fixed in location according to fMRI results and their orientations were modeled in order to fit the topographic distribution of specific ERP components. Although the fMRI constrained source analysis has a physiological basis, there is some disagreement between electrophysiological and hemodynamic measurements because fMRI and ERP measure physiologically different aspects of brain activity. Therefore, it is possible that changes in the hemodynamic signal will not have an ERP correlate unless they involve synchronous modulation of an neural population in the `open field' configuration (Nunez, 1981). These cases could be easily identified in that neural generators located in these areas will not fulfill the electro-physiological constraints of limited activation strength (Nunez, 1990
; Opitz et al., 1999
). Conversely, neural activity as reflected in the ERPs might not have a detectable hemodynamic counterpart. Considering the amount of experimental variance unexplained by the generator model, one can approximately estimate the likelihood of such activity; the more variance remains unexplained, the more likely are missing sources. Nevertheless, this approach enables us to describe temporal aspects of neural activation in a distributed network underlying novelty processing.
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Materials and Methods |
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We measured the electrophysiological and hemodynamic brain response in 16 paid healthy volunteers (ages 2028 years, median 22 years, six male). Due to coarse movement artifacts in the fMRI session, two subjects had to be excluded from all analyses.
Stimuli
The stimuli used in this study were pure sine tones and unique environmental sounds. The frequencies of the pure tones were 600 and 1000 Hz. The environmental sounds (hereafter referred to as novels) were the same as used previously by Mecklinger et al. (Mecklinger et al., 1997). Novel sounds were divided into two groups: identifiable novel sounds, which were reliably identified by subjects, and non-identiflable novels, which were not. This separation was based on a pilot study in which 15 subjects that did not participate in the main experiment were asked (i) to write down the first word that came to mind after hearing the sound, and (ii) to indicate how certain they were about their judgment on a four-point rating scale ranging from very uncertain (0) to very certain (3). Based on this rating the two groups of 50 novels each were selected out of 165 novel sounds. The confidence ratings were 1.98 for identifiable and 0.34 for non-identifiable novels. All stimuli had a duration of 200 ms (including 10 ms rise and 40 ms fall time) and were matched for mean intensity (85 dB/SPL). The stimuli were delivered to the subjects using speakers (EEG-session) or non-magnetic air-conducting headphones (fMRI session).
Procedure
The experiment included separate EEG and fMRI sessions 4 weeks apart, each of which consisted of two tasks: a two-tone auditory oddball task and a novelty oddball task. In the two-tone oddball task subjects were presented with series of low and high tones. Following the two-tone oddball task both sessions continued with the novelty oddball task, including low and high tones as well as novel auditory stimuli. The present report focuses on the novelty oddball task as the results of the two-tone oddball task were reported elsewhere (Opitz et al.,1999).
In order to guarantee an optimal comparison of fMRI and ERP data, stimuli were grouped in a blocked design with three block types: standard, deviant and novel blocks. Standard blocks comprised 24 low tones (standard tones) while deviant blocks comprised 16 low-frequency standards and 8 high-frequency, deviant tones. Each novel block contained 16 low tones and 8 novel sounds. The interstimulus interval (1S1) from offset to onset was 550 ms. A complete experimental run consisted of 24 blocks, including 12 standard, 6 deviant and 6 novel blocks, yielding a probability of a deviant tone or a novel sound of 0.083 across all 24 blocks. Standard, deviant and novel blocks alternated in a fixed order, as shown in Figure 1. To control for attentional aspects of deviancy and novelty processing in each session there were two separate runs of 24 blocks each. During the first run, subjects were instructed to watch carefully a silent cartoon video (unattend condition), which was not timelocked to the auditory stimulation, whereas during a second run they had to fixate the center of the black screen and silently count the high tones designated as task relevant targets (attend condition). Subjects were not informed that the novel stimuli would be presented, and if they asked, they were reminded to respond only to the target tones. The order of experimental runs was constant across subjects, with the unattend condition being performed before the attend condition.
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Imaging was performed at 3 T on a Bruker Medspec 30/100 system. The standard birdcage head coil was used. Subjects were supine on the scanner bed, with cushions used to reduce head motion. For each subject high-resolution, whole-brain images were acquired, to assist localization of activation foci using a T1-weighted three-dimensional segmented MDEFT (128 slice sagittal, 1.5 mm thickness, 256 x 256 pixel matrix). To align the echo planar functional images to the three-dimensional images conventional anatomical images in plane with the functional images were acquired as an intermediate step using an IR-RARE sequence (TE = 20 ms, TR = 3750 ms, matrix 512 x 512). Finally, functional images were acquired using a gradient EPI sequence (TE = 40 ms) sensitive to BOLD contrast. Data were collected from seven axial slices, parallel to the ACPC line at a rate of 2 s/image. Slice thickness was 6 mm and interslice distance was 2 mm. The field of view (FOV) was 250 mm with a matrix of 128 x 64.
fMRI data were processed using the BRIAN software package (Kruggel and Lohmann, 1996). Prior to any statistical analyses movement artifacts were detected by thresholding the ratio of foreground (brain) and background intensity for each timestep. Timesteps at which this ratio was <12.5 were classified as artifacts (Kruggel et al., 1998
). Markov random fields (Chalmond, 1988
; Kruggel et al., 1998
) were used for signal restoration in spatial and temporal domain. For each subject voxel-wise Pearson correlations of fMRI time series with a box car reference waveform were calculated to contrast activation related to the processing of both novel events with the standard tones. The box car function resembled the blocked design and was delayed for 4 s to account for delay in the hemodynamic response (Buckner et al., 1998
). The correlation statistics were normalized to Z-scores. A significance level threshold [P< 0.05, corrected for multiple spatial comparisons (Friston et al., 1994
)] was used to determine the presence of significant activation foci. Activation maps were registered with individual high-resolution three-dimensional datasets and transformed into stereotactic Talairach space (Friston et al., 1995
; Kruggel, 1995
). Multisubject averaging was used to enhance the signal-to-noise ratio.
For each subject clusters of activation of interest were determined by identifying all contiguous voxels within a distance of 15 mm from the center of the averaged activation that reached the significance level. The mean value of the number of activated voxels of these clusters across the two hemispheres was calculated for each individual subject separately for identifiable and non-identifiable novels and subjected to a Wilcoxon signed-rank test to assess significant overall differences in brain activation between both novel types. In a second analysis, the leftright difference of the number of activated voxels was estimated for either novel type and subjected to a Wilcoxon test to evaluate novel type-specific lateralization of brain activity.
EEG Recordings
EEGs and EOGs were recorded continuously with a bandpass filter of 0.170 Hz and were digitized at a rate of 250 Hz. EEGs were recorded from 128 electrode sites using an Electrocap. Vertical and horizontal EOGs were recorded from three electrode pairs placed on the infraand supraorbital ridges of the left and the right eye and the outer canthi of the two eyes. All leads were referenced to nosetip. Electrode impedance was kept <2 k. ERP data were epoched off-line for a 1000 ms period (including a 200 ms prestimulus baseline). Prior to averaging, epochs were scanned for eye movement and other artifacts. Whenever the standard deviation in a 200 ms interval exceeded 40 µV an epoch was excluded from averaging. ERPs were computed separately for standards, deviants and both groups of novel sounds. For analogous comparison with fMRI data, only difference waveforms were analyzed. These difference waveforms were derived by subtracting the standard from the deviant or novel ERPs separately for both conditions*. The latency of ERP components was measured relative to stimulus onset.
For statistical analyses the ERPs to novel stimuli were quantified as mean voltages in an early (320360 ms) and late (400440 ms) time interval. To minimize type I error due to a large number of statistical tests of multi-electrode and multi-time window data, analyses were carried out for topographical regions (Oken and Chiappa, 1986). Six regions, comprised of six electrodes each, were defined over left, medial and right frontocentral and parietal scalp sites where the ERP effects of interest were largest. Repeated-measure ANOVAs were used to compare the ERPs to both novel types in the attend and the unattend condition. Factors were novel type (two levels), region (six levels) and time interval (two levels). HuynhFeldt correction was used where appropriate. Uncorrected degrees of freedom and corrected P-values are reported in the Results.
Dipole Modeling
In order to assess temporal aspects of the processing network identified in fMRI activation maps a neuroanatomically constrained source analysis was utilized. For source localization purposes realistically shaped head models were developed using the boundary element method (BEM). Three compartments of the head were taken into account: the brain (including cerebrospinal fluid), skull and scalp (Cuffin, 1990). The conductivities were set to 0.33 S/m for the brain and the scalp and 0.0042 S/m for the skull. The head model was derived from 50 averaged, Talairach normalized MRIs, stored in a local brain database.
All estimations related to fMRI or EEG measurements were carried out in the reversed head system (Wieringa, 1993). The y-axis runs through the preauricular points from right to left and the x-axis runs perpendicular to the y-axis towards the nasion. The z-axis points to the vertex. On the MRI the nasion and both preauricular points were identified. Thus the MRI could be transformed to the head system using these markers.
Dipole locations were kept fixed according to the fMRI activation foci averaged across subjects. Orientations of dipoles were fitted with the ASA software (ANT Software BV, Hengelo, The Netherlands) using the average reference ERP data. The obtained model was subjected to further evaluation. First, explained variances were determined to assess the goodness of fit. Second, we evaluated whether the fitted dipole parameters, orientation and strength fulfill neuroanatomical and electro-physiological constraints, i.e. best-fitting dipole orientations were expected to be perpendicular to local cortical gray matter and the dipole strength should be in accordance with the characteristics of neural currents (Freeman, 1975; Nunez, 1990
). Finally, the specificity of the dipole model to a particular ERP component was estimated by keeping dipole location and orientations fixed and calculating the time course of dipole strength and goodness of fit over the period from 100 ms before to 600 ms after stimulus onset.
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Results |
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Unattend Condition
Figure 2 shows the ERP waveforms averaged across 14 subjects in the unattend condition. Deviant stimuli evoked a mismatch negativity (MMN), i.e. an enhanced negativity at frontal electrode sites, with polarity reversal at mastoid sites (Näätänen et al., 1978
). Using a repeated-measure ANOVA with the two-level factor stimulus type this observation was confirmed by significant differences between deviants and standards in the 120160 ms time interval at Fz [1.82 µV, F (1,13) = 8.25, P< 0.001) and mastoid recording sites (1.39 µV, F(1,13) = 9.75, P < 0.001). No further systematic differences between standards and deviants were obtained.
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Attend Condition
Task performance was high across subjects, with a mean error rate of 2.1%. In this condition, the deviants evoked a frontally focused MMN complex. Contrasts between standards and deviants yielded larger negative defiections at Fz for deviants than for standards [2.42 µV, F(1,13) = 5.54, P< 0.001]. As revealed by an ANOVA contrasting the mean voltages between 120 and 160 ms in both conditions (unattend versus attend) the attention manipulation did not affect the MMN component [F(1,13) = 0.90, P > 0.36]. The subsequent P3b component to deviants showed a parietal maximum with a peak latency of 364 ms (at Pz electrode, Fig. 3).
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To summarize the ERP results, both novel types (identifiable and non-identifiable) elicited a frontocentrally distributed novel P3 in both the attend and the unattend condition. There was a significant effect of attention on the amplitude of the novel P3, with the novel P3 being larger in the attend condition. Only in this condition did the ERPs to both novel types differ. At frontal recording sites the non-identifiable novels evoked larger novel P3s, whereas at posterior electrodes a parietal P3 effect for non-identifiable novels and a subsequent N4-like effect for identifiable novels were obtained.
fMRI
Unattend Condition
The statistical parametric maps, representing the BOLD response to both novel stimuli in the unattend condition, revealed two significant clusters of activity in the left and right superior temporal gyri (STG) (see Table 1 and Fig. 4
). A Wilcoxon signed-rank test at an
-level of 0.05 did not reveal any significant differences in fMRI activation between identifiable and non-identifiable novels (Wilcoxon t = 0.30), nor was there a significant difference in lateralization between the two novel types (Wilcoxon t = 0.66, P > 0.51).
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In this condition the fMRI activation pattern again was comprised of two significant clusters of activity in the left and right STG (see Table 2 for Talairach coordinates), which were almost identical in size and location to those obtained in the unattend condition. As in the unattend condition, a Wilcoxon signed-rank test at an
-level of 0.05 did not reveal any significant differences in mean fMRI activation size between identifiable and nonidentifiable novels (Wilcoxon t = 0.34). Furthermore, no specific lateralization could be obtained for either novel type (Wilcoxon t = 1.09, P > 0.27).
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When the fMRI data analysis was conducted separately for the LD-and SD-groups, the activation pattern for identifiable and non-identifiable novels was clearly dissociable for the LD-group, but not for the SD-group (Fig. 6).
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Based on these results it can be hypothesized that (i) bilateral activation of the middle STG accounts for the generation of the novel P3, whereas (ii) an additional right frontal generator might contribute solely to the ERP waveforms for identifiable novels. To test these hypotheses we modeled the scalp ERP distribution of the LD-group, for which reliable ERP differences between both novel types were obtained, using dipole source locations in both STGs as derived from functional images. The obtained best-fitting orientations for the identifiable novels were superimposed on an averaged MRI (Fig. 7). As is apparent from the figure, the modeled dipole orientations were almost perpendicular to the gray matter.
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Discussion |
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By contrasting novel and standard blocks in the fMRI session a bilateral increased hemodynamic response in the middle part of the superior temporal gyrus was obtained for both novel types, demonstrating the involvement of this brain region in novelty processing.
At this point it remains unclear how and to what extent the ERP and fMRI findings obtained in the present study overlap. Combining ERP and fMRI results by means of neuroanatomically constrained inverse modeling suggested that the middle part of the STG substantially contribute to the generation of the novel P3. The sources of the novel P3 are located more anterior in the STG as compared with the sources of the auditory target P3 reported in a previous study (Opitz et al., 1999). This could account for the distinctive scalp distribution of the novel P3. Consistent with this result, a contribution of anterior temporal cortex activity to the novel P3 has been observed in a MEG study (Alho et al., 1998
). Further evidence for temporal cortex contribution to the anterior P3 is also provided by intracranial recordings (Alain et al., 1989
; Halgren et al., 1995a
,b
). Moreover, extensive temporo-parietal lesions centered in the superior temporal cortex attenuated the P3 to novel sounds especially at posterior recordings (Knight et al., 1989
).
Despite this converging evidence for a STG contribution to novelty processing there is a lack of consistency with respect to hippocampal involvement in these processes. Human lesion studies (Knight, 1996) as well as intracranial recordings (Halgren et al., 1995b
) have suggested an important role of the hippocampal/parahippocampal region in the processing of novel information. The patients investigated by Knight (Knight, 1996
) showed heterogeneous hippocampal/parahippocampal lesions particularly extending laterally and anteriorly. As indicated in a recent single-neuron recording study in rhesus monkeys, the inferior temporal cortex appears to be critically involved in novelty processing (Miller et al., 1991
) and therefore might contribute to Knight's findings (Knight, 1996
). Our data, however, did not reveal significant activation within or in the vicinity of this region. Other studies also failed to demonstrate hippocampal activity in similar task situations (Shallice et al., 1994
; Tulving et al., 1994
; Buckner et al., 1995
). There are at least two possible explanations for this discrepancy. First, the differences in medial temporal lobe activity between novel and standard blocks simply might have been too low to cause detectable changes in the BOLD response in the present study (Rugg, 1998
). Second, Halgren et al. (Halgren et al., 1995b
), using depth electrode recordings in the medial temporal lobes in epileptic patients, did not find the typical local polarity inversions and assume that these potentials are generated in cortical regions of the superior temporal lobes, an argument compatible with our findings.
There may be some limitations of the utility of the fMRI data to constrain ERP source localization in the present study, as not all brain structures described in earlier studies to be critically involved in novelty processing could be imaged due to the limited slice nuinber. But the high amount of explained variances (>90%) in the novel P3 time interval suggested that the midportion of the superior temporal gyri are the major contributors to novelty detection processes, reflected in the novel P3.
Those subjects that showed an enhanced N4-response to identifiable novels in the ERP also yielded increased hemodynamic activity to these sounds in the right prefrontal cortex (rPFC). The involvement of prefrontal cortex in novelty processing was suggested by a SPECT study demonstrating a correlation of novel P3 amplitude and blood flow in the anterior cingulate cortex (Ebmeier et al., 1995). Further evidence for the involvement of PFC in novelty processing was provided by neuropsychological studies showing a decreased ERP response to auditory and visual novel stimuli after unilateral prefrontal lesions including fiber pathways from dorsolateral as well as medial prefrontal regions (Knight, 1984
, 1997
). However, the lack of selective amplitude reduction of the novel P3 over the lesioned hemisphere led Knight (Knight, 1984
) to conclude that the prefrontal cortex is not the primary generator of these brain potentials but rather modulates generators located elsewhere, e.g. in the superior temporal cortex. In patients with lesions centered in the temporal plane a selectively reduced novel P3 over the hemisphere ipsilateral to the lesion was observed, indicating a direct contribution of these brain structures to the novel P3 (Knight, 1997
). Another line of evidence for the notion that the prefrontal cortex might act as an attentional control system was added by a recent study that compared the novel P3 in young and old adults (Friedman et al., 1998
). They examined the novel P3 in an attend and an ignore condition and found a reduced novel P3 for old as compared to young adults in the attend condition, but identical novel P3 for young and old adults in the ignore condition. This finding may also be taken to suggest that prefrontal activity during an attended novelty oddball task more likely reflects attentional modulations rather than a true generator of the scalp recorded novel P3. Under the assumption that such an attention modulating function of the prefrontal cortex is also engaged in the present study it might have been similarly involved in standard and novel blocks and thus not been observable in the present fMRI comparisons. This similarly high involvement of attentional processes in the two blocks may be caused by the high auditory background noise produced by the scanner. Moreover, unlike the present study, other studies only used one or a restricted set of novel stimuli, thus limiting the examination space of conceptual-semantic aspects of novelty processing. Furthermore, as none of these studies reported a specific lateralization of frontal lobe involvement in novelty processing, processes other than novelty detection seem to be reflected in lateralized PFC activity in general, and in the rPFC found in the present study in particular.
The results of the combined analyses suggest that the rPFC is activated only for those novel events for which a semantic concept can be activated and that this activation is delayed relative to processes underlying novelty detection. In previous functional imaging studies rPFC activation of similar kind has been found when previously learned materials had to be retrieved from episodic memory relative to a comparable reference task [For an overview see Nyberg et al. (Nyberg et al., 1996)]. These studies have led to the idea that the PFC, especially in the right hemisphere, is engaged in either post-retrieval monitoring (Rugg et al., 1996
) or in maintaining a retrieval set (Nyberg et al., 1995
). Similar suggestions have been made based on ERP recordings that showed a late developing sustained positive slow wave with a right frontal topography that is related to post-retrieval control processes (Wilding and Rugg, 1996
; Mecklinger and Meinshausen, 1998
). Based on these findings it is conceivable that accessing and retrieving a sound's meaning is associated with some sort of post-retrieval processing or with the activation of a retrieval set, and that these latter processes are mediated by the rPFC [similar arguments are given by Moscovitch (Moscovitch, 1992
) and Fletcher et al. (Fletcher et al., 1997
)]. Conversely, recent brain imaging studies have suggested that the PFC plays an important role for the encoding of verbal and non-verbal memories with a left dominant activation for the verbal domain (Wagner et al., 1998
) and a right dominant activation for the non-verbal domain (Brewer et al., 1998
). In the latter study the magnitude of focal rPFC activation during the encoding of complex figures was predictive for the subsequent memory for these pictures. Thus, the rPFC activation might reflect more efficient encoding of semantically identified novel sounds. The absence of left PFC activation found for lexical-semantic processes may be related to the acousticconceptual rather than language-related character of the present stimuli. The notion that the rPFC activity reflects the efficiency of encoding operations is also consistent with the novelty/ encoding hypothesis (Tulving et al., 1996
) that claims that temporal regions provide the input for frontal encoding networks.
The data presented, together with those of previous studies, point to differential brain activation networks for identifiable and non-identifiable novel sounds. From the combined analyses of ERP and fMRI data we, moreover, conclude that novelty processing consists of at least two sequential subprocesses: first an automatically operating novelty detection mechanism, subserved by cortical neural networks including the superior temporal gyrus, and second, further processes based on a novel sound's meaning, subserved by right frontal cortical areas. The precise nature of the psychological process reflected in this rPFC activation remains to be elucidated. Nevertheless our data indicate that rather different neuronal networks are active depending on the proportion of conceptual semantic and generic novel information carried by a stimulus.
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Notes |
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Address correspondence to B. Opitz, Max-Planck-Institute of Cognitive Neuroscience, PO Box 500 355, D-04303 Leipzig, Germany. E-mail: opitz{at}cns.mpg.de.
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Footnotes |
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References |
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