Brain Topography, Volume 11, Number 1, 1998
33
L eft Frontal EEGCoherence Reflects Modality Independent Language Processes Sabine Weiss*+ and Peter Rappelsberger* Summary: Previous studies showed that distinct components of higher cognitive processes like memorizing of words could be correlated with changes in different frequency bands of the human EEG. This study was designed in order to find out if 1) some frequency bands show power and coherence changes only due to the modality of presented stimuli (either auditory or visual) and 2) if other frequency bands show modality independent effects which should reflect real cognitive-linguistic differences between word classes (either concrete and abstract nouns). EEG was recorded from sixteen right-handed females which had to memorize auditorily and visually presented concrete and abstract nouns. Results show the alpha-1 band to reveal no differences between word classes but demonstrate an influence of modality of stimulus presentation. The only modality independent differences between concrete and abstract noun processing were found in the delta, theta and beta-1 band at left frontal electrodes. Key words: EEG coherence; Auditory; Visual; Concrete; Abstract; Language.
Introduction During human language processing numerous distributed cortical and subcortical neuronal systems are activated (Binder et al. 1997) which have to co-operate and according to task demand act as a single functional subcomponent. One possible mechanism of binding together these distributed systems in the brain is the temporal synchronization of the participating substrates. Recent neurobiological findings revealed by extensive studies of the visual cortex in cats and monkeys showed that neurons which are likely to perform a certain task synchronize their discharges whereas neurons which are engaged in another task do not (Eckhorn et al. 1988; Gray et al. 1989; Singer 1994). This local synchronization of Cell Assemblies can influence a global synchronization over large cortical distances, which is most effectively achieved if neurons oscillate within a narrow frequency band (Bressler 1990; Basar-Eroglu et al. 1996). * Institute of Neurophysiology, University of Vienna, Vienna, Austria. +Experimental Neurolinguistics Group, Faculty of Linguistics, University of Bielefeld, Bielefeld, Germany. Accepted for publication: June 23,1998. Supported by the FWF (Proj. P11572-MED) and the "Hochschuljubilaumsstiftung der Stadt Wien" (Proj. H-00195/95). Correspondence and reprint requests should be addressed to Dr. Sabine Weiss, Institute of Neurophysiology, University of Vienna, Waehringerstrasse 17,1090 Vienna, Austria. Fax: +43-1-4028525 e-mail:
[email protected] Copyright © 1998, Human Sciences Press, Inc.
The neurobiological mechanism mentioned above seems to be equally important for higher brain functions, like language processes. As a consequence, knowledge about activities within certain frequency bands as well as information about cortical synchronization or co-operation, respectively, seems to be necessary for an adequate characterization of brain functioning during language processing. Hence, spectral analysis of the EEG, especially the computation of coherence between EEG signals, seems to be a suitable method for the analysis of such a complex cognitive skill like language processing (Petsche et al. 1993; Weiss and Rappelsberger 1996). During such a high developed cognitive skill like language processing one may assume increasing and decreasing synchronization of distributed neuronal systems over large cortical distances to play an important role. Moreover, spectral analysis provides information about the roles of different frequencies of the human EEG which are likely to reflect different components of information processing (Klimesch 1996; Basar et al. 1994; Weiss and Rappelsberger 1996). In contrast to EEG power changes at a single electrode which exhibit more local changes in electric activity of underlying neuronal networks, coherence changes reflect large scale synchronization and desynchronization. Thus coherence analyses yield important new aspects of brain activities during language processing which complement the data obtained by power spectral analyses (Pulvermuller 1997). In mathematical terms, coherence between two EEG signals is the correlation coefficient in the frequency do-
34
main and can be interpreted as a measure for the functional co-operation or information transfer between the underlying generators of these EEG signals. If coherence is high between the EEG signals of two electrodes positioned on the scalp, there is an increased functional interplay between the neuronal networks generating those signals. If coherence is low the functional interplay between them is low. In previous experiments we calculated EEG coherence to study human word processing and used concrete and abstract nouns as stimuli to address the question if EEG coherence reflects the cognitive-linguistic difference between these word classes (Weiss 1994; Weiss and Rappelsberger 1996). From a linguistic point of view concrete nouns are characterised by high reference to things and high intension (meaning). They represent individual entities of the world with constant features, which can be referred to in the three-dimensional space. In contrast, abstract nouns have no spatio-temporal concreteness and their individuality is low (Ewald 1992; Vogel 1996). The lexeme "rabbit", for instance, refers to an object that can be seen, heard, smelled, felt or tasted whereas the lexeme "truth" cannot be experienced through our senses and is represented mainly verbally within our brain. As a consequence, the representation of abstract nouns may be more difficult to access and the processing of abstract nouns should be easier to disturb (Hinton and Shallice 1991). Furthermore, various neuropsychological studies showed that certain patients have a selective difficulty to process abstract nouns whereas they still are able to cope with concrete nouns (Warrington and Shallice 1984; Coltheart 1987; Tyler et al. 1995). Processing differences for both patients and healthy subjects have not only been demonstrated for nouns but also for grammatical word classes such as nouns and verbs (Hillis and Caramazza 1995; Weiss et al. 1997b), for proper names compared with common nouns (Muller and Kutas 1996) and even for distinct categories of concrete nouns, e.g., "animals" and "tools" (Damasio et al. 1996; Tranel et al. 1997). Different concrete and abstract noun processing can also be observed within normal participants, which show a remarkable concreteness effect while processing nouns (Bleasdale 1987; Eviatar et al. 1990). This effect can be explained by two facts, namely by the high individuality and the multimodal representation of concrete nouns. Based on these findings, in a previous study we postulated different patterns of EEG coherences for the processing of concrete and abstract nouns (Weiss and Rappelsberger 1996). We hypothesized that due to the multimodal nature of the concrete nouns more distributed brain areas should cooperate and should be functionally synchronized. Therefore a higher number of coherences should be observed during concrete noun
Welss and Rappelsberger
processing than during abstract noun processing. We found a higher number of coherences between distributed brain regions for auditorily presented concrete nouns compared with abstract nouns in the beta-1 frequency band but we did not find any differences in the alpha-1 band. Therefore we hypothesized that the alpha1 band reflects processes which are common to both word classes, for instance the modality of stimulus presentation. If the beta-1 band reflects a real cognitive-linguistic difference between concrete and abstract nouns this difference would occur independently of the modality of presentation and regardless of the kind of task the participants are engaged in. Consequently in the present paper we designed a new experiment where we presented concrete and abstract nouns in the auditory as well as in the visual modality and participants had to memorize them. The purpose of this study was to examine the question if the alpha-1 band reflects the modality of stimulus presentation and would differentiate between the auditory and the visual modality. Furthermore, we wanted to study which additional frequency bands beside the beta-1 band would reflect real cognitive-linguistic differences between the memorizing of concrete and abstract nouns independent of the modality of stimulus presentation.
Methods Participants Sixteen right-handed females (23.4 ±2.9 years), native speakers of German and not bilingually educated participated in the experiment. Stimuli 150 disyllabic German nouns were selected and equated for frequency of occurrence. Nouns were ranked on a 12-point scale based on a corpus of about 10 million words (Meier 1967). Concrete nouns showed an average of 6.49 + 2.80, abstract nouns 4.61 ± 1.73. T-tests yielded no significant word frequency difference between abstract and concrete nouns. Furthermore, words were matched on imageability and concrete-/abstractness. 70 words were matched due to studies of Baschek et al. (1977) and Offe et al. (1981). On a bipolar scale (-20 < 0 < + 20) the score for the concrete nouns was 16.54 ± 0.75 for imagery and 16.20 ± 2.41 for concrete-/abstractness. The abstract nouns showed -3.18 ± 4.22 for imagery and-4.76 ±4.38 for concrete-/abstractness. The remaining 80 words were matched based on a study of Mitterdorfer (1976). On a 7-point rating scale the concrete nouns had a score of 6.77± 0.11 for imagery and 6.92 ± 0.07 for concrete-/abstractness, the abstract nouns
Modality Independent EEG Coherence
2.30 ± 0.40 for imagery and 1.92 ± 0.46 for concrete-/abstractness. The reason why different studies and scales, respectively had been used to match the 150 words for imageability and concrete/abstractness was that none of the studies provided enough disyllabic german nouns to suffice the demands of our EEG study. Finally, 75 highly concrete and 75 highly abstract nouns were presented to the participants. Both samples of concrete and abstract nouns, respectively, used in this study differed significantly for the variables "imagery" and "concrete-/ abstractness" (t-test, 2p < 0.0001). It is important to note that the nouns presented in the auditory or visual modality were different and hence the effects of word repetition was excluded (Rugg et al. 1994). Experimental design and general procedure Participants were seated in a dimly lit, sound-reduced room. During listening to words and during the resting periods they fixed their eyes on a black point on a computer monitor. a) Auditory condition: 50 concrete and 50 abstract nouns, spoken by a female voice and digitized at 22 KHz were presented via computer, HiFi-amplifier and headphones. They had a mean articulatory duration of 0.76 ± 0.12 s. Concrete and abstract words were grouped separately into four blocks of 25 words each. The four blocks were presented in random order across the experiment, words within one block were also randomly presented with a stimulus onset asynchrony of 2.5 s. b) Visual condition: Another two blocks of 25 concrete and 25 abstract stimuli were presented visually. These blocks were also randomly presented across the experiment. Stimuli were black upper-case letters on a light gray background displayed on the center of a 15" monitor and subtended a visual angle of 1.4 degrees horizontally and 0.3 degrees vertically. Words were presented for 500 ms with a randomized stimulus onset asynchrony of 2 to 3 s. Participants were requested to memorize the auditorily and visually presented nouns and had to recall them after the presentation of each block. EEG recording and analysis EEG was recorded with 19 electrodes according to the 10/20 system against averaged signals of both earlobes (Essl and Rappelsberger 1998) and digitized at 256 Hz (TC 0.3 s, filter 35 Hz). Artifacts were eliminated after visual analysis of the raw EEG, an additional computer analysis and the visual inspection of the power spectra. EEG was recorded during memorizing the six different blocks of nouns and during four resting periods with eyes opened (EEGr) lasting one minute each. The beginning of each noun was marked by a trigger and the following 1 s EEG epochs were selected for Fourier trans-
35
form. All one second artifact-free epochs of the EEGr were also Fourier transformed. According to the nineteen electrode positions 19 averaged power spectra and 30 intrahemispheric and 8 interhemispheric cross-power spectra between homologous electrode sites for each condition were computed. The 30 intrahemispheric crosspower spectra were calculated between adjacent electrodes of the longitudinal and transversal electrode rows including the midline electrodes. Broad band parameters were obtained by averaging adjacent spectral lines for the following frequency bands: delta (1-4 Hz), theta (5-7 Hz), alpha-1 (8-10 Hz), alpha-2 (11-12 Hz), beta-1 (13-18 Hz) and beta-2 (19-31 Hz). Finally, 19 mean amplitudes (square root of power) per frequency band were computed and the normalization of the 38 crosspower spectra yielded coherence per frequency band. Amplitude, intra- and interhemispheric coherence values were obtained for 1) auditory concrete nouns, 2) visual concrete nouns, 3) auditory abstract nouns, 4) visual abstract nouns and 5) the resting EEG (EEGr). For the evaluation of significant amplitude, intraand interhemispheric coherence differences between selected conditions, paired Wilcoxon-tests (two-tailed) were applied and the resulting error probabilities were presented in topographic maps. However, due to the numerous parallel comparisons the statistical results can be used only for exploration and description i.e., give hints at the potential difference existing over the many comparisons but cannot be used to reject or accept the null hypotheses (further methodological details see Rappelsberger and Petsche 1988).
Results Behavioral data Within the auditory condition, on average 36% of concrete nouns and 22% of abstract nouns were recalled per block of 25 words. Within the visual condition 35% of the concrete nouns and 22% of the abstract nouns were recalled. No significant recalling difference was found between auditorily and visually presented nouns. Recalling of concrete nouns was significantly better than recalling of abstract nouns (paired t-test, 2p < 0.0001). EEG data Modality specific effects In order to confirm according to previous hypotheses (Weiss and Rappelsberger 1996) whether the alpha-1 band plays an essential role concerning the distinction of the modality of stimulus presentation, comparisons of EEG parameters between memorizing of concrete and abstract
36
Weiss and Rappelsberger
Figure 1. Spectraiparameter maps of the alpha-1 band (8-10 Hz) demonstrating differences between word processing, either concrete or abstract nouns, and the EEG at rest (EEGr). The respective three columns relate to amplitude-, intrahemispheric- and interhemispheric differences. Red color means higher amplitude or coherence during word processing compared to the EEGr, blue color indicates the opposite.
nouns compared with the parameters during EEG at rest (EEGr) were made for both the auditory and visual modality. Amplitude and intra- and interhemispheric coherence differences between the memorization of concrete and abstract nouns compared with the EEGr are presented in colored spectralparameter maps (figure 1). In comparison with the EEGr during memorizing of auditorily presented nouns amplitudes decreased at T3 and T4 for both the concrete and the abstract nouns. All other electrodes showed amplitude increase. In contrast, during the visual condition only amplitude decrease was found, especially at posterior electrodes. During the auditory condition intrahemispheric coherence mainly increased between frontal electrodes and between temporal and central sites for both the concrete and abstract nouns (figure 1). Interhemispheric coherences increased mainly frontally and centrally. As for the visual condition intrahemispheric coherences increased mainly between temporal and central electrodes and decreased between frontal electrodes and between posterior sites. Interhemispheric coherence increased between central and occipital electrodes. A clear amplitude and coherence difference between the auditory and the visual modality was shown for the alpha-1 band but no significant differences between concrete and abstract noun processing were found within
this band (see also figure 3 for statistical results). One explanation concerning the different amplitude findings for the auditory and the visual condition may be found by the visual inspection of the raw EEG (figure 2). An alpha-1 amplitude decrease or desynchronization, respectively could be observed in the spontaneous EEG almost at the very moment or shortly after a word was visually presented (figure 2, lower part). During spoken word processing a delayed alpha desynchronization (figure 2, upper part) could be observed. We found these different alpha desynchronization patterns reliably within the EEG of 62.5% of the participants of this study. In a next step a direct comparison between the EEG coherence of concrete and abstract nouns was made for both the auditory and the visual modality for all frequency bands (figure 3). Paired Wilcoxon-tests (twotailed) were calculated between concrete and abstract nouns and the error probabilities of significant differences were mapped on schematic head models. Significant intra-and interhemispheric coherence differences between the memorization of concrete and abstract nouns for both the auditory and the visual modality were found (figure 3). Within the auditory modality significant higher coherence during processing of concrete compared with abstract nouns was found in the delta, theta and beta-1
Modallty Independent EEG Coherence
37
Figure 2. Band-pass filtered EEG (8 to 10 Hz) of a single participant during auditory and visual presentation of words. Vertical lines indicate the beginning of each word, horizontal bars represent the length of the auditory and visual stimulus presentation. Icons symbolize either the auditory or visual mode of stimulus presentation. During the visual condition alpha-1 desynchronization occurs almost at stimulus onset or shortly after, during the auditory condition in most cases alpha-1 desynchronization occurs with great delay.
band. Most of the intrahemispheric coherence differences were found at left- and right frontal electrodes.
Interhemispheric differences were found mainly between frontal and temporal electrodes. Within the visual
Weiss and Rappelsberger
38
Figure 3. Error probability maps of significant intra- and interhemispheric coherence differences between memorizing of concrete and abstract nouns. Intra hemispheric coherence differences are plotted as squares between the corresponding electrode sites, interhemispheric coherence is plotted as squares at homologous sites of both hemispheres connected by a line. Full squares indicate significant higher intra- and interhemispheric coherence for concrete noun processing empty squares indicate higher coherence for abstract noun processing.
modality additional higher coherence was found in the alpha-2 and the beta-2 band. Those differences were mainly between left hemispheric frontal electrodes. Additionally, significant lower intrahemispheric coherence during concrete word processing was found between some positions and in four frequency bands. In contrast to visual presentation during the auditory modality no significant differences were observed in the alpha-2 and the beta-2 band. In the alpha-1 band both modalities demonstrated no significant differences between concrete and abstract noun processing except between F1-F2 during visual presentation.
Modality independent effects Figure 3 demonstrates various significant coherence differences between concrete and abstract noun processing which differ dependent on the modality of stimulus presentation. The only modality independent differences between abstract and concrete noun processing were reflected by coherence within the delta, theta and beta-1 band (figure 4). As the essential result figure 4 shows all significant EEG coherence differences between concrete and abstract nouns found for both the auditory and the visual modality. Differences were found between left frontal elec-
Modallty Independent EEG Coherence
39
band is the only frequency band that differs between the auditory and visual modality of stimulus presentation but not between concrete and abstract nouns; 2) all other frequency bands show modality specific EEG differences between concrete and abstract nouns and 3) the delta, theta and beta-1 bands demonstrate left frontal EEG properties independent of the modality of stimulus presentation. Modality specific effects
Figure 4. Modality independent coherence differences between concrete and abstract nouns. Memorizing of concrete nouns induces significant higher coherence at left frontal electrodes for both the auditory and visual modality (* 2p < .05, ** 2p < .01).
trodes with significant higher coherence for concrete noun processing. Significant coherence differences in delta were found between F1-F3 and F3-F4, in theta between F7-F3 and in beta-1 between F1-F7 and F3-Fz.
Discussion Three main findings were obtained: 1) the alpha-1
The alpha-1 band does not indicate a difference between concrete and abstract noun processing but shows a clear difference between the auditory and visual mode of stimulus presentation. During memorizing of auditorily presented nouns compared to the EEG at rest (EEGr) alpha-1 amplitudes decrease at left and right temporal electrodes. This desynchronization of alpha-1 amplitude can be correlated with an increase of activity in underlying brain regions during auditory processing. In contrast, at all other electrodes prominent amplitude increase is shown. During memorizing of visually presented nouns all electrodes show alpha-1 desynchronization, mostly pronounced in posterior regions engaged in visual processing. Alpha desynchronization or blocking indicates an increase of neuronal activity (e.g., Pfurtschelleretal. 1996). Blocking could be observed in the spontaneous EEG almost at the very moment or shortly after a word was visually presented (figure 2). This desynchronization can be correlated with the perceptual processing of the visual stimulus. During spoken word processing alpha desynchronization occurs at temporal electrodes due to auditory information processing. All other electrodes show a delayed alpha desynchronization. The longer articulatory duration of the auditory stimuli may be responsible for the observed differences in the alpha-1 band within the one-second window used for spectral analysis. A possible explanation for the differences in alpha-1 band amplitudes can be given by considering the different time courses of auditory and visual perceptual processing. Auditory perceptual processing and storage of natural language is a sequential process in time and continues during the whole period of a spoken word whereas in the visual modality simultaneously presented items have to be processed as a whole (Penney 1989; Rushkin et al. 1997). Visual word processing is performed relatively quick (around 50-200 ms; e.g., Skrandies 1998) but within this period of time only parts of phonemes are perceived auditorily. Maybe the different time course of auditory and visual perceptual processing leads to the different time course of alpha desynchronization. Hence, this may lead to the modality specific type of alpha desynchronization which could be observed in the spontaneous EEG. An
40
influence of the different length of auditory and visual stimulus presentation can be excluded because within the auditory condition the end of the alpha-1 desynchronization obviously exceeds the average word end whereas during the visual condition the alpha-1 desynchronization occurs far before the word end. If the stimulus length would influence the desynchronization, the alpha-1 desynchronization in the visual condition should at least last till the end of the stimulus or even should exceed the stimulus end. As for coherence memorizing of auditorily and visually presented nouns predominantly leads to different patterns of changes within the alpha-1 band. The auditory modality is correlated with intrahemispheric coherence increase whereas during visual processing coherence decrease is dominating except between central and temporo-central electrodes. Since all participants reported about inner rehearsal during memorizing of the nouns intra- and interhemispheric coherence increase between central and temporo-central electrodes may reflect motor processes necessary for the inner automatic rehearsal of the nouns which should not differ between the modalities. Interhemispheric coherence reveals clear modality specific results. During auditory noun processing both hemispheres show an intensive exchange of information which is indicated by frontal and central coherence increase whereas during visual noun processing interhemispheric coherence mainly increases between posterior regions, indicating hemispheric coupling during visual processing. All of the above mentioned results do not differ significantly between concrete and abstract noun processing within the alpha-1 band. In contrast, the other frequency bands show EEG differences between concrete and abstract nouns whose topography seems to depend on the modality of stimulus presentation. However, concrete nouns tend to show a higher coherence within both modalities. These topographic modality-specific findings support the notion about separate auditory and visual processing streams within verbal memory that have different properties and capabilities and represent information in different ways (Penney 1989; Ruchkin et al. 1997; Gomes et al. 1997). Nevertheless we found coherence differences between concrete and abstract nouns which occur independently of the modality of stimulus presentation and should reflect real cognitive-linguistic differences between these word categories. Modality independent effects A clear modality independent difference between memorizing of concrete and abstract nouns was observed. Concrete nouns show higher coherence compared to abstract nouns for both the auditory and the
Weiss and Rappelsberger
visual modality between left frontal electrodes. These modality independent differences occur only in the frequency bands delta, theta and beta-1 and it can be assumed, that higher coherence for concrete nouns indicates a higher synchronization of neuronal systems within the left frontal cortex in comparison to abstract nouns. This higher synchronization probably reflects encoding and storage strategies which differ for concrete and abstract nouns (Bleasdale 1987; Eviatar et al. 1990). During memorizing of words retrieval of information from the semantic memory and simultaneous encoding of information in the episodic memory occurs. According to Tulving et al. (1994) the left prefrontal cortex is engaged with semantic information processing whereas the right prefrontal cortex is engaged with the retrieval of information from the episodic memory. Activity of the left frontal region, especially the left inferior prefrontal lobe is often correlated with semantic processing of words (Petersen et al. 1988; McCarthy et al. 1993). This modality-independent region is called the left frontal semantic area or frontal lexical semantic area. Abdullaev et al. (1993) reported about a patient with implanted intracortical electrodes who performed a lexical decision task with concrete and abstract nouns. Neurons in the left prefrontal cortex (Brodmann areas 10 and 46) responded only during the presentation of abstract nouns and not during the presentation of concrete nouns. This is another indication for a difference between concrete and abstract noun processing within this left frontal region. During language processing semantic encoding differs for concrete and abstract nouns since concrete material can be categorized and organized more easily because of multiple sources (e.g., imagery) that support the process (Paivio et al. 1968; Christian et al. 1978; Kroll and Merves 1986). It can be speculated that higher EEGsynchronization at left frontal electrodes can be correlated with more elaborate encoding strategies for concrete nouns and therefore an improved storage in comparison with abstract nouns. It has to be considered that one major difference between concrete and abstract nouns is the better recall performance of concrete nouns compared with abstract nouns. A mean recall performance of 35.5% for the concrete nouns and 22% for the abstract nouns has been found in the present study. In the present paper we concentrated on the difference in encoding and storage between concrete and abstract nouns and we did not distinguish between recalled nouns and not recalled ones although an EEG difference between them could be expected (Klimesch et al. 1996b). It may be argued that the left frontal difference between recalled concrete and abstract nouns does not occur between not recalled concrete and abstract nouns. However, previous results indicate that the left frontal coherence difference between con-
Modality Independent EEG Coherence
crete and abstract nouns reflect real cognitive-linguistic encoding differences and not only storage processes (Weiss 1994). In the present study the delta, theta as well as the beta-1 band reflect modality independent coherence differences between concrete and abstract nouns at left frontal electrodes. At present, it cannot be determined if all these frequency bands reflect the same cognitive differences or if they represent different aspects of cognitive differences between concrete and abstract noun processing. Due to findings in literature it maybe speculated that these three frequency bands reflect different cognitive components although all coherence differences were found at left frontal electrodes. Due to Klimesch et al. (1996a) episodic memory processes are shown in the theta band whereas semantic long term memory processes are reflected in the upper alpha band or higher frequencies. The role of the delta band is not clear yet, but there are hints that it reflects global mechanisms like focused attention and attention to internal processing (Harmony et al. 1996) and signal detection (Basar et al. 1994). The alpha-1 band does not show differences between concrete and abstract noun processing but reflects the modality of presentation and probably motor processes which do not differ between the memorization of abstract and concrete nouns. This is in accordance with findings of other studies on auditory word processing (Weiss and Rappelsberger 1996; Weiss et al. 1997b) and sentence processing (Muller et al. 1997). Delta, theta and beta-1 activities show left frontal coherence differences between concrete and abstract noun processing which reflect the different encoding and storage strategies for concrete and abstract verbal material.
References Abdullaev, Y.G. and Bechtereva, N.P. Neuronal correlate of the higher-order semantic code in human prefrontal cortex in language tasks. Int. J. Psychophysiol., 1993,14:167-177. Basar, E., Schumann, M., Basar-Eroglu, C. and Demiralp, T. Theta and delta responses in cognitive event-related potential paradigms and their possible psychophysiological correlates. In: H-J. Heinze, T.F. Miinte and G.R. Mangun (Eds.), Cognitive Electrophysiology. Birkhauser, Boston, 1994: 334-367. Basar-Eroglu, C., Struber, D., Schurmann, M., Stadler, M. and Basar, E. Gamma-band responses in the brain: a short review of psychophysiological correlates and functional significance. Int. J. Psychophysiol., 1996,24:101-112. Baschek, I.-L., Bredenkamp, J., Oehrle, B. and Wippich, W. Bestimmung der Bildhaftigkeit (I), Konkretheit, (C) und der Bedeutungshaltigkeit (m') von 800 Substantiven. Z. Exp. Psychol., 1977,24:353-396. Binder, J.R., Frost, J. A., Hammeke, T. A., Cox, R.W. and Prieto, T. Human brain language areas identified by functional magnetic resonance imaging. J. Neurosci., 1997,17:353-362.
41
Bressler, St.L. The gamma wave: a cortical information carrier? Trends Neurosci., 1990,13:161-162. Bleasdale, F.A. Concreteness-dependent associative priming: seperate lexical organization for concrete and abstract words.J. Exp. Psychol. Learn. Mem. Cogn., 1987,13:582-594. Coltheart, M. Deep dyslexia: A right-hemisphere hypothesis. In: M. Coltheart, K.E. Patterson and J.C. Marshall (Eds.), Deep dyslexia. Routledge and Kegan Paul, London, 1987:326-380. Christian, J., Bickley, W., Tarka, M. and Clayton, K. Measures of free recall of 900 English nouns: Correlations with imagery, concreteness, meaningfulness, and frequency. Mem. Cognit., 1978,6: 379-390. Damasio, H., Grabowski, T.J., Tranel, D., Hichwa, R.D. and Damasio, A.R. A neural basis for lexical retrieval. Nature, 1996,380: 499-505. Demb, J.B., Desmond, J.E., Wagner, A.D., Vaidya, C.J., Glover, G.H. and Gabrieli, J.D.E. Semantic encoding and retrieval in the left inferior prefrontal cortex: a functional MRI study of task difficulty and process specificity. J. Neurosci., 1995, 15:5870-5878. Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M. and Reitboeck, H.J. Coherent oscillations: A mechanism for feature linking in the visual cortex? Biol. Cybernet., 1988,60:121-130. Essl, M. and Rappelsberger, P. EEG coherence and reference signals: experimental results and mathematical explanations. Med. Biol. Eng. Comput, 1998,36:1-8. Eviatar, Z., Menn, L. and Zaidel, E. Concreteness: nouns, verbs, and hemispheres. Cortex, 1990,26: 611-624. Ewald, P. Konkreta versus Abstrakta. Zur semantischen Subklassifikation deutscher Substantive. Sprachwissenschaft, 1992,17: 259-281. Gomes, H., Ritter, W., Tartter, V.C., Vaughan Jr., H.G. and Rosen, J.J. Lexical processing of visually and auditorily presented nouns and verbs: evidence from reaction time and N400 priming data. Cogn. Brain Res., 1997,6:121-134. Gray, C.M., Konig, P., Engel, A.K. and Singer, W. Oszillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature, 1989,338:334-337. Harmony, T., Fernandez, T., Silva, J., Bernal, J., Diaz-Comas, L., Reyes, A., Marosi, E., Rodriguez, M. and Rodriguez, M. EEG delta activity: an indicator of attention to internal processing during performance of mental tasks. Int. J. Psychophysiol., 1996,24:161-171. Hillis, A.E. and Caramazza, A. Representation of grammatical categories of words in the brain. JOCN, 1995,7:396-407. Hinton, G.E. and Shallice, T. Lesioning an attractor network: investigations of acquired dyslexia. Psychol. Rev., 1991,98: 74-95. Klimesch, W. Memory processes, brain oscillations and the EEG synchronization. Int. J. Psychophysiol., 1996,24:61-100. Klimesch, W., Doppelmayr, M., Russegger, H. and Pachinger, T. Theta band power in the human scalp EEG and the encoding of new information. Neuroreport, 1996a, 7:1235-1240. Klimesch, W., Schimke, H., Doppelmayr, M., Ripper, B., Schwaiger, J. and Pfurtscheller, G. Event-related desynchronisation (ERD) and the Dm effect: Does alpha desynchronization during encoding predict later recall
42
performance? Int. J. PsychophysioL, 1996b, 24:47-60. Kroll, J.F. and Merves, J.S. Lexical access for concrete and abstract words.J. Exp. Psychol. Learn. Mem. Cogn., 1986,12: 92-107. McCarthy, G., Blamire, A.M., Rothman, D.L., Gruetter, R. and Shulman, R.G. Echo-planar magnetic resonance imaging studies of frontal cortex activation during word generation in humans. Proc. Natl. Acad. Sci. USA, 1993,90:4952-4956. Meier, H. Deutsche Sprachstatistik, Georg Olms, Hildesheim, 1967. Mitterdorfer, F. Experimented Untersuchungen zum DualCoding-Modell. Thesis, University of Vienna, 1976. Muller, H.M. and Kutas, M. What's in a name? Electrophysiological differences between spoken nouns, proper names, and one's own name. Neuroreport, 1996, 8: 221-225. Muller, H.M., Weiss, S. and Rappelsberger, P. EEG coherence analysis of auditory sentence processing. In: H. Witte, U. Zwiener, B. Schack and A. Doering (Eds.), Quantitative and Topological EEG and MEG Analysis. Druckhaus Mayer, Jena, 1997: 429-431. Offe, H., Anneken, G. and Kessler, E. Normen fur die Konkretheits- und Vorstellbarkeitseinschatzungen von 234 Substantiven. Psychologische Beitrage, 1981,23: 65-85. Paivio, A. and Csapo, K. Concrete image and verbal memory codes. J. Exp. Psychol., 1969, 80: 279-285. Penney, C.G. Modality effects and the structure of short-term verbal memory. Mem. Cognit, 1989,17: 398-422. Petersen, S.P., Fox, P.T., Posner, M.I., Mintun, M. and Raichle, M.E. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature, 1988, 331: 585-589. Petsche, H., Etlinger, S.C. and Filz, O. Brain electrical mechanisms of bilingual speech management: an initial investigation. Electroencephalogr. Clin. Neurophysiol., 1993, 86: 385-394. Pfurtscheller, G., Stancak, A. and Neuper, Ch. Event-related synchronization (ERS) in the alpha band - an electrophysiological correlate of cortical idling: a review. Int. J. Psychophysiol., 1996,24: 39-46. Pulvermuller, F., Birbaumer, N., Lutzenberger, W. and Mohr, B. High-frequency brain activity: its possible role in attention, perception and language processing. Prog. Neurobiol, 1997,52: 427-445. Rappelsberger, P. and Petsche, H. Probability mapping: power and coherence analyses of cognitive processes. Brain Topography, 1988,1: 46-54. Ruchkin, D.S., Berndt, R.S., Johnson Jr, R., Ritter, W., Grafman, J. and Canoune, H.L. Modality-specific processing streams in verbal working memory: evidence from spatio-temporal patterns of brain activity. Cogn. Brain Res., 1997,6:95-113. Rugg, M.D., Doyle, M.C. and Holdstock, J.S. Modulation of
Weiss and Rappelsberger
event-related brain potentials by word repetition: Effects of local context. Psychophysiology, 1994, 31:447-459. Schack, B., Bareshova, E., Grieszbach, G. and Witte, H. Methods of dynamic spectral analysis by self-exciting autoregressive moving average models and their application to analysing biosignals. Med. Biol. Eng. Comput., 1995, 33: 492-498. Singer, W. Coherence as an organizing principle of cortical functions. International Review of Neurobiology, 1994,37: 153-183. Skrandies, W. Evoked potential correlates of semantic meaning - a brain mapping study. Cogn. Brain Res., 1998,6:173-183. Tranel, D., Damasio, H. and Damasio, A.R. A neural basis for the retrieval of conceptual knowledge. Neuropsychologia, 1997,35:1319-1327. Tulving, E., Kapur, S., Craik, F.I.M., Moscovitch, M. and Houle, S. Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. Proc. Natl. Acad. Sci. USA, 1994, 91: 2016-2020. Tyler, L.K., Moss, H.E. and Jennings, F. Abstract word deficits in Aphasia: Evidence from semantic priming. Neuropsychol, 1995,9: 354-363. Vogel, P.M. Wortarten und Wortartenwechsel. Zu Konversion und verwandten Erscheinungen im Deutschen und in anderen Sprachen. De Gruyter, Berlin, 1996. Warrington, E.K. and Shallice, T. Category specific semantic impairments. Brain, 1984,107: 829-854. Weiss, S. EEG als Korrelat mentaler Prozesse: Spektralanalyse des Spontan-EEG in Ruhe und whrend sprachlicher Aufgaben. Thesis, University of Vienna, 1994. Weiss, S. EEG-Koharenz und Sprachverarbeitung: Die funktionelle Verkopplung von Gehirnregionen wahrend der Verarbeitung unterschiedlicher Nomina. In: G. Rickheit (Ed.), Studien zur klinischen Linguistik: Modelle, Methoden, Intervention. Westdeutscher Verlag, Opladen, 1997:125-146. Weiss, S. and Rappelsberger, P. EEG coherence within the 13-18 Hz band as a correlate of a distinct lexical organisation of concrete and abstract nouns in humans. Neurosci. Lett., 1996, 209:17-20. Weiss, S., Muller, H.M. and Rappelsberger, P. Processing concepts and scenarios: electrophysiologial findings on language representation. In: A. Riegler and M. Peschl (Eds.), Does Representation Need Reality? Austrian Society for Cognitive Science, Technical Report 97-01,1997a: 200-206. Weiss S., Schack, B. and Rappelsberger P. Lexical processing within the brain: evidence from EEG spectral analysis and dynamic topographic coherence analysis. In: H. Witte, U. Zwiener, B. Schack and A. Doering (Eds.), Quantitative and Topological EEG and MEG Analysis. Druckhaus Mayer, Jena, 1997b: 403-405.