Event-related potentials (ERPs) derived from the electroence-phalogram before, during or after an event of interest have the advantage of revealing more directly differences of processes intervening between input and output than it is the case for behavior indices as reaction time and error rate. The latter measures are necessarily omnibus measures in which stimulus- and response-related effects are integrated. In contrast, an ERP effect as the N400 effect is primarily related to differences in processes which mediate between input and output and which are largely independent of stimulus bound processes (e.g., perceptual discriminability) or response bound processes (e.g., response frequency). Evidence accumulated over the last 30 years revealed that the N400 effect is a sensitive measure of the effort required to process a word, and the amplitude might be interpreted as reflecting the ease of memory access. The easier such access is, due to contextual, morphological or semantic priming, the smaller is the N400 effect (Kutas and Federmeier, 2011).

With respect to morphological processing, ERPs may reveal whether morphological priming effects resemble form processing that is reflected in early negativities or whether morphological effects ensue semantic memory access as reflected in N400 effects.

Similar to the behavioral studies, most ERP studies on morphological processing have applied repetition priming under masked or unmasked stimulus presentation. In the studies considered here, priming is concluded if the negative going ERP amplitude in the latency range of 250 ms (N250) or 400 ms (N400) is attenuated relative to an unrelated baseline condition (in which prime and target are neither semantically nor form-related), that is, to the most pronounced negativity. In other words, priming effects are concluded if the negativity in the N250 or N400 latency range is attenuated or reduced in the related condition relative to the unrelated condition (for a review, see Kutas and Federmeier, 2011).¹ For a summary of morphological ERP effects induced by violation paradigms as compared to repetition priming, see Smolka et al. (2013). Table 1 of the present study summarizes the ERP findings of priming effects generated by real morphological derivations as compared to pseudoderivations or stem homographs, as compared to the effects of pure form or meaning relatedness.

ERP Studies using the masked visual priming paradigm with short prime presentations (below 50 ms) observed that real morphologically related (semantically transparent or identical) word pairs like hunter-hunt or table-table induced either an N250 attenuation alone (cf. Morris et al., 2008) or both N250 and N400 attenuations relative to the unrelated condition (cf. Holcomb and Grainger, 2006; Lavric et al., 2007; Morris et al., 2007, 2008, 2011, 2013). The variation of effects was more diverse regarding pseudocomplex word or nonword pairs of the corner-corn or *cornity-corn type or regarding form-related word pairs of the scandal-scan or *teble-table type, ranging from no effect in either condition (Morris et al., 2007), to N250 attenuations in both conditions (cf. Morris et al., 2008), to N250 alongside N400 attenuations in form-related pairs (cf. Holcomb and Grainger, 2006) or in both the pseudocomplex and form-related pairs (cf. Lavric et al., 2007; Morris et al., 2008, 2011, 2013).

Different results were obtained when the priming for morphologically complex words was compared with that of pseudocomplex or form-related words. While Morris et al. (2007) observed significantly more priming from morphologically related words than by either pseudocomplex or form-related words in both the N250 and N400 latency range, other studies by Morris et al. (2008, 2011, 2013) found no priming differences between these three types of complexity. Other studies, yet, revealed differential processing patterns during the early (N250) and later (N400) negativity. The similar N250 deflections by real morphologically and pseudomorphologically related word pairs were taken as evidence that all words undergo the same segmentation process in early visual word recognition. Similar N400 effects of pseudocomplex words and real complex words (Lavric et al., 2007; Morris et al., 2011) were interpreted to indicate a single mechanism with two-stages (orthography-based morphological decomposition followed by semantic interpretation, (see e.g., Meunier and Longtin, 2007; Lavric et al., 2011). By contrast, similar N400 effects of pseudocomplex and form-related words (Morris et al., 2008, 2011) were interpreted as evidence for a dual-route model that comprises two-mechanisms of decomposition (one orthography-based plus one semantically based, (see e.g., Diependaele et al., 2005; Holcomb and Grainger, 2006; Morris et al., 2013)).

Since the present study focuses on lexical representations (and not on early visual word recognition), we are indifferent with respect to models on early visual word recognition. Most importantly, all models so far assume different processing outcomes for semantically transparent and opaque words at the lexical level, when semantic information is integrated (in the two-stage model, e.g., Lavric et al., 2011), or when shared representations operate at the morpho-semantic level (in the dual-route model, e.g., Morris et al., 2013), or when form and meaning codes overlap (in the connectionist model, e.g., Plaut and Gonnerman, 2000). We will now turn to review the ERP studies that examined lexical representation and processing.

Under overt priming conditions with either auditory or visual prime presentations at long SOAs all the studies reviewed here observed N400 attenuations relative to the unrelated baseline for morphologically related and semantically transparent or inflected word pairs like hunter-hunt or loca-loco (“crazy woman”-“crazy man”), respectively (cf. Barber et al., 2002; Domínguez et al., 2004; Kielar and Joanisse, 2011; Lavric et al., 2011), as well as an additional early positivity for inflected word pairs (Domínguez et al., 2004). The picture was again, more diverse for pseudocomplex word-pairs of the corner-corn type or stem homographs of the rata-rato (“rat”-“time”) type, ranging from no effect at all for pseudocomplex words (Kielar and Joanisse, 2011), to an early positivity for stem homographs (Domínguez et al., 2004), to N400 attenuations for pseudocomplex words or stem homographs (cf. Barber et al., 2002; Domínguez et al., 2004; Lavric et al., 2011), and an additional modulation of a late negativity for stem homographs (cf. Barber et al., 2002; Domínguez et al., 2004). In contrast to pseudocomplex words, purely form-related words did not reveal substantial effects relative to the unrelated condition (cf. Domínguez et al., 2004; Kielar and Joanisse, 2011), though an N400 attenuation was found as well (cf. Lavric et al., 2011).

The main interest of the above studies was to investigate the processing of different levels of word complexity. For example, Lavric et al. (2011) found that the N400 effect was largest when it was induced by morphologically related word pairs like hunter-hunt, smaller by pseudocomplex words like corner-corn and smallest by purely form-related words like brothel-broth. They interpreted the differences in deflections in favor of a two-stage model of visual word recognition, with orthography-based morphological decomposition in the first stage, and validation by semantic information at a later stage.

By contrast, Kielar and Joanisse (2011) found evidence in favor of their convergence of codes view: They manipulated the semantic transparency between real morphological derivations by constructing a fully transparent condition of the government-govern type, a semi-transparent condition of the dresser-dress type, and a semantically opaque condition that comprised about two thirds real morphological derivations of the apartment-apart type and one third pseudomorphological derivations of the corner-corn type. They found similar N400 priming effects for semantically transparent and semi-transparent and no effect at all for semantically opaque pairs. In line with the distributed-connectionist or convergence of codes view “morphological effects were graded in nature and modulated by phonological and semantic factors” (Kielar and Joanisse, 2011, p. 170). Since neither pure form similarity like panel-pan nor semantic associations like sofa-coach produced any significant effects, the authors concluded that the morphological effects could not be explained by pure form or meaning relatedness alone.

To summarize, previous studies on lexical representation (using auditory or visual prime presentation at long SOAs) in English or French observed that semantic transparency plays a key role in lexical representation. These findings strongly contrast with our behavioral findings in German (Smolka et al., 2009, 2014): Under overt priming with either auditory or visual prime presentation (at long SOAs) complex verbs primed their base to the same extent regardless of whether they were semantically transparent (e.g., aufstehen-stehen, “stand up”-“stand”) or semantically opaque (e.g., verstehen-stehen, “understand”-“stand”). Unlike the English and French findings, these findings suggest that lexical representation in German is independent of semantic compositionality: A complex verb like understand is not only segmented into {under} and {stand} during early visual (or auditory) word recognition but is also lexically represented via its base {stand}.

Given that there are hardly any studies of this issue in German, we seek to investigate it more fully by means of ERPs. Behavioral responses reflect the endpoint of multiple stages of the word recognition process as well as response preparation. ERPs provide the possibility to tap online into the different processes of morphological, semantic, and form-relatedness—all processes that are hard to detect by means of purely behavioral priming techniques.

The present study used German complex verbs to examine whether morphologically complex words are lexically represented via their base or via their whole form. German complex verbs provide the opportunity to manipulate the semantic transparency and opacity relating to the same base verb. For example, the complex verbs ankommen (“arrive”), mitkommen (“come along”), zurückkommen (“come back”), nachkommen (“follow”), entkommen (“escape”), abkommen (“digress”), bekommen (“get”), verkommen (“degenerate”), and umkommen (“perish”) generate a wide range of meaning variation with respect to the same base verb kommen (“come”).

The linguistic literature (e.g., Fleischer and Barz, 1992; Olsen, 1996) distinguishes between prefix and particle verbs. Both types comprise a simple verb and a prefix or a particle. Prefix and particle verbs differ in some syntactic and prosodic characteristics. However, these differences do not surface under the stimulus presentation of the present study (i.e., in citation form under visual presentation). Further, previous studies (using phoneme monitoring or priming) found similar effects by prefix and particle verbs in German (Drews et al., unpublished) and Dutch (Schriefers et al., 1991). Hence, the two types are not further differentiated here and subsumed under the general term “complex verbs”.

Most importantly, prefix and particle verbs may be both transparently and opaquely related to the meaning of a base verb. For example, the prefix ver- occurs in the transparent prefix verb verbleiben (“remain”) of the base verb bleiben (“stay”), and in the opaque derivation verschwimmen (“blur”) of the base schwimmen (“swim”). Similarly, the particle auf (“up”) may occur in a transparent derivation like aufheben (“lift”) of the base verb heben (“lift”) as well as in an opaque derivation like aufhören (“stop”) of the verb hören (“hear”).

Importantly, and different from previous studies in English (e.g., Rastle et al., 2000, 2004; Morris et al., 2007), all complex verbs used in this study share a morphological relationship established on etymological grounds with their base, even if they are not semantically compositional.

The present study is closely modeled on the behavioral study of Smolka et al. (2009). In that study, response latencies and accuracies were measured under overt priming conditions with visual prime presentations at long SOAs (300 ms) to ensure that the experimental conditions were sensitive to semantic processing and tapped into lexical processing. Morphologically related primes were complex verb derivations that were either transparently (e.g., mitkommen, “come along”) or opaquely (e.g, umkommen, “perish”) related to their base verb (e.g, kommen, “come”) that served as target. Contrary to the view that semantic meaning presides over conscious word processing, semantic transparency did not modulate the magnitude of morphological priming. In the first experiment, semantically transparent (mitkommen, “come along”), opaque (umkommen, “perish”), and identity (kommen, “come”) primes facilitated the recognition of base verbs (kommen, “come”) to the same extent. By contrast, purely semantically associated verbs (nahen, “approach”) did not prime.

The second experiment examined the influence of form overlap on morphological processing and exchanged the identical primes with form-related primes (kämmen, “comb”). However, form relatedness hindered target recognition (kommen, “come”) at the same time as morphological relatedness facilitated target recognition, again regardless of semantic transparency. In that experiment, semantic associates (nahen, “approach”) induced significant priming, though weaker in magnitude than that by morphologically related primes. In the third experiment, this time under prime-exposure durations of 1000 ms, priming from semantic associates was as strong as that by morphologically related primes; and accuracy (but not latency) data showed a small semantic transparency effect in favor of semantically transparent over opaque derivations.

To summarize, the three experiments demonstrated strong morphological priming that was (a) equivalent for semantically transparent and opaque complex verbs; (b) stronger than semantic priming (at SOA 300); and (c) different from form inhibition. These results were in line with previous behavioral experiments in German that observed equivalent priming from semantically transparent and opaque primes under overt priming conditions (e.g., Drews et al., unpublished; Schirmeier et al., 2004).

In the present study, we modeled on the second experiment of Smolka et al. (2009) and measured ERPs under overt visual priming conditions at 300 ms SOA. Priming was measured against the control condition with unrelated verb pairs like tarnen-ziehen (“mask”-“pull”). This condition was expected to yield the most negative potentials. As described above, we concluded priming, if the ERP amplitude of a related condition was attenuated (in the latency range around 250 ms or around 400 ms) relative to this baseline condition, which shows neither form nor semantic relatedness between primes and targets. A condition with semantic associations between verb pairs like zerren-ziehen (“drag”-“pull”) was used to measure the pure meaning relatedness between verbs. We hypothesized that this condition will induce an N400 attenuation, if semantic associations between verbs are strong enough to activate the automatic spreading within a semantic network. Looking at previous results (see Table 1) it is possible though, that semantic associations do not induce significant effects (cf. Kielar and Joanisse, 2011), while synonyms do (cf. Domínguez et al., 2004).

We induced morphological priming by using real morphological derivations that were either semantically transparent or opaque with respect to their base, such as zuziehen-ziehen (“pull together”-“pull”) and erziehen-ziehen (“educate”-“pull”), respectively. As in all previous ERP studies using overt priming (Barber et al., 2002; Domínguez et al., 2004; Kielar and Joanisse, 2011; Lavric et al., 2011), we expected a strong N400 attenuation for semantically transparent derivations.

With respect to the semantically opaque condition, this is the first ERP study that used semantically opaque words that were real morphological derivations of their base. There is only one comparable study that used (partly) real morphological but semantically opaque derivations, and they did not find any priming effect in this condition (Kielar and Joanisse, 2011). According to the two-stage model or dual route view that morphological structure and processing depends on semantic compositionality (i.e., the meaning relation between prime and target), we should not find any effect for semantically opaque words. If, however, German complex words are accessed and represented via their stem regardless of meaning compositionality, we will observe a priming effect in form of an N400 attenuation in this condition, too.

Similarly the connectionist or convergence of codes view assumes that semantic similarity plays a role in that “morphological effects vary continuously as a function of the degree of semantic and form similarity among words” (Kielar and Joanisse, 2011, p. 162). In the present study, the morphologically related primes all contain the complete target and thus share the same form overlap between prime and target. Hence, the only difference between morphologically related primes in the semantically transparent and opaque conditions is that the former have a strong meaning similarity with the target, while the latter show no or only little meaning similarity with the target. Semantically opaque words should thus induce either no priming at all—as it was the case in the behavioral study by Gonnerman et al. (2007) and in the ERP study by Kielar and Joanisse (2011)—or, in case that semantically opaque words do induce priming, its magnitude should be significantly weaker than that by transparent words. In ERP terms, if the morphological effects were a combination of form and meaning overlap, we should find stronger effects, that is, more positive-going N400 amplitudes, for semantically transparent than for semantically opaque primes. If, however, our view holds that all German complex words access and activate their base, and if our previous behavioral findings (Smolka et al., 2009, 2014) generalize to electrophysiological data, we will find equivalent priming effects by semantically transparent and opaque derivations. Additionally, if our hypothesis holds that morphological regularities generalize beyond meaning relatedness, we should expect stronger morphological than semantic effects. In ERP terms, the N400 effects will be more positive-going for the two morphological conditions than for the semantic condition.

Morphologically related pairs are always form-related as well. Hence, orthographically similar verbs like zielen-ziehen (“aim”-“pull”) were used to measure the effects of form similarity between verbs. Previous overt priming studies so far revealed either a very small form effect (cf. Lavric et al., 2011) or none at all (Domínguez et al., 2004, 2006; Kielar and Joanisse, 2011). For this reason, we were indifferent as to whether we should expect a significant form effect relative to the baseline condition. Importantly, though, if our hypothesis holds that morphological structure in German generalizes beyond form, the amplitude in the form condition will be more similar to the unrelated condition and hence more negative than that of the morphologically related but semantically opaque condition (both representing form without meaning relatedness).

Seventeen students of the Philipps-University, Marburg, took part in the experiment for course credit or payment. All participants were monolingual speakers of German, not dyslexic and had normal or corrected-to-normal vision. All participants were right-handed and gave their written informed consent.

Stimuli were presented on a 17″ monitor, connected to an IBM-compatible personal computer. Stimulus presentation and data collection were controlled by the Presentation software developed by Neurobehavioral Systems.² Responses were recorded from the left and right “control” keys on a standard keyboard.

Each participant saw all 36 simple verbs in all five priming conditions. Primes of the same target were rotated over ten blocks according to a Latin Square design, in such a way that the same target appeared in every second block. Likewise, the prime-target pairs of similar pseudoverb targets were distributed across the ten blocks. The remaining filler pairs were evenly allocated to the blocks, so that each block comprised equal numbers of complex and simple primes as well as verb and pseudoverb targets.

In total, an experimental session comprised 720 prime-target pairs, presented in ten experimental blocks, with 72 prime-target pairs per block. Within blocks, prime-target pairs were randomized separately for each participant with the constraint that there were maximal four adjacent word or nonword targets. There were 20 practice trials.

Participants were tested individually in a dimly lit room and were seated at a viewing distance of about 60 cm from the screen. Each trial started with a fixation cross in the center of the screen for 1000 ms. Primes and targets were presented in the center of the screen, in white Sans Serif letters on a black background. Primes were presented in uppercase letters, point 22, targets in lowercase letters, point 26. The prime appeared for 200 ms, followed by a blank screen for 100 ms (SOA = 300 ms), after which the target appeared for 500 ms. A prompt (“?”) appeared 1000 ms after target-onset on the screen. The inter-trial interval was constant at 2000 ms.

Participants were asked to refrain from blinking and to respond until after the prompt. Participants made lexical decisions to the targets, in other words, they responded whether the stimuli were existing words or not, and were instructed to respond as accurately as possible.³ “Word” responses were made by pressing the right “control” keyboard key with the index finger of the right hand, “nonword” responses were made with the left hand on the left “control” key. During practice trials, participants received feedback on the accuracy of each response; during the experimental session, feedback was given only on incorrect responses.

The experiment lasted for about 1 h. Participants self-administered the breaks between the ten blocks, and took at least two longer breaks.

The EEG was recorded from 61 scalp electrodes using a cap in which Ag/AgCl inserts are fixated by individual electrode supports (System Falk Minow, Munich, Germany). All scalp electrodes were randomly referenced to the left or right earlobe during the recording and re-referenced offline to averaged earlobes; the left or right mastoid served as ground. Horizontal and vertical eye movements were monitored with appropriate electrode pairs. Impedances of all electrodes were kept below 5 kΩ. Two 32-channel amplifiers (SYNAMPS, NeuroScan) were used for EEG recording. Band pass was set from DC to 40 Hz and the sampling rate was 500 Hz. Prior to the beginning of each experimental block, a DC reset was manually initiated. DC drift was corrected according to the method suggested by Hennighausen et al. (1993). Eye blinks and trials with other artifacts were removed by applying a threshold criterion (max. voltage step per sampling point >50 μV or absolute difference in a trial segment >100 μV). ERPs were extracted from the edited set of raw data by averaging single trials separately for subjects, electrodes, and experimental conditions. Post-stimulus epochs were baseline-adjusted to the average amplitude of a 100 ms epoch preceding the onset of the target word. Only segments with correct responses entered the analysis. We created a subset of electrodes resembling the 19 standard electrodes of the 10–20-system. Three adjacent electrodes were pooled for each of these “standard” electrodes (see Figure 1). The pooled 19 electrodes entered the statistical analysis.

Semantic priming effects were investigated to assess the sensitivity of the experimental setup. For this purpose, the ERPs to targets with semantically related primes were compared to unrelated primes (S vs. U) using standard ad hoc methods for ERP comparisons of two conditions. Semantic priming effects were assumed at those electrodes and time intervals at which S differed from U in pointwise t tests (α = 5% two-tailed) for an interval of at least 50 ms. Similar ad hoc analyses were performed to assess the influence of morphology (O vs. U) and form (F vs. U). The electrodes and locations at which semantic priming effects were observed were then used to define a region of interest (ROI) for the analyses of the interplay between semantic and morphological priming.

Permutation tests were used to assess whether these ad hoc methods yielded robust results (Blair and Karniski, 1993). Permutation tests allow controlling the family-wise Type 1 error rate in multiple, possibly dependent significance tests (for a review, see Maris and Oostenveld, 2007). To this end we calculated a t_max distribution for S – U using 10,000 permutations. In each permutation, the sign of S – U was selected at random for each participant, thereby simulating the null hypothesis in which x = S – U has the same probability than −x = U – S. We calculated the t values at each sampling point that fell into the ROI, and chose the maximum absolute value over all electrode clusters and time points (t_max). The 95th percentile of this permutation distribution was selected as the critical t_max. This means that the probability is 5% that any absolute t_max value in the main analysis is above the critical t_max value if the null hypothesis holds. Similar procedures were applied for investigating morphological and form-related priming.

The primary question of this study is whether semantic transparency exerts priming on top of morphological priming (T vs. O). In order to avoid overly conservative correction due to the high number of partial tests in the permutation procedure, the permutation test that examined T – O was restricted to a ROI that was defined on the basis of the standard semantic priming effect, obtained by the comparison of semantically related to semantically unrelated primes, S – U. The ROI included those electrodes and time intervals at which S – U differed from zero in running t tests (α = 5% two-tailed) for at least 50 ms. Such a ROI approach is able to control the Type 1 error while preserving power: For electrodes and intervals where semantic priming effects are observed, that is, S ≠ U, it can be expected that T differs from O to a similar extent, if the same processes of semantic analyses are activated. Since we are interested in the differential effect of semantic priming on top of morphology, we will be testing the difference between T and O only at electrodes and intervals where semantic priming effects are visible (e.g., Gondan et al., 2007). Excluding other time points and electrodes from the analysis thereby reduces the set of partial tests that have to be controlled. The critical t_max value is equally reduced, thereby increasing power to detect priming effects within the ROI.

Figure 2 shows the grand averages of semantically related (S, zerren-ziehen, “drag”-“pull”) and unrelated (U, tarnen-ziehen, “mask”-“pull”) prime-target pairs. The curves start to deviate from each other at about 300 ms after stimulus onset with unrelated targets being more negative than associated targets on the central and posterior electrodes. The maximum difference is reached around 400–600 ms, indicating the typical attenuation of the N400 component by semantic associations. The upper panel in Figure 6 provides the significant t- and permutation tests for this semantic effect.

Do morphologically related complex verbs prime their base? To calculate the priming induced by morphological relatedness, both morphological conditions (T and O) were compared with the unrelated condition U. Figure 3 depicts the results. Each of the morphological conditions was far more positive going than the unrelated condition. The curves start to deviate in an early negativity, indicating an N250, followed by a positivity (P325), which again was followed by a strong N400 effect. The amplitude deviations between U and T as well as between U and O in the range of the N250, P325, and N400 components were significant for all electrode clusters and for both semantically transparent and opaque derivations. The second panel from the top in Figure 6 provides the significant t- and permutation tests for the pure morphological effect (O vs. U).

Is there a semantic transparency effect in the lexical representation of morphologically related German words? To this end, we compared the ERPs of morphologically and semantically transparent word pairs (T, zuziehen-ziehen, “pull together”-“pull”) to those of morphologically related, but semantically opaque word pairs (O, erziehen-ziehen, “educate”-“pull”). Figure 3 shows the striking similarity of the two conditions: Most importantly, the priming effects of T and O were equivalent in amplitude. In line with this, the permutation test within the ROI defined by S – U did not reveal any significant difference between T and O. The third panel from the top in Figure 6 demonstrates this resemblance between the two morphological conditions (T and O) in the t- and permutation tests.

We further tested the hypothesis whether or not morphological regularities generalize beyond meaning relatedness. If this is the case, we should find stronger morphological than semantic effects. Indeed, Figure 4 shows the comparison between the conditions S and T, and indicates that the effects induced by morphologically and semantically related prime-target pairs were much stronger than the N400 effect produced by pure semantic associations.

To calculate whether form-relatedness affects target recognition, a condition with orthographically similar verbs (F, zielen-ziehen, “aim”-“drag”) was compared with the unrelated baseline condition (U). As can be seen in Figure 5, this form effect starts at about 180 ms in a right frontal positivity (relative to the unrelated condition) that converges to an N250 effect and further extends to a weak frontal N400 effect. Form-related prime-target pairs typically induce the early positivity and N250 effects.

Importantly, this form effect significantly differed from the priming effect by morphologically related word pairs. While the form effect is right frontal, the morphological effect occurs at centro-parietal sites that characterize a typical N250 and N400 effect. The forth panel from the top in Figure 6 provides the significant t- and permutation tests comparing the two effects “form without meaning”, that is, O vs. F.

Finally, we calculated the comparison (O – F) vs. (T – S). This comparison represents the effects of form-relatedness (without meaning) with those of meaning relatedness. The effect occurs left anterior, with the difference (O – F) more negative going than the amplitude of the comparison (T – S), indicating an extended N250 effect or an anterior positivity. The bottom panel in Figure 6 provides the corresponding significant t- and permutation tests for this comparison.

As hypothesized, we found a broad N400 effect with attenuated curves for semantically related verbs (zerren-ziehen, “drag”-“pull”) relative to the unrelated verbs (tarnen-ziehen, “mask”-“pull”). This modulation of the N400 component is typical for semantic associations and it indicates that the semantic associations between verbs are strong enough to activate automatic spreading within a semantic network. In contrast to Kielar and Joanisse (2011) who observed no effect for semantic associations, our findings indicate that not only synonyms (cf. Domínguez et al., 2004) but also semantic associations are automatically activated within the semantic network.

Even though the N400 attenuation we found for semantic associations might be smaller than expected, one has to keep in mind that we are dealing with verb-verb pairs, which generally show smaller priming effects than noun-noun associations. While there are plenty of ERP studies measuring the effects of semantic association between nouns (e.g., Bentin et al., 1985), there are only few measuring the semantic relatedness between verbs (cf. Rösler et al., 2001; Smolka et al., 2013), so that there are only few studies for a direct comparison. With respect to verb pairs, we have repeatedly found a dissociation between the electrophysiological and the behavioral data: While the former always indicated strong semantic-priming effects in terms of N400 modulations (Rösler et al., 2001; Smolka et al., 2013), the latter generated both significant (cf. Exp. 2 and 3 in Smolka et al., 2009; Exp. 3 in Smolka et al., 2014) and nonsignificant priming effects (cf. Exp. 1 and 2 in Smolka et al., 2014; Exp. 1 in Smolka et al., 2009, 2013). This dissociation between electrophysiological and behavioral data suggests that ERPs represent a fine-grained means that makes it possible to measure subtle effects that do not surface under behavioral data collection.

Most importantly, the present N400 deflection by semantic associations proves that the experimental procedure in this experiment is sensitive to detecting semantic influences and tapping into lexical processing.

To control the effects of form similarity, we compared orthographically similar verbs like zielen-ziehen (“aim”-“drag”) with the unrelated baseline condition. Orthographically similar primes induced a priming effect in terms of an early right frontal positivity that converges into an N250 effect and further extends to a frontal N400 effect. Form-related prime-target pairs typically induce the early positivity and N250 effects. This finding corresponds to previous masked priming studies that found anterior N250 and N400 effects (Holcomb and Grainger, 2006; Lavric et al., 2007; Morris et al., 2008, 2011, 2013) as well as to an overt priming study that observed an N400 attenuation effect for form priming (Lavric et al., 2011).

The early positivity is typical for form-related relative to unrelated prime-target pairs. The dual-route model, for example, assumes two parallel mechanisms (one orthography-based and one semantically based). Form-priming in terms of the N250 reflects the mapping of prelexical representations onto whole-word representations (specifically, a feed-forward prelexical morpho-orthographic segmentation that operates independently of lexical status and semantic transparency, see Morris et al., 2011), while later (N400) effects are thought to indicate the mapping of shared representations at the morpho-semantic level (see e.g., Diependaele et al., 2005; Holcomb and Grainger, 2006; Morris et al., 2011, 2013). By contrast, the two stage-model assumes a single mechanism with two-stages, an orthography-based morphological decomposition followed by semantic interpretation (e.g., Meunier and Longtin, 2007; Lavric et al., 2011).

Most importantly, the form condition in our study was more negative going than the morphologically related but semantically opaque condition. Since both conditions represent form similarity without meaning relatedness, it is interesting to note that the comparison of the two generates an N400 attenuation, which is typical for semantic effects (with the morphological modulation being more positive than the form condition). This indicates that even semantically opaque but morphologically related pairs are more strongly meaning related to their base than purely form-related pairs are. We will discuss this issue in more detail in the description of the model below.

Overall, we may conclude that the morphological effects we obtained with German complex verbs cannot be reduced to pure semantic and form relatedness between words.

To examine whether morphologically related complex verbs prime their base, we compared the two morphological conditions relative to the unrelated condition. Both curves were far more positive going than the unrelated condition, each producing an N250, followed by a P325, again followed by a strong N400 attenuation effect at all electrode clusters.

The strong N400 attenuation for semantically transparent derivations corresponds to the findings of all previous ERP studies using overt priming (Barber et al., 2002; Domínguez et al., 2004; Kielar and Joanisse, 2011; Lavric et al., 2011). In addition, we also found a strong N400 attenuation for semantically opaque derivations, which contrasts with a previous study using (partly) real morphological but semantically opaque derivations, which did not find any priming in this condition (Kielar and Joanisse, 2011). Our findings thus indicate that German complex words are accessed and represented via their stem regardless of meaning compositionality.

Moreover, we observed not only a strong N400 modulation by semantically opaque derivations but also that this N400 attenuation was as strong as that by semantically transparent derivations. That is, erziehen (“educate”, semantically opaque) primed its base ziehen (“pull”) to the same extent as zuziehen (“pull together”, semantically transparent) did. This indicates that both derivations are accessed via their base regardless of their meaning relation to it.

The finding of equivalent priming from semantically transparent and opaque derivations corresponds to our previous behavioral findings (e.g., Smolka et al., 2014). Specifically, in the behavioral experiment using the same stimulus material and priming conditions as in this ERP study (Smolka et al., 2009), semantically transparent and opaque derivations yielded 43 ms and 40 ms priming effects, respectively (see also the summary of behavioral effects in Table 6 in Smolka et al., 2014). Altogether, these data indicate that semantically transparent and opaque derivations are lexically represented and processed in similar ways. We will discuss this issue in more detail in our proposed model of lexical representations (see below).

Finally, we asked whether morphological regularities generalize beyond meaning relatedness. Indeed, we found stronger N400 attenuation effects for morphological than semantic relatedness. This finding is particularly interesting, because the ratings of the association test indicated that semantic associates like zerren (“drag”) were rated as significantly higher (5.9) related in meaning to the target ziehen (“pull”) than the morphologically related and semantically transparent (5.1) primes like zuziehen (“pull together”).

Stronger priming for morphologically related and semantically transparent primes (i.e., in the T condition) than in the semantic condition can be readily explained by the convergence of codes view. Given that primes and targets in the T condition overlap both in form and meaning, the N400 should be more positive-going than with either orthographic (in the F condition) or semantic overlap (in the S condition) only. However, according to the same argument, the N400 amplitude in the O condition should be significantly less positive-going than in the T condition, since opaque primes share the form but no or little meaning with the target, but this was not the case.

With respect to the pure semantic effect, its occurrence is important since it indicates that the design of this study was sensitive to detecting semantic influences. The lack of semantic transparency effect in the morphological condition is thus not due to a general lack of semantic processing in this study.

A direct comparison of the present ERP data and the corresponding RT data from the study, modeled on Smolka et al. (2009), reveals striking similarities. Figure 7 provides all conditions for an easy overview. Targets in the unrelated condition showed slow RTs (532 ms) and the most-negative going N400 amplitude. This condition served as the baseline against which the priming effects were calculated. Form-related primes significantly inhibited responses (+16 ms) in the behavioral data and induced slightly more positive-going N250 and N400 amplitudes as compared with the unrelated condition. By contrast, the semantic associates yielded faster RTs (−21 ms) and a more positive-going N400 amplitude than the unrelated condition. This semantic effect was smaller than the morphological effects, that is, RTs were slower (≈20 ms) and ERPs were more negative-going than in the morphological conditions. Further, the two morphological conditions, T and O, yielded the strongest priming effects relative to the unrelated condition. This was evident in terms of the fastest RTs (−43 ms and −40 ms, respectively) and the most positive-going N400 amplitudes. Most importantly, neither the RTs nor the ERPs differed between the two morphological conditions. Finally, the morphologically related but semantically opaque condition showed significantly faster RTs (−56 ms) and far more positive-going N400 amplitudes than the form condition.

If we summarize the behavioral (Smolka et al., 2009, 2014) and the electrophysiological data presented here, we may conclude that both types of data revealed strong morphological priming effects that were significantly larger than those induced by purely semantically related or form related complex verbs. This general convergence means that the morphological-priming mechanism involves a general cognitive phenomenon that can be captured by different methods. This renders our results even more robust: We have shown that complex verbs in German are accessed and processed via their stem, regardless of their meaning compositionality.

We thus provide evidence for the existence of a morphological dimension to lexical organization that cannot be reduced to formal or semantic relations between primes and targets. Most importantly, this indicates that morphological structure needs to be incorporated in the modeling of lexical representation in German.

Why is it that morphological processing and representation seems to be different in German compared to other Indo-European languages like English or French? In the following, we consider some possible factors that may affect language processing.

In the following, we shortly describe the frequency-based model previously suggested by Smolka et al. (for details, see Smolka, 2005; Smolka et al., 2007b, 2009, 2013, 2014). Its main feature is that complex verbs, including regularly and irregularly inflected verbs as well as semantically transparent and opaque derivations are segmented into stem and affixes and are lexically represented via their stems (and affixes).

The model assumes segmentation processes similar to those suggested by models of prelexical processing. We refer to these studies for a detailed description of the nature of early form-to-meaning mappings (cf. Diependaele et al., 2005; Marslen-Wilson et al., 2008; Crepaldi et al., 2010). Importantly, since morphemes are the smallest meaningful units, they emerge as the product of form-to-meaning mappings. In German, letter strings like zuziehen (“pull together”) and erziehen (“educate”) are segmented into their constituent morphemes regardless of meaning compositionality: zu-, er-, zieh, -en. This accounts for our finding of an N250 effect for all prefixed verbs in the morphological conditions of this study, which fits with the interpretation that N250 modulations indicate a “feed-forward prelexical morpho-orthographic segmentation process that operates independently of lexical status and semantic transparency” (cf. Morris et al., 2011, p. 581).

Then the constituents activate their representations at the lexical level, so that both the transparent verb zuziehen and the opaque verb erziehen are lexically represented via their base {zieh} and affixes {zu}, {er}, and {en}, respectively. Since the target ziehen (“pull”) activates the same lexical units {zieh} and {en}, its recognition is facilitated by the prior presentation of a complex verb with the same base. This accounts for our findings that the N400 attenuations induced by morphologically related words are independent of meaning compositionality. This also accounts for our finding that the facilitation in form of N400 modulations by verbs sharing the same base is larger than that by semantically associated verbs holding a different base.

Further, the finding that semantically opaque verbs induce the same amount of facilitation as transparent ones explains why both types of derivation induce an additional P325: Both types of derivations are lexically represented via the stem, just as the base verb is. Hence, the priming effect of the base corresponds to identity priming, which is typically reflected in positivities that precede the N400, such as the P325. For example, the P325 was found in repetition priming studies that used identical prime target pairs like table-table (Holcomb and Grainger, 2006) or gender-inflected nouns like bobo-boba (cf. Domínguez et al., 2004), see also Table 1.

The finding that semantically opaque verbs induce the same amount of facilitation as transparent ones indicates that the stems were accessed before the meaning of the whole word, which contradicts the assumptions of a supralexical model (e.g., Giraudo and Grainger, 2000; Diependaele et al., 2005). This finding further contradicts the assumptions of distributed-connectionist approaches or the convergence of codes view, according to which semantically transparent words should always yield stronger effects than semantically opaque words (e.g., Rueckl et al., 1997; Plaut and Gonnerman, 2000; Kielar and Joanisse, 2011). These assume that morphological regularities emerge during visual word processing when orthographic codes are mapped onto meaning codes. During this mapping process, the strength of the semantic association is expected to affect the form-to-meaning mappings. Accordingly, semantically transparent derivations should always yield stronger priming effects than semantically opaque ones. However, this was not the case in the present study.

So far, we have explained how complex verbs are segmented (as indicated by the N250) and accessed via their stem regardless of meaning compositionality (as indicated by the P325 and the N400). How is the specific meaning of a complex word derived? If we are aware of the fact that even semantically transparent derivations yield specific idiosyncratic concepts from the meaning of the base and the function of the prefix, we may assume that transparent and opaque meanings are generated in similar manners. The very specific—more or less idiosyncratic—meaning of a complex word is activated by the lexical constituents that represent a word. For example, the stem-affix combination zieh (“pull”) and zu (“together”) will activate the transparent concept PULL TOGETHER, while the stem-affix combination zieh (“bind”) and er-⁴ will activate the opaque concept EDUCATE. Note that both concepts differ from the concept PULL of the single constituent.

In our frequency-based model, the specific meanings are selected by mechanisms that rely only on connections between lexical and conceptual units, choosing the most frequently activated concept upon the co-activation of the constituents. It is possible, though, to assume separate whole-word lemmas similar to “superlemmas” in idiom processing that are activated by the simultaneous activation of several constituents at the lexical level (e.g., Sprenger et al., 2006; Kuiper et al., 2007; Smolka et al., 2007a; Rabanus et al., 2008). Irrespective of how the specific meaning is activated following lexical access, our findings indicate that the complex verb is lexically accessed and processed via its stem.

In sum, our findings indicate that lexical representation in German refers to the base of a complex verb, regardless of meaning compositionality. This indicates that morphological structure represents an important aspect of language processing in German and must be incorporated in the lexical representation of German words.