Visual semantic features are activated during the processing of concrete words: event-related potential evidence for perceptual semantic priming

Cognitive Brain Research 10 (2000) 67–75 www.elsevier.com / locate / bres

Research report

Visual semantic features are activated during the processing of concrete words: event-related potential evidence for perceptual semantic priming Marion L. Kellenbach a , *, Albertus A. Wijers b , Gijsbertus Mulder b b

a Department of Linguistics, University of Groningen, Groningen, The Netherlands Experimental and Work Psychology, University of Groningen, Groningen, The Netherlands

Accepted 28 March 2000

Abstract There has been conflicting evidence to date regarding the existence of non-strategic semantic priming based on semantic similarity, and in particular on visual–perceptual semantic features (e.g., button–coin: words refer to objects with the same global shape). Both event-related potential (ERP) and reaction time (RT) measures were employed to investigate visual–perceptual semantic priming in a word-pair lexical decision task designed to minimise the contribution of conscious strategic processing. While no RT priming effect was observed, a robust priming effect was obtained on the N400 component of the ERP. This result shows that semantic priming, as indexed by the N400 component, can be supported by nonassociative visual–perceptual semantic relations. The data are consistent with perceptual form information being accessed during the processing of concrete words, and provide support for models of semantic representation which incorporate semantic features and form information.  2000 Elsevier Science B.V. All rights reserved. Theme: Neural basis of behavior Topic: Cognition Keywords: Perceptual semantic priming; Semantic features; N400; Event-related potential

1. Introduction Semantic priming refers to the highly consistent processing advantage shown by words which are preceded by a semantically relevant word (or other context), relative to when it is preceded by a semantically unrelated word (e.g., Refs. [1,33]; see Ref. [39] for a review). A distinction can be made, however, between associative and nonassociative semantic relations, which are often confounded in priming studies (e.g., Refs. [11,16,33]). Associative relatedness is generally indexed by free association norms (e.g., Refs. [45]). In contrast, a nonassociated semantic relation specifies a degree of semantic similarity between two concepts, defined by shared semantic attributes which can *Corresponding author. MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 2EF, UK. Tel.: 144-1223-355-294, ext. 311; fax: 144-1223-359-062. E-mail address: [email protected] (M.L. Kellenbach).

potentially be based on a range of semantic properties (e.g., categorical: onion–garlic, functional: button–collar, script / theme: restaurant–wine; see Refs. [36,53]). Evidence for nonassociative semantic priming would provide support for componential theories of representation which propose that a word’s meaning is comprised of a number of semantic features or properties (for a review see Ref. [32]). Furthermore, identifying the types of semantic information or properties capable of supporting nonassociative semantic priming enables characterisation of the aspects of semantic representation which are activated during the processing of a (prime) word [36]. For example, priming for the word pair plum–cherry would be consistent with co-ordinate category information being activated by the processing of plum, while priming for hammer–nail might be interpreted as hammer activating functional–instrumental information. A complicating factor for interpretation of semantic priming based on these types of nonassociative relations, however, is the difficulty of isolating the precise aspects of semantic representation

0926-6410 / 00 / $ – see front matter  2000 Elsevier Science B.V. All rights reserved. PII: S0926-6410( 00 )00023-9

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which may account for the facilitation. For example, plum and cherry are not only category co-ordinates, but share other semantic properties, such as that they both grow on trees, taste sweet, contain vitamin C, have stones, are red, are round, etc. Similarly, hammer may prime nail, not because of their functional–instrumental relationship, but because they are both items of hardware, occur in the same situation (script), have a similar shape, etc. Visual–perceptual semantic priming is a specific example of nonassociative semantic priming which refers to priming elicited by two words which are semantically related only in that their referents are visually perceptually similar. For example, the word pair button–coin share perceptual semantic features pertaining to the physical properties of the objects to which they refer (global shape: round, flat). A number of characteristics of visual–perceptual semantic priming make it an ideal tool for investigating the activation of form-based semantic properties during lexical processing. Firstly, unlike priming based on other nonassociative semantic relations, visual–perceptual semantic priming is defined by a single overlapping semantic feature (shape), making the semantic relation exceptionally precisely defined and enabling clear interpretation of effects in terms of the activation of form information. Another advantage of studying perceptually based relations is that they are obscure to participants (as the relationship is not conceptually based and without direct or mediated semantic associations), minimising the likelihood that conscious strategic processes will be engaged. Avoidance of the engagement of conscious strategic processing is important, as indexing such processes would be less informative about the aspects of representation retrieved during default word processing. The empirical evidence for the existence of perceptual semantic priming is, however, both scant and inconclusive. Perceptual semantic priming was first reported by Schreuder and co-workers [12,48], using a word-pair semantic priming paradigm which included word pairs with a ‘conceptual’ semantic relationship (e.g., cheque– coin), with a perceptual semantic relationship (e.g., button–coin), or with no semantic relationship (unrelated: e.g., pen–coin). Although in this initial study the perceptual semantic priming effect did not reach conventional levels of statistical significance, Schreuder and co-workers [12,48] subsequently showed that while ‘conceptual’ semantic priming effects were most robust on tasks where the response was made late in the decision process (lexical decision and delayed naming), perceptual semantic priming effects were largest under conditions requiring fast responses (speeded lexical decision and naming). This pattern of results suggests that the observation of perceptual priming effects may be contingent on the precise point in processing at which a response is made, and led to the intriguing suggestion that perceptual semantic features may have an earlier activation timecourse than ‘conceptual’ semantic features. These results remain inconclusive,

however, as the paradigm used in these studies was compromised by a number of frequently cited methodological problems [36,44,52,55].1 Using a somewhat different approach, Moss et al. [37] have also demonstrated priming for perceptual semantic properties and differential priming timecourses for target words that referred to a perceptual or functional property of the prime word’s referent (e.g., perceptual: aeroplane– wing; functional: aeroplane–fly), using a cross-modal (auditory prime, visual target) priming paradigm. However, in contrast to the experiments of Schreuder and co-workers [48,52], functional properties were shown to be activated earlier than perceptual properties when the prime words were concrete nouns referring to manmade objects. Given the varying paradigms used, however, the comparability of these results to those of Schreuder and colleagues is unclear. Recently Pecher et al. [44] failed to observe perceptual semantic priming using a standard priming paradigm including both perceptually related word pairs and ‘conceptually’ related and associated word pairs, with either a lexical decision task or a naming task. When the perceptual properties of the stimulus concepts were made salient, however, by requiring a perceptual judgement (e.g., does the word refer to an oblong object?) to individually presented perceptually related stimuli prior to the priming experiment, a perceptual semantic priming effect was elicited when a naming task was used, but not when the task was lexical decision. It was hypothesised that the absence of perceptual semantic priming in lexical decision with perceptual pre-activation may have been due to the presence of semantically associated items, which promote relatedness checking strategies and mask any perceptual semantic priming effects (see also Refs. [1,7,31]). Consistent with this proposal, perceptual semantic priming was obtained when the associative pairs were removed. It remains a possibility, however, that perceptual semantic priming may have been observed in this experiment simply because of the exclusion of associative pairs, rather than because of the pre-activation of perceptual features, as these manipulations were not tested separately. Nonetheless, Pecher et al. [44] concluded that while perceptual semantic features are not generally salient enough to be activated during lexical processing, pre-activation of these features within the experimental context increases their accessibility sufficiently to elicit priming (see also Refs. [2,34–36]). Extending this point, they suggested that priming between two concepts is dependent on the overlap between activated features, rather than the overlap of all 1

For example, the target stimuli were repeated four times during the experiment, each time with a prime stimulus from a different category (perceptually related, conceptually related, unrelated, or perceptually and conceptually related). Furthermore, the target stimuli were presented while the prime stimulus remained on the screen, and both stimuli remained visible until a response was made.

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defining features, and that which features are activated is influenced by contextual factors. The goal of the present study was to further investigate whether perceptual form information is activated during the lexical processing of concrete words, as reflected in visual–perceptual semantic priming, using both behavioural and event-related potential (ERP) measures. The paradigm was designed to maximise the possibility of observing visual–perceptual semantic priming effects, while minimising the contribution of conscious strategic processes. As noted above, the (from the participants’ point of view) obscure nature of visual–perceptual semantic priming relations considerably reduces the possibility of conscious strategic processing based on these relations. In addition, a short SOA was employed, which has been claimed to limit the contribution of controlled strategic mechanisms to lexical processing (e.g., Refs. [10,28,38]). Finally, conceptually semantically related and / or associated stimuli were not included in the current paradigm, as such stimuli are likely to draw attention to the semantic relationships between stimuli, encouraging strategic semantic matching and perhaps obscuring any priming effects associated with the visually perceptually related stimuli in the lexical decision task [44] (see also Refs. [1,31]). This aspect of the design also enables us to examine the possibility that the visual–perceptual semantic priming observed in the lexical decision task of Pecher et al. [44] was due to the exclusion of associative stimuli, rather than the pre-activation of perceptual features. The N400 component of the ERP was used as a supplementary index of semantic priming, as it has reliably been shown to be highly sensitive to manipulations of semantic relations, being attenuated to words which are preceded by a semantically congruous context, relative to when preceded by a semantically incongruous context (e.g., Refs. [3,20,21,17,22,25–27,46,47]). To our knowledge, only one ERP study to date has investigated nonassociative semantic priming. Hagoort et al. [15] utilised an auditory word-pair priming paradigm, with no explicit task, to investigate language processing impairments in brain-lesioned patients compared to an elderly control group. In the control group, nonassociative (categorical) semantic relations elicited an N400 priming effect which closely resembled that elicited in a concurrent associative semantic priming condition, indicating the sensitivity of N400 amplitude to at least one type of nonassociative semantic relation between lexical stimuli. The use of ERPs as a second dependent measure offers several advantages over behavioural measures alone. ERPs provide a continuous and covert index of processing which is not limited to the precise timing of the discrete motor response, a factor which has been implicated in the observation of visual–perceptual priming effects ([12,48]; see also Ref. [36]). Furthermore, the inconsistencies between the few visual–perceptual priming studies to date may be indicative that the behavioural measures utilised

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are not sensitive enough to reliably index a small but perhaps reliable effect. The sensitivity of the ERP as a dependent variable may provide a means for overcoming such a barrier, particularly as a number of studies have shown dissociations between RT and N400 measures of semantic priming, indicating that these indices may be sensitive to different aspects of the underlying processes [7,14,19,18,23]. Observation of visual–perceptual semantic priming effects in the ERP and / or RT data elicited in the current paradigm would provide evidence for the semantic information accessed by concrete words including information about its shape, and for overlap of this single semantic feature being sufficient for supporting priming.

2. Materials and methods

2.1. Participants Twenty native Dutch-speaking undergraduate students, 14 females and six males with a mean age of 22.1 years, were paid for their participation. All were right handed as determined by a Dutch translation of the Oldfield Handedness Inventory [40], had normal or corrected-to-normal visual acuity, and no known neurological impairments or history of reading problems, as determined by self-report.

2.2. Materials All words utilised in the present study were concrete nouns which referred to inanimate objects. The critical (prime-target) pairs of stimuli were based on 148 critical target words (Dutch), each of which was paired with two types of primes, which had either a visual–perceptual semantic relationship, or no relationship to the target word. Perceptually related pairs were selected on the basis of pretesting, during which 54 undergraduate psychology students rated 228 potential critical pairs on two five-point scales referring to the dimensions of perceptual (overall shape) similarity and conceptual semantic relatedness (similar function, used in same context, same semantic category). One hundred and fourteen filler pairs which were judged by the experimenters to have varying scores on the two dimensions were also included in the pretest to prevent subjects from consistently scoring high on one dimension and low on the other. The 148 critical perceptually related pairs were chosen for use in the experiment based on the ratings, using the following criteria: a rating of .3.5 on perceptual similarity (mean54.18, S.D.50.40), and ,2.5 on conceptual relatedness (mean51.34, S.D.5 0.31). Unrelated primes, defined as concrete nouns which had no perceptual, conceptual, or associative semantic relation to the targets with which they were paired, were then selected on the basis of agreement between three judges. The 148 targets were divided into two sets of 74,

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Table 1 Mean (S.D. in parentheses) word lengths and written frequencies for all word types, and for two sets of experimental words when appropriate (necessary for counterbalancing)a Word length

Written frequency

Set 1

Set 2

Set 1

Set 2

Perceptual primes Neutral primes Critical targets

8.1 (2.4) 7.9 (2.1) 8.0 (2.5)

8.2 (2.4) 8.1 (2.0) 7.8 (2.2)

127 (405) 126 (207) 156 (339)

126 (328) 127 (257) 155 (324)

Nonword primes Nonwords (targets)

8.0 (2.3) 8.0 (2.1)

were requested to minimise body and eye movements, and were given a practice of 50 trials prior to presentation of the experiment. Following the experimental session subjects completed a questionnaire which probed their awareness of the relationships between the stimuli, any strategies used, and the perceived purpose of the experiment. No feedback as to correctness of the responses was provided until the questionnaire was completed. The questions were as follows:

126 (243)

a

Written frequencies refer to occurrences per 42 million words of text (CELEX database, Nijmegen).

matched on word length and written frequency (CELEX database, Nijmegen: written frequency per 42 million, see Table 1). The corresponding perceptual and unrelated primes were also matched on word length and written frequency across sets and conditions. This division of the critical stimuli into two sets allowed for each subject to see each target only once, but for a given target to be paired with each prime type across subjects (Table 1). Each set of critical pairs was matched on mean perceptual and conceptual relatedness scores. Finally, 148 orthographically legal and pronounceable nonword targets were created, matched to the two critical target sets on word length (Table 1). Two further concrete noun prime sets were created for the nonword targets, and matched to the other prime sets on word length and written frequency (Table 1). These stimuli were combined with each of the two sets of critical pairs to give two sets of experimental stimuli.

2.3. Procedure Each subject was presented with one set of the experimental stimuli, comprised of 296 prime-target trials (148 experimental trials, 148 nonword trials). The stimuli were presented in a single block, and in a different random order for each subject. Each word was presented foveally in light grey upper-case letters (letter size: vertical, 1 cm; horizontal (mean), 0.5 cm) on a 15-inch computer monitor with a dark background. Words (primes and targets) were presented for 150 ms, with an ISI of 150 ms (SOA5300 ms), and an inter-trial interval of 1000 ms. Two small vertically aligned dark grey fixation dots were presented during the inter-stimulus and inter-trial intervals. Viewing distance was 100 cm. Subjects were tested individually in a dimly illuminated, sound-attenuated, and electrically shielded room. Following electrode application, subjects were instructed to fixate on the fixation points, silently read both the prime and target stimuli, and lift one index finger off a button as quickly as possible if the target was a legal Dutch word, and the other index finger if it was not a legal Dutch word. Which index finger (right / left) corresponded to which response was counterbalanced across subjects. Subjects

• Did you notice relationships of any kind between any of the words in the experiment? • Did you use any sort of strategy to do the task? • What do you think the experiment was investigating?

2.4. ERP recording The EEG was recorded from 37 sites using an electrode cap (Electro-Cap International). Electrodes were placed at the following sites [51]: Fz, Cz, Pz, POz, Oz, Fp1, Fp2, F3, F4, F7, F8, FC3, FC4, FT7, FT8, C3, C4, T7, T8, TP7, TP8, P3, P4, P7, P8, PO3, PO4, PO7, PO8, O1, O2, P9, P10, PO9, PO10, O9, O10. All scalp electrodes were referred to the electronic average of right and left earlobes. Vertical and horizontal EOGs were recorded via electrodes placed above and below the left eye, and on the outer canthus of each eye, respectively. Electrode impedance was reduced to less than 5 kV. The EEG and EOG recordings were amplified with a 10-s time constant and a 200-Hz low pass filter, sampled at 1000 Hz, digitally filtered with a lowpass cutoff frequency of 30 Hz, and reduced on-line to a sample frequency of 100 Hz.

2.5. Data analysis ERPs were averaged offline. A 1100-ms epoch of EEG data beginning 100 ms pre-stimulus was computed separately for each electrode location for each target type (visual–perceptually related prime, unrelated prime), and aligned to a 100-ms prestimulus baseline. Trials were excluded if invalidated by incorrect behavioural response, ocular artefact (vertical EOG .50 mV, horizontal EOG .30 mV), or out of range artefacts. A mean amplitude analysis of the N400 component was performed over the latency range 350–450 ms following the target. This epoch was chosen on the basis that previous N400 studies have shown this interval to be optimal for the measurement of N400 priming effects, while visual inspection of the waveforms confirmed the appropriateness of this latency range in the present paradigm. In addition, exploratory analyses were performed on mean amplitudes calculated over 50-ms windows from 0–350 to 450–1000 ms poststimulus to investigate any novel effects of visual–perceptual priming. Electrode sites were divided into midline (Fz, Cz, Pz,

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POz, Oz) and lateral (Fp1, Fp2, F3, F4, F7, F8, FC3, FC4, FT7, FT8, C3, C4, T7, T8, TP7, TP8, P3, P4, P7, P8, PO3, PO4, PO7, PO8, O1, O2, P9, P10, PO9, PO10, O9, O10) sets for analysis. Repeated measures ANOVAs were carried out on the mean amplitudes of the ERPs over the specified intervals for each set of sites with the following factors: • Midline: two levels of target stimulus type (visual– perceptually primed or unrelated prime; ‘Priming’ henceforth); and five levels of electrode site (‘Site’ henceforth). • Lateral: two levels of target stimulus type (visual– perceptually primed or unrelated prime; ‘Priming’); 16 levels of electrode site (‘Site’); and two levels of hemisphere (‘Hemisphere’ henceforth). The significance criterion used for the ANOVAs was P,0.05, with the degrees of freedom adjusted, when appropriate, by the Greenhouse–Geisser [13] procedure to avoid Type I errors through violation of the assumption of sphericity [54]. Mean reaction times and response accuracy were calculated for perceptually and unrelated primed targets separately and analysed using one-way repeated measures ANOVAs (P,0.05) to investigate priming effects. Only correct responses with a latency between 100 and 1150 ms were included.

3. Results

3.1. Behavioural data 3.1.1. Reaction time ( RT) and accuracy No significant differences between behavioural responses to perceptually primed and unrelated primed targets were observed in either the RT or accuracy data (see Table 2: priming main effect. RT, F[1,19]50.08, P50.784; Accuracy, F[1,19]50.32, P50.577). The rather low accuracy level probably reflects the difficulty of the task caused by the speed of presentation. 3.1.2. Post-experimental questionnaire No subjects reported awareness of any type of relation between the prime and target stimuli. Most subjects Table 2 Mean (S.D. in parentheses) reaction time (RT) and percent correct responses for target words preceded by a perceptually related or unrelated prime word Perceptually primed targets

Unprimed targets

RT

% Correct

RT

% Correct

654 (70)

88.7 (8.6)

653 (67)

88.1 (8.4)

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expressed surprise when told of the visual–perceptual semantic relations.

3.2. ERP data The grand average ERPs for visual–perceptually primed and unrelated primed targets, from the 37 scalp sites and vertical and horizontal EOG channels, are plotted in Fig. 1. The unusual morphology of the waveforms can be attributed to the overlapping epochs associated with the prime and target stimuli (SOA5300 ms). The most notable feature is a large negativity evident at most sites with an onset between 250 and 0 ms and peaking around 100 ms post-target-stimulus. The peak latency of this component (|400 ms post-prime-stimulus onset), and its centro-parietal maximum, are consistent with its categorisation as an N400 component elicited by the prime words. The absence of any difference between the amplitude and latency of this component elicited by visual–perceptual and unrelated primes suggests these prime stimuli were well matched. Otherwise, the waveforms are characterised by a more standard series of components, including a posteriorly maximal P1 / N1 complex (peaking at |120 and 180 ms, respectively), followed by a substantial P2 component evident across the whole scalp, with peak latency between 250 (posteriorly) and 280 ms (anteriorly). These components are followed at all but the most anterior sites by a negative component (N400) and / or a large positivity (P3 / SW complex) to the target stimuli. Finally, a late negativity onsetting around 800 ms is evident over left anterior sites for both target stimulus types.

3.2.1. 350 – 450 ms Fig. 1 shows that the latency range 350–450 ms captures the peak of a centro-posteriorly maximal negative deflection which resembles the N400 component observed in previous studies (e.g., Ref. [18]). This N400 component is clearly attenuated to visual–perceptually primed targets relative to unrelated primed targets. This observation was statistically confirmed in both the midline and lateral site analyses over this latency interval (Priming main effect. Midline, F[1,19]58.73, P50.008; Lateral, F[1,19]5 11.49, P50.003). Surprisingly, however, the centro-posterior distribution of this effect clearly evident in Fig. 1 was not reflected in the statistical analyses (Priming3Site interaction. Midline, F[4,76]50.80, GG50.443; Lateral, F[15,285]51.79, GG50.182). Although the N400 priming effects are often claimed to have a centro-parietal distribution, it is worth noting that this assertion is not always based on statistical evidence (e.g., Refs. [6,15]), making it difficult to compare this aspect of N400 priming effects between studies. 3.2.2. 0 – 350 ms and 450 – 1000 ms Only very small differences between the waveforms

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Fig. 1. (A) Grand average ERPs evoked at 37 scalp sites by visual–perceptually primed and neutrally primed targets. The plots are arranged to resemble their positions on the scalp. Negative is plotted upwards. (B) The midline parietal site Pz has been magnified to show the priming effect on the N400 component (350–450 ms).

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elicited by the visual–perceptually primed and unrelated primed targets can be identified over the intervals 0–350 and 450–1000 ms in Fig. 1. Consistent with this observation, no statistically reliable differences between the two target types were obtained in the 50-ms epoch analyses performed over these latency ranges.

4. Discussion The present experiment investigated visual–perceptual semantic priming, utilising both behavioural (RT) and ERP measures in a paired word semantic priming paradigm using a lexical decision task. Both the behavioural and ERP experimental results were simple and unambiguous: there was no evidence of visual–perceptual priming in the RT measure, while a robust N400 priming effect was observed. The lack of a RT priming effect does not confirm the hypothesis that a behavioural priming effect would be obtained when other conceptual semantic and / or associative relations were excluded from the experiment (without the use of a perceptual pre-activation task), thereby eliminating relatedness checking strategies which could mask perceptual priming effects. The absence of a RT priming effect is, however, consistent with recent evidence that robust visual–perceptual priming effects may only be reflected in RT measures when the salience of the visual semantic properties is increased within the experimental context [44]. This is a possibility the current experiment was explicitly designed to avoid. Although on the basis of the RT data alone it would be concluded that no visual–perceptual priming occurs in the lexical decision task under implicit processing conditions, the elicitation of a robust N400 priming effect precludes this interpretation. The N400 priming effect observed in the current experiment closely resembles previously reported N400 priming effects elicited by associatively and / or conceptually based semantic relations, in terms of scalp distribution, morphology, and latency. The similarity of the scalp distribution of the N400 visual–perceptual priming effect to that observed in priming studies based on associative and / or conceptual semantic relations, suggests that these different types of priming are supported by the same neural system or cognitive mechanism. Of course, this aspect of the data will remain at best suggestive, as comparisons depend on previously reported data rather than direct comparison within the same paradigm and subjects. The implication is, however, that the mechanism indexed by the amplitude of the N400 component in priming studies operates similarly regardless of the precise representational nature of the semantic relation involved. The visual–perceptual priming effect in the current paradigm demonstrates the sensitivity of the amplitude of the N400 component to a nonassociative semantic relation between incoming stimuli. The nonassociative semantic priming data of Hagoort et al. [15] has previously indicated

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that semantic similarity, or overlap of semantic properties, can elicit an N400 priming effect. The current result extends this assertion by showing that the N400 component indexes semantic similarity based semantic priming under more implicit processing conditions than those utilised by Hagoort et al. [15], and that the overlap of a single semantic property (global shape) is sufficient to support such priming.2 The N400 is sensitive to form relations between concepts, even when these are not made salient within the experimental context. In the current paradigm minimisation of the contribution of conscious strategic processing mechanisms was partially achieved by using a short SOA and excluding associated and / or conceptually related pairs, but the strongest control of the use of strategic processing was inherent in the obscure nature of the visual–perceptual semantic relations. No subjects were aware of the relations between the stimuli in the current experiment, so these relations could not have directed conscious strategic processing. Consequently, the N400 priming effect is argued to reflect implicit processes which are independent of conscious strategy and provide insight into the nature of the underlying semantic representations activated by concrete words in the context of the current paradigm. The present data therefore indicate that visual–perceptual semantic similarity can support such implicit priming, and that visual–perceptual semantic features are accessed during the processing of concrete nouns. A number of dissociations between the N400 and RT measures of semantic processing, such as that observed in the current experiment, have recently been reported in the literature, providing evidence that RT latency and N400 amplitude modulations reflect non-identical cognitive processes involved in priming [14,18,19,23]. Although precise definition of the differential nature of the processes indexed by RT and N400 awaits further delineation in the literature and is clearly beyond the scope of the present data, there are a number of interpretations which may be considered. For the current discussion we will make the simple assumption that the N400 priming effect reflects the increased ease with which a semantic representation is activated or integrated when some of its features or properties overlap with those of a previously activated concept (for discussion of the mechanisms underlying N400 priming effects, see Refs. [5,6,18,41]). One tempting interpretation is that while the N400 is sensitive to overlapping form-based aspects of representation, RT is not. This possibility is perhaps best examined within the dual coding framework of Paivio [42,43], which claims that semantic information is coded using both verbal and nonverbal or image-based systems. While words referring to concrete concepts, which by definition have a

2

In the Hagoort et al. (1996) study a long SOA was used, half the subjects saw the associated priming condition first, and the semantic relations were transparent to subjects.

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visual–perceptual semantic component, are proposed to subsequently invoke activation in the image-based system, the meaning of abstract words is represented only in the verbal system. According to dual coding theory, it is this additional activation of the image-based semantic system which explains the consistently observed processing advantage of concrete words over abstract words (‘concreteness effect’: e.g., Refs. [4,29,50]). Thus, in the current paradigm, the N400 amplitude modulation could reflect semantic priming within an image-based system, while RT reflects primarily verbally based processes associated with the lexical decision. This account is rendered somewhat unlikely, however, given that concreteness effects have previously been observed in RT for single-word lexical decision tasks (e.g., Refs. [9,24,49]), indicating that imagebased aspects of representation accessed during concrete word processing do influence RT lexical decision times. Nonetheless, it remains possible that interactions between the priming context and form-based aspects of representation in the current priming paradigm provided a unique set of processing conditions. A more parsimonious interpretation, in the light of the evidence that RT visual–perceptual semantic priming effects are only observed when visual semantic properties are made salient in the experimental context [44], might be that while the minimisation of such salience in the current paradigm indeed eliminated the processes reflected by the RT effect, the same was not true of the N400. If N400 amplitude reflects the degree of overlap of semantic feature representations which are stable across contexts, while the RT measure is sensitive to the degree of overlap between semantic features which have been activated (perhaps over a given threshold; see Ref. [44]), the observed dissociation between RT and N400 measures could result. This account posits that the N400 index of visual–semantic priming is insensitive to the relative accessibility of the semantic features comprising the representation of concepts, as determined by context. Despite the speculative nature of this interpretation, it would be interesting to test experimentally whether the amplitude of the N400 priming effect is modulated by contextual influences on relative attribute salience as has been shown to be the case for behavioural measures [8,30,44]. In summary, the current finding of an N400 visual– perceptual semantic priming effect in the lexical decision task, while not also reflected in RT, provides support for priming on the basis of this nonassociative semantic relation. This result indicates that visual–perceptual semantic attributes are activated during the reading of inanimate concrete nouns, and is consistent with models which propose that semantic knowledge is organised according to a semantic feature format. Furthermore, the data suggest that N400 amplitude can index a nonassociative semantic relation based on the overlap of a single semantic feature, and that this measure is sensitive to relations between form-based semantic representations.

The current paradigm was designed to examine implicit priming processes; however, further investigation of the degree of automaticity of the observed visual–perceptual semantic priming effect on the N400 component and its susceptibility to both conscious and unconscious strategic and contextual influences would aid in interpretation of the effect and delineating the processing nature of the N400.

Acknowledgements This research was supported by a grant from the Netherlands Organisation for Scientific Research (NWO) awarded to L. Stowe for the Pioneer Project ‘The Neurological Basis of Language’. We are grateful to Lidewei Houtman and Inne Bruinsma for assistance in constructing the stimuli, and Marjolijn Hovius and Juul Mulder for collection of the data. We would also like to thank Joop Clots for technical support.

References [1] D.A. Balota, R. Lorch, Depth of automatic spreading activation: mediated priming effects in pronunciation but not in lexical decision, J. Exp. Psychol.: Learn. Mem. Cogn. 12 (1986) 336–345. [2] L.W. Barsalou, Context-independent and context-dependent information in concepts, Mem. Cogn. 10 (1982) 82–93. [3] S. Bentin, G. McCarthy, C. Wood, Event-related potentials, lexical decision and semantic priming, Electroencephalogr. Clin. Neurophysiol. 60 (1985) 353–355. [4] F.A. Bleasdale, Concreteness-dependent associative priming: separate organization for concrete and abstract words, J. Exp. Psychol.: Learn. Mem. Cogn. 13 (1987) 582–594. [5] C. Brown, P. Hagoort, The processing nature of the N400: evidence from masked priming, J. Cogn. Neurosci. 5 (1993) 34–44. [6] D.J. Chwilla, P. Hagoort, C.M. Brown, The mechanism underlying backward priming in a lexical decision task: spreading activation versus semantic matching, Quart. J. Exp. Psychol. 51A (1998) 531–560. [7] D.J. Chwilla, H.H.J. Kolk, G. Mulder, Mediated priming in the paired lexical decision task: evidence from event-related potentials and reaction time, J. Mem. Lang. 42 (2000) 314–341. [8] C. Conrad, Some factors involved in the recognition of words, in: J.W. Cotton, R.L. Klatzky (Eds.), Semantic Factors in Cognition, Erlbaum, Hillsdale, NJ, 1978. [9] J. Day, Right-hemisphere language processing in normal righthanders, Quart. J. Exp. Psychol.: Hum. Percept. Performance 3 (1977) 518–528. [10] A.M.B. de Groot, Primed lexical decisions: combined effects of the proportion of related prime-target pairs and the stimulus-onset asynchrony of prime and target, Quart. J. Exp. Psychol. 36A (1984) 253–280. [11] I. Fischler, Associative facilitation without expectation in a lexical decision task, J. Exp. Psychol.: Hum. Percept. Performance 3 (1977) 18–26. [12] G.B. Flores d’Arcais, R. Schreuder, G. Glazenborg, Semantic activation during recognition of referential words, Psychol. Res. 47 (1985) 39–49. [13] S.W. Greenhouse, S. Geisser, On methods in the analysis of profile data, Psychometrika 24 (1959) 95–112. [14] P. Hagoort, Impairments of lexical-semantic processing in aphasia:

M.L. Kellenbach et al. / Cognitive Brain Research 10 (2000) 67 – 75

[15]

[16] [17]

[18]

[19]

[20]

[21] [22]

[23]

[24]

[25]

[26] [27] [28]

[29]

[30]

[31]

[32] [33]

[34]

evidence from the processing of lexical ambiguities, Brain Lang. 45 (1993) 189–232. P. Hagoort, C.M. Brown, T.Y. Swaab, Lexical-semantic event-related potential effects in patients with left hemisphere lesions with aphasia, and patients with right hemisphere lesions without aphasia, Brain 119 (1996) 627–650. J. Hodgson, Informational constraints on pre-lexical priming, Lang. Cogn. Proc. 6 (1991) 169–206. P.J. Holcomb, Automatic and attentional processing: an event-related potential analysis of semantic priming, Brain Lang. 35 (1988) 66–85. P.J. Holcomb, Semantic priming and stimulus degradation: implications for the role of N400 in language processing, Psychophysiology 30 (1993) 47–61. P.J. Holcomb, J. Kounios, Semantic memory: An ERP and reaction time analysis, in: C.H.M. Brunia, A.W.K. Gaillard, A. Kok (Eds.), Psychophysiological Brain Research, Tilburg University Press, Tilburg, The Netherlands, 1990, pp. 285–288. P.J. Holcomb, H.J. Neville, Auditory and visual semantic priming in lexical decision: a comparison using event-related potentials, Lang. Cogn. Proc. 5 (1990) 281–312. P.J. Holcomb, H. Neville, The electrophysiology of spoken sentence processing, Psychobiology 19 (1991) 286–300. M.L. Kellenbach, P.T. Michie, Modulation of event-related potentials by semantic priming: effects of color-cued selective attention, J. Cogn. Neurosci. 8 (1996) 155–173. J. Kounios, P.J. Holcomb, Structure and process in semantic memory: evidence from event-related brain potentials and reaction times, J. Exp. Psychol.: Gen. 121 (1992) 459–479. J. Kounios, P.J. Holcomb, Concreteness effects in semantic processing: ERP evidence supporting dual-coding theory, J. Exp. Psychol.: Learn. Mem. Cogn. 20 (1994) 804–823. M. Kutas, S.A. Hillyard, Event-related brain potentials to semantically inappropriate and surprisingly large words, Biol. Psychol. 11 (1980) 99–115. M. Kutas, S.A. Hillyard, Brain potentials during reading reflect word expectancy and semantic association, Nature 307 (1984) 161–163. M. Kutas, S.A. Hillyard, An electrophysiological probe of incidental semantic association, J. Cogn. Neurosci. 1 (1989) 38–49. R.F. Lorch, D.A. Balota, E.G. Stamm, Locus of inhibition effects in the priming of lexical decisions: pre- or postlexical access?, Mem. Cognit. 14 (1986) 95–103. M. Marschark, A. Paivio, Integrative processing of concrete and abstract sentences, J. Verbal Learn. Verbal Behav. 16 (1977) 217– 231. G. McKoon, R. Ratcliff, Conceptual combinations and relational contexts in free association and in priming in lexical decision and naming, Psychonomic Bull. Rev. 2 (1995) 527–533. T.P. McNamara, J. Altirriba, Depth of spreading activation revisited: semantic mediated priming occurs in lexical decisions, J. Mem. Lang. 27 (1988) 545–559. T.P. McNamara, D.L. Miller, Attributes of theories of meaning, Psychol. Bull. 106 (1989) 355–376. D.E. Meyer, R.W. Schvaneveldt, Facilitation in recognizing pairs of words: evidence of a dependence between retrieval operations, J. Exp. Psychol. 90 (1971) 227–234. H.E. Moss, W.D. Marslen-Wilson, Access to word meanings during spoken language comprehension: effects of sentential semantic context, J. Exp. Psychol.: Learn. Mem. Cogn. 19 (1993) 1254–1276.

75

[35] H.E. Moss, M.L. Hare, P. Day, L.K. Tyler, A distributed memory model of the associative boost, Connect. Sci. 6 (1994) 413–427. [36] H.E. Moss, R.K. Ostrin, L.K. Tyler, W.D. Marslen-Wilson, Accessing different type of lexical semantic information: evidence from priming, J. Exp. Psychol.: Learn. Mem. Cogn. 21 (1995) 1–21. [37] H.E. Moss, F. McCormick, L.K. Tyler, The time course of activation of semantic information during spoken word recognition, Lang. Cogn. Proc. 12 (1997) 695–731. [38] J.H. Neely, Semantic priming and retrieval from lexical memory: roles of inhibitionless spreading activation and limited-capacity attention, J. Exp. Psychol.: Gen. 106 (1977) 226–254. [39] J.H. Neely, Semantic priming effects in visual word recognition: a selective review of current findings and theories, in: D. Besner, G. Humphreys (Eds.), Basic Processes in Reading: Visual Word Recognition, Erlbaum, Hillsdale, NJ, 1991, pp. 264–336. [40] R.C. Oldfield, The assessment and analysis of handedness: the Edinburgh inventory, Neuropsychologia 9 (1971) 97–113. [41] L. Osterhout, P.J. Holcomb, Event-related potentials and language comprehension, in: M.D. Rugg, M.G.H. Coles (Eds.), Electrophysiology of Mind: Event-related Brain Potentials and Cognition, Oxford University Press, Oxford, 1995, pp. 171–215. [42] A.U. Paivio, in: Mental Representations: A Dual Coding Approach, Oxford University Press, New York, 1986. [43] A.U. Paivio, Dual coding theory: retrospect and current status, Can. J. Psychol. 45 (1991) 255–287. [44] D. Pecher, R. Zeelenberg, J.G.W. Raaijmakers, Does pizza prime coin? Perceptual priming in lexical decision and pronunciation, J. Mem. Lang. 38 (1998) 401–418. [45] L. Postman, G. Keppel, in: Norms of Word Associations, Academic Press, New York, 1970. [46] M.D. Rugg, The effects of semantic priming and word repetition on event-related potentials, Psychophysiology 22 (1985) 642–647. [47] M.D. Rugg, Dissociation of semantic priming, word and non-word repetition effects by event-related potentials, Quart. J. Exp. Psychol. 39A (1987) 123–148. [48] R. Schreuder, G.B. Flores d’Arcais, G. Glazenborg, Effects of perceptual and conceptual similarity in semantic priming, Psychol. Res. 45 (1984) 339–345. [49] P.J. Schwanenflugel, E.J. Shoben, Differential context effects in the comprehension of abstract and concrete verbal material, J. Exp. Psychol.: Learn. Mem. Cogn. 9 (1983) 82–102. [50] P.J. Schwanenflugel, K.K. Harnishfeger, R.W. Stowe, Context availability and lexical decisions for abstract and concrete words, J. Mem. Lang. 27 (1988) 499–520. ¨ [51] F. Sharbrough, G.E. Chatrian, R.P. Lesser, H. Luders, M. Nuwer, T.W. Picton, AEEGS guidelines for standard electrode position nomenclature, J. Clin. Neurophysiol. 8 (1991) 200–202. [52] J.R. Shelton, R.C. Martin, How semantic is automatic semantic priming?, J. Exp. Psychol.: Learn. Mem. Cogn. 18 (1992) 1191– 1210. [53] S.L. Thompson-Schill, K.J. Kurtz, J.D.E. Gabrieli, Effects of semantic and associative relatedness on automatic priming, J. Mem. Lang. 38 (1998) 440–458. [54] M.W. Vasey, J.F. Thayer, The continuing problem of false positives in repeated measures ANOVA in psychophysiology: a multivariate solution, Psychophysiology 24 (1987) 479–486. [55] J.N. Williams, Is automatic priming semantic?, Eur. J. Cogn. Psychol. 8 (1996) 113–161.