Véronique Boulenger

Nathalie Décoppet

Alice Roy

Yves Paulignan

Tatjana A Nazir
email: nazir@isc.cnrs.fr

Differential effects of Age-of-Acquisition for concrete nouns and action verbs: Evidence for partly distinct representations?

There is growing evidence that words that are acquired early in life are processed faster and more accurately than words acquired later, even by adults. As neuropsychological and neuroimaging studies have implicated different brain networks in the processing of action verbs and concrete nouns, the present study was aimed at contrasting reaction times to early and later-acquired action verbs and concrete nouns, in order to determine whether effects of word learning age express differently for the two types of words. Our results show that while word frequency affected both types of words in the same way, distinct learning age effects were observed for action verbs and concrete nouns. A further experiment specified that this difference was observed for verbs describing actions belonging to the human motor repertoire, but not for verbs denoting actions past this repertoire (e.g. to neigh). We interpret these data within a recently emerging framework according to which language processing is associated with sensory motor programs.

Introduction

Since the work of Carroll and White (1973ab), there is growing evidence that the age at which a word is acquired during childhood affects performance throughout life. Words that are acquired early in life are processed faster and more accurately than later-acquired words, even as factors such as frequency of usage and word imageability are controlled [START_REF] Barry | Naming the Snodgrass and Vanderwart pictures: Effects of age-of-acquisition, frequency and name agreement[END_REF][START_REF] Bonin | Age of acquisition and word frequency in written picture naming[END_REF][START_REF] Brown | First in, first out: Word learning age and spoken word frequency as predictors of word familiarity and word naming latency[END_REF][START_REF] Brysbaert | Word frequency affects naming latency in Dutch when age of acquisition is controlled[END_REF][START_REF] Morrison | Age of acquisition, not word frequency, affect object naming, not object recognition[END_REF][START_REF] Stadthagen-Gonzalez | Age of acquisition effects in lexical decision: Evidence from expert vocabularies[END_REF].

Though researchers differ in the way they precisely account for the underlying mechanisms of age of acquisition (AoA hereafter; for a review see [START_REF] Ghyselinck | Age of acquisition and the cumulative frequency hypothesis: a review of the literature and a new multi-task investigation[END_REF], there is a general agreement that these effects are the consequence of the way information is stored and accessed in the brain. According to recent theoretical accounts, AoA-effects could be characteristic of human learning in general and might reflect the gradual loss of plasticity in the learning system [START_REF] Ellis | Age of acquisition effects in adult lexical processing reflect loss of plasticity in maturing systems: Insights from connectionist networks[END_REF][START_REF] Ghyselinck | Age of acquisition and the cumulative frequency hypothesis: a review of the literature and a new multi-task investigation[END_REF][START_REF] Zevin | Age of acquisition effects in word reading and othertasks[END_REF]. In support of this hypothesis, connectionist models that employ distributed representations can simulate genuine AoA-effects, provided that learning patterns are introduced at different points into training, learning of early and late patterns is cumulative and interleaved [START_REF] Ellis | Age of acquisition effects in adult lexical processing reflect loss of plasticity in maturing systems: Insights from connectionist networks[END_REF][START_REF] Monaghan | What exactly interacts with spelling-sound consistency in word naming?[END_REF], and what is learned about one pattern does not entirely carry over to other patterns with which it shares structures [START_REF] Zevin | Age of acquisition effects in word reading and othertasks[END_REF].

In the present study, we determined AoA-effects for action verbs and concrete nouns that were acquired at different periods during childhood. Verbs and nouns play different semantic and syntactic roles in language. While nouns are pointer to objects, persons, places, things, or ideas, verbs generally refer to actions or states of being. In apparent conformity with this word class partition, neuropsychological studies have provided evidence that processing of nouns and verbs can be independently disrupted, suggesting that the two types of words may be represented in partly distinct neural substrates (Pulvermüller, 1999a;[START_REF] Shapiro | The representation of grammatical categories in the brain[END_REF]. Hence, while damage to frontal, motor-processing areas in the left hemisphere correlates more often with difficulties in processing action verbs, damage to left temporal regions correlates with difficulties in processing nouns [START_REF] Caramazza | Lexical organization of nouns and verbs in the brain[END_REF][START_REF] Damasio | Nouns and verbs are retrieved with differently distributed neural systems[END_REF][START_REF] Daniele | Evidence for a possible neuroanatomical basis for lexical processing of nouns and verbs[END_REF][START_REF] Miceli | On the basis for the agrammatic's difficulty in producing main verbs[END_REF][START_REF] Shapiro | Grammatical distinctions in the left frontal cortex[END_REF]. Electrophysiological [START_REF] Preissl | Evoked potentials distinguish between nouns and verbs[END_REF][START_REF] Pulvermüller | Nouns and verbs in the intact brain: Evidence from event-related potentials and high-frequency cortical responses[END_REF]) and neuroimaging studies with healthy subjects [START_REF] Martin | Discrete cortical regions associated with knowledge of color and knowledge of action[END_REF][START_REF] Perani | The neural correlates of verb and noun processing[END_REF][START_REF] Petersen | Positron emission tomography studies of the processing of single words[END_REF] further support this view by showing that different neural regions are active during processing of the two types of words.

More recent studies add to this picture by specifying that words designating actions performed with different body parts activate the premotor and motor cortex in a somatotopic manner, similar to movement execution (Hauk, Johnsrude & Pulvermüller, 2004a;Pulvermüller, 2005a;[START_REF] Tettamanti | Listening to action related sentences activates fronto-parietal motor circuits[END_REF]. By describing the spatio-temporal activity patterns during processing of words with different action-related meaning Pulvermüller and colleagues (Pulvermüller, Shtyrov & Ilmoniemi, 2005b) could further show that activity in these regions emerged within the first 200 ms following word onset, that is, almost immediately after first brain responses were observed in perisylvian language areas. Pulvermüller and colleagues interpreted these results within the frame of Hebbian learning principles [START_REF] Hebb | The organization of behavior. A neuropsychological theory[END_REF] following which action verbs could have meaning-related correlates in motor and premotor cortex because caretakers typically produce an action word to prompt children to execute the corresponding action [START_REF] Goldfield | Nouns before verbs in comprehension vs. production: the view from pragmatics[END_REF]. By contrast, words that represent objects (e.g., most of concrete nouns) could have meaning-related correlates in temporal visual areas because they often co-occur with visual percepts (Pulvermüller, 1999a[START_REF] Pulvermüller | The neuroscience of language: On brain circuits of words and serial order[END_REF]. In other terms, aspects of word meaning could be laid down by specific corticocortical links that evolve through correlation learning (Hauk et al., 2004a;[START_REF] Hauk | Neurophysiological distinction of action words in the fronto-central cortex[END_REF]Pulvermüller, 2005a) and this could explain the differential nature of neural representation for action verbs and concrete nouns.

If action verbs and concrete nouns do not make use of fully overlapping neural structures, AoA-effects could evolve differently for the two types of words [START_REF] Bogka | Object and action picture naming in English and Greek[END_REF][START_REF] Bonin | Psycholinguistic norms for action photographs in French and their relationships with spoken and written latencies[END_REF][START_REF] Colombo | The influence of age of acquisition, root frequency and context availability in processing nouns and verbs[END_REF][START_REF] Morrison | Age of acquisition, ageing, and verb production: Normative and experimental data[END_REF]. The purpose of the present study was to contrast reaction times to early and later-acquired action verbs and concrete nouns in order to determine whether the hypothesized difference in cortical representations could be noticed in participants' performance. Distinct AoA-dependent reaction time profiles (i.e., difference in reaction time slopes when plotted as a function of AoA) for action verbs and concrete nouns would support such a view.

To test this possibility, we first established AoA ratings for a set of action verbs and concrete nouns following a procedure that has been shown to be a valid index of real word learning age [START_REF] Bonin | Age of acquisition and word frequency in written picture naming[END_REF][START_REF] Morrison | Age of acquisition norms for a large set of object names and their relation to adult estimates and other variables[END_REF]. As imageability of action verbs and concrete nouns generally differs, we also established ratings for word imageability.

We then proposed a visual lexical decision task for two classes of target words and determined reaction time profiles as a function of rated AoA.

Subjective ratings of AoA and word imageability

Participants

Twenty-five volunteers (between 19 and 28 years old) performed AoA ratings and twentytwo volunteers (between 18 and 26 years old) imageability ratings. All participants were native French speakers and had intact or corrected vision.

Materials

Three hundred and six words (153 verbs and 153 nouns) were selected from the French lexical database "Lexique" [START_REF] New | Une base de données lexicales du français contemporain sur internet: LEXIQUE[END_REF]. Verbs, all in infinitive form, denoted actions that could be performed with arms/hands, legs or mouth. Nouns, all in singular form, referred to imageable, concrete entities. Words that stand for nouns as well as verbs were excluded from the list. Verbs and nouns were matched one-to-one for relevant lexical variables (see Supplementary Methods 1).

Procedure

Following the procedure proposed by [START_REF] Gilhooly | Methods and designs: Age of acquisition, imagery, concreteness, familiarity, and ambiguity measures for 1,944 words[END_REF], participants were asked to estimate the age at which they thought to have acquired the meaning of the words on a seven-point scale (with 1 = [0-2 years old], 2 = [3-4 years old], etc., and 7 = [older than 13]).

For word imageability estimations, participants were asked to evaluate the ease with which they could create an image of the concept referred to by the word. Rating was performed on a seven-point scale (with 0 = impossible and 6 = very easy). The total of 306 verbs and nouns were presented in booklets of four pages with random and different order for each participant.

Results

AoA and imageability-scores were determined for each word item by averaging ratings over all participants. Table 1 plots results for verbs and nouns. The data show that action verbs were rated as acquired earlier than nouns and were significantly less imageable than nouns.

Table 1 (about here)

A subset of 30 early and 30 later-acquired target verbs and 30 early and 30 later-acquired target nouns, for which word frequency and imageability were controlled, were selected from the initial pool of 306 items (see Appendix). As the initial pool of verbs and nouns differed considerably in terms of mean AoA and imageability, these variables could only be equated within, but not between the two groups of words (see Supplementary Methods 2). This is not problematic, however, as we were looking for differences in reaction time slopes between groups. To verify whether surface features such as the systematic ending of French verbs with "-er" may allow distinguishing the two groups of words prior to more advanced word processing, the same target words were also analyzed according to word frequency (low and high). If word frequency has comparable effects on reaction time for verbs and nouns, this proviso can be discarded. Unfortunately, when regrouped according to word frequency, the selected pool of target words could not be matched on all relevant lexical variables. For this reason, an additional subset of 152 low and higher frequency control-words was selected matched on all variables but word-and lemma frequency.

Lexical decision experiment

Participants

Twenty volunteers (10 women and 10 men), aged from 22 to 29 years old, participated in the lexical decision task. All were native French speakers and had normal or corrected to normal vision. Right-handedness was determined with the Edinburgh inventory (scores between 0.63 and 0.94; [START_REF] Oldfield | The assessment and analysis of handedness: the Edinburgh Inventory[END_REF]. None of the participants took part in the previous ratings of AoA or imageability.

Materials

The experimental stimuli consisted of the entire set of 306 words described earlier.

Furthermore, 306 pseudo-words, constructed by changing one letter from real nouns or real verbs, were added to perform the lexical decision task. Hence, pseudo-words were either "pseudo-nouns" or "pseudo-verbs" and were all pronounceable. Pseudo-words were matched to words for lexical variables (see Supplementary Methods 1). We also carefully matched verbs and pseudo-verbs for endings, such that as many verbs as pseudo-verbs (130 out of 153) ended with "-er", to prevent it from serving as discriminating feature. All items were presented in lower case.

Procedure

Stimuli were displayed at the center of the screen of a Macintosh monitor, using Psyscope software. A central fixation cross was presented for 500 ms. The stimulus appeared immediately following the offset of the fixation cross and remained on the screen until participant indicated by a button press whether the stimulus was a word or not. Participants were instructed to respond as quickly and accurately as possible. Stimulus presentation was randomized and a short break occurred half way through the experiment. A training phase consisting of 10 words and 10 pseudo-words (different from the experimental stimuli) preceded the experiment. Accuracy and response latencies were recorded.

Results

Trials with reaction times below or above 2.5 standard deviations from individual means (calculated over the entire set of 306 words) were excluded from the analysis (a total of 2.25% trials). Accuracy and response latencies for nouns, verbs, pseudo-nouns and pseudo-verbs were first calculated individually and were then averaged over all participants. a) For the set of 306 words A first analysis of variance by subject (ANOVA) over the entire set of 306 words and 306 pseudo-words revealed significant longer reaction times for pseudo-words than for words (677 ms vs. 601 ms respectively, [F (1,19) = 46.692; p < .0001]). Furthermore, despite the strict control for word-, bigram-, and trigram frequency, mean reaction times for nouns (611 ms) were significantly longer than for verbs (591 ms; [F (1,19) = 8.856; p = .0078]). A similar pattern was found for the percentage of errors (4.41% vs. 2.68% respectively; [F (1, 19) = 9.378; p = .0064]). Simple regression analyses showed that, when reaction times were plotted as a function of AoA, the slope parameter and coefficient of determination (R 2 ) were greater for nouns (slope = 24.17, R 2 = .3247, p < .0001) than for verbs (slope = 15.39, R 2 = .1833, p < .0001). Plotted as a function of word-and lemma frequency, however, the difference between the two groups of words was mainly on axis intercept (word frequency: slope = -19.55, R 2 = .2584, p < .0001 for nouns, and slope = -14.48, R 2 = .2142, p < .0001 for verbs; lemma frequency: slope = -12.74, R 2 = .1389, p = .0014 for nouns, and slope = -15.81, R 2 = .1935, p = .0025 for verbs). Finally, when reaction times were plotted as a function of imageability, the slope parameter and coefficient of determination were also greater for nouns (slope = -27.45, R 2 = .1925, p < .0001) than for verbs (slope = -14.58, R 2 = .0508, p = .0051).

To disentangle the effects of the different variables, we performed multiple regressions accompanied by hierarchical analyses using mean reaction time as dependent variable and seven independent variables: bigram and trigram frequency, number of syllables, number of letters, imageability, word frequency, and AoA. These analyses showed that while word frequency significantly predicted performance for both nouns and verbs, AoA was a significant predictor of reaction time only for nouns. Imageability did not explain additional variance in either case (for details see Supplementary Results). b) For the subset of 2*60 early and late acquired words show that whereas AoA-effects were obtained for nouns, no such effect was observed for verbs. The slope parameter and coefficient of determination (R 2 ) were about three times larger for nouns than for verbs (Figure 1d). By contrast, effects of word frequency were comparable for both word categories (Figure 1e andf). Given that word frequency had the same effect on verbs and nouns, differential AoA-effects cannot be attributed to factors that occur prior to word processing. Multiple regression analyses (see Supplementary Results) confirmed this conclusion by showing a significant effect of word frequency in all cases, but a significant effect of AoA only for target nouns. Imageability did not explain additional variance.

Figure 1 (about here)

General discussion

The present study shows that while word frequency has the same effect on lexical decision time for concrete nouns and action verbs, AoA has not. Reaction times to early-acquired concrete nouns are generally faster than to later-acquired nouns, whereas no significant effect of AoA is evident for action verbs. It is important to note here that AoA-effects for verbs had been obtained in other studies, especially when using tasks that required word production (e.g., word or picture naming, Bogka et al., 2003 for English and Greek;Bonin et al., 2004 for French;[START_REF] Colombo | The influence of age of acquisition, root frequency and context availability in processing nouns and verbs[END_REF] for Italian; Morrison et al., 2003 for English). Hence, the present results should not be interpreted as demonstrating that there is no AoA-effect on performance for verbs. Effects of AoA may show up differently depending on task requirements, because different tasks are probing different aspects of word processing (e.g. phonological output lexicon in word production tasks vs. input stages in lexical decision tasks; Ghyselink et al., 2004). What we illustrate here is simply that with the same task and participants, estimated age of word learning affects performance differently for action verbs and concrete nouns. This difference is suggestive of the assumption that at some levels of processing, the way in which information is stored and accessed in the brain may differ for the two types of words.

As mentioned in the introduction, cortical motor regions are activated during processing of action-related language (Boulenger, Roy, Paulignan, Déprez, Jeannerod & Nazir, in press; [START_REF] Buccino | Listening to action-related sentences modulates the activity of the motor system: a combined TMS and behavioural study[END_REF]Hauk et al., 2004ab;[START_REF] Oliveri | All talk and no action: a transcranial magnetic stimulation study of motor cortex activation during action word production[END_REF]Pulvermüller et al., 2005b;Pulvermüller, Hauk, Nikulin, & Ilmoniemi, 2005c;[START_REF] Shtyrov | Distributed neuronal networks for encoding category-specific semantic information: the mismatch negativity to action words[END_REF][START_REF] Tettamanti | Listening to action related sentences activates fronto-parietal motor circuits[END_REF]. In a recent study, we could show that this language-related motor activity is significant to a point that it can interfere with the concurrent execution of overt motor behavior (Boulenger et al., in press). Hence, fine-grained analyses of movement kinematics revealed that, within the first 200 ms following word/movement onset, encoding of (arm) action verbs interfered with the concurrent execution of an arm reaching movement, in that it delayed the wrist acceleration peak (relative to nouns with no specific motor associations) by approximately 20 ms. We interpreted this finding in terms of competition between motor and language tasks for common resources, thus supporting the view that neural representation of action words involves cortical motor regions [START_REF] Buccino | Listening to action-related sentences modulates the activity of the motor system: a combined TMS and behavioural study[END_REF]Hauk et al., 2004ab;Pulvermüller, 2005a). On this background, we speculate that the absence of AoA-effects for action verbs in our present study may result from a failure to capture real learning-age by subjective AoA-estimations of the verbal form of verbs because the organization of neural representation for action verbs may also depend on developing motor behavior. In other terms, rated AoA did not affect performance for action verbs because our early and lateracquired items may not actually differ in learning-age if this motor component were properly controlled.

To substantiate this claim, we conducted an additional lexical decision experiment using verbs that do not contain such a motor component. In line with Buccino et al. [START_REF] Buccino | Neural circuits involved in the recognition of actions performed by nonconspecifics: an fMRI study[END_REF]; see also [START_REF] Mason | Thinking about actions: the neural substrates of person knowledge[END_REF] who showed that distinct brain regions are active during observation of motor actions common to humans and animals (i.e. biting) and motor actions that are specific to animals (i.e. barking), we hypothesize that AoA-effects for verbs may become evident more readily if we use verbs that describe actions that do not belong to the human motor repertoire. Our second experiment thus included early and late acquired verbs designating actions, which were either specific to animals (i.e. neigh; n=18) or specific to humans (i.e. knead; n=18; see Supplementary Methods 3 for experimental details). The results of this experiment are given in Figure 2. Though this data should be interpreted with caution as it is based on a restricted number of words, it replicates the results of the first experiment in showing no effect of rated AoA for verbs denoting actions belonging to the human motor repertoire. However, for verbs denoting actions that do not belong to this repertoire, rated AoA affected performance in much the same way as it did for concrete nouns.

Figure 2 (about here)

Conclusion

The result of our first experiment shows that rated AoA has a different effect on lexical decision for concrete nouns and action verbs. This result thus lends credibility to the view that the two types of words may be represented in partly distinct neural substrates (Pulvermüller, 1999a;[START_REF] Shapiro | The representation of grammatical categories in the brain[END_REF]. The result of our second experiment further specifies that these differential effects occur only for verbs that describe actions belonging to the human motor repertoire. If we accept as general rule that AoA affects performance [START_REF] Ellis | Age of acquisition effects in adult lexical processing reflect loss of plasticity in maturing systems: Insights from connectionist networks[END_REF][START_REF] Ghyselinck | Age of acquisition and the cumulative frequency hypothesis: a review of the literature and a new multi-task investigation[END_REF][START_REF] Zevin | Age of acquisition effects in word reading and othertasks[END_REF], the absence of AoA-effects for verbs denoting human actions indicates that subjective estimations of the age at which the verbal form of these words were acquired may not capture real learning-age. The failure of capturing learning-age for these verbs by means of subjective estimations may simply be due to difference in the ease of this estimation for nouns and action verbs (e.g., it could be more difficult to rate the age at which we acquired the verbal form of action verbs than of concrete nouns). Alternatively, however, this difference may result from existing links between language processes and sensory and motor programs (Boulenger et al., in press;[START_REF] Lieberman | On the nature and evolution of the neural bases of human language[END_REF][START_REF] Martin | Discrete cortical regions associated with knowledge of color and knowledge of action[END_REF]Pulvermüller, 1999aPulvermüller, , 2005a;;[START_REF] Tettamanti | Listening to action related sentences activates fronto-parietal motor circuits[END_REF]. If the neural representations of verbs that describe human actions involve cortical motor regions, the age at which this representation sets may depend on developing motor behavior and may not be captured by estimations of AoA of the verbal form only.

Authors'note

We would like to thank three anonymous reviewers for helpful comments on an earlier version of this article. (a) Target words.

Figure

  Figure 1a plots mean reaction time for the group of early and late acquired target words.

Figure

  Figure 1b plots mean reaction time for the same items when organized as a function of word frequency, and Figure 1c plots the data for the subset of 152 control-words. The lower panel of Figure 1 (d-f) gives the corresponding scatterplots and simple regression analyses. Results

Figure 2 :

 2 Figure 2: Left panel: Mean reaction time for verbs denoting actions specific to animals and to

  Figure1

Table 1 :

 1 Tatjana A. Nazir is a member of the Marie Curie Research and Training Network: Language and Brain (RTN: LAB) funded by the European Commission (MRTN-CT-2004-512141) as part of its "Sixth Framework Program". Mean values of word frequency, rated AoA, and rated imageability for the 306

		Appendix
		Target words used in Experiment 1
			NOUNS	LETT SYLL FQ	LEM	BIGR	TRIG	AoA IMAG
			algue	5	1	1,81 14,91	1433,2	140,62	4	5,23
			alouette	8	3	1,71	3,1	2139,55	356,21	4,04	3,36
			bâtiment	8	3 19,26 45,91	2565,18	807,14	4,2	5,00
			bordure	7	2	8,65	9,68	3814,2	392,42	4,08	3,14
			cabine	6	2 16,35 20,03	2548,7	341,33	3,92	4,14
			casier	6	2	3,16	6,84	5375,81	328,88	4,08	4,32
			caverne	7	2	4,9	9,09	2999,25	412,82	3,72	4,86
			cerisier	8	3	1,68	2,91	6076,53	479,05	4,04	5,55
			dindon	6	2	0,94	1,42	4158,66	43,2	4,08	5,00
			étable	6	2	5,39	7,2	4094,23	1665,8	3,92	4,32
			étagère	7	3	4,74	8,64	3647,75	1353,76	3,92	5,55
	EARLY-ACQUIRED WORDS	flocon grenier hélice hibou hotte igloo koala limace	6 7 6 5 5 5 5 6	2 2 13,68 1,1 2 4,42 2 1,48 1 1,77 2 0,03 3 0,06 2 1,97	5,1 17 5,94 1,96 1,93 0,13 0,06 3,13	1898,56 3922,9 1347,87 1129,82 4705,12 408,86 830,73 2008,57	177,65 612,65 184,38 70,6 883,37 0,34 19,6 195,68	3,16 3,6 4,12 2,76 3,12 3,6 4,04 3,08	5,27 4,68 5,18 5,64 4,41 5,77 5,55 5,45
			mairie	6	2 10,16	11,1	7211,44	1712,29	4,2	5,27
			moquette	8	2	7,97	8,84	2650,77	339,62	3,12	4,82
			panda	5	2	0,06	0,06	9829,56	490,58	3,32	5,77
			panneau	7	2 12,16 24,26	7099,81	527,75	3,24	5,32
			prairie	7	2	9,29 20,26	6623,51	663,49	3,6	5,14
			préau	5	2	1,97	2,87	3854,63	868,27	3,16	4,18
			rosier	6	2	1,16	3,19	3269,42	240,26	4,08	5,09
			ruche	5	1	1,97	3,2	1443,66	443,07	3,92	5,18
			vaisseau	8	2	6,16 14,93	5042,73	1769,35	3,8	4,32
			vipère	6	2	2,06	3,32	3307,5	122,96	3,76	5,09
			virage	6	2	5,94	8,68	3063,64	336,67	3,76	5,09
			auberge	7	2	9,71 12,32	3713,96	124,84	4,8	4,77
	LATE-ACQUIRED	WORDS	baobab barreau bécane bélier buffet	6 7 6 6	3 2 2 2	0,42 2,87 12,26 0,65 2,1 2,58 0,55 1,26	761,13 5837,49 2296,35 2716,51	58,97 586,01 4,44 6 157,76 5,56 338,99 4,68	4,00 4,82 4,05 5,18

Figure 1: Upper panel: Mean reaction time for early and late acquired target nouns and verbs plotted as a function of (1a) AoA and (1b) word frequency. Result for the subset of 152 control items is plotted as a function of frequency in (1c). ANOVAs by subjects are reported in the figures ((*) = significant; (ns) = non significant). Lower panel: Corresponding scatterplots with regression analyses, coefficient of determination (R 2 ) and p-values. Nouns = black circles; verbs = grey circles.

1,58) = 56.634; p < .0001] [F(1,58) = 11.975 ; p = .0011]

  The same words as in (a) when grouped as a function of word frequency.

	NOUN	AoA	FQ		LEM	IMAG		LETT	BIGR	TRIG SYLL
	Early
	(n=30)	3.71	5.07		9	4.92		6.26	3617	533	2
	Late
	(n=30)	5.02	5.07		8	4.62		6.06	3931	609	2
	Statistics	[F(1,58) = 107,68; p <
		.0001]	ns		ns	ns		ns	ns	ns	ns
	VERB	AoA	FQ		LEM	IMAG		LETT	BIGR	TRIG SYLL
	Early
	(n=30)	3.03	5.02		34.71	4.23		6.66	3711	496	2.37
	Late
	(n=30)	4.54	4.7		42	4.08		6.13	4675	470	2
	Statistics	[F(1,58) = 98.397; p <
		.0001]	ns		ns	ns		ns	ns	ns	ns
	(b) NOUN	AoA	FQ		LEM	IMAG		LETT	BIGR	TRIG SYLL
	Low (n=30) 4.39	1.34		2.89	4.85		5.86	3023	316	2.1
	High (n=30) 4.34	8.79		13.81	4.68		6.46	4524	825	2
	Statistics	ns	[F(1,58) = 55.938 ; p < .0001]	[F(1,58) = 39.600 ; p < .0001]	ns	[F(1,58) = 6.4005 ; p = .0141]	[F(1,58) = 63.869 ; p = .0142]	[F(1,58) = 10.593 ; p = .0019]	ns
	VERB	AoA	FQ		LEM	IMAG		LETT	BIGR	TRIG SYLL
	Low (n=30)	4	1.44		19.13	4.17		6.46	4004	449	2.26
	High (n=30) 3.56	8.27		57.90	4.14		6.33	4381	515	2.3
	Statistics	ns	[F(ns		ns	ns	ns	ns
	(c) The 152 control-words.
	NOUN	AoA	FQ		LEM	IMAG	LETT BIGR TRIG SYLL
	Low (n=38)	3.6	2.5		4.8	5.2		6.3	4036	631	2
	High (n=38)	3.6	13.2		19.8	5.2		6.7	4229	586	2
	Statistics		[F(1,74) =		[F(1,74) =
			125.95; p <	65.52; p <
		ns	.0001]		.0001]	ns		ns	ns	ns	ns
	VERB	AoA	FQ		LEM	IMAG	LETT BIGR TRIG SYLL
	Low (n=38)	3.7	2.5		24	4.1		6.4	3877	390	2.3
	High (n=38)	3.5	12.6		72.4	4.1		6.6	4263	507	2.2
	Statistics		[F(1,74) =		[F(1,74) =
			53.65; p <		21.39; p <
		ns	.0001]		.0001]	ns		ns	ns	ns	ns

12,19 13,54 840,36 89,52 4,6 4,91

Note that we included word-rather than lemma frequency as independent variable, since the simple regression analyses for the set of 306 words showed stronger effect of word-than of lemma frequency on performance for the two word categories.

Supplementary Methods 1

Lexical statistics for the set of 306 words and pseudo-words used in Experiment 1 Mean values of word frequency (FQ), lemma frequency (LEM), length in letters (LETT), bigram frequency (BIGR) and trigram frequency (TRIG), and analyses of variance (ANOVA) by item, for nouns, verbs and pseudo-words. Note: lemma frequency could not be matched between the two classes of words, but the simple regression analysis below reveals a high correlation between lemma-and word frequency (which was controlled) for the two word categories. for verbs designating actions specific to animals and to humans with different mean AoA. Word age of acquisition was controlled with empirical ratings of 15 subjects on a seven-point scale (according to [START_REF] Gilhooly | Methods and designs: Age of acquisition, imagery, concreteness, familiarity, and ambiguity measures for 1,944 words[END_REF]; 1 = [0-2] and 7 = [older than 13 years old]). Word imageability was evaluated in the same way by another group of 15 subjects (with 0 = impossible and 6 = very easy to generate a mental image of the word). Note that imageability could not be matched between early and late-acquired items for the two conditions. However, it was higher for early than for late-acquired items for both subcategories of verbs (difference of 1 and 1.11, respectively).

NOUNS VERBS

ANIMALS

Supplementary Results

Multiple regressions analyses for words used in Experiment 1.

Multiple regressions with hierarchical analysis using mean reaction time as dependent variable and the seven following independent variables


Tatjana A Nazir
email: nazir@isc.cnrs.fr

Véronique Boulenger

Alice Roy

Beata Silber

Marc Jeannerod

Yves Paulignan

Language-induced motor perturbations during the execution of a reaching movement

 found that processing action verbs assisted reaching movement when the word was processed prior to movement onset, and interfered with the movement when the word was processed at movement onset. The present study aimed to further corroborate the existence of such cross talk between language processes and overt motor behavior by demonstrating that the reaching movement can be disturbed by action words even when the words are presented delayed with respect to movement onset (50 ms and 200 ms). The results are compared to studies that show language-motor interaction in conditions were the word is presented prior to movement onset and are discussed within the context of embodied theories of language comprehension.

Introduction

Recent brain imaging studies have revealed that within 150-200 ms following the onset of a spoken word which denotes human body actions, a short-living cortical activity is observed outside the classical language areas in regions that have generally been associated with motor control (Pulvermüller, Shtyrov & Ilmoniemi, 2005a; see also Hauk & Pulvermüller, 2004a). This language-induced cortical motor activity follows the somatotopy of motor actions in that words referring to actions involving the face, for instance, activate inferior frontocentral regions, while words referring to actions involving the leg activate superior central sites (Pulvermüller, Hauk, Nikulin, & Ilmoniemi, 2005b; see also [START_REF] Hauk | Somatotopic representation of action words in human motor and premotor cortex[END_REF]Pulvermuller, 2004b and[START_REF] Tettamanti | Listening to actionrelated sentences activates fronto-parietal motor circuits[END_REF]. Studies using transcranial magnetic stimulation (TMS) corroborate this findings by indicating that processing action-related words or sentences alters the excitability of the left but not the right motor cortex, and modulates reaction times when the motor response and the words call the same effector [START_REF] Buccino | Listening to action-related sentences modulates the activity of the motor system: a combined TMS and behavioral study[END_REF][START_REF] Meister | Motor cortex hand area and speech: implications for the development of language[END_REF]Olivieri et al., 2004;Pullvermüller et al., 2005b). This languageinduced activity in cortical motor regions is believed to reflect early automatic processes involved in word meaning access and is therefore taken to suggest that neural systems for action are also involved in the perception of language [START_REF] Pulvermüller | Brain mechanisms linking language and action[END_REF]. Their exact functional role for language, however, remains largely underspecified (see [START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF][START_REF] Mahon | The orchestration of the sensory-motor systems: Clues from neuropsychology[END_REF] for discussion).

To show that language-induced cortical motor activity reflects behaviorally relevant processes, Boulenger and colleagues [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF] recently developed a paradigm that allowed measuring the effect of action word processing on the execution of a reaching movement. The underlying assumption of their study was that if processing of action words recruits cortical regions that are also involved in the programming and execution of actions, processing these words should interfere with overt motor behavior when the two tasks are performed concurrently. Fine-grained analyses of movement kinematics of reaching movements revealed that this assumption was correct. When visual words were processed prior to the reaching movement, that is, when the word-display triggered the movement, action words assisted the ensuing movement in that the latency of the wrist acceleration peak appeared earlier when the word was an action verb than when it was a concrete noun.

However, when movement onset triggered the word-display, action verbs interfered with the concurrent reaching movement, i.e., the latency and amplitude of the wrist acceleration peak appeared later and was smaller, respectively, when the word was a verb relative to a noun. These interference effects were observed within less than 180 ms following word onset, which is the limit within which lexicosemantic processes are typically noticed (e.g. word frequency effects or effects of word category; [START_REF] Pulvermüller | Nouns and verbs in the intact brain: Evidence from event-related potentials and high-frequency cortical responses[END_REF][START_REF] Pulvermüller | Brain reflections of words and their meaning[END_REF][START_REF] Preissl | Evoked potentials distinguish between nouns and verbs[END_REF][START_REF] Sauseng | When does the brain register deviances from standard word spellings? An ERP study[END_REF][START_REF] Sereno | Establishing a time-line of word recognition: evidence from eye movements and event-related potentials[END_REF][START_REF] Sereno | Measuring word recognition in reading: eye movements and event-related potentials[END_REF]. The short delay within which language-induced motor effects were observed and the fact that cross-talk between language and motor tasks switched from facilitation to interference when action words were processed concurrently to the movement, suggest that cortical motor regions are not merely activated as consequence of word recognition but are indeed recruited during word encoding [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF].

Evidences for cross-talk between language processes and motor actions are actually abundant in the literature (e.g., [START_REF] Gentilucci | Influence of automatic word reading on motor control[END_REF][START_REF] Gentilucci | Language and motor control[END_REF][START_REF] Gentilucci | Object motor representation and language[END_REF][START_REF] Glenberg | Grounding language in action[END_REF][START_REF] Glover | Grasping the meaning of words[END_REF][START_REF] Tucker | Action priming by briefly presented objects[END_REF][START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF]. Among the first to report such effects were Gentilucci and colleagues who showed that printed words on an object modulate the movement directed to that object [START_REF] Gentilucci | Influence of automatic word reading on motor control[END_REF]. Hence, when participants were required to grasp a wooden block on which the word 'long' was printed, larger maximum grip aperture was observed compared to a condition where the word 'short' was printed on the same wooden block. [START_REF] Glover | Grasping the meaning of words[END_REF] showed similar effects when using printed words that described large (e.g., apple) or small (e.g., grape) graspable objects.

Note though that these studies measured effect of language processing on motor action in conditions where words were presented prior to movement onset, which is thus comparable to the condition in [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF] where action words were shown to facilitate the ensuing reaching movement. Yet, presenting words prior to movement onset does not allow excluding that the observed cross-talk between language processes and motor actions occurs subsequent to word encoding. What we are aiming at, by contrast, is establishing that cortical motor regions are recruited during (and not after) language perception. For this, it is essential to show that processing action words interferes with a movement almost instantly following word onset because this limits the possibility that language-induced motor activity stems from processes that arise after the word has been identified (see [START_REF] Pulvermüller | Brain mechanisms linking language and action[END_REF] for related arguments). We will come back to this point later.

The aim of the present study is to test whether language-induced motor interferences such as reported in [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF] can also be observed when words are displayed after the movement has started. Although it is known that large parts of the motor program that underlie a movement are computed prior to movement onset, cortical motor activity is observed all along the motor action (see [START_REF] Riehle | Preparation for action: one of the key functions of the motor cortex[END_REF] for a review of single cell studies in monkeys). Figure 1a schematically plots three main types of neurons recorded in the monkey brain that are encountered during movement preparation and execution [START_REF] Riehle | Preparation for action: one of the key functions of the motor cortex[END_REF]. The vertical line on the left side denotes a signal that tells the animal to prepare for the movement and the second vertical line indicates the "go" signal following which the movement is executed. The upper panel of the figure shows activity of neurons that are involved in movement preparation only, the mid-panel shows activity of neurons that are involved in movement preparation as well as in movement execution, and the bottom panel shows pure execution related neurons. Figure 1b plots the relative distribution of these three types of neurons in the sensory (S1), parietal (PA), primary motor (M1) and premotor cortex (PM). As evident from this schema, the majority of movement-related neurons sustain their activity from the preparation signal to the end of the movement. Assuming that similar relations hold for human primates (see [START_REF] Georgopoulos | Neural aspects of cognitive motor control[END_REF], processing action-related language at any time between movement preparation and the end of a movement should thus interfere with overt motor behavior.

We will test this hypothesis by determining the impact of action word processing on a concurrent reaching movement when the word is displayed delayed by either 50 ms or 200 ms with respect to movement onset. Besides substantiating our previous finding [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF], this study was also aimed at determining whether fine-grained analysis of movement kinematics can be used as online measure of language-induced motor effects, in a similar way as evoked-response potentials (ERPs) are used for exploring cognitive tasks. If so, this paradigm could serve more sophisticated linguistic experiments using sentences, for instance, (that could be displayed along the movement) in order to determine whether language-induced motor effects are modulated by the sentence context or are simply limited to the verb itself.

Method

Participants

Nine French native volunteers participated in each of the two delay-conditions.

All were right-handed as measured by the Edinburgh Inventory [START_REF] Oldfield | The assessment and analysis of handedness: the Edinburgh Inventory[END_REF], and had normal or corrected-to-normal vision. None of the volunteers participated in both experiments.

Stimuli

The stimuli used in this experiment were exactly the same stimuli used in the study by [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF]. Eighty-four words (42 verbs and 42 nouns) were selected from the French lexical database "Lexique" [START_REF] New | Une base de données lexicales du français contemporain sur internet : LEXIQUE[END_REF]. Verbs were all in the infinitive form and denoted actions performed either with the hand/arm, leg, or mouth/face (e.g. paint, jump, cry). Nouns were all in singular form and referred to imageable, concrete entities that cannot be manipulated (e.g. star, cliff, meadow). Words that could be used as both nouns and verbs were excluded from the selection. Stimuli were matched for relevant lexical variables including word frequency, length in letters, number of syllables, biand trigram frequency, and number and cumulative frequency of orthographic neighbors (for details see [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF]. Word age of acquisition was also controlled using empirical ratings performed by 20 volunteers on a seven-point scale (1 = [0-2 years] and 7 = [older than 13 years]; [START_REF] Gilhooly | Methods and designs: Age of acquisition, imagery, concreteness, familiarity, and ambiguity measures for 1,944 words[END_REF]. Word imageability was estimated following the same procedure by another 18 volunteers (with 0 = impossible and 6 = very easy to generate a mental image of the word).

To prevent participants from focusing on word-class discrimination, they were asked to perform a lexical decision task (deciding whether a letter string is a word or not). Eighty-four pseudo-words (constructed by changing one letter from real nouns or real verbs) were added as fillers to perform this task. Pseudo-words were either "pseudo-nouns" (42 items) or "pseudo-verbs" (42 items) and were all pronounceable. Pseudo-words were matched to words for relevant lexical variables such as number of letters and syllables, bi-and trigram frequency, and number and frequency of neighbors. Verbs and pseudo-verbs were also carefully matched for endings, such that as many verbs as pseudo-verbs (32 out of 42) ended with "er", which is a frequent ending for verbs in French. All items were presented in lower case.

To guarantee that potential differences in movement kinematics during verb and noun displays were not due to surface features inherent to our specific word stimuli, nine French right-handed volunteers performed a classical visual lexical decision task with the stimuli by indicating as per keystroke (using the left and right index fingers) whether the stimulus was a word or not. Participants were significantly slower to respond to pseudo-words (617ms) than to words (560ms; [F (1, 8) = 12.9878; p = .0069]). However, no significant difference was observed between nouns and verbs (564ms and 556ms, respectively; [F (1, 8) = .7815; p = .4024]). Difference in movement kinematics during noun and verb displays can therefore not be attributed to differences in the word lists per se.

Procedure

Participants were asked to touch a home-pad (10cm from their chest) with their right thumb and index finger held in a pinch grip position, while fixating on a monitor (95cm from their chest). When a white cross appeared at the center of the monitor (500 ms; go-signal), participants were required to leave the home-pad to reach and grasp a cylindrical object (height: 30mm, diameter: 15mm) placed vertically in front of them (40cm from the home-pad). In the 50 ms delay condition, a letter string appeared on the monitor 50 ms after the onset of the movement (i.e. leaving the home-pad). In the 200 ms delay condition, the orthographic stimuli was delayed by 200 ms. If the string was a word, participants were required to carry on the movement. If the string was a pseudo-word, they had to interrupt the movement and return to the home-pad. The stimulus remained on the screen until participants grasped the object (in the word condition), or returned to the homepad (in the pseudo-word condition). The experimenter triggered the next trial once participants were in the starting position. Video recording assured that participants maintained their gaze on the cylindrical object during final movement execution (word condition only). Each stimulus was presented once, and in random order.

Twenty practice trials (different from the experimental stimuli) were given to familiarize participants with the task.

Movement recordings

An Optotrak 3020 (Northern Digital) was used to record the spatial positions of four markers (infrared light-emitting diodes), at a frequency of 200 Hz and with a spatial resolution of 0.1 mm. One marker was taped to the wrist. The three remaining markers were fixed on the experimental set-up to define a space in which all recorded movements were systematically placed from participant to participant.

Data analysis

A second-order Butterworth dual pass filter (low pass cutoff frequency, 10 Hz) was used for raw data processing. Movements were then visualized and analyzed using Optodisp software (Optodisp copyright UCBL-CNRS, [START_REF] Thévenet | OPTODISP Progam[END_REF]. Kinematic parameters for the word condition were assessed for each individual movement. Movement onset was determined as the first value of a sequence of at least eleven increasing points on the basis of wrist velocity profile.

End of movements were determined similarly, going backwards from the end. For each participant, tangential velocity was calculated for individual trials. The initial part of trials (50 or 200 ms following movement onset depending on delay condition) was then removed and the remaining part normalized in time to 100 frames. Note that by normalizing the data, information about real time is lost.

However, without such normalization it is difficult to compare the data point by point along the movement. Individual trials were then averaged as a function of word category and acceleration/deceleration profiles were computed. Paired (onetailed) t-tests (per time unit) were used to identify periods in the acceleration/deceleration profiles where the two word conditions started to differed significantly (p ≤ .05). Within such periods, movement parameters were then defined for further statistical analyses. Two movement parameters served such analyses: the deceleration peak and the velocity peak (the velocity peak corresponds to the point in time where the acceleration curve crosses 0 mm/s 2 ), which were gained from the individual data of each participant.

Trials in which participants made errors, anticipated or delayed movement execution were excluded from the analysis.

Results and Discussion

One participant in the 200 ms delay condition was excluded from the analyses because of unusual strong variations in the data. For the remaining participants, a total of 12% of trials was excluded from the analyses (13% for nouns and 11% for verbs). In the 50 ms delay condition, 17% of trials were excluded (19% for nouns and 14% for verbs).

Total movement time in the 50 ms delay condition was 1316 ms and 1304 ms for noun and verb displays, respectively. In the 200 ms delay condition, it was 1384 ms and 1379 ms, respectively. Movement time did not distinguish between word displays.

<FIGURE 2 about here>

In the 50 ms delay condition, the noun and verb displays differed significantly starting from 32% to 40% (i.e., time frames, indicated by the transparent grey bar) of movement time after word onset. In the 200 ms delay condition, significant differences were observed from 23% to 27% (i.e., 5 time frames) and from 36%-43% of movement time after word onset. Note that in both delay conditions differences between noun and verb displays were observed around the deceleration and the velocity peaks (i.e., the point in time where the acceleration curve crosses 0 mm/s 2 ). Deceleration was generally stronger for noun than for verb displays, which indicates that verb displays interferes more with the execution of the movement than noun displays. Table 1 gives the real latencies of the two movement parameters. Except for the amplitude of the deceleration peak in the 200 ms delay, none of the parameters captured significant differences in the data. Note that on average, velocity peak was attained 413 ms after word onset in the 50 ms delay condition and 226-229 ms after word onset in the 200 ms delay condition. The significant differences between noun and verb displays observed in the normalized data near the velocity peak thus occurred at variable intervals with respect to word onset in the 50 ms and 200 ms delay conditions. Similarly, the time interval around the deceleration peak within which significant differences between noun and verb displays were observed occurred earlier with respect to word onset in the two delay conditions. Hence, although significant differences between noun and verb displays could be observed, these differences did not occur locked on word onset. Rather, in both delay conditions, differences between noun and verb displays were evident at the same moment between the velocity and the deceleration peak of the reaching movement.

While the present study replicated and substantiated our previous findings [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF]) that processing action words interferes with the execution of a concurrent reaching movement, it also showed that cross-talk between language processing and movement execution surfaces at particular moments during the reaching movement, and not after a constant interval following word onset. In the study by [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF], where the delay between movement and word onset was 0 ms, this cross-talk could be captured at and around the peak of wrist acceleration -which occurred within 160-177 ms following word onset. With the present delays of 50 ms and 200 ms between movement and word onset, however, wrist acceleration peak occurred too early with respect to word onset and the "next possible moment" where this effect could surface seemed to be around the velocity peak. Since characteristics of the movement itself appear to partially mask the immediate impact of the linguistic stimulus, information about when exactly word processing starts to affect motor behavior is therefore lost.

Unlike ERPs for cognitive tasks, fine-grained analyses of movement kinematics can thus not capture effects of action word processing on cortical motor structures in an online manner.

General Discussion

Consistent with [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF], and together with the accumulating TMS and brain imaging studies [START_REF] Buccino | Listening to action-related sentences modulates the activity of the motor system: a combined TMS and behavioral study[END_REF][START_REF] Hauk | Somatotopic representation of action words in human motor and premotor cortex[END_REF]Pulvermüller et al., 2005ab;[START_REF] Tettamanti | Listening to actionrelated sentences activates fronto-parietal motor circuits[END_REF], the present results further add to speculations that action words are -at least partly -represented in cortical motor regions [START_REF] Pulvermüller | Brain mechanisms linking language and action[END_REF][START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF]. However, since lesions over left motor cortex do not predictably lead to impairment in processing action words [START_REF] De Renzi | Sparing of verbs and preserved, but ineffectual reading in a patient with impaired word production[END_REF][START_REF] Mahon | The orchestration of the sensory-motor systems: Clues from neuropsychology[END_REF][START_REF] Saygin | Action comprehension in aphasia: linguistic and non linguistic deficits and their lesion correlates[END_REF], motor processes alone do not represent all that we know about these words. The functional role of cortical motor regions for language understanding needs therefore to be specified.

As we pointed out earlier, cross-talk between language processes and motor behavior differs qualitatively depending on whether the word is presented prior (facilitation) or concurrently (interference) to the movement and these contrasting patterns are likely to reflect different aspects of word processing. Languageinduced cortical motor activity that occurs early after action word onset -as evidenced in the brain imaging study by Pulvermüller et al. (2005a), and indicated by the motor perturbations seen in the present and in our previous study [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF] -may indeed participate during action word encoding.

Language-induced motor effects that occur when the word is processed prior to movement onset, however, may probably not (e.g., the second experiment in [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF][START_REF] Gentilucci | Influence of automatic word reading on motor control[END_REF][START_REF] Gentilucci | Language and motor control[END_REF][START_REF] Gentilucci | Object motor representation and language[END_REF][START_REF] Glenberg | Grounding language in action[END_REF][START_REF] Glover | Grasping the meaning of words[END_REF][START_REF] Tucker | Action priming by briefly presented objects[END_REF][START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF]. Note that as demonstrated by the so-called "Actionsentence Compatibility Effect" (ACE; [START_REF] Glenberg | Grounding language in action[END_REF], these latter effects can bridge entire sentences. To obtain an ACE, participants are asked to judge the sensibility of sentences describing the transfer of objects towards or away from themselves, such as "you delivered the Pizza to Leo" or "Leo delivered the Pizza to you", by moving their hand towards or away from their body.

Judgment time (i.e. the time elapsed between sentence onset and the beginning of the movement) is generally shorter when transfer direction implied by the sentence is consistent with the direction of the required response movement than when it is inconsistent. This judgment time, however, can exceed action word display by some 1000 ms, which makes it unlikely that the ACE arises from action word encoding. Given the systematic nature of these language-motor interactions, however, it is reasonable to assume that they might reflect functionally relevant aspects of language processing. Both phenomena need therefore to be addressed.

Lexical access vs. access to meaning: A speculation

While some of the studies that investigated language-motor relations have tested the impact of single action words [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF][START_REF] Gentilucci | Influence of automatic word reading on motor control[END_REF][START_REF] Glover | Grasping the meaning of words[END_REF]Hauk et al. 2004ab;[START_REF] Oliveri | All talk and no action: a transcranial magnetic stimulation study of motor cortex activation during action word production[END_REF]Pulvermüller et al. 2005ab), others have tested the impact of action words embedded within a sentence [START_REF] Buccino | Listening to action-related sentences modulates the activity of the motor system: a combined TMS and behavioral study[END_REF][START_REF] Glenberg | Grounding language in action[END_REF][START_REF] Tettamanti | Listening to actionrelated sentences activates fronto-parietal motor circuits[END_REF][START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF]. The meaning of a word without context, however, is generally indeterminate (e.g., [START_REF] Frege | Über Sinn und Bedeutung[END_REF]Borer, 2005ab).

The "action" word <take>, for instance, can have a number of different meanings depending on whether it is part of a sentence like "take a break", "take the example of", "take a book", or "take the train" etc. In trying to understand the potential role of cortical motor regions in language processing, it is therefore useful to distinguish between lexical access and access to word meaning (as determined by the context). Language-induced motor activity/effects that are observed early after word onset (150-200 ms) could reflect processes that are involved in lexical access. Motor effects that occur subsequent to word display, by contrast, may arise as consequence of access to meaning. Hebbian association learning during language acquisition (e.g., "kick the ball", which links the word <kick> with the action of kicking) could explain why lexical access for action words (but not for nouns) involves these cortical motor regions [START_REF] Pulvermüller | Words in the brain's language[END_REF]Pluvermüller, 2005). Motor effects that occur subsequent to word displays, by contrast, may arise consequence of access to (context induced) meaning and may involve more complex mechanisms than Hebbian association learning. We want to emphasize though that we are not suggesting that cortical motor regions are the bases of lexical access or access to action word meaning but simply that they are implicated in these processes.

Though admittedly speculative, this hypothesis allows a series of interesting predictions. First of all, brain imaging studies such as the MEG study by Pulvermüller, et al., (2005a), which demonstrated short-lived language-induced cortical motor activity around 150 ms, should observe that neural activity in these regions reappear at a later moment following action word onset if context information is provided. Why language-induced motor effects switch from interference during the hypothesized lexical access to facilitation during the hypothesized access to meaning need to be specified though. Second, early language-induced motor activity/effects should occur only for action words but not for nouns such as "apple" and "grape", for which [START_REF] Glover | Grasping the meaning of words[END_REF] have shown that they affect reaching grasping kinematics when processed prior to movement onset. Third, action words that are used as metaphors such as "his expensive hobby swallowed all his savings" should engage cortical motor region during lexical access for the word <swallow> but probably not during subsequent access to the meaning as implied by the sentence. Fourth, since access to meaning depends on sentence context, language-induced cortical motor activity that reflects processes involved in meaning access should vary depending on how sentence context modifies the action (see Glenberg et al., (this issue) for first evidence). But what is the function of language-induced cortical motor activity?

The potential role of cortical motor regions for language

Embodied theories of language have proposed that understanding verbal description of actions requires, as one essential component, the involvement of the motor system [START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF]; see also [START_REF] Gallese | The Brain's Concepts: The Role of the Sensory-Motor System in Reason and Language[END_REF]. The cell assembly approach by [START_REF] Pulvermüller | The neuroscience of language[END_REF], and complementary theoretical views for the perception of objects by Barsalou, Simmons, Barbey, & Wilson, (2003) or [START_REF] Rogers | Structure and deterioration of semantic memory: a neuropsychological and computational investigation[END_REF] similarly imply that conceptual content is grounded in modalities and that semantic knowledge emerges from the interactions between sensorymotor information and the words that are used to describe them. Yet, damage to cortical motor structures, though it affects motor behavior, seems not to systematically affect the perception and production of action related language.

Equally, while language induced cortical motor activity in healthy participants has been shown to affect motor behavior (e.g. the present study; [START_REF] Boulenger | Cross-talk between language processes and overt motor behavior in the first 200 ms of processing[END_REF][START_REF] Gentilucci | Influence of automatic word reading on motor control[END_REF][START_REF] Glenberg | Grounding language in action[END_REF][START_REF] Glover | Grasping the meaning of words[END_REF][START_REF] Zwaan | Seeing, acting, understanding: motor resonance in language comprehension[END_REF], it has not yet been shows that it also serves language understanding.

To better grasp the functional role of the observed language-induced motor effects/activity for language, one should thus focus on a language task instead on a motor task. So far, [START_REF] Myung | Playing on the typewriter, typing on the piano: manipulation knowledge of objects[END_REF] are among the few have done so. Myung et al. could show that lexical decision to auditory presented words and pseudowords was faster when the target word (e.g., typewriter) was preceded by a prime word that shared manipulation features (typing with the fingers) with the target (e.g., piano), compared to a prime that did not (e.g., Blanket). Note that in their experiment no overt typing was required, which thus suggest that word-associated knowledge about how to manipulate the objects had mediated priming. More evidence for such effects of the "motor system in language" (instead of "language in the motor system") is urgently required.

However, one very likely role of the motor system for the comprehension of action related language could reside in supplying this motor knowledge. How essential this contribution is for language understanding remains to be established though, as those who do not know how to "ride a bike" or to "knit a sock", can still talk about it.

Figure 2

 2 Figure 2 plots normalized wrist acceleration profiles in the two delay conditions

CAPTIONSFIGURE 1A :

 1A FIGURE 1A: Three main types of neurons encountered during movement

FIGURE 2 :

 2 FIGURE 2: Averaged wrist acceleration/deceleration profiles of all

TABLE 1 :

 1 Latencies and amplitude of movement parameters in the noun and verb displays. Data are given separately for the two delay conditions (ms= milliseconds; SE= Standard error).

		50 ms delay (latencies are from word onset)
		velocity peak (ms)	deceleration peak (ms)	amplitude of deceleration peak mm/sec 2
		MEAN	SE	MEAN	SE	MEAN	SE
	noun	413	39	590	49	-1587	265
	verb	413	36	577	49	-1408	262
	Diff.	0		13 ns		-178 ns
		200 ms delay (latencies are from word onset)
		velocity peak (ms)	deceleration peak (ms)	amplitude of deceleration peak mm/sec 2
		MEAN	SE	MEAN	SE	MEAN	SE
	noun	226	25	482	36	-1296	219
	verb	230	37	486	35	-1194	238
	Diff.	-4 ns		-4 ns		-102 p<.014