Psychological Research (2010) 74:71–81DOI 10.1007/s00426-008-0182-2

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ORIGINAL ARTICLE

Speed of processing explains the picture–word asymmetry in conditional naming

Claudio Mulatti · Lorella Lotto · Francesca Peressotti · Remo Job

Received: 27 November 2007 / Accepted: 16 October 2008 / Published online: 12 November 2008© Springer-Verlag 2008

Abstract In this study, we investigated picture (Experi-ments 1 and 2) and word (Experiments 3 and 4) processingusing diVerent tasks. In Experiments 1 and 3, easy and diY-cult conditional naming tasks were compared to a free nam-ing task. In Experiments 2 and 4, easy and diYcultconditional naming tasks were compared to easy and diY-cult manual forced-choice semantic decision tasks. For pic-tures, we showed that a diYcult semantic categorizationdetermined a cost for the conditional naming with respectto the free naming (Experiment 1). Also, we found that thediVerence in RTs between the easy and diYcult conditionalnaming tasks was much smaller than the diVerence betweenthe easy and diYcult forced-choice semantic decision tasks(Experiment 2). For words, results showed that free readingwas faster than easy conditional reading, which in turn wasfaster than diYcult conditional reading (Experiment 3). Ananalogous pattern of results was obtained when the easyand diYcult conditional reading tasks were compared to theeasy and diYcult forced-choice semantic decision tasks(Experiment 4). Globally, the results showed that whether acost is observed or not depends upon the relative timing ofthe classiWcation and name retrieval processes. A theoreti-cal framework has been proposed.

Introduction

Many models of cognition have postulated a functionalarchitecture for the processing of visuo-verbal stimuli thatallows for similarities and diVerences between picture andword processing (e.g., Roelofs, 1992, 1997; Levelt, Roe-lofs, & Meyer, 1999; Humphreys, Price, & Riddoch, 1999;Humphreys & Forde, 2001; Caramazza, 1997; Coltheart,Rastle, Perry, Langdon, & Ziegler, 2001).

Of the diVerences, it is assumed that whereas word cate-gorization requires access to the semantic system, word read-ing may be performed through a lexical non-semantic paththat activates phonological units directly from the ortho-graphic units (McCann & Besner, 1987; Morton & Patterson,1980; Coltheart et al., 2001). Since the rate of activation inthe semantic units is supposed to be slower than the rate ofactivation in the phonological units (Coltheart, 1985), wordcategorization should be performed more slowly than wordreading. This is indeed the case (e.g., Job, Rumiati, & Lotto,1992; Lloyd-Jones & Humphreys, 1997; Potter & Faulconer,1975; Snodgrass & McCullough, 1986).

Instead, both the naming and the semantic categorizationof pictures require access to the semantic system (e.g.Humphreys, Lamote, & Lioyd-Jones, 1995). Indeed, pic-tures do not provide any superWcial code allowing the directmapping from print to sound, and conceptual identiWcationis required in order to recover the name corresponding tothe depicted object (e.g. Humphreys et al., 1995). Concep-tual identiWcation is also required to perform semantic cate-gorization. Thus, the processes underlying picture namingand picture categorization largely overlap. Despite this sim-ilarity, picture naming might be slower than picture catego-rization, whereas the former task requires the picture befully identiWed, the latter task might be accomplished onthe basis of partial activation of the semantic representation

Portions of this research were presented at the 46th Annual Meeting of the Psychonomic Society, Toronto, 10–13 November, 2005.

C. Mulatti (&) · L. Lotto · F. PeressottiDipartimento di Psicologia dello Sviluppo e della Socializzazione, Università degli Studi di Padova, Via Venezia, 8, 35131 Padova, Italye-mail: claudio.mulatti@unipd.it

R. JobDiSCoF, Università degli Studi di Trento, Corso Bettini, 31, 38068 Rovereto, Trento, Italy

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(Rapp & Caramazza, 1991). Also, as shown by Humphreyset al. (1995), picture categorization might be accomplished byexploiting the activation of the semantic representations ofvisually similar objects, if “physical similarity correlates withthe classiWcation decision” (Humphreys et al., 1995, p. 539).

Job and Tenconi (2002) highlighted a further asymmetrybetween words and pictures using a conditional namingtask, in which the response is the result of both semanticcategorization and name retrieval of the stimulus. In theirstudy, participants were asked to name only the stimulibelonging to a pre-speciWed category (animals), and to oth-erwise withhold the response. While for words conditionalnaming was much slower than free naming, for picturesconditional naming took as long as free naming.

The authors explained this pattern within a frameworksimilar to that outlined above. For words, free reading can beaccomplished with little or no semantic involvement, thusallowing fast responses, whereas conditional reading alwaysrequires access to semantic information thus slowing downresponses. As for pictures, on the contrary, conceptual identi-Wcation always precedes name retrieval, and therefore condi-tional naming can be performed without additional costs.

This explanation rests on two main assumptions. On theone hand, the mental processes required to take a semanticcategorization should run in parallel with those required toperform name retrieval. Otherwise, an additional cost due tothe decision would be observed in the reaction times (RTs).On the other hand, the semantic categorization required toperform the conditional naming should be faster than the lex-ical retrieval, so that it can be absorbed into the time taken toretrieve the picture name (e.g. Job et al., 1992; Lloyd-Jones& Humphreys, 1997; Smith & Magee, 1980; Theios &Amrhein, 1989; Viswanathan & Childers, 2003). This shouldbe true at least when the semantic categorization is relativelyeasy, such as categorizing a picture as an animal or not.

From these two assumptions a number of predictions canbe drawn. First, a diYcult conditional naming task (i.e., aconditional naming task in which the decision aboutwhether or not to name the stimuli is based on a diYcultsemantic categorization, provisionally, we deWne a ‘diY-cult semantic categorization’ as a time consuming one; seethe General Discussion for an explanation situated within afunctional framework) should be performed more slowlythan the free naming of the same items. In other words,given a picture, the time required to access some “diYcultaspects” of its meaning may be slower than the retrieval ofits name. For example, we can ask participants to respond ifthe picture is an animal usually living in Italy and to with-hold the response in the case of animals living outside ofItaly. Such semantic categorization is likely to take moretime than the processes involved in name retrieval. If this isthe case, the response has to be postponed, even if ready tobe uttered, until the process of semantic categorization has

been completed. Thus, naming should be longer in this con-dition than when all the stimuli have to be named.

Second, we can hypothesize that the lack of cost observedby Job and Tenconi (2002) in the conditional naming task isdue to the fact that the time to take the semantic categoriza-tion is fully absorbed into the time required to retrieve thename of the picture. To focus on this issue, we will comparea conditional naming with a manual forced-choice semanticdecision task. In the semantic decision task participants pro-duce their responses as soon as the categorization is made;therefore, the diVerence between an easy categorization (ani-mals vs. artifacts) and a diYcult categorization (Italian vs.foreign animals) is fully expressed in the reaction times(RTs). This way, the cost due to a diYcult decision results inits whole magnitude. On the contrary, in the conditional nam-ing, when the response criterion is based on an easy semanticcategorization, the response has to be postponed; in this con-dition, RTs should not reXect directly the time needed tomake the semantic decision. It follows that the diVerencebetween a diYcult and an easy semantic categorizationshould be much smaller in the conditional naming task thanin the forced-choice semantic decision task.

Third, we hypothesize that correlation analyses on RTswill show diVerences between the easy and the diYculttask. In particular, since in the easy conditional naming taskresponses mainly reXect the processes needed to retrievethe picture names, RTs in this task should not be correlatedwith RTs in the easy semantic decision task. Instead, sincein the diYcult conditional naming task the response mainlyreXects the semantic processes involved in picture categori-zation, RTs in this task should be correlated with RTs in thediYcult semantic decision task.

Experiments 1 and 2 of the present paper aimed at test-ing these predictions. In Experiment 1, easy and diYcultconditional naming tasks were compared to a free namingtask on the same pictures. In Experiment 2, easy and diY-cult conditional naming tasks were compared to easy anddiYcult manual forced-choice semantic decision tasks.

The interpretative framework outlined above will be fur-ther tested by extending it to the word processing domain;we will defer predictions about words (Experiments 3 and4) until after presenting the results for pictures.

Experiment 1

Methods

Participants

Twenty-four undergraduate students at the Università degliStudi di Padova with normal or corrected-to-normal visionparticipated as volunteers.

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Materials

The stimuli consisted of 40 line drawing pictures selectedfrom an Italian standardized set (Dell’Acqua, Lotto, & Job,2000). Half of them portrayed animals, and half artifacts.Of the animals, ten represented animals that are typicallyfound in Italy (hereafter, Italian animals), and ten repre-sented animals that are not typical of Italy (hereafter, for-eign animals). In the Appendix we report the letter length,the frequency, the familiarity, the typicality, the age ofacquisition, and the name agreement of each item (Lotto,Dell’Acqua, & Job, 2001).

In addition to the experimental items, Wve pictures ofItalian animals, Wve pictures of foreign animals, and tenpictures of artifacts were selected to be used only in thepractice sessions.

Apparatus

The experiment took place in a sound attenuated and dimlylit room. Participants were tested individually. The partici-pant sat in front of a computer screen. The experimenter satbehind the participants to record, manually, naming errorsor equipment failures. Stimuli presentation and data acqui-sition were controlled by a software developed in E-primeand running on a personal computer to which a keyboardand a voice key were connected.

Design and procedure

Each trial consisted of the following sequence of events,after a Wxation cross presented for 400 ms, a stimulusappeared and stayed in view until either the participant pro-duced the vocal response or 1,500 ms elapsed. After aninterstimulus interval of 1,000 ms the Wxation pointappeared again. Each participant performed three tasks,free naming, easy conditional naming and diYcult condi-tional naming. The tasks diVered for the instructions givento the participants and for the stimulus set participants werepresented with. In the free naming, participants were pre-sented with the set of 40 items (20 animals and 20 arti-facts), and instructed to name each item. In the easyconditional naming, participants were presented with theset of 40 items (20 animals and 20 artifacts), and instructedto name only the items belonging to the category of animalsand to otherwise withhold their responses. In the diYcultconditional naming task, participants were presented withthe set of 20 animals (10 Italian and 10 foreign), andinstructed to name only those denoting animals which typi-cally inhabit Italy and to otherwise withhold theirresponses.

The order of presentation of tasks was counterbalancedacross participants; this means that each task appeared an

equal number of times in each of the three orders (thusresulting in six orders of presentation), even if each partici-pant was presented with one order of presentation.

To familiarize participants with the task, 12 practiceitems were presented at the start of each session.

Results

In order to allow comparisons among tasks, only the RTs tothe Italian animal items were considered in the followinganalyses, since only those items were used in all tasks.

Equipment failures and naming errors (6.2%) wereremoved prior to analysis of the RTs. The remaining cor-rect RTs were submitted to a recursive data trimming pro-cedure, in which the criterion cut-oV for outlier removalwas established by the sample size in each condition foreach subject (Van Selst & Jolicoeur, 1994). Outliers (1.6%)were removed prior to RTs analysis. Mean RTs accordingto conditions are reported in Table 1.

An ANOVA with Task (free naming, easy conditionalnaming, and diYcult conditional naming) as within-subjectfactor was conducted. Task was signiWcant F(2, 46) = 4.2,p < 0.02, MSE = 7,178.

Contrasts among means showed that whereas there wasno diVerence between free naming and easy conditionalnaming, t < 1, the diVerence between easy and diYcult con-ditional naming was signiWcant, t(23) = 2.40, p < 0.03, aswell as the diVerence between free naming and diYcultconditional naming t(23) = 2.54, p < 0.02. The resultsshowed that conditional picture naming required just asmuch time as free picture naming when the decision wasbased on an easy semantic categorization. This result nicelyreplicates that of Job and Tenconi (2002). In addition, con-sistent with the prediction sketched in the introduction,when the categorization decision was diYcult, conditionalpicture naming was slower than free picture naming.

Order eVects

A further issue needs to be addressed. Each participant waspresented with the three tasks in a diVerent order, and thestimulus material was repeated across tasks. To rule out the

Table 1 Mean reaction times (RT) and percentage of errors (%E)according with conditions of Experiment 1

Task

Free Conditional

Easy DiYcult

RT %E RT %E RT %E

743 0.6 747 0.5 806 0.5

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possibility that either the order of presentation of tasks orthe repetition of items inXuenced the results, we adoptedtwo approaches.

In the experiment, each task appeared as Wrst task anequal number of times, i.e., eight participants performedWrst the free naming, eight participants performed Wrst theeasy conditional naming, and eight participants performedWrst the diYcult conditional naming. We took advantage ofthis fact and performed a between-subject analysis usingthe data collected in the Wrst task only. We reasoned that ifthere were no diVerences between this analysis and thewithin-subject analysis, than there were no reasons to worryabout order/repetition eVects.

Thus, an ANOVA with Task (free naming, easy condi-tional naming, and diYcult conditional naming) asbetween-subjects factor was conducted. Task was signiW-cant F(2, 21) = 3.7, p < 0.05, MSE = 11,548, thus conWrm-ing the pattern of results obtained in the within-subjectanalysis. Comparisons between means revealed thatwhereas there were no statistical diVerences between thefree naming and the easy conditional naming (752 vs.750 ms, respectively), t < 1, the diVerence between the easyconditional naming and the diYcult conditional naming(878 ms) was signiWcant, t(14) = 2.4, p < 0.05.

Another way to control for eVects due to the counterbal-ancing procedure is to treat the counterbalancing assign-ment as a covariate in an ANCOVA with Task as within-subject factor. If the covariate does not interact with Taskthen the eVect of Task should be considered as independentof order of task or repetition of materials. The ANCOVAshowed that whereas the main eVect of Task was signiW-cant, F(2, 44) = 3.2, p < 0.05, MSE = 7,102, the interactionbetween counterbalancing and Task was not signiWcant,F(2,44) = 1.245, p > 0.29.

Experiment 2

This experiment aimed at testing the following prediction, thediVerence in RTs between the easy and the diYcult conditionalnaming should be much smaller than the diVerence betweenthe easy and the diYcult forced-choice semantic decision.In other words, an under-additive interaction between thefactors Task (conditional naming vs. semantic decision) andType of Decision (diYcult vs. easy) would be expected.

Methods

Participants

Twenty-four undergraduate students at the Università degliStudi di Padova with normal or corrected-to-normal visionparticipated as volunteers.

Material

See Experiment 1.

Apparatus

See Experiment 1.

Design and procedure

Each participant performed four tasks, easy conditionalnaming, diYcult conditional naming, easy semantic deci-sion, and diYcult semantic decision. The order of task pre-sentation was counterbalanced across participants. Eachtask appeared an equal number of times in each of the fourpositions (Wrst, second, third, or fourth task), resulting in 24orders of presentation. Each participant was presented withonly one order of presentation.

In the easy conditional naming, participants were pre-sented with a random sequence of the 40 pictures (20 animalsand 20 artifacts), and instructed to name the animals and tootherwise withhold their responses. In the diYcult condi-tional naming task, participants were presented with a ran-dom sequence of the 20 pictures of animals (10 Italian and 10foreign animals), and instructed to name the Italian animalsand to otherwise withhold their responses. In the easy seman-tic decision task, participants were presented with a randomsequence of the 40 pictures (20 animals and 20 artifacts), andinstructed to press the X key of the keyboard if the picturesdepicted an animal, and the N key if the pictures depicted anartifact. In the diYcult semantic decision, participants werepresented with a random sequence of the 20 pictures of ani-mals (10 Italian and 10 foreign animals), and instructed topress X if the pictures depicted an Italian animal, and N if thepicture depicted a foreign animal.

Each trial consisted of the following sequence of events.A Wxation point (+) was presented for 496 ms, followed bya blank screen for 96 ms. The target stimulus then appearedand remained on the screen until participants responded or3,000 ms had elapsed.

To familiarize the participants with the tasks, prior toeach experimental session, participants performed a prac-tice session consisting of 10 (diYcult conditional namingand semantic decision) or 20 (easy conditional naming andsemantic decision) trials.

Results

In order to allow comparisons among tasks, only the RTs tothe Italian animal items were considered in the followinganalyses, since only those items were used in all tasks.

Equipment failures, naming errors, and categorizationerrors (3.5%) were removed prior to RTs analysis and not

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further dealt with. The remaining correct RTs were submit-ted to a recursive data trimming procedure, in which thecriterion cut-oV for outlier removal was established by thesample size in each condition for each subject (Van Selst &Jolicoeur, 1994). Outliers (2.4%) were removed prior toRTs analysis. Mean RTs by condition are reported inTable 2.

An ANOVA with Task (conditional naming vs. semanticdecision) and Type of Decision (diYcult vs. easy) aswithin-subject factors was conducted. Semantic decisionwas performed faster than conditional naming, as shown bya signiWcant main eVect of Task F(1, 23) = 122.7,p < 0.001, MSE = 12617 (note that the two conditionsinvolve diVerent response mechanisms—manual vs.vocal—and thus nothing can be extrapolated from thisresult per se; see also Experiment 3). The main eVect ofType of Decision was also signiWcant F(1,23) = 80.2,p < 0.001, MSE = 4,893, showing that the diYcult categori-zation took longer than the easy categorization.

Furthermore, the main eVects were qualiWed by a signiW-cant interaction, F(1,23) = 30.7; p < 0.001, MSE = 5,863due to the fact that the diVerence between the diYcult andthe easy decision was smaller in the conditional naming(41 ms) than in the semantic categorization (214 ms).

As for the by items correlations, the analyses showedthat the RTs in the easy conditional naming did not corre-late with the RTs in the easy semantic decision, r = 0.343,p > 0.3, whereas the RTs in the diYcult conditional namingcorrelated with the RTs in the diYcult semantic decision,r = 0.775, p < 0.01.

Order eVects

In this experiment, each task appeared as Wrst task sixtimes, i.e. six participants performed Wrst the easy condi-tional naming, six participants performed Wrst the diYcultconditional naming, six participants performed Wrst thediYcult semantic decision, and six participants performedWrst the easy semantic decision. The ANOVA with Taskand Type of Decision as between-subjects factors showed amain eVect of Task F(1,20) = 18.8, p < 0.001, MSE =16,410, a main eVect of Type of Decision F(1,20) = 8.8,

p < 0.01, MSE = 16,410, and a signiWcant interactionF(1,20) = 8, p < 0.01, MSE = 16,410.

The ANCOVA with counterbalancing assignment as acovariate and Task and Type of Decision as within-subjectfactors showed that whereas the interaction between Taskand Type of Decision was signiWcant, F(1,22) = 11,p < 0.005, MSE = 5,975, the three-way interaction amongTask, Type of Decision, and counterbalancing was not sig-niWcant, F < 1.

Discussion of Experiments 1 and 2

If the easy semantic categorization process gets absorbedinto the time taken to retrieve the name of the picture, then(a) a diYcult semantic categorization—that needs moretime to be made—should determine a cost for the condi-tional naming with respect to the free naming; (b) the diVer-ence between the diYcult and the easy semantic decisionshould be larger than the diVerence between the diYcultand easy conditional naming. The results of Experiments 1and 2 were consistent with these predictions. In addition,the pattern of correlations in Experiment 2 indicated that (a)RTs in both the diYcult conditional picture naming and thediYcult semantic decision were inXuenced by variablesaVecting the processes underlying the semantic decision,and (b) whereas RTs in the easy conditional picture namingwere inXuenced by variables aVecting lexical retrieval, RTsin the easy semantic decision were inXuenced by variablesaVecting the processes involved in the semantic decision.

This pattern clearly supports a functional architecture inwhich picture naming and semantic categorization are dis-tinct processes that (can) run in parallel. In the conditionalnaming of pictures, the response can be inXuenced by thesemantic categorization only when the decision requiresmore time to be taken than the picture name retrieval. Oth-erwise, the response simply reXects the time required toname the picture.

If we now consider words as stimuli, a diVerent patternof results would be expected.

Since word reading is faster than word categorization,the time to perform a word semantic categorization cannotbe absorbed into the time taken to retrieve the word phono-logical representation; in this case, therefore, the latter pro-cess has to wait for the former to be completed. Thisinterval is likely to be longer when the semantic decisionunderlying the conditional reading is diYcult than when itis easy. Therefore, if we compare a free reading, an easyconditional reading, and a diYcult conditional reading forthe same words, responses should be slower in the secondthan in the Wrst condition (thus replicating the resultsobtained by Job and Tenconi), and they should be evenslower in the third condition. The diVerence between theeasy and the diYcult conditional word reading should fully

Table 2 Mean reaction times (RT) and percentage of errors (%E)according with conditions of Experiment 2

Task Type of decision

Easy DiYcult

RT %E RT %E

Conditional naming 825 0.6 866 0.5

Semantic decision 484 0.4 699 0.5

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reXect the cost due to the diYculty of the decision, similarlyto what happens in the case of a forced-choice word catego-rization task. Therefore, for word stimuli, if we compare aconditional reading with a semantic decision the costobserved for a diYcult semantic categorization should beanalogous in both tasks. Also, the RTs in the two tasksshould be correlated for both the easy and the diYcultsemantic decisions. In Experiments 3 and 4 we tested thesepredictions.

Experiment 3

Methods

Participants

Twenty-four undergraduate students at the Università degliStudi di Padova with normal or corrected-to-normal visionparticipated as volunteers.

Materials

The stimuli were the names of the pictures used in Experi-ment 1.

Apparatus

See Experiment 1.

Design and procedure

See Experiment 1. Note the stimuli are now words insteadof pictures.

Results

In order to allow comparisons among tasks, only the RTs tothe Italian animal items were considered in the followinganalyses, since only those items were used in all tasks.

Equipment failures and reading errors (1.4%) wereremoved prior to RTs analysis and not further dealt with.

The remaining correct RTs were submitted to a recursivedata trimming procedure, in which the criterion cut-oV foroutlier removal was established by the sample size in eachcondition for each subject (Van Selst & Jolicoeur, 1994).Outliers (1.7%) were removed prior to RTs analysis. MeanRTs according to conditions are reported in Table 3.

An ANOVA with Task (free reading, easy conditionalreading, and diYcult conditional reading) as within-subjectfactor was conducted.

Task reached signiWcance, F(2,46) = 175.9, p < 0.001,MSE = 1,722. Contrasts among means showed that the

diVerence between free reading and easy conditional read-ing was signiWcant, t(23) = 12.4, p < 0.001, as well as thediVerence between easy and diYcult conditional reading,t(23) = 9.9, p < 0.001.

Order eVects

An ANOVA with Task as between-subjects factor was con-ducted on the data of the tasks presented as Wrsts. Task wassigniWcant F(2,21) = 16.5, p < 0.001, MSE = 4,976. Com-parisons between means revealed that both the free readingcondition was faster than the easy conditional reading (461vs. 582 ms, respectively), t(14) = 4.6, p < 0.001, and thatthe easy conditional reading was faster than the diYcultconditional reading (663 ms), t(14) = 2.0, p < 0.05 (one-tail).

The ANCOVA with Task as within-subject factor andcounterbalancing assignment as a covariate variableshowed that whereas the main eVect of Task was signiW-cant, F(2,44) = 35.4, p < 0.001, MSE = 1,767, the interac-tion between counterbalancing and Task was notsigniWcant, F < 1.

Experiment 4

Methods

Participants

Twenty-four undergraduate students at the Università degliStudi di Padova with normal or corrected-to-normal visionparticipated as volunteers.

Materials

The stimuli were the names of the pictures used in Experi-ment 1.

Apparatus

See Experiment 1.

Table 3 Mean reaction times (RT) and percentage of errors (%E)according with conditions of Experiment 3

Task

Free Conditional

Easy DiYcult

RT %E RT %E RT %E

455 0.0 561 0.0 680 0.3

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Design and procedure

See Experiment 2. Note, however, that the stimuli werewords instead of pictures.

Results

In order to allow comparisons among tasks, only the RTs tothe Italian animal items were considered in the followinganalyses, since only those items were used in all tasks.

Equipment failures, reading errors, and categorizationerrors (7.1%) were removed prior to RT analysis and notfurther dealt with.

The remaining correct RTs were submitted to a recursivedata trimming procedure, in which the criterion cut-oV foroutlier removal was established by the sample size in eachcondition for each subject (Van Selst & Jolicoeur, 1994).Outliers (1%) were removed from the RT analysis. MeansRTs by condition are reported in Table 4.

An ANOVA with Task (conditional reading vs. semanticdecision) and Type of Decision (diYcult vs. easy) aswithin-subject factors was conducted. Type of DecisionF(1, 23) = 65, p < 0.001, MSE = 9,043 reached signiW-cance, while Task was not signiWcant, F < 1. Crucially, theinteraction was not signiWcant, F < 1.

The by items correlations showed that—as for picturesin Experiment 2—RTs in the diYcult conditional readingcorrelated signiWcantly with the RTs in the diYcult seman-tic decision (r = 0.944, p < 0.001). More crucially, anddiVerently from what was obtained in Experiment 2 withpictures, a high correlation was found between the easyconditional reading and the easy semantic decision(r = 0.857, p < 0.001).

Order eVects

As in the main analysis, the ANOVA with Task and Typeof Decision as between-subjects factors—conducted on thetasks presented as Wrsts—showed a main eVect of Type ofDecision F(1, 20) = 8.2, p < 0.01, MSE = 21,958. TheeVect of Task and the interaction between the two factorswas not signiWcant, Fs < 1.

The ANCOVA with counterbalancing assignment as acovariate and Task and Type of Decision as within-subjectfactors showed that neither the interaction between Taskand Type of Decision nor the three-way interactionbetween Task, Type of Decision, and counterbalancing wassigniWcant, Fs < 1.

Discussion of Experiments 3 and 4

The results showed that free reading was faster than condi-tional reading; furthermore, the diYculty of the semanticdecision that was required by the latter task determined RTsin the conditional reading task; the more diYcult was thesemantic decision, the longer were the RTs. This patternsuggests that—diVerently from picture processing—thecovert easy semantic categorization involved in the easyconditional word reading cannot be absorbed into the timetaken to retrieve the word’s phonological form.

Along with the structural similarities and diVerencesbetween the procedures and the representations inXuencingperformance in these diVerent tasks, what seems to be cru-cial in determining whether a cost is observed or not is therelative timing of each single process.

General discussion

To provide a uniWed account of the pattern of results, weWrst outline a simple model of picture and word processing.Our intention is not to unfold the nature of the internal rep-resentations and processes involved but only to capture theeVects reported in this paper. To this end, we combine—ona purely theoretical ground—two existing models: theinteractive activation (IAC) model of object processing(Humphreys et al., 1995), and a simpliWed version of thedual-route-cascaded (DRC) model of reading aloud (Colt-heart et al., 2001). Both models are instances of the interac-tive-activation family (McClelland & Rumelhart, 1981)with local representations (each unit stands for a mentalrepresentation). In both models, activation spreads in a cas-caded fashion; as soon as there is even the slightest activa-tion in a unit, this activation is spread to all connected units(McClelland, 1979). The combined model is outlined inFig. 1.

The picture processing portion of the model, adaptedfrom the IAC model of object processing, posits three prin-cipal types of representations which are hierarchically orga-nized—structural representations (stored knowledge aboutthe visual form of the objects), semantic representations(stored knowledge about the functional and associativeproperties of the objects), and phonological representations(the mental representation of the phonological characteris-tics of the objects’ names). Furthermore, representations at

Table 4 Mean reaction times (RT) and percentage of errors (%E)according with conditions of Experiment 4

Task Type of decision

Easy DiYcult

RT %E RT %E

Conditional reading 577 0.3 742 0.3

Semantic decision 579 0.4 727 0.3

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each level have excitatory connections to related represen-tations at contiguous level(s) and inhibitory connections tounrelated representations.

The word processing portion of the model is adaptedfrom the DRC model, which implements two proceduresfor computing the phonology of a letter string: The lexicalroute, which is a procedure that retrieves the whole-wordphonology from stored lexical representations, and the non-lexical route that converts serially, from left-to-right, eachgrapheme into the corresponding phoneme, according tolanguage-speciWc rules. Because the non-lexical route, theletter level, and the phoneme level, are not crucial to theaccount here proposed, they will not be covered in this dis-cussion. As can be seen in Fig. 1, the lexical route com-prises two pathways, the direct lexical route that directlyconnects the orthographic input lexicon (stored knowledgeof the words’ orthographic form) with the phonologicaloutput lexicon (stored knowledge of the words’ phonologi-cal form), and the lexical-semantic route that activates thephonological output lexicon through the semantic system.Activation Xows both forward toward the output and back-ward toward the input. Upon the presentation of a word,phonological and semantic units start to be activated andactivation is assumed to grow more slowly in the semanticunits than in the phonological units (Coltheart, 1985;Strain, Patterson, & Seidenberg, 1995).

In the next paragraphs we will show how the resultsreported in the present paper can be accommodated withinthis framework.

Why is the easy semantic decision faster than the diY-cult semantic decision in the IAC-DRC model? As pro-posed by Humphreys and Forde (2001), at the semanticlevel of representation both the super-ordinate category andencyclopedic units are represented at the same hierarchical

level1. In other words, each semantic unit is connected withthe corresponding super-ordinate category unit as well aswith units representing encyclopedic knowledge. To pro-vide an example taken from our study, semantic units rep-resenting elements belonging to the same semanticcategory as <DOG> and <LION> map onto the super-ordi-nate category unit <ANIMAL>. At the same time, thesemantic unit standing for <DOG> is connected with theencyclopedic unit standing for <TYPICAL-OF-ITALY>,whereas the semantic unit representing <LION> is con-nected with the encyclopedic unit representing <FOREIGN>.

Given this state of aVairs, on the one hand the diVerenceobserved in the time required to activate these two kinds ofunits (super-ordinate category vs. encyclopedic) cannot beascribed to a diVerent number of steps needed to go fromthe structural description (or from the lexical orthographicrepresentation) to either the super-ordinate category unit orto the encyclopedic unit. On the other hand, taking intoconsideration our results showing that it is easier to catego-rize a stimulus as belonging to the category of “animals”than to categorize it as “typical of Italy”, we should hypoth-esize that the rate of activation is faster for the super-ordi-nate category than for the encyclopedic units2. ThisdiVerence in activation reXects on RTs, producing theresults here obtained; the easy semantic decision is fasterthan the diYcult semantic decision.

The IAC model also accounts for diVerences betweenpictures belonging to categories in which exemplars arehighly similar to each other with respect to categories thatcomprise very dissimilar objects. In particular, Riddoch andHumphreys (1987) showed that naming is faster for percep-tually dissimilar objects, whereas semantic decisions arefaster for perceptually similar objects. According to theIAC model, objects in input activate not only their corre-sponding structural descriptions but also the structuraldescriptions of perceptually similar objects. Thus, structur-ally similar objects activate a higher number of representa-tions than structurally dissimilar objects in the structuraldescription system, and successively, in the semanticand phonological systems. Given that all semantic repre-sentations within a category are connected to the same

Fig. 1 Outline of the model

1 Note that in order to explain our data, other functionally equivalentarchitectures could be developed (e.g., the encyclopedic units could belocated at a lower hierarchical level with respect to the super-ordinatecategory, in such a way that in order to activate the former, the latterhas to be activated; see Collins & Loftus, 1975). However, since wehad no data on which to base such conjectures, we selected the simplestpossible architecture.2 Postulating diVerent rates of activation for super-ordinate units andfor encyclopedic units might seem an ad hoc solution; however, it par-allels the solution adopted to implement frequency in models of theinteractive-activation family (McClelland & Rumelhart, 1981; Colt-heart et al., 2001.

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super-ordinate unit, the co-activation of units at the semanticlevel for structurally similar objects facilitates semanticclassiWcation. “In contrast, for naming to occur, there mustbe diVerentiation between activated name and semanticrepresentation in order for the name appropriate to the tar-get object to emerge as the winner. This takes longer themore competitor items there are, and hence is longer forstructurally similar than for structurally dissimilar items”(Humphreys et al., 1995, p. 562). Note that although visualsimilarity might have an eVect in word categorization (Jobet al., 1992; Lotto, Job, & Rumiati, 1999; Snodgrass &McCullough, 1986), this is larger in picture categorization(Riddoch & Humphreys, 1987).

In the present study, considering the distinction betweenthe easy and diYcult categorization, it might be assumedthat the stimuli within both Italian and foreign animal cate-gories were more visually similar to each other than stimuliwithin the categories of animals and artifacts. Hence, a por-tion of the eVect due to the diYculty manipulation obtainedin the picture semantic decision task (Experiment 2) can beascribed to the diVerent degree of visual similarity betweenthe stimuli in the easy and diYcult semantic decision condi-tions (Snodgrass & McCullough, 1986).

This eVect of visual similarity, however, should not beobserved in the case of the word stimuli used in Experiment4. We can therefore predict that the size of the eVect due tothe diYculty of the semantic categorization should belarger for pictures than for words. An independent-samplest test was performed comparing the magnitude of the eVectobserved with pictures and the magnitude of the eVectobserved with words. Consistent with the prediction, thesize of the eVect was larger for pictures than for words (214vs. 148 ms, respectively), t(46) = 1.84, p = 0.035 (one-tail).

Why does conditional picture naming sometimes coststime and sometimes does not in the IAC-DRC model? Uponthe presentation of a picture, the corresponding structuraldescription unit is activated which, in turn, sends activationto the semantic representation with which it is connected.In the case of the easy conditional naming, the semanticrepresentation sends activation to both the super-ordinateunit and the phonological representation unit. The pro-cesses of classifying the stimulus and of retrieving its nameproceed in parallel. However, since activation grows fasterin the super-ordinate unit, the classiWcation process endsbefore that of the name retrieval. The cost of the classiWca-tion is thus fully absorbed into the time taken to retrieve thename.

In the case of the diYcult conditional naming task, thesemantic representation sends activation to both the ency-clopedic and the phonological units. Although the classiW-cation and name retrieval processes proceed in parallel, theactivation grows slower in the encyclopedic units withrespect to the phonological units. Thus, the name is

retrieved before the classiWcation is made. As a conse-quence, naming has to be postponed until the classiWcationdecision is taken.

Why does the conditional reading of words cost time inthe IAC-DRC model? Following the presentation of a wordin input, the corresponding orthographic representationreceives activation. The orthographic representationspreads activation to both the phonological and semanticrepresentations. Since activation in the phonological systemis assumed to grow faster than in the semantic system(Coltheart, 1985), neither the easy nor the diYcult semanticcategorization can be absorbed into the time taken toretrieve the word’s phonological form. In both the easy andthe diYcult conditional word reading, the phonological rep-resentation is retrieved before the classiWcation is made;overt responses always have to be postponed.

To conclude, by manipulating the diYculty of thesemantic decision on which an oral response was condi-tioned we were able to provide evidence of the parallel pro-cessing of semantic activation and name retrieval in pictureprocessing, as well as for the time-induced eVects of thesequencing of the two tasks.

Acknowledgments This research was supported by grants fromMURST at the Università degli Studi di Padova. We warmly thankMax Coltheart for his helpful comments on a preliminary version of thepaper.

Appendix

Length of names (in letters, LET; and in syllable SYL), fre-quency (FRQ), familiarity (FAM), typicality (TYP), age o facquisition (AoA), and name agreement (NA) for the stim-ulus material

LET SYL FRQ FAM TYP AoA NA

Italian animals

Aquila (Eagle) 6 3 2.28 4.1 6.3 4.1 71

Cervo (Deer) 5 2 1.99 4.9 4.8 3.9 79

Gufo (Owl) 4 2 1.90 4.1 4.2 4.1 90

Maiale (Pig) 6 3 2.08 5.4 4.5 2.5 98

Oca (Goose) 3 2 2.65 5.0 3.4 3.1 71

Pavone (Peacock) 6 3 1.34 4.1 3.6 4.5 98

Pecora (Sheep) 6 3 1.89 5.3 4.5 2.8 98

Picchio (Woodpecker) 7 2 0.70 4.3 5.6 4.3 86

Scoiattolo (Squirrel) 10 4 1.04 4.5 4.1 2.9 93

Topo (Mouse) 4 2 2.59 5.5 2.5 2.6 98

Mean 5.7 2.6 1.8 4.7 4.3 3.5 88

Foreign animals

Cammello (Camel) 8 3 1.53 3.1 3.6 3.9 93

Canguro (Kangaroo) 7 3 0.95 3.7 4.9 3.9 98

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References

Caramazza, A. (1997). How many levels of processing are there in lex-ical access? Cognitive Neuropsychology, 14, 177–208.

Coltheart, M. (1985). Cognitive neuropsychology and the study ofreading. In M. I. Posner & O. S. Marin (Eds.), Attention and per-formance XI (pp. 3–40). Hillsdale: Erlbaum.

Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001).DRC: A dual route cascaded model of visual word recognitionand reading aloud. Psychological Review, 108, 204–256.

Dell’Acqua, R., Lotto, L., & Job, R. (2000). Naming times and stan-dardized norms for the Italian PD/DPSS set of 266 pictures: Di-rect comparisons with American, English, French, and Spanishpublished databases. Behaviour Research Methods, Instruments,and Computers, 32, 588–615.

Humphreys, G. W., & Forde, E. M. E. (2001). Hierarchies, similarity,and interactivity in object recognition: “Category-speciWc”.Behavioral and Brian Sciences, 24, 453–509.

Humphreys, G. W., Lamote, C., & Lloyd-Jones, T. J. (1995). An inter-active activation-competition approach to object processing:

EVects of structural similarity, name frequency and task in nor-mality an pathology. Memory, 3, 535–586.

Humphreys, G. W., Price, C. J., & Riddoch, M. J. (1999). From objectsto names: A cognitive neuroscience approach. Psychological Re-search, 62, 118–130.

Job, R., Rumiati, R., & Lotto, L. (1992). The picture superiority eVectin categorization: Visual or semantic? Journal of ExperimentalPsychology: Learning, Memory, and Cognition, 18, 1019–1028.

Job, R., & Tenconi, E. (2002). Naming pictures at no cost: Asymme-tries in picture and word conditional naming. Psychonomic Bulle-tin and Review, 9, 790–794.

Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999). A theory of lex-ical access in speech production. Behavioural and Brain Sciences,22, 1–75.

Lloyd-Jones, T. J., & Humphreys, G. W. (1997). Categorizing chairsand naming pears: Category diVerences in object processing as afunction of task and priming. Memory and Cognition, 25, 606–624.

Lotto, L., Dell’Acqua, R., & Job, R. (2001). Le Wgure PD/DPSS Mi-sure di accordo sul nome, tipicità, familiarità, età di acquisizionee tempi di denominazione per 266 Wgure. Giornale Italiano diPsicologia, 28, 231–245.

Lotto, L., Job, R., & Rumiati, R. (1999). Visual eVects in picture andword categorization. Memory and Cognition, 127, 674–684.

McCann, R. S., & Besner, D. (1987). Reading pseudohomophones:Implications for models of pronunciation assembly and the locusof word-frequency eVects in naming. Journal of ExperimentalPsychology: Human perception and Performance, 13, 14–24.

McClelland, J. L. (1979). On the time relations of mental processes: Anexamination of systems of processes in cascade. PsychologicalReview, 86, 287–330.

McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activationmodel of context eVects in letter perception: I An account of basicWndigs. Psychological Review, 88, 375–407.

Morton, J., & Patterson, K. E. (1980). A new attempt at interpretation,or an attempt at a new interpretation. In M. Coltheart, K. E. Patt-erson & J. Marshall (Eds.), Deep dyslexia (pp. 91–118). London:Routledge.

Potter, M. C., & Faulconer, B. A. (1975). Time to understand picturesand words. Nature, 253, 437–438.

Rapp, B. C., & Caramazza, A. (1991). Cognitive neuropsychology:From impaired performance to normal cognitive structure. In R.G. Lister & H. J. Weingartner (Eds.), Perspectives on cognitiveneurosciences (pp. 384–404). New York: Oxford UniversityPress.

Riddoch, M. J., & Humphreys, G. W. (1987). Picture naming. In G. W.Humphreys & M. J. Riddoch (Eds.), Visual object processing: Acognitive neuropsychological approach (pp. 107–143). London:Erlbaum UK.

Roelofs, A. (1992). A spreading-activation theory of lemma retrievalin speaking. Cognition, 42, 107–142.

Roelofs, A. (1997). The WEAVER model of word-form encoding inspeech production. Cognition, 64, 249–284.

Smith, M. C., & Magee, L. E. (1980). Tracing the time course of pic-ture—word processing. Journal of Experimental Psychology:General, 109, 373–392.

Snodgrass, J. G., & McCullough, B. (1986). The role of visual similar-ity in picture categorization. Journal of Experimental Psychol-ogy: Learning, Memory, and Cognition, 12, 147–154.

Strain, E. S., Patterson, K., & Seidenberg, M. S. (1995). SemanticeVects in single-word naming. Journal of Experimental Psychol-ogy: Learning, Memory, and Cognition, 21, 1140–1154.

Theios, J., & Amrhein, P. C. (1989). Theoretical analysis of the cogni-tive processing of lexical and pictorial stimuli: Reading, naming,and visual and conceptual comparisons. Psychological Review,96, 5–24.

Elefante (Elephant) 8 4 1.85 4.2 5.5 2.7 100

GiraVa (GiraVe) 7 3 1.00 4.0 4.8 2.9 98

Ippopotamo (Hippopotamus)

10 5 0.95 2.9 3.9 4.0 83

Leone (Lion) 5 3 2.61 4.3 5.9 2.4 100

Pinguino (Penguin) 8 3 1.26 3.6 3.2 3.3 95

Struzzo (Ostrich) 7 2 1.28 3.3 2.9 4.9 83

Tigre (Tiger) 5 2 2.17 4.1 5.7 3.0 95

Zebra (Zebra) 5 2 1.20 3.8 4.8 3.6 95

Mean 7.0 3.0 1.5 3.7 4.5 3.4 94

Objects

Bottiglia (Bottle) 9 3 2.40 6.3 5.9 1.9 98

Coltello (Knife) 8 3 2.40 6.9 6.3 2.3 100

Coperchio (Lid) 9 3 1.85 6.7 4.9 3.0 81

Cucchiaio (Spoon) 9 3 2.02 6.8 6.5 2.0 100

Forchetta (Fork) 9 3 1.67 6.8 6.2 1.8 100

Grattugia (Grater) 9 3 0.70 6.9 5.2 4.2 95

Imbuto (Funnel) 6 3 1.38 6.7 4.3 3.8 100

Pentola (Pot) 7 3 1.95 7.0 6.7 2.7 98

Scopa (Broom) 5 2 1.40 6.9 6.0 2.7 98

Teiera (Teapot) 6 3 1.32 4.7 3.7 5.1 79

Antenna (Antenna) 7 3 1.93 5.4 4.5 5.0 95

Bicicletta (Bicycle) 10 4 2.45 6.9 5.3 2.3 95

Divano (Couch) 6 3 2.22 6.7 6.9 2.5 93

Guanto (Glove) 6 2 1.76 5.3 4.3 2.9 100

Ombrello (Umbrella) 8 3 1.85 6.1 2.9 2.9 98

Pigiama (Pyjamas) 7 3 1.51 6.1 2.5 2.3 98

Poltrona (Armchair) 8 3 2.58 6.3 6.2 2.7 88

Sciarpa (Scarf) 7 2 1.79 6.3 5.9 2.5 100

Scrivania (Desk) 9 4 2.48 6.2 5.7 3.9 83

Sveglia (Clock) 7 2 1.93 6.9 6.0 3.6 90

Mean 7.6 2.9 1.9 6.4 5.3 3.0 94

LET SYL FRQ FAM TYP AoA NA

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Van Selst, M., & Jolicoeur, P. (1994). A solution to the eVect of samplesize on outlier elimination. Quarterly Journal of ExperimentalPsychology: Human Experimental Psychology, 47A, 631–650.

Viswanathan, M., & Childers, T. L. (2003). An enquiry into the pro-cess of categorization of pictures and words. Perceptual and Mo-tor Skills, 96, 267–287.

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