Behavior Research Methods, Instruments, & Computers1999,31 (3), 531-552

A set of 400 pictures standardized for French:Norms for name agreement, image agreement,familiarity, visual complexity, Image variability,

and age of acquisition

F.-XAVIER ALARIO and LUDOVIC FERRANDCNRS and Unioersite Rene Descartes, Paris, France

The present article provides Freneh normative measures for 400 line drawings taken from Cyeowiez,Friedman, Rothstein, and Snodgrass (1997), including the 260 line drawings that were normed bySnodgrass and Vanderwart (1980). The pictures have been standardized on the following variables:name agreement, Image agreement, familiarity, visual eomplexity, Image variability, and age of acqui­sition. These normative data also include word frequeney values and the first verbal associate (takenfrom Ferrand & Alario, 1998). The six variables obtained are important beeause of their potential ef­feet in many fields of psyehology, especially the study of eognitive processes such as visual perception,language, and memory.

531

Inrecent years, experiments employing pietures ofob­jeets have proliferated. However, little standardization ofline drawings exists. To date, each investigator has beenforeed to develop his or her own set of pietures, whiehare neeessarily highly idiosyncratie (Snodgrass, Levy­Berger, & Haydon, 1985). One exception is the pioneer­ing work of Snodgrass and Vanderwart (1980). Theseauthors have provided a set of 260 pictures (blaek-and­white line drawings) that have been standardized on fourvariables of relevanee to experimentation in visual per­eeption, language, and memory. The four variables eol­leeted were name agreement (the degree to whieh sub­jects agree on the name ofthe pieture), image agreement(the degree to which images generated by subjects to apieture's name agree with the pieture's appearanee), fa­miliarity (the familiarity ofthe eoncept depicted), and vi­sual complexity (the amount of lines and details in thedrawing). These normative data for pietures were col­leeted in Ameriean English for young adults.

Since then, other normative data for pictures have beencollected by Berman, Friedman, Hamberger, and Snod­grass (1989) for 5- and 6-year-old ehildren and by Cy­cowiez, Friedman, Rothstein, and Snodgrass (1997) for 8­to 10-year-old ehildren. More reeently, these normative

This research was supported by a grant from the Direction de laRecherche et de la Technologie (a division ofthe Direction Generale deI'Armement) to the first author. We are grateful to Robert Proctor, JoanGay Snodgrass, Carmen Sanfeliu, Ronald Peereman, and Juan Seguifor helpful feedback on an earlier version of this manuscript. Thanksare extended to Carmen Sanfeliu for sending the set of data for Span­ish and English. Correspondence conceming this article should be ad­dressed to F.-X. Alario or to L. Ferrand, CNRS and Universite ReneDescartes, Laboratoire de Psychologie Experimentale, 28 rue Serpente,75006 Paris, France (e-mail: alario@psycho.univ-paris5.frorferrand@psycho.univ-paris5.fr).

data have also been collected for adults in British English(Barry, Morrison, & Ellis, 1997; Vitkovitch & Tyrrell,1995), in Spanish (Sanfeliu & Femandez, 1996), and inDutch (Martein, 1995). However, to our knowledge, thereis no such normative database available in Freneh. Be­eause it is vital for the experimenter to have as much con­trol of the experimental situation as possible, careful se­lection ofstimuli is necessary. The present article providesnormative measures for 400 line drawings and their corre­sponding names viewed by French-speaking young adults.

When available, these normative studies have been ex­tremely useful in many fields of psychology, includingmemory and language, through the use ofdifferent kindsof subjects (e.g., children, adults, and pathologiealcases). Coneerning the study of language, for instance,these databases have been used to study the processes in­volved in pieture naming (e.g., Ferrand, Grainger, & Segui,1994; Ferrand, Humphreys, & Segui, 1998; Humphreys,Lamote, & Lloyd-Jones, 1995; Johnson, Paivio, & Clark,1996; Snodgrass & Yuditsky, 1996) and, more generally,in speech production (e.g., Ferrand & Segui, 1998; Fer­rand, Segui, & Grainger, 1996). These normative datahave also been very useful in the fields of perceptualidentifieation and recognition (e.g., Kroll & Potter, 1984;Snodgrass & Poster, 1992) and implicit memory (e.g.,Feenan & Snodgrass, 1990; Hirshman, Snodgrass, Min­des, & Feenan, 1990; Snodgrass & Feenan, 1990; Snod­grass, Smith, Feenan, & Corwin, 1987; Snodgrass & Sur­prenant, 1989).

The motivation for the present study was to obtain anormative database for pictorial material that will be use­ful for future studies with French-speaking subjeets. Weeonducted a study in which the stimuli were the 400 pic­tures used by Cycowicz et al. (1997), including the 260line drawings that were normed by Snodgrass and Van-

Copyright 1999 Psyehonomie Soeiety, Ine.

532 ALARIO AND FERRAND

derwart (1980). In closely following Snodgrass and Van­derwart's procedure, norms for name agreement, imageagreement, picture familiarity, visual complexity, imagevariability, and age of acquisition were collected. Thenormative database also include the most common namegiven to each of the 400 concepts (modal name), wordfrequency (taken from Content, Mousty, & Radeau,1990), and the first verbal associate ofthe names ofthepictures (taken from Ferrand & Alario, 1998).

In what follows, we briefly discuss empirical findingsrelated to each variable. Name agreement refers to thedegree to which subjects agree on the name of the pic­ture. This information is important for naming latencystudies, picture-name matehing studies, recall memorystudies, and recognition studies in which verbal encod­ing is manipulated. Name agreement is measured bythe number of different names given to a particular pic­ture across subjects. Pictures that elicit many differentnames have lower name agreement than those eliciting asingle name. Name agreement is a robust predictor ofnaming difficulty. Pictures with a single dominant re­sponse are named more quickly and accurately thanthose with multiple responses (Barry et al., 1997; Lach­man, Shaffer, & Hennrikus, 1974; Paivio, Clark, Digdon,& Bons, 1989; Vitkovitch & Tyrrell, 1995). More impor­tant, name agreement affects naming independently ofthe effects of correlated attributes, such as word fre­quency and rated age of name acquisition (Lachman etal., 1974).

Image agreement refers to the degree to which imagesgenerated by subjects to a picture's name agree with thepicture's appearance. Barry et al. (1997) showed that pic­tures with higher ratings ofimage agreement were namedfaster than were those with lower ratings. They sug­gested that image agreement has its influence at the levelof object recognition, so that the closer a picture is toone's mental image of an object, the faster the namingtime for that item will be.

Familiarity refers to the familiarity ofthe concept de­picted. Familiarity has been shown to have important ef­fects on various memory and cognitive processing tasks(see, e.g., Gernsbacher, 1984). In particular, Snodgrassand Yuditsky (1996) and Feyereisen, Van der Borght, andSeron (1988) showed that rated familiarity is an impor­tant predictor of picture-naming latencies, so that themore familiar a concept is, the faster the naming time forthat item will be.

Visual complexity refers to the amount oflines and de­tails in the drawing. It is supposed to determine the easeof processing at or before the structural stage of objectrecognition. Visual complexity may affect such variablesas naming latencies, tachistoscopic recognition thresh­olds, and memorability. Early research using pictorialstimuli has established that, when complexity is rnanip­ulated, more complex stimuli are more difficult to processthan simple stimuli (Attneave, 1957; Ellis & Morrison,1998). However, other investigators showed that com­plex objects are identified and named as readily as sim-

ple objects (Biederman, 1987; Paivio et al., 1989; Snod­grass & Corwin, 1988; Snodgrass & Yuditsky, 1996).

Forfrequency and age ofacquisition, picture-naminglatencies decrease as name frequency increases (Old­field & Wingfield, 1965) and increase as age ofword ac­quisition increases (Carroll & White, 1973; Ellis & Mor­rison, 1998). It is possible that the influence of wordfrequency on learning, memory, and perception dependson another attribute, such as the age at which the partic­ular word was first learned. Some investigators (Carroll& White, 1973; Ellis & Morrison, 1998; Morrison, Chap­pell, & Ellis, 1997; Morrison, Ellis, & Quinlan, 1992)suggested that age of acquisition is a more importantvariable than frequency in print, However, Barry et al.(1997) and Snodgrass and Yuditsky (1996) found thatthe time taken to name a pictured object correctly wasaffected both by rated age of acquisition and by the fre­quency ofthe name (in accordance with Lachman, 1973;Lachman et al., 1974). Interestingly, Barry et al. (1997)showed that the age-of-acquisition effect interacted withfrequency, the age-of-acquisition effect being more pro­nounced for pictures with low-frequency names.

METHOD

SubjectsA total of 173 students from introductory courses in psychology

from the Ecole des Psychologues Praticiens and from UniversiteRene Descartes in Paris participated in the study. Different subjectsparticipated in each of the six tasks. There were 28 in the nameagreement task, 30 in the image agreement task, 30 in the familiar­ity task, 29 in the visual complexity task, 30 in the image variabil­ity agreement task, and 26 in the age-of-acquisition task. All thesubjects were native French speakers and participated voluntarily asa course activity. The subjects were run in groups offrom 26 to 30in a classroom.

MaterialsThe pictures were the 400 black-and-white line drawings ofcom­

mon objects taken from Cycowicz et al. (1997). These pictures weredownloaded from the Internet (http://www.nyspi.cpmc.columbia.edu/nyspi/respaprs/picnorm.htm). Some ofthe originalline draw­ings (n = 7) were replaced for obvious reasons: The pictures hadbeen selected in the American context (things such as a baseballbat, a football heimet, or a pretzel are more familiar to Englishspeakers in America than to French speakers in France). In partic­ular, we replaced the following drawings (a baseball bat, a football,a football heimet, a fishing reel, a grocery bag, a baseball glove,and a pretzel) by drawings of objects more common in the Frenchspeakers' realm of experience (a ski, a French croissant, a motor­bike heimet, a swimsuit, a rugby ball, a fishing rod, and a super­market caddie). These seven pictures were adapted from two Frenchbooks of pictures (Des Mots en Images, 1988; L'imagier du PereCastor, 1991; they are available on request).

ProeedureThe procedure closely followed the steps described by Snodgrass

and Vanderwart (1980) and by Morrisson et al. (1997; for age ofac­quisition), both in terms ofthe tasks performed and in the way thetasks were done.

The name agreement task, the image agreement task, the famil­iarity task, and the complexity task were run in a similar way.How­ever, for the image variability task and the age-of-acquisition task,

the modalname ofthe object (instead ofthe object itself) was pre­sentedto the subjects. The400 pictureswere projected sequentiallyon a large white screen at the front of a slightly darkened room,using an overheadprojector.At the beginningofeach task, the sub­jects wereread the instructionsand eneouraged to answerearefullyand consistently. They weregiven individualanswer sheets and in­strueted to respond to every drawing. They were informed of thegeneralnatureofthe pictures-s-that is, that they were relativelysim­ple black-and-whiteoutline drawings.Each slide was presentedforaperiod of 5 sec. Halfway through the slides, the subjects weregiven a 15-min rest period. The total amount of time was about11/ 2 h.

In the name agreement task, the subjeetswere instructedto iden­tify the drawingwith the first name that eame to mind and to writethe name on the answer sheet. They were told that a name couldconsistofmore than one word.1fthat was not possible, they had toindieatewhether the reasonwasdon't know the object (DKO),don 'tknow the name (DKN), or tip ofthe tongue (TOT).

In the image agreement task, the subjects were asked to judgehow elosely eaeh picture resembled their mental image of the ob­jeet. Prior to presenting eaeh pieture, the experimenter ealled outthe pieture's most eommon name, waited approximately5 sec, andthen projected the picture on the sereen. During the 5-sec period,the subjects looked at the blank sereen and formed their mentalimageofthe named objeet. Following the appearance ofthe pictureon the sereen, the subjeets rated the degree of agreement betweentheir imageand the pieture,using the 5-pointseale. A ratingof I in­dieated low agreement, that the pieture provided a poor match totheir image, and a rating of 5 indieated high agreement.

In the familiarity task, the subjeets were asked to judge thefamiliarity of the eoncept of eaeh pieture "according to how usualor unusual the objeet is in your realm of experience." Familiaritywas defined as "the degree to whieh you eome in contact with orthink about the concept." They were told to rate the coneept itself,rather than the way it was drawn. Their answer to each itemwas again a whole number from a 5-point seale (1 = a very unfa­miliar object, 5 = a very familiar object). The subjects were en­couragedto employ the full range of scalevalues throughoutthe setof pictures.

The visual complexity task requiredthe subjects to rate the com­plexity of each drawing, rather than the complexity of the object itrepresented.They also had to provide ratings from a 5-point scale(I = drawing very simple, 5 = drawing very complex). Complex­ity was defined as the amountof detailsor the intricacy ofthe linesin the picture.

The two remaining tasks (image variability and age of acquisi­tion) consistedofjudgments on the names ofthe pictures.No over­head projector was used here. The subjects were given a four-pagebookletwith the 400 names ofthe pictures. In the image variabilitytask, they were instructed to rate on a 5-pointscale (I = few images,5 = many images) whether the name evoked few or manydifferentimagesfor that particular object. In the age-of-acquisitiontask, thesubjects were asked to estimate the age at which they thought theyhad learned each ofthe names, in its written or its oral form. Weal­tered the scale used by Morrison et al. (1997) from 7 points to 5points,where I = learned at 0-3 years and 5 = learned at age 12+,with 3-year age bands in between.For this specific task, 17wordswere repeated, to provide a reliability check. The correlation be­tween these repeated ratings was .94, and the means were not sig­nificantly different [2.68 vs. 2.56; t(16) = 0.11].

Concerning verbal association measures,we report Ferrand andAlario's (1998) results (when available for the present stimuli).Overall, 263 associations were available out of the 400 stimuli.These free association norms were collected by presenting a largegroup of French-speaking subjects (n = 89) with a written stimu­lus wordand asking them to respond with the first word they thinkof, as quickly as they can (for details, see Ferrand & Alario, 1998).

PICTURES STANDARDIZED FOR FRENCH 533

RESULTS AND DISCUSSION

A summary ofthe rating data obtained from our sam­pIe of French-speaking subjects is presented in Appen­dix A. To allow for easy reference and data comparison,entries are listed according to the identifying numbersoriginally assigned to each drawing by Cycowicz et al.(1997). Moreover, a computer file (Excel or ASCII for­mat) with all the data is available on request for researchfacilities. For each picture, the following information ispresented: (1) the most frequent name given in French(with an English translation); (2) two measures ofnameagreement, the statistic H (taken from Snodgrass & Van­derwart, 1980) and the percentage of subjects producingthe most common name; and (3) the means and standarddeviations for image agreement, familiarity, visual com­plexity, image variability, and age of acquisition. Alongwith the ratings obtained for French-speaking subjects,Appendix A presents the frequency of the single name(taken from Content et al., 1990), as well as the first ver­bal associate (obtained by Ferrand & Alario, 1998). Ap­pendix B lists the alternate names given to each draw­ing, with an indication oftheir frequency. A frequency ofzero indicates that the single-word name did not occur inthe Content et al. corpus. Because the Content et al. cor­pus does not provide counts for names of more than oneword, these unavailable frequencies are indicated by adash. Failures in the naming task are listed as DKN,DKO, and TOT. All nondominant names given for eachconcept are listed and accompanied by their frequencies(when available).

Following Snodgrass and Vanderwart (1980), we useda strict criterion for counting different instances ofnames when computing H values. In many cases, thename given by a subject was similar to but not identicalwith an established name category. A picture that elicitedthe same name from every subject in the sampIe who wasable to name it has an H value of .00. Increasing H val­ues indicate decreasing name agreement and, generally,decreasing percentages of subjects who all gave the samename. According to Snodgrass and Vanderwart,

the H value captures more information about the distrib­ution of names across subjects than does the percentageagreement measure. For example, iftwo concepts both aregiven their dominant name by 60% of the subjects, butone is given a single other name and the second is givenfour other names, both concepts will have equal percent­age agreement scores, but the first will have a lower Hvalue. (p. 184)

Table 1 presents summary statistics for the followingindices: H (reflecting name agreement), percentage ofsubjects producing the modal names, image agreement,familiarity, complexity, variability, age of acquisition,and frequency. Although Hand percentage are two mea­sures ofname agreement, following Snodgrass and Van­derwart's (1980) arguments, we will use H as the mea­sure of name agreement. The 25th (Ql) and the 75th(Q3) percentiles are shown to facilitate selection ofcon-

534 ALARIO AND FERRAND

Table 1Summary Statistics for All Variables

NameAgreement Image Image

Statistic H* % Agreement Familiarity Complexity Variability A-A F

M 0.36 84.63 3.44 2.72 3.09 2.76 2.56 29.82SD 0.43 20.31 0.78 1.19 0.92 0.63 0.79 78.96Median 0.15 96 3.57 2.42 3.07 2.60 2.51 7.04Range 1.87 82 3.90 3.94 4 3.50 3.65 892Min 0 18 1 1.03 I 1.20 1.12 0Max 1.87 100 4.90 4.97 5 4.70 4.77 892QI 0 75 2.97 1.73 2.38 2.30 1.95 1.61Q3 0.65 100 4 3.77 3.74 3.17 3.08 21.88IRQ 0.65 25 1.03 2.04 1.36 0.87 1.13 20.27Skew 3.33 0.19 0.72 1.98 0.97 1.90 1.02 2.74

Note-H, name agreement; A-A, age of acquisition; F, frequency (taken from Content, Mousty, & Radeau,1990); Ql, 25thpercentile; Q3, 75th percentile; IRQ, interquartile range; skew, (Q3 - Median)/(Median - QI); >I is positivelyskewed. *Increasing H values indicate decreasing name agreement.

cepts from the extremes of the distribution. The distrib­ution ofH valueshas a low mean and is positively skewed,reflecting the fact that many concepts show high nameagreement.

Table 2 presents summary statistics for the followingindices: H, image agreement, familiarity, and complex­ity. This table contains the summary for the French sam­pIes of the current study, the Spanish-speaking sampIesreported by Sanfeliu and Fernändez (1996), and theEnglish-speaking sampIes reported by Snodgrass andVanderwart (1980). As can be seen from this table, therewere small differences for image agreement, familiarity,and complexity. There was a larger difference when theH value was considered. The English-speaking sampIehad bigger H values than did the French and Spanishones. It seems to indicate that the French sampIe and theSpanish sampIe showed less variability in the number ofnames applied to objects than did the English-speakingsampIe.

We performed two correlational analyses on the data.The first one correlated (1) the data provided by Snod­grass and Vanderwart (1980) with the data obtained inthe present study (for the 253 drawings common to bothstudies) for H, image agreement, familiarity, and visual

complexity and (2) the data provided by Sanfeliu andFernandez (1996) with the data obtained in the presentstudy for the same variables. As is shown in Tables 3 and4, there were fairly high and significant correlations forall the variables. Correlations were higher for familiar­ity and complexity (for both French-English and French­Spanish) than for name agreement (H and %) and imageagreement.

The second correlational analysis concemed the dataobtained in the present study for the 400 line drawingstaken from Cycowicz et al. (1997). To determine the de­gree of relationship among our measures and betweenthem and some important measures already available, wecomputed the interitem correlations among all the at­tributes presented in Appendix A (following Snodgrass& Vanderwart, 1980). Table 5 shows the matrix of cor­relations for all the concepts, with the significant corre­lation coefficients marked with an asterisk. Because fre­quency measures (taken from Content et al., 1990) wereavailable for only 355 ofthe 400 concept names, a sepa­rate set of correlations was computed for this subset.

As was expected, the two measurcs ofname agreement(H and %) show a high negative correlation (- .952 inTable 5). The correlations among the other measures col-

Table2Summary Statistics for Four Variables: American, Spanish, and French Sampies

(for Snodgrass and Vanderwart Pietures)

Name Agreement (H) Image Agreement Familiarity Complexity

Statistic US. Spain France US. Spain France US. Spain France US. Spain France

M 0.56 0.27 0.28 3.69 3.71 3.46 3.29 3.12 3.06 2.96 2.67 3.00SD 0.53 0.41 0.36 0.58 0.60 0.78 0.96 1.11 l.21 0.89 0.93 0.96Median 0.42 0.12 0.15 3.72 3.84 3.60 3.32 3.06 2.92 2.93 2.52 2.95Range 2.55 2.19 1.41 2.68 3.03 3.73 3.72 3.67 3.90 3.78 3.68 4Min 0 0 0 2.05 1.74 1.17 1.18 1.27 1.07 I 1.05 IMax 2.55 2.19 1.41 4.73 4.77 4.90 4.90 4.94 4.97 4.78 4.73 5Ql 0.12 0.04 0 3.27 3.29 2.93 2.49 2.16 1.97 2.28 1.98 2.28Q3 0.87 0.28 0.47 4.15 4.16 4.05 4.09 4.08 4.17 3.59 3.39 3.71Skew 1.5 2.39 2.13 0.96 -0.71 0.67 0.93 0.01 1.32 1.02 0.28 1.13Valid cases 260 254 256 260 245 256 260 254 256 260 254 256

Note--QI, 25th percentile; Q3, 75th percentile; skew, (Q3 - Median)/(Median - QI); > I is positively skewed. * In-creasing H values indicate decreasing name agreement.

PICTURES STANDARDIZED FOR FRENCH 535

Table3Significant Correlations Among the Measured Variables in the French and

American SampIes (for Snodgrass and Vanderwart Pictures)

American SampIe

French Sampie NA (H) % IA Farn Comp

Name agreement (H) .428Name agreement (%) .429Image agreement .498Familiarity .913Visual complexity .945

Note-NA, name agreement; IA, image agreement; Farn, familiarity; Comp, visualcomplexity. Alllisted correlation coefficients for the present study and the Snodgrassand Vanderwart (1980) study are significant at p < .0I.

Table4Significant CorreIations Among the Measured Variables in the French and

Spanish SampIes (for Snodgrass and Vanderwart Pictures)

Spanish SampIe (Sanfeliu & Fernandez, 1996)

French SampIe NA (H) % IA Fam Comp

Name agreement (H) .313Name agreement (%) .506Image agreement .524Familiarity .778Visual complexity .727

Note-NA, name agreement; IA, image agreement; Farn, familiarity; Comp, visualcomplexity. All listed correlation coefficients for the present study and the Sanfeliuand Fernandez (1996) study are significant at p < .0I.

leeted in the present study (familiarity, eomplexity, imageagreement, image variability, and age of aequisition) areall relatively small in magnitude, suggesting that the mea­sures represent independent attributes. Overall, these cor­relations are similar to the ones obtained by Snodgrassand Vanderwart (1980) and by Cyeowiez et al. (1997).

Familiarity is negatively eorrelated with age ofaequi­sition (- .578), suggesting that names of eoneepts thatare familiar tend to be learned at an early age. As is shownin Table 5, familiarity is positively eorrelated with fre­queney (.360). The eorrelation between age of aequisi­tion and frequeney, although modest ( - .367), is also sig­nifieant. Of the eorrelations among our own measures,name agreement and image agreement are negativelyeorrelated (- .343), suggesting that eoneepts that have

many names also evoke many different images. The eor­relation between age ofaequisition and name agreement(.453) suggests that, for eoneepts aequired at an earlyage, the level of agreement is high. The faet that Frenehspeakers' name agreement eorre1ates less with word fre­queney than with age ofaequisition is similar to the find­ing that, for Ameriean and Eng1ish speakers, age of ae­quisition has a greater influenee on pieture naming thando other variables (Caroll & White, 1973; Ellis & Mor­rison, 1998). The eorrelations between image variabi1ityand both age of aequisition (- .654) and familiarity(.616) suggest that eoneepts that are 1earned early evokemore images than do eoneepts that are learned late. Fi­nally, visually eomplex pietures tend to be rated as unfa­miliar (signifieant eorre1ation of - .391).

Table5Correlations Among the Measured Variables in a French SampIe for Cycowicz, Friedman, Rothstein,

and Snodgrass (1997) Pictures

Variable NA % IA Farn Comp I-Var A-A Freq]

Name agreement (H) 1.000Name agreement (%) - .952* 1.000Image agreement - .343* .370* 1.000Familiarity -.183* .215* -.035 1.000Visual complexity .081 - .081 - .009 - .391* 1.000Image variability - .255* .317* - .097 .616* - .210* 1.000Age ofacquisition .453* -.524* -.140* -.578* .214* -.654* 1.000Frequencyt - .140* .151* - .005 .360* - .136* .340* - .367* 1.000

Note-NA, name agreement; IA, image agreement; Farn, familiarity; Comp, visual complexity; I-Var, imagevariability; A-A, age ofacquisition; Freq, frequency (taken from Content, Mousty, & Radeau, 1990). *Corre­lation coefficients significant atp < .0I. t Conceming the frequency variable, correlations among all measuredvariables were obtained for a sampIe of 355 concepts only, for which frequency values were available.

536 ALARIO AND FERRAND

CONCLUSION

The main goal of the present research was to collectnormative data for pictorial stimuli that could be used inresearch with French-speaking sampies (see Sanfeliu &Fernändez, 1996, for the same approach in Spanish). De­scriptive ratings for a number of picture attributes of thedrawings previously presented by Cycowicz et al. (1997)and by Snodgrass and Vanderwart (1980) with AmericanEnglish-speaking subjects are now available for French­speaking subjects. We believe that these normative datawill be particularly useful for French researchers inter­ested in memory, language, and other cognitive processes.

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3.07

1.11

3.17

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3.87

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830.

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630.

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632.

300.

792.

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329

cage

cage

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100

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1.80

0.89

4.38

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0.86

2.27

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330

pois

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570.

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652.

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200.

484.

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341

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0.69

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0.42

342

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893.

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140.

443.

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349

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3.43

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0.46

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6.8)

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inen

tran

ches

(-),

cake

(0.6

3),

mic

hede

pain

(-)

38br

osse

bros

seb

rush

00

0ba

laye

tte

(0.0

4)39

bus

bus

bus

00

0ca

r(8

05.7

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eau

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eau

cam

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00

drom

adai

re(0

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45ca

non

cano

nca

nnon

00

Ifu

sil

(44.

6)46

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sque

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cap

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0be

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5.0)

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chen

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0m

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cele

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3fe

noui

l(0

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queu

ede

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chai

nech

aine

chai

nI

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brac

elet

(4.8

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aino

n(1

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coll

ier

(13.

0)54

cen

sece

rise

cher

ry0

00

prun

e(0

.5),

po

mm

epo

urri

e(-

)55

poul

epo

ule

chic

ken

00

0po

ulet

(10.

7),

coq

(18.

4)56

buri

nto

urne

vis

chis

eI4

27

tour

nevi

s(0

.6),

rabo

t(0

.5),

spat

ule

(0.4

),pi

ncea

u(9

.1),

outi

l(2

5.1)

AP

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ND

IXB

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tin

ued

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Item

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nded

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eE

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dom

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chur

ch0

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chap

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(32.

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ciga

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ciga

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00

clop

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horl

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horl

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62nu

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5.4)

63cl

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0te

tede

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n(-

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man

teau

man

teau

coat

00

0im

perm

eabl

e(5

.0),

vest

e(2

0.6)

66m

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rnat

sco

rn0

00

epis

dem

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(-)

67ca

nape

cana

peco

uch

00

0di

van

(16.

4)70

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cup

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0bo

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71ce

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(68.

8),

bich

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74po

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fill

ette

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peti

tefi

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port

epo

rte

door

00

0fe

netr

e(1

96.4

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rte

vitr

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poig

nee

poig

nee

door

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0el

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e(0

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rroq

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ucon

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(112

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ppe

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lettr

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0cl

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port

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flut

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arin

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rdre

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fox

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0lo

up(3

8.8)

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cor

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chho

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02

trom

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1.9)

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frog

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ede

lune

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trx

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rais

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110

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inse

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mou

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te(6

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4m

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gant

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145

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146

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153

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coll

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neck

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ingl

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3.9)

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guil

leac

oudr

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156

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uec

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2bo

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7oi

gnon

oign

onon

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20

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l(4

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echa

lote

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2.6)

158

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geor

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oran

ge0

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man

dari

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159

autr

uche

autr

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0fl

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rush

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0pl

ume

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0fu

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163

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ange

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rune

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ande

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styl

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styl

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169

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00

0m

anch

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170

poiv

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poiv

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pepp

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172

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0po

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175

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eter

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pitc

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0ca

rafe

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176

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178

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sae

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sac

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n(0

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coch

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180

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me

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pom

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dete

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to0

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pata

te(1

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181

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n(0

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183

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189

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roll

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190

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sail

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206

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207

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247

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born

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mpe

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econ

ham

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fish

hook

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2gl

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she

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0ca

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(11.

7),

casq

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pioc

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mpe

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tri

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1),

tore

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buch

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bois

(215

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fago

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(-),

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5m

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asm

arac

asm

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as6

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cast

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(0),

cym

bale

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296

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mic

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mic

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2tl

297

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tap

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0m

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0ch

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302

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308

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0re

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110

pell

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pilo

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show

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(-),

pom

mea

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douc

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2se

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ring

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e0

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piqü

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0.8)

313

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bour

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30

2cy

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(0)

314

tele

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tele

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60

shak

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0ro

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318

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cabi

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tele

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rem

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319

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ran

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03

tapi

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tato

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omit

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324

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63

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pois

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344

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bell

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