Pupillary responses to syntactic ambiguity of sentences

BRAIN

AND

LANGUAGE

27, 322-344 (1986)

Pupillary Responses

to Syntactic Ambiguity of Sentences

MICHAEL SCHLUROFF,THOMASE. ZIMMERMANN, R. B. FREEMAN,JR., KLAUS HOFMEISTER,THOMASLORSCHEID,AND ARNO WEBER University

of Konstanz,

Konstanz,

West Germany

Pupillary responses have proven to be reliable physiological correlates of cognitive effort in a variety of tasks, including language processing. To investigate the relation between psychological and syntactic complexity 20 syntactically ambiguous sentences, balanced for bias, were presented to 16 subjects, while their pupil size was continuously measured. These sentences could be read as verb oriented (syntactically more complex) or object oriented (syntactically less complex). Principal components analysis of pupillary movements revealed that verb-oriented readings resulted in greater pupillary dilations than object-oriented readings, indicating that syntactically more complex sentences, as determined via a formal grammar, require greater cognitive effort in processing. This is viewed as further evidence for the notion that syntactic and psychological complexity are related. High- and low-bias sentences did not induce comparable differences in pupillary movements, indicating that the “multiple meaning theory” may have to be modified. D 1986 Academic

Press.

Inc.

SYNTACTIC AND PSYCHOLOGICAL

COMPLEXITY

OF SENTENCES

Words and sentences with more than one meaning are so much part of our everyday use of language that we are not usually aware of ambiguities. The language mechanisms allowing us to resolve most of these ambiguities with ease and with such speed that we do not, as a rule, consciously choose among the possible meanings, must be quite powerful. Understanding these mechanisms would supply insight into human language processing and thus into the workings of the human brain. One approach to gaining this insight has been to compare the relative cognitive effort required in the processing of different sentences. The development of generative grammatical theory inspired various studies purporting to find a direct correspondence between generative, This work was conducted at the “Sonderforschungsbereich 99” at the University of Konstanz, West Germany, and supported by grants of the “Deutsche Forschungsgemeinschaft.” Address requests for reprints to Dr. M. Schluroff, Postfach 5560, SFB 99, AG Freeman, 7750 Konstanz, West Germany. 322 0093-934X/86 $3.00 Copyright All rights

0 1986 by Academic Press, Inc. of reproduction m any form reserved.

SYNTACTIC AMBIGUITY

323

particularly transformational, derivations of sentences on the one hand, and the cognitive effort required in the comprehension of these sentences, on the other hand. The results of these studies were equivocal (Mehler, 1963; Gough, 1965; Clifton, Kurcz, & Jenkins, 1965; Savin & Perchonock, 1965; Smith & Gough, 1969; Clifton & Odom, 1966; Koplin & Davis, 1966; Matthews, 1968; Wright, 1968; Glucksberg & Danks, 1969; Scholes, Heilman, & Rasbury, 197.5; Richardson, 1976). Thus, a first-order (“oneto-one”) correspondence between formal rules of (generative) grammar and psychological complexity did not seem tenable. But the idea is all too intriguing that syntactic and psychological complexity should be correlated. For a number of years it has been a widely held opinion that “if one sentence is syntactically more complex than another, then ceteris pariblrs, it should, perhaps only on the average, create more difficulties in its comprehension” (Bar-Hillel. 1964, p. 200). Some researchers, using second-order measures of syntactic complexity such as mean Yngve depth (Yngve. 1960: Martin & Roberts. 1966). achieved results indicating just such correlations (Forster, 1966, 1967. 1968a. 1968b; Herriot, 1968: Wright, 1969; Wang, 1970a, 1970b; Beatty, 1982: Schluroff, 1983). Beatty and Schluroff (1980) and Schluroff (1982). using mean Yngve depth and an explicit generative grammar (Wienold. Schluroff, Guenther, & Lutz, 197s) ranging over a substantial part of the English language, supplied further evidence that cognitive effort in the processing of sentences is greater with syntactically more complex sentences. The use of such correlations in predicting the relative cognitive effort required for sentence processing may have practical impact, for example, on language teaching (Carroll. 1963. 1975: Harnischfeger & Wiley, 1977; Wienold, Achtenhagen, Van Buer, Rosner, & Schluroff. 1976; Wienold et al., 1982). The claim that a formal grammar may in part predict cognitive effort in sentence processing requires convincing and consistent evidence, because the very complexity of language and the number of confounding factors determining psychological complexity of sentences often allow for alternative explanations of experimental data. Savin and Perchonock’s data (1965) at first seemed to make a convincing case for the psychological reality of some then-current concepts of generative transformational grammar. Yet investigations along these lines brought forth new questions rather than unequivocal evidence supporting the original conclusions. Goldman-Eisler and Cohen (1970) even suggested that the effects found in these studies could be explained more easily by frequency effects. The frequency of language features (such as frequency of phoneme combinations, lexical items, or syntactic constructions or phrases) constitutes but one confounding effect contributing to the psychological complexity of sentences. Other factors are, to name just a few, familiarity

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ET AL.

with these features, recency, sentence length, semantic or emotional content, or different combinations of these. Responses to different sentences are thus responses to very complex aggregates of features determining psychological complexity. It is nearly impossible to change one feature of a sentence without changing other features, too. The very complexity of language, however, offers a way out of this problem. Ambiguous sentences hold the opportunity of studying responses to different readings of the same sentence rather than responses to different sentences. By using ambiguous sentences as stimuli it is thus possible to control perfectly for sentence length, frequency effects, familiarity with lexical items, and other factors. Differences in processing effort may then be ascribed to the different readings given to a sentence rather than to a change of experimental conditions. For this reason we investigated the relation between syntactic and psychological complexity of sentences by using ambiguous sentences in which the two different readings differed in syntactic complexity, hypothesizing that greater syntactic complexity induces greater psychological complexity. AMBIGUITY AND BIAS

Sentences may be ambiguous lexically (There is water in the port, where port may mean “wine” or “harbor”) or syntactically (They are racing horses, which may either refer to activities of some people or to a breed of horses). Ambiguous sentences usually have a more or less pronounced bias toward one of their meanings, which means that one of the meanings is usually preferred over the other, either in general, in a given context, or to an individual. An example for a syntactically ambiguous sentence in German is (1). (1) Peter verfolgte den Mann mit dem Motorrad. (Peter chased the man on the motor bike).

In German, this sentence may be read in two ways. In the first reading the grammatical subject of the sentence (“Peter”) used the object (“Motorrad”/motor bike) denoted in the prepositional phrase to perform the action denoted by the verb (“verfolgte”/chased). We call this reading verb oriented. In the second reading of this sentence the grammatical object of the sentence (“den Mann”/the man) is in possession of the object (“Motorrad”/motor bike) denoted in the prepositional phrase. This reading we call object oriented. The difference between the two meanings becomes readily apparent when (1) is transformed into the

SYNTACTIC

325

AMBIGUITY

passive voice. Thus (2) reflects the verb-oriented, meaning:

(3) the object-oriented

(2) Der Mann wurde von Peter mit dem Motorrad verfolgt. (The man was chased by Peter on the motor bike.) (3) Der Mann mit dem Motorrad wurde von Peter verfolgt. (The man on the motor bike was chased by Peter.)

As both readings appear likely, (1) is a lo~+bias ambiguous sentence. An example for a high-bias sentence of the same syntactic type is (4). Most persons would read (4) as verb oriented as paraphrased in (4’) rather than as object oriented such as paraphrased in (4”). (4) (4’) (4”)

The The The

boy boy boy

caught caught caught

the ball the ball the ball

with the left hand. using his left hand. which had a left hand

(e.g..

painted

on it)

Thus (4) is a sentence highly biased toward its verb-oriented reading. Research on sentential ambiguity has focused mainly on the “onemeaning hypothesis” versus the “multiple-meaning hypothesis” (for an overview see Kess & Hoppe, 1978). According to the one-meaning hypothesis-or “unitary perception hypothesis” (Carey, Mehler, & Bever. 1970a, 1970b)-a sentence is first interpreted one way, and only if that interpretation does not fit the context is an alternative interpretation tried out. The multiple-meaning hypothesis-or “exhaustive computation hypothesis” (Carey et al., 1970a, 1970b)-proposes that all meanings of a sentence are at least partially computed, and then one of the possible meanings is selected. If more than one meaning is computed one would expect additional cognitive resources to be employed in the processing of ambiguous sentences compared to unambiguous ones. With high-bias sentences, the ambiguity goes unnoticed more easily. The processing of high-bias sentences may be very similar to the processing of unambiguous sentences (Carey et al., 1970a, 1970b). Thus, the degree to which sentences are biased should be taken into account with an investigation of ambiguous sentences. Task requirements emerge as another important variable. Mistler-Lachman (1972) demonstrated that different task requirements may result in different processing strategies, with different task requirements involving different levels of comprehension, hence different levels of cognitive effort. She argued that some of the equivocal results pertaining to the processing of ambiguous sentences may be due to different task requirements, which may change processing strategies (Wright & Kahneman, 1971). It appears advisable, then, to keep task requirements as close as possible to “natural” sentence processing so as not to confound the effects of experimenter-induced task requirements

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ET AL.

with sentence-induced ones, Therefore, as indicator of psychological processing as possible of experimenter-induced task of unobtrusive measurement would be end.

PUPILLARY

the experimental variable used mode should be as independent requirements. An on-line method a useful asset in achieving this

MOVEMENTS AS A PHYSIOLOGICAL PSYCHOLOGICAL COMPLEXITY

CORRELATE

OF

Physiological measures appear appropriate, as they do not necessarily interfere with the subject’s task. We chose pupillary movements to monitor cognitive activities during sentence processing, since pupillary movements have proven to be reliable indicators of relative cognitive difficulty across a variety of cognitive tasks and even across different laboratories (Beatty, 1982). Variations in pupil size have been proposed as a correlate of the complexity of mental processes (for an overview see Goldwater, 1972; Janisse, 1977, chap. 4). In a sentence comprehension task, Schluroff (1982) presented sentences of various length, construction, and content, each of which had been assigned a value of grammatical complexity. As an index of psychological complexity mean pupil dilation during listening was found to correlate strongly with grammatical complexity, better even than the subjects’ ratings of sentence comprehensibility.

MEASURING

SYNTACTIC

COMPLEXITY

Syntactic complexity, as opposed to psychological complexity, reflects the complexity of syntactic descriptions of sentences. To obtain measures of syntactic complexity, abstract representations of sentences are needed where elements and their relations can be counted. To distinguish different meanings of a sentence, such representations have to differ for different meanings of the same sentence. Formal grammars, as developed by linguists, supply such representations of sentences. One method of representing the different meanings of sentences like (1) is bracketing as in (5) and (6), where (5) indicates the verb-oriented, and (6) the object-oriented reading. (4) (Peter (5) (Peter

(verfolgte (verfolgte

(den (den

(Mann Mann)

(mit (mit

(dem (dem

Motorrad)))))). Motorrad)))).

An equivalent mode of representing these two readings are tree structures as in (5’) and (6’) (Kratzer, Pause, & v. Stechow, 1973, pp. 34 ff).

SYNTACTIC

(5’) Pi :r verfolgte

AMBIGUITY

327

den Mann mit dem Motorrad.

L I

S (6’) Peter verfolgte

den Mann mit dem Motorrad.

S A measure of structural complexity applicable to tree graphs, and with some empirical support as a second-order approximation to psychological complexity, is mean Yngve depth (Yngve, 1960; Forster, 1966; Schluroff, 1982, 1983). Mean Yngve depths (y) for (5’) and (6’) are 0.86 and 1.14, respectively. We expected, therefore, that syntactically ambiguous sentences like (1) would induce higher cognitive effort, hence greater pupillary dilations, in subjects resolving the ambiguity into the verb-oriented meaning, compared to subjects resolving the ambiguity into the object-oriented meaning. From these assumptions we derived our first hypothesis: verboriented responses will be associated with greater pupillary dilations than object-oriented responses. High-bias ambiguous sentences seem to be processed much like unambiguous sentences. Following the multiplemeaning hypothesis, we assumed low-bias ambiguous sentences to require additional cognitive effort to (fully or partially) compute both meanings. With high-bias ambiguous sentences we assumed that less computation would be required, hence less cognitive effort. From these assumptions

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ET AL

we derived our second hypothesis: low-bias syntactically ambiguous sentences will be associated with greater pupillary dilations than high-bias sentences. METHOD Stimulus Material A list of 37 different sentences in German was constructed, similar in length and syntactic structure to (1). This list was presented to 65 subjects (university students with German as their native language) with the instruction to transform the sentences into the passive voice. If they felt that more than one transform was possible they were instructed to write down the transform they found more natural. In this manner we obtained “preferred readings” for each sentence on the list, either object oriented (0) or verb oriented (V). The quotient (0-V)/(V-0), ranging from - I .OO to 1.00, was taken as the “bias index” (BI) for that particular sentence, with a low BI indicating predominantly verb-oriented readings for the particular sentence, and a high BI indicating predominantly object-oriented readings. From this list of sentences a subset of 20 sentences was formed, containing the 5 sentences with a high bias toward their verb-oriented reading (- 1.00 < BI < -0.92), 5 sentences with a high bias toward their object-oriented reading (1.00 < BI < .93), and IO low-bias (- 0.67 < Bl < 0.26, mean = - 0.27) sentences.

Subjects Subjects were 16 volunteers (9 female, 7 male; mean age 22.6, SD = 4.79) who were either paid DM 10 (deutsche marks) or received course credit for their participation.

Apparatus During the experiment proper, subjects were seated at a table on which there was a lever with which they were to initiate each trial. Head fixation during trials was achieved by means of a combined chin and head rest. At a distance of I.10 m, with the center at eye level, there was a visual display screen (Hewlett-Packard) on which stimuli were projected under the control of a general purpose digital computer and interface system (Hewlett-Packard HPl000/45F and LlOOO). Vertical pupil diameter was measured by a television pupillometer (Whittaker 19943). The camera was aligned on the horizontal plane of the subject’s left eye and displaced 35” of visual angle from the line of gaze. Momentary pupil diameter was sampled and digitized at IOO-msec intervals during experimental trials. All phases of experimentation-stimulus presentation, data acquisition, and timing--except initiation of trials were under the control of the computer system.

Procedure Subjects were first familiarized with the general purpose of the experiment and the equipment used. Then a test of “grammatical sensitivity” (see appendix) was administered. This test consisted of five blocks of three sentences each, which the subjects had to transform according to a given model into a grammatically different form. This test served to assure that subjects understood the nature of the task in the experiment proper, were capable of performing it, and to divide the subjects into two groups based on their differences in grammatical sensitivity. All of the subjects had sufficient abilities to participate in the subsequent experimental task. Subjects were then seated at the table, and the chin rest and chair position were adjusted to achieve maximum subject comfort. The procedure was explained to the subject with

SYNTACTIC

AMBIGUITY

329

the instruction to refrain from blinking as much as possible during trials. After administration of four practice trials the subject again was asked to refrain from blinking during trials, and then the subject initiated each trial. Between trials the subject was free to blink or move. In general, subjects took at most only a few seconds between trials. After the 10th trial there was a 2-min break, during which the subject was asked to leave the chair. The appearance of the word “Fertig?” (ready) on the display screen signaled to the subject that the next trial could be initiated by moving the lever. After a delay of 1.5 sec. a row of x’s appeared on the screen, spaced at the same intervals as the words of the subsequently displayed sentence. These x’s remained on the screen for 2 set, to obtain pupil baseline diameter, and were then replaced by the stimulus sentence. The sentence was displayed for 3.5 set and then replaced by the row of x’s again. This signaled to the subject to transform the sentence to the passive voice. The x’s stayed on the screen for 6 sec. then the subjects were signaled to voice their transform within the following 4 sec. The transform was recorded by the experimenter. This 4-set response period was followed by a 2-set control period, at the end of which a short tone signaled the end of the trial to the subject. During the 18 set of the trial, vertical pupil diameter was sampled and recorded every 100 msec. After all 16 subjects had been run, they were ranked according to their scores in the grammatical sensitivity test. To achieve better separation between high and low scorers, the six subjects closest to the overall mean score were dropped from the analysis. Thus the data of 10 subjects remained in the analysis. Pupillary records for individual samples were inspected for eye blinks and other artifacts. Trials with only a few eye blinks and/or small artifacts were corrected according to a linear interpolation procedure. Trials with major artifacts were discarded. Also discarded were trials for which subjects failed to verbalize an identifiable transform of the stimulus sentence. The remaining trials were then averaged within subjects in two ways: (a) according to subject answers: verb- and object-oriented; (b) according to “bias index”: responses to low-bias sentences were assigned to one group, “low bias,” and responses to the highbias sentences to another group, “high bias.” This resulted in two sets of grouped data consisting of 20 averaged trials each (10 subjects, two groups). Note that both sets comprise the same data, i.e., all pupillary responses, with the difference between both sets lying in the method of averaging only.

RESULTS

Grammatical Sensitivity Test The highest achievable score in this test was 35 points. The scores achieved by the subjects ranged from 18 to 33.5 (x = 25.35, SD = 6.72). The five subjects with the highest scores in the grammatical sensitivity test were assigned to one group, HI (x = 31.60, SD = 1.64), and the five subjects with the lowest scores to another group, LO (x = 19.10, SD = 1.14). The task in the last of the five blocks of the test was to transform sentences into the passive. The results of this subtest were correlated with total test scores. They were found not to change the grouping of the subjects. Disambiguation Subjects in the experiment the subjects in the normative

disambiguated sentences very much like study: Bias indices of the 20 sentences

330

SCHLUROFF

ET AL.

used in the experiment correlated highly with those of the corresponding sentences in the normative study (Y = .96), indicating that the difference in procedure (written vs. oral answers, lab situation) did not have a major influence on preferred readings of the sentences. Valid trials (n = 177) included 112 verb-oriented, and 65 object-oriented subject responses. This tendency toward verb-oriented disambiguations was significant (t(l8) = 4.92, p < .Ol). The mean bias index of the subject responses in the experiment (BI = - 0.27) equaled that obtained from the same set of sentences in the normative study (BI = -0.27). Low scorers in the grammatical sensitivity test tended to choose verboriented disambiguations more often than high scorers (r(8) = 2.41, p = < .05). Pupillary

Changes

Figure 1 presents averaged evoked pupillary responses across all trials and subjects. Temporal variations in processing load while reading, transforming, and speaking may be inferred from the task-evoked pupillary response. During the baseline period (O-2 set) there is a pupillary constriction, as a reflex to the x’s appearing on the otherwise darker screen. Beginning with the presentation of the sentence (2 set) there was a substantial dilation over baseline, which continued until about 7.5 set during the transformation phase. From that time onward, during most of the transformation phase (5.5 through 11.5 set), there was no substantial change in the average diameter of the pupil. About 1 set after the signal READ

ClONTROl

SAY

TRANSFOAM

\

;/-;i

\

3.90

0.00

2.00

4.00

I

I

I

6.00

8.00

10.00

I

J

I

12.00

14.00

16.00

18.00

SECOND!.

FIG. 1. Pupillary evoked responses during reading syntactically and transforming them into the passive voice. (Mean of 10 subjects, sentences of syntactically similar construction.)

ambiguous 177 trials,

sentences 20 different

SYNTACTIC

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AMBIGUITY

tone, there was again a substantial rise, peaking at about 14 set, followed by a fairly even reconstriction continuing into the control period (16-18 set), at the end of which pupil diameter reached its initial diameter. Papillary Changes as Effect of Subject Disambiguation Figure 2 shows pupillary dilations over baseline, averaged according to subject answers: pupil dilations in trials with verb-oriented and objectoriented responses, respectively. Figure 2 thus represents pupillary responses to the same sentences answered in two different ways. To correct for differences in baseline values, each trial was baseline corrected, i.e., mean pupil diameter during the baseline period (O-2 set) was subtracted from all values. (Tryon, 1975; Hakerem, 1974). Greater pupil dilations ensued in trials which were read by subjects as verb oriented, compared to object-oriented readings, as is shown in Fig. 3. To test this difference we submitted our data-to our knowledge for the first time in a study on pupillary movements-to a principal components analysis (BMDP4M. Dixon, 1979). The advantage of principal components analysis (PCA) for the evaluation of pupillary movements lies in the fact that all information in the pupil data is taken into consideration rather than that of single data points as in latency, peak, or mean dilation measures. Furthermore, components computed in PCA, together with their factor scores, directly correspond to the underlying pupillary movements. Following Chapman, McCrary, Bragdon, & Chapman (1979, p. 82: cf. Lorscheid, 1983) we assumed that, analogous to an evoked cortical re-

0.00

2.00

4.00

6.00

6.00

10.00

12.00

14.00

16.00

FIG. 2. Influence of type of disambiguation on pupillary dilation. oriented disambiguation: broken line: object-oriented disambiguation.

Solid

16.00

SECONDS

line:

verb-

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ET AL.

TRANSFORM

fAcTa I

SAY

FMIOI 2

FACTM 3

FACTCR4

a6 FET(R 6 ---

0.5

FIG. 3. Pupillary dilations: Principal components analysis. Factor loadings time, for pupillary data (as represented in Fig. 1). Seven factors extracted. above 0.5 are shown. The factor loadings represent the contribution of component to the variance about the centroid of pupillary movement at time points.

sponse, an evoked pupillary of independent components

plotted against Only loadings the respective the respective

response can be expressed as a summation

R(t) = Fl At) + F2 g(t) + . . . + Fkp(r) + C(t), where R(t) represents the evoked pupillary response as a function R of time (f), j(t), g(t), etc., represent the so-called “fundamental time courses” of each of the components (for their computation see Dixon, 1979, pp. 74-75), with Fl, F2, etc., as factor scores indicating the amount of contribution of each factor to the evoked pupillary responses. C(t) stands for the centroid (mean) of all evoked pupillary responses on which the PCA is computed. Using the BMDP4M analysis the pupil data were first transformed into a correlation matrix of intercorrelations between each pair of time points. Principal components (the term “component” will be used here synonymously with factor) were then extracted from the whole data set, and normalized varimax rotation (Kaiser, 1958) was performed. This method makes it possible to extract the minimum number of components which account for most of the variance in the original data. Varimax rotation preserves orthogonality and thus uncorrelatedness between components. Seven factors (principal components), accounting for 96.8% of the total

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333

variance, were extracted from the correlation matrix for evoked pupillary responses, using an eigenvalue of 1.0 as criterion. These were then normalized and rotated using the varimax method as described above. The loadings of the five factors with values above 0.5 are shown in Fig. 3. Values of factor loadings may range from - 1.O to 1.0, indicating “degree” of relatedness of the factor to the data points. Contrary to significance levels, where the 5 and 1% levels have come to be generally accepted, no comparable standards of acceptance exist for the cutoff point for factor loadings. Therefore, we chose a very conservative approach, setting the cutoff point at 0.8. With this approach, Factors 1, 2, and 3 demand attention. Factor 1 extends from 8 set to at least 18 set, with a maximum at about 12 set, during the SAY period. Factor 2 extends from about 3 to 6 set, with a maximum loading at 4 set, during the READ period. Factor 3 falls almost fully into the second half of the BASE period. Thus, it would appear that these factors may be associated with the time periods of the experimental trials. Because the PCA by itself provides no information on the relation of components to the experimental conditions (here, pupillary movements associated with different interpretations of sentences by the subjects), seven independent ANOVAs were computed with the factor scores of each principal component. The results of these ANOVAs reflect the association of each principal component with the original variables under study. Factor 1 was due to an effect of subject answers (F( 1, 8) = 6.51, p < .034). Factor 3, with the highest loadings during the READ period in this analysis, failed to reach significance (F(1, 8) = 4.06, p = .08) for the effect of subject answer. Figures 2 and 3 suggest that the full difference between object- or verb-oriented subject response appears less than 1 set after sentence presentation. In the light of this closer analysis the apparent difference does not appear sufficiently reliable. Factor 3 was due to an effect of group (HI vs. LO in grammatical sensibility), F(1, 8) = 7.74, p = .024. No other factors reached significance in this analysis. Based on the assumption that an evoked pupillary response can be expressed as a summation of independent components (see above), we may regard the factors extracted via PCA as factors associated with experimental variables. By combining factor scores with the fundamental time course of the original data, we have an estimate of the influence of a factor on pupillary movements in units of the original data, that is, in millimeters. These estimates were recomputed from the results of the PCAs using the method introduced by Chapman et al. (1979): for each of the time points the loading of the respective factor was multiplied by the centroid’s

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standard deviation for the corresponding time point, to reconvert the normalized scores into the original metric of pupil dilation. The “fundamental time course” obtained in this way was then multiplied point by point with the score obtained from PCA corresponding to that factor and experimental condition. This method reconverts the factor loadings to the original metric of pupil dilation and thus indicates the contribution of the factor to pupillary movement depending on its contribution to the total variance of the centroid. An analysis 6f variance revealed Factor 1 to be associated with verboriented vs. object-oriented interpretations of sentences by subjects. Figure 4 presents the estimated influence of this factor on the pupillary movement associated with verb-oriented and object-oriented responses. Figure 4 was obtained by plotting Fl ff(t) against the time points of the trials, where FZ represents the factor scores for component 1, fit) the product of the mean and standard deviation for the particular time point. This may be conceptualized as an estimate of pupillary dilation attributable to the effect of subject answers (verb oriented vs. object oriented). Figure 4 suggests that verb-oriented answers resulted in greater pupillary dilations than object-oriented answers. The effect seems to begin early in the READ phase and continues throughout the remainder of the trial. However, as we chose a cutoff point of 0.8 for factor loadings, ESTIK FWILLMY OILATICN

1

-4-a

/N--l--

-

-.-----,./---. ---JJ

-88

-

-128

FIG. 4.

I

I

I

I

I

I

I

II

Ii

I

I

I

I

Time course of Factor 1 of PCA for pupillary dilations in a sentence transformation This time course is an estimate of the pupillary variation around the centroid due to interpretation of the sentence by subjects. Solid line: verb-oriented readings; broken line: object-oriented readings. task.

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AMBIGUITY

we are justified in interpreting this figure only for the time period in which factor loadings are at least 0.8, that is, from 8 set on. Figure 5 shows the estimated time course for Factor 3, the factor shown to be associated with grammatical sensitivity. High scorers on the grammatical sensitivity test show less pupil dilation during the BASE period. Figure 5 appears to suggest that the same effect holds for the READ period and that during the remainder of the trial the effect is reversed: high scorers appear to show more pupil dilation than low scorers, mostly during the SAY period, with little difference between groups during the TRANSFORM period. However, as we chose a cutoff point of 0.8 for the factor loadings, we are justified in interpreting factor loadings only for the BASE period, in which factor loadings are greatet than 0.8. The estimated effect of grammatical sensibility is considerably greater than the effect of ANSWER (cf. Figs. 4 and 5. respectively). However, it is statistically reliable-with a cutoff point of 0.8 for factor loadingsfor the BASE period only. This indicates high interindividual variance of pupillary movements in regard to the effect of grammatical sensibility. ESIIY 128

WILtNN

. BASE

DlLATlLH

READ

TRANSFORM

SAY :ONTACIL

Fm. 5. Estimated effect of grammatical sensitivity of subjects on pupillary evoked responses: Time course of Factor 2 of PCA for pupillary dilations in the sentence transformation task. Solid line: grammatically more sensitive subjects (II = 5): broken line: grammatically less sensitive subjects 07 = 5). Note the crossover of the two lines shortly after set: grammatically more sensitive subjects seem to exert less cognitive effort while reading than do grammatically less sensitive subjects. In the latter part of the trial (TRANSFORM, SAY, and CONTROL periods, respectively). grammatically less sensitive subjects appear to exert more cognitive effort.

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Therefore, an analysis of pupil movements was performed excluding the BASE and CONTROL periods, and pooling HI and LO groups. The PCA extracted five factors using an eigenvalue of 1.0 as criterion. These five factors accounted for 96.1% of the total variance. Factors l-4 had loadings over 0.5. The loadings of these factors are plotted against time in Fig. 6. Using a loading of 0.8 as cutoff point, Factors 1, 2, and 4 deserve mentioning. Factor 4 is in Second 2, and may thus be regarded as reflecting baseline effects. This leaves Factors 1 (8-16 set) and 2 (3-6 set), respectively, for further analysis. Five independent ANOVAs were performed on the factor loadings. Factor 1 reflected an effect of ANSWER (F(l) 9) = 7.90, p = .02), as did Factor 2 (F(1, 9) = 5.28, p = .047). As Fig. 6 indicates, Factors 1 and 2 have loadings above .8 in the time periods 8-16 set, and 3-6 set, respectively. Thus, the effects of Factor 2 are related to the READ period, and the effects of Factor 1 to the TRANSFORM and SAY periods, respectively. The results of the ANOVAs indicated that both these factors were due to an effect of how subjects disambiguated the stimulus sentences.

FETm

1

5

SAY

\ FACTOR 2

FMTrn

3

-...-

FACTce I

FIG. 6. Factor loadings plotted against time, for principal components analysis of pupillary data (as represented in Fig. 3). neglecting BASE and CONTROL period. Five factors have been extracted. Only loadings above 0.5 are plotted. Note that only three factors seem to remain, with Factor 4 as a baseline effect. Factors 1 and 2 appear to differentiate between the READ and the remaining time periods of the trial.

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Pupillary Changes us Effect of Bias In the present study, bias of a sentence was determined via a normative study: sentences which most subjects in the normative study had read as verb oriented were considered high bias, as were sentences which most subjects read as object oriented. Sentences which were read as either verb or object oriented by about equal numbers of subjects in the normative study were assigned to the low-bias group. Pupil responses to both groups of sentences were baseline corrected (see above) and averaged per subject. Mean pupillary responses to highand low-bias sentences are plotted against time in Fig. 7. Figure 7 suggests that low-bias sentences evoked greater pupil dilation than did high-bias sentences. To test this difference, we subjected these data to a PCA in the manner described above. This PCA extracted seven factors, using an eigenvalue of I .O as criterion. These seven factors accounted for 977~ of the variance. Figure 8 shows the values of these seven factors for values over OS, plotted against time. Note the similarity of the factors with those extracted from evoked pupil responses averaged by ANSWERS (Fig. 3). There is one exception: in this analysis, in the period of about 7-18 set there are two factors with loadings over .5. These two factors appear to be related to the TRANSFORM and SAY periods, whereas in the analysis of pupillary responses according to subject answers (cf. Fig. 3), only one factor had loadings over 0.5 in these periods. Seven independent ANOVAs were performed on the scores of these factors. Only Factor 4 reached significance (Ft I, 8) = 5.86, p = ,042) .60 BASE 1

READ

SO

.40 1

I

I 0.00

2.00

4.00

6.00

6.00

10.00

12.00

14.00

-I 16.00

1 B.OC

SECONDS

FIG. 7. sentences;

Pupil dilations for high- and low-bias broken line: high-bias sentences.

ambiguous

sentences.

Solid line:

low-bias

338

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ET AL.

IIW

T \\

BASE-T 6.9 FkXR2

TRANSFORM

SAY

CONTROL

----6-6 Fmm 3 ---

P7 FNJlR4

.------

06

FOR5 -.--

I

9.5 FACTW 6

-..-

I

I

2

3

4

5

I 6

7

6

9

16

I,

12

13

14

15

16

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18

5EaN6

FIG. 8. Pupil dilations with high- and low-bias ambiguous sentences. Factor loadings plotted against time (for factors and time points where factor loadings are greater than 0.5).

for grammatical sensitivity. Factor 4 obviously falls mostly into the BASE period and thus does not appear related to stimuli. DISCUSSION

Pupillary dilations in the present study were, for the READ phase, about 0.20 mm. This agrees with Wright and Kahneman (1971). Maximum dilation, averaged across subjects, was about 0.5 mm, comparable to the largest pupillary dilation in Beatty’s (1982) review, evoked by difficult mental multiplication (from Ahern, 1978; cf. Ahern & Beatty, 1979, 1981), and higher than that evoked by short-term recall of seven digits (cf. Janisse, 1977, p.165). It is slightly lower than the maximum dilation reported by Kahneman et al. (1969) for a digit transformation task, in which 4 digits had to be recalled and repeated after being incremented by 3. Subject responses interpreting syntactically ambiguous sentences as verb oriented were associated with greater pupillary dilations. This result is consistent with our hypothesis. Since the verb-oriented sentences had been classified as syntactically more complex than object-oriented sentences, this result is also compatible with the assumption that analysis of syntactical complexity is suited to predicting relative cognitive effort required for processing a sentence. The results of our experiment may

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339

thus be viewed as further support for the assumption that linguistically derived models or grammars may be appropriate for predicting psychophysiologically relevant events associated with language processing (Stanners, Headley, & Clark, 1972; Wright & Kahneman, 1971; Schluroff, 1982, 1983). An alternative explanation for the differential pupillary dilations would be that verb-oriented readings are generally less frequent, hence less practiced, than object-oriented readings. For our sample, this does not seem to have been the case, as there was a bias toward the verb-oriented reading. It appears plausible to assume that more frequently chosen sentence forms are more practiced and thus require less cognitive effort (Goldman-Eisler & Cohen, 1970; Yngve, 1960). In our experiment, however, the more frequently chosen verb-oriented reading of sentences induced greater pupillary dilation, indicating that, despite its higher frequency. this reading required more cognitive effort. This lends further credibility to the conclusion that structural complexity, not the use of more efficient strategies, was responsible for the observed differences in pupillary movements. Using pupillary movements as a measure for cognitive effort we had a quasi “on line” indicator of momentary changes in cognitive effort. Our method of analysis, following suggestions by Chapman et al. (1979). allowed for separation of effects of experimental variables for different time periods. One of the experimental variables was which of two possible readings of a sentence would be chosen, with the verb-oriented reading considered to be syntactically more complex. Various investigations have shown (see Garrett, 1970) that experiments testing for the effect of ambiguity depend a great deal on whether the effects were tested for during or ufter processing. For both the reading and the transformation periods of the trials, our analysis indicated pupillary dilations compatible with our first hypothesis, that pupillary dilations would be greater for verb-oriented readings. Thus, we have further evidence supporting the notion that second-order measures of syntactic complexity are related to psychological complexity (Wang, 1970a; Schluroff, 1982, 1983; Beatty & Schluroff, 1980). Our second hypothesis was that low-bias syntactically ambiguous sentences would be associated with greater pupillary dilations than highbias sentences. Although mean pupillary dilations did show the expected difference, data analysis failed to reach statistical significance. One explanation for this might be that our subjects’ attention was mostly occupied with the task of reading and transforming a sentence in a prescribed time, fixating their eyes to the display, and refraining from blinking. The ambiguity of the sentences had not been pointed out to them and thus may have been noticed in too few instances. This explanation is consistent with earlier observations (Foss, Bever, & Silver, 1968; Carey et al., 1970a, 1970b) that it is the realization of ambiguity which complicates

340

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ET AL.

sentence-related tasks, not ambiguity as such. Task requirements in these investigations were not identical with the ones employed in ours. With ambiguous sentences, different task requirements may result in different levels of comprehension (Mistler-Lachman, 1972) and thus different amounts of cognitive effort. Thus, our results may be interpreted only as not providing clear evidence supporting the multiple-meaning hypothesis. High and low scorers in the grammatical sensitivity test exhibited different pupillary movements. Low scorers appeared to exert more cognitive effort during reading and less cognitive effort during the later phases of the trial, compared to high scorers (cf. Fig. 6). However, this difference reached statistical significance for the baseline period only. For low scorers, reading seems to have been associated with higher cognitive effort. Thus, the slower constriction during the baseline period may have been an anticipatory reaction: expecting a difficult task dilates the pupil or weakens an ongoing constriction (Kahneman & Beatty, 1966; Bradshaw, 1967; Nunnally, Knott, Duchnowski, & Parker, 1967; Bernick & Oberlander, 1968; Peavler, 1974). The differential effect of pupillary movements for high and low scorers suggests that the two groups differed in their cognitive and/or emotional state in the time period immediately preceding the processing of a sentence. Our data do not offer a ready explanation for why this should be so. The large estimated differences for the reading and postreading time periods, respectively (cf. Fig. 6), suggest that-although the differences were not statistically reliablehigh scorers and low scorers may differ in the cognitive effort exerted in the processing of sentences. To resolve this, further research is called for. Finally, our methods of data analysis require comment. We are aware of the controversy over the use and tenability of factorial analysis in regard to data which do not meet certain requirements. We do not claim that the structure of our data meet the requirements necessary to use principal components analysis for testable statements. We regard our analyses rather as explorative and awaiting confirmation by successive investigations. Principal components analysis combined with analysis of variance has been used meaningfully and successfully in evoked potential research (Chapman et al., 1979). One advantage of this combination lies in its potential to obtain interpretable results from averaged physiological responses when the time course of these responses is determined by several interdependent factors. This is the case for both pupillary and evoked potential responses. In addition, the methods used here may be one way of resolving the apparent paradox that pupillary movements might be the most reliable physiological index of cognitive load, yet measures of the pupil have remained comparatively unidimensional, such as mean size, mean dilation, peak size, or latency (Janisse, 1977, pp. 14 ff). With the pupil appearing to be a good “on line” indicator of cognitive load,

SYNTACTIC

341

AMBIGUITY

exploring the time course of pupillary movements may prove particularly fruitful for investigations into language processing, in which on-line indices of momentary load are particularly called for. APPENDIX: Setzen Sie die folgenden Prateritum). MUSTER:

Der Der

[GRAMMATICAL drei Satze

Vorgesetzte Vorgesetzte

ins Prateritum

weckt weckte

SENSITIVITY (einfache

ist, bekommen

Machen Sie aus den folgenden drei Aussagesltzen MUSTER: Der Vorgesetzte weckt Siegfried. Weckt der Vorgesetzte Siegfried?

wir noch

ein Bier,

Fragesatze.

4. Die Fussballmanschaft hat gegen Algerien 5. Niemand muss hier ein Referat halten. 6. Wer andern eine Grube grabt. fallt selbst Setzen Sie die folgenden drei Satze in die Mehrzahl MUSTER: Der Vorgesetzte weckt Siegfried. Die Vorgesetzten wecken Siegfried.

Setzen Sie die folgenden drei MUSTER: Der Vorgesetzte Der Vorgesetzte

Vergangenheitsform:

Siegfried. Siegfried.

1. Der Professor schlaft ein. 2. Obwohl es schon halb zwei 3. Geld stinkt nicht.

7. Der Saugling 8. Ein Lastwagen 9. Dieser Mann

TEST]

verloren. hinein.

(Plural)

schreit. fahrt vorbei. ist ein Betriiger. Satze ins Perfekt weckt Siegfried. hat Siegfried geweckt.

10. Picasso malt viele Bilder. I I. Der Kanzler kann Klavier 12. Nicht jeder kann Chines&h.

spielen

Setzen Sie die folgenden Satze ins Passiv (Leideform). MUSTER: Der Vorgesetzte weckt Siegfried. Siegfried wird vom Vorgesetzten geweckt 13. Das Volk hat den Prasidenten 14. Der Lehrer gibt der Schtilerin 15. Jemand wird den Einbrecher

begrtisst. das Buch. sehen.

List of sentences

used

1. Der Bankrguber erschoss den Kunden mit dem Nummernkonto. 2. Ignaz verfolgte den Mann mit dem Motorrad.

SCHLUROFF

342

3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

ET AL

Ein Passagier beltistigte eine Nachbarin mit Mundgeruch. Der Junge fing den Ball mit der linken Hand. Hans beleuchtete das Zimmer mit den beiden Stehlampen. Der Bauer verjagte den Hahn mit den gebrochenen Fliigeln. Die Gymnasiasten tirgerten den Lehrer mit der ewigen Fragerei. Der Verktiufer %rgerte den Kunden mit dem vielen Kleingeld. Der Partygast bedrtingte die Frau mit dem Mundgeruch. Der Ehemann erwiirgte den Liebhaber mit der Telefonschnur. Das Mtidchen fing den Ball mit den roten Punkten. Der Theatergast beobachtete die Dame mit dem Opernglas. Monika entfernte den Fleck mit dem neuen Mittel. Der Lehrling bemalte den Eimer mit der roten Farbe. Ein Geisteskranker erwiirgte den Dressman mit dem modischen Halstuch. Der Einbrecher erwiirgte den Mann mit der Narbe. Der T%ter erwiirgte die Frau mit dem teuren Schal. Der Spaziergtinger beobachtete den FZjrster mit dem Feldstecher. Ede beobachtete den Norweger mit der gestreiften Krawatte. Heinrich zerlegte die Ente mit der Gefliigelschere. REFERENCES

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Chapman, R. M., McCrary, J. W., Bragdon, H. R., & Chapman, J. A. 1979. Latent components of event-related potentials functionally related to information processing. In J. E. Desmedt (Ed.), Cognitive components in cerebral event-related potentials and selective attention. Progress in Clinicul Neurophysiology, 6, 80-105. Clifton, C., Kurcz, I., & Jenkins, J. J. 1965. Grammatical relations as determinants of sentence similarity. Journal of Verbal Learning and Verbal Behavior, 4, 112-l 17. Clifton, C.. & Odom, P. 1966. Similarity relations among certain English sentence constructions. Psychological Monographs, 80, (Whole No. 614). Dixon, W. J. (Ed.). 1979. BMDP biomedicul computer programs. Los Angeles: Univ. of California Press. Forster, K. 1. 1966. Left-to-right processes in the construction of sentences. Jorrrnul of Verbal Learning and Verbal Behavior, 5, 285-291. Forster, K. I. 1967. Sentence completion latencies as a function of constituent structure. Journal qf Verbal Learning and Verbal Behcrr,ior. 6, X78-883. Forster, K. I.. 1968a. The effect of removal of length constraints on sentence completion times. Jownal of Verbal Learning and Verbal Behavior, 7, 253-258. Forster, K. I., 1968b. Sentence completion in left- and right-branching languages. Jorrrnal of Verbul Learning and Verbul Behtrvior, I, 196-299. Foss. D. J.. Bever. T. G., & Silver, M. 1968. The comprehension and verification of ambiguous sentences. Percepption & Psychophy.sic~.s. 4, 304-306. Garrett. M. F. 1970. Does ambiguity complicate the perception of sentences’? In G. B. Flares d’Arcais & W. J. M. Levelt (Eds.). Adwnces in p.\?c.llolinqrri.\ric.\. Amsterdam: North-Holland. Pp. 48-60. Glucksberg, S. & Danks. J. 1969. Grammatical structure and recall: A function of the space in immediate memory or of recall delay? Perception & Ps~c./2oph~.sic,,s, 6, 113117. Goldman-Eisler. F., & Cohen. M. 1970. Is N. P. and PN difficulty a valid criterion of transformational operations? Journctl of Verbal Lecrrning and Verbal Behtr\~ior. 9, l61166. Goldwater. B. C.. 1972. Psychological significance of pupillary movements. P.v~c~l~o/o,~ic~n/ Bulletin, 71, 340-355. Gough, P. B. 1965. Grammatical transformations and speed of understanding. Journrrl of Verbal Learning trnd Verbtrl Behcl\ior. 4, 107-l I I. Hakerem, G. 1974. Conceptual stimuli, pupillary dilation. and evoked cortical potentials: A review of recent advances. In M. P. Janisse (Ed.). P(rpi//tq d\tlrrmics trt7tl bchtr~~ior. New York: Plenum. Pp. 135-158. Harnischfeger, A., & Wiley, D. 1977. Kernkonrepte des Schullernens. Zeir.cc~hr(fi ,fiwr Eni~~~ic~klrrng.sp.s~t~~fo/ogie, 9, 207-228. Herriot, P.. 196X. The comprehension of sentences as a function of grammatical depth and order. Journtrl of Verbul Learning rend Verbrrl Brhccvior. 7, 93X-941 Janisse, M. P. 1977. Plrpillomerry: The p.sycho/og:? c$tltr prrpillory rcsponsr. Washington. DC: Hemisphere. Kahneman, D., & Beatty. J.. 1966. Pupil diameter and load on memory. Sciewe f Washington. D.C.J. 154, 1583-1585. Kaiser. H. F. 1958. The varimax criterion for rotation in factor analysis. P.s~c,ho,,lr,t~ikrr. 23, 1X7-200. Kess, J. F., & Hoppe, R. A. 1978. On psycholinguistic experiments in ambiguity. Litlg/ctr. 45, 125-140. Koplin. J. H., & Davis, J. 1966. Grammatical transformations and recognition memory of sentences. Psychonornic Science, 6, 257-258. Kratzer, A.. Pause, E.. & v.Stechow, A.. 1973. Einfrrehrung in Therwic und Anwendrrng der generuti\vn Synfcr.u: Vol. I. Syntoxtheorir. Frankfurt: Fischer.

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of Experimental

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Wright, P. 1969. Two studies of the depth hypothesis. British Journal of Psychology, 60, 63-69. Wright, P., & Kahneman, D., 1971. Evidence for alternative strategies for sentence retention. Quarterly

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Yngve, V. H., 1960. A model and hypothesis for language structure. Proceedings American

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of the