Are scalar implicatures automatically processed and different for each individual? A mismatch negativity (MMN) study
Authors: Gang Chen
Feiyan Chen
Tao Liu
Ming Zhao
Journal: Brain Research (2015)
Discipline: NEUROSCIENCE & BEHAVIOR
Keywords: Automatic processing; Individual differences; MMN (mismatch negativity); Pragmatic abilities; SN (sustained negativity)
Affiliations: School of Literature, Law & Politics, China University of Mining and Technology, China; Bio-X Laboratory, Department of Physics, Zhejiang University, China. Electronic address: ., Jiangsu Key Laboratory of Language and Cognitive Neuroscience, Jiangsu Normal University, China., School of Foreign Studies, Anhui University, China., Bio-X Laboratory, Department of Physics, Zhejiang University, China. Electronic address: .

Abstract:  Scalar implicatures are ordinarily activated in human communication when the speaker uses a weak expression (e.g., some) from a set of stronger alternatives (e.g., many, all). It has been debated whether scalar inferences are generated by default. To clarify this issue and examine whether individual pragmatic ability will affect the mechanism of scalar inference processing, we performed experiment with an MMN paradigm to capture the neurophysiological indicators of automatic processing of spoken sentences and divided participants into high and low pragmatic ability groups. Experimental results showed that compared with the condition that an informative sentence ("Some animals have tails") is the deviant stimuli, when an underinformative sentence ("Some tigers have tails") is the deviant stimuli, the high pragmatic ability group induced mismatch negativity (MMN) and sustained negativity, while the low pragmatic ability group had no ERP effects. These results indicated that at least some people can automatically activate the scalar implicatures when encountering scalar trigger words, even in the inattentive status. 

Retracted: No

PubPeer comments:
 This study claims to demonstrate, based on the mismatch negativity brain response, that people vary in how they process scalar implicatures but at least some people process them automatically. The paper actually does not provide evidence for this claim, because of a design problem and an error in the interpretation of the results. Some brief background: a lot of attention in experimental pragmatics has been devoted to *scalar inferences*, i.e., the interpretation of a sentence like  Some cats are mammals as meaning  some *but not all* cats are mammals , as opposed to its literal, existential meaning, roughly  there is at least one cat that s a mammal, and I m not making any commitment to whether or not every cat is mammal . Historically, a major debate regarding these inferences has been whether comprehenders derive them automatically and effortlessly, or whether the derivation of scalar implicatures is cognitively effortful and thus is only done when licensed by the context. (Nowadays we know that both of these stories are straw men. Judith Degen s work has done a lot to point out how both these positions are inadequate, and I think her proposal of a more gradient, constraint-based mechanism is more consistent with most of the experimental results so far; [Chemla Singh, 2014] , also give a good explanation of how scalar implicature processing likely involves both kinds of mechanisms. But the putative default vs. context-based debate is still sometimes used as a handy shorthand for contextualizing the issue.) Seminal research into this topic presented readers with  *some* sentences, which could be interpreted either pragmatically (as meaning  *some* but *not all* ) or semantically (as meaning  *some* and no-commitment-to-whether-or-not-*all*-is-true ), and pretty much explicitly asked participants which interpretation they had made (by asking whether they think the sentence is true;  *some cats are mammals* is true when interpreted semantically as  at least one cat is a mammal but false when interpreted pragmatically as  some, but not all, cats are mammals ). In the present paper, Zhao and colleagues point out an important concern about this method: those kinds of explicit judgments conflate the process of deriving an implicature in the first place with the process of evaluating the respective interpretations relative to context, world knowledge, etc. This criticism that they raise is valid; I too have harped on this point in much of my own research, so I definitely share their concern. The central motivation of their study, then, is to test the automaticity of scalar inference realization while avoiding these kind of explicit judgment tasks. The authors propose to do this by using the mismatch negativity (MMN), a component of brain activity related to noticing the change between a frequently-presented stimulus and an infrequently-presented stimulus. This is a shrewd way to get at the issue, since the MMN is generally known to reflect automatic processes, and such an experiment can be done without requiring participants to make explicit judgments. Zhao and colleagues designed an experiment in which participants heard two sentences: [the Mandarin equivalents of]  some tigers have _tails_ or  some animals have _tails_ . (The italicized word is the one that the study will examine the brain response to.) The first sentence is **underinformative** because presumably all tigers have tails, and thus if you realize a scalar inference and interpret some as meaning  not all then the sentence sounds wrong, even though it s actually true if you interpret *some* logically semantically; the second sentence is **informative** because it is indeed the case that some but not all animals have tails. In this experiment, participants would hear one block in which the informative sentence is presented a whole bunch of times, interspersed with only a few presentations of the underinformative sentence; they would hear another block in which the underinformative sentence is presented a lot and the informative one rarely. For each block, subtracting the average neural response elicited by the common stimulus from the average neural response elicited from the rare stimulus leaves you with an MMN. Based on some known properties of the MMN the authors predicted that, if scalar inferences are realized automatically, then there would be a bigger MMN in blocks where the common stimulus is the informative sentence (i.e., where the rare stimulus is the underinformative sentence) compared to vice versa. So far so good. Because of the study design, however, I don t believe the authors actually observed MMN effects. The neural responses were measured relative to the onset of the underlined words above (i.e., the objects). This was done for good reason: the MMN is so sensitive to low-level differences, it is important to measure it time-locked to the same stimulus across all your manipulations, otherwise there will likely be differences due to phonetic or perceptual differences between the words. However, since these two sentences were literally the only stimuli used in the study, participants could know with 100% certainty that the sentence was going to be about having tails. Therefore, the earliest instance in which the participant can recognize whether the sentence is informative or underinformative (and, therefore, the spot at which the change-detection mechanism would be expected to generate an MMN) is actually at the subject of the sentence,  tigers or  animals . It is hard to know what was going on at the object, but it is unlikely to have been an MMN effect. (The authors did perform some additional analyses demonstrating that the effect on the object does not seem to be just a continuation of earlier effects. This does not, however, fully address my concern. First of all, while they examined neural responses to the word preceding the object, they did not examine responses to the subject, which is the most important test here. Secondly, while they showed that the effect elicited at the object was larger than the effects present in the 500 ms preceding the object, this does not necessarily mean that no effects were present before the object; baseline-correction hides such effects, and indeed in [Politzer-Ahles et al. 2013](http: www.sciencedirect.com science article pii S000689931201699X) (experiment 2) we found a perhaps similar effect, in which underinformativeness-related effects were first elicited at the subject but persisted and grew over the course of the sentence. It s not clear to me whether these effects really were sustained for the whole sentence and slowly growing [in which case if we detrended, by subtracting the linear trend present in the baseline, rather than just subtracting the mean of the baseline, then the late effect may disappearu00e2u20acu201dwe never tried this], or whether the effects went away and then reappeared at some key points in the sentence, such as the object, where participants  crap, it looks like this sentence is going to be underinformative prediction finally gets confirmed.) The data also do not look like MMNs. In fact, looking at the high-pragmatic-ability participants in Figures 1 and 2 (the low-pragmatic-ability ones did not show robust effects either way), one could easily summarize the data patterns without making reference to anything having to do with MMNs; rather, it simply looks like underinformative objects always elicited more positive neural responses than informative objects, regardless of which was the frequent and which the infrequent stimuli. Overall, these two issues suggest that the observed effects are MMNs at all, and if the observed effects are not MMNs then the initial predictions become irrelevant, and it s hard to say then what these effects mean for pragmatics. I have a small quibble as well, which has also been raised about some of the stimuli in the groundbreaking study [Noveck Posada (2003)](http: www.sciencedirect.com science article pii S0093934X03000531), is that  some tigers have tails is not necessarily underinformative (similar to some of Noveck Posada s sentences, e.g.,  some televisions have screens or  some cherries have pits ). Any marginally creative hearer can think of exceptions (a tiger whose tail has been chopped off, an old television in a junk pile with its screen smashed in, a jar of pitted cherries) by searching long-term memory for such counterexamples or by imagining possible worlds; once they ve thought of an exception like this, the  not all interpretation of the sentence is perfectly reasonable. Of course, counterexamples may be easier or harder to find for any given sentence (for example, pitted cherries are less of a logical leap for me than tailless tigers), but these types of sentence are certainly of a different class than taxonomical underinformative sentences like  some sentences have words or  some cats are mammals , which cannot be counterexampled without flouting the meanings of the categories involved. All this makes me curious about the other key result in Zhao and colleagues paper, the observation that brain responses to putatively underinformative sentences differed as a function of scores on the Autism Spectrum Quotient. The authors argue that this is evidence for a role of pragmatic ability in comprehending scalar implicatures; but could it instead be that something like imagination ability plays a role in how good people are at thinking of counterexamples? (They only used the Communication subscale and the Social Skills subscale, not the Imagination subscale. However, without having shown the scores for the other subscales, we can t be sure if those weren t also correlated with Imagination in this sample; it s likely that the five subscales of the ASQ aren t really representing orthogonal constructs. Plus, in general, given the ease of p-hacking garden-of-forking-paths-ing, I think analyses of ASQ subscales are not very trustworthy unless the choice of subscale was pre-registered or the authors use and report all subscales and appropriately address the multiple comparisons problem.) If it is indeed the case that the observed differences have something to do with how good participants are at imagning counterxamples, the results might have nothing to do with deriving scalar inferences at all (e.g., it s possible that every single participant always realized the scalar inference, but participants differed in how good they were at thinking of counterexamples to accommodate the potentially weird  not all interpretation--if one participant has a certain reaction to  some tigers have tails and another participant does not, that might not mean that one participant interpreted *some* as *all* and another did not, it might instead mean that they both interpreted *some* as *all* but one person was able to imagine tailless tigers and the other participant was not able to). This kind of brings us full circle, because the main goal of the study was to isolate inference derivation mechanisms from evaluation mechanisms, but here we have a result that might still be more about how participants dealt with the ultimate interpretation than how they got there in the first place. Overall, then, I don t think the findings of this study have to say about the processing of scalar implicatures. The use of an oddball design to study scalar implicatures is a great idea, for the reasons I mentioned above, and it is possible to design an experiment that does this well ([Cu00e9cile Barbet] , for example, done some fascinating work in this direction), but the present study is not it. In the several years since it has been published this paper has sometimes been cited as evidence about how scalar implicatures are realized and how this process varies across individuals, which is disappointing because the paper actually provides no such evidence. ,