Cultural evolution creates the statistical structure of language

Human language is unique in its structure: language is made up of parts that can be recombined in a productive way. The parts are not given but have to be discovered by learners exposed to unsegmented wholes. Across languages, the frequency distribution of those parts follows a power law. Both statistical properties-having parts and having them follow a particular distribution-facilitate learning, yet their origin is still poorly understood. Where do the parts come from and why do they follow a particular frequency distribution? Here, we show how these two core properties emerge from the process of cultural evolution with whole-to-part learning. We use an experimental analog of cultural transmission in which participants copy sets of non-linguistic sequences produced by a previous participant: This design allows us to ask if parts will emerge purely under pressure for the system to be learnable, even without meanings to convey. We show that parts emerge from initially unsegmented sequences, that their distribution becomes closer to a power law over generations, and, importantly, that these properties make the sets of sequences more learnable. We argue that these two core statistical properties of language emerge culturally both as a cause and effect of greater learnability.

Zipfian Distributions in Child-Directed Speech

Across languages, word frequency and rank follow a power law relation, forming a distribution known as the Zipfian distribution. There is growing experimental evidence that this well-studied phenomenon may be beneficial for language learning. However, most investigations of word distributions in natural language have focused on adult-to-adult speech: Zipf's law has not been thoroughly evaluated in child-directed speech (CDS) across languages. If Zipfian distributions facilitate learning, they should also be found in CDS. At the same time, several unique properties of CDS may result in a less skewed distribution. Here, we examine the frequency distribution of words in CDS in three studies. We first show that CDS is Zipfian across 15 languages from seven language families. We then show that CDS is Zipfian from early on (six-months) and across development for five languages with sufficient longitudinal data. Finally, we show that the distribution holds across different parts of speech: Nouns, verbs, adjectives and prepositions follow a Zipfian distribution. Together, the results show that the input children hear is skewed in a particular way from early on, providing necessary (but not sufficient) support for the postulated learning advantage of such skew. They highlight the need to study skewed learning environments experimentally.

The Impact of Information Structure on the Emergence of Differential Object Marking: An Experimental Study

Many languages exhibit differential object marking (DOM), where only certain types of grammatical objects are marked with morphological cases. Traditionally, it has been claimed that DOM arises as a way to prevent ambiguity by marking objects that might otherwise be mistaken for subjects (e.g., animate objects). While some recent experimental work supports this account, research on language typology suggests at least one alternative hypothesis. In particular, DOM may instead arise as a way of marking objects that are atypical from the point of view of information structure. According to this account, rather than being marked to avoid ambiguity, objects are marked when they are given (already familiar in the discourse) rather than new. Here, we experimentally investigate this hypothesis using two artificial language learning experiments. We find that information structure impacts participants’ object marking, but in an indirect way: atypical information structure leads to a change in word order, which then triggers increased object marking. Interestingly, this staged process of change is compatible with documented cases of DOM emergence. We argue that this process is driven by two cognitive tendencies. First, a tendency to place discourse given information before new information, and second, a tendency to mark noncanonical word order. Taken together, our findings provide corroborating evidence for the role of information structure in the emergence of DOM systems.

Do Children Use Multi-Word Information in Real-Time Sentence Comprehension?

Meaning in language emerges from multiple words, and children are sensitive to multi-word frequency from infancy. While children successfully use cues from single words to generate linguistic predictions, it is less clear whether and how they use multi-word sequences to guide real-time language processing and whether they form predictions on the basis of multi-word information or pairwise associations. We address these questions in two visual-world eye-tracking experiments with 5- to 8-year-old children. In Experiment 1, we asked whether children generate more robust predictions for the sentence-final object of highly frequent sequences (e.g., "Throw the ball"), compared to less frequent sequences (e.g., "Throw the book"). We further examined if gaze patterns reflect event knowledge or phrasal frequency by comparing the processing of phrases that have the same event structure but differ in multi-word content (e.g., "Brush your teeth" vs. "Brush her teeth"). In the second study, we employed a training paradigm to ask if children are capable of generating predictio.ns from novel multi-word associations while controlling for the overall frequency of the sequences. While the results of Experiment 1 suggested that children primarily relied on event associations to generate real-time predictions, those of Experiment 2 showed that the same children were able to use recurring novel multi-word sequences to generate real-time linguistic predictions. Together, these findings suggest that children can draw on multi-word information to generate linguistic predictions, in a context-dependent fashion, and highlight the need to account for the influence of multi-word sequences in models of language processing.

The learnability consequences of Zipfian distributions in language

While the languages of the world differ in many respects, they share certain commonalties, which can provide insight on our shared cognition. Here, we explore the learnability consequences of one of the striking commonalities between languages. Across languages, word frequencies follow a Zipfian distribution, showing a power law relation between a word's frequency and its rank. While their source in language has been studied extensively, less work has explored the learnability consequences of such distributions for language learners. We propose that the greater predictability of words in this distribution (relative to less skewed distributions) can facilitate word segmentation, a crucial aspect of early language acquisition. To explore this, we quantify word predictability using unigram entropy, assess it across languages using naturalistic corpora of child-directed speech and then ask whether similar unigram predictability facilitates word segmentation in the lab. We find similar unigram entropy in child-directed speech across 15 languages. We then use an auditory word segmentation task to show that the unigram predictability levels found in natural language are uniquely facilitative for word segmentation for both children and adults. These findings illustrate the facilitative impact of skewed input distributions on learning and raise questions about the possible role of cognitive pressures in the prevalence of Zipfian distributions in language.

Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K'iche'

How do language learners avoid the production of verb argument structure overgeneralization errors ( *The clown laughed the man c.f. The clown made the man laugh), while retaining the ability to apply such generalizations productively when appropriate? This question has long been seen as one that is both particularly central to acquisition research and particularly challenging. Focussing on causative overgeneralization errors of this type, a previous study reported a computational model that learns, on the basis of corpus data and human-derived verb-semantic-feature ratings, to predict adults' by-verb preferences for less- versus more-transparent causative forms (e.g., * The clown laughed the man vs The clown made the man laugh) across English, Hebrew, Hindi, Japanese and K'iche Mayan. Here, we tested the ability of this model (and an expanded version with multiple hidden layers) to explain binary grammaticality judgment data from children aged 4;0-5;0, and elicited-production data from children aged 4;0-5;0 and 5;6-6;6 ( N=48 per language). In general, the model successfully simulated both children's judgment and production data, with correlations of r=0.5-0.6 and r=0.75-0.85, respectively, and also generalized to unseen verbs. Importantly, learners of all five languages showed some evidence of making the types of overgeneralization errors - in both judgments and production - previously observed in naturalistic studies of English (e.g., *I'm dancing it). Together with previous findings, the present study demonstrates that a simple learning model can explain (a) adults' continuous judgment data, (b) children's binary judgment data and (c) children's production data (with no training of these datasets), and therefore constitutes a plausible mechanistic account of the acquisition of verbs' argument structure restrictions.

The Starting Big approach to language learning

The study of language acquisition has a long and contentious history: researchers disagree on what drives this process, the relevant data, and the interesting questions. Here, I outline the Starting Big approach to language learning, which emphasizes the role of multiword units in language, and of coarse-to-fine processes in learning. I outline core predictions and supporting evidence. In short, the approach argues that multiword units are integral building blocks in language; that such units can facilitate mastery of semantically opaque relations between words; and that adults rely on them less than children, which can explain (some of) their difficulty in learning a second language. The Starting Big approach is a theory of how children learn language, how language is represented, and how to explain differences between first and second language learning. I discuss the learning and processing models at the heart of the approach and their cross-linguistic implications.

Individual Differences in Learning Abilities Impact Structure Addition: Better Learners Create More Structured Languages

Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non-structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of change. Here, we identify and test two contrasting predictions: The first sees learning as a pre-requisite for structure addition, and predicts a positive correlation between learning accuracy and structure addition, whereas the second maintains that it is those learners who struggle with learning and reproducing their input who add structure to it. This prediction is hard to test in standard iterated learning paradigms since each learner is exposed to a different input, and since structure and accuracy are computed using the same test items. Here, we test these contrasting predictions in two experiments using a one-generation artificial language learning paradigm designed to provide independent measures of learning accuracy and structure addition. Adults (N = 48 in each study) were exposed to a semi-regular language (with probabilistic structure) and had to learn it: Learning was assessed using seen items, whereas structure addition was calculated over unseen items. In both studies, we find a strong positive correlation between individuals' ability to learn the language and their tendency to add structure to it: Better learners also produced more structured languages. These findings suggest a strong link between learning and generalization. We discuss the implications of these findings for iterated language models and theories of language change more generally.

Starting Big: The Effect of Unit Size on Language Learning in Children and Adults

Multiword units play an important role in language learning and use. It was proposed that learning from such units can facilitate mastery of certain grammatical relations, and that children and adults differ in their use of multiword units during learning, contributing to their varying language-learning trajectories. Accordingly, adults learn gender agreement better when encouraged to learn from multiword units. Previous work has not examined two core predictions of this proposal: (1) that children also benefit from initial exposure to multiword units, and (2) that their learning patterns reflect a greater reliance on multiword units compared to adults. We test both predictions using an artificial-language. As predicted, both children and adults benefit from early exposure to multiword units. In addition, when exposed to unsegmented input - adults show better learning of nouns compared to article-noun pairings, but children do not, a pattern consistent with adults' predicted tendency to focus less on multiword units.

'Clap your hands' or 'take your hands'? One-year-olds distinguish between frequent and infrequent multiword phrases

Although words are often described as the basic building blocks of language, there is growing evidence that multiword sequences also play an integral role in language learning and processing. It is not known, however, whether children become sensitive to multiword information at an age when they are still building knowledge of individual words. Using a central fixation paradigm, the present study examined whether infants between 11 and 12 months (N = 36) distinguish between three-word sequences (trigrams) with similar substring frequencies but different multiword frequency in infant-directed speech (e.g., high frequency: 'clap your hands' vs. low frequency: 'take your hands'). Infants looked significantly longer at frequent trigrams compared to infrequent ones. This provides the first evidence that infants at the cusp of one-word production are already sensitive to the frequency of multiword sequences, and suggests they represent linguistic units of varying sizes from early on, raising the need to evaluate knowledge of both words and larger sequences during development.

Visual statistical learning is facilitated in Zipfian distributions

Humans can extract co-occurrence regularities from their environment, and use them for learning. This statistical learning ability (SL) has been studied extensively as a way to explain how we learn the structure of our environment. These investigations have illustrated the impact of various distributional properties on learning. However, almost all SL studies present the regularities to be learned in uniform frequency distributions where each unit (e.g., image triplet) appears the same number of times: While the regularities themselves are informative, the appearance of the units cannot be predicted. In contrast, real-world learning environments, including the words children hear and the objects they see, are not uniform. Recent research shows that word segmentation is facilitated in a skewed (Zipfian) distribution. Here, we examine the domain-generality of the effect and ask if visual SL is also facilitated in a Zipfian distribution. We use an existing database to show that object combinations have a skewed distribution in children's environment. We then show that children and adults showed better learning in a Zipfian distribution compared to a uniform one, overall, and for low-frequency triplets. These results illustrate the facilitative impact of skewed distributions on learning across modality and age; suggest that the use of uniform distributions may underestimate performance; and point to the possible learnability advantage of such distributions in the real-world.

The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'

This preregistered study tested three theoretical proposals for how children form productive yet restricted linguistic generalizations, avoiding errors such as *The clown laughed the man, across three age groups (5-6 years, 9-10 years, adults) and five languages (English, Japanese, Hindi, Hebrew and K'iche'). Participants rated, on a five-point scale, correct and ungrammatical sentences describing events of causation (e.g., *Someone laughed the man; Someone made the man laugh; Someone broke the truck; ?Someone made the truck break). The verb-semantics hypothesis predicts that, for all languages, by-verb differences in acceptability ratings will be predicted by the extent to which the causing and caused event (e.g., amusing and laughing) merge conceptually into a single event (as rated by separate groups of adult participants). The entrenchment and preemption hypotheses predict, for all languages, that by-verb differences in acceptability ratings will be predicted by, respectively, the verb's relative overall frequency, and frequency in nearly-synonymous constructions (e.g., X made Y laugh for *Someone laughed the man). Analysis using mixed effects models revealed that entrenchment/preemption effects (which could not be distinguished due to collinearity) were observed for all age groups and all languages except K'iche', which suffered from a thin corpus and showed only preemption sporadically. All languages showed effects of event-merge semantics, except K'iche' which showed only effects of supplementary semantic predictors. We end by presenting a computational model which successfully simulates this pattern of results in a single discriminative-learning mechanism, achieving by-verb correlations of around r = 0.75 with human judgment data.

A learning bias for word order harmony: Evidence from speakers of non-harmonic languages

Word order harmony describes the tendency, found across the world's languages, to consistently order syntactic heads relative to dependents. It is one of the most well-known and well-studied typological universals. Almost since it was first noted by Greenberg (1963), there has been disagreement about what role, if any, the cognitive system plays in driving harmony. Recently, a series of studies using artificial language learning experiments reported that harmonic noun phrase word orders were preferred over non-harmonic orders by English-speaking adults and children (Culbertson et al., 2012; Culbertson & Newport, 2015, 2017). However, this evidence is potentially confounded by the fact that English is itself a harmonic language (Goldberg, 2013). Here we sought to extend the results from these studies by exploring whether learners who have substantial experience with a non-harmonic language still showed a bias for harmonic patterns during learning. We found that monolingual French- and Hebrew-speaking children, whose language has a non-harmonic noun phrase order (N Adj, Num N) nevertheless preferred harmonic patterns when learning an artificial language. We also found evidence for a harmony bias across several populations of adult learners, although this interacted in complex ways with their L2 experience. Our results suggest that transfer from the L1 cannot explain the preference for harmony found in previous studies. Moreover, they provide the strongest evidence yet that a cognitive bias for harmony is a plausible candidate for shaping linguistic typology.

Statistical Learning, Implicit Learning, and First Language Acquisition: A Critical Evaluation of Two Developmental Predictions

The role of distributional information in language learning, and learning more generally, has been studied extensively in both the statistical learning and the implicit learning literatures. Despite the similarity in research questions, the two literatures have remained largely separate. Here, we draw on findings from the two traditions to critically evaluate two developmental predictions that are central to both. The first is the question of age invariance: Does learning improve during development or is it fully developed in infancy? The combined findings suggest that both implicit and statistical learning improve during childhood, contra the age invariance prediction. This raises questions about the role of implicit statistical learning (ISL) in explaining the age-related deterioration in language learning: Children's better language learning abilities cannot be attributed to their improved distributional learning skills. The second issue we examine is the predictive relation to language outcomes: Does variation in learning predict variation in language outcomes? While there is evidence for such links, there is concern in both research traditions about the reliability of the tasks used with children. We present data suggesting that commonly used statistical learning measures may not capture stable individual differences in children, undermining their utility for assessing the link to language outcomes in developmental samples. The evaluation of both predictions highlights the empirical parallels between the implicit and statistical learning literatures, and the need to better integrate their developmental investigation. We go on to discuss several of the open challenges facing the study of ISL during development.

SES effects on the use of variation sets in child-directed speech

Socio-economic status (SES) impacts the amount and type of input children hear in ways that have developmental consequences. Here, we examine the effect of SES on the use of variation sets (successive utterances with partial self-repetitions) in child-directed speech (CDS). Variation sets have been found to facilitate language learning, but have been studied only in higher-SES groups. Here, we examine their use in naturalistic speech in two languages (Hebrew and English) for both low- and high-SES caregivers. We find that variation sets are more frequent in the input of high-SES caregivers in both languages, indicating that SES also impacts structural properties of CDS.

Minding the gaps: literacy enhances lexical segmentation in children learning to read

Can emergent literacy impact the size of the linguistic units children attend to? We examined children's ability to segment multiword sequences before and after they learned to read, in order to disentangle the effect of literacy and age on segmentation. We found that early readers were better at segmenting multiword units (after controlling for age, cognitive, and linguistic variables), and that improvement in literacy skills between the two sessions predicted improvement in segmentation abilities. Together, these findings suggest that literacy acquisition, rather than age, enhanced segmentation. We discuss implications for models of language learning.

The Role of Multiword Building Blocks in Explaining L1-L2 Differences

Why are children better language learners than adults despite being worse at a range of other cognitive tasks? Here, we explore the role of multiword sequences in explaining L1-L2 differences in learning. In particular, we propose that children and adults differ in their reliance on such multiword units (MWUs) in learning, and that this difference affects learning strategies and outcomes, and leads to difficulty in learning certain grammatical relations. In the first part, we review recent findings that suggest that MWUs play a facilitative role in learning. We then discuss the implications of these findings for L1-L2 differences: We hypothesize that adults are both less likely to extract MWUs and less capable of benefiting from them in the process of learning. In the next section, we draw on psycholinguistic, developmental, and computational findings to support these predictions. We end with a discussion of the relation between this proposal and other accounts of L1-L2 difficulty.

More Than Words: The Role of Multiword Sequences in Language Learning and Use

The ability to convey our thoughts using an infinite number of linguistic expressions is one of the hallmarks of human language. Understanding the nature of the psychological mechanisms and representations that give rise to this unique productivity is a fundamental goal for the cognitive sciences. A long-standing hypothesis is that single words and rules form the basic building blocks of linguistic productivity, with multiword sequences being treated as units only in peripheral cases such as idioms. The new millennium, however, has seen a shift toward construing multiword linguistic units not as linguistic rarities, but as important building blocks for language acquisition and processing. This shift-which originated within theoretical approaches that emphasize language learning and use-has far-reaching implications for theories of language representation, processing, and acquisition. Incorporating multiword units as integral building blocks blurs the distinction between grammar and lexicon; calls for models of production and comprehension that can accommodate and give rise to the effect of multiword information on processing; and highlights the importance of such units to learning. In this special topic, we bring together cutting-edge work on multiword sequences in theoretical linguistics, first-language acquisition, psycholinguistics, computational modeling, and second-language learning to present a comprehensive overview of the prominence and importance of such units in language, their possible role in explaining differences between first- and second-language learning, and the challenges the combined findings pose for theories of language.

More than words: the effect of multi-word frequency and constituency on phonetic duration

There is mounting evidence that language users are sensitive to the distributional properties of multi-word sequences. Such findings expand the range of information speakers are sensitive to and call for processing models that can represent larger chains of relations. In the current paper we investigate the effect of multi-word statistics on phonetic duration using a combination of experimental and corpus-based research. We ask (a) if phonetic duration is affected by multi-word frequency in both elicited and spontaneous speech, and (b) if syntactic constituency modulates the effect. We show that phonetic durations are reduced in higher frequency sequences, regardless of constituency: duration is shorter for more frequent sequences within and across syntactic boundaries. The effects are not reducible to the frequency of the individual words or substrings. These findings open up a novel set of questions about the interaction between surface distributions and higher order properties, and the resulting need (or lack thereof) to incorporate higher order properties into processing models.

Granularity and the acquisition of grammatical gender: how order-of-acquisition affects what gets learned

Why do adult language learners typically fail to acquire second languages with native proficiency? Does prior linguistic experience influence the size of the "units" adults attend to in learning, and if so, how does this influence what gets learned? Here, we examine these questions in relation to grammatical gender, which adult learners almost invariably struggle to master. We present a model of learning that predicts that exposure to smaller units (such as nouns) before exposure to larger linguistic units (such as sentences) can critically impair learning about predictive relations between units: such as that between a noun and its article. This prediction is then confirmed by a study of adult participants learning grammatical gender in an artificial language. Adults learned both nouns and their articles better when they were first heard nouns used in context with their articles prior to hearing the nouns individually, compared with learners who first heard the nouns in isolation, prior to hearing them used in context. In the light of these results, we discuss the role gender appears to play in language, the importance of meaning in artificial grammar learning, and the implications of this work for the structure of L2-training.

The source ambiguity problem: Distinguishing the effects of grammar and processing on acceptability judgments

Judgments of linguistic unacceptability may theoretically arise from either grammatical deviance or significant processing difficulty. Acceptability data are thus naturally ambiguous in theories that explicitly distinguish formal and functional constraints. Here, we consider this source ambiguity problem in the context of Superiority effects: the dispreference for ordering a wh-phrase in front of a syntactically "superior" wh-phrase in multiple wh-questions, e.g. What did who buy? More specifically, we consider the acceptability contrast between such examples and so-called D-linked examples, e.g. Which toys did which parents buy? Evidence from acceptability and self-paced reading experiments demonstrates that (i) judgments and processing times for Superiority violations vary in parallel, as determined by the kind of wh-phrases they contain, (ii) judgments increase with exposure while processing times decrease, (iii) reading times are highly predictive of acceptability judgments for the same items, and (iv) the effects of the complexity of the wh-phrases combine in both acceptability judgments and reading times. This evidence supports the conclusion that D-linking effects are likely reducible to independently motivated cognitive mechanisms whose effects emerge in a wide range of sentence contexts. This in turn suggests that Superiority effects, in general, may owe their character to differential processing difficulty.

Rethinking child difficulty: the effect of NP type on children's processing of relative clauses in Hebrew

Children find object relative clauses difficult. They show poor comprehension that lags behind production into their fifth year. This finding has shaped models of relative clause acquisition, with appeals to processing heuristics or syntactic preferences to explain why object relatives are more difficult than subject relatives. Two studies here suggest that children (age 4 ; 6) do not find all object relatives difficult: a corpus study shows that children most often hear and produce object relatives with pronominal subjects. But they are most often tested on ones with lexical-NP subjects (e.g. The nurse that the girl is drawing). When tested on object relatives with pronominal subjects (e.g. The nurse that I am drawing), similar to those they actually hear and produce, Hebrew speakers aged 4 ; 6 show good comprehension (85% accuracy) that matches their production ability. This suggests a different path of relative clause acquisition, one that is sensitive to fine-grained distributional information.

Long term course of chronic posttraumatic stress disorder in traffic accident victims: a three-year prospective follow-up study

The purpose of the present study was to gather prospective longitudinal data on the long-term course and outcome of chronic posttraumatic stress disorder (PTSD). The target population for this study was 74 injured traffic accident victims who had been previously followed-up for one year after the trauma. Nineteen of the original 24 PTSD subjects (79%) and 39 of the original 50 Non-PTSD subjects (78%) were available for this study, which took place during the fourth year after the accident. Our results show that 10 (53%) of the 19 patients with PTSD at one-year still suffered from PTSD after another two-year follow-up interval, while 9 recovered from PTSD during this follow-up period. Only 2 of the 39 without PTSD at one year developed delayed onset PTSD. The best predictor of recovery from chronic PTSD was the initial level of posttraumatic reaction immediately after the accident. These results demonstrate that spontaneous recovery from PTSD can occur even among patients who are currently considered chronic. Severity of initial reaction to the trauma appears to be a major risk factor for non-remitting chronic PTSD.

Acute stress response and posttraumatic stress disorder in traffic accident victims: a one-year prospective, follow-up study

OBJECTIVE

This study was designed to assess the natural course of posttraumatic symptoms formation, as well as the degree to which acute stress reactions predict later posttraumatic stress disorder (PTSD) in injured traffic accident victims.

METHOD

A prospective, 1-year follow-up study was carried out on 74 injured traffic accident victims and a comparison group of 19 patients who were hospitalized for elective orthopedic surgery. Participants were interviewed within the first week following the accident, and follow-up interviews were performed 1, 3, 6, and 12 months after the accident. At 12 months, a structured clinical interview was administered to determine a formal DSM-III-R diagnosis of PTSD.

RESULTS

Twenty-four (32%) of the 74 traffic accident victims, but none of the 19 comparison subjects, met DSM-III-R criteria for PTSD at 1 year. Traffic accident victims who developed PTSD had higher levels of premorbid and comorbid psychopathology. Levels of posttraumatic symptoms were significantly higher from the outset in the subjects who developed PTSD and worsened progressively over the first 3 months, in contrast to subjects without PTSD, who manifested gradual amelioration of symptoms during this time. Existence of posttraumatic symptoms immediately after the accident was a better predictor of later PTSD than was accident or injury severity.

CONCLUSIONS

In this study, a significant portion of injured traffic accident victims manifested PTSD 1 year after the event. The development of PTSD at 1 year can be predicted as early as 1 week after the accident on the basis of the existence and severity of early PTSD-related symptoms. However, the first 3 months following the accident appear to be the critical period for the development of PTSD.

Motion sickness and anxiety

Ninety-four Israeli pilot trainees completed a battery of anxiety related questionnaires: Taylor Manifest Anxiety Scale, EPQ, 16PF, and Spielberger's State and Trait Anxiety Scores. Self reports and flight instructor observations of motion sickness symptoms were collected after initial flights. No significant correlations were found between these two sources. Anxiety scores derived from the battery of anxiety questionnaires were correlated with self reports of motion sickness but not with instructor observations. Discussion focused on the potential limitations of external observers in assessing motion sickness, the convergence of anxiety assessments, and the overlap between anxiety and motion sickness symptoms. Methodological and practical implications conclude the review.