Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI.

How do polyglots-individuals who speak five or more languages-process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants' high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network's response magnitude scales with the degree of engagement of linguistic computations (e.g. related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages coexist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.

High-level language brain regions process sublexical regularities.

A network of left frontal and temporal brain regions supports language processing. This "core" language network stores our knowledge of words and constructions as well as constraints on how those combine to form sentences. However, our linguistic knowledge additionally includes information about phonemes and how they combine to form phonemic clusters, syllables, and words. Are phoneme combinatorics also represented in these language regions? Across five functional magnetic resonance imaging experiments, we investigated the sensitivity of high-level language processing brain regions to sublexical linguistic regularities by examining responses to diverse nonwords-sequences of phonemes that do not constitute real words (e.g. punes, silory, flope). We establish robust responses in the language network to visually (experiment 1a, n = 605) and auditorily (experiments 1b, n = 12, and 1c, n = 13) presented nonwords. In experiment 2 (n = 16), we find stronger responses to nonwords that are more well-formed, i.e. obey the phoneme-combinatorial constraints of English. Finally, in experiment 3 (n = 14), we provide suggestive evidence that the responses in experiments 1 and 2 are not due to the activation of real words that share some phonology with the nonwords. The results suggest that sublexical regularities are stored and processed within the same fronto-temporal network that supports lexical and syntactic processes.

A syntax-lexicon trade-off in language production.

Spoken language production involves selecting and assembling words and syntactic structures to convey one's message. Here we probe this process by analyzing natural language productions of individuals with primary progressive aphasia (PPA) and healthy individuals. Based on prior neuropsychological observations, we hypothesize that patients who have difficulty producing complex syntax might choose semantically richer words to make their meaning clear, whereas patients with lexicosemantic deficits may choose more complex syntax. To evaluate this hypothesis, we first introduce a frequency-based method for characterizing the syntactic complexity of naturally produced utterances. We then show that lexical and syntactic complexity, as measured by their frequencies, are negatively correlated in a large (n = 79) PPA population. We then show that this syntax-lexicon trade-off is also present in the utterances of healthy speakers (n = 99) taking part in a picture description task, suggesting that it may be a general property of the process by which humans turn thoughts into speech.

Concepts Are Restructured During Language Contact: The Birth of Blue and Other Color Concepts in Tsimane'-Spanish Bilinguals.

Words and the concepts they represent vary across languages. Here we ask if mother-tongue concepts are altered by learning a second language. What happens when speakers of Tsimane', a language with few consensus color terms, learn Bolivian Spanish, a language with more terms? Three possibilities arise: Concepts in Tsimane' may remain unaffected, or they may be remapped, either by Tsimane' terms taking on new meanings or by borrowing Bolivian-Spanish terms. We found that adult bilingual speakers (n = 30) remapped Tsimane' concepts without importing Bolivian-Spanish terms into Tsimane'. All Tsimane' terms become more precise; for example, concepts of monolingual shandyes and yushñus (~green or blue, used synonymously by Tsimane' monolinguals; n = 71) come to reflect the Bolivian-Spanish distinction of verde (~green) and azul (~blue). These results show that learning a second language can change the concepts in the first language.

Color naming across languages reflects color use.

What determines how languages categorize colors? We analyzed results of the World Color Survey (WCS) of 110 languages to show that despite gross differences across languages, communication of chromatic chips is always better for warm colors (yellows/reds) than cool colors (blues/greens). We present an analysis of color statistics in a large databank of natural images curated by human observers for salient objects and show that objects tend to have warm rather than cool colors. These results suggest that the cross-linguistic similarity in color-naming efficiency reflects colors of universal usefulness and provide an account of a principle (color use) that governs how color categories come about. We show that potential methodological issues with the WCS do not corrupt information-theoretic analyses, by collecting original data using two extreme versions of the color-naming task, in three groups: the Tsimane', a remote Amazonian hunter-gatherer isolate; Bolivian-Spanish speakers; and English speakers. These data also enabled us to test another prediction of the color-usefulness hypothesis: that differences in color categorization between languages are caused by differences in overall usefulness of color to a culture. In support, we found that color naming among Tsimane' had relatively low communicative efficiency, and the Tsimane' were less likely to use color terms when describing familiar objects. Color-naming among Tsimane' was boosted when naming artificially colored objects compared with natural objects, suggesting that industrialization promotes color usefulness.

Large-scale evidence of dependency length minimization in 37 languages.

Explaining the variation between human languages and the constraints on that variation is a core goal of linguistics. In the last 20 y, it has been claimed that many striking universals of cross-linguistic variation follow from a hypothetical principle that dependency length--the distance between syntactically related words in a sentence--is minimized. Various models of human sentence production and comprehension predict that long dependencies are difficult or inefficient to process; minimizing dependency length thus enables effective communication without incurring processing difficulty. However, despite widespread application of this idea in theoretical, empirical, and practical work, there is not yet large-scale evidence that dependency length is actually minimized in real utterances across many languages; previous work has focused either on a small number of languages or on limited kinds of data about each language. Here, using parsed corpora of 37 diverse languages, we show that overall dependency lengths for all languages are shorter than conservative random baselines. The results strongly suggest that dependency length minimization is a universal quantitative property of human languages and support explanations of linguistic variation in terms of general properties of human information processing.

Don't Underestimate the Benefits of Being Misunderstood.

Being a nonnative speaker of a language poses challenges. Individuals often feel embarrassed by the errors they make when talking in their second language. However, here we report an advantage of being a nonnative speaker: Native speakers give foreign-accented speakers the benefit of the doubt when interpreting their utterances; as a result, apparently implausible utterances are more likely to be interpreted in a plausible way when delivered in a foreign than in a native accent. Across three replicated experiments, we demonstrated that native English speakers are more likely to interpret implausible utterances, such as "the mother gave the candle the daughter," as similar plausible utterances ("the mother gave the candle to the daughter") when the speaker has a foreign accent. This result follows from the general model of language interpretation in a noisy channel, under the hypothesis that listeners assume a higher error rate in foreign-accented than in nonaccented speech.

Structural priming is most useful when the conclusions are statistically robust.

Branigan & Pickering (B&P) claim that the success of structural priming as a method should "end the current reliance on acceptability judgments." Structural priming is an interesting and useful phenomenon, but we are dubious that the effect is powerful enough to test many detailed claims about specific points of syntactic theory.

Reliable individual-level neural markers of high-level language processing: A necessary precursor for relating neural variability to behavioral and genetic variability.

The majority of functional neuroimaging investigations aim to characterize an average human brain. However, another important goal of cognitive neuroscience is to understand the ways in which individuals differ from one another and the significance of these differences. This latter goal is given special weight by the recent reconceptualization of neurological disorders where sharp boundaries are no longer drawn either between health and neuropsychiatric and neurodevelopmental disorders, or among different disorders (e.g., Insel et al., 2010). Consequently, even the variability in the healthy population can inform our understanding of brain disorders. However, because the use of functional neural markers is still in its infancy, no consensus presently exists about which measures (e.g., effect size?, extent of activation?, degree of lateralization?) are the best ones to use. We here attempt to address this question with respect to one large-scale neural system: the set of brain regions in the frontal and temporal cortices that jointly support high-level linguistic processing (e.g., Binder et al., 1997; Fedorenko, Hsieh, Nieto-Castanon, Whitfield-Gabrieli, & Kanwisher, 2010). In particular, using data from 150 individuals all of whom had performed a language "localizer" task contrasting sentences and nonword sequences (Fedorenko et al., 2010), we: a) characterize the distributions of the values for four key neural measures of language activity (region effect sizes, region volumes, lateralization based on effect sizes, and lateralization based on volumes); b) test the reliability of these measures in a subset of 32 individuals who were scanned across two sessions; c) evaluate the relationship among the different regions of the language system; and d) evaluate the relationship among the different neural measures. Based on our results, we provide some recommendations for future studies of brain-behavior and brain-genes relationships. Although some of our conclusions are specific to the language system, others (e.g., the fact that effect-size-based measures tend to be more reliable than volume-based measures) are likely to generalize to the rest of the brain.

Syntactic processing is distributed across the language system.

Language comprehension recruits an extended set of regions in the human brain. Is syntactic processing localized to a particular region or regions within this system, or is it distributed across the entire ensemble of brain regions that support high-level linguistic processing? Evidence from aphasic patients is more consistent with the latter possibility: damage to many different language regions and to white-matter tracts connecting them has been shown to lead to similar syntactic comprehension deficits. However, brain imaging investigations of syntactic processing continue to focus on particular regions within the language system, often parts of Broca's area and regions in the posterior temporal cortex. We hypothesized that, whereas the entire language system is in fact sensitive to syntactic complexity, the effects in some regions may be difficult to detect because of the overall lower response to language stimuli. Using an individual-subjects approach to localizing the language system, shown in prior work to be more sensitive than traditional group analyses, we indeed find responses to syntactic complexity throughout this system, consistent with the findings from the neuropsychological patient literature. We speculate that such distributed nature of syntactic processing could perhaps imply that syntax is inseparable from other aspects of language comprehension (e.g., lexico-semantic processing), in line with current linguistic and psycholinguistic theories and evidence. Neuroimaging investigations of syntactic processing thus need to expand their scope to include the entire system of high-level language processing regions in order to fully understand how syntax is instantiated in the human brain.

Dissociating language and thought in large language models.

Large language models (LLMs) have come closest among all models to date to mastering human language, yet opinions about their linguistic and cognitive capabilities remain split. Here, we evaluate LLMs using a distinction between formal linguistic competence (knowledge of linguistic rules and patterns) and functional linguistic competence (understanding and using language in the world). We ground this distinction in human neuroscience, which has shown that formal and functional competence rely on different neural mechanisms. Although LLMs are surprisingly good at formal competence, their performance on functional competence tasks remains spotty and often requires specialized fine-tuning and/or coupling with external modules. We posit that models that use language in human-like ways would need to master both of these competence types, which, in turn, could require the emergence of separate mechanisms specialized for formal versus functional linguistic competence.

Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI.

How do polyglots-individuals who speak five or more languages-process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher-proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants' high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network's response magnitude scales with the degree of engagement of linguistic computations (e.g., related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages co-exist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.

An information-theoretic approach to the typology of spatial demonstratives.

We explore systems of spatial deictic words (such as 'here' and 'there') from the perspective of communicative efficiency using typological data from over 200 languages Nintemann et al. (2020). We argue from an information-theoretic perspective that spatial deictic systems balance informativity and complexity in the sense of the Information Bottleneck (Zaslavsky et al., (2018). We find that under an appropriate choice of cost function and need probability over meanings, among all the 21,146 theoretically possible spatial deictic systems, those adopted by real languages lie near an efficient frontier of informativity and complexity. Moreover, we find that the conditions that the need probability and the cost function need to satisfy for this result are consistent with the cognitive science literature on spatial cognition, especially regarding the source-goal asymmetry. We further show that the typological data are better explained by introducing a notion of consistency into the Information Bottleneck framework, which is jointly optimized along with informativity and complexity.

Grammatical cues to subjecthood are redundant in a majority of simple clauses across languages.

Grammatical cues are sometimes redundant with word meanings in natural language. For instance, English word order rules constrain the word order of a sentence like "The dog chewed the bone" even though the status of "dog" as subject and "bone" as object can be inferred from world knowledge and plausibility. Quantifying how often this redundancy occurs, and how the level of redundancy varies across typologically diverse languages, can shed light on the function and evolution of grammar. To that end, we performed a behavioral experiment in English and Russian and a cross-linguistic computational analysis measuring the redundancy of grammatical cues in transitive clauses extracted from corpus text. English and Russian speakers (n = 484) were presented with subjects, verbs, and objects (in random order and with morphological markings removed) extracted from naturally occurring sentences and were asked to identify which noun is the subject of the action. Accuracy was high in both languages (∼89% in English, ∼87% in Russian). Next, we trained a neural network machine classifier on a similar task: predicting which nominal in a subject-verb-object triad is the subject. Across 30 languages from eight language families, performance was consistently high: a median accuracy of 87%, comparable to the accuracy observed in the human experiments. The conclusion is that grammatical cues such as word order are necessary to convey subjecthood and objecthood in a minority of naturally occurring transitive clauses; nevertheless, they can (a) provide an important source of redundancy and (b) are crucial for conveying intended meaning that cannot be inferred from the words alone, including descriptions of human interactions, where roles are often reversible (e.g., Ray helped Lu/Lu helped Ray), and expressing non-prototypical meanings (e.g., "The bone chewed the dog.").

How Efficiency Shapes Human Language.

Cognitive science applies diverse tools and perspectives to study human language. Recently, an exciting body of work has examined linguistic phenomena through the lens of efficiency in usage: what otherwise puzzling features of language find explanation in formal accounts of how language might be optimized for communication and learning? Here, we review studies that deploy formal tools from probability and information theory to understand how and why language works the way that it does, focusing on phenomena ranging from the lexicon through syntax. These studies show how a pervasive pressure for efficiency guides the forms of natural language and indicate that a rich future for language research lies in connecting linguistics to cognitive psychology and mathematical theories of communication and inference.

A robust dissociation among the language, multiple demand, and default mode networks: Evidence from inter-region correlations in effect size.

Complex cognitive processes, including language, rely on multiple mental operations that are carried out by several large-scale functional networks in the frontal, temporal, and parietal association cortices of the human brain. The central division of cognitive labor is between two fronto-parietal bilateral networks: (a) the multiple demand (MD) network, which supports executive processes, such as working memory and cognitive control, and is engaged by diverse task domains, including language, especially when comprehension gets difficult; and (b) the default mode network (DMN), which supports introspective processes, such as mind wandering, and is active when we are not engaged in processing external stimuli. These two networks are strongly dissociated in both their functional profiles and their patterns of activity fluctuations during naturalistic cognition. Here, we focus on the functional relationship between these two networks and a third network: (c) the fronto-temporal left-lateralized "core" language network, which is selectively recruited by linguistic processing. Is the language network distinct and dissociated from both the MD network and the DMN, or is it synchronized and integrated with one or both of them? Recent work has provided evidence for a dissociation between the language network and the MD network. However, the relationship between the language network and the DMN is less clear, with some evidence for coordinated activity patterns and similar response profiles, perhaps due to the role of both in semantic processing. Here we use a novel fMRI approach to examine the relationship among the three networks: we measure the strength of activations in different language, MD, and DMN regions to functional contrasts typically used to identify each network, and then test which regions co-vary in their contrast effect sizes across 60 individuals. We find that effect sizes correlate strongly within each network (e.g., one language region and another language region, or one DMN region and another DMN region), but show little or no correlation for region pairs across networks (e.g., a language region and a DMN region). Thus, using our novel method, we replicate the language/MD network dissociation discovered previously with other approaches, and also show that the language network is robustly dissociated from the DMN, overall suggesting that these three networks contribute to high-level cognition in different ways and, perhaps, support distinct computations. Inter-individual differences in effect sizes therefore do not simply reflect general differences in vascularization or attention, but exhibit sensitivity to the functional architecture of the brain. The strength of activation in each network can thus be probed separately in studies that attempt to link neural variability to behavioral or genetic variability.

Word Forms Are Structured for Efficient Use.

Zipf famously stated that, if natural language lexicons are structured for efficient communication, the words that are used the most frequently should require the least effort. This observation explains the famous finding that the most frequent words in a language tend to be short. A related prediction is that, even within words of the same length, the most frequent word forms should be the ones that are easiest to produce and understand. Using orthographics as a proxy for phonetics, we test this hypothesis using corpora of 96 languages from Wikipedia. We find that, across a variety of languages and language families and controlling for length, the most frequent forms in a language tend to be more orthographically well-formed and have more orthographic neighbors than less frequent forms. We interpret this result as evidence that lexicons are structured by language usage pressures to facilitate efficient communication.

Wordform Similarity Increases With Semantic Similarity: An Analysis of 100 Languages.

Although the mapping between form and meaning is often regarded as arbitrary, there are in fact well-known constraints on words which are the result of functional pressures associated with language use and its acquisition. In particular, languages have been shown to encode meaning distinctions in their sound properties, which may be important for language learning. Here, we investigate the relationship between semantic distance and phonological distance in the large-scale structure of the lexicon. We show evidence in 100 languages from a diverse array of language families that more semantically similar word pairs are also more phonologically similar. This suggests that there is an important statistical trend for lexicons to have semantically similar words be phonologically similar as well, possibly for functional reasons associated with language learning.