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This chapter discusses the default mode network (DMN), a set of anatomically distinct and functionally correlated brain regions robustly active during the resting state. Once considered the “task negative” network, the DMN is now appreciated as integral to a variety of higher-level, goal-directed skills that are bidirectionally linked to language. Such abilities are dependent on optimal interaction of the DMN with other brain networks. We first review the DMN’s association with cognition and language in the healthy brain, as well as how these change with aging, stroke, and neurodegeneration. Next, we survey existing research describing changes in DMN activation and functional connectivity in post-stroke and primary progressive aphasia as they relate to language impairment. While this connection remains poorly elaborated, we propose that current evidence supports a potential therapeutic role for the DMN, such as through offering targets for noninvasive brain stimulation that support domain-general skills and are also better structurally preserved in post-stroke and primary progressive aphasias compared to the language regions primarily impacted by these disorders. Greater understanding of the DMN’s role in language disruption, decline, maintenance, and recovery could ultimately help to improve outcomes for individuals with aphasia due to stroke or neurodegeneration.
Location mentions in local news are crucial for examining issues like spatial inequalities, news deserts and the impact of media ownership on news diversity. However, while geoparsing – extracting and resolving location mentions – has advanced through statistical and deep learning methods, its use in local media studies remains limited and fragmented due to technical challenges and a lack of practical frameworks. To address these challenges, we identify key considerations for successful geoparsing and review spatially oriented local media studies, finding over-reliance on limited geospatial vocabularies, limited toponym disambiguation and inadequate validation of methods. These findings underscore the need for adaptable and robust solutions, and recent advancements in fine-tuned large language models (LLMs) for geoparsing offer a promising direction by simplifying technical implementation and excelling at understanding contextual nuances. However, their application to U.K. local media – marked by fine-grained geographies and colloquial place names – remains underexplored due to the absence of benchmark datasets. This gap hinders researchers’ ability to evaluate and refine geoparsing methods for this domain. To address this, we introduce the Local Media UK Geoparsing (LMUK-Geo) dataset, a hand-annotated corpus of U.K. local news articles designed to support the development and evaluation of geoparsing pipelines. We also propose an LLM-driven approach for toponym disambiguation that replaces fine-tuning with accessible prompt engineering. Using LMUK-Geo, we benchmark our approach against a fine-tuned method. Both perform well on the novel dataset: the fine-tuned model excels in minimising coordinate-error distances, while the prompt-based method offers a scalable alternative for district-level classification, particularly when relying on predictions agreed upon by multiple models. Our contributions establish a foundation for geoparsing local media, advancing methodological frameworks and practical tools to enable systematic and comparative research.
Lateralization and localization of language in the brain is a critical component of surgical planning for patients with epilepsy or brain tumors who require neurosurgical intervention. Accurate language mapping allows the surgeon to conduct the most aggressive surgery possible, enhancing the chance for cure, while avoiding regions critical for language function; striking this balance is critical for maximizing the patient’s quality of life. A range of invasive and non-invasive language mapping techniques are available. This chapter provides a comparative analysis of these techniques and offers a detailed discussion on a newer, non-invasive method called transcranial magnetic stimulation (TMS). Using a superficial coil placed on the scalp, TMS generates a magnetic field that creates a temporary “virtual lesion” in the brain, thereby delineating eloquent cortex. TMS is a safe and well-tolerated procedure for both pediatric and adult populations which closely mimics the “gold-standard” invasive mapping techniques. TMS is becoming an integral component of neurosurgical planning and also shows promise as a research tool for studying typical language development and function in healthy populations.
Variability in ultimate learning outcomes is a conspicuous trait of second language (L2) acquisition. After enumerating well-studied conditioning factors in L2 attainment, the present chapter identifies five for particular attention: working memory, attitudes, music background, genetic makeup, and age of acquisition. Along with detailing the factors’ individual roles in L2 attainment, we demonstrate inter-relationships between them. For example, the aptitude factor of working memory ability is subject to genetic variation and may decline over age of L2 learning. We examine variable outcomes from two distinct perspectives: magnitude (i.e., how the identified factors contribute to higher or lower levels of L2 attainment) and dispersion (i.e., how the factors contribute to greater or lesser variability of L2 attainment). Notably, later ages of L2 learning are associated with both lower L2 attainment levels and greater L2 attainment variability. In this vein, we consider the possibility that magnitudes and variability of L2 outcomes over age of learning may be isomorphic with working memory levels and dispersion over the lifespan. In addition, we underscore the transitory nature of individual-level L2 outcomes, which are subject to destabilization following shifts of dominance between the L1 (first language) and the L2.
It is a privilege to present the introduction to this new volume of The Cambridge Handbook of Language and Brain. The chapters in this volume represent important trends, methods, and central questions in research on brain and language that encompasses perspectives that include a spectrum of studies in methodology that range from healthy subjects that use one or multiple languages to neurodiversity and neurological disorders. A reader looking to come up to speed on a particular topic in language and the brain need look no further than thorough the list of contributions in this book.
Music & spoken language share many features by combining smaller units (e.g., words, notes) into larger structures (e.g., sentences, musical phrases). This hierarchical organization of sound is culturally contingent & communicates meaning to listeners. Comparisons of music & language from a cognitive neuroscience perspective provide several insights into commonalities & differences between these systems, how they are represented in the brain. The cognitive neuroscience research of music & language, emphasizes the pitfalls & promises identified, including (1) the apparent acoustic & structural similarities between these systems, (2) how both systems convey meaning to listeners, (3) how these systems are learned over the course of development, & (4) the ways in which experience in one domain influences processing in the other domain. We conclude that searching for similarities in how these complex systems are structured (e.g., comparing musical syntax to linguistic syntax) represents a pitfall that researchers should approach with caution. A promising approach in this area of research is to examine how general cognitive mechanisms underlie the learning & maintenance of both systems
Anticipatory processes can influence how quickly comprehenders can process novel linguistic input and how they learn from linguistic surprises. This chapter outlines experimental evidence establishing the psychological reality of anticipatory processes and sketches some contemporary accounts that explain how comprehenders generate predictions from linguistic input. Accounts like Pickering & Gambi’s (2018) formulation suggest that comprehenders covertly engage language production mechanisms to generate predictions about future input and to know when it is time to stop processing current input. Kuperberg and colleagues’ (2021, 2023) formulation lays out a multi-layered network that produces predictions for several different types of linguistic and semantic information (phonological/orthographic, syntactic, lexical, event). N-gram accounts (Brennan, 2020; Hale, 2003, 2016) focus on word predictions and include formal metrics of entropy and surprisal derived from information-theoretic frameworks like Shallice’s. On this account, comprehenders store in long-term memory strings of words (N-grams) and these stored patterns serve as the basis for calculating entropy (how many different continuations are possible at a given point) and surprisal (how likely is a specific word in a specific context). We present a variety of evidence indicating that n-grams may not be the sole or main basis for predictions.
Since the late 1990s, thousands of fMRI studies have been conducted on different aspects of language processing in the human brain. The earlier studies were generally devoted to first language or monolingual processing, but the field has continued to expand to include both studies of a single first language, and bi/multilingual language processing in the brain. A modest number of fMRI longitudinal studies of second language acquisition began to emerge over the past 13 years. The following analysis uses the findings of these BOLD fMRI longitudinal studies of second language acquisition, including comparison with cross-sectional studies of L2 acquisition, to make recommendations for enhancing the research design and empirical measurements to facilitate new methodologies and approaches. Conclusions include a discussion of the utility of longitudinal studies, elucidation of the theoretical foundation of dynamic modeling underlying individual user variation in L1/L2 language processing, inclusion of a broader array of imaging techniques (structural DTI, resting state fMRI and functional connectivity), and the importance of proficiency measurements and proficiency testing as a part of research design.
Prosody not only signals the speaker’s cognitive states but can also imitate various concepts. However, previous studies on the latter, the iconic function of prosody, have mostly analyzed novel words and nonlinguistic vocalizations. To fill this gap in the literature, the current study has examined the iconic potential of the prosodic features of existing Japanese imitative words known as ideophones. In Experiment 1, female Japanese speakers pronounced 20 sentences containing ideophones in infant-directed speech. They used a higher f0 to express faster and more pleasant movements. Similar iconic associations were observed in Experiment 2, in which Japanese speakers chose the best-matching pitch–intensity–duration combination for each of the ideophones. In Experiment 3, Japanese speakers chose the best-matching voice quality – creaky voice, falsetto, harsh voice or whisper – for the ideophones. Falsetto was preferred for a light object’s fast motion, harsh voice for violent motion and whisper for quiet motion. Based on these results, we entertain the possibility that the iconic prosody of ideophones provides a missing link in the evolutionary theory of language that began with iconic vocalizations. Ideophones with varying degrees of iconic prosody can be considered to be located between nonlinguistic vocalizations and arbitrary words in this evolutionary path.
The emergence of robust accessibility to functional neuroimaging in the late 1990s and early 2000s provided a new way to study language processing in the human brain, the most common techniques being PET and fMRI studies. Prior to this moment, neural language mappings were tied to invasive procedures in surgery and pathology, where CSM (cortical stimulation mapping) was one of the primary sources of data. Reframing approaches to understanding language processing in the brain allowed for closer ties between the cognitive neurosciences and linguistic theory, as well as new perspectives of multimodalities, resting state functional connectivity, and embodied cognition. Here we explore the range of outcomes in functional and structural neuroimaging studies focusing on language processing in the brain, including studies of bi- and multilingualism. The chapter concludes with a discussion of some of the central challenges in neuroimaging studies of language(s), including software and inter-method discrepancies, protocol design, proficiency measurements, and ecological validity.
Language and other cognitive abilities interact with each other in a complex fashion. This interaction affects how we understand and develop models of cognitive function, interpret data reflecting neural activation and connectivity, and diagnose and treat language and cognitive conditions. The goal of this chapter is to provide a cohesive narrative introduction to major cognitive processes and some of the ways in which they interact with language processing. The chapter addresses four key non-linguistic cognitive processes: attention, memory, working memory, and executive function. Each process is discussed in terms of current thinking and prominent models regarding how it functions, its neural substrates, and how it affects and is affected by language function. While the cognitive processes discussed are presented separately, they share underlying relationships, and some models of cognition conceptualize the divisions between constructs differently. This chapter offers a clear but somewhat simplified overview in the interest of providing a basis for conceptualizing the interactive nature of language and other cognitive skills.