The role of domain-general cognitive control in language comprehension

What role does domain-general cognitive control play in understanding linguistic input? Although much evidence has suggested that domain-general cognitive control and working memory resources are sometimes recruited during language comprehension, many aspects of this relationship remain elusive. For example, how frequently do cognitive control mechanisms get engaged when we understand language? And is this engagement necessary for successful comprehension? I here a) review recent brain imaging evidence for the neural separability of the brain regions that support high-level linguistic processing vs. those that support domain-general cognitive control abilities; b) define the space of possibilities for the relationship between these sets of brain regions; and c) review the available evidence that constrains these possibilities to some extent. I argue that we should stop asking whether domain-general cognitive control mechanisms play a role in language comprehension, and instead focus on characterizing the division of labor between the cognitive control brain regions and the more functionally specialized language regions

Domain-General Brain Regions Do Not Track Linguistic Input as Closely as Language-Selective Regions

Language comprehension engages a cortical network of left frontal and temporal regions. Activity in this network is language-selective, showing virtually no modulation by nonlinguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, c ingulate, and insular regions. Activity in this “multiple demand” (MD) network scales with comprehension difficulty, but also with cognitive effort across a wide range of nonlinguistic tasks in a domain-general fashion. Given the functional dissociation between the language and MD networks, their respective contributions to comprehension are likely distinct, yet such differences remain elusive. Prior neuroimaging studies have suggested that activity in each network covaries with some linguistic features that, behaviorally, influence on-line processing and comprehension. This sensitivity of the language and MD networks to local input characteristics has often been interpreted, implicitly or explicitly, as evidence that both networks track linguistic input closely, and in a manner consistent across individuals. Here, we used fMRI to directly test this assumption by comparing the BOLD signal time courses in each network across different people (n=45, men and women) listening to the same story. Language network activity showed fewer individual differences, indicative of closer input tracking, whereas MD network activity was more idiosyncratic and, moreover, showed lower reliability within an individual across repetitions of a story. These findings constrain cognitive models of language comprehension by suggesting a novel distinction between the processes implemented in the language and MD networks. Keywords: comprehension; functional localization; intersubject correlation; language network; multiple-demand network; naturalistic cognitio

The nature of the working memory system underlying language processing and its relationship to the long-term memory system

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2007.Includes bibliographical references (leaves 139-145).This thesis examines two questions concerning the working memory system underlying language processing: (1) To what extent is the working memory system underlying language processing domain-specific? and (2) What is the relationship between the working memory system and the long-term memory system in language processing? In Chapter 1, I describe ten experiments investigating the extent to which the working memory system underlying linguistic integrations is domain-specific. I argue that the results of these experiments demonstrate that at least some aspects of the working memory system used for linguistic integrations are not domain-specific, being involved in arithmetic, and possibly, musical processing. In Chapter 2, I describe six experiments investigating the relationship between the two retrieval operations that are required when an incoming word is integrated into an evolving structure: the retrieval of the lexical properties of the word from long-term memory and the retrieval of its structural dependents from working memory. I demonstrate that the relative ease or difficulty of retrieving the lexical properties of an incoming word affect the difficulty of retrieving its structural dependents. I therefore argue that the two retrieval operations rely on overlapping pools of resources.by Evelina G. Fedorenko.Ph.D

The Time-Course of Lexical and Structural Processes in Sentence Comprehension

Online sentence comprehension involves multiple types of cognitive processes: lexical processes such as lexical access, which call on the user's knowledge of the meaning of words in the language, and structural processes such as the integration of incoming words into an emerging representation. In this article, we investigate the temporal dynamics of lexical access and syntactic integration. Unlike much previous work that has relied on temporary ambiguity to investigate this question, we manipulate the frequency of the verb in unambiguous structures involving a well-studied syntactic complexity manipulation (subject- vs. object-extracted clefts). The results demonstrate that for high-frequency verbs, the difficulty of reading a more structurally complex object-extracted cleft structure relative to a less structurally complex subject-extracted cleft structure is largely experienced in the cleft region, whereas for low-frequency verbs this difficulty is largely experienced in the postcleft region. We interpret these results as evidence that some stages of structural processing follow lexical processing. Furthermore, we find evidence that structural processing may be delayed if lexical processing is costly, and that the delay is proportional to the difficulty of the lexical process. Implications of these results for contemporary accounts of sentence comprehension are discussed

An algorithmic method for functionally defining regions of interest in the ventral visual pathway

In a widely used functional magnetic resonance imaging (fMRI) data analysis method, functional regions of interest (fROIs) are handpicked in each participant using macroanatomic landmarks as guides, and the response of these regions to new conditions is then measured. A key limitation of this standard handpicked fROI method is the subjectivity of decisions about which clusters of activated voxels should be treated as the particular fROI in question in each subject. Here we apply the Group-Constrained Subject-Specific (GSS) method for defining fROIs, recently developed for identifying language fROIs (Fedorenko et al., 2010), to algorithmically identify fourteen well-studied category-selective regions of the ventral visual pathway (Kanwisher, 2010). We show that this method retains the benefit of defining fROIs in individual subjects without the subjectivity inherent in the traditional handpicked fROI approach. The tools necessary for using this method are available on our website (http://web.mit.edu/bcs/nklab/GSS.shtml).Ellison Medical Foundatio

Activity in the fronto-parietal multiple-demand network is robustly associated with individual differences in working memory and fluid intelligence.

Numerous brain lesion and fMRI studies have linked individual differences in executive abilities and fluid intelligence to brain regions of the fronto-parietal "multiple-demand" (MD) network. Yet, fMRI studies have yielded conflicting evidence as to whether better executive abilities are associated with stronger or weaker MD activations and whether this relationship is restricted to the MD network. Here, in a large-sample (n = 216) fMRI investigation, we found that stronger activity in MD regions - functionally defined in individual participants - was robustly associated with more accurate and faster responses on a spatial working memory task performed in the scanner, as well as fluid intelligence measured independently (n = 114). In line with some prior claims about a relationship between language and fluid intelligence, we also found a weak association between activity in the brain regions of the left fronto-temporal language network during an independent passive reading task, and performance on the working memory task. However, controlling for the level of MD activity abolished this relationship, whereas the MD activity-behavior association remained highly reliable after controlling for the level of activity in the language network. Finally, we demonstrate how unreliable MD activity measures, coupled with small sample sizes, could falsely lead to the opposite, negative, association that has been reported in some prior studies. Taken together, these results demonstrate that a core component of individual differences variance in executive abilities and fluid intelligence is selectively and robustly positively associated with the level of activity in the MD network, a result that aligns well with lesion studies

JOSA: Joint surface-based registration and atlas construction of brain geometry and function

Surface-based cortical registration is an important topic in medical image analysis and facilitates many downstream applications. Current approaches for cortical registration are mainly driven by geometric features, such as sulcal depth and curvature, and often assume that registration of folding patterns leads to alignment of brain function. However, functional variability of anatomically corresponding areas across subjects has been widely reported, particularly in higher-order cognitive areas. In this work, we present JOSA, a novel cortical registration framework that jointly models the mismatch between geometry and function while simultaneously learning an unbiased population-specific atlas. Using a semi-supervised training strategy, JOSA achieves superior registration performance in both geometry and function to the state-of-the-art methods but without requiring functional data at inference. This learning framework can be extended to any auxiliary data to guide spherical registration that is available during training but is difficult or impossible to obtain during inference, such as parcellations, architectonic identity, transcriptomic information, and molecular profiles. By recognizing the mismatch between geometry and function, JOSA provides new insights into the future development of registration methods using joint analysis of the brain structure and function.Comment: A. V. Dalca and B. Fischl are co-senior authors with equal contribution. arXiv admin note: text overlap with arXiv:2303.0159

The multiple-demand system but not the language system supports fluid intelligence.

A set of frontoparietal brain regions - the multiple-demand (MD) system [1, 2] - has been linked to fluid intelligence in brain imaging [3, 4] and in studies of patients with brain damage [5-7].For example, the amount of damage to frontal or parietal, but not temporal, cortices predicts fluid intelligence deficit [5]. However, frontal and parietal lobes are structurally [8] and functionally [9, 10] heterogeneous. They contain domain-general regions that respond across diverse tasks [11, 12], but also specialized regions that respond selectively during language processing [13]. Since language may be critical for complex thought [14-24, cf. 25-26], intelligence loss following damage to frontoparietal cortex could have important contributions from damage to language-selective regions. To evaluate the relative contributions of MD vs. language-selective regions, we employed large fMRI datasets to construct probabilistic maps of the two systems. We used these maps to weigh the volume of lesion (in each of 80 patients) falling within each system. MD-weighted, but not language-weighted, lesion volumes predicted fluid intelligence deficit (with the opposite pattern observed for verbal fluency), suggesting that fluid intelligence is specifically tied to the MD system, and undermining claims that language is at the core of complex thought