Idan Blank

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 Brocas 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.

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, cingulate, 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. SIGNIFICANCE STATEMENT Language comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized “core language network”, whereas domain-general mechanisms are implemented in the bilateral “multiple demand” (MD) network. Here, we report the first direct comparison of the respective contributions of these networks to naturalistic story comprehension. Using a novel combination of neuroimaging approaches we find that MD regions track stories less closely than language regions. This finding constrains the possible contributions of the MD network to comprehension, contrasts with accounts positing that this network has continuous access to linguistic input, and suggests a new typology of comprehension processes based on their extent of input tracking.

An Integrated Neural Framework for Dynamic and Static Face Processing

Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant aspects, whereas the OFA and FFA showed similar response across all four conditions. These findings support an integrated neural model of face processing in which the ventral areas extract form information from both invariant and changeable facial aspects whereas the dorsal face areas are sensitive to dynamic and changeable facial aspects.

The processing of dynamic faces in the human brain: Support for an integrated neural framework of face processing.

Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two major functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant facial aspects, whereas the OFA and FFA showed similar response across all four conditions. Our results reveal no dissociation between the processing of changeable and invariant facial aspects, but higher sensitivity to the processing of changeable facial aspects by the motion-sensitive face area in the superior temporal sulcus.

Can neuroimaging help aphasia researchers? Addressing generalizability, variability, and interpretability

ABSTRACT Neuroimaging studies of individuals with brain damage seek to link brain structure and activity to cognitive impairments, spontaneous recovery, or treatment outcomes. To date, such studies have relied on the critical assumption that a given anatomical landmark corresponds to the same functional unit(s) across individuals. However, this assumption is fallacious even across neurologically healthy individuals. Here, we discuss the severe implications of this issue, and argue for an approach that circumvents it, whereby: (i) functional brain regions are defined separately for each subject using fMRI, allowing for inter-individual variability in their precise location; (ii) the response profile of these subject-specific regions are characterized using various other tasks; and (iii) the results are averaged across individuals, guaranteeing generalizabliity. This method harnesses the complementary strengths of single-case studies and group studies, and it eliminates the need for post hoc “reverse inference” from anatomical landmarks back to cognitive operations, thus improving data interpretability.

Expanding the language network: Domain-specific hippocampal recruitment during high-level linguistic processing

Language processing requires us to encode linear relations between acoustic forms and map them onto hierarchical relations between meaning units. Such relational binding of linguistic elements might recruit the hippocampus given its engagement by similar operations in other cognitive domains. Historically, hippocampal engagement in online language use has received little attention because patients with hippocampal damage are not aphasic. However, recent studies have found that these patients exhibit language impairments when the demands on flexible relational binding are high, suggesting that the hippocampus does, in fact, contribute to linguistic processing. A fundamental question is thus whether language processing engages domain-general hippocampal mechanisms that are also recruited across other cognitive processes or whether, instead, it relies on certain language-selective areas within the hippocampus. To address this question, we conducted the first systematic analysis of hippocampal engagement during comprehension in healthy adults (n=150 across three experiments) using fMRI. Specifically, we functionally localized putative “language-regions” within the hippocampus using a language comprehension task, and found that these regions (i) were selectively engaged by language but not by six non-linguistic tasks; and (ii) were coupled in their activity with the cortical language network during both “rest” and especially story comprehension, but not with the domain-general “multiple-demand (MD)” network. This functional profile did not generalize to other hippocampal regions that were localized using a non-linguistic, working memory task. These findings suggest that some hippocampal mechanisms that maintain and integrate information during language comprehension are not domain-general but rather belong to the language-specific brain network. Significance statement According to popular views, language processing is exclusively supported by neocortical mechanisms. However, recent patient studies suggest that language processing may also require the hippocampus, especially when relations among linguistic elements have to be flexibly integrated and maintained. Here, we address a core question about the place of the hippocampus in the cognitive architecture of language: are certain hippocampal operations language-specific rather than domain-general? By extensively characterizing hippocampal recruitment during language comprehension in healthy adults using fMRI, we show that certain hippocampal subregions exhibit signatures of language specificity in both their response profiles and their patterns of activity synchronization with known functional regions in the neocortex. We thus suggest that the hippocampus is a satellite constituent of the language network.

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

ABSTRACT 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. HighlightsIs the language network dissociable from multiple‐demand and default mode networks?Novel test: do individual differences in effect size (ES) correlate across regions?Individual differences co‐vary within networks much more than between networks.Data‐driven support for a triple language/multiple‐demand/default mode dissociation.Individual differences in regional ES respect the brains functional organization.

An attempt to replicate a dissociation between syntax and semantics during sentence comprehension reported by Dapretto & Bookheimer (1999, Neuron)

Does processing the meanings of individual words vs. assembling words into phrases and sentences rely on distinct pools of cognitive and neural resources? Many have argued for such a dissociation, although the field is lacking a consensus on which brain region(s) support lexico-semantic vs. syntactic processing. Although some have also argued against such a dissociation, the dominant view in the field remains that distinct brain regions support these two fundamental components of language. One of the earlier and most cited pieces of evidence in favor of this dissociation comes from a paper by Dapretto & Bookheimer (1999, Neuron; DB). Using a sentence meaning comparison task, DB observed two distinct peaks within the left inferior frontal gyrus (LIFG): one more active when comparisons relied on lexico-semantic cues, and another – when they instead relied on syntactic cues. Although the paper has been highly cited over the years, no attempt has been made, to our knowledge, to replicate the original finding. We here report an fMRI study that attempts to do so. Using a combination of three approaches – whole-brain, group-level ROIs, and individual functional ROIs – we fail to replicate the originally reported dissociation. In particular, parts of the LIFG respond reliably more strongly during lexico-semantic than syntactic processing, but no part of the LIFG (including in the region defined around the peak reported by DB) shows the opposite response pattern. We hypothesize that the original result was a false positive, possibly driven by one participant or item given the use of a fixed-effects analysis and a small number of items (8 per condition) and participants (n=8).

Language-selective brain regions track linguistic input more closely than domain-general 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 non-linguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, cingulate, and insular regions. Activity in this “Multiple Demand (MD)” network scales with comprehension difficulty, but also with cognitive effort across a wide range of non-linguistic 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. Critically, given that each network is sensitive to some linguistic features, prior research has assumed – implicitly or explicitly – 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 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. Significance Statement Language comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized “core language network”, whereas domain-general mechanisms are implemented in the bilateral “Multiple Demand (MD)” network. Here, we report the first direct comparison of the respective contributions of these networks to naturalistic story comprehension. Using a novel combination of neuroimaging approaches we find that MD regions track stories less closely than language regions. This finding constrains the possible contributions of the MD network to comprehension, contrasts with accounts positing that this network has continuous access to linguistic input, and suggests a new typology of comprehension processes based on their extent of input tracking.