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

The language network as a natural kind within the broader landscape of the human brain

Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent of input and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive only to these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.

CHANGES IN FUNCTIONAL CONNECTIVITY FOLLOWING INTENSIVE ATTENTION TRAINING IN PATIENTS WITH TRAUMATIC BRAIN INJURY. A PILOT STUDY

Objective

To explore functional connectivity after intensive attention training in the chronic phase after traumatic brain injury as clinical evidence indicates that intensive attention training improves attention dysfunction in persons with traumatic brain injury.

Design and subjects

A case series study. Two young adults, 13- and 18-months post traumatic brain injury, with traumatic brain injury induced attention deficits were assigned to 20 h of intensive attention training and neuroimaging.

Methods

Functional magnetic resonance imaging during a psychomotor vigilance test was conducted pre- and post-intervention.

Results

The neuroimaging indicated both increased and decreased connectivity density in frontal, posterior and subcortical brain regions, for some regions with separate change patterns for left and right hemisphere respectively, and an overall reduction in variability in functional connectivity.

Conclusion

The changed and decreased variability of functional connectivity in various brain regions, captured by fMRI during a psychomotor vigilance test after direct attention training in a small sample of persons with traumatic brain injury, suggests further studies of functional connectivity changes in neural networks.

Modality-Specificity of the Neural Correlates of Linguistic and Non-Linguistic Demand

Imaging studies of language processing in clinical populations can be complicated to interpret for several reasons, one being the difficulty of matching the effortfulness of processing across individuals or tasks. To better understand how effortful linguistic processing is reflected in functional activity, we investigated the neural correlates of task difficulty in linguistic and non-linguistic contexts in the auditory modality and then compared our findings to a recent analogous experiment in the visual modality in a different cohort. Nineteen neurologically normal individuals were scanned with fMRI as they performed a linguistic task (semantic matching) and a non-linguistic task (melodic matching), each with two levels of difficulty. We found that left hemisphere frontal and temporal language regions, as well as the right inferior frontal gyrus, were modulated by linguistic demand and not by non-linguistic demand. This was broadly similar to what was previously observed in the visual modality. In contrast, the multiple demand (MD) network, a set of brain regions thought to support cognitive flexibility in many contexts, was modulated neither by linguistic demand nor by non-linguistic demand in the auditory modality. This finding was in striking contradistinction to what was previously observed in the visual modality, where the MD network was robustly modulated by both linguistic and non-linguistic demand. Our findings suggest that while the language network is modulated by linguistic demand irrespective of modality, modulation of the MD network by linguistic demand is not inherent to linguistic processing, but rather depends on specific task factors.

Treatment-induced neuroplasticity after anomia therapy in post-stroke aphasia: A systematic review of neuroimaging studies

We systematically reviewed the literature on neural changes following anomia treatment post-stroke. We conducted electronic searches of CINAHL, Cochrane Trials, Embase, Ovid MEDLINE, MEDLINE-in-Process and PsycINFO databases; two independent raters assessed all abstracts and full texts. Accepted studies reported original data on adults with post-stroke aphasia, who received behavioural treatment for anomia, and magnetic resonance brain imaging (MRI) pre- and post-treatment. Search results yielded 2481 citations; 33 studies were accepted. Most studies employed functional MRI and the quality of reporting neuroimaging methodology was variable, particularly for pre-processing steps and statistical analyses. The most methodologically robust data were synthesized, focusing on pre- versus post-treatment contrasts. Studies more commonly reported increases (versus decreases) in activation following naming therapy, primarily in the left supramarginal gyrus, and left/bilateral precunei. Our findings highlight the methodological heterogeneity across MRI studies, and the paucity of robust evidence demonstrating direct links between brain and behaviour in anomia rehabilitation.

The human language system, including its inferior frontal component in "Broca's area," does not support music perception

Language and music are two human-unique capacities whose relationship remains debated. Some have argued for overlap in processing mechanisms, especially for structure processing. Such claims often concern the inferior frontal component of the language system located within "Broca's area." However, others have failed to find overlap. Using a robust individual-subject fMRI approach, we examined the responses of language brain regions to music stimuli, and probed the musical abilities of individuals with severe aphasia. Across 4 experiments, we obtained a clear answer: music perception does not engage the language system, and judgments about music structure are possible even in the presence of severe damage to the language network. In particular, the language regions' responses to music are generally low, often below the fixation baseline, and never exceed responses elicited by nonmusic auditory conditions, like animal sounds. Furthermore, the language regions are not sensitive to music structure: they show low responses to both intact and structure-scrambled music, and to melodies with vs. without structural violations. Finally, in line with past patient investigations, individuals with aphasia, who cannot judge sentence grammaticality, perform well on melody well-formedness judgments. Thus, the mechanisms that process structure in language do not appear to process music, including music syntax.

Causal Evidence for the Multiple Demand Network in Change Detection: Auditory Mismatch Magnetoencephalography across Focal Neurodegenerative Diseases

The multiple demand (MD) system is a network of fronto-parietal brain regions active during the organization and control of diverse cognitive operations. It has been argued that this activation may be a nonspecific signal of task difficulty. However, here we provide convergent evidence for a causal role for the MD network in the "simple task" of automatic auditory change detection, through the impairment of top-down control mechanisms. We employ independent structure-function mapping, dynamic causal modeling (DCM), and frequency-resolved functional connectivity analyses of MRI and magnetoencephalography (MEG) from 75 mixed-sex human patients across four neurodegenerative syndromes [behavioral variant fronto-temporal dementia (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), posterior cortical atrophy (PCA), and Alzheimer's disease mild cognitive impairment with positive amyloid imaging (ADMCI)] and 48 age-matched controls. We show that atrophy of any MD node is sufficient to impair auditory neurophysiological response to change in frequency, location, intensity, continuity, or duration. There was no similar association with atrophy of the cingulo-opercular, salience or language networks, or with global atrophy. MD regions displayed increased functional but decreased effective connectivity as a function of neurodegeneration, suggesting partially effective compensation. Overall, we show that damage to any of the nodes of the MD network is sufficient to impair top-down control of sensation, providing a common mechanism for impaired change detection across dementia syndromes.SIGNIFICANCE STATEMENT Previous evidence for fronto-parietal networks controlling perception is largely associative and may be confounded by task difficulty. Here, we use a preattentive measure of automatic auditory change detection [mismatch negativity (MMN) magnetoencephalography (MEG)] to show that neurodegeneration in any frontal or parietal multiple demand (MD) node impairs primary auditory cortex (A1) neurophysiological response to change through top-down mechanisms. This explains why the impaired ability to respond to change is a core feature across dementias, and other conditions driven by brain network dysfunction, such as schizophrenia. It validates theoretical frameworks in which neurodegenerating networks upregulate connectivity as partially effective compensation. The significance extends beyond network science and dementia, in its construct validation of dynamic causal modeling (DCM), and human confirmation of frequency-resolved analyses of animal neurodegeneration models.

The Language Network Is Recruited but Not Required for Nonverbal Event Semantics

The ability to combine individual concepts of objects, properties, and actions into complex representations of the world is often associated with language. Yet combinatorial event-level representations can also be constructed from nonverbal input, such as visual scenes. Here, we test whether the language network in the human brain is involved in and necessary for semantic processing of events presented nonverbally. In Experiment 1, we scanned participants with fMRI while they performed a semantic plausibility judgment task versus a difficult perceptual control task on sentences and line drawings that describe/depict simple agent-patient interactions. We found that the language network responded robustly during the semantic task performed on both sentences and pictures (although its response to sentences was stronger). Thus, language regions in healthy adults are engaged during a semantic task performed on pictorial depictions of events. But is this engagement necessary? In Experiment 2, we tested two individuals with global aphasia, who have sustained massive damage to perisylvian language areas and display severe language difficulties, against a group of age-matched control participants. Individuals with aphasia were severely impaired on the task of matching sentences to pictures. However, they performed close to controls in assessing the plausibility of pictorial depictions of agent-patient interactions. Overall, our results indicate that the left frontotemporal language network is recruited but not necessary for semantic processing of nonverbally presented events.

Distinct neural correlates of linguistic demand and non-linguistic demand

In this study, we investigated how the brain responds to task difficulty in linguistic and non-linguistic contexts. This is important for the interpretation of functional imaging studies of neuroplasticity in post-stroke aphasia, because of the inherent difficulty of matching or controlling task difficulty in studies with neurological populations. Twenty neurologically normal individuals were scanned with fMRI as they performed a linguistic task and a non-linguistic task, each of which had two levels of difficulty. Critically, the tasks were matched across domains (linguistic, non-linguistic) for accuracy and reaction time, such that the differences between the easy and difficult conditions were equivalent across domains. We found that non-linguistic demand modulated the same set of multiple demand (MD) regions that have been identified in many prior studies. In contrast, linguistic demand modulated MD regions to a much lesser extent, especially nodes belonging to the dorsal attention network. Linguistic demand modulated a subset of language regions, with the left inferior frontal gyrus most strongly modulated. The right hemisphere region homotopic to Broca's area was also modulated by linguistic but not non-linguistic demand. When linguistic demand was mapped relative to non-linguistic demand, we also observed domain by difficulty interactions in temporal language regions as well as a widespread bilateral semantic network. In sum, linguistic and non-linguistic demand have strikingly different neural correlates. These findings can be used to better interpret studies of patients recovering from aphasia. Some reported activations in these studies may reflect task performance differences, while others can be more confidently attributed to neuroplasticity.

Comprehension of computer code relies primarily on domain-general executive brain regions

Computer programming is a novel cognitive tool that has transformed modern society. What cognitive and neural mechanisms support this skill? Here, we used functional magnetic resonance imaging to investigate two candidate brain systems: the multiple demand (MD) system, typically recruited during math, logic, problem solving, and executive tasks, and the language system, typically recruited during linguistic processing. We examined MD and language system responses to code written in Python, a text-based programming language (Experiment 1) and in ScratchJr, a graphical programming language (Experiment 2); for both, we contrasted responses to code problems with responses to content-matched sentence problems. We found that the MD system exhibited strong bilateral responses to code in both experiments, whereas the language system responded strongly to sentence problems, but weakly or not at all to code problems. Thus, the MD system supports the use of novel cognitive tools even when the input is structurally similar to natural language.

Lack of selectivity for syntax relative to word meanings throughout the language network

To understand what you are reading now, your mind retrieves the meanings of words and constructions from a linguistic knowledge store (lexico-semantic processing) and identifies the relationships among them to construct a complex meaning (syntactic or combinatorial processing). Do these two sets of processes rely on distinct, specialized mechanisms or, rather, share a common pool of resources? Linguistic theorizing, empirical evidence from language acquisition and processing, and computational modeling have jointly painted a picture whereby lexico-semantic and syntactic processing are deeply inter-connected and perhaps not separable. In contrast, many current proposals of the neural architecture of language continue to endorse a view whereby certain brain regions selectively support syntactic/combinatorial processing, although the locus of such "syntactic hub", and its nature, vary across proposals. Here, we searched for selectivity for syntactic over lexico-semantic processing using a powerful individual-subjects fMRI approach across three sentence comprehension paradigms that have been used in prior work to argue for such selectivity: responses to lexico-semantic vs. morpho-syntactic violations (Experiment 1); recovery from neural suppression across pairs of sentences differing in only lexical items vs. only syntactic structure (Experiment 2); and same/different meaning judgments on such sentence pairs (Experiment 3). Across experiments, both lexico-semantic and syntactic conditions elicited robust responses throughout the left fronto-temporal language network. Critically, however, no regions were more strongly engaged by syntactic than lexico-semantic processing, although some regions showed the opposite pattern. Thus, contra many current proposals of the neural architecture of language, syntactic/combinatorial processing is not separable from lexico-semantic processing at the level of brain regions-or even voxel subsets-within the language network, in line with strong integration between these two processes that has been consistently observed in behavioral and computational language research. The results further suggest that the language network may be generally more strongly concerned with meaning than syntactic form, in line with the primary function of language-to share meanings across minds.

Lack of selectivity for syntax relative to word meanings throughout the language network

To understand what you are reading now, your mind retrieves the meanings of words and constructions from a linguistic knowledge store (lexico-semantic processing) and identifies the relationships among them to construct a complex meaning (syntactic or combinatorial processing). Do these two sets of processes rely on distinct, specialized mechanisms or, rather, share a common pool of resources? Linguistic theorizing, empirical evidence from language acquisition and processing, and computational modeling have jointly painted a picture whereby lexico-semantic and syntactic processing are deeply inter-connected and perhaps not separable. In contrast, many current proposals of the neural architecture of language continue to endorse a view whereby certain brain regions selectively support syntactic/combinatorial processing, although the locus of such "syntactic hub", and its nature, vary across proposals. Here, we searched for selectivity for syntactic over lexico-semantic processing using a powerful individual-subjects fMRI approach across three sentence comprehension paradigms that have been used in prior work to argue for such selectivity: responses to lexico-semantic vs. morpho-syntactic violations (Experiment 1); recovery from neural suppression across pairs of sentences differing in only lexical items vs. only syntactic structure (Experiment 2); and same/different meaning judgments on such sentence pairs (Experiment 3). Across experiments, both lexico-semantic and syntactic conditions elicited robust responses throughout the left fronto-temporal language network. Critically, however, no regions were more strongly engaged by syntactic than lexico-semantic processing, although some regions showed the opposite pattern. Thus, contra many current proposals of the neural architecture of language, syntactic/combinatorial processing is not separable from lexico-semantic processing at the level of brain regions-or even voxel subsets-within the language network, in line with strong integration between these two processes that has been consistently observed in behavioral and computational language research. The results further suggest that the language network may be generally more strongly concerned with meaning than syntactic form, in line with the primary function of language-to share meanings across minds.

fMRI reveals language-specific predictive coding during naturalistic sentence comprehension

Much research in cognitive neuroscience supports prediction as a canonical computation of cognition across domains. Is such predictive coding implemented by feedback from higher-order domain-general circuits, or is it locally implemented in domain-specific circuits? What information sources are used to generate these predictions? This study addresses these two questions in the context of language processing. We present fMRI evidence from a naturalistic comprehension paradigm (1) that predictive coding in the brain's response to language is domain-specific, and (2) that these predictions are sensitive both to local word co-occurrence patterns and to hierarchical structure. Using a recently developed continuous-time deconvolutional regression technique that supports data-driven hemodynamic response function discovery from continuous BOLD signal fluctuations in response to naturalistic stimuli, we found effects of prediction measures in the language network but not in the domain-general multiple-demand network, which supports executive control processes and has been previously implicated in language comprehension. Moreover, within the language network, surface-level and structural prediction effects were separable. The predictability effects in the language network were substantial, with the model capturing over 37% of explainable variance on held-out data. These findings indicate that human sentence processing mechanisms generate predictions about upcoming words using cognitive processes that are sensitive to hierarchical structure and specialized for language processing, rather than via feedback from high-level executive control mechanisms.