ABSTRACT
Prediction has a fundamental role in language processing. However, predictions can be made at different levels, and it is not always clear whether speech sounds, morphemes, words, meanings, or communicative functions are anticipated during dialogues. Previous studies reported specific brain signatures of communicative pragmatic function, in particular enhanced brain responses immediately after encountering an utterance used to request an object from a partner, but relatively smaller ones when the same utterance was used for naming the object. The present experiment now investigates whether similar neuropragmatic signatures emerge in recipients before the onset of upcoming utterances carrying different predictable communicative functions. Trials started with a context question and object pictures displayed on the screen, raising the participant's expectation that words from a specific semantic category (food or tool) would subsequently be used to either name or request one of the objects. Already 600 msec before utterance onset, a larger prediction potential was observed when a request was anticipated relative to naming expectation. As this result is congruent with the neurophysiological difference previously observed right after the critical utterance, the anticipatory brain activity may index predictions about the social-communicative function of upcoming utterances. In addition, we also found that the predictable semantic category of the upcoming word was likewise reflected in the anticipatory brain potential. Thus, the neurophysiological characteristics of the prediction potential can capture different types of upcoming linguistic information, including semantic and pragmatic aspects of an upcoming utterance and communicative action.
Subject(s)
Brain , Communication , Electroencephalography , Semantics , Humans , Male , Female , Adult , Young Adult , Brain/physiology , Evoked Potentials/physiology , Language , Speech/physiology , Anticipation, Psychological/physiology , Reaction Time/physiologyABSTRACT
Processing action words (e.g., fork, throw) engages neurocognitive motor representations, consistent with embodied cognition principles. Despite age-related neurocognitive changes that could affect action words, and a rapidly aging population, the impact of healthy aging on action-word processing is poorly understood. Previous research suggests that in lexical tasks demanding semantic access, such as picture naming, higher motor-relatedness can enhance performance (e.g., fork vs. pier)-particularly in older adults, perhaps due to the age-related relative sparing of motor-semantic circuitry, which can support action words. However, motor-relatedness was recently found to affect performance in younger but not older adults in lexical decision. We hypothesized this was due to decreased semantic access in this task, especially in older adults. Here we tested effects of motor-relatedness on 2,174 words in younger and older adults not only in lexical decision but also in reading aloud, in which semantic access is minimal. Mixed-effects regression, controlling for phonological, lexical, and semantic variables, yielded results consistent with our predictions. In lexical decision, younger adults were faster and more accurate at words with higher-motor relatedness, whereas older adults showed no motor-relatedness effects. In reading aloud, neither age group showed such effects. Multiple sensitivity analyses demonstrated that the patterns were robust. Altogether, whereas previous research indicates that in lexical tasks demanding semantic access, higher motor-relatedness can enhance performance, especially in older adults, evidence now suggests that such effects are attenuated with decreased semantic access, which in turn depends on the task as well as aging itself. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Subject(s)
Aging , Cognition , Reading , Semantics , Humans , Aged , Aging/physiology , Aging/psychology , Male , Female , Adult , Young Adult , Cognition/physiology , Middle Aged , Reaction Time/physiology , Aged, 80 and over , Decision Making/physiology , AdolescentABSTRACT
Neural circuits related to language exhibit a remarkable ability to reorganize and adapt in response to visual deprivation. Particularly, early and late blindness induce distinct neuroplastic changes in the visual cortex, repurposing it for language and semantic processing. Interestingly, these functional changes provoke a unique cognitive advantage - enhanced verbal working memory, particularly in early blindness. Yet, the underlying neuromechanisms and the impact on language and memory-related circuits remain not fully understood. Here, we applied a brain-constrained neural network mimicking the structural and functional features of the frontotemporal-occipital cortices, to model conceptual acquisition in early and late blindness. The results revealed differential expansion of conceptual-related neural circuits into deprived visual areas depending on the timing of visual loss, which is most prominent in early blindness. This neural recruitment is fundamentally governed by the biological principles of neural circuit expansion and the absence of uncorrelated sensory input. Critically, the degree of these changes is constrained by the availability of neural matter previously allocated to visual experiences, as in the case of late blindness. Moreover, we shed light on the implication of visual deprivation on the neural underpinnings of verbal working memory, revealing longer reverberatory neural activity in 'blind models' as compared to the sighted ones. These findings provide a better understanding of the interplay between visual deprivations, neuroplasticity, language processing and verbal working memory.
Subject(s)
Language , Memory, Short-Term , Humans , Memory, Short-Term/physiology , Blindness , Brain , Occipital LobeABSTRACT
Language influences cognitive and conceptual processing, but the mechanisms through which such causal effects are realized in the human brain remain unknown. Here, we use a brain-constrained deep neural network model of category formation and symbol learning and analyze the emergent model's internal mechanisms at the neural circuit level. In one set of simulations, the network was presented with similar patterns of neural activity indexing instances of objects and actions belonging to the same categories. Biologically realistic Hebbian learning led to the formation of instance-specific neurons distributed across multiple areas of the network, and, in addition, to cell assembly circuits of "shared" neurons responding to all category instances-the network correlates of conceptual categories. In two separate sets of simulations, the network learned the same patterns together with symbols for individual instances ["proper names" (PN)] or symbols related to classes of instances sharing common features ["category terms" (CT)]. Learning CT remarkably increased the number of shared neurons in the network, thereby making category representations more robust while reducing the number of neurons of instance-specific ones. In contrast, proper name learning prevented a substantial reduction of instance-specific neurons and blocked the overgrowth of category general cells. Representational similarity analysis further confirmed that the neural activity patterns of category instances became more similar to each other after category-term learning, relative to both learning with PN and without any symbols. These network-based mechanisms for concepts, PN, and CT explain why and how symbol learning changes object perception and memory, as revealed by experimental studies.
Subject(s)
Brain , Learning , Humans , Learning/physiology , Brain/physiology , Neural Networks, Computer , Language , LinguisticsABSTRACT
Sentence fragments strongly predicting a specific subsequent meaningful word elicit larger preword slow waves, prediction potentials (PPs), than unpredictive contexts. To test the current predictive processing models, 128-channel EEG data were collected from both sexes to examine whether (1) different semantic PPs are elicited in language comprehension and production and (2) whether these PPs originate from the same specific "prediction area(s)" or rather from widely distributed category-specific neuronal circuits reflecting the meaning of the predicted item. Slow waves larger after predictable than unpredictable contexts were present both before subjects heard the sentence-final word in the comprehension experiment and before they pronounced the sentence-final word in the production experiment. Crucially, cortical sources underlying the semantic PP were distributed across several cortical areas and differed between the semantic categories of the expected words. In both production and comprehension, the anticipation of animal words was reflected by sources in posterior visual areas, whereas predictable tool words were preceded by sources in the frontocentral sensorimotor cortex. For both modalities, PP size increased with higher cloze probability, thus further confirming that it reflects semantic prediction, and with shorter latencies with which participants completed sentence fragments. These results sit well with theories viewing distributed semantic category-specific circuits as the mechanistic basis of semantic prediction in the two modalities.
Subject(s)
Semantics , Sensorimotor Cortex , Male , Female , Humans , Comprehension/physiology , Language , Reading , ElectroencephalographyABSTRACT
Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the structure and function of real brains. Brain-constrained networks differ from classic neural networks by implementing brain similarities at different scales, ranging from the micro- and mesoscopic levels of neuronal function, local neuronal links and circuit interaction to large-scale anatomical structure and between-area connectivity. This review shows how brain-constrained neural networks can be applied to study in silico the formation of mechanisms for symbol and concept processing and to work towards neurobiological explanations of specifically human cognitive abilities. These include verbal working memory and learning of large vocabularies of symbols, semantic binding carried by specific areas of cortex, attention focusing and modulation driven by symbol type, and the acquisition of concrete and abstract concepts partly influenced by symbols. Neuronal assembly activity in the networks is analyzed to deliver putative mechanistic correlates of higher cognitive processes and to develop candidate explanations founded in established neurobiological principles.
Subject(s)
Brain , Language , Humans , Brain/physiology , Learning/physiology , Neural Networks, Computer , Memory, Short-TermABSTRACT
In communication, much information is conveyed not explicitly but rather covertly, based on shared assumptions and common knowledge. For instance, when asked "Did you bring your cat to the vet?" a person could reply "It got hurt jumping down the table", thereby implicating that, indeed, the cat was brought to the vet. The assumption that getting hurt jumping down a table motivates a vet visit is tacitly attributed to the speaker by the listener, which implies Theory of Mind (ToM) processes. In the present study, we apply repetitive transcranial magnetic stimulation to the right temporo-parietal junction (rTPJ), a key brain region underlying ToM, with the aim to disrupt ToM processes necessary for language understanding. We then assess effects on the comprehension of indirect speech acts and their matched direct controls. In one set of conditions, the direct and indirect stimuli where not matched for speech act type, whereas, in the other, these were matched, therefore providing an unconfounded test case for in/directness. When indirect speech acts and direct controls were matched for speech act type (both statements), the indirect ones took longer to process both following sham and verum TMS. However, when the indirect and direct speech acts were not matched for communicative function (accept/decline offer vs. descriptive statement respectively), then a delay was detected for the indirect ones following sham TMS but, crucially, not following verum TMS. Additionally, TMS affected behavior in a ToM task. We therefore do not find evidence that the rTPJ is causally involved in comprehending of indirectness per se, but conclude that it could be involved instead in the processing of specific social communicative activity of rejecting of accepting offers, or to a combination of differing in/directness and communicative function. Our findings are consistent with the view that ToM processing in rTPJ is more important and/or more pronounced for offer acceptance/rejection than for descriptive answers.
Subject(s)
Theory of Mind , Transcranial Magnetic Stimulation , Humans , Speech , Brain/physiology , Comprehension/physiology , Communication , Theory of Mind/physiologyABSTRACT
Although teaching animals a few meaningful signs is usually time-consuming, children acquire words easily after only a few exposures, a phenomenon termed "fast-mapping." Meanwhile, most neural network learning algorithms fail to achieve reliable information storage quickly, raising the question of whether a mechanistic explanation of fast-mapping is possible. Here, we applied brain-constrained neural models mimicking fronto-temporal-occipital regions to simulate key features of semantic associative learning. We compared networks (i) with prior encounters with phonological and conceptual knowledge, as claimed by fast-mapping theory, and (ii) without such prior knowledge. Fast-mapping simulations showed word-specific representations to emerge quickly after 1-10 learning events, whereas direct word learning showed word-meaning mappings only after 40-100 events. Furthermore, hub regions appeared to be essential for fast-mapping, and attention facilitated it, but was not strictly necessary. These findings provide a better understanding of the critical mechanisms underlying the human brain's unique ability to acquire new words rapidly.
Subject(s)
Brain , Semantics , Child , Humans , Linguistics , Brain Mapping , Occipital LobeABSTRACT
A neurobiologically constrained model of semantic learning in the human brain was used to simulate the acquisition of concrete and abstract concepts, either with or without verbal labels. Concept acquisition and semantic learning were simulated using Hebbian learning mechanisms. We measured the network's category learning performance, defined as the extent to which it successfully (i) grouped partly overlapping perceptual instances into a single (abstract or concrete) conceptual representation, while (ii) still distinguishing representations for distinct concepts. Co-presence of linguistic labels with perceptual instances of a given concept generally improved the network's learning of categories, with a significantly larger beneficial effect for abstract than concrete concepts. These results offer a neurobiological explanation for causal effects of language structure on concept formation and on perceptuo-motor processing of instances of these concepts: supplying a verbal label during concept acquisition improves the cortical mechanisms by which experiences with objects and actions along with the learning of words lead to the formation of neuronal ensembles for specific concepts and meanings. Furthermore, the present results make a novel prediction, namely, that such 'Whorfian' effects should be modulated by the concreteness/abstractness of the semantic categories being acquired, with language labels supporting the learning of abstract concepts more than that of concrete ones. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.
Subject(s)
Concept Formation , Language , Humans , Concept Formation/physiology , Brain/physiology , Learning , Semantics , PerceptionABSTRACT
This study explored the feasibility and effectiveness of a short-term (10-week) intervention trial using Donepezil administered alone and combined with intensive language action therapy (ILAT) for the treatment of apathy and depression in ten people with chronic post-stroke aphasia. Outcome measures were the Western Aphasia Battery and the Stroke Aphasia Depression Questionnaire-21. Structural magnetic resonance imaging and 18fluorodeoxyglucose positron emission tomography were acquired at baseline and after two endpoints (Donepezil alone and Donepezil-ILAT). The intervention was found to be feasible to implement. Large treatment effects were found. Donepezil alone and combined with ILAT reduced aphasia severity, while apathy and depression only improved with Donepezil-ILAT. Structural and functional neuroimaging data did not show conclusive results but provide hints for future research. Given these overall positive findings on feasibility, language and behavioral benefits, further studies in larger sample sizes and including a placebo-control group are indicated.
Subject(s)
Apathy , Aphasia , Humans , Aphasia/drug therapy , Aphasia/etiology , Depression/drug therapy , Depression/etiology , Donepezil/therapeutic use , Feasibility Studies , Language , Language Therapy/methods , Treatment OutcomeABSTRACT
Understanding language semantically related to actions activates the motor cortex. This activation is sensitive to semantic information such as the body part used to perform the action (e.g. arm-/leg-related action words). Additionally, motor movements of the hands/feet can have a causal effect on memory maintenance of action words, suggesting that the involvement of motor systems extends to working memory. This study examined brain correlates of verbal memory load for action-related words using event-related fMRI. Seventeen participants saw either four identical or four different words from the same category (arm-/leg-related action words) then performed a nonmatching-to-sample task. Results show that verbal memory maintenance in the high-load condition produced greater activation in left premotor and supplementary motor cortex, along with posterior-parietal areas, indicating that verbal memory circuits for action-related words include the cortical action system. Somatotopic memory load effects of arm- and leg-related words were observed, but only at more anterior cortical regions than was found in earlier studies employing passive reading tasks. These findings support a neurocomputational model of distributed action-perception circuits (APCs), according to which language understanding is manifest as full ignition of APCs, whereas working memory is realized as reverberant activity receding to multimodal prefrontal and lateral temporal areas.
Subject(s)
Magnetic Resonance Imaging , Motor Cortex , Brain/diagnostic imaging , Brain/physiology , Brain Mapping , Humans , Language , Magnetic Resonance Imaging/methods , Memory, Short-Term , Motor Cortex/diagnostic imaging , Motor Cortex/physiologyABSTRACT
The recent finding of predictive brain signals preceding anticipated perceptual and linguistic stimuli opens new questions for experimental research. Here, we address the possible brain basis of phonological predictions regarding the features of specific speech sounds and their relationship to phonological priming. To this end, we recorded EEG correlates of both pre- and post-stimulus brain responses in a phonological priming study. Redundant spoken sounds induced stimulus expectations, which manifested as a slow-wave anticipatory activity (the Prediction Potential, PP), whereas articulatory-congruent (e.g.,/bÆ/in the context of expected/pÆ/) pairs elicited weaker post-stimulus MMN-like responses as compared to the articulatory-incongruent (e.g.,/bÆ/in the context of expected/dÆ/) pairs, a pattern reminiscent of perceptual priming mediated by articulatory-motor areas. Source analysis reveal clusters of activation in lateral prefrontal, temporal and ventral motor areas, thus providing the proof of the relevance of multimodal representation units subserving predictive and perceptual phonemic processing.
Subject(s)
Motor Cortex , Speech Perception , Acoustic Stimulation , Brain/physiology , Electroencephalography , Humans , Phonetics , Speech Perception/physiologyABSTRACT
During conversations, speech prosody provides important clues about the speaker's communicative intentions. In many languages, a rising vocal pitch at the end of a sentence typically expresses a question function, whereas a falling pitch suggests a statement. Here, the neurophysiological basis of intonation and speech act understanding were investigated with high-density electroencephalography (EEG) to determine whether prosodic features are reflected at the neurophysiological level. Already approximately 100 ms after the sentence-final word differing in prosody, questions, and statements expressed with the same sentences led to different neurophysiological activity recorded in the event-related potential. Interestingly, low-pass filtered sentences and acoustically matched nonvocal musical signals failed to show any neurophysiological dissociations, thus suggesting that the physical intonation alone cannot explain this modulation. Our results show rapid neurophysiological indexes of prosodic communicative information processing that emerge only when pragmatic and lexico-semantic information are fully expressed. The early enhancement of question-related activity compared with statements was due to sources in the articulatory-motor region, which may reflect the richer action knowledge immanent to questions, namely the expectation of the partner action of answering the question. The present findings demonstrate a neurophysiological correlate of prosodic communicative information processing, which enables humans to rapidly detect and understand speaker intentions in linguistic interactions.
Subject(s)
Speech Perception , Speech , Humans , Speech Perception/physiology , Evoked Potentials/physiology , Electroencephalography/methods , LinguisticsABSTRACT
Humans share the ability to intuitively map 'sharp' or 'round' pseudowords, such as 'bouba' versus 'kiki', to abstract edgy versus round shapes, respectively. This effect, known as sound symbolism, appears early in human development. The phylogenetic origin of this phenomenon, however, is unclear: are humans the only species capable of experiencing correspondences between speech sounds and shapes, or could similar effects be observed in other animals? Thus far, evidence from an implicit matching experiment failed to find evidence of this sound symbolic matching in great apes, suggesting its human uniqueness. However, explicit tests of sound symbolism have never been conducted with nonhuman great apes. In the present study, a language-competent bonobo completed a cross-modal matching-to-sample task in which he was asked to match spoken English words to pictures, as well as 'sharp' or 'round' pseudowords to shapes. Sound symbolic trials were interspersed among English words. The bonobo matched English words to pictures with high accuracy, but did not show any evidence of spontaneous sound symbolic matching. Our results suggest that speech exposure/comprehension alone cannot explain sound symbolism. This lends plausibility to the hypothesis that biological differences between human and nonhuman primates could account for the putative human specificity of this effect.
Subject(s)
Hominidae , Language , Animals , Male , Pan paniscus , Phonetics , Phylogeny , SpeechABSTRACT
A neurobiologically constrained deep neural network mimicking cortical area function relevant for sensorimotor, linguistic and conceptual processing was used to investigate the putative biological mechanisms underlying conceptual category formation and semantic feature extraction. Networks were trained to learn neural patterns representing specific objects and actions relevant to semantically 'ground' concrete and abstract concepts. Grounding sets consisted of three grounding patterns with neurons representing specific perceptual or action-related features; neurons were either unique to one pattern or shared between patterns of the same set. Concrete categories were modelled as pattern triplets overlapping in their 'shared neurons', thus implementing semantic feature sharing of all instances of a category. In contrast, abstract concepts had partially shared feature neurons common to only pairs of category instances, thus, exhibiting family resemblance, but lacking full feature overlap. Stimulation with concrete and abstract conceptual patterns and biologically realistic unsupervised learning caused formation of strongly connected cell assemblies (CAs) specific to individual grounding patterns, whose neurons were spread out across all areas of the deep network. After learning, the shared neurons of the instances of concrete concepts were more prominent in central areas when compared with peripheral sensorimotor ones, whereas for abstract concepts the converse pattern of results was observed, with central areas exhibiting relatively fewer neurons shared between pairs of category members. We interpret these results in light of the current knowledge about the relative difficulty children show when learning abstract words. Implications for future neurocomputational modelling experiments as well as neurobiological theories of semantic representation are discussed.
Subject(s)
Brain , Concept Formation , Child , Humans , Concept Formation/physiology , Brain/physiology , Semantics , Neural Networks, Computer , KnowledgeABSTRACT
Introduction: Depressive symptoms are a major drawback of aphasia, negatively impacting on functional outcomes. In a previous study, Intensive Language-Action Therapy (ILAT) was effective in improving depression and low mood in persons with chronic non-fluent aphasia. We present a proof-of-concept case-control study that evaluates language and mood outcomes amongst persons with fluent post-stroke aphasia.Participants: Thirteen Spanish speaking persons with fluent aphasia due to chronic stroke lesions in the left hemisphere participated in the study.Intervention: Five participants (intervention group) received ILAT for 3 h/day during two consecutive weeks, for an overall of 30 h, and 8 participants (control group) entered a waiting-list no-treatment arm.Results: The main finding was that participants receiving active treatment showed significant improvements on depression and aphasia severity scores, whereas no significant changes were found in the control group.Conclusions: The implementation of ILAT was efficient in improving clinical language deficits in people with fluent aphasia and contributes to improvement in mood after therapy.Trial registration: EUDRACT (2008-008481-12).
Subject(s)
Aphasia , Stroke Rehabilitation , Aphasia/etiology , Case-Control Studies , Humans , Language Therapy , Speech TherapyABSTRACT
This study seeks to confirm whether lesions in posterior regions of the brain involved in visuo-spatial processing are of functional relevance to the processing of words with spatial meaning. We investigated whether patients with Posterior Cortical Atrophy (PCA), an atypical form of Alzheimer's Disease which predominantly affects parieto-occipital brain regions, is associated with deficits in working memory for spatial prepositions. Case series of patients with PCA and matched healthy controls performed tests of immediate and delayed serial recall on words from three lexico-semantic word categories: number words (twelve), spatial prepositions (behind) and function words (e.g., shall). The three word categories were closely matched for a number of psycholinguistic and semantic variables including length, bi-/tri-gram frequency, word frequency, valence and arousal. Relative to controls, memory performance of PCA patients on short word lists was significantly impaired on spatial prepositions in the delayed serial recall task. These results suggest that lesions in posterior parieto-occipital regions specifically impair the processing of spatial prepositions. Our findings point to a pertinent role of posterior cortical regions in the semantic processing of words with spatial meaning and provide strong support for modality-specific semantic theories that recognize the necessary contributions of sensorimotor regions to conceptual semantic processing.
ABSTRACT
Brain tumors cause local structural impairments of the cerebral network. Moreover, brain tumors can also affect functional brain networks more distant from the lesion. In this study, we analyzed the impact of glioma WHO grade II-IV tumors on grey and white matter in relation to impaired language function. In a retrospective analysis of 60 patients, 14 aphasic and 46 non-aphasic, voxel-based lesion-symptom mapping (VLSM) was used to identify tumor induced lesions in grey (GM) and white matter (WM) related to patients' performance in subtests of the Aachen Aphasia Test (AAT). Significant clusters were analyzed for atlas-based grey and white matter involvements in relation to different linguistic modalities. VLSM analysis indicated significant contribution of a posterior perisylvian cluster covering WM and GM to AAT performance averaged across subtests. When considering individual AAT subtests, a substantial overlap between significant clusters for analysis of the token test, picture naming and language comprehension results could be observed. The WM-cluster intersections reflect the overall importance of the perisylvian area in language function, similarly to GM participations. Especially the constant high percentages of Heschl's gyrus, superior temporal gyrus, inferior longitudinal and middle longitudinal fascicles, but also arcuate and inferior fronto-occipital fascicles highlight the importance of the posterior perisylvian area for language function.