Neurobiological Mechanisms for Semantic Feature Extraction and Conceptual Flexibility

Signs and symbols relate to concepts and can be used to speak about objects, actions, and their features. Theories of semantic grounding address the question how the latter two, concepts and real‐world entities, come into play and interlink in symbol learning. Here, a neurobiological model is used to spell out concrete mechanisms of symbol grounding, which implicate the “association” of information about sign and referents and, at the same time, the extraction of semantic features and the formation of abstract representations best described as conjoined and disjoined feature sets that may or may not have a real‐life equivalent. The mechanistic semantic circuits carrying these feature sets are not static conceptual entries, but exhibit rich activation dynamics related to memory, prediction, and contextual modulation. Four key issues in specifying these activation dynamics will be highlighted: (a) the inner structure of semantic circuits, (b) mechanisms of semantic priming, (c) task specificity in semantic activation, and (d) context‐dependent semantic circuit activation in the processing of referential, existential, and universal statements. These linguistic‐semantic examples show that specific mechanisms are required to account for context‐dependent semantic function or conceptual “flexibility.” Static context‐independent concepts as such are insufficient to account for these different semantic functions. Whereas abstract amodal models of concepts did so far not spell out concrete mechanisms for context‐dependent semantic function, neuronal assembly mechanisms offer a workable perspective

Composition and Correctness

AbstractThis paper presents an approach to ensure correctness of composed systems. It takes into consideration that correctness can usually be achieved only to a certain degree (except for some small and very mission-critical applications) and complete specifications are usually not practicable. By modelling the parts, the composition activities and the requirements specification we automise the checking procedures using model checking. An important issue hereby is that our approach allows partial modelling and specification

Brain-Language Research: Where is the Progress?

Recent cognitive neuroscience research improved our understanding of where, when, how, and why language circuits emerge and activate in the human brain. Where: Regions crucial for very specific linguistic processes were delineated; phonetic features and fine semantic categories could be mapped onto specific sets of cortical areas. When: Brain correlates of phonological, syntactic and semantic processes were documented early-on, suggesting language understanding in an instant (within 250ms). How: New mechanistic network models mimicking structure and function of left-perisylvian language areas suggest that multimodal action-perception circuits — rather than separate modules for action and perception — carry the processing resources for language use and understanding. Why language circuits emerge in specific areas, become active at specific early time points and are connected in specific ways is best addressed in light of neuroscience principles governing neuronal activation, correlation learning, and, critical-ly, partly predetermined structural information wired into connections between cortical neurons and areas

Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks

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

Nouns, verbs, objects, actions, and abstractions: Local fMRI activity indexes semantics, not lexical categories

Noun/verb dissociations in the literature defy interpretation due to the confound between lexical category and semantic meaning; nouns and verbs typically describe concrete objects and actions. Abstract words, pertaining to neither, are a critical test case: dissociations along lexical-grammatical lines would support models purporting lexical category as the principle governing brain organisation, whilst semantic models predict dissociation between concrete words but not abstract items. During fMRI scanning, participants read orthogonalised word categories of nouns and verbs, with or without concrete, sensorimotor meaning. Analysis of inferior frontal/insula, precentral and central areas revealed an interaction between lexical class and semantic factors with clear category differences between concrete nouns and verbs but not abstract ones. Though the brain stores the combinatorial and lexical-grammatical properties of words, our data show that topographical differences in brain activation, especially in the motor system and inferior frontal cortex, are driven by semantics and not by lexical class

a mismatch negativity study

Complex words can be seen as combinations of elementary units, decomposable into stems and affixes according to morphological rules. Alternatively, complex forms may be stored as single lexical entries and accessed as whole forms. This study uses an event-related potential brain response capable of indexing both whole-form retrieval and combinatorial processing, the Mismatch Negativity (MMN), to investigate early brain activity elicited by morphologically complex derived words in German. We presented complex words consisting of stems “sicher” (secure), or “sauber” (clean) combined with abstract nominalising derivational affixes –heit or –keit, to form either congruent derived words: “Sicherheit” (security) and “Sauberkeit” (cleanliness), or incongruent derived pseudowords: *”Sicherkeit”, and *”Sauberheit”. Using this orthogonal design, it was possible to record brain responses for –heit and –keit in both congruent and incongruent contexts, therefore balancing acoustic variance. Previous research has shown that incongruent combinations of symbols elicit a stronger MMN than congruent combinations, but that single words or constructions stored as whole forms elicit a stronger MMN than pseudowords or non-existent constructions. We found that congruent derived words elicited a stronger MMN than incongruent derived words, about 150 milliseconds after perception of the critical morpheme. This pattern of results is consistent with whole-form storage of morphologically complex derived words as lexical units, or mini-constructions. Using distributed source localisation methods, the MMN enhancement for well-formed derivationally complex words appeared to be most prominent in the left inferior anterior-temporal, bilateral superior parietal and bilateral post- central, supra-marginal areas. In addition, neurophysiological results reflected the frequency of derived forms, thus providing further converging evidence for whole form storage and against a combinatorial mechanism

Congruency of Separable Affix Verb Combinations Is Linearly Indexed by the N400

Separable affix verbs consist of a stem and a derivational affix, which, in some languages can appear together or in discontinuous, distributed form, e.g., German “aufgreifen” and “greifen … auf” [“up-pick(ing)” and “pick … up”]. Certain stems can combine with only certain affixes. However, many such combinations are evaluated not as clearly correct or incorrect, but frequently take an intermediate status with participants rating them ambiguously. Here, we mapped brain responses to combinations of verb stems and affixes realized in short sentences, including more and less common particle verbs, borderline acceptable combinations and clear violations. Event-related potential responses to discontinuous particle verbs were obtained for five affixes re-combined with 10 verb stems, situated within short, German sentences, i.e., “sie en es ,” English: “they it .” The congruity of combinations was assessed both with behavioral ratings of the stimuli and corpus-derived probability measures. The size of a frontal N400 correlated with the degree of incongruency between stem and affix, as assessed by both measures. Behavioral ratings performed better than corpus-derived measures in predicting N400 magnitudes, and a combined model performed best of all. No evidence for a discrete, right/wrong effect was found. We discuss methodological implications and integrate the results into past research on the N400 and neurophysiological studies on separable-affix verbs, generally

Flexibility in Language Action Interaction: The Influence of Movement Type

Recent neuropsychological studies in neurological patients and healthy subjects suggest a close functional relationship between the brain systems for language and action. Facilitation and inhibition effects of motor system activity on language processing have been demonstrated as well as causal effects in the reverse direction, from language processes on motor excitability or performance. However, as the documented effects between motor and language systems were sometimes facilitatory and sometimes inhibitory, the “sign” of these effects still remains to be explained. In a previous study, we reported a word-category-specific differential impairment of verbal working memory for concordant arm- and leg-related action words brought about by complex sequential movements of the hands and feet. In this article, we seek to determine whether the sign of the functional interaction between language and action systems of the human brain can be changed in a predictable manner by changing movement type. We here report that the sign of the effect of motor movement on action word memory can be reversed from interference to facilitation if, instead of complex movement sequences, simple repetitive movements are performed. Specifically, when engaged in finger tapping, subjects were able to remember relatively more arm-related action words (as compared to control conditions), thus documenting an enhancement of working memory brought about by simple hand movements. In contrast, when performing complex sequences of finger movements, an effector-specific degradation of action word memory was found. By manipulating the sign of the effect in accord with theory-driven predictions, these findings provide support for shared neural bases for motor movement and verbal working memory for action-related words and strengthen the argument that motor systems play a causal and functionally relevant role in language processing semantically related to action

Predictive and perceptual phonemic processing in articulatory motor areas: A prediction potential & mismatch negativity study

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.,/bƏ/in the context of expected/pƏ/) pairs elicited weaker post-stimulus MMN-like responses as compared to the articulatory-incongruent (e.g.,/bƏ/in the context of expected/dƏ/) 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

A Role for the Motor System in Binding Abstract Emotional Meaning

Sensorimotor areas activate to action- and object-related words, but their role in abstract meaning processing is still debated. Abstract emotion words denoting body internal states are a critical test case because they lack referential links to objects. If actions expressing emotion are crucial for learning correspondences between word forms and emotions, emotion word–evoked activity should emerge in motor brain systems controlling the face and arms, which typically express emotions. To test this hypothesis, we recruited 18 native speakers and used event-related functional magnetic resonance imaging to compare brain activation evoked by abstract emotion words to that by face- and arm-related action words. In addition to limbic regions, emotion words indeed sparked precentral cortex, including body-part–specific areas activated somatotopically by face words or arm words. Control items, including hash mark strings and animal words, failed to activate precentral areas. We conclude that, similar to their role in action word processing, activation of frontocentral motor systems in the dorsal stream reflects the semantic binding of sign and meaning of abstract words denoting emotions and possibly other body internal states