Papers by Friedemann Pulvermuller
The project repository journal, Nov 22, 2023
Developing neural networks to unlock the secrets of human cognition.
There has been a long debate in the literature of semantics between the arbitrariness of language... more There has been a long debate in the literature of semantics between the arbitrariness of language proposed by Saussure (1959) and the non-arbitrary associations, known as sound symbolism. Sound symbolism is a form of iconicity based on similarity between a linguistic form and the sensory-motor properties of its referent . A classic example of sound symbolism is the sound-shape correspondence, as described by , where the non-word "maluma" was judged to be a good match with a round shape whereas the non-word "takete" matched better to a spiky shape. Recent theories have highlighted the relevant role of sound symbolism and that of iconicity for the evolution of language (
Scientific Reports, Sep 3, 2019
Philosophical Transactions of the Royal Society B, Jun 18, 2018
How can we understand causal relationships and how can we understand words such as 'cause'? Some ... more How can we understand causal relationships and how can we understand words such as 'cause'? Some theorists assume that the underlying abstract concept is given to us, and that perceptual correlation provides the relevant hints towards inferring causation from perceived real-life events. A different approach emphasizes the role of actions and their typical consequences for the emergence of the concept of causation and the application of the related term. A model of causation is proposed that highlights the family resemblance between causal actions and postulates that symbols are necessary for binding together the different partially shared semantic features of subsets of causal actions and their goals. Linguistic symbols are proposed to play a key role in binding the different subsets of semantic features of the abstract concept. The model is spelt out at the neuromechanistic level of distributed cortical circuits and the cognitive functions they carry. The model is discussed in light of behavioural and neuroscience evidence, and questions for future research are highlighted. In sum, taking causation as a concrete example, I argue that abstract concepts and words can be learnt and grounded in real-life interaction, and that the neurobiological mechanisms realizing such abstract semantic grounding are within our grasp. This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.
Scientific Reports, Jul 29, 2020
Sound symbolism, the surprising semantic relationship between meaningless pseudowords (e.g., 'mal... more Sound symbolism, the surprising semantic relationship between meaningless pseudowords (e.g., 'maluma', 'takete') and abstract (round vs. sharp) shapes, is a hitherto unexplained human-specific knowledge domain. Here we explore whether abstract sound symbolic links can be explained by those between the sounds and shapes of bodily actions. To this end, we asked human subjects to match pseudowords with abstract shapes and, in a different experimental block, the sounds of actions with the shapes of the trajectories of the actions causing these same sounds. Crucially, both conditions were also crossed. Our findings reveal concordant matching in the sound symbolic and action domains, and, importantly, significant correlations between them. We conclude that the sound symbolic knowledge interlinking speech sounds and abstract shapes is explained by audiovisual information immanent to action experience along with acoustic similarities between speech and action sounds. These results demonstrate a fundamental role of action knowledge for abstract sound symbolism, which may have been key to human symbol-manipulation ability. Sound symbolism is an umbrella term that covers the non-arbitrary associations between meaningless speech sounds and sensory or other meanings 1 (for a review see 2 ). The iconic links between pseudowords and abstract visual shapes is the most popular demonstration of this phenomenon. In the present study, the term "sound symbolism" will refer to these latter associations. In his seminal book entitled "Gestalt Psychology", Köhler 3 described the classic "maluma-takete" paradigm in which humans match a round figure to a 'round' sounding pseudoword, such as "maluma", and a sharp figure to a 'sharp' sounding pseudoword such as "takete", thus presupposing an abstract 'resemblance' between the otherwise meaningless symbol (pseudoword) and the corresponding shape, possibly based on shared modality general abstract properties. Many experimental studies confirmed Köhler's example and demonstrated the postulated iconic speech-sound/meaning mappings across languages 4-6 , even at early age (for a meta-analysis see 7 ) and across stimulus modalities . Furthermore, the ability to perform well on sound symbolic tasks has been related to word learning capacity in young children . These results led to some skepticism towards the linguistic Saussurean 13 position that the relationship between form and meaning of signs is arbitrary and even suggest an important role of sound symbolic mechanisms in language development 14 and evolution 15 . Specifically, vocal iconic mappings between infants' first spoken words and the referents these words are used to speak about appear to be substantial, so that iconic signs may have a special status for our ability to talk about things not present in the environment, a feature sometimes called 'displacement in communication' 6 . Today, iconicity and sound symbolism along with their bootstrapping role in language development and evolution are widely upon agreement 15 , with recent evidence coming from a study in great apes showing the human specificity of sound symbolic mappings. Margiotoudi et al. tested humans and great apes in the same two-alternative forced choice (2AFC) task. Both species were presented with different 'round' versus 'sharp' sounding pseudowords and were required to select a (round vs. sharp) shape that best matched the pseudoword. Humans but not great apes showed significant congruency effects. These results suggest that, similar to language, sound symbolism is a human-specific trait. It has also been argued that sound symbolism may depend on human-specific neuroanatomical connectivity also relevant for language , in particular on the presence of strong long-distance connection between frontal and temporal perisylvian areas . Despite the numerous studies documenting sound symbolism, few theories attempt to explain the underlying mechanism. Sound symbolism may be considered as a specific type of crossmodal correspondence implicating the matching of shared sensory or semantic features across modalities . In this spirit, the frequency code theory proposed by Ohala 20 states that the association of large (small) objects with segments of low (high) frequency,
A realistic model of language should specify the mechanisms underlying language use and comprehen... more A realistic model of language should specify the mechanisms underlying language use and comprehension. A neurobiological approach has been shown to be an effective means toward this end. The Neuroscience of Language provides results of brain activation studies, patients with brain lesions, and hints from computer simulations of neural networks to help answer the question: How is language organized in the human brain? At the book's core are neuronal mechanisms that is, the nerve cell wiring of language in the brain. Neuronal models of word and serialorder processing are presented in the form of a computational and connectionist neural network. The linguistic emphasis is on words and elementary syntactic rules. The book introduces basic knowledge from disciplines relevant in the cognitive neuroscience of language. Introductory chapters focus on neuronal structure and function, cognitive brain processes, the basics of classical aphasia research and modern neuroimaging of language, neural network approaches to language, and the basics of syntactic theories. The essence of the work is contained in chapters on neural algorithms and networks, basic syntax, serial-order mechanisms, and neuronal grammar. Throughout, excursuses illustrate the functioning of brain models of language, some of which are simulations accessible as animations on the book's accompanying web site. This self-contained text and reference puts forth the first systematic model of language at a neuronal level that is attractive to language theorists but that is also well grounded in empirical research.
Psychological Research-psychologische Forschung, Feb 14, 2022
In the original publication of the article, there was a mistake in Eq. ( ) in the Appendix. In li... more In the original publication of the article, there was a mistake in Eq. ( ) in the Appendix. In lines 2 and 3 of the equation, it should read V(j,t) instead of V(y,t). Furthermore, several minor corrections to the text were made. The original article has been corrected.
Psychological Research-psychologische Forschung, Nov 11, 2021
A neurobiologically constrained deep neural network mimicking cortical areas relevant for sensori... more A neurobiologically constrained deep neural network mimicking cortical areas 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.
Proceedings of the Royal Society B: Biological Sciences
Humans share the ability to intuitively map ‘sharp’ or ‘round’ pseudowords, such as ‘bouba’ versu... more 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 bonob...
Proceedings of the 12th International Conference on the Evolution of Language (Evolang12), 2018
There has been a long debate in the literature of semantics between the arbitrariness of language... more There has been a long debate in the literature of semantics between the arbitrariness of language proposed by Saussure (1959) and the non-arbitrary associations, known as sound symbolism. Sound symbolism is a form of iconicity based on similarity between a linguistic form and the sensory-motor properties of its referent . A classic example of sound symbolism is the sound-shape correspondence, as described by , where the non-word "maluma" was judged to be a good match with a round shape whereas the non-word "takete" matched better to a spiky shape. Recent theories have highlighted the relevant role of sound symbolism and that of iconicity for the evolution of language (
Topics in Cognitive Science, 2018
Signs and symbols relate to concepts and can be used to speak about objects, actions, and their f... more 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 s...
Philosophical Transactions of the Royal Society B: Biological Sciences, 2018
How can we understand causal relationships and how can we understand words such as ‘cause’? Some ... more How can we understand causal relationships and how can we understand words such as ‘cause’? Some theorists assume that the underlying abstract concept is given to us, and that perceptual correlation provides the relevant hints towards inferring causation from perceived real-life events. A different approach emphasizes the role of actions and their typical consequences for the emergence of the concept of causation and the application of the related term. A model of causation is proposed that highlights the family resemblance between causal actions and postulates that symbols are necessary for binding together the different partially shared semantic features of subsets of causal actions and their goals. Linguistic symbols are proposed to play a key role in binding the different subsets of semantic features of the abstract concept. The model is spelt out at the neuromechanistic level of distributed cortical circuits and the cognitive functions they carry. The model is discussed in ligh...
Progress in Neurobiology, 2017
Neuroanatomical structure specific to humans and neural plasticity driven by correlation predicts... more Neuroanatomical structure specific to humans and neural plasticity driven by correlation predicts the formation of circuits binding together information about actions and perceptions. These action perception circuits provide mechanisms for working memory, intention and prediction, attention, and combination, including abstract rule formation. The review discusses results indicating that (1) Action perception circuits for language sounds and spoken word forms differ in their cortical distribution depending on phonological properties (e.g., place of articulation). (2) Semantic symbol types are supported by cortical circuits with different topographies reaching into sensory and motor systems. (3) Linguistic actions in communicative context exploit action sequence structure representations, The current debate about the role of mirror neurons and conceptual grounding in human cognition is critically assessed.
Encyclopedia of Neuroscience, 2009
Connectionist psycholinguistics is an emerging approach to modeling empirical data on human langu... more Connectionist psycholinguistics is an emerging approach to modeling empirical data on human language processing using connectionist computational architectures. This article reviews progress made in the area of connectionist syntactic processing. Constituency, structure dependency, and recursion are notions central to traditional generative theories of language and are seen as the hallmark of symbolic processing. Because connectionist models are subsymbolic and their knowledge emerges from large distributed activation of neuronlike units, their ability to learn and process aspects of syntax represents an important alternative paradigm in cognitive science. They also invite one to rethink traditional notions such as the competence–performance distinction and boundless recursion.
Trends in Cognitive Sciences, 2001
164 Cognitive Neuroscience Society left hemisphere than right hemisphere, just as low familiarity... more 164 Cognitive Neuroscience Society left hemisphere than right hemisphere, just as low familiarity words were more accurately processed by the left hemisphere. These ndings t the assumption that the left hemisphere shifts to phonological processing as words become more challenging, and provide new evidence that laterality and the effect of hemispheric interaction are subject to context effects.
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How long does it take the human mind to grasp the idea when hearing or reading a sentence? Neurop... more How long does it take the human mind to grasp the idea when hearing or reading a sentence? Neurophysiological methods looking directly at the time course of brain activity indexes of comprehension are critical for finding the answer to this question. As the dominant cognitive approaches, models of serial/cascaded and parallel processing, make conflicting predictions on the time course of psycholinguistic information access, they can be tested using neurophysiological brain activation recorded in MEG and EEG experiments. Seriality and cascading of lexical, semantic and syntactic processes receives support from late (latency ~1/2s) sequential neurophysiological responses, especially N400 and P600. However, parallelism is substantiated by early near-simultaneous brain indexes of a range of psycholinguistic processes, up to the level of semantic access and context integration, emerging already 100-250 ms after critical stimulus information is present. Crucially, however, there are reliable latency differences of 20-50 ms between early cortical area activations reflecting lexical, semantic and syntactic processes, which are left unexplained by current serial and parallel brain models of language. We here offer a mechanistic model grounded in cortical nerve cell circuits that builds upon neuroanatomical and neurophysiological knowledge and explains both near-simultaneous activations and finegrained delays. A key concept is that of discrete distributed cortical circuits with specific inter-area topographies. The full activation, or ignition, of specifically distributed binding circuits explains the near-simultaneity of early neurophysiological indexes of lexical, syntactic and semantic processing. Activity spreading within circuits determined by between-area conduction delays accounts for comprehension-related regional activation differences in the millisecond range.
Theory in Biosciences, 2003
Grammar processing may build upon serial-order mechanisms known from non-human species. A circuit... more Grammar processing may build upon serial-order mechanisms known from non-human species. A circuit similar to that underlying direction-sensitive movement detection in arthropods and vertebrates may become selective for sequences of words, thus yielding grammatical sequence detectors in the human brain. Sensitivity to the order of neuronal events arises from unequal connection strengths between two input units and a third element, the sequence detector. This mechanism, which critically depends on the dynamics of the input units, can operate at the single neuron level and may be relevant at the level of neuronal ensembles as well. Due to the repeated occurrence of sequences, for example word strings, the sequence-sensitive elements become more firmly established and, by substitution of elements between strings, a process called auto-associative substitution learning (AASL) is triggered. AASL links the neuronal counterparts of the string elements involved in the substitution process to the sequence detector, thereby providing a brain basis of what can be described linguistically as the generalization of rules of grammar. A network of sequence detectors may constitute grammar circuits in the human cortex on which a separate set of mechanisms establishing temporary binding and recursion can operate.
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Papers by Friedemann Pulvermuller