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How is semantic information stored in the human mind and brain? Some philosophers and cognitive scientists argue for vectorial representations of concepts, where the meaning of a word is represented as its position in a high-dimensional neural state space. At the intersection of natural language processing and artificial intelligence, a class of very successful distributional word vector models has developed that can account for classic EEG findings of language, that is, the ease versus difficulty of integrating a word with its sentence context. However, models of semantics have to account not only for context-based word processing, but should also describe how word meaning is represented. Here, we investigate whether distributional vector representations of word meaning can model brain activity induced by words presented without context. Using EEG activity (event-related brain potentials) collected while participants in two experiments (English and German) read isolated words, we encoded and decoded word vectors taken from the family of prediction-based Word2vec algorithms. We found that, first, the position of a word in vector space allows the prediction of the pattern of corresponding neural activity over time, in particular during a time window of 300 to 500 ms after word onset. Second, distributional models perform better than a human-created taxonomic baseline model (WordNet), and this holds for several distinct vector-based models. Third, multiple latent semantic dimensions of word meaning can be decoded from brain activity. Combined, these results suggest that empiricist, prediction-based vectorial representations of meaning are a viable candidate for the representational architecture of human semantic knowledge.
Despite a large body of research, the linguistic nature of exhaustivity in single wh-questions is unresolved. Moreover, little empirical evidence exists as to which related structures pattern with bare wh-questions regarding exhaustivity. This paper explores the felicity of various exhaustivity violations in unembedded single bare wh-questions in German and compares them to related structures. In two novel felicity judgment experiments, a total of 441 participants rated exhaustive as well as non-exhaustive plural and non-exhaustive singleton answers to wh-questions or statements in a questionnaire. Answers were based on picture stimuli depicting individuals performing various actions. The felicity of non-exhaustive answers was compared across four main test conditions: bare wh-questions (wer ‘who’), wh-questions with a lexical exhaustivity marker (wer alles ‘who all’), plural definite descriptions contained in a restrictive relative clause (e.g., “the people who are fishing in the garden”), and the scalar quantifier “some” (e.g., “some people who are fishing in the garden”).
We employ a novel methodological approach to improve the interpretability of statistical differences between experimental conditions by using the statistical measure of Minimal Important Difference (MID). Our results from estimated MIDs reveal that adults’ felicity judgments of non-exhaustive plural answers to bare wh-questions pattern with those to wer alles-questions and to plural definite descriptions: exhaustivity violations in the bare wh, the wer alles and the plural definite conditions were rated as less felicitous than exhaustivity violations in the some-condition.
Synesthesia is a phenomenon in which additional perceptual experiences are elicited by sensory stimuli or cognitive concepts. Synesthetes possess a unique type of phenomenal experiences not directly triggered by sensory stimulation. Therefore, for better understanding of consciousness it is relevant to identify the mental and physiological processes that subserve synesthetic experience. In the present work we suggest several reasons why synesthesia has merit for research on consciousness. We first review the research on the dynamic and rapidly growing field of the studies of synesthesia. We particularly draw attention to the role of semantics in synesthesia, which is important for establishing synesthetic associations in the brain. We then propose that the interplay between semantics and sensory input in synesthesia can be helpful for the study of the neural correlates of consciousness, especially when making use of ambiguous stimuli for inducing synesthesia. Finally, synesthesia-related alterations of brain networks and functional connectivity can be of merit for the study of consciousness.
Currently, little is known about how synesthesia develops and which aspects of synesthesia can be acquired through a learning process. We review the increasing evidence for the role of semantic representations in the induction of synesthesia, and argue for the thesis that synesthetic abilities are developed and modified by semantic mechanisms. That is, in certain people semantic mechanisms associate concepts with perception-like experiences—and this association occurs in an extraordinary way. This phenomenon can be referred to as “higher” synesthesia or ideasthesia. The present analysis suggests that synesthesia develops during childhood and is being enriched further throughout the synesthetes’ lifetime; for example, the already existing concurrents may be adopted by novel inducers or new concurrents may be formed. For a deeper understanding of the origin and nature of synesthesia we propose to focus future research on two aspects: (i) the similarities between synesthesia and ordinary phenomenal experiences based on concepts; and (ii) the tight entanglement of perception, cognition and the conceptualization of the world. Importantly, an explanation of how biological systems get to generate experiences, synesthetic or not, may have to involve an explanation of how semantic networks are formed in general and what their role is in the ability to be aware of the surrounding world.