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  • Publication . Article . 2022 . Embargo End Date: 16 Nov 2022
    Open Access English
    Authors: 
    Harm Brouwer; Matthew W. Crocker; Noortje J. Venhuizen; John Hoeks;
    Publisher: Universität des Saarlandes
    Project: EC | LANPERCEPT (316748)

    Abstract Ten years ago, researchers using event‐related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a Semantic Illusion: Semantically anomalous, but structurally well‐formed sentences did not affect the N400 component—traditionally taken to reflect semantic integration—but instead produced a P600 effect, which is generally linked to syntactic processing. This finding led to a considerable amount of debate, and a number of complex processing models have been proposed as an explanation. What these models have in common is that they postulate two or more separate processing streams, in order to reconcile the Semantic Illusion and other semantically induced P600 effects with the traditional interpretations of the N400 and the P600. Recently, however, these multi‐stream models have been called into question, and a simpler single‐stream model has been proposed. According to this alternative model, the N400 component reflects the retrieval of word meaning from semantic memory, and the P600 component indexes the integration of this meaning into the unfolding utterance interpretation. In the present paper, we provide support for this “Retrieval–Integration (RI)” account by instantiating it as a neurocomputational model. This neurocomputational model is the first to successfully simulate the N400 and P600 amplitude in language comprehension, and simulations with this model provide a proof of concept of the single‐stream RI account of semantically induced patterns of N400 and P600 modulations.

  • Open Access English
    Authors: 
    Yoolim Kim; Sandra Kotzor; Aditi Lahiri;
    Publisher: Elsevier
    Country: United Kingdom
    Project: EC | MOR-PHON (695481)

    Korean can be transcribed in two different scripts, one alphabetic (Hangul) and one logographic (Hanja). How does the mental lexicon represent the contributions of multiple scripts? Hangul’s highly transparent one-to-one relationship between spellings and sounds creates homophones in spoken Korean that are also homographs in Hangul, which can only be disambiguated through Hanja. We thus tested whether native speakers encoded the semantic contributions of the different Hanja characters sharing the same homographic form in Hangul in their mental representation of Sino-Korean. Is processing modulated by the number of available meanings, that is, the size of the semantic cohort? In two cross-modal lexical decision tasks with semantic priming,participants were presented with auditory primes that were either syllables (Experiment 1) or full Sino-Korean words (Experiment 2), followed by visual Sino-Korean full word targets. In Experiment 1, reaction times were not significantly modulated by the size of the semantic cohort. However, in Experiment 2, we observed significantly faster reaction times for targets preceded by primes with larger semantic cohorts. We discuss these findings in relation to the structure of the mental lexicon for bi-scriptal languages and the representation of semantic cohorts across different scripts. 1. Introduction 2. Hanja and Hangul during processing 3. Experiment 1: Cross-modal fragment priming 3.1. Method 3.1.1. Participants 3.1.2. Materials and design 3.1.3. Procedure 3.2. Results 3.3. Discussion 4. Experiment 2: Cross-modal full word priming 4.1. Method 4.1.1. Participants 4.1.2. Materials and design 4.1.3. Procedure 4.2. Results 4.3. Discussion 5. General discussion 6. Conclusions

  • Open Access
    Authors: 
    Axel Constant; Alexander Daniel Dunsmoir Tschantz; Alexander Daniel Dunsmoir Tschantz; Beren Millidge; Beren Millidge; Felipe Criado-Boado; Luis M Martinez; Johannes Müeller; Andy Clark; Andy Clark; +1 more
    Publisher: Frontiers Media
    Countries: United Kingdom, Spain
    Project: EC | XSPECT (692739), SSHRC

    This paper presents an active inference based simulation study of visual foraging. The goal of the simulation is to show the effect of the acquisition of culturally patterned attention styles on cognitive task performance, under active inference. We show how cultural artefacts like antique vase decorations drive cognitive functions such as perception, action and learning, as well as task performance in a simple visual discrimination task. We thus describe a new active inference based research pipeline that future work may employ to inquire on deep guiding principles determining the manner in which material culture drives human thought, by building and rebuilding our patterns of attention. Researchers on this article were supported by an Australian Laureate Fellowship project A Philosophy of Medicine for the 21st Century (Ref: FL170100160) and by a Social Sciences and Humanities Research Council doctoral fellowship (Ref: 752-2019-0065) (AC), by a PhD studentship from the Sackler Foundation and the School of Engineering and Informatics at the University of Sussex (AT); by an EPSRC PhD Studentship (BM), by a GAIN-Xunta de Galiza Groups of Excellence 2020 (FC-B), and by Horizon 2020 European Union ERC Advanced Grant XSPECT - DLV-692739 (AC). AT is grateful to the Mortimer and Theresa Sackler Foundation, which supports the Sackler Centre for Consciousness Science.

  • Open Access English
    Authors: 
    Kun Sun; Rong Wang;
    Publisher: Universität Stuttgart
    Country: Germany
    Project: EC | WIDE (742545)

    This study applies relative entropy in naturalistic large-scale corpus to calculate the difference among L2 (second language) learners at different levels. We chose lemma, token, POStrigram, conjunction to represent lexicon and grammar to detect the patterns of language proficiency development among different L2 groups using relative entropy. The results show that information distribution discrimination regarding lexical and grammatical differences continues to increase from L2 learners at a lower level to those at a higher level. This result is consistent with the assumption that in the course of second language acquisition, L2 learners develop towards a more complex and diverse use of language. Meanwhile, this study uses the statistics method of time series to process the data on L2 differences yielded by traditional frequency-based methods processing the same L2 corpus to compare with the results of relative entropy. However, the results from the traditional methods rarely show regularity. As compared to the algorithms in traditional approaches, relative entropy performs much better in detecting L2 proficiency development. In this sense, we have developed an effective and practical algorithm for stably detecting and predicting the developments in L2 learners’ language proficiency. H2020 European Research Council

  • Open Access English
    Authors: 
    Howard Litwin; Michal Levinsky;
    Publisher: Oxford University Press
    Project: EC | SHARE-COVID19 (101015924), EC | SSHOC (823782), EC | SHARE-COHESION (870628), EC | SERISS (654221), EC | SHARE-DEV3 (676536)

    Abstract Background and Objectives To clarify whether awareness of the extent and severity of exposure to the coronavirus disease 2019 (COVID-19) in the social networks of older adults is related to the engagement by the latter in self-protective behaviors. The inquiry is guided by the Health Belief Model and by concepts from the domain of social networks. Research Design and Methods Data from the Survey of Health, Ageing and Retirement in Europe (SHARE) were used, including the SHARE COVID-19 Survey executed in the summer of 2020. The study sample numbered 33,053 persons aged 50 and older in 26 countries. We regressed a logged count of self-protective behaviors on network-exposure severity, controlling for sociodemographic background, country, personality traits, and self-exposure severity. Age and network-exposure interaction terms were examined, as were “close family” and “other” network ties. Results Network-exposure severity was positively associated with the extent of engagement in self-protective behaviors among older adults, but mainly among the oldest group, aged 70 and older. Awareness of exposure severity in “close family” and “other” networks were similarly associated with self-protection. Respondents from countries with the lowest rates of COVID-19 infection at the time (Latvia, Finland, and Denmark) engaged in fewer self-protective behaviors, while those from countries with high infection rates (Spain, Italy, and Portugal) self-protected to a greater degree. Discussion and Implications The study findings point to the role of the social network, even if indirect, in promoting self-protective behaviors among the oldest segment of society. Policymakers should collaborate with the social networks of older adults in order to promote the adoption of self-protective behaviors. Such intervention might help to reduce the threat of infection among the most vulnerable age group.

  • Open Access
    Authors: 
    Kun Sun; Haitao Liu; Wenxin Xiong;
    Publisher: Zenodo
    Project: EC | WIDE (742545)

    AbstractScientific writings, as one essential part of human culture, have evolved over centuries into their current form. Knowing how scientific writings evolved is particularly helpful in understanding how trends in scientific culture developed. It also allows us to better understand how scientific culture was interwoven with human culture generally. The availability of massive digitized texts and the progress in computational technologies today provide us with a convenient and credible way to discern the evolutionary patterns in scientific writings by examining the diachronic linguistic changes. The linguistic changes in scientific writings reflect the genre shifts that took place with historical changes in science and scientific writings. This study investigates a general evolutionary linguistic pattern in scientific writings. It does so by merging two credible computational methods: relative entropy; word-embedding concreteness and imageability. It thus creates a novel quantitative methodology and applies this to the examination of diachronic changes in the Philosophical Transactions of Royal Society (PTRS, 1665–1869). The data from two computational approaches can be well mapped to support the argument that this journal followed the evolutionary trend of increasing professionalization and specialization. But it also shows that language use in this journal was greatly influenced by historical events and other socio-cultural factors. This study, as a “culturomic” approach, demonstrates that the linguistic evolutionary patterns in scientific discourse have been interrupted by external factors even though this scientific discourse would likely have cumulatively developed into a professional and specialized genre. The approaches proposed by this study can make a great contribution to full-text analysis in scientometrics.

  • Publication . Article . Preprint . 2020 . Embargo End Date: 06 Jul 2020
    Open Access
    Authors: 
    Claude J. Bajada; Lucas Q Costa Campos; Svenja Caspers; Richard Muscat; Geoff J M Parker; Matthew A. Lambon Ralph; Lauren L. Cloutman; Nelson J. Trujillo-Barreto;
    Publisher: Apollo - University of Cambridge Repository
    Countries: Malta, Germany, United Kingdom
    Project: EC | HBP SGA2 (785907), EC | HBP SGA3 (945539)

    There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature. Articles that investigate various “neural gradients” (for example based on region studied “cortical gradients,” “cerebellar gradients,” “hippocampal gradients” etc … or feature of interest “functional gradients,” “cytoarchitectural gradients,” “myeloarchitectural gradients” etc …) have increased in popularity. Thus, we believe that it is opportune to discuss what is generally meant by “gradient analysis”. We introduce basics concepts in graph theory, such as graphs themselves, the degree matrix, and the adjacency matrix. We discuss how one can think about gradients of feature similarity (the similarity between timeseries in fMRI, or streamline in tractography) using graph theory and we extend this to explore such gradients across the whole MRI scale; from the voxel level to the whole brain level. We proceed to introduce a measure for quantifying the level of similarity in regions of interest. We propose the term “the Vogt-Bailey index” for such quantification to pay homage to our history as a brain mapping community. We run through the techniques on sample datasets including a brain MRI as an example of the application of the techniques on real data and we provide several appendices that expand upon details. To maximise intuition, the appendices contain a didactic example describing how one could use these techniques to solve a particularly pernicious problem that one may encounter at a wedding. Accompanying the article is a tool, available in both MATLAB and Python, that enables readers to perform the analysis described in this article on their own data. We refer readers to the graphical abstract as an overview of the analysis pipeline presented in this work. Graphical abstract The two basic algorithms to compute the VB Index and the principal gradient. The algorithm on the left depicts a searchlight algorithm that identifies local borders. The algorithm on the right (yellow route) depicts the creation of a gradient map and single VB Index for the whole brain or (inclusion of orange route) multiple clusters.Image 1 Highlights • This article provides a beginner friendly review of the main steps for creating gradient maps. • We introduce a new index for quantifying mesoscopic gradients (the “VB Index”). • We use historical background to highlight the need for such quantification. • Software for computing gradient maps and the VB Index is made available.

  • Open Access English
    Authors: 
    Kun Sun; R. Harald Baayen;
    Publisher: Zenodo
    Project: EC | WIDE (742545)

    Abstract Hyphenated compounds have largely been neglected in the studies of compounding, which have seldom analysed compounds in context. In this study, we argue that the hyphen use in compounds is strongly motivated. Hyphenation is used when words form a unit, which reduces the possibility of parsing them into separate units or other forms. The current study adopts a new perspective on contextual factors, namely, which part of speech (PoS) the compound as a whole belongs to and how people correctly parse a compound into a unit. This process can be observed and analysed by considering examples. This study therefore holds that hyphenation might have gradually become a compounding technique that differs from general compounding principles. To better understand hyphenated compounds and the motivation for using hyphenation, we conduct a quantitative investigation into their distribution frequency to explore how English hyphenated compounds have been used in over the last 200 years. Diachronic change in the frequency of the distribution for compounds has seldom been considered. This question is explored by using frequency data obtained from the three databases that contain hyphenated compounds. Diachronic analysis shows that the frequencies of tokens and types in hyphenated compounds have been increasing, and changes in both frequencies follow the S-curve model. Historical evidence shows that hyphenation in compounds, as an orthographic form, does not seem to disappear easily. Familiarity and economy, as suggested in the cognitive studies of compounding, cannot adequately explain this phenomenon. The three databases that we used provide cross-verification that suggests that hyphenation has evolved into a compounding technique. Language users probably unconsciously take advantage of the discriminative learning model to remind themselves that these combinations should be parsed differently. Thus the hyphenation compounding technique facilitates communication efficiency. Overall, this study significantly enhances our understanding of the nature of compounding, the motivations for using hyphenation, and its cognitive processing.

  • Open Access English
    Authors: 
    Steffen Lepa; Martin Herzog; Jochen Steffens; Andreas Schoenrock; Hauke Egermann;
    Country: United Kingdom
    Project: EC | ABC DJ (688122)

    We describe the development of a computational model predicting listener-perceived expressions of music in branding contexts. Representative ground truth from multi-national online listening experiments was combined with machine learning of music branding expert knowledge, and audio signal analysis toolbox outputs. A mixture of random forest and traditional regression models is able to predict average ratings of perceived brand image on four dimensions. Resulting cross-validated prediction accuracy (R²) was Arousal: 61%, Valence: 44%, Authenticity: 55%, and Timeliness: 74%. Audio descriptors for rhythm, instrumentation, and musical style contributed most. Adaptive sub-models for different marketing target groups further increase prediction accuracy.

  • Open Access
    Authors: 
    Kim A. Jördens; Nicole Gotzner; Katharina Spalek;
    Project: EC | FAHMRRR (677742)

    ABSTRACTCategorisation is arguably the most important organising principle in semantic memory. However, elements that are not in a categorical relation can be dynamically grouped together when the context provides a common theme for these elements. In the field of sentence (and discourse) comprehension, alternatives to a focused element can be thought of as a set of elements determined by a theme given in the utterance context. According to Alternative Semantics (Rooth, 1985, 1992), the main function of linguistic focus is to introduce a set of alternatives to the focused element within an utterance. Here, we will investigate the contribution of the utterance context to the composition of focus alternative sets. Specifically, we test whether a focus alternative set can contain elements that belong to different taxonomic categories (i.e., that are not closely semantically related). Using a behavioural probe recognition experiment, we show that participants activate elements from another taxonomic category than the focused element as part of sentence comprehension. This finding suggests that the composition of a focus alternative set is not simply based on semantic relations between the members of the set and the focused element, but that contextual relations also play a crucial role.

Advanced search in Research products
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The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.
44 Research products, page 1 of 5
  • Publication . Article . 2022 . Embargo End Date: 16 Nov 2022
    Open Access English
    Authors: 
    Harm Brouwer; Matthew W. Crocker; Noortje J. Venhuizen; John Hoeks;
    Publisher: Universität des Saarlandes
    Project: EC | LANPERCEPT (316748)

    Abstract Ten years ago, researchers using event‐related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a Semantic Illusion: Semantically anomalous, but structurally well‐formed sentences did not affect the N400 component—traditionally taken to reflect semantic integration—but instead produced a P600 effect, which is generally linked to syntactic processing. This finding led to a considerable amount of debate, and a number of complex processing models have been proposed as an explanation. What these models have in common is that they postulate two or more separate processing streams, in order to reconcile the Semantic Illusion and other semantically induced P600 effects with the traditional interpretations of the N400 and the P600. Recently, however, these multi‐stream models have been called into question, and a simpler single‐stream model has been proposed. According to this alternative model, the N400 component reflects the retrieval of word meaning from semantic memory, and the P600 component indexes the integration of this meaning into the unfolding utterance interpretation. In the present paper, we provide support for this “Retrieval–Integration (RI)” account by instantiating it as a neurocomputational model. This neurocomputational model is the first to successfully simulate the N400 and P600 amplitude in language comprehension, and simulations with this model provide a proof of concept of the single‐stream RI account of semantically induced patterns of N400 and P600 modulations.

  • Open Access English
    Authors: 
    Yoolim Kim; Sandra Kotzor; Aditi Lahiri;
    Publisher: Elsevier
    Country: United Kingdom
    Project: EC | MOR-PHON (695481)

    Korean can be transcribed in two different scripts, one alphabetic (Hangul) and one logographic (Hanja). How does the mental lexicon represent the contributions of multiple scripts? Hangul’s highly transparent one-to-one relationship between spellings and sounds creates homophones in spoken Korean that are also homographs in Hangul, which can only be disambiguated through Hanja. We thus tested whether native speakers encoded the semantic contributions of the different Hanja characters sharing the same homographic form in Hangul in their mental representation of Sino-Korean. Is processing modulated by the number of available meanings, that is, the size of the semantic cohort? In two cross-modal lexical decision tasks with semantic priming,participants were presented with auditory primes that were either syllables (Experiment 1) or full Sino-Korean words (Experiment 2), followed by visual Sino-Korean full word targets. In Experiment 1, reaction times were not significantly modulated by the size of the semantic cohort. However, in Experiment 2, we observed significantly faster reaction times for targets preceded by primes with larger semantic cohorts. We discuss these findings in relation to the structure of the mental lexicon for bi-scriptal languages and the representation of semantic cohorts across different scripts. 1. Introduction 2. Hanja and Hangul during processing 3. Experiment 1: Cross-modal fragment priming 3.1. Method 3.1.1. Participants 3.1.2. Materials and design 3.1.3. Procedure 3.2. Results 3.3. Discussion 4. Experiment 2: Cross-modal full word priming 4.1. Method 4.1.1. Participants 4.1.2. Materials and design 4.1.3. Procedure 4.2. Results 4.3. Discussion 5. General discussion 6. Conclusions

  • Open Access
    Authors: 
    Axel Constant; Alexander Daniel Dunsmoir Tschantz; Alexander Daniel Dunsmoir Tschantz; Beren Millidge; Beren Millidge; Felipe Criado-Boado; Luis M Martinez; Johannes Müeller; Andy Clark; Andy Clark; +1 more
    Publisher: Frontiers Media
    Countries: United Kingdom, Spain
    Project: EC | XSPECT (692739), SSHRC

    This paper presents an active inference based simulation study of visual foraging. The goal of the simulation is to show the effect of the acquisition of culturally patterned attention styles on cognitive task performance, under active inference. We show how cultural artefacts like antique vase decorations drive cognitive functions such as perception, action and learning, as well as task performance in a simple visual discrimination task. We thus describe a new active inference based research pipeline that future work may employ to inquire on deep guiding principles determining the manner in which material culture drives human thought, by building and rebuilding our patterns of attention. Researchers on this article were supported by an Australian Laureate Fellowship project A Philosophy of Medicine for the 21st Century (Ref: FL170100160) and by a Social Sciences and Humanities Research Council doctoral fellowship (Ref: 752-2019-0065) (AC), by a PhD studentship from the Sackler Foundation and the School of Engineering and Informatics at the University of Sussex (AT); by an EPSRC PhD Studentship (BM), by a GAIN-Xunta de Galiza Groups of Excellence 2020 (FC-B), and by Horizon 2020 European Union ERC Advanced Grant XSPECT - DLV-692739 (AC). AT is grateful to the Mortimer and Theresa Sackler Foundation, which supports the Sackler Centre for Consciousness Science.

  • Open Access English
    Authors: 
    Kun Sun; Rong Wang;
    Publisher: Universität Stuttgart
    Country: Germany
    Project: EC | WIDE (742545)

    This study applies relative entropy in naturalistic large-scale corpus to calculate the difference among L2 (second language) learners at different levels. We chose lemma, token, POStrigram, conjunction to represent lexicon and grammar to detect the patterns of language proficiency development among different L2 groups using relative entropy. The results show that information distribution discrimination regarding lexical and grammatical differences continues to increase from L2 learners at a lower level to those at a higher level. This result is consistent with the assumption that in the course of second language acquisition, L2 learners develop towards a more complex and diverse use of language. Meanwhile, this study uses the statistics method of time series to process the data on L2 differences yielded by traditional frequency-based methods processing the same L2 corpus to compare with the results of relative entropy. However, the results from the traditional methods rarely show regularity. As compared to the algorithms in traditional approaches, relative entropy performs much better in detecting L2 proficiency development. In this sense, we have developed an effective and practical algorithm for stably detecting and predicting the developments in L2 learners’ language proficiency. H2020 European Research Council

  • Open Access English
    Authors: 
    Howard Litwin; Michal Levinsky;
    Publisher: Oxford University Press
    Project: EC | SHARE-COVID19 (101015924), EC | SSHOC (823782), EC | SHARE-COHESION (870628), EC | SERISS (654221), EC | SHARE-DEV3 (676536)

    Abstract Background and Objectives To clarify whether awareness of the extent and severity of exposure to the coronavirus disease 2019 (COVID-19) in the social networks of older adults is related to the engagement by the latter in self-protective behaviors. The inquiry is guided by the Health Belief Model and by concepts from the domain of social networks. Research Design and Methods Data from the Survey of Health, Ageing and Retirement in Europe (SHARE) were used, including the SHARE COVID-19 Survey executed in the summer of 2020. The study sample numbered 33,053 persons aged 50 and older in 26 countries. We regressed a logged count of self-protective behaviors on network-exposure severity, controlling for sociodemographic background, country, personality traits, and self-exposure severity. Age and network-exposure interaction terms were examined, as were “close family” and “other” network ties. Results Network-exposure severity was positively associated with the extent of engagement in self-protective behaviors among older adults, but mainly among the oldest group, aged 70 and older. Awareness of exposure severity in “close family” and “other” networks were similarly associated with self-protection. Respondents from countries with the lowest rates of COVID-19 infection at the time (Latvia, Finland, and Denmark) engaged in fewer self-protective behaviors, while those from countries with high infection rates (Spain, Italy, and Portugal) self-protected to a greater degree. Discussion and Implications The study findings point to the role of the social network, even if indirect, in promoting self-protective behaviors among the oldest segment of society. Policymakers should collaborate with the social networks of older adults in order to promote the adoption of self-protective behaviors. Such intervention might help to reduce the threat of infection among the most vulnerable age group.

  • Open Access
    Authors: 
    Kun Sun; Haitao Liu; Wenxin Xiong;
    Publisher: Zenodo
    Project: EC | WIDE (742545)

    AbstractScientific writings, as one essential part of human culture, have evolved over centuries into their current form. Knowing how scientific writings evolved is particularly helpful in understanding how trends in scientific culture developed. It also allows us to better understand how scientific culture was interwoven with human culture generally. The availability of massive digitized texts and the progress in computational technologies today provide us with a convenient and credible way to discern the evolutionary patterns in scientific writings by examining the diachronic linguistic changes. The linguistic changes in scientific writings reflect the genre shifts that took place with historical changes in science and scientific writings. This study investigates a general evolutionary linguistic pattern in scientific writings. It does so by merging two credible computational methods: relative entropy; word-embedding concreteness and imageability. It thus creates a novel quantitative methodology and applies this to the examination of diachronic changes in the Philosophical Transactions of Royal Society (PTRS, 1665–1869). The data from two computational approaches can be well mapped to support the argument that this journal followed the evolutionary trend of increasing professionalization and specialization. But it also shows that language use in this journal was greatly influenced by historical events and other socio-cultural factors. This study, as a “culturomic” approach, demonstrates that the linguistic evolutionary patterns in scientific discourse have been interrupted by external factors even though this scientific discourse would likely have cumulatively developed into a professional and specialized genre. The approaches proposed by this study can make a great contribution to full-text analysis in scientometrics.

  • Publication . Article . Preprint . 2020 . Embargo End Date: 06 Jul 2020
    Open Access
    Authors: 
    Claude J. Bajada; Lucas Q Costa Campos; Svenja Caspers; Richard Muscat; Geoff J M Parker; Matthew A. Lambon Ralph; Lauren L. Cloutman; Nelson J. Trujillo-Barreto;
    Publisher: Apollo - University of Cambridge Repository
    Countries: Malta, Germany, United Kingdom
    Project: EC | HBP SGA2 (785907), EC | HBP SGA3 (945539)

    There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature. Articles that investigate various “neural gradients” (for example based on region studied “cortical gradients,” “cerebellar gradients,” “hippocampal gradients” etc … or feature of interest “functional gradients,” “cytoarchitectural gradients,” “myeloarchitectural gradients” etc …) have increased in popularity. Thus, we believe that it is opportune to discuss what is generally meant by “gradient analysis”. We introduce basics concepts in graph theory, such as graphs themselves, the degree matrix, and the adjacency matrix. We discuss how one can think about gradients of feature similarity (the similarity between timeseries in fMRI, or streamline in tractography) using graph theory and we extend this to explore such gradients across the whole MRI scale; from the voxel level to the whole brain level. We proceed to introduce a measure for quantifying the level of similarity in regions of interest. We propose the term “the Vogt-Bailey index” for such quantification to pay homage to our history as a brain mapping community. We run through the techniques on sample datasets including a brain MRI as an example of the application of the techniques on real data and we provide several appendices that expand upon details. To maximise intuition, the appendices contain a didactic example describing how one could use these techniques to solve a particularly pernicious problem that one may encounter at a wedding. Accompanying the article is a tool, available in both MATLAB and Python, that enables readers to perform the analysis described in this article on their own data. We refer readers to the graphical abstract as an overview of the analysis pipeline presented in this work. Graphical abstract The two basic algorithms to compute the VB Index and the principal gradient. The algorithm on the left depicts a searchlight algorithm that identifies local borders. The algorithm on the right (yellow route) depicts the creation of a gradient map and single VB Index for the whole brain or (inclusion of orange route) multiple clusters.Image 1 Highlights • This article provides a beginner friendly review of the main steps for creating gradient maps. • We introduce a new index for quantifying mesoscopic gradients (the “VB Index”). • We use historical background to highlight the need for such quantification. • Software for computing gradient maps and the VB Index is made available.

  • Open Access English
    Authors: 
    Kun Sun; R. Harald Baayen;
    Publisher: Zenodo
    Project: EC | WIDE (742545)

    Abstract Hyphenated compounds have largely been neglected in the studies of compounding, which have seldom analysed compounds in context. In this study, we argue that the hyphen use in compounds is strongly motivated. Hyphenation is used when words form a unit, which reduces the possibility of parsing them into separate units or other forms. The current study adopts a new perspective on contextual factors, namely, which part of speech (PoS) the compound as a whole belongs to and how people correctly parse a compound into a unit. This process can be observed and analysed by considering examples. This study therefore holds that hyphenation might have gradually become a compounding technique that differs from general compounding principles. To better understand hyphenated compounds and the motivation for using hyphenation, we conduct a quantitative investigation into their distribution frequency to explore how English hyphenated compounds have been used in over the last 200 years. Diachronic change in the frequency of the distribution for compounds has seldom been considered. This question is explored by using frequency data obtained from the three databases that contain hyphenated compounds. Diachronic analysis shows that the frequencies of tokens and types in hyphenated compounds have been increasing, and changes in both frequencies follow the S-curve model. Historical evidence shows that hyphenation in compounds, as an orthographic form, does not seem to disappear easily. Familiarity and economy, as suggested in the cognitive studies of compounding, cannot adequately explain this phenomenon. The three databases that we used provide cross-verification that suggests that hyphenation has evolved into a compounding technique. Language users probably unconsciously take advantage of the discriminative learning model to remind themselves that these combinations should be parsed differently. Thus the hyphenation compounding technique facilitates communication efficiency. Overall, this study significantly enhances our understanding of the nature of compounding, the motivations for using hyphenation, and its cognitive processing.

  • Open Access English
    Authors: 
    Steffen Lepa; Martin Herzog; Jochen Steffens; Andreas Schoenrock; Hauke Egermann;
    Country: United Kingdom
    Project: EC | ABC DJ (688122)

    We describe the development of a computational model predicting listener-perceived expressions of music in branding contexts. Representative ground truth from multi-national online listening experiments was combined with machine learning of music branding expert knowledge, and audio signal analysis toolbox outputs. A mixture of random forest and traditional regression models is able to predict average ratings of perceived brand image on four dimensions. Resulting cross-validated prediction accuracy (R²) was Arousal: 61%, Valence: 44%, Authenticity: 55%, and Timeliness: 74%. Audio descriptors for rhythm, instrumentation, and musical style contributed most. Adaptive sub-models for different marketing target groups further increase prediction accuracy.

  • Open Access
    Authors: 
    Kim A. Jördens; Nicole Gotzner; Katharina Spalek;
    Project: EC | FAHMRRR (677742)

    ABSTRACTCategorisation is arguably the most important organising principle in semantic memory. However, elements that are not in a categorical relation can be dynamically grouped together when the context provides a common theme for these elements. In the field of sentence (and discourse) comprehension, alternatives to a focused element can be thought of as a set of elements determined by a theme given in the utterance context. According to Alternative Semantics (Rooth, 1985, 1992), the main function of linguistic focus is to introduce a set of alternatives to the focused element within an utterance. Here, we will investigate the contribution of the utterance context to the composition of focus alternative sets. Specifically, we test whether a focus alternative set can contain elements that belong to different taxonomic categories (i.e., that are not closely semantically related). Using a behavioural probe recognition experiment, we show that participants activate elements from another taxonomic category than the focused element as part of sentence comprehension. This finding suggests that the composition of a focus alternative set is not simply based on semantic relations between the members of the set and the focused element, but that contextual relations also play a crucial role.