Project acronym BABYRHYTHM
Project Oscillatory Rhythmic Entrainment and the Foundations of Language Acquisition
Researcher (PI) Usha Claire GOSWAMI
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary Half of “late talkers”, infants who are not yet speaking by 2 years of age, will go on to develop language impairments. Currently, we have no reliable means of identifying these infants. Here we combine our developmental approach to phonology (psycholinguistic grain size theory), to the neural mechanisms underlying speech encoding (temporal sampling [TS] theory) and our work on the developmental importance of the speech amplitude envelope (AE) to open a new research front in the foundations of language acquisition. Recent adult research confirms our decade-long focus on the importance of sensitivity to AE ‘rise time’ in children’s language development, showing that rise times (‘auditory edges’) re-set the endogenous cortical oscillations that encode speech. Accordingly, we now apply our in-house state-of-the-art methods for measuring oscillatory rhythmic entrainment in children along with our recent theoretical and behavioural advances concerning AE processing to infant studies. Our core aim is to use the TS theoretical perspective and analysis methods to generate robust early neural and behavioural markers of phonological and morphological development: TS for infants. We have published the first-ever studies of oscillatory entrainment to speech rhythm by children and we have developed methods for technically-challenging EEG speech envelope reconstruction. We now apply these innovative methods to infant language learning and infant-directed speech. Using our cutting-edge EEG methods, we will deliver a novel and innovative road map for charting early language acquisition from a rhythmic entrainment perspective. Our recent 5-year study of rise time sensitivity in infants confirms the feasibility of a TS approach. As our focus is on prosody, syllable stress and syllable processing, our methods will apply across European languages.
Summary
Half of “late talkers”, infants who are not yet speaking by 2 years of age, will go on to develop language impairments. Currently, we have no reliable means of identifying these infants. Here we combine our developmental approach to phonology (psycholinguistic grain size theory), to the neural mechanisms underlying speech encoding (temporal sampling [TS] theory) and our work on the developmental importance of the speech amplitude envelope (AE) to open a new research front in the foundations of language acquisition. Recent adult research confirms our decade-long focus on the importance of sensitivity to AE ‘rise time’ in children’s language development, showing that rise times (‘auditory edges’) re-set the endogenous cortical oscillations that encode speech. Accordingly, we now apply our in-house state-of-the-art methods for measuring oscillatory rhythmic entrainment in children along with our recent theoretical and behavioural advances concerning AE processing to infant studies. Our core aim is to use the TS theoretical perspective and analysis methods to generate robust early neural and behavioural markers of phonological and morphological development: TS for infants. We have published the first-ever studies of oscillatory entrainment to speech rhythm by children and we have developed methods for technically-challenging EEG speech envelope reconstruction. We now apply these innovative methods to infant language learning and infant-directed speech. Using our cutting-edge EEG methods, we will deliver a novel and innovative road map for charting early language acquisition from a rhythmic entrainment perspective. Our recent 5-year study of rise time sensitivity in infants confirms the feasibility of a TS approach. As our focus is on prosody, syllable stress and syllable processing, our methods will apply across European languages.
Max ERC Funding
2 614 275 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym CANDICE
Project CEREBRAL ASYMMETRY: NEW DIRECTIONS IN CORRELATES AND ETIOLOGY
Researcher (PI) Dorothy Vera Margaret BISHOP
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary "150 years after Broca's seminal statement "Nous parlons avec l'hémisphère gauche" we still do not know how or why we have this bias. I propose that by studying cases of impaired language development and combining genetic and neuropsychological approaches we will be able to make a leap forward in our understanding of the quintessentially human characteristic of functional cerebral asymmetry. I argue that contradictory findings in the literature may be reconciled if we adopt a novel approach to cerebral asymmetry. In particular, I propose a network efficiency hypothesis which maintains that optimal development depends on organisation of key language functions within the same cerebral hemisphere.
In project A, I will combine behavioural measures with functional transcranial Doppler ultrasound (fTCD) measures of blood flow and functional magnetic resonance imaging (fMRI) to identify individual differences in patterns of dissociation between language functions in lateralisation. In project B I will test the prediction that risk for language and literacy impairment is increased if different language functions are represented in opposite hemispheres. For project C, simulations of predictions from genetic models will be tested using data on twin-cotwin similarity in language lateralisation. Project D will test a 'double hit' genetic model that predicts that neurodevelopmental abnormalities, including language deficits and inconsistent asymmetry, arise when there is more than one hit on a functional brain circuit. For this study we will use an existing sample of individuals already known to have one 'hit' on the neuroligin-neurexin circuit, viz people with an additional dose of neuroligin caused by an extra sex chromosome. Project E will focus on individuals with inconsistent patterns of language laterality and will look for rare genetic mutations and structural rearrangements associated with a departure from consistent left hemisphere language."
Summary
"150 years after Broca's seminal statement "Nous parlons avec l'hémisphère gauche" we still do not know how or why we have this bias. I propose that by studying cases of impaired language development and combining genetic and neuropsychological approaches we will be able to make a leap forward in our understanding of the quintessentially human characteristic of functional cerebral asymmetry. I argue that contradictory findings in the literature may be reconciled if we adopt a novel approach to cerebral asymmetry. In particular, I propose a network efficiency hypothesis which maintains that optimal development depends on organisation of key language functions within the same cerebral hemisphere.
In project A, I will combine behavioural measures with functional transcranial Doppler ultrasound (fTCD) measures of blood flow and functional magnetic resonance imaging (fMRI) to identify individual differences in patterns of dissociation between language functions in lateralisation. In project B I will test the prediction that risk for language and literacy impairment is increased if different language functions are represented in opposite hemispheres. For project C, simulations of predictions from genetic models will be tested using data on twin-cotwin similarity in language lateralisation. Project D will test a 'double hit' genetic model that predicts that neurodevelopmental abnormalities, including language deficits and inconsistent asymmetry, arise when there is more than one hit on a functional brain circuit. For this study we will use an existing sample of individuals already known to have one 'hit' on the neuroligin-neurexin circuit, viz people with an additional dose of neuroligin caused by an extra sex chromosome. Project E will focus on individuals with inconsistent patterns of language laterality and will look for rare genetic mutations and structural rearrangements associated with a departure from consistent left hemisphere language."
Max ERC Funding
2 497 907 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym DALI
Project Disagreements and Language Interpretation
Researcher (PI) Massimo POESIO
Host Institution (HI) QUEEN MARY UNIVERSITY OF LONDON
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary Natural language expressions are supposed to be unambiguous in context. Yet more and more examples of use of expressions that are ambiguous in context, yet felicitous and rhetorically unmarked, are emerging. In my own work, I demonstrated that ambiguity in anaphoric reference is ubiquitous, through the study of disagreements in annotation, that I pioneered in CL. Since then, additional cases of ambiguous anaphoric reference have been found; and similar findings have been made for other aspects of language interpretation, including wordsense disambiguation, and even part-of-speech tagging. Using the Phrase Detectives Game-With-A-Purpose to collect massive amounts of judgments online, we found that up to 30% of anaphoric expressions in our data are ambiguous. These findings raise a serious challenge for computational linguistics (CL), as assumptions about the existence of a single interpretation in context are built in the dominant methodology, that depends on a reliably annotated gold standard.
The goal of the proposed project is to tackle this fundamental issue of disagreements in interpretation by using computational methods for collecting and analysing such disagreements, some of which already exist but have never before been applied in linguistics on a large scale, some we will develop from scratch. Specifically, I propose to develop more advanced games-with-a-purpose to collect massive amounts of data about anaphora from people playing a game. I propose to use Bayesian models of annotation, widely used in epidemiology but not in linguistics, to analyse such data and identify genuine ambiguities; doing this for anaphora will require novel methods. Third, I propose to use these data to revisit current theories about anaphoric expressions that do not seem to cause infelicitousness when ambiguous. Finally, I propose to develop the first supervised approach to anaphora resolution that does not require a gold standard as a blueprint for other areas.
Summary
Natural language expressions are supposed to be unambiguous in context. Yet more and more examples of use of expressions that are ambiguous in context, yet felicitous and rhetorically unmarked, are emerging. In my own work, I demonstrated that ambiguity in anaphoric reference is ubiquitous, through the study of disagreements in annotation, that I pioneered in CL. Since then, additional cases of ambiguous anaphoric reference have been found; and similar findings have been made for other aspects of language interpretation, including wordsense disambiguation, and even part-of-speech tagging. Using the Phrase Detectives Game-With-A-Purpose to collect massive amounts of judgments online, we found that up to 30% of anaphoric expressions in our data are ambiguous. These findings raise a serious challenge for computational linguistics (CL), as assumptions about the existence of a single interpretation in context are built in the dominant methodology, that depends on a reliably annotated gold standard.
The goal of the proposed project is to tackle this fundamental issue of disagreements in interpretation by using computational methods for collecting and analysing such disagreements, some of which already exist but have never before been applied in linguistics on a large scale, some we will develop from scratch. Specifically, I propose to develop more advanced games-with-a-purpose to collect massive amounts of data about anaphora from people playing a game. I propose to use Bayesian models of annotation, widely used in epidemiology but not in linguistics, to analyse such data and identify genuine ambiguities; doing this for anaphora will require novel methods. Third, I propose to use these data to revisit current theories about anaphoric expressions that do not seem to cause infelicitousness when ambiguous. Finally, I propose to develop the first supervised approach to anaphora resolution that does not require a gold standard as a blueprint for other areas.
Max ERC Funding
2 499 471 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym ECOLANG
Project Ecological Language: A multimodal approach to language and the brain
Researcher (PI) Gabriella VIGLIOCCO
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Call Details Advanced Grant (AdG), SH4, ERC-2016-ADG
Summary The human brain has evolved the ability to support communication in complex and dynamic environments. In such environments, language is learned, and mostly used in face-to-face contexts in which processing and learning is based on multiple cues: linguistic (such as lexical, syntactic), but also discourse, prosody, face and hands (gestures). Yet, our understanding of how language is learnt and processed, and its associated neural circuitry, comes almost exclusively from reductionist approaches in which the multimodal signal is reduced to speech or text. ECOLANG will pioneer a new way to study language comprehension and learning using a real-world approach in which language is analysed in its rich face-to-face multimodal environment (i.e., language’s ecological niche). Experimental rigour is not compromised by the use of innovative technologies (combining automatic, manual and crowdsourcing methods for annotation; creating avatar stimuli for our experiments) and state-of-the-art modelling and data analysis (probabilistic modelling and network-based analyses). ECOLANG studies how the different cues available in face-to-face communication dynamically contribute to processing and learning in adults, children and aphasic patients in contexts representative of everyday conversation. We collect and annotate a corpus of naturalistic language which is then used to derive quantitative informativeness measures for each cue and their combination using computational models, tested and refined on the basis of behavioural and neuroscientific data. We use converging methodologies (behavioural, EEG, fMRI and lesion-symptom mapping) and we investigate different populations (3-4 years old children, healthy and aphasic adults) in order to develop mechanistic accounts of multimodal communication at the cognitive as well as neural level that can explain processing and learning (by both children and adults) and can have impact on the rehabilitation of language functions after stroke.
Summary
The human brain has evolved the ability to support communication in complex and dynamic environments. In such environments, language is learned, and mostly used in face-to-face contexts in which processing and learning is based on multiple cues: linguistic (such as lexical, syntactic), but also discourse, prosody, face and hands (gestures). Yet, our understanding of how language is learnt and processed, and its associated neural circuitry, comes almost exclusively from reductionist approaches in which the multimodal signal is reduced to speech or text. ECOLANG will pioneer a new way to study language comprehension and learning using a real-world approach in which language is analysed in its rich face-to-face multimodal environment (i.e., language’s ecological niche). Experimental rigour is not compromised by the use of innovative technologies (combining automatic, manual and crowdsourcing methods for annotation; creating avatar stimuli for our experiments) and state-of-the-art modelling and data analysis (probabilistic modelling and network-based analyses). ECOLANG studies how the different cues available in face-to-face communication dynamically contribute to processing and learning in adults, children and aphasic patients in contexts representative of everyday conversation. We collect and annotate a corpus of naturalistic language which is then used to derive quantitative informativeness measures for each cue and their combination using computational models, tested and refined on the basis of behavioural and neuroscientific data. We use converging methodologies (behavioural, EEG, fMRI and lesion-symptom mapping) and we investigate different populations (3-4 years old children, healthy and aphasic adults) in order to develop mechanistic accounts of multimodal communication at the cognitive as well as neural level that can explain processing and learning (by both children and adults) and can have impact on the rehabilitation of language functions after stroke.
Max ERC Funding
2 243 584 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym M and M
Project Generalization in Mind and Machine
Researcher (PI) jeffrey BOWERS
Host Institution (HI) UNIVERSITY OF BRISTOL
Call Details Advanced Grant (AdG), SH4, ERC-2016-ADG
Summary Is the human mind a symbolic computational device? This issue was at the core Chomsky’s critique of Skinner in the 1960s, and motivated the debates regarding Parallel Distributed Processing models developed in the 1980s. The recent successes of “deep” networks make this issue topical for psychology and neuroscience, and it raises the question of whether symbols are needed for artificial intelligence more generally.
One of the innovations of the current project is to identify simple empirical phenomena that will serve a critical test-bed for both symbolic and non-symbolic neural networks. In order to make substantial progress on this issue a series of empirical and computational investigations are organised as follows. First, studies focus on tasks that, according to proponents of symbolic systems, require symbols for the sake of generalisation. Accordingly, if non-symbolic networks succeed, it would undermine one of the main motivations for symbolic systems. Second, studies focus on generalisation in tasks in which human performance is well characterised. Accordingly, the research will provide important constraints for theories of cognition across a range of domains, including vision, memory, and reasoning. Third, studies develop new learning algorithms designed to make symbolic systems biologically plausible. One of the reasons why symbolic networks are often dismissed is the claim that they are not as biologically plausible as non-symbolic models. This last ambition is the most high-risk but also potentially the most important: Introducing new computational principles may fundamentally advance our understanding of how the brain learns and computes, and furthermore, these principles may increase the computational powers of networks in ways that are important for engineering and artificial intelligence.
Summary
Is the human mind a symbolic computational device? This issue was at the core Chomsky’s critique of Skinner in the 1960s, and motivated the debates regarding Parallel Distributed Processing models developed in the 1980s. The recent successes of “deep” networks make this issue topical for psychology and neuroscience, and it raises the question of whether symbols are needed for artificial intelligence more generally.
One of the innovations of the current project is to identify simple empirical phenomena that will serve a critical test-bed for both symbolic and non-symbolic neural networks. In order to make substantial progress on this issue a series of empirical and computational investigations are organised as follows. First, studies focus on tasks that, according to proponents of symbolic systems, require symbols for the sake of generalisation. Accordingly, if non-symbolic networks succeed, it would undermine one of the main motivations for symbolic systems. Second, studies focus on generalisation in tasks in which human performance is well characterised. Accordingly, the research will provide important constraints for theories of cognition across a range of domains, including vision, memory, and reasoning. Third, studies develop new learning algorithms designed to make symbolic systems biologically plausible. One of the reasons why symbolic networks are often dismissed is the claim that they are not as biologically plausible as non-symbolic models. This last ambition is the most high-risk but also potentially the most important: Introducing new computational principles may fundamentally advance our understanding of how the brain learns and computes, and furthermore, these principles may increase the computational powers of networks in ways that are important for engineering and artificial intelligence.
Max ERC Funding
2 495 578 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
Project acronym MOR-PHON
Project Resolving Morpho-Phonological Alternation: Historical, Neurolinguistic, and Computational Approaches
Researcher (PI) Aditi LAHIRI
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary In morpho-phonological alternations the shapes of morphemes differ between morphologically related word forms. In these alternations the morphological environment is also implicated (revére ~ réverence verb [iː] ~ noun [ɛ] and stress differ) unlike alternations which are conditioned only by the phonological environment.
The opaque phonological relationship between morphologically related forms has been a long-standing challenge in theoretical, historical, psycho- and neuro-linguistics, and computational linguistics alike. Morpho-phonological alternations of all kinds have been analysed across the languages of the world; but fundamental questions have remained controversial or indeed unasked:
▪ Why do they exist in the first place and why are they so widespread?
▪ How do they come about and what is their diachronic time-course?
▪ How are they represented in mental lexicons and how are they processed?
Rather than setting morpho-phonological alternations aside as irregularities of morphology (requiring individual listing and storing), we recognise certain kinds of them (stress shifts, feature changes, deletions, and tonal changes) as something universally to be expected in mental lexicons and as something the brains of speakers and listeners can easily handle. The position that we advocate is that morpho-phonological variants are not listed and stored independently, but rather are mapped onto single abstract representations. This is a controversial position, and its defence requires the systematic study of types of alternations and their histories, and precise hypotheses about the nature of mental representations.
What distinguishes our approach is that we combine expertise in (a) theoretical and typological linguistics, (b) brain-imaging methods, and (c) computational modeling to shed light on our questions concerning the existence and cross-linguistic incidence of morpho-phonological alternations, their diachronic profiles, their processing and mental representation.
Summary
In morpho-phonological alternations the shapes of morphemes differ between morphologically related word forms. In these alternations the morphological environment is also implicated (revére ~ réverence verb [iː] ~ noun [ɛ] and stress differ) unlike alternations which are conditioned only by the phonological environment.
The opaque phonological relationship between morphologically related forms has been a long-standing challenge in theoretical, historical, psycho- and neuro-linguistics, and computational linguistics alike. Morpho-phonological alternations of all kinds have been analysed across the languages of the world; but fundamental questions have remained controversial or indeed unasked:
▪ Why do they exist in the first place and why are they so widespread?
▪ How do they come about and what is their diachronic time-course?
▪ How are they represented in mental lexicons and how are they processed?
Rather than setting morpho-phonological alternations aside as irregularities of morphology (requiring individual listing and storing), we recognise certain kinds of them (stress shifts, feature changes, deletions, and tonal changes) as something universally to be expected in mental lexicons and as something the brains of speakers and listeners can easily handle. The position that we advocate is that morpho-phonological variants are not listed and stored independently, but rather are mapped onto single abstract representations. This is a controversial position, and its defence requires the systematic study of types of alternations and their histories, and precise hypotheses about the nature of mental representations.
What distinguishes our approach is that we combine expertise in (a) theoretical and typological linguistics, (b) brain-imaging methods, and (c) computational modeling to shed light on our questions concerning the existence and cross-linguistic incidence of morpho-phonological alternations, their diachronic profiles, their processing and mental representation.
Max ERC Funding
2 605 261 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym NEUROMEM
Project A Neurocomputational Model of Episodic Memory
Researcher (PI) Neil BURGESS
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary Our memories define us, and their disruption in psychiatric and neurological conditions can be devastating. However, how we are able, e.g., to remember our wedding day and re-imagine the scene that was around us, remains one of the great mysteries of the human mind. NEUROMEM is an integrated experimental and computational attempt at a fundamental breakthrough in this problem. Building on recent insights into how environmental location and orientation is encoded by neurons in the mammalian brain, I aim to develop a mechanistic understanding of how events we experience are stored, recalled and imagined, i.e. a neurocomputational model of how specific memories result from patterns of activity in neuronal populations.
NEUROMEM will provide mechanistic answers to 3 long-standing questions: 1) What is the link between memory and space, and role of spatial context in re-imagining episodes? 2) How are the multiple diverse elements of complex life-like events recollected together? 3) How can remembered events be read-out as visuospatial imagery? Work will comprise psychological and functional neuroimaging experiments using sophisticated designs including use of virtual reality, and corresponding simulations of how such behaviour can be driven by neuronal activity. The computational modelling will directly contact neurophysiological data such as the firing of place and grid cells in the hippocampal formation, and provide quantitative behavioural predictions, while neuroimaging provides a read out of population activity during this processing in the human brain.
NEUROMEM will generate new hypotheses and explanations at the cognitive level, of interest to all scholars of the complexity of the human mind, and allow neurophysiological interpretation of behavioural data - providing a vital link between cognitive theory and neuroimaging and neurological data. Its implications extend beyond memory, including the mechanism for imagining views that have not been experienced.
Summary
Our memories define us, and their disruption in psychiatric and neurological conditions can be devastating. However, how we are able, e.g., to remember our wedding day and re-imagine the scene that was around us, remains one of the great mysteries of the human mind. NEUROMEM is an integrated experimental and computational attempt at a fundamental breakthrough in this problem. Building on recent insights into how environmental location and orientation is encoded by neurons in the mammalian brain, I aim to develop a mechanistic understanding of how events we experience are stored, recalled and imagined, i.e. a neurocomputational model of how specific memories result from patterns of activity in neuronal populations.
NEUROMEM will provide mechanistic answers to 3 long-standing questions: 1) What is the link between memory and space, and role of spatial context in re-imagining episodes? 2) How are the multiple diverse elements of complex life-like events recollected together? 3) How can remembered events be read-out as visuospatial imagery? Work will comprise psychological and functional neuroimaging experiments using sophisticated designs including use of virtual reality, and corresponding simulations of how such behaviour can be driven by neuronal activity. The computational modelling will directly contact neurophysiological data such as the firing of place and grid cells in the hippocampal formation, and provide quantitative behavioural predictions, while neuroimaging provides a read out of population activity during this processing in the human brain.
NEUROMEM will generate new hypotheses and explanations at the cognitive level, of interest to all scholars of the complexity of the human mind, and allow neurophysiological interpretation of behavioural data - providing a vital link between cognitive theory and neuroimaging and neurological data. Its implications extend beyond memory, including the mechanism for imagining views that have not been experienced.
Max ERC Funding
2 429 964 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym RitualModes
Project Divergent modes of ritual, social cohesion, prosociality, and conflict.
Researcher (PI) Harvey Whitehouse
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary The project aims to establish an authoritative scientific framework for understanding the relationship between group ritual, social cohesion, and pro-group behaviour. Rituals have shaped human societies for millennia, but the exact social consequences of rituals are poorly understood. The proposed research will identify the fundamental components of rituals worldwide and chart their effects on patterns of group alignment and action. Doing so will have a lasting impact on basic understandings of the nature, causes, and consequences of ritual dynamics as well as open up exciting new avenues of inquiry that bridge the humanities and social sciences.
It is proposed that within numerous cultures and group types, collective rituals come in two main forms with distinct consequences: 1) affectively-intense, rarely-enacted rituals bond group members tightly and motivate extreme self-sacrifice; 2) frequently repeated rituals create allegiance to broad collectives and motivate ingroup bias. Using this model as a starting point, the proposed research programme will seek to achieve three tightly linked objectives. Objective 1 will examine psychological mechanisms underlying rituals’ effects on group cohesion and behaviour in ten nations. Objective 2 will focus on the ritual dynamics of special populations exposed to group-related violence (e.g., war veterans, ex-convicts, war-torn communities). Objective 3 will examine the functions of ritual and cohesion in cultural group selection. Using new techniques, we will quantitatively code and analyse qualitative data on ritual and cohesion in large historical databases from hundreds of groups over the past 12,000 years. Overall, these research objectives aim to provide insights into key questions (e.g., what are the fundamental building blocks of group rituals?), understudied groups (e.g., revolutionary combatants), and unresolved debates in many fields (e.g., what motivates self-sacrifice?).
Summary
The project aims to establish an authoritative scientific framework for understanding the relationship between group ritual, social cohesion, and pro-group behaviour. Rituals have shaped human societies for millennia, but the exact social consequences of rituals are poorly understood. The proposed research will identify the fundamental components of rituals worldwide and chart their effects on patterns of group alignment and action. Doing so will have a lasting impact on basic understandings of the nature, causes, and consequences of ritual dynamics as well as open up exciting new avenues of inquiry that bridge the humanities and social sciences.
It is proposed that within numerous cultures and group types, collective rituals come in two main forms with distinct consequences: 1) affectively-intense, rarely-enacted rituals bond group members tightly and motivate extreme self-sacrifice; 2) frequently repeated rituals create allegiance to broad collectives and motivate ingroup bias. Using this model as a starting point, the proposed research programme will seek to achieve three tightly linked objectives. Objective 1 will examine psychological mechanisms underlying rituals’ effects on group cohesion and behaviour in ten nations. Objective 2 will focus on the ritual dynamics of special populations exposed to group-related violence (e.g., war veterans, ex-convicts, war-torn communities). Objective 3 will examine the functions of ritual and cohesion in cultural group selection. Using new techniques, we will quantitatively code and analyse qualitative data on ritual and cohesion in large historical databases from hundreds of groups over the past 12,000 years. Overall, these research objectives aim to provide insights into key questions (e.g., what are the fundamental building blocks of group rituals?), understudied groups (e.g., revolutionary combatants), and unresolved debates in many fields (e.g., what motivates self-sacrifice?).
Max ERC Funding
2 499 980 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym SEMANTAX
Project Form-Independent Semantics for Natural Language Understanding
Researcher (PI) Mark STEEDMAN
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Call Details Advanced Grant (AdG), SH4, ERC-2016-ADG
Summary The project addresses the most important open problem in NLP, to develop a robust semantics that is invariant across different linguistic forms within a language and across languages, and embodies aspects of common-sense knowledge. It will be derived by machine-learning from machine-reading of vast amounts of text, using an existing state-of-the-art wide-coverage CCG semantic parser developed under previous ERC funding to the PI, initially to build traditional semantic analyses of sentences relating named entities.
Patterns of entailment across semantic expressions relating the same named entities will be then detected across other entities of the same types, to construct directed entailment graphs. Cliques within the graphs constitute paraphrases, and can be collapsed to a single cluster identifier. The paraphrase-clustered entailment graph can then be used to redefine the semantics delivered by the parser as conjunctions of entailed paraphrase clusters, to make it invariant under paraphrase and common-sense entailment, yet compatible with a traditional logical operator semantics. The semantics will be extended to a wide range of logical operators, including tense, modality, aspect, and voice, and to implicative and evidential verbs, light verbs, multi-word expressions, and idioms. The method will be applied to semantic parsing, machine translation, knowledge-graph query, and the construction of large knowledge graphs or semantic nets from text, using spreading activation to limit growth in costs of updating and querying the knowledge graph.
In the later stages of the project, the paraphrase-clustered entailment semantics will form the bassi for an incremental semantic parser, using a novel shift-reduce architecture proposed for CCG by the PI in 2000, guided by a modern neural network parsing model acting as a categorial "supertagger" and parser action model, for application to language modeling for the machine translation component.
Summary
The project addresses the most important open problem in NLP, to develop a robust semantics that is invariant across different linguistic forms within a language and across languages, and embodies aspects of common-sense knowledge. It will be derived by machine-learning from machine-reading of vast amounts of text, using an existing state-of-the-art wide-coverage CCG semantic parser developed under previous ERC funding to the PI, initially to build traditional semantic analyses of sentences relating named entities.
Patterns of entailment across semantic expressions relating the same named entities will be then detected across other entities of the same types, to construct directed entailment graphs. Cliques within the graphs constitute paraphrases, and can be collapsed to a single cluster identifier. The paraphrase-clustered entailment graph can then be used to redefine the semantics delivered by the parser as conjunctions of entailed paraphrase clusters, to make it invariant under paraphrase and common-sense entailment, yet compatible with a traditional logical operator semantics. The semantics will be extended to a wide range of logical operators, including tense, modality, aspect, and voice, and to implicative and evidential verbs, light verbs, multi-word expressions, and idioms. The method will be applied to semantic parsing, machine translation, knowledge-graph query, and the construction of large knowledge graphs or semantic nets from text, using spreading activation to limit growth in costs of updating and querying the knowledge graph.
In the later stages of the project, the paraphrase-clustered entailment semantics will form the bassi for an incremental semantic parser, using a novel shift-reduce architecture proposed for CCG by the PI in 2000, guided by a modern neural network parsing model acting as a categorial "supertagger" and parser action model, for application to language modeling for the machine translation component.
Max ERC Funding
1 996 792 €
Duration
Start date: 2017-08-01, End date: 2022-07-31
Project acronym XSPECT
Project Expecting Ourselves: Embodied Prediction and the Construction of Conscious Experience
Researcher (PI) Andy CLARK
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Call Details Advanced Grant (AdG), SH4, ERC-2015-AdG
Summary This project (short name, XSPECT) aims to harness the emerging science of the predictive brain to deliver new insights into the nature, scope, mechanisms and (most importantly) the very possibility of conscious experience. The project thus explores and extends the vision of the brain as an inner engine continuously striving to predict the incoming sensory barrage. The key innovation is to consider this increasingly popular vision in the special context of embodied agents able to predict many of their own evolving states and responses – agents able to ‘expect themselves’. These crucial self-expectations span the interoceptive (targeting the internal sensory flows signaling our own physiological states, such as hunger, arousal, itch, and muscular and visceral sensations) and the exteroceptive (targeting the world, and our own behaviors as they might unfold over multiple scales of space and time). XSPECT explores the idea that such interacting states of complex, layered self-prediction hold the key to understanding much that is puzzling about conscious experience.
The project is divided into three simultaneously active sub-projects. The first sub-project concerns relations between prediction, motor action, and experience. The second sub-project targets the role of interoceptive prediction in the construction of experience. The third sub-project considers ways in which more reflective forms of conscious experience (involving agency, selfhood, and the introspection of own experiential states) are further enriched by a spiraling array of socially mediated higher-level self-predictions.
XSPECT will combine integrative philosophical argument, collaborative experimentation, and leading edge interdisciplinary research and discussion, leveraging two very successful but under-communicating research programs (‘embodied cognition’ and ‘the predictive brain’) to offer new perspectives on the puzzle of conscious experience.
Summary
This project (short name, XSPECT) aims to harness the emerging science of the predictive brain to deliver new insights into the nature, scope, mechanisms and (most importantly) the very possibility of conscious experience. The project thus explores and extends the vision of the brain as an inner engine continuously striving to predict the incoming sensory barrage. The key innovation is to consider this increasingly popular vision in the special context of embodied agents able to predict many of their own evolving states and responses – agents able to ‘expect themselves’. These crucial self-expectations span the interoceptive (targeting the internal sensory flows signaling our own physiological states, such as hunger, arousal, itch, and muscular and visceral sensations) and the exteroceptive (targeting the world, and our own behaviors as they might unfold over multiple scales of space and time). XSPECT explores the idea that such interacting states of complex, layered self-prediction hold the key to understanding much that is puzzling about conscious experience.
The project is divided into three simultaneously active sub-projects. The first sub-project concerns relations between prediction, motor action, and experience. The second sub-project targets the role of interoceptive prediction in the construction of experience. The third sub-project considers ways in which more reflective forms of conscious experience (involving agency, selfhood, and the introspection of own experiential states) are further enriched by a spiraling array of socially mediated higher-level self-predictions.
XSPECT will combine integrative philosophical argument, collaborative experimentation, and leading edge interdisciplinary research and discussion, leveraging two very successful but under-communicating research programs (‘embodied cognition’ and ‘the predictive brain’) to offer new perspectives on the puzzle of conscious experience.
Max ERC Funding
1 391 134 €
Duration
Start date: 2017-01-01, End date: 2020-12-31