Objective
The ability to recognise spoken words relies on extracting phonological features from the acoustic input that distinguish a word from its cohort competitors. Neuronal circuits were suggested to use context to predict and pre-activate specific speech features. Bottom-up feature recognition is enabled by phase and amplitude coupling between cortical oscillations and acoustic signals and this process is facilitated by top-down predictive processing. Predictions may be critical for the speed, accuracy and noise resistance that distinguish fluent speech recognition and were related to specific cortical oscillatory patterns (theta/delta synchronisation, beta increase). Despite evidence, the nature and the timing of these predictions remains unclear. This project will address these key questions using MEG and EEG that provide good spatiotemporal resolution. Increasing predictability of a word should have two effects: A) Neuronal populations encoding its phonological form will become active before this word is uniquely identifiable from its potential competitors by bottom-up analysis (uniqueness point UP). Using spatiotemporal multivariate pattern analysis we will test if the latency of phonological feature detection, used for word identification, is modulated by word's contextual predictability. If specific predictions are made, divergence should occur before the UP and should be supported by changes in oscillatory activity; B) Generating predictions should decrease bottom-up feature processing demands. We expect predictability to reduce the phase-amplitude coupling between the speech envelope and the gamma oscillations (a neuronal measure of phonological processing). In summary we aim to identify whether and how context enables predictions of incoming words’ form before it can be acoustically established. This will be critical for understanding the cortical architecture of speech processing with practical applications in artificial speech recognition.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2017
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20009 San Sebastian
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.