The Delta of Language
DELTA-LANG aims to predict psychotic relapses by analyzing spontaneous speech through NLP, linking language changes to neural signatures and enabling timely interventions.
Projectdetails
Introduction
Mental life fluctuates, changing from moment to moment as the incessant and turbulent flow of thought rages. In 3% of the world’s population, the fragile equilibrium that we all hope to maintain gives way to dynamical changes resulting in psychotic episodes, which after remission tend to recur over time.
Importance of Prediction
A capacity to predict these episodes at a clinically relevant temporal resolution, similar to our capacity to forecast a thunderstorm, would be a major advance in public health. The important difference is that, unlike thunderstorms, psychosis can be prevented.
Research Hypothesis
We test a previously untested and untestable hypothesis:
- Meaning encoded in spontaneous speech, translated into digitalized quantitative features,
- Computationally analyzed with natural language processing (NLP) tools,
- Can serve as a key personalized and interpretable predictor of phase transitions from remission to psychotic relapse.
Methodological Breakthroughs
Addressing this hypothesis requires conceptual and methodological breakthroughs in our understanding of language and what signals its variability can carry for a pathophysiological process. We pursue these breakthroughs with a synergetic combination of:
- Linguistic insights
- Neuroimaging insights
- Psychiatric insights
- E-health insights
Research Approach
Using a hypothesis-driven approach, we will:
- Define generalizable language metrics relating to symptom variability cross-sectionally.
- Identify individually-specific neural signatures of psychosis and remission related to changes in these linguistic metrics, using a dense-sampling approach.
- Test the metrics retrospectively as predictors of relapse in an independent longitudinal cohort.
- Take the paradigm from the lab to the patient’s home in a prospective clinical study testing whether we can predict state change before it is catastrophic, at the temporal resolutions clinically required.
Conclusion
DELTA-LANG (ΔLANG) thereby identifies the delta of language – a linguistic change that enables the prediction of clinically significant change before it occurs.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 9.939.329 |
Totale projectbegroting | € 9.939.329 |
Tijdlijn
Startdatum | 1-6-2024 |
Einddatum | 31-5-2030 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- ACADEMISCH ZIEKENHUIS GRONINGENpenvoerder
- UNIVERSIDAD POMPEU FABRA
- UNIVERSITAT ZURICH
- UNIVERSITETET I TROMSOE - NORGES ARKTISKE UNIVERSITET
- UMCG RESEARCH BV
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Language in the Dyad. Linking linguistic and neural alignment.This project investigates the relationship between neural and linguistic alignment in dyadic communication using EEG hyper-scanning and interactive language games to enhance understanding of dialogue dynamics. | ERC Consolid... | € 1.997.048 | 2025 | Details |
Making sense of referenceThis project aims to investigate the neural mechanisms of reference construction in grammar during story comprehension in psychosis, using advanced computational models and real-time tracking methods. | ERC Proof of... | € 150.000 | 2025 | Details |
iSPEAK: a Natural Language Processing Study in youth with subclinical psychotic experiencesThe project aims to identify natural language patterns in young people's self-reported psychotic experiences to differentiate between pathological and non-pathological cases for better mental health interventions. | ERC Proof of... | € 150.000 | 2024 | Details |
Aligning Brain Rhythms: Understanding the mechanisms of cortical tracking of speech to improve language functions with real time closed-loop neurofeedbackThis project aims to identify early biomarkers for learning disabilities and enhance language processing through neuroimaging, cortical tracking of speech, and real-time neurofeedback interventions. | ERC Advanced... | € 2.500.000 | 2025 | Details |
Bidirectional Brain/Neural-Computer Interaction for Restoration of Mental HealthThis project aims to develop a portable neuromodulation system using quantum sensors and magnetic stimulation to precisely target brain oscillations for treating mental health disorders. | ERC Consolid... | € 1.999.875 | 2025 | Details |
Language in the Dyad. Linking linguistic and neural alignment.
This project investigates the relationship between neural and linguistic alignment in dyadic communication using EEG hyper-scanning and interactive language games to enhance understanding of dialogue dynamics.
Making sense of reference
This project aims to investigate the neural mechanisms of reference construction in grammar during story comprehension in psychosis, using advanced computational models and real-time tracking methods.
iSPEAK: a Natural Language Processing Study in youth with subclinical psychotic experiences
The project aims to identify natural language patterns in young people's self-reported psychotic experiences to differentiate between pathological and non-pathological cases for better mental health interventions.
Aligning Brain Rhythms: Understanding the mechanisms of cortical tracking of speech to improve language functions with real time closed-loop neurofeedback
This project aims to identify early biomarkers for learning disabilities and enhance language processing through neuroimaging, cortical tracking of speech, and real-time neurofeedback interventions.
Bidirectional Brain/Neural-Computer Interaction for Restoration of Mental Health
This project aims to develop a portable neuromodulation system using quantum sensors and magnetic stimulation to precisely target brain oscillations for treating mental health disorders.
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A novel and accurate emotion recognition system for real-time and continuous patient monitoring in psychiatryCephalgo has developed an AI-driven emotion tracker to remotely monitor patients' emotional status, enhancing treatment effectiveness and reducing trial and error in psychiatric care. | EIC Accelerator | € 2.497.708 | 2023 | Details |
Intelligent psychodiagnostisch platform: Sensor ondersteunde diagnostiekHet project ontwikkelt een diagnostisch platform met camera en slimme software om verbale en non-verbale communicatie te analyseren voor nauwkeurigere psychiatrische diagnoses. | Mkb-innovati... | € 139.335 | 2016 | Details |
YOUR HEALFIE VOICEHet project ontwikkelt een AI-systeem voor stemanalyse om vocale biomarkers te identificeren, met als doel diagnoses te stellen voor onverklaarbare klachten en vroegtijdige signalering van gezondheidsproblemen. | Mkb-innovati... | € 20.000 | 2023 | Details |
A novel and accurate emotion recognition system for real-time and continuous patient monitoring in psychiatry
Cephalgo has developed an AI-driven emotion tracker to remotely monitor patients' emotional status, enhancing treatment effectiveness and reducing trial and error in psychiatric care.
Intelligent psychodiagnostisch platform: Sensor ondersteunde diagnostiek
Het project ontwikkelt een diagnostisch platform met camera en slimme software om verbale en non-verbale communicatie te analyseren voor nauwkeurigere psychiatrische diagnoses.
YOUR HEALFIE VOICE
Het project ontwikkelt een AI-systeem voor stemanalyse om vocale biomarkers te identificeren, met als doel diagnoses te stellen voor onverklaarbare klachten en vroegtijdige signalering van gezondheidsproblemen.