Sofia De La Fuente Garcia (PhD, MBPsS, FHEA)

Teaching Fellow in Clinical Psychology

Background

I am a Teaching Fellow in Clinical Psychology, School of Health in Social Science. I support postgraduate students through their studies and am primarily involved in the MSc Mental Health in Children and Young People: Psychological Approaches.

I am originally from Asturias, a green, rainy and beautiful region of Spain, where I lived until I went to university in Madrid. After completing the first year at the medical school, I decided to change degrees, in search for a framework to engage with the study of the human mind and human behaviour, and started Psychology (BSc Hons). This included an Erasmus year at the University of Edinburgh, where I had my first hands-on research experience. Afterwards, I completed a postgraduate on Methodology for Health and Behavioural Sciences (MSc).

After a traineeship on clinical neuroscience research at the Karolinska Institutet, in Stockholm, I moved to Edinburgh in autumn 2016, to start my PhD in language markers for neurodegeneration, with Saturnino Luz and Craig Ritchie, and I have remained here since. The core of my doctoral research consisted of the development of a methodology for monitoring cognitive health through speech, with a focus on neurodegenerative diseases. Afterwards, I worked as a research fellow in Dr. Luz's lab, in order to continue and expand the development of this methodology. Currently, I conduct research on the psychological consequences of lockdown in Scotland, and on the relationship between moral reasoning, personality and attachment. 

A broad interest in psychology and well-being leads my continuos personal and professional development, which includes training in Gestalt psychotherapy and systems and family therapy.

 

CV

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Qualifications

PhD Precision Medicine

MSc Methodology for Behavioural and Health Sciences

BSc (Hons) Psychology

 

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Fellow of the Higher Education Academy

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Diploma on Systemsmand Family Threapy

Gestalt Psychotherapy Foundational course 

 

Responsibilities & affiliations

Graduate member of the British Psychological Society (with basis for chartered membership)

Postgraduate teaching

Teaching Fellow in Clinical Psychology, School of Health in Social Science.

 

 

Open to PhD supervision enquiries?

No

Areas of interest for supervision

Open to topics on attachment psychology,  consciousness, language and the mind.

Research summary

Psychology of mental health, neuroscience, attachment, consciousness, integrated functions of the mind, cognitive evolution.

Current research interests

I currently work on the potential of speech and language for monitoring cognitive health, as well as on the links between language, coping strategies, personality and the psychological consequences of COVID-19. Parallely, I run a project to investigate the associations between moral reasoning, personality and attachment. Areas that I would like to explore in the near future are consciousness, evolution and cognition.

Past research interests

Language and speech as cognitive markers for dementia. Psychophysiology of language comprehension and neuroscience of memory

Project activity

1) PsyVoiD: I lead the psyvoid study, an online study that investigates the links between language, coping strategies, personality and the psychological consequences of COVID-19. Collection of voice and psychological data took place from June 2020 to March 2021.

2) Prevent-ED: I led and coordinated a dialogue sub-study in the Prevent Dementia cohort, based in Edinburgh, in collaboration with Prof Craig Ritchie and the Centre for Dementia Prevention. The connection with Prevent allows us to study language in relationship with a comprehensive database (genetics, cognitive testing, family history of dementia, lifestyle variables), in order to establish the potential of speech and language not only for dementia diagnosis but also for risk modelling. Data collection stopped in March 2020 and the project is currently in the analysis stage.

3) Comparing dementia detection methods across different datasets, particularly diagnosed cohorts (e.g. Pitt Corpus) and healthy cohorts at different levels of risk (i.e. Prevent-ED cohort).

4) ADReSS Challenge 2020 and ADReSSo Challenge 2021 (http://www.homepages.ed.ac.uk/sluzfil/ADReSSo-2021/), organised through the annual Interspeech conference. The overall objective of the these Challenges is to host a shared task and provide a benchmark dataset for the systematic comparison of approaches to the detection of cognitive impairment and decline based on spontaneous speech. 

Past project grants

Transitional Fellowship, 13 months: MRC, grant number MR/N013166/1. The project is also supported by our industrial partner in Japan: PST Inc.
Doctoral training: MRC Precision medicine, 4 years 2016-2020.
Traineeship at Karolinska Institutet, summer 2016: erasmus traineeship and local funding.
Collaborative award by the Universidad Autonoma de Madrid, 2015-2016: financial support for researching at Laboratory of Cognitive and Computational Neuroscience.
Collaborative Award by the Spanish Government, 2014-2015: financial support for researching at Laboratory of Cognitive and Computational Neuroscience.

Participant

Alzheimer's Association Neuroscience Next Online event, November 2020: Factor analysis of prosodic features for predicting risk-factors for dementia in a healthy population.

Prevent General Assembly Online event, September 2020: Investigating the potential of speech features for monitoring cognitive health in dementia.

Scottish Research Dementia Consortium, Glasgow, UK, April 2019: Prevent-ED: investigating dialogue features to prevent dementia.

International Neuropsychological Society Meeting Prague, Czech Republic, July 2018: Natural Language Processing for Cognitive Status Prediction.

10th Dubrovnik Conference on Cognitive Science Dubrovnik, Croatia, May 2018: Evaluating cognition through linguistic features.

2nd Human Brain Project Student Conference Ljubljana, Slovenia, February 2018: Detecting Cognitive Decline through Dialogue Processing.

EU - Latin America Countries Early Career Researchers Integration, Heriot-Watt University, October 2017: Human-Robot interaction: linguistic features as early signs for dementia detection.

  • Deng, Q., Luz, S., & de la Fuente Garcia, S. (2023). Hierarchical attention interpretation: an interpretable speech-level transformer for bi-modal depression detection. arXiv preprint DOI: https://doi.org/10.48550/arXiv.2309.13476 . Submitted to IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP: computation and Language; Sound, Audio and Speech Processing)
  • Luz, S., Haider, F., de la Fuente Garcia, S., Fromm, D., & MacWhinney, B. (2021). Editorial: Alzheimer's Dementia Recognition through Spontaneous Speech. Frontiers in Computer Science. DOI: https://doi.org/10.3389/fcomp.2021.780169
  • de la Fuente Garcia, S., Haider, F. & Luz, S. (2021). COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2326-2329). IEEE. DOI: 10.1109/EMBC46164.2021.9630833
  • Luz, S., Haider, F., de la Fuente Garcia, S., Fromm, D., & MacWhinney, B. (2021). Speech Analysis for Alzheimer's Dementia Recognition. Frontiers in Computer Science, 96.
  • Ambegaonkar, A., Ritchie, C., & de la Fuente Garcia, S. (2021). The Use of Mobile Applications as Communication Aids for People with Dementia: Opportunities and Limitations. Journal of Alzheimer's Disease Reports, (Preprint), 1-12. DOI: 10.3233/ADR-200259
  • de la Fuente Garcia, S., Ritchie, C., & Luz, S. (2020, November). Factor analysis of acoustic-prosodic features as an approach to predicting risk-factors for dementia in a healthy population. In Alzheimer’s Association International Conference (AAIC) Neuroscience Next.  
  • de la Fuente Garcia, S., Ritchie, C. & Luz, S. (2020). Artificial Intelligence, speech and language processing approaches to monitoring Alzheimer's Disease: a systematic review. Journal of Alzheimer's Disease.  DOI: 10.3233/JAD-200888  
  • Luz, S., Haider, F., de la Fuente Garcia, S., Fromm, D., & MacWhinney, B. (2020) Alzheimer's Dementia Recognition Through Spontaneous Speech: The ADReSS Challenge. In Proc. Interspeech 2020, 2172-2176, DOI: 10.21437/Interspeech.2020-2571.    
  • de la Fuente Garcia, S., Haider, F., & Luz, S. (2020). Cross-corpus Feature Learning between Spontaneous Monologue and Dialogue for Automatic Classication of Alzheimer's Dementia Speech. In 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 202) (pp. 5851-5855). 10.1109/EMBC44109.2020.9176305    
  • Haider, F., de la Fuente Garcia, S., Albert, P., & Luz, S. (2020). Afective speech for Alzheimer's dementia recognition. In LREC 2020: Language Resources and Evaluation Conference 11-16 May 2020 (p. 67).    
  • de Frutos-Lucas, J., Lopez-Sanz, D., Cuesta, P., Bruña, R., de la Fuente Garcia, S., Serrano, N., Lopez, M. E., Delgado-Losada, M. L., Lopez-Higes, R., Marcos, A. & Maestu, F. (2020). Enhancement of posterior brain functional networks in bilingual older adults. Bilingualism: Language and Cognition, 23 (2), 387-400.  DOI: 10.1017/S1366728919000178   
  • Haider, F., de La Fuente Garcia, S., & Luz, S. (2019). An Assessment of Paralinguistic Acoustic Features for Detection of Alzheimer's Dementia in Spontaneous Speech. IEEE Journal of Selected Topics in Signal Processing, 14 (2), 272-281. DOI: 10.1109/JSTSP.2019.2955022  
  • de la Fuente Garcia, S., Ritchie, C. W., & Luz, S. (2019). Protocol for a conversation-based analysis study: PREVENT-ED investigates dialogue features that may help predict dementia onset in later life. BMJ open, 9 (3), e026254.  DOI: 10.1136/bmjopen-2018-026254  
  • Luz, S., de la Fuente Garcia, S., & Albert, P. (2018). A method for analysis of patient speech in dialogue for dementia detection. In LREC: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments (RaPID) (pp. 35-42) ELRA.