Connectionists: Essex BCI-NE webinar: EEG markers of chronic pain: repeatability challenges by Aleksandra Vuckovic

[Perdikis, Serafeim]

https://www.linkedin.com/company/essex-bcine-lab/

The Essex BCI-NE Lab invites you to join our next monthly webinar:
EEG markers of chronic pain: repeatability challenges

Delivered by

Prof Aleksandra Vuckovic
James Watt School of Engineering, University of Glasgow, Scotland, United Kingdom

The webinar will take place over Zoom on Wednesday, 15th April 2026, at 2 PM UK time
RSVP: https://www.linkedin.com/events/7447896566465667073<https://www.linkedin.com/events/7447896566465667073?viewAsMember=true>


Abstract: Electroencephalography (EEG) holds significant potential for identifying diagnostic, predictive, and prognostic biomarkers across a range of neurological conditions. Most EEG-based biomarkers rely on developing classifiers that can distinguish individuals with specific neurological disorders. Typically, classifier performance is validated using leave-one-out or N-fold cross-validation, where training and testing datasets are collected under the same conditions—recorded in the same environment, by the same experimenters, and using the same EEG equipment. However, real-world clinical applications require accurate classification of entirely unseen datasets that do not share hidden common features with the training data. Most classifiers based on N-fold cross-validation fail to repeat performance on a new dataset. Using the example of central neuropathic pain, Prof. Vuckovic will illustrate the challenges involved in developing a machine learning approach capable of classifying unseen datasets of comparable size to the training set, collected at different times and under varying environmental conditions.


Speaker Biography: Aleksandra Vuckovic holds an MEng in Engineering Physics and an MSc in Control Systems from the University of Belgrade. She received her Ph.D. from the Centre for Sensory-Motor Interaction, Aalborg University, Denmark in 2004, where she has also served as post-doc. Between 2005 and 2007 she worked as a senior research officer at the Brain-Computer Interface Group, Department of Computer Science, University of Essex. Since 2008 she has been with the James Watt School of Engineering, University of Glasgow. Aleksandra is interested in Brain-Computer Interface (BCI) as a new form of non-muscular channel for communication between patients and their environment, which compensates a loss of sensory-motor functions or alternatively provides strengthening or modulation of preserved neuro-muscular pathways in patients with impairments of the Central Nervous System. She is in particular interested in developing and implementing patient-managed Brain-Computer Interface systems for home-based neurorehabilitation. Further areas of interest are improvements of existing rehabilitation therapies combining Brain-Computer Interface and Functional Electrical Stimulation and exploring a correlation between the recovery and changes in the brain responses i.e., brain plasticity. She also applies BCI for operant conditioning training of the brain (neurofeedback) for the treatment of Central Neuropathic pain following injuries to the Spinal Cord. Her research further focuses on EEG as a neuroimaging modality to identify markers of neuropathic pain (diagnostic, predictive, and prognostic). She uses machine learning techniques to develop transferable individualized markers of pain to aid stratified pain prevention and treatment.

The Essex BCI-NE Lab webinars series takes place monthly (usually, on the second or third Wednesday of the month) over Zoom and is open to all. Speakers are invited to talk about their research for 45-50 minutes followed by Q&A.

Where speakers allow it, we record the talks and make them available to everyone on our YouTube channel. You can watch previous talks at: https://www.youtube.com/@essexbcis

If you don’t want to miss our next webinars, please email serafeim.perdikis at essex.ac.uk to ask to be added to our webinars mailing list.

Best wishes,
Simis


Dr Serafeim Perdikis, Associate Professor (Senior Lecturer)
Brain-Computer Interfaces and Neural Engineering Laboratory
School of Computer Science and Electronic Engineering
University of Essex
Wivenhoe Park, Colchester CO4 3SQ
United Kingdom
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