Title:Uncovering Low-dimensional Manifolds of Neural
Dynamics for Motor-Imagery based Stroke
Rehabilitation: An EEG-based Brain-Computer
Interface Study
Abstract: Stroke rehabilitation aims to repair neural circuits and dynamics through the
remapping of neuronal functions. However, there is currently a gap in understanding
the alteration of neural population dynamics-the fundamental computational unit
driving functions-under clinical settings. In this talk, I will present a novel method that
we developed to identify stable low-dimensional structures of neural population
dynamics in Stroke patients during motor tasks. We applied this method on whole-
brain EEG recordings collected in our lab from chronic stroke patients performing
motor imagery (MI) tasks before and after brain-computer interface (BCI) training, as
well as on a public EEG dataset of acute stroke patients performing MI tasks. Our
analysis revealed three key findings: (1) For right-handed patients, task-related low-
dimensional dynamics in the left motor cortex remain stable across subjects, with its
features holding potential as biomarkers for stroke rehabilitation; (2) BCI training
promotes global and sustained restoration of neural population dynamics; (3) EEG
theta-band oscillations show strong correlation with these dynamics, highlighting their
macroscopic nature. This study proposes a new, simple, and powerful tool for
comprehension and validation of stroke rehabilitation mechanisms confirming the
effectiveness of BCI training in restoring neural dynamics. Bio:Prof. Sadia Shakil is a Research Assistant Professor of Biomedical Engineering at
the Chinese University of Hong Kong (CUHK). Before joining CUHK she has
worked as a Senior Researcher in the Faculty of Information Technology at Brno
University of Technology in Czech Republic, as an Adjunct Research Associate
with the Turner Institute of Brain & Mental Health at the Monash University in
Australia, and as an Assistant Professor of Electrical Engineering at the Institute of Space Technology in Pakistan. She was also the founding director of the 'Bio-signal Processing
and Computational Neuroscience' lab at the Institute of Space Technology in Pakistan. Prof. Shakil
has successfully supervised theses of more than forty undergraduate and graduate students.
Prof. Shakil completed her PhD in Electrical and Computer Engineering from Georgia Institute
of Technology after securing a Fulbright Scholarship award. Her focus during PhD was to analyse
and develop algorithms for the study of spatiotemporal dynamics in brain networks. Prof. Shakil did
her postdoctoral fellowship in ‘Computational Connectomics’ from Rotman Research Institute at the
Baycrest Health Sciences in Canada, after securing Schlumberger Faculty for the Future Fellowship
award. During Postdoc, her focus was to understand the relationship between brain and behaviour
using brain data collected during music listening.
Prof. Shakil’s research is highly inter- and multi-disciplinary, and she works with multiple
neuroimaging data modalities such MRI, fMRI, and EEG. Her research focus is on integrating AI
and algorithms from other domains to study brain structural and functional dynamics. She is working
on various mental and brain health issues such as stress, stroke, brain tumour, Alzheimer's disease,
and harmful effects of naturalistic stimuli such as movies on mental health.
