Primary Supervisor: Dr Davinia Fernandez-Espejo, School of Psychology
Secondary supervisors: Dr Magdalena Chechlacz, School of Psychology
PhD project title: Using multimodal neuroimaging to predict individual responses to electrical brain stimulation
University of Registration: University of Birmingham
Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that is able to modulate neural excitability and plasticity by delivering a small current via electrodes placed on the scalp. Importantly, tDCS can safely be delivered in the MRI scanner, thus enabling us to interfere with and manipulate brain function while we record these changes in real time. This allow us to establish causal inferences between changes in specific networks and resulting behaviour, which has drastically changed the fields of psychology and cognitive neuroscience. Moreover, tDCS’ ability to induce plastic changes has led to exciting new avenues for therapeutic interventions in psychiatric and neurologic conditions.
While there is vast evidence supporting that tDCS can modulate brain function and cognition, these effects are highly heterogeneous across subjects. Recent research has suggested that the variability in responsiveness to tDCS may arise due to the effect of individual anatomical differences in the distribution of current across the brain. Indeed, there is evidence that cranial and meningeal thickness, volume of cerebrospinal fluid, and cortical folding can induce variance in electric field in neurotypical individuals. These effects are exacerbated in clinical populations where differences in brain morphology and microstructure are more pronounced (as a result of damage). Moreover, there is increasing evidence that differences in the functional state of the brain at baseline, and during stimulation, may influence subsequent responses to tDCS.
The main aim of this PhD project is to understand and characterise individual variations in behavioural and neural effects of tDCS, and to identify biomarkers that can predict whether an individual will be likely to respond to a particular stimulation protocol. To fully characterise individual differences in neural architecture, the student will focus on advanced analyses of structural and functional MRI data (i.e., cortical thickness, tractography, and functional and effective connectivity at rest). The student will assess how differences in the neuroanatomy and function of specific networks modulate individual responses to stimulation. Specifically, they will pool metrics extracted from the above MRI modalities and test the power for different classification techniques (i.e., Support Vector Machines, and Deep Learning). Additionally, the student will explore the construction of Decision Tree classifiers. These provide explicit information about why the algorithm came to a particular classification decision and, thus, can have higher value in medical contexts, where justification can be very important.
This project will use existing data, collected as part of an ongoing grant with the primary supervisor as PI (Medical Research Council [MRC]; 2017-2021). This will ensure resilience to potential disruptions to data collection related to the current pandemic. Additionally, the student will be able to test their methods in a cohort of patients with severe brain injury.
Reducing the variability in responses to tDCS by using protocols that are tailored to each individual will not only advance applications for investigating how different cognitive functions emerge in the brain but also increase the effectiveness of therapeutic interventions across neurologic and psychiatric conditions.
- Datta, A., Baker, J. M., Bikson, M., & Fridriksson, J. (2011). Individualized model predicts brain current flow during transcranial direct-current stimulation treatment in responsive stroke patient. Brain stimulation, 4(3), 169–174. https://doi.org/10.1016/j.brs.2010.11.001
- Laakso, I., Tanaka, S., Koyama, S., De Santis, V., & Hirata, A. (2015). Inter-subject Variability in Electric Fields of Motor Cortical tDCS. Brain stimulation, 8(5),906–913. https://doi.org/10.1016/j.brs.2015.05.002
- Wiethoff, S., Hamada, M., & Rothwell, J. C. (2014). Variability in response to transcranial direct current stimulation of the motor cortex. Brain stimulation, 7(3), 468–475. https://doi.org/10.1016/j.brs.2014.02.003
BBSRC Strategic Research Priority: Understanding the Rules of Life: Neuroscience and behaviour
Techniques that will be undertaken during the project:
- Structural magnetic resonance imaging
- Diffusion Weighted Imaging
- Functional magnetic resonance imaging (fMRI).
- Non-invasive brain stimulation (i.e., transcranial direct current stimulation)
- Advanced signal processing and statistical analyses.
- Computational modelling