
Center for Medical Physics and Biomedical Engineering
siddharth.mittal@meduniwien.ac.at
Keywords
Brain Mapping; Functional Magnetic Resonance; Functional Neuroimaging; Retinotopy; Ultrahigh field MRI; Visual Cortex; Visual Perception
Research group(s)
- Functional Magnetic Resonance Imaging
Head: Christian Windischberger
Research Area: Mapping the functional organization of the human brain
Members:
Research interests
I study how the brain processes visual information by mapping the connection between the visual field and brain activity. This process, known as visual mapping, helps us understand how different areas of the brain respond to what we see. To achieve this, I use the population receptive field (pRF) approach, which estimates how regions in the visual cortex respond to visual stimuli based on functional MRI (fMRI) data.
My research focuses on improving the accuracy and reliability of pRF mapping by refining estimation methods and addressing variability in measurements. A key challenge in this field is the lack of ground truth data for validation. To overcome this, I am developing a validation framework for systematically evaluating pRF models and visual stimulation patterns.
By combining statistical modelling, High-Performance Computing (using GPUs), and neuroimaging principles, I aim to improve visual mapping techniques and contribute to advancements in vision science and clinical research.
Techniques, methods & infrastructure
Data is collected using 3T and 7T MRI scanners, which provide high-resolution functional MRI (fMRI) signals for retinotopy experiments. To process and analyze large-scale fMRI data, I utilize HPC systems equipped with GPU clusters. Parallelized computing with CUDA enables efficient pRF model fitting, significantly reducing computation time. I work with programming languages such as C++ and Python to develop and optimize analysis pipelines. The understanding of MR physics and fMRI helps me interpret signal properties, noise, and scanner settings. By combining advanced imaging, fast computing, and neuroimaging expertise, I aim to improve pRF mapping for both research and clinical use.
Selected publications
- Mittal, S. et al. (2024) ‘A novel approach for population-receptive field mapping using high-performance computing’, Journal of Vision, 24(10), p. 536. Available at: https://doi.org/10.1167/jov.24.10.536.