Understanding how networks of neurons in the brain convey and process information requires recording neural activity with high spatial and temporal resolution. Conventional imaging methods such as fMRI or PET are cumbersome, expensive, and cannot be applied in freely moving subjects.
Functional UltraSound imaging (fUSI) is a novel ultrasound-based technology that allows us to monitor brain-wide neuronal activity through changes in local hemodynamics (activated brain regions require higher blood flow than non-activated regions). Coupled with video recordings of small animal experiments, the setup allows the researchers to map the brain activity to distinct movements/behavior of laboratory animals. However, such setup requires (1) accurate automatic segmentation of smallest brain blood vessels in fUSI (often obstructed with noise and unequal contrast), (2) automatic detection of animal movements in recorded videos, and (3) mapping between the detected brain activations and animal movements. Such a complex setup is still not in place, and most of the processing steps are still performed manually, which is cumbersome and time-consuming. Therefore, there is an urgent need for automatic image processing and analysis methods to segment brain blood vessels in fUSI and movement/gesture detection for animal studies.
Neuro-Electronics Research Flanders (NERF) group of IMEC-VIB-KU Leuven has vast experience developing the fUSI technology and conducting animal studies to detect and link brain activity to animal behavior. NERF team recently developed volumetric (3D in time) fUSI (vfUSI) for imaging large-scale functional networks in real-time and at high spatial resolution (up to 100 μm3 voxel size). Such an abundance of data requires accurate and automatic image processing techniques. The Image Processing and Interpretation group of IMEC has been working on several biomedical and medical image processing and analysis applications and has a long-standing experience in the field.
We are looking for a motivated Ph.D. candidate interested in pushing the fUSI technology to the forefront of functional brain imaging. You will:
1. Develop novel image segmentation and analysis methods to allow for efficient and accurate brain activation detection.
2. Develop novel methods for gesture/movement detection in videos of experimental animals.
3. Design methods to perform the mapping between the detected brain activations and detected animal actions.
Graphical abstract shows the mapping of brain activity during a water droplet reaching task by combining fUSI and video markerless motion tracking.