Kendrick Kay: Advancing visual and cognitive neuroscience through intensive neuroimaging datasets

University of Minnesota, Department of Radiology, Center for Magnetic Resonance Research

Title:  Advancing visual and cognitive neuroscience through intensive neuroimaging datasets

Abstract:

I will present three diverse lines of work, all sharing the common theme of focusing on data to advance cognitive neuroscience. First, I will summarize the influential large-scale 7T fMRI Natural Scenes Dataset (NSD), which consists of whole-brain BOLD responses while each of 8 participants viewed tens of thousands of natural scenes over the course of 30-40 scan sessions. This dataset exemplifies an 'intensive neuroimaging' approach in which cognitive phenomena are extensively sampled in a small set of individuals in order to support computational modeling and detailed investigation of brain function. Second, although careful quantification and control of visual stimuli have served as the backbone of visual neuroscience, there has been less emphasis on how an observer's task influences the processing of sensory inputs. I will preview an ongoing 7T fMRI data collection effort to broadly sample how different tasks influence stimulus-driven responses in the human brain. Finally, neural response measurements are invariably corrupted by noise, and conventional trial averaging is often insufficient for adequately suppressing noise. I will discuss ongoing development of a new denoising technique based on signal-aware low-rank reconstruction. The method is robust, general (applicable to any data modality), and substantially improves recovery of signal while incurring minimal bias.

 

Guests are welcome!

 

Organized by

Radek Cichy / Lisa Rosenbluhm