Mesoscale Signals in the Human Brain: Multimodal Imaging and Computational Modeling

Date(s) - 01/17/2017
9:30 am

Dora Hermes, Ph.D., Postdoctoral Fellow, Brain Center Rudolf Magnus, University Medical Center Utrecht

Measurements of human brain activity, such as field potentials and the blood oxygen level dependent (BOLD) fMRI response, pool signals over large populations of neurons. Quantitatively modeling these human brain responses is essential to understand how neuronal responses relate to perception and behavior, and how we can incorporate neuronal measurement for clinical applications such as neural prosthetics. I will first describe a series of studies that directly relate the BOLD signal and field potentials measured with electrocorticography (ECoG). Second, rather than directly relating measurements, I will show a computational model that starts with the neuronal population responses, and from this derives predictions of both the BOLD and field potential responses. The results from the model were tested against empirical fMRI and ECoG data recorded in human visual cortex. This model-based approach helps to reconcile a wide range of previous findings. These results show that a combination between multi-modal imaging and quantitative modeling can be used to advance our understanding of typical (and atypical) responses in the human brain. 



Dora Hermes attended college at the University of Utrecht in the Netherlands, where she received her undergraduate
degree and MSc in Neuroscience and Cognition. She continued her graduate training in Neuroscience at the UMC Utrecht. Her post-doctoral work was done at Stanford and NYU and she is now a post-doctoral (veni) fellow at the Brain Center Rudolf Magnus in Utrecht and a visiting fellow at Stanford University. Her research includes multimodal imaging, brain-computer
interfaces and computational modeling of mesoscale signals in the human brain during health and disease.