Peter Zeidman - CMIC/WEISS Joint Seminar Series

Speaker: Peter Zeidman

Title:  Inferring Neural Mechanisms with Variational Bayesian Modelling

Abstract: 

Experimental neuroscience involves testing hypotheses about quantities that cannot be directly observed. Examples of these quantities include the time constants of neural synapses, or the presence of neuropathology or psychopathology that evolves over time. In this talk, I will address the technical challenge of inferring these latent variables and their dynamics from downstream measurements, such as timeseries from medical imaging devices (fMRI, EEG and MEG), behavioural performance and symptom scores. I will review the suite of variational Bayesian modelling approaches implemented in the Statistical Parametric Mapping (SPM) software package, as well as recent applications to multi-modal neuroimaging and longitudinal modelling of psychiatric disease progression.

Bio:

Peter Zeidman is a Senior Independent Research Fellow at the Wellcome Centre for Human Neuroimaging, UCL. He started his training at the University of Birmingham, with a degree in Artificial Intelligence and Computer Science. After working in industry as a software engineering consultant, Peter came to UCL where he studied for an MSc and PhD in neuroscience, specialising in the function of the human hippocampus. Today he chairs the Methods Group, leading the development of tools for modelling neural circuitry, which are made available via the open source Statistical Parameter Mapping (SPM) software package.

Chair: Danny Alexander