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Peter Zeidman

Wellcome Centre for Human Neuroimaging, University College London

Builder The claim is about what the hardware does, and the philosophy is left open

Peter Zeidman is a senior researcher at the Wellcome Centre for Human Neuroimaging at University College London and a core developer of the Statistical Parametric Mapping (SPM) software suite. His methodological work focuses on Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB), enabling researchers to infer directed effective connectivity and laminar synaptic gain from functional magnetic resonance imaging and electrophysiological data.

In November 2026, Zeidman co-authored Embodied Dynamic Causal Modelling: Brain and Cardiac Effective Connectivity (bioRxiv 2026.10.27.762241) with Andrew D. Levy, Micah Allen, and Karl J. Friston. The paper extends the neural mass equations of DCM to include peripheral autonomic effectors, uniting five brainstem nuclei, viscerosensory thalamus, and sinoatrial cardiac pacemaker dynamics inside a single variational Bayesian inversion pipeline.

Zeidman carries the Builder classification on this site because his work centers on building the mathematical and software instruments used to measure effective connectivity in living nervous systems. Those causal inversion tools allow empirical consciousness researchers to test whether recurrent cortical-subcortical loops are actively driving behavior or merely covarying with arousal.

Known for. Dynamic Causal Modelling, Parametric Empirical Bayes, Embodied DCM software and statistical methods

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