Amsterdam Neuroscience

Stephen Coombes
Professor of Applied Mathematics in the School of Mathematical Sciences at Nottingham and member of the Brain and Body Centre.

Understanding the effect of white matter delays on large scale brain dynamics
The presence of myelin is a powerful structural factor that controls the conduction speed of mammalian axons. Here, we present perspectives from neural mass and network modelling and develop a new set of mathematical tools able to unravel the contributions of axonal delays to large-scale spatiotemporal patterning of brain activity.  Firstly, we show that the method of harmonic balance is ideally suited to describing delay-induced and delay-modulated periodic oscillations and their linear stability, at both the node and network level.  When combined with numerical continuation techniques this allows us to build the skeleton of a network bifurcation diagram and highlight the role of distance-dependent delays in contributing to novel spatiotemporal patterns arising from the instability of a synchronous state, including travelling periodic waves, alternating anti-phase solutions, cluster states, and more exotic behaviours.  Secondly, we consider reductions to delay differential equation (DDE) systems for the evolution of phases. We highlight that relative equilibria in the form of phase-locked network states (and not just synchrony) can be analysed with many of the standard tools previously developed for the analysis of steady states in more general DDE settings.  Finally, we discuss outstanding challenges for when the delays are plastic and state dependent, and present preliminary results for a new form of biologically motivated white matter plasticity rule. 

Anne van Nifterick
Postdoctoral researcher, Alzheimer Center Amsterdam, Amsterdam UMC.

Unravelling neuronal hyperexcitability in Alzheimer's disease: from networks to genes
Alzheimer’s disease (AD) patients frequently exhibit seizures and subclinical epileptiform abnormalities on electro- and magnetoencephalography (E/MEG) recordings, reflecting network hyperexcitability. However, noninvasive detection of (subclinical) hyperexcitability remains challenging, and understanding of its pathophysiological mechanisms is limited. Using computational modelling, we developed quantitative measures of Excitation/Inhibition (E/I), revealing regional network dysfunction that correlated with tau pathology in AD patients. Cross-species comparison of neurophysiological recordings in mice and humans carrying mutations in the APP and PSEN1 genes revealedspecies-specific differences, highlighting the need for human-specific mechanistic studies. To further validate these network measures, we are comparing E/I measures between AD patients with and without epileptiform abnormalities on E/MEG. To investigate the cellular and molecular mechanisms that could drive hyperexcitability in AD, we will now perform single-cell RNA sequencing in postmortem hippocampal tissue from individuals for whom EEG/MEG recordings were obtained during life. These studies combined will provide validated quantitative E/MEG measures of hyperexcitability and identify cellular mechanisms underlying network dysfunction. These insights will enhance our ability to identify individuals with hyperexcitability using routine E/MEG recordings, and reveal potential target mechanisms for early intervention to normalize neuronal functioning and slow down cognitive decline in AD.