73 research outputs found
Conditional Intensity and Gibbsianness of Determinantal Point Processes
The Papangelou intensities of determinantal (or fermion) point processes are
investigated. These exhibit a monotonicity property expressing the repulsive
nature of the interaction, and satisfy a bound implying stochastic domination
by a Poisson point process. We also show that determinantal point processes
satisfy the so-called condition which is a general form of
Gibbsianness. Under a continuity assumption, the Gibbsian conditional
probabilities can be identified explicitly.Comment: revised and extende
On infinite-volume mixing
In the context of the long-standing issue of mixing in infinite ergodic
theory, we introduce the idea of mixing for observables possessing an
infinite-volume average. The idea is borrowed from statistical mechanics and
appears to be relevant, at least for extended systems with a direct physical
interpretation. We discuss the pros and cons of a few mathematical definitions
that can be devised, testing them on a prototypical class of infinite
measure-preserving dynamical systems, namely, the random walks.Comment: 34 pages, final version accepted by Communications in Mathematical
Physics (some changes in Sect. 3 -- Prop. 3.1 in previous version was
partially incorrect
Spatial point process theory
No abstract
A Bayesian approach to modelling heterogeneous calcium responses in cell populations
Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory. To achieve this goal it is necessary to reliably predict the temporal evolution of calcium spike sequences for a given stimulus. Here, we propose a modelling framework that allows us to quantitatively describe the timing of calcium spikes. Using a Bayesian approach, we show that Gaussian processes model calcium spike rates with high fidelity and perform better than standard tools such as peri-stimulus time histograms and kernel smoothing. We employ our modelling concept to analyse calcium spike sequences from dynamically-stimulated HEK293T cells. Under these conditions, different cells often experience diverse stimuli time courses, which is a situation likely to occur in vivo. This single cell variability and the concomitant small number of calcium spikes per cell pose a significant modelling challenge, but we demonstrate that Gaussian processes can successfully describe calcium spike rates in these circumstances. Our results therefore pave the way towards a statistical description of heterogeneous calcium oscillations in a dynamic environmen
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