The psychometric function describes how an experimental variable, such as stimulus
strength, influences the behaviour of an observer. Estimation of psychometric functions from …

We demonstrate unprecedented accuracy for rapid gravitational wave parameter estimation
with deep learning. Using neural networks as surrogates for Bayesian posterior distributions…

Scientists and engineers employ stochastic numerical simulators to model empirically
observed phenomena. In contrast to purely statistical models, simulators express scientific …

Neurons in the neocortex code and compute as part of a locally interconnected population.
Large-scale multi-electrode recording makes it possible to access these population …

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging
cellular structures with nanometer resolution, but standard analysis algorithms require sparse …

Deep neural networks progressively transform their inputs across multiple processing layers.
What are the geometrical properties of the representations learned by these networks? …

Behavior relies on the distributed and coordinated activity of neural populations. Population
activity can be measured using multi-neuron recordings and neuroimaging. Neural …

Spike trains recorded from populations of neurons can exhibit substantial pairwise correlations
between neurons and rich temporal structure. Thus, for the realistic simulation and …

Mechanistic models of single-neuron dynamics have been extensively studied in
computational neuroscience. However, identifying which models can quantitatively reproduce …

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial
heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, …