Michael Fauth

TL;DR: This work proposes a simple algorithm that extracts and processes object contexts from an image database and yields semantic vectors for objects, and shows empirically that these representations exhibit on par performance with state-of-the-art distributional models over a set of conventional objects.

TL;DR: A biophysical model that links spine shape fluctuations to the dynamics of the spine’s actin-based cytoskeleton and provides a quantitative characterization of the link between spine morphology and the underlying molecular processes forms an essential step towards a better understanding of synaptic transmission during steady state but also during synaptic plasticity.

TL;DR: In this paper, a biophysical model of spine shape fluctuations was proposed, which reproduces experimentally measured spine fluctuations and predicts that the actin dynamics underlying shape fluctuations self-organizes into a critical state, which creates a fine balance between static actin filaments and free monomers.

TL;DR: In this system the conflict of rapid spine turnover (probabilities) and long-term memory is resolved by storing the information collaboratively in multiple synapses by using the bimodal stationary distributions as the working point.