Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials.

The trajectory of the somatic membrane potential of a cortical neuron exactly reflects the computations performed on its afferent inputs. However, the spikes of such a neuron are a very low-dimensional and discrete projection of this continually evolving signal. We explored the possibility that the neuron's efferent synapses perform the critical computational step of estimating the membrane potential trajectory from the spikes. We found that short-term changes in synaptic efficacy can be interpreted as implementing an optimal estimator of this trajectory. Short-term depression arose when presynaptic spiking was sufficiently intense as to reduce the uncertainty associated with the estimate; short-term facilitation reflected structural features of the statistics of the presynaptic neuron such as up and down states. Our analysis provides a unifying account of a powerful, but puzzling, form of plasticity.

Auxetic nuclei in embryonic stem cells exiting pluripotency.

Embryonic stem cells (ESCs) self-renew in a state of naïve pluripotency in which they are competent to generate all somatic cells. It has been hypothesized that, before irreversibly committing, ESCs pass through at least one metastable transition state. This transition would represent a gateway for differentiation and reprogramming of somatic cells. Here, we show that during the transition, the nuclei of ESCs are auxetic: they exhibit a cross-sectional expansion when stretched and a cross-sectional contraction when compressed, and their stiffness increases under compression. We also show that the auxetic phenotype of transition ESC nuclei is driven at least in part by global chromatin decondensation. Through the regulation of molecular turnover in the differentiating nucleus by external forces, auxeticity could be a key element in mechanotransduction. Our findings highlight the importance of nuclear structure in the regulation of differentiation and reprogramming.