The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Evidence from multiple model systems supports a shift away from heme transport and toward metabolic dysfunction and oxidative stress as key drivers of TANGO2 deficiency.

It is remarkable that Raman spectra can, with the help of statistical inference, be used to predict cellular physiology and proteome composition. By making this possible, the work of Kamei et al. has ...

In visual cortex, neural correlates of subjective perception can be generated by modulation of activity from beyond the classical receptive field (CRF). In macaque V1, activity generated by ...

Veronika Koren talks about pursuing a theory of neural coding that doesn’t fit a simple narrative, and the resilience it took to see it through.

Pupil dilation provides a physiological readout of information gain during the brain's internal process of belief updating in the context of associative learning.

Collagen is the most abundant protein in the human body and has an important role in healthy tissue as well as in a range of prevalent diseases. Medical research and diagnostics hence call for means ...

This is an important study on the sensory roles of Cerebrospinal fluid-contacting neurons (CBF-cn) in mammals. The authors identify PKD2L1 as the predominant pH-sensing channel CBF-cn and show how the ...

Nucleosomes are barriers to RNA Polymerase II (Pol II) transcribing along gene bodies in eukaryotes. We found that a fragile “tailless nucleosome” could be generated to resolve the Pol II pausing ...

Antigen-driven TCR signaling in the epidermis during CD8+ TRM differentiation results in a lower TGFβ requirement for persistence and increased proliferative capacity that together enhance epidermal ...

A conserved signaling axis linking Drosophila adipose tissue to nephrocyte function reveals how obesity can drive kidney dysfunction and points to new opportunities for therapeutic intervention.

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...