Foraging Under Uncertainty Follows the Marginal Value Theorem with Bayesian Updating of Environment Representations.

Foraging theory has been a remarkably successful approach to understanding the behavior of animals in many contexts. In patch-based foraging contexts, the marginal value theorem (MVT) shows that the optimal strategy is to leave a patch when the marginal rate of return declines to the average for the environment. However, the MVT is only valid in deterministic environments whose statistics are known to the forager; naturalistic environments seldom meet these strict requirements.

Borrelia-specific antibody profiles and complement deposition in joint fluid distinguish antibiotic-refractory from -responsive Lyme arthritis.

Lyme arthritis, caused by the spirochete is the most common feature of late disseminated Lyme disease in the United States. While most Lyme arthritis resolves with antibiotics, termed "antibiotic-responsive", some individuals develop progressive synovitis despite antibiotic therapy, called "antibiotic-refractory" Lyme arthritis (LA). The primary drivers behind antibiotic-refractory arthritis remain incompletely understood.

ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks.

Deep neural networks have demonstrated improved performance at predicting sequence specificities of DNA- and RNA-binding proteins. However, it remains unclear why they perform better than previous methods that rely on k-mers and position weight matrices. Here, we highlight a recent deep learning-based software package, called ResidualBind, that analyzes RNA-protein interactions using only RNA sequence as an input feature and performs global importance analysis for model interpretability.

Electrocorticography Analysis in Patients With Dual Neurostimulators Supports Desynchronization as a Mechanism of Action for Acute Vagal Nerve Stimulator Stimulation.

Purpose: Both vagal nerve stimulation (VNS) and responsive neurostimulation (RNS System) are treatment options for medically refractory focal epilepsy. The mechanism of action of both devices remains poorly understood. Limited prior evidence suggests that acute VNS stimulation may reduce epileptiform activity and cause EEG desynchronization on electrocorticography (ECoG).

Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks.

Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability methods, such as attribution methods, can be employed to identify motif-like representations along a given sequence. Because explanations are given on an individual sequence basis and can vary substantially across sequences, deducing generalizable trends across the dataset and quantifying their effect size remains a challenge.

Vagus nerve stimulation induces widespread cortical and behavioral activation.

Vagus nerve stimulation (VNS) is used for management of a variety of neurological conditions, although the therapeutic mechanisms are not fully understood. Accumulating evidence suggests that VNS may modulate cortical state and plasticity through activation of broadly projecting neuromodulatory systems. Using a mouse model, we compared arousal-linked behaviors with dorsal cortical activity obtained with widefield and two-photon GCaMP6s calcium imaging and electrophysiological recordings.

Distinct Waking States for Strong Evoked Responses in Primary Visual Cortex and Optimal Visual Detection Performance.

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, this variability is rarely characterized across the full spectrum of waking states, leaving the characteristics of the optimal state for sensory processing unresolved.