The need to breathe links the mammalian olfactory system inextricably to the respiratory rhythms that draw air through the nose. In rodents and other small animals, slow oscillations of local field potential activity are driven at the rate of breathing (ϳ2-12 Hz) in olfactory bulb and cortex, and faster oscillatory bursts are coupled to specific phases of the respiratory cycle. These dynamic rhythms are thought to regulate cortical excitability and coordinate network interactions, helping to shape olfactory coding, memory, and behavior. However, while respiratory oscillations are a ubiquitous hallmark of olfactory system function in animals, direct evidence for such patterns is lacking in humans. In this study, we acquired intracranial EEG data from rare patients (Ps) with medically refractory epilepsy, enabling us to test the hypothesis that cortical oscillatory activity would be entrained to the human respiratory cycle, albeit at the much slower rhythm of ϳ0.16 -0.33 Hz. Our results reveal that natural breathing synchronizes electrical activity in human piriform (olfactory) cortex, as well as in limbic-related brain areas, including amygdala and hippocampus. Notably, oscillatory power peaked during inspiration and dissipated when breathing was diverted from nose to mouth. Parallel behavioral experiments showed that breathing phase enhances fear discrimination and memory retrieval. Our findings provide a unique framework for understanding the pivotal role of nasal breathing in coordinating neuronal oscillations to support stimulus processing and behavior.

Motivation Sequence-based protein–protein interaction (PPI) prediction represents a fundamental computational biology problem. To address this problem, extensive research efforts have been made to extract predefined features from the sequences. Based on these features, statistical algorithms are learned to classify the PPIs. However, such explicit features are usually costly to extract, and typically have limited coverage on the PPI information. Results We present an end-to-end framework, PIPR (Protein–Protein Interaction Prediction Based on Siamese Residual RCNN), for PPI predictions using only the protein sequences. PIPR incorporates a deep residual recurrent convolutional neural network in the Siamese architecture, which leverages both robust local features and contextualized information, which are significant for capturing the mutual influence of proteins sequences. PIPR relieves the data pre-processing efforts that are required by other systems, and generalizes well to different application scenarios. Experimental evaluations show that PIPR outperforms various state-of-the-art systems on the binary PPI prediction problem. Moreover, it shows a promising performance on more challenging problems of interaction type prediction and binding affinity estimation, where existing approaches fall short. Availability and implementation The implementation is available at https://github.com/muhaochen/seq_ppi.git. Supplementary information Supplementary data are available at Bioinformatics online.

These findings confirm a functional connection between the amygdala and respiratory control in humans. Moreover, they suggest specific amygdalar nuclei may be critical in mediating this effect and that attentional state is critical to apnea mediated by amygdala activation-perhaps alluding to future development of strategies for the prevention of SUDEP. Ann Neurol 2018;83:460-471.

Previous studies have provided evidence of structural and task-related functional changes in the brains of patients with migraine without aura. Resting-state brain activity in patients with migraine provides clues to the pathophysiology of the disease. However, few studies have focused on the resting-state abnormalities in patients with migraine without aura. In the current study, we employed a data-driven method, regional homogeneity (ReHo), to analyze the local features of spontaneous brain activity in patients with migraine without aura during the resting state. Twenty-six patients with migraine without aura and 26 age-, education- and gender-matched healthy volunteers participated in this study. Compared with healthy controls, patients with migraine without aura showed a significant decrease in ReHo values in the right rostral anterior cingulate cortex (rACC), the prefrontal cortex (PFC), the orbitofrontal cortex (OFC) and the supplementary motor area (SMA). In addition, we found that ReHo values were negatively correlated with the duration of disease in the right rACC and PFC. Our results suggest that the resting-state abnormalities of these regions may be associated with functional impairments in pain processing in patients with migraine without aura. We hope that our results will improve the understanding of migraine.

Given that decreased AD may suggest axonal loss, our findings may reveal axonal loss in MWoA.