One new cucurbitane triterpenoid from the fruits of Momordica charantia

One new cucurbitane triterpenoid commonly named neokuguaglucoside, together with three known compounds momordicoside M, momordicoside N, and momordicoside A were isolated from the fresh fruits of Momordica charantia. The new one's structure with an interesting sugar-like groups attached to the side chain was elucidated by spectroscopic analysis and semiepirical (AM1) quantum chemical method

Mechanisms Of Intrinsic Epileptogenesis In Human Gelastic Seizures With Hypothalamic Hamartoma

Human hypothalamic hamartoma (HH) is a rare developmental malformation often characterized by gelastic seizures, which are refractory to medical therapy. Ictal EEG recordings from the HH have demonstrated that the epileptic source of gelastic seizures lies within the HH lesion itself. Recent advances in surgical techniques targeting HH have led to dramatic improvements in seizure control, which further supports the hypothesis that gelastic seizures originate within the HH. However, the basic cellular and molecular mechanisms of epileptogenesis in this subcortical lesion are poorly understood. Since 2003, Barrow Neurological Institute has maintained a multidisciplinary clinical program to evaluate and treat patients with HH. This program has provided a unique opportunity to investigate the basic mechanisms of epileptogenesis using surgically resected HH tissue. The first report on the electrophysiological properties of HH neurons was published in 2005. Since then, ongoing research has provided additional insights into the mechanisms by which HH generate seizure activity. In this review, we summarize this progress and propose a cellular model that suggests that GABA-mediated excitation contributes to epileptogenesis in HH lesions

Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks

Spiking neural networks (SNNs) are emerging as an energy-efficient alternative to traditional artificial neural networks (ANNs) due to their unique spike-based event-driven nature. Coding is crucial in SNNs as it converts external input stimuli into spatio-temporal feature sequences. However, most existing deep SNNs rely on direct coding that generates powerless spike representation and lacks the temporal dynamics inherent in human vision. Hence, we introduce Gated Attention Coding (GAC), a plug-and-play module that leverages the multi-dimensional gated attention unit to efficiently encode inputs into powerful representations before feeding them into the SNN architecture. GAC functions as a preprocessing layer that does not disrupt the spike-driven nature of the SNN, making it amenable to efficient neuromorphic hardware implementation with minimal modifications. Through an observer model theoretical analysis, we demonstrate GAC's attention mechanism improves temporal dynamics and coding efficiency. Experiments on CIFAR10/100 and ImageNet datasets demonstrate that GAC achieves state-of-the-art accuracy with remarkable efficiency. Notably, we improve top-1 accuracy by 3.10\% on CIFAR100 with only 6-time steps and 1.07\% on ImageNet while reducing energy usage to 66.9\% of the previous works. To our best knowledge, it is the first time to explore the attention-based dynamic coding scheme in deep SNNs, with exceptional effectiveness and efficiency on large-scale datasets.Comment: 12 pages, 7 figure