Results 41 to 50 of about 22,581 (258)
Advancing Neural Networks: Innovations and Impacts on Energy Consumption
Advanced Electronic MaterialsThe energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level.
Alina Fedorova +9 more
doaj +1 more source
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage
Brain SciencesBackground: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing ...
Yongqiang Zhang +5 more
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Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA
FEBS Open Bio, EarlyView.Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley +1 more source
High-performance deep spiking neural networks with 0.3 spikes per neuron
Nature CommunicationsCommunication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks.
Ana Stanojevic +5 more
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Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi +8 more
wiley +1 more source
Improving Spiking Neural Network Performance with Auxiliary Learning
Machine Learning and Knowledge Extraction, 2023 The use of back propagation through the time learning rule enabled the supervised training of deep spiking neural networks to process temporal neuromorphic data. However, their performance is still below non-spiking neural networks. Previous work pointed
Paolo G. Cachi +2 more
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Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks [PDF]
Frontiers in Computational Neuroscience, 2015 Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as ...
Daniel de Santos-Sierra +4 more
openaire +4 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Variants in SLC6A1, encoding the GABA transporter 1 (GAT‐1), cause epilepsy, autism spectrum disorder, and developmental delay via loss of GABA uptake, impaired trafficking, and ER retention. We previously found that 4‐Phenylbutyrate (PBA), an FDA‐approved drug, restores GABA uptake and reduces seizures in SLC6A1‐related disorders ...
Melissa B. DeLeeuw +5 more
wiley +1 more source
Sparse Computation in Adaptive Spiking Neural Networks
Frontiers in Neuroscience, 2019 Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a computationally and ...
Davide Zambrano +4 more
doaj +1 more source