Results 41 to 50 of about 27,240 (263)

Encountering Spiking Neural Networks

Visual Anthropology Review, 2023
AbstractOver the past two decades, the term “intelligent media” has surfaced to describe media that take on problematics of cognition, communication, and sensory perception loosely modeled after human intelligence. Taking the form of hardware‐software assemblages, these novel media demonstrate forms of autonomy that challenge human control and herald a
Alexandre Saunier, David Howes
openaire   +1 more source

Spiking Neural Network Pressure Sensor

Neural Computation
Abstract Von Neumann architecture requires information to be encoded as numerical values. For that reason, artificial neural networks running on computers require the data coming from sensors to be discretized. Other network architectures that more closely mimic biological neural networks (e.g., spiking neural networks) can be simulated ...
Markiewicz, Michał, Brzozowski, Ireneusz, Janusz, Szymon   +2 more
openaire   +3 more sources

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

RIPK4 function interferes with melanoma cell adhesion and metastasis

Molecular Oncology, EarlyView.
RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski, Sławomir Lasota, Ewelina Madej, Anna A. Brożyna, Małgorzata Szczygieł, Agnieszka Harazin‐Lechowska, Jan Czerbniak, Janusz Rys, Jaroslaw Czyz, Agnieszka Wolnicka‐Glubisz   +9 more
wiley   +1 more source

Hepatic encephalopathy detection using deep learning based optimized spiking neural network

Measurement: Sensors
Hepatic encephalopathy is caused by liver insufficiency or poor portal-systemic blood flow. In this work, a novel optimized spiking neural network (OSNN) is used to classify normal and HE cases by using CT images.
R.K. Shanmugha Priya, Dr K. Suthendran
doaj   +1 more source

Spiking Neural Networks Trained via Proxy

IEEE Access, 2022
We propose a new learning algorithm to train spiking neural networks (SNN) using conventional artificial neural networks (ANN) as proxy. We couple two SNN and ANN networks, respectively, made of integrate-and-fire (IF) and ReLU neurons with the same network architectures and shared synaptic weights.
Kheradpisheh, Saeed Reza, Mirsadeghi, Maryam, Masquelier, Timothee   +2 more
openaire   +5 more sources

Visual Recovery Reflects Cortical MeCP2 Sensitivity in Rett Syndrome

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Rett syndrome (RTT) is a devastating neurodevelopmental disorder with developmental regression affecting motor, sensory, and cognitive functions. Sensory disruptions contribute to the complex behavioral and cognitive difficulties and represent an important target for therapeutic interventions.
Alex Joseph Simon, Nathalie Picard, Valeria d'Andrea, Enchi Chang, Joseph Leffler, Eleonora Centofante, Matthew Taylor, Francesca Bardi, Francesca Cavicchiolo, Takao K. Hensch, Stefano Panzeri, Chinfei Chen, Michela Fagiolini   +12 more
wiley   +1 more source

Constructing an Associative Memory System Using Spiking Neural Network

Frontiers in Neuroscience, 2019
Development of computer science has led to the blooming of artificial intelligence (AI), and neural networks are the core of AI research. Although mainstream neural networks have done well in the fields of image processing and speech recognition, they do
Hu He, Yingjie Shang, Xu Yang, Yingze Di, Jiajun Lin, Yimeng Zhu, Wenhao Zheng, Jinfeng Zhao, Mengyao Ji, Liya Dong, Ning Deng, Yunlin Lei, Zenghao Chai   +12 more
doaj   +1 more source

Training a digital model of a deep spiking neural network using backpropagation [PDF]

E3S Web of Conferences, 2020
Deep spiking neural networks are one of the promising eventbased sensor signal processing concepts. However, the practical application of such networks is difficult with standard deep neural network training packages.
Bondarev V
doaj   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source