Goldman MS: Memory without feedback in a neural network. Neuron 2009, 61(4):621‐634.Memory without feedback in a neural network - MS - 2009Goldman MS. Memory without Feedback in a Neural Network. Neuron. 2009; 61(4):621-34. https://doi. org/10.1016/j....
We introduce a new structure for memory neural networks, called feedforward sequential memory networks (FSMN), which can learn long-term dependency without using recurrent feedback. The proposed FSMN is a standard feedforward neural networks equipped with learnable sequential memory blocks in the hidde...
Neurofeedback (NF) training is a closed-loop brain training in which participants learn to regulate their neural activation. NF training of alpha (8–12 Hz) activity has been reported to enhance working memory capacity, but whether it affects the precision in working memory has not yet been...
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed way. Further, synaptic plasticity in the b
In this paper, we propose a novel neural network structure, namely \\emph{feedforward sequential memory networks (FSMN)}, to model long-term dependency in time series without using recurrent feedback. The proposed FSMN is a standard fully-connected feedforward neural network equipped with some ...
We developed a recurrent neural network model of V1 able to learn from feedback experienced over the course of a long-term orientation discrimination experiment. After first exposing the model to one discrimination task for 3480 consecutive trials, we assessed how its performance was affected by ...
Introduction 1.1 Learning in Recurrent Networks Connectionist networks having feedback connections are interesting for a number of reasons. Biological neur... RJ Williams,D Zipser - L. Erlbaum Associates Inc. 被引量: 613发表: 1998年 Short-term memory for serial order: a recurrent neural network ...
Reference Feedback DefinitionNamespace: Microsoft.VisualStudio.Imaging Assembly: Microsoft.VisualStudio.ImageCatalog.dll Package: Microsoft.VisualStudio.ImageCatalog v17.12.40391 C++ 複製 public: static property Microsoft::VisualStudio::Imaging::Interop::ImageMoniker RunMemorySampling { Microsoft::Visual...
Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems that exploit the unique physical properties of nanostructured materials. In addition to their neural network-like physical structure, NWNs also exhibit resistive memory switchin
The cholinergic system is essential for memory. While degradation of cholinergic pathways characterizes memory-related disorders such as Alzheimer’s disease, the neurophysiological mechanisms linking the cholinergic system to human memory remain unknown