Results 121 to 130 of about 15,760 (244)
Metaplastic Breast Cancer [PDF]
Mayo Clinic Proceedings, 2021 Beiyun Chen, Lori A. Erickson
openaire +3 more sources
Using Neural Networks to Simulate the Alzheimer's Disease [PDF]
, 2008 Making use of biologically plausible artificial neural networks that implement Grossberg’s presynaptic learning rule, we simulate the possible effects of calcium dysregulation in the neuron’s activation function, to represent the most accepted model of ...
Andina de la Fuente, Diego +3 more
core
Nanogenerator-induced synaptic plasticity and metaplasticity of bio-realistic artificial synapses
, 2017 A bio-realistic artificial synapse integrated with a nanogenerator (NG), which can be used in neuromorphic systems, is demonstrated for self-powered biomedical devices in this study.
Bo-Yun Kim +6 more
semanticscholar +1 more source
Computational principles of biological memory [PDF]
arXiv, 2015 Memories are stored, retained, and recollected through complex, coupled processes operating on multiple timescales. To understand the computational principles behind these intricate networks of interactions we construct a broad class of synaptic models that efficiently harnesses biological complexity to preserve numerous memories.
arxiv
A State of Mediocrity in Art [PDF]
, 2014 Recently, art works that make trajectories in a situation fragmented by postmodernism as a reaction to modernism, have risen. They show trajectory of travels over different time and different space. Allochronic or multiplicity makes it possible.
Takehara, Shinji
core
Sparse distributed representation, hierarchy, critical periods, metaplasticity: the keys to lifelong fixed-time learning and best-match retrieval [PDF]
arXiv, 2018 Among the more important hallmarks of human intelligence, which any artificial general intelligence (AGI) should have, are the following. 1. It must be capable of on-line learning, including with single/few trials. 2. Memories/knowledge must be permanent over lifelong durations, safe from catastrophic forgetting.
arxiv
A Model of Fast Hebbian Spike Latency Normalization
Frontiers in Computational Neuroscience, 2017 Hebbian changes of excitatory synapses are driven by and enhance correlations between pre- and postsynaptic neuronal activations, forming a positive feedback loop that can lead to instability in simulated neural networks.
Hafsteinn Einarsson +4 more
doaj +1 more source
Synaptic consolidation across multiple timescales
Frontiers in Systems Neuroscience, 2014 The brain is bombarded with a continuous stream of sensory events, but retains only a small subset in memory. The selectivity of memory formation prevents our memory from being overloaded with irrelevant items that would rapidly bring the brain to its ...
Lorric Ziegler
doaj +1 more source
Materiality and human cognition [PDF]
, 2019 In this paper, we examine the role of materiality in human cognition. We address issues such as the ways in which brain functions may change in response to interactions with material forms, the attributes of material forms that may cause change in brain ...
Overmann, Karenleigh, Wynn, Thomas
core
Probabilistic Metaplasticity for Continual Learning with Memristors [PDF]
arXivEdge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge to achieve this, as continual learning entails memory and computational overhead.
arxiv