Both processes can be facilitated if the inputs to the system, representing simultaneously activated memories, possess noisy components. In the binding problem ...
In models of nonlinear oscillatory neurons and neuronal cell assemblies, we represent binding by phase locking of assemblies in different networks, and.
Both processes can be facilitated if the inputs to the system, representing simultaneously activated memories, possess noisy components. In the binding problem ...
Modeling compositionality in biological neural networks by dynamic binding ... The importance of noise for segmentation and binding in dynamical neural systems.
Oct 17, 2024 · We (1) mathematically demonstrate that under realistic assumptions, neural noise can be used to separate objects from each other; (2) that ...
May 11, 2023 · On the other hand, neural noise has been found to help maintain and promote brain function, including shaping resting-state functional networks ...
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We emphasize the importance of fluctuating input signals in producing binding and in enabling segmentation of a large set of common inputs. Segmentation ...
We propose a counter-intuitive computational approach to solving unsupervised perceptual grouping and segmentation: that they arise because of neural noise.
Dec 1, 2021 · Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns.
Emerging phenomena in neural networks with dynamic synapses ...
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The attractor behavior of the recurrent neural network has the important property to complete a memory based on partial or noisy stimulus information. In ...