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Memory

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Passivity and Passification of Memristor-Based Recurrent Neural Networks With Additive Time-Varying Delays.

IEEE transactions on neural networks and learning systems
This paper presents a new design scheme for the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with additive time-varying delays. The predictable assumptions on the boundedness and Lipschitz continuity of ...

Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays.

IEEE transactions on neural networks and learning systems
In this paper, adaptive synchronization of memristor-based neural networks (MNNs) with time-varying delays is investigated. The dynamical analysis here employs results from the theory of differential equations with discontinuous right-hand sides as i...

Phase Oscillatory Network and Visual Pattern Recognition.

IEEE transactions on neural networks and learning systems
We explore a properly interconnected set of Kuramoto type oscillators that results in a new associative-memory network configuration, which includes second- and third-order additional terms in the Fourier expansion of the network's coupling. Investig...

Humanoid robotics in health care: An exploration of children's and parents' emotional reactions.

Journal of health psychology
A new non-pharmacological method of distraction was tested with 57 children during their annual flu vaccination. Given children's growing enthusiasm for technological devices, a humanoid robot was programmed to interact with them while a nurse admini...

Improving Recall in Sparse Associative Memories That Use Neurogenesis.

Neural computation
The creation of future low-power neuromorphic solutions requires specialist spiking neural network (SNN) algorithms that are optimized for neuromorphic settings. One such algorithmic challenge is the ability to recall learned patterns from their nois...

Heterogeneous Forgetting Rates and Greedy Allocation in Slot-Based Memory Networks Promotes Signal Retention.

Neural computation
A key question in the neuroscience of memory encoding pertains to the mechanisms by which afferent stimuli are allocated within memory networks. This issue is especially pronounced in the domain of working memory, where capacity is finite. Presumably...

A Computational Framework for Memory Engrams.

Advances in neurobiology
Memory engrams in mice brains are potentially related to groups of concept cells in human brains. A single concept cell in human hippocampus responds, for example, not only to different images of the same object or person but also to its name written...

In Silico Clinical Trials: Is It Possible?

Methods in molecular biology (Clifton, N.J.)
Modeling and simulation (M&S), including in silico (clinical) trials, helps accelerate drug research and development and reduce costs and have coined the term "model-informed drug development (MIDD)." Data-driven, inferential approaches are now becom...

Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies.

Neural computation
Catastrophic forgetting remains an outstanding challenge in continual learning. Recently, methods inspired by the brain, such as continual representation learning and memory replay, have been used to combat catastrophic forgetting. Associative learni...

Perception and memory in the medial temporal lobe: Deep learning offers a new lens on an old debate.

Neuron
In this issue of Neuron, Bonnen et al. (2021) use artificial neural networks to resolve a long-standing controversy surrounding the neurocognitive dichotomy between memory and perception. They show that the perirhinal cortex supports performance on t...