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Memory

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Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework.

Cognition
Emotional arousal often facilitates memory for some aspects of an event while impairing memory for other aspects of the same event. Across three experiments, we found that emotional arousal amplifies competition among goal-relevant representations, s...

Modelling PTSD diagnosis using sleep, memory, and adrenergic metabolites: An exploratory machine-learning study.

Human psychopharmacology
OBJECTIVE: Features of posttraumatic stress disorder (PTSD) typically include sleep disturbances, impaired declarative memory, and hyperarousal. This study evaluated whether these combined features may accurately delineate pathophysiological changes ...

Gated Orthogonal Recurrent Units: On Learning to Forget.

Neural computation
We present a novel recurrent neural network (RNN)-based model that combines the remembering ability of unitary evolution RNNs with the ability of gated RNNs to effectively forget redundant or irrelevant information in its memory. We achieve this by e...

Estimating Scale-Invariant Future in Continuous Time.

Neural computation
Natural learners must compute an estimate of future outcomes that follow from a stimulus in continuous time. Widely used reinforcement learning algorithms discretize continuous time and estimate either transition functions from one step to the next (...

Continual lifelong learning with neural networks: A review.

Neural networks : the official journal of the International Neural Network Society
Humans and animals have the ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. This ability, referred to as lifelong learning, is mediated by a rich set of neurocognitive mechanisms that together c...

Dreaming neural networks: Forgetting spurious memories and reinforcing pure ones.

Neural networks : the official journal of the International Neural Network Society
The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is α∼0.14, far from the theoretical bound for symme...

Clone-Based Encoded Neural Networks to Design Efficient Associative Memories.

IEEE transactions on neural networks and learning systems
In this paper, we introduce a neural network (NN) model named clone-based neural network (CbNN) to design associative memories. Neurons in CbNN can be cloned statically or dynamically which allows to increase the number of data that can be stored and...

A small-world topology enhances the echo state property and signal propagation in reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Cortical neural connectivity has been shown to exhibit a small-world (SW) network topology. However, the role of the topology in neural information processing remains unclear. In this study, we investigated the learning performance of an echo state n...

Self-limited single nanowire systems combining all-in-one memristive and neuromorphic functionalities.

Nature communications
The ability for artificially reproducing human brain type signals' processing is one of the main challenges in modern information technology, being one of the milestones for developing global communicating networks and artificial intelligence. Electr...

Perceptual Decision-Making: Biases in Post-Error Reaction Times Explained by Attractor Network Dynamics.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Perceptual decision-making is the subject of many experimental and theoretical studies. Most modeling analyses are based on statistical processes of accumulation of evidence. In contrast, very few works confront attractor network models' predictions ...