AIMC Topic: Association Learning

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Sparse coding with a somato-dendritic rule.

Neural networks : the official journal of the International Neural Network Society Jun 26, 2020
Cortical neurons are silent most of the time: sparse activity enables low-energy computation in the brain, and promises to do the same in neuromorphic hardware. Beyond power efficiency, sparse codes have favourable properties for associative learning...
Humans Neuronal Plasticity Dendrites Association Learning Neural Networks, Computer Machine Learning Feedback
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Probabilistic associative learning suffices for learning the temporal structure of multiple sequences.

PloS one Aug 1, 2019
From memorizing a musical tune to navigating a well known route, many of our underlying behaviors have a strong temporal component. While the mechanisms behind the sequential nature of the underlying brain activity are likely multifarious and multi-s...
Humans Neural Networks, Computer Models, Neurological Action Potentials Bayes Theorem Memory Mental Recall Association Learning
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Artificial neural networks reveal individual differences in metacognitive monitoring of memory.

PloS one Jul 31, 2019
Previous work supports an age-specific impairment for recognition memory of pairs of words and other stimuli. The present study tested the generalization of an associative deficit across word, name, and nonword stimulus types in younger and older adu...
Memory Recognition, Psychology Association Learning Metacognition Neural Networks, Computer Age Factors Female Memory Disorders Aged Individuality Humans Middle Aged Aged, 80 and over Adolescent Young Adult Adult
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Nonmonotonic Plasticity: How Memory Retrieval Drives Learning.

Trends in cognitive sciences Jul 26, 2019
What are the principles that govern whether neural representations move apart (differentiate) or together (integrate) as a function of learning? According to supervised learning models that are trained to predict outcomes in the world, integration sh...
Mental Recall Association Learning Humans Machine Learning
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Robust Associative Learning Is Sufficient to Explain the Structural and Dynamical Properties of Local Cortical Circuits.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jul 3, 2019
The ability of neural networks to associate successive states of network activity lies at the basis of many cognitive functions. Hence, we hypothesized that many ubiquitous structural and dynamical properties of local cortical networks result from as...
Conditioning, Classical Association Learning Neural Networks, Computer Synapses Memory Models, Neurological Action Potentials Neurons
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A neural network architecture for learning word-referent associations in multiple contexts.

Neural networks : the official journal of the International Neural Network Society May 27, 2019
This article proposes a biologically inspired neurocomputational architecture which learns associations between words and referents in different contexts, considering evidence collected from the literature of Psycholinguistics and Neurolinguistics. T...
Humans Association Learning Machine Learning Linguistics
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Deep associative neural network for associative memory based on unsupervised representation learning.

Neural networks : the official journal of the International Neural Network Society Feb 1, 2019
This paper presents a deep associative neural network (DANN) based on unsupervised representation learning for associative memory. In brain, the knowledge is learnt by associating different types of sensory data, such as image and voice. The associat...
Humans Neural Networks, Computer Pattern Recognition, Automated Association Learning Algorithms Models, Statistical Unsupervised Machine Learning
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Clone-Based Encoded Neural Networks to Design Efficient Associative Memories.

IEEE transactions on neural networks and learning systems Jan 28, 2019
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...
Association Learning Neural Networks, Computer Memory Humans
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Deep(er) Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jul 13, 2018
Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptabl...
Olfactory Receptor Neurons Neuropil Synapses Conditioning, Operant Animals Association Learning Reinforcement, Psychology Signal-To-Noise Ratio Afferent Pathways Deep Learning Signal Detection, Psychological Drosophila melanogaster Mushroom Bodies Conditioning, Classical Reward Models, Neurological Olfactory Perception Avoidance Learning Odorants Nerve Net Environment
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Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Neuron Jun 14, 2018
The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both lea...
Temporal Lobe Animals Association Learning Neural Networks, Computer Neuronal Plasticity Memory Learning
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