AIMC Topic: Association 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...
Neural Networks, Computer Models, Neurological Memory Conditioning, Classical Association Learning Action Potentials Neurons Synapses
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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...
Algorithms Pattern Recognition, Automated Humans Models, Statistical Association Learning Unsupervised Machine Learning Neural Networks, Computer
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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...
Humans Association Learning Neural Networks, Computer Memory
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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...
Avoidance Learning Association Learning Signal Detection, Psychological Reinforcement, Psychology Conditioning, Classical Olfactory Receptor Neurons Neuropil Conditioning, Operant Afferent Pathways Mushroom Bodies Synapses Signal-To-Noise Ratio Drosophila melanogaster Olfactory Perception Nerve Net Environment Models, Neurological Reward Odorants Animals Deep Learning
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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...
Learning Animals Neuronal Plasticity Memory Temporal Lobe Association Learning Neural Networks, Computer
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Associative Learning Should Go Deep.

Trends in cognitive sciences Jun 28, 2017
Conditioning, how animals learn to associate two or more events, is one of the most influential paradigms in learning theory. It is nevertheless unclear how current models of associative learning can accommodate complex phenomena without ad hoc repre...
Animals Association Learning Humans Neural Networks, Computer
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Multivoxel Object Representations in Adult Human Visual Cortex Are Flexible: An Associative Learning Study.

Journal of cognitive neuroscience Feb 2, 2016
Learning associations between co-occurring events enables us to extract structure from our environment. Medial-temporal lobe structures are critical for associative learning. However, the role of the ventral visual pathway (VVP) in associative learni...
Neuropsychological Tests Young Adult Photic Stimulation Adult Pattern Recognition, Visual Male Humans Visual Cortex Support Vector Machine Female Brain Mapping Association Learning Magnetic Resonance Imaging Linear Models Repetition Priming Multivariate Analysis
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Cross-validation of matching correlation analysis by resampling matching weights.

Neural networks : the official journal of the International Neural Network Society Dec 22, 2015
The strength of association between a pair of data vectors is represented by a nonnegative real number, called matching weight. For dimensionality reduction, we consider a linear transformation of data vectors, and define a matching error as the weig...
Models, Theoretical Humans Support Vector Machine Neural Networks, Computer Association Learning Probability
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Memory Stacking in Hierarchical Networks.

Neural computation Dec 14, 2015
Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to stud...
Neurons Synapses Memory Models, Neurological Humans Neural Networks, Computer Action Potentials Association Learning Brain Computer Simulation
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