AIMC Topic: Mental Recall

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Chinese Emergency Event Recognition Using Conv-RDBiGRU Model.

Computational intelligence and neuroscience May 21, 2020
In view of the weak generalization of traditional event recognition methods, the limitation of dependence on field knowledge of expert, the longer train time of deep neural network, and the problem of gradient dispersion, the neural network joint mod...
Humans Neural Networks, Computer Machine Learning Databases, Genetic Asian People Semantics Mental Recall Research Design Computer Simulation Learning Recognition, Psychology
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From spatial navigation via visual construction to episodic memory and imagination.

Biological cybernetics Apr 13, 2020
This hybrid of review and personal essay argues that models of visual construction are essential to extend spatial navigation models to models that link episodic memory and imagination. The starting point is the TAM-WG model, combining the Taxon Affo...
Animals Rats Cognition Models, Neurological Humans Computer Simulation Mental Recall Imagination Spatial Navigation Visual Pathways Brain Mapping Robotics Memory, Episodic
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Using machine learning analyses to explore relations between eyewitness lineup looking behaviors and suspect guilt.

Law and human behavior Feb 27, 2020
OBJECTIVE: We conducted 2 experiments using machine learning to better understand which lineup looking behaviors postdict suspect guilt., Hypotheses: We hypothesized that (a) lineups with guilty suspects would be subject to shorter viewing duration o...
Criminal Law Adolescent Child Support Vector Machine Recognition, Psychology Guilt Decision Making Mental Recall Female Humans Machine Learning Young Adult Male
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Gated spiking neural network using Iterative Free-Energy Optimization and rank-order coding for structure learning in memory sequences (INFERNO GATE).

Neural networks : the official journal of the International Neural Network Society Sep 25, 2019
We present a framework based on iterative free-energy optimization with spiking neural networks for modeling the fronto-striatal system (PFC-BG) for the generation and recall of audio memory sequences. In line with neuroimaging studies carried out in...
Reinforcement, Psychology Memory, Short-Term Neurons Mental Recall Humans Prefrontal Cortex Action Potentials Neural Networks, Computer Learning
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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 Action Potentials Bayes Theorem Neural Networks, Computer Models, Neurological Memory Mental Recall Association Learning
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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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Spatiotemporal discrimination in attractor networks with short-term synaptic plasticity.

Journal of computational neuroscience May 27, 2019
We demonstrate that a randomly connected attractor network with dynamic synapses can discriminate between similar sequences containing multiple stimuli suggesting such networks provide a general basis for neural computations in the brain. The network...
Long-Term Synaptic Depression Computer Simulation Animals Neural Pathways Cognition Mental Recall Humans Electrophysiological Phenomena Neurons Neuronal Plasticity Neural Networks, Computer Machine Learning Synapses Decision Making Algorithms
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Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings.

Journal of neural engineering Sep 13, 2018
OBJECTIVE: We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordin...
Electrodes, Implanted Theta Rhythm Algorithms Stochastic Processes Computer Simulation Deep Learning Humans Memory, Episodic Support Vector Machine Logistic Models Mental Recall Predictive Value of Tests Electroencephalography
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The computerized scoring algorithm for the autobiographical memory test: updates and extensions for analyzing memories of English-speaking adults.

Memory (Hove, England) Aug 6, 2018
The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In ...
United States Cognition Emotions Cues Female Adult Male Memory, Episodic Mental Recall Humans Machine Learning Algorithms
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Dynamics of brain activity reveal a unitary recognition signal.

Journal of experimental psychology. Learning, memory, and cognition Jul 19, 2018
Dual-process models of recognition memory typically assume that independent familiarity and recollection signals with distinct temporal profiles can each lead to recognition (enabling 2 routes to recognition), whereas single-process models posit a un...
Models, Psychological Adult Recognition, Psychology Memory, Episodic Electroencephalography Humans Mental Recall Cerebral Cortex Machine Learning Young Adult
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