AIMC Topic: Memory

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Zebrafish exhibit associative learning for an aversive robotic stimulus.

Lab animal Aug 10, 2020
Zebrafish have quickly emerged as a species of choice in preclinical research, holding promise to advance the field of behavioral pharmacology through high-throughput experiments. Besides biological and heuristic considerations, zebrafish also consti...
Animals Memory Conditioning, Classical Avoidance Learning Robotics Zebrafish Fear
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Exploiting defective RRAM array as synapses of HTM spatial pooler with boost-factor adjustment scheme for defect-tolerant neuromorphic systems.

Scientific reports Jul 16, 2020
A crossbar array architecture employing resistive switching memory (RRAM) as a synaptic element accelerates vector-matrix multiplication in a parallel fashion, enabling energy-efficient pattern recognition. To implement the function of the synapse in...
Memory Neocortex Neural Networks, Computer Synapses Humans Software Transistors, Electronic Computer Simulation Algorithms Pattern Recognition, Automated Data Management Data Accuracy
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Generation of Scale-Invariant Sequential Activity in Linear Recurrent Networks.

Neural computation May 20, 2020
Sequential neural activity has been observed in many parts of the brain and has been proposed as a neural mechanism for memory. The natural world expresses temporal relationships at a wide range of scales. Because we cannot know the relevant scales a...
Linear Models Memory Rats Exercise Test Neurons Neural Networks, Computer Brain Animals
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A Mathematical Analysis of Memory Lifetime in a Simple Network Model of Memory.

Neural computation May 20, 2020
We study the learning of an external signal by a neural network and the time to forget it when this network is submitted to noise. The presentation of an external stimulus to the recurrent network of binary neurons may change the state of the synapse...
Neuronal Plasticity Memory Mathematical Concepts Humans Neural Networks, Computer Computer Simulation Animals
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Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses.

Scientific reports May 15, 2020
Spiking neural networks (SNN) are computational models inspired by the brain's ability to naturally encode and process information in the time domain. The added temporal dimension is believed to render them more computationally efficient than the con...
Humans Neural Networks, Computer Algorithms Neurons Synapses Pattern Recognition, Automated Brain Action Potentials Supervised Machine Learning Memory
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Network Dynamics Governed by Lyapunov Functions: From Memory to Classification.

Trends in neurosciences May 5, 2020
In 1982, John Hopfield published a neural network model for memory retrieval, a model that became a cornerstone in theoretical neuroscience. In a recent paper, Krotov and Hopfield built on these early studies and showed how a network that incorporate...
Learning Memory Neural Networks, Computer Algorithms
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Neural memory plasticity for medical anomaly detection.

Neural networks : the official journal of the International Neural Network Society Apr 18, 2020
In the domain of machine learning, Neural Memory Networks (NMNs) have recently achieved impressive results in a variety of application areas including visual question answering, trajectory prediction, object tracking, and language modelling. However,...
Brain Neoplasms Magnetic Resonance Imaging Neuronal Plasticity Electroencephalography Attention Memory Neural Networks, Computer Machine Learning Databases, Factual Humans
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Neuronal mechanisms for sequential activation of memory items: Dynamics and reliability.

PloS one Apr 16, 2020
In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions: activation of regular or irregular sequences....
Cerebral Cortex Memory Synaptic Transmission Humans Animals Neural Networks, Computer Models, Neurological Reproducibility of Results Neurons
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Multiple-target tracking in human and machine vision.

PLoS computational biology Apr 9, 2020
Humans are able to track multiple objects at any given time in their daily activities-for example, we can drive a car while monitoring obstacles, pedestrians, and other vehicles. Several past studies have examined how humans track targets simultaneou...
Cognition Brain Vision, Ocular Motion Memory Animals Video Recording Humans Neurosciences Image Processing, Computer-Assisted Artificial Intelligence Algorithms
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Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Artificial intelligence in medicine Jan 21, 2020
Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, lo...
Adult Sleep Wake Disorders Male Autonomic Nervous System Middle Aged Humans Parkinson Disease Female Disease Progression Machine Learning Affect Anxiety Aged Prognosis Memory Cognition Aged, 80 and over
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