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...
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...
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 ...
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...
Dementia and geriatric cognitive disorders
Apr 4, 2018
BACKGROUND: The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) developed a neuropsychological battery (CERAD-NP) to screen patients with Alzheimer's dementia. Mild cognitive impairment (MCI) has received attention as a pre-dementi...
The presented research was conducted in order to investigate the connections between developmental dyslexia and the functioning of verbatim and gist memory traces-assumed in the fuzzy-trace theory. The participants were 71 high school students (33 wi...
Computational intelligence and neuroscience
May 3, 2017
Many models of neural networks have been extended to complex-valued neural networks. A complex-valued Hopfield neural network (CHNN) is a complex-valued version of a Hopfield neural network. Complex-valued neurons can represent multistates, and CHNNs...
Proceedings of the National Academy of Sciences of the United States of America
Mar 14, 2017
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature ...
Clinical nutrition (Edinburgh, Scotland)
Dec 25, 2015
BACKGROUND & AIMS: Epidemiological data of dietary patterns and anaemia among older Chinese remains extremely scarce. We examined the association between dietary patterns and anaemia in older Chinese, and to assess whether biomarkers of serum magnesi...
Learning & memory (Cold Spring Harbor, N.Y.)
Jan 15, 2015
Human memory stores vast amounts of information. Yet recalling this information is often challenging when specific cues are lacking. Here we consider an associative model of retrieval where each recalled item triggers the recall of the next item base...
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