AIMC Topic: Memory, Episodic

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Decoding intracranial EEG data with multiple kernel learning method.

Journal of neuroscience methods
BACKGROUND: Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their app...

Cognitively impaired elderly exhibit insulin resistance and no memory improvement with infused insulin.

Neurobiology of aging
Insulin resistance is a risk factor for Alzheimer's disease (AD), although its role in AD etiology is unclear. We assessed insulin resistance using fasting and insulin-stimulated measures in 51 elderly subjects with no dementia (ND; n = 37) and with ...

Episodic Memory-Double Actor-Critic Twin Delayed Deep Deterministic Policy Gradient.

Neural networks : the official journal of the International Neural Network Society
Existing deep reinforcement learning (DRL) algorithms suffer from the problem of low sample efficiency. Episodic memory allows DRL algorithms to remember and use past experiences with high return, thereby improving sample efficiency. However, due to ...

Replay as a Basis for Backpropagation Through Time in the Brain.

Neural computation
How episodic memories are formed in the brain is a continuing puzzle for the neuroscience community. The brain areas that are critical for episodic learning (e.g., the hippocampus) are characterized by recurrent connectivity and generate frequent off...

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Cerebral cortex (New York, N.Y. : 1991)
Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode im...

Identifying Mild Cognitive Impairment by Using Human-Robot Interactions.

Journal of Alzheimer's disease : JAD
BACKGROUND: Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associated with global population aging has spurred the development of new digital tools for the assessmen...

Identification of the Neural Circuit Underlying Episodic Memory Deficit in Amnestic Mild Cognitive Impairment via Machine Learning on Gray Matter Volume.

Journal of Alzheimer's disease : JAD
Based on whole-brain gray matter volume (GMV), we used relevance vector regression to predict the Rey's Auditory Verbal Learning Test Delayed Recall (AVLT-DR) scores of individual amnestic mild cognitive impairment (aMCI) patient. The whole-brain GMV...

Memory and mental time travel in humans and social robots.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
From neuroscience, brain imaging and the psychology of memory, we are beginning to assemble an integrated theory of the brain subsystems and pathways that allow the compression, storage and reconstruction of memories for past events and their use in ...

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification.

Journal of Alzheimer's disease : JAD
BACKGROUND: Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient manage...

Neural activity reveals interactions between episodic and semantic memory systems during retrieval.

Journal of experimental psychology. General
Whereas numerous findings support a distinction between episodic and semantic memory, it is now widely acknowledged that these two forms of memory interact during both encoding and retrieval. The precise nature of this interaction, however, remains p...