AIMC Topic: Memory, Episodic

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Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework.

JMIR medical informatics
BACKGROUND: In recent years, the incidence of cognitive diseases has also risen with the significant increase in population aging. Among these diseases, Alzheimer disease constitutes a substantial proportion, placing a high-cost burden on health care...

Defining individualized theta frequency for memory modulation: A machine learning approach across brain states and regions.

NeuroImage
Recent transcranial alternating current stimulation (tACS) studies suggest that theta-frequency stimulation can modulate memory performance, with evidence highlighting individual variability in optimal stimulation frequency. However, it remains uncle...

The effect of stress on prospective memory in robotic command and control.

Cognitive research: principles and implications
Remembering to carry out an intention at the appropriate time (prospective memory-PM) requires attentional resources that may be limited in stressful circumstances. PM failures in high-risk/high stress environments, such as military operations, can h...

Hippocampal blood oxygenation predicts choices about everyday consumer experiences: A deep-learning approach.

Proceedings of the National Academy of Sciences of the United States of America
This research investigates the neurophysiological mechanisms of experiential versus monetary choices under risk. While ventral striatum and insula activity are instrumental in predicting monetary choices, we find that hippocampal activity plays a key...

Assessing autobiographical memory consistency: Machine and human approaches.

Behavior research methods
Memory is far from a stable representation of what we have encountered. Over time, we can forget, modify, and distort the details of our experiences. How autobiographical memory-the memories we have for our personal past-changes has important ramific...

Temporal interactions between neural proxies for memory recall, negative affect, and emotion regulation in major depression.

Molecular psychiatry
Dysfunction in emotion regulation (ER) and autobiographical memory are components of major depressive disorder (MDD). However, little is known about how they mechanistically interact with mood disturbances in real time. Using machine learning-based n...

Using machine learning to simultaneously quantify multiple cognitive components of episodic memory.

Nature communications
Why do we remember some events but forget others? Previous studies attempting to decode successful vs. unsuccessful brain states to investigate this question have met with limited success, potentially due, in part, to assessing episodic memory as a u...

An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.

Asian journal of psychiatry
BACKGROUND: Individuals with anxious-depressed (AD) symptoms have more severe mood disorders and cognitive impairment than those with non-anxious depression (NAD) symptoms. Therefore, it is important to clarify the underlying neurophysiology of these...

Computational models suggest that human memory judgments exhibit interference due to the use of overlapping representations.

Psychological review
Episodic memory is a core function that allows us to remember the events of our lives. Given that many events in our life contain overlapping elements (e.g., similar people and places), it is critical to understand how well we can remember the specif...

Elements of episodic memory: insights from artificial agents.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Many recent artificial intelligence (AI) systems take inspiration from biological episodic memory. Here, we ask how these 'episodic-inspired' AI systems might inform our understanding of biological episodic memory. We discuss work showing that these ...