AIMC Topic: Memory

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Dynamic brain mechanisms supporting salient memories under cortisol.

Science advances
Cortisol is known to promote memory for emotionally arousing experiences, yet the neural networks involved in enhancing these memories are unknown. Here, we combine pharmacological fMRI with an analysis approach to determine the dynamic brain network...

Similarity as likelihood ratio: Coupling representations from machine learning (and other sources) with cognitive models.

Psychonomic bulletin & review
Similarity lies at the core of theories of memory and perception. To understand similarity relations among complex items like text and images, researchers often rely on machine learning to derive high-dimensional vector representations of those items...

Electromechanically induced membrane restructuring enables learning and memory.

Proceedings of the National Academy of Sciences of the United States of America
Human neural networks of interconnected neurons have evolved to be remarkably efficient and are capable of learning and memory through the brain's synaptic plasticity, including short-term plasticity (STP), and long-term potentiation (LTP) and depres...

Two-factor synaptic consolidation reconciles robustness with pruning and homeostatic scaling.

Proceedings of the National Academy of Sciences of the United States of America
Memory consolidation refers to a process of engram reorganization and stabilization that is thought to occur primarily during sleep through a combination of neural replay, homeostatic plasticity, synaptic maturation, and pruning. From a computational...

LyricEmotionNet for robust emotion recognition with hybrid CapsNet-memory network architecture.

Scientific reports
With the rapid development of music streaming platforms, accurate understanding of lyric emotions has become crucial for enhancing personalized services in music recommendation systems. However, existing methods show significant limitations in proces...

Advancing Cell Therapy to Enhance Passive Avoidance Memory: Integrative Approaches Combining Neural-Like Cells and Rosmarinic Acid Through Behavioral, Molecular, and Histological Analyses.

Neurochemical research
Alzheimer's disease (AD) is characterized by progressive neurodegeneration, synaptic dysfunction, and cognitive decline. Regenerative strategies aim to replace lost neurons and modulate the inflammatory milieu to restore neural networks. This study e...

Judgments of learning distinguish humans from large language models in predicting memory.

Scientific reports
Large language models (LLMs) increasingly mimic human cognition in various language-based tasks. However, their capacity for metacognition-particularly in predicting memory performance-remains unexplored. Here, we introduce a cross-agent prediction m...

Route-centric ant-inspired memories enable panoramic route-following in a car-like robot.

Nature communications
Solitary foraging ants excel at route following using minimal neural resources, Robots don't. Recent biological studies proposed lateralized, nest-centric memories to explain ants' direct visual homing but did not address how ants follow curved visua...

The evolution of discrimination under finite memory constraints.

Scientific reports
We develop an evolutionary model for individual discriminatory behavior that emerges naturally in a mixed population as an adaptive strategy. Our findings show that, when individuals have finite memory and face uncertain environments, they may rely o...

Reinforced Odor Representations in the Anterior Olfactory Nucleus Can Serve as Memory Traces for Conspecifics.

eNeuro
Recognition of conspecific individuals in mammals is an important skill, thought to be mediated by a distributed array of neural networks, including those processing olfactory cues. Recent data from our groups have shown that social memory can be sup...