AIMC Topic: Memory, Short-Term

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Stacked long and short-term memory (SLSTM) - assisted terahertz spectroscopy combined with permutation importance for rapid red wine varietal identification.

Talanta
Mislabeling of low-value red wines as high-value ones is common, which seriously undermines consumer rights and interests. However, traditional sensory and chemical analysis methods have limitations, which highlights the need for novel detection tech...

Development of compositionality through interactive learning of language and action of robots.

Science robotics
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental que...

Random noise promotes slow heterogeneous synaptic dynamics important for robust working memory computation.

Proceedings of the National Academy of Sciences of the United States of America
Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neural circuits perform cognitive tasks. Training such networks to perform tasks that require information main...

Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling.

Brain research bulletin
Working memory, a fundamental cognitive function of the brain, necessitates the evaluation of cognitive load intensity due to limited cognitive resources. Optimizing cognitive load can enhance task performance efficiency by preventing resource waste ...

Multiple constraint network classification reveals functional brain networks distinguishing 0-back and 2-back task.

Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale
Working memory is associated with general intelligence and is crucial for performing complex cognitive tasks. Neuroimaging investigations have recognized that working memory is supported by a distribution of activity in regions across the entire brai...

Estimation of Forces and Powers in Ergometer and Scull Rowing Based on Long Short-Term Memory Neural Networks.

Sensors (Basel, Switzerland)
Analyzing performance in rowing, e.g., analyzing force and power output profiles produced either on ergometer or on boat, is a priority for trainers and athletes. The current state-of-the-art methodologies for rowing performance analysis involve the ...

Biologically plausible gated recurrent neural networks for working memory and learning-to-learn.

PloS one
The acquisition of knowledge and skills does not occur in isolation but learning experiences amalgamate within and across domains. The process through which learning can accelerate over time is referred to as learning-to-learn or meta-learning. While...

Screening for Depression and Anxiety Using a Nonverbal Working Memory Task in a Sample of Older Brazilians: Observational Study of Preliminary Artificial Intelligence Model Transferability.

JMIR formative research
BACKGROUND: Anxiety and depression represent prevalent yet frequently undetected mental health concerns within the older population. The challenge of identifying these conditions presents an opportunity for artificial intelligence (AI)-driven, remote...

Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer's disease and normal aging.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To apply machine learning approaches on EEG event-related oscillations (ERO) to discriminate preclinical Alzheimer's disease (AD) from age- and sex-matched controls.

A digital neuromorphic system for working memory based on spiking neuron-astrocyte network.

Neural networks : the official journal of the International Neural Network Society
Among various types of memory, working memory (WM) plays a crucial role in reasoning, decision-making, and behavior regulation. Neuromorphic computing is a well-established engineering approach that offers promising avenues for advancing our understa...