IEEE transactions on neural networks and learning systems
Apr 4, 2025
In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (DSD) technology performs well in computation, programming, and information processing. In this article, the multiplication gate, addition gate, and thr...
IEEE transactions on biomedical circuits and systems
Apr 2, 2025
Associative memory is a cornerstone of cognitive intelligence within the human brain. The Bayesian confidence propagation neural network (BCPNN), a cortex-inspired model with high biological plausibility, has proven effective in emulating high-level ...
Trends in cognitive sciences
Mar 19, 2025
Cognitive neuroscience research has begun to use natural language processing (NLP) to examine memory narratives with the hopes of gaining a nuanced understanding of the mechanisms underlying differences in memory recall, both across groups and tasks....
Proceedings of the National Academy of Sciences of the United States of America
Mar 5, 2025
Despite the impressive performance of biological and artificial networks, an intuitive understanding of how their local learning dynamics contribute to network-level task solutions remains a challenge to this date. Efforts to bring learning to a more...
Nature communications
Mar 4, 2025
The backpropagation method has enabled transformative uses of neural networks. Alternatively, for energy-based models, local learning methods involving only nearby neurons offer benefits in terms of decentralized training, and allow for the possibili...
Materials horizons
Mar 4, 2025
Olfactory memory forms the basis for biological perception and environmental adaptation. Advancing artificial intelligence to replicate this biological perception as artificial olfactory memory is essential. The widespread use of various robotic syst...
Neural networks : the official journal of the International Neural Network Society
Feb 13, 2025
Endowing robots with human-like emotional and cognitive abilities has garnered widespread attention, driving deep investigations into the complexities of these processes. However, few studies have examined the intricate circuits that govern the inter...
IEEE transactions on neural networks and learning systems
Feb 6, 2025
Our brains extract durable, generalizable knowledge from transient experiences of the world. Artificial neural networks come nowhere close to this ability. When tasked with learning to classify objects by training on nonrepeating video frames in temp...
IEEE transactions on neural networks and learning systems
Feb 6, 2025
Spiking neural networks (SNNs) are the basis for many energy-efficient neuromorphic hardware systems. While there has been substantial progress in SNN research, artificial SNNs still lack many capabilities of their biological counterparts. In biologi...
Nature communications
Feb 2, 2025
Current artificial systems suffer from catastrophic forgetting during continual learning, a limitation absent in biological systems. Biological mechanisms leverage the dual representation of specific and generalized memories within corticohippocampal...