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Distributional reinforcement learning in prefrontal cortex
The prefrontal cortex is crucial for learning and decision-making. Classic reinforcement learning (RL) theories center on learning the expectation of...
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Timescales of learning in prefrontal cortex
The lateral prefrontal cortex (PFC) in humans and other primates is critical for immediate, goal-directed behaviour and working memory, which are...
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The Role of the Human Cerebellum for Learning from and Processing of External Feedback in Non-Motor Learning: A Systematic Review
This review aimed to systematically identify and comprehensively review the role of the cerebellum in performance monitoring, focusing on learning...
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Multi-contrast learning-guided lightweight few-shot learning scheme for predicting breast cancer molecular subtypes
Invasive gene expression profiling studies have exposed prognostically significant breast cancer subtypes: normal-like, luminal, HER-2 enriched, and...
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Motor learning drives dynamic patterns of intermittent myelination on learning-activated axons
Myelin plasticity occurs when newly formed and pre-existing oligodendrocytes remodel existing patterns of myelination. Myelin remodeling occurs in...
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Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning
The large amount of training samples required to develop a deep learning brain injury model demands enormous computational resources. Here, we study...
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Meta-reinforcement learning via orbitofrontal cortex
The meta-reinforcement learning (meta-RL) framework, which involves RL over multiple timescales, has been successful in training deep RL models that...
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Climbing fibers provide essential instructive signals for associative learning
Supervised learning depends on instructive signals that shape the output of neural circuits to support learned changes in behavior. Climbing fiber...
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Harnessing deep learning for population genetic inference
In population genetics, the emergence of large-scale genomic data for various species and populations has provided new opportunities to understand...
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Implicit reward-based motor learning
Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can...
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A Review of Machine Learning Algorithms for Biomedical Applications
As the amount and complexity of biomedical data continue to increase, machine learning methods are becoming a popular tool in creating prediction...
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Goal-directed learning in adolescence: neurocognitive development and contextual influences
Adolescence is a time during which we transition to independence, explore new activities and begin pursuit of major life goals. Goal-directed...
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Big data and deep learning for RNA biology
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries....
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Inferring neural activity before plasticity as a foundation for learning beyond backpropagation
For both humans and machines, the essence of learning is to pinpoint which components in its information processing pipeline are responsible for an...
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Deep-learning-enabled antibiotic discovery through molecular de-extinction
Molecular de-extinction aims at resurrecting molecules to solve antibiotic resistance and other present-day biological and biomedical problems. Here...
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Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques
The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test...
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A novel paradigm for observational learning in rats
The ability to learn by observing the behavior of others is energy efficient and brings high survival value, making it an important learning tool...
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The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke
BackgroundRobots can generate rich kinematic datasets that have the potential to provide far more insight into impairments than standard clinical...
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Medial entorhinal cortex mediates learning of context-dependent interval timing behavior
Episodic memory requires encoding the temporal structure of experience and relies on brain circuits in the medial temporal lobe, including the medial...
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Advances in AI and machine learning for predictive medicine
The field of omics, driven by advances in high-throughput sequencing, faces a data explosion. This abundance of data offers unprecedented...
