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Concept Formation

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Concept learning through deep reinforcement learning with memory-augmented neural networks.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks have shown superior performance in many regimes to remember familiar patterns with large amounts of data. However, the standard supervised deep learning paradigm is still limited when facing the need to learn new concepts efficie...

Modeling of Brain-Like Concept Coding with Adulthood Neurogenesis in the Dentate Gyrus.

Computational intelligence and neuroscience
Mammalian brains respond to new concepts via a type of neural coding termed "concept coding." During concept coding, the dentate gyrus (DG) plays a vital role in pattern separation and pattern integration of concepts because it is a brain region with...

Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots.

Computational intelligence and neuroscience
This paper proposes an artificial spiking neural network (SNN) sustaining the cognitive abstract process of spatial concept learning, embedded in virtual and real robots. Based on an operant conditioning procedure, the robots learn the relationship o...

Body Patches in Inferior Temporal Cortex Encode Categories with Different Temporal Dynamics.

Journal of cognitive neuroscience
An unresolved question in cognitive neuroscience is how representations of object categories at different levels (basic and superordinate) develop during the course of the neural response within an area. To address this, we decoded categories of diff...

Integrating functional connectivity and MVPA through a multiple constraint network analysis.

NeuroImage
Traditional general linear model-based brain mapping efforts using functional neuroimaging are complemented by more recent multivariate pattern analyses (MVPA) that apply machine learning techniques to identify the cognitive states associated with re...

Tensors and compositionality in neural systems.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Neither neurobiological nor process models of meaning composition specify the operator through which constituent parts are bound together into compositional structures. In this paper, we argue that a neurophysiological computation system cannot achie...

The interplay between multisensory integration and perceptual decision making.

NeuroImage
Facing perceptual uncertainty, the brain combines information from different senses to make optimal perceptual decisions and to guide behavior. However, decision making has been investigated mostly in unimodal contexts. Thus, how the brain integrates...

Above and beyond "Above and beyond the concrete".

The Behavioral and brain sciences
The commentaries address our view of abstraction, our ontology of abstract entities, and our account of predictive cognition as relying on relatively concrete simulation or relatively abstract theory-based inference. These responses revisit classic q...

Philosophical evaluation of the conceptualisation of trust in the NHS' Code of Conduct for artificial intelligence-driven technology.

Journal of medical ethics
The UK Government's Code of Conduct for data-driven health and care technologies, specifically artificial intelligence (AI)-driven technologies, comprises 10 principles that outline a gold-standard of ethical conduct for AI developers and implementer...

Incremental Concept Learning via Online Generative Memory Recall.

IEEE transactions on neural networks and learning systems
The ability to learn more concepts from incrementally arriving data over time is essential for the development of a lifelong learning system. However, deep neural networks often suffer from forgetting previously learned concepts when continually lear...