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"Neural representation" is a multidisciplinary book category exploring how information is encoded, transformed, and stored by neural systems—both biological brains "Neural representation" is a cross‑disciplinary book category that examines how information is encoded, transformed, and stored by neural systems—ranging from single neurons and neural populations in biological brains to artificial neural networks. Books in this category cover theories and methods for decoding the neural code (population coding, sparse/dense representations, receptive fields), mathematical and computational models (representational geometry, embeddings, latent spaces), experimental techniques (electrophysiology, imaging, neural decoding), and applications to perception, cognition, memory, and machine learning. Suitable for researchers, advanced students, and technically minded general readers, these titles bridge neuroscience, cognitive science, computer science, and AI to explain how patterns of activity become meaningful representations and how those representations give rise to behavior and intelligence.

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