Unraveling Information Encoding and Representation in Memory Formation and Learning

Understanding how information is encoded and represented in neural circuits during memory formation and learning processes is a fundamental challenge in neuroscience. Neural coding refers to the mechanisms by which the brain translates sensory inputs into meaningful representations, enabling the formation and retrieval of memories. By exploring the neural codes that represent different types of information, researchers aim to decipher the complex orchestration of neural activity underlying cognitive processes. This field of study has significant implications for the development of computational models that mimic the brain's information processing capabilities and can advance our understanding of memory-related disorders.

The goal of this Research Topic is to shed light on the mechanisms by which information is encoded and represented in neural circuits during memory formation and learning. By investigating the neural codes that capture various types of information, we aim to unravel the underlying principles and processes that govern the formation, updating, and retrieval of these representations. This understanding can guide the development of computational models that simulate neuronal activity and provide insights into how memories are stored, consolidated, and retrieved. Ultimately, this research will improve our understanding of the brain's information processing mechanisms and contribute to the development of innovative approaches to memory-related disorders.

This Research Topic invites researchers to contribute original research articles, methodological advancements, reviews, or position papers that explore the neural coding and representations in memory formation and learning. Authors are encouraged to investigate various aspects, including:

· Encoding mechanisms of sensory information
· Temporal dynamics of neural coding
· Plasticity and adaptation of neural representations
· Neural ensemble and population coding
· Decoding and reconstruction of neural representations.

Additionally, authors are encouraged to employ interdisciplinary approaches, utilizing computational modeling, machine learning, and experimental techniques, to address key questions in this field. This Research Topic aims to foster collaboration and exchange of ideas among researchers striving to unravel the neural symphony of memory formation and learning.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: neural coding, information representation, memory formation, learning processes, sensory encoding, temporal dynamics, plasticity, neural ensembles, population coding, decoding algorithms, computational models.

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.