Neural coding, a cornerstone in neuroscience, investigates how neurons encode sensory data and transmit it through networks to create meaningful sensory representations. This collection of articles delves into recent advancements in neural coding principles that underpin sensation, exploring diverse coding strategies and their roles in generating responses to sensory stimuli. At its core, neural coding seeks to characterize how stimuli relate to individual or collective neuronal responses, as well as the interconnected electrical activity within neural ensembles. Sensory information from the periphery travels through synaptically linked neurons, with each neuron encoding information by modulating the rate and timing of its action potentials. Changes in spiking patterns across neuronal populations form the basis of sensory representations. Sensory coding elucidates how various stimuli are encoded through distinct neural activity patterns and how single-trial neural activity is utilized to inform behavioral decisions. Recent progress underscores the concept of multiplexed encoding, where different neural codes operating on various timescales encode complementary stimulus features, collectively enhancing the system's encoding capacity. Consequently, there is a pressing need to further investigate neural coding principles and the contributions of each neural code to the overall response to sensory stimuli across various sensory systems. The development of hardware implementations of neural codes is crucial for real-world neuromorphic computing applications, particularly for edge computing tasks. Therefore, exploring more efficient neural encoder implementations and multiplexing encoders with higher data capacity holds promise. This issue also aims to discuss both field-programmable gate array (FPGA) and integrated circuit (IC) realizations of neural encoders with high data capacity and how these implementations respond to noise impacts. By spotlighting recent advancements in neural coding principles, this collection of articles aims to deepen our understanding of how different coding strategies contribute to sensory perception, action manifestation, and the impact of internal or external noise on these coding paradigms.

This research topic aims to deepen our understanding of how different neural coding strategies contribute to sensory perception, action manifestation, and the impact of internal or external noise on these coding paradigms. Specifically, it seeks to answer questions about the contributions of various neural codes to the overall response to sensory stimuli across different sensory systems. Additionally, the research will test hypotheses related to the efficiency and capacity of neural encoder implementations in real-world applications, particularly in the context of neuromorphic computing.

To gather further insights into the boundaries of neural coding, we welcome articles addressing, but not limited to, the following themes:
- Multiplexed encoding and its role in sensory information processing
- Single-trial neural activity and its influence on behavioral decisions
- Hardware implementations of neural codes, including FPGA and IC realizations
- The impact of internal and external noise on neural coding strategies
- Comparative studies of neural coding across different sensory systems
- Advances in neuromorphic computing and edge computing applications
- Theoretical models and simulations of neural coding mechanisms

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Advancements in Neural Coding: Sensory Perception and Multiplexed Encoding Strategies