Spiking neural networks: A survey
The field of Deep Learning (DL) has seen a remarkable series of developments with
increasingly accurate and robust algorithms. However, the increase in performance has …
increasingly accurate and robust algorithms. However, the increase in performance has …
Artificial intelligence techniques for retinal prostheses: A comprehensive review and future direction
Objective. Retinal prostheses are promising devices to restore vision for patients with severe
age-related macular degeneration or retinitis pigmentosa disease. The visual processing …
age-related macular degeneration or retinitis pigmentosa disease. The visual processing …
Learning rules in spiking neural networks: A survey
Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …
Neural decoding of visual information across different neural recording modalities and approaches
Vision plays a peculiar role in intelligence. Visual information, forming a large part of the
sensory information, is fed into the human brain to formulate various types of cognition and …
sensory information, is fed into the human brain to formulate various types of cognition and …
Robust transcoding sensory information with neural spikes
Neural coding, including encoding and decoding, is one of the key problems in
neuroscience for understanding how the brain uses neural signals to relate sensory …
neuroscience for understanding how the brain uses neural signals to relate sensory …
Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks
Traditional models of retinal system identification analyze the neural response to artificial
stimuli using models consisting of predefined components. The model design is limited to …
stimuli using models consisting of predefined components. The model design is limited to …
Threaten spiking neural networks through combining rate and temporal information
Spiking Neural Networks (SNNs) have received widespread attention in academic
communities due to their superior spatio-temporal processing capabilities and energy …
communities due to their superior spatio-temporal processing capabilities and energy …
Reconstruction of natural visual scenes from neural spikes with deep neural networks
Neural coding is one of the central questions in systems neuroscience for understanding
how the brain processes stimulus from the environment, moreover, it is also a cornerstone …
how the brain processes stimulus from the environment, moreover, it is also a cornerstone …
Decoding pixel-level image features from two-photon calcium signals of macaque visual cortex
Images of visual scenes comprise essential features important for visual cognition of the
brain. The complexity of visual features lies at different levels, from simple artificial patterns …
brain. The complexity of visual features lies at different levels, from simple artificial patterns …
Dynamic spatiotemporal pattern recognition with recurrent spiking neural network
Our real-time actions in everyday life reflect a range of spatiotemporal dynamic brain activity
patterns, the consequence of neuronal computation with spikes in the brain. Most existing …
patterns, the consequence of neuronal computation with spikes in the brain. Most existing …