1999/09/15 by Garrett B. Stanley, Fei F. Li, Yang Dan · 251 citations
Neuroscience · Biochemistry, Genetics and Molecular Biology · Mathematics · #Neural dynamics and brain function #Neuroscience and Neuropharmacology Research #Retinal Development and Disorders #Lateral geniculate nucleus #Decoding methods #Neuroscience #Sensory system #Neural coding #Coding (social sciences) #Computer science #Visual space #Artificial intelligence #Computer vision #Visual cortex #Pattern recognition (psychology) #Biology #Algorithm #Mathematics
paper · pdf · doi:10.1523/jneurosci.19-18-08036.1999
published in Journal of Neuroscience 19(18), 8036-8042 (Society for Neuroscience)
openalex publication_date 1999/09/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
A major challenge in studying sensory processing is to understand the meaning of the neural messages encoded in the spiking activity of neurons. From the recorded responses in a sensory circuit, what information can we extract about the outside world? Here we used a linear decoding technique to reconstruct spatiotemporal visual inputs from ensemble responses in the lateral geniculate nucleus (LGN) of the cat. From the activity of 177 cells, we have reconstructed natural scenes with recognizable moving objects. The quality of reconstruction depends on the number of cells. For each point in space, the quality of reconstruction begins to saturate at six to eight pairs of on and off cells, approaching the estimated coverage factor in the LGN of the cat. Thus, complex visual inputs can be reconstructed with a simple decoding algorithm, and these analyses provide a basis for understanding ensemble coding in the early visual pathway.