Reconstruction of natural scenes from ensemble responses in the lateral geniculate nucleus

A major challenge in studying sensory processing is to understand the meani ng of the neural messages encoded in the spiking activity of neurons. From the recorded responses in a sensory circuit, what information can we extrac t about the outside world? Here we used a linear decoding technique to reco nstruct spatiotemporal visual inputs from ensemble responses in the lateral geniculate nucleus (LGN) of the cat. From the activity of 177 cells, we ha ve reconstructed natural scenes with recognizable moving objects. The quali ty of reconstruction depends on the number of cells. For each point in spac e, the quality of reconstruction begins to saturate at six to eight pairs o f 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 de coding algorithm, and these analyses provide a basis for understanding ense mble coding in the early visual pathway.