Fast population coding (Huys et al. 2007)

"Uncertainty coming from the noise in its neurons and the ill-posed nature of many tasks plagues neural computations. Maybe surprisingly, many studies show that the brain manipulates these forms of uncertainty in a probabilistically consistent and normative manner, and there is now a rich theoretical literature on the capabilities of populations of neurons to implement computations in the face of uncertainty. However, one major facet of uncertainty has received comparatively little attention: time. In a dynamic, rapidly changing world, data are only temporarily relevant. Here, we analyze the computational consequences of encoding stimulus trajectories in populations of neurons. ..."

Model Type: Connectionist Network

Model Concept(s): Methods

Simulation Environment: MATLAB


Huys QJ, Zemel RS, Natarajan R, Dayan P. (2007). Fast population coding. Neural computation 19 [PubMed]