title: Statistical analysis of the information content in the activity of cortical neurons.
abstract: We sought to quantify the information in the activity of posterior parietal neurons in behaving Rhesus monkeys. We found several models that were adequate to represent the neurons' response fields. We used a gaussian model to construct a signal/noise ratio, which provided an estimate of the number of distinguishable levels (NDL) of activity within the response field. For the typical neuron, an unbiased ideal observer could reliably discriminate 3.4 levels of activity. At change levels of detectability, the threshold limit of reliable discrimination, there was an average of 5.8 NDL. We then used the NDL to divide the response field into regions of spatial ambiguity. For an individual neuron, we suggest that firing rate is a measure of the probability that the target is at the center of the neuron's response field.
authors.affiliation: Department of Neurobiology and Behavior, State University of New York, Stony Brook 11794, USA. jgnadt@brain.bio.sunysb.edu
authors.forename: J W
authors.initials: JW
authors.lastname: Gnadt
authors.forename: B
authors.initials: B
authors.lastname: Breznen
mesh_terms: D000200:Action Potentials; D000818:Animals; D005133:Eye Movements / Q000502:physiology*; D008253:Macaca mulatta; D008433:Mathematics; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D012044:Regression Analysis; D013997:Time Factors; D014793:Visual Cortex / Q000502:physiology*