PT  - JOURNAL ARTICLE
AU  - Thaddeus R. Cybulski
AU  - Joshua I. Glaser
AU  - Adam H. Marblestone
AU  - Bradley M. Zamft
AU  - Edward S. Boyden
AU  - George M. Church
AU  - Konrad P. Kording
TI  - Spatial Information in Large-Scale Neural Recordings
AID  - 10.1101/002923
DP  - 2014 Jan 01
TA  - bioRxiv
PG  - 002923
4099  - http://biorxiv.org/content/early/2014/02/21/002923.short
4100  - http://biorxiv.org/content/early/2014/02/21/002923.full
AB  - A central issue in neural recording is that of distinguishing the activities of many neurons. Here, we develop a framework, based on Fisher information, to quantify how separable a neuron’s activity is from the activities of nearby neurons. We (1) apply this framework to model information flow and spatial distinguishability for several electrical and optical neural recording methods, (2) provide analytic expressions for information content, and (3) demonstrate potential applications of the approach. This method generalizes to many recording devices that resolve objects in space and thus may be useful in the design of next-generation scalable neural recording systems.