Abstract
SummaryLogistic classification is a simple way to make choices based on a set of factors: give each factor a weight, sum them, and use the result to set the log odds of a random draw. This operation is known to describe human and animal choices based on value (economic decisions). There is increasing evidence that it also describes choices based on sensory inputs (perceptual decisions). Here I briefly review this evidence and I fit data from multiple studies in multiple species to show that logistic classification can describe a variety of choices. These include sensory choices influenced by stimuli of other modalities (multisensory integration) or by non-sensory factors such as value and recent history. Logistic classification is the optimal strategy if factors are independent of each other, and a useful heuristic in other conditions. Using it to describe sensory choices is useful to characterize brain function and the effects of brain inactivations.
Publisher
Cold Spring Harbor Laboratory
Reference81 articles.
1. McFadden, D. in Frontiers in Econometrics (ed Paul Zarembka ) Ch. 4, 105–142 (Academic Press, 1973).
2. Banburismus and the Brain
3. Goodfellow, I. , Bengio, Y. & Courville, A. Deep Learning. (MIT Press, 2016).
4. Cramer, J. S. The origins of logistic regression (University of Amsterdam and Tinbergen Institute, Amsterdam, 2002).
5. Logistic analysis of choice data: A primer