--- res: bibo_abstract: - The number of possible activity patterns in a population of neurons grows exponentially with the size of the population. Typical experiments explore only a tiny fraction of the large space of possible activity patterns in the case of populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled regime, to estimate the probabilities with which most of the activity patterns occur. As a result, the corresponding entropy - which is a measure of the computational power of the neural population - cannot be estimated directly. We propose a simple scheme for estimating the entropy in the undersampled regime, which bounds its value from both below and above. The lower bound is the usual 'naive' entropy of the experimental frequencies. The upper bound results from a hybrid approximation of the entropy which makes use of the naive estimate, a maximum entropy fit, and a coverage adjustment. We apply our simple scheme to artificial data, in order to check their accuracy; we also compare its performance to those of several previously defined entropy estimators. We then apply it to actual measurements of neural activity in populations with up to 100 cells. Finally, we discuss the similarities and differences between the proposed simple estimation scheme and various earlier methods. © 2013 IOP Publishing Ltd and SISSA Medialab srl.@eng bibo_authorlist: - foaf_Person: foaf_givenName: Michael foaf_name: Berry, Michael foaf_surname: Berry - foaf_Person: foaf_givenName: Gasper foaf_name: Tkacik, Gasper foaf_surname: Tkacik foaf_workInfoHomepage: http://www.librecat.org/personId=3D494DCA-F248-11E8-B48F-1D18A9856A87 orcid: 0000-0002-6699-1455 - foaf_Person: foaf_givenName: Julien foaf_name: Dubuis, Julien foaf_surname: Dubuis - foaf_Person: foaf_givenName: Olivier foaf_name: Marre, Olivier foaf_surname: Marre - foaf_Person: foaf_givenName: Ravá foaf_name: Da Silveira, Ravá foaf_surname: Da Silveira bibo_doi: 10.1088/1742-5468/2013/03/P03015 bibo_issue: '3' bibo_volume: 2013 dct_date: 2013^xs_gYear dct_language: eng dct_publisher: IOP Publishing Ltd.@ dct_title: A simple method for estimating the entropy of neural activity@ ...