--- res: bibo_abstract: - 'The ability of an organism to distinguish between various stimuli is limited by the structure and noise in the population code of its sensory neurons. Here we infer a distance measure on the stimulus space directly from the recorded activity of 100 neurons in the salamander retina. In contrast to previously used measures of stimulus similarity, this "neural metric" tells us how distinguishable a pair of stimulus clips is to the retina, based on the similarity between the induced distributions of population responses. We show that the retinal distance strongly deviates from Euclidean, or any static metric, yet has a simple structure: we identify the stimulus features that the neural population is jointly sensitive to, and show the support-vector-machine- like kernel function relating the stimulus and neural response spaces. We show that the non-Euclidean nature of the retinal distance has important consequences for neural decoding.@eng' bibo_authorlist: - 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: Einat foaf_name: Granot Atedgi, Einat foaf_surname: Granot Atedgi - foaf_Person: foaf_givenName: Ronen foaf_name: Segev, Ronen foaf_surname: Segev - foaf_Person: foaf_givenName: Elad foaf_name: Schneidman, Elad foaf_surname: Schneidman bibo_doi: 10.1103/PhysRevLett.110.058104 bibo_issue: '5' bibo_volume: 110 dct_date: 2013^xs_gYear dct_language: eng dct_publisher: American Physical Society@ dct_title: 'Retinal metric: a stimulus distance measure derived from population neural responses@' ...