--- _id: '5584' abstract: - lang: eng text: "This package contains data for the publication \"Nonlinear decoding of a complex movie from the mammalian retina\" by Deny S. et al, PLOS Comput Biol (2018). \r\n\r\nThe data consists of\r\n(i) 91 spike sorted, isolated rat retinal ganglion cells that pass stability and quality criteria, recorded on the multi-electrode array, in response to the presentation of the complex movie with many randomly moving dark discs. The responses are represented as 648000 x 91 binary matrix, where the first index indicates the timebin of duration 12.5 ms, and the second index the neural identity. The matrix entry is 0/1 if the neuron didn't/did spike in the particular time bin.\r\n(ii) README file and a graphical illustration of the structure of the experiment, specifying how the 648000 timebins are split into epochs where 1, 2, 4, or 10 discs were displayed, and which stimulus segments are exact repeats or unique ball trajectories.\r\n(iii) a 648000 x 400 matrix of luminance traces for each of the 20 x 20 positions (\"sites\") in the movie frame, with time that is locked to the recorded raster. The luminance traces are produced as described in the manuscript by filtering the raw disc movie with a small gaussian spatial kernel. " article_processing_charge: No author: - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Vicente full_name: Botella-Soler, Vicente last_name: Botella-Soler - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. 2018. doi:10.15479/AT:ISTA:98 apa: Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98 chicago: Deny, Stephane, Olivier Marre, Vicente Botella-Soler, Georg S Martius, and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:98. ieee: S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkačik, “Nonlinear decoding of a complex movie from the mammalian retina.” Institute of Science and Technology Austria, 2018. ista: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. 2018. Nonlinear decoding of a complex movie from the mammalian retina, Institute of Science and Technology Austria, 10.15479/AT:ISTA:98. mla: Deny, Stephane, et al. Nonlinear Decoding of a Complex Movie from the Mammalian Retina. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:98. short: S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkačik, (2018). datarep_id: '98' date_created: 2018-12-12T12:31:39Z date_published: 2018-03-29T00:00:00Z date_updated: 2024-02-21T13:45:26Z day: '29' ddc: - '570' department: - _id: ChLa - _id: GaTk doi: 10.15479/AT:ISTA:98 file: - access_level: open_access checksum: 6808748837b9afbbbabc2a356ca2b88a content_type: application/octet-stream creator: system date_created: 2018-12-12T13:02:24Z date_updated: 2020-07-14T12:47:07Z file_id: '5590' file_name: IST-2018-98-v1+1_BBalls_area2_tile2_20x20.mat file_size: 1142543971 relation: main_file - access_level: open_access checksum: d6d6cd07743038fe3a12352983fcf9dd content_type: application/pdf creator: system date_created: 2018-12-12T13:02:25Z date_updated: 2020-07-14T12:47:07Z file_id: '5591' file_name: IST-2018-98-v1+2_ExperimentStructure.pdf file_size: 702336 relation: main_file - access_level: open_access checksum: 0c9cfb4dab35bb3dc25a04395600b1c8 content_type: application/octet-stream creator: system date_created: 2018-12-12T13:02:26Z date_updated: 2020-07-14T12:47:07Z file_id: '5592' file_name: IST-2018-98-v1+3_GoodLocations_area2_20x20.mat file_size: 432 relation: main_file - access_level: open_access checksum: 2a83b011012e21e934b4596285b1a183 content_type: text/plain creator: system date_created: 2018-12-12T13:02:26Z date_updated: 2020-07-14T12:47:07Z file_id: '5593' file_name: IST-2018-98-v1+4_README.txt file_size: 986 relation: main_file file_date_updated: 2020-07-14T12:47:07Z has_accepted_license: '1' keyword: - retina - decoding - regression - neural networks - complex stimulus license: https://creativecommons.org/publicdomain/zero/1.0/ month: '03' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publisher: Institute of Science and Technology Austria related_material: record: - id: '292' relation: used_in_publication status: public status: public title: Nonlinear decoding of a complex movie from the mammalian retina tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '9943' abstract: - lang: eng text: Segmentation is the process of partitioning digital images into meaningful regions. The analysis of biological high content images often requires segmentation as a first step. We propose ilastik as an easy-to-use tool which allows the user without expertise in image processing to perform segmentation and classification in a unified way. ilastik learns from labels provided by the user through a convenient mouse interface. Based on these labels, ilastik infers a problem specific segmentation. A random forest classifier is used in the learning step, in which each pixel's neighborhood is characterized by a set of generic (nonlinear) features. ilastik supports up to three spatial plus one spectral dimension and makes use of all dimensions in the feature calculation. ilastik provides realtime feedback that enables the user to interactively refine the segmentation result and hence further fine-tune the classifier. An uncertainty measure guides the user to ambiguous regions in the images. Real time performance is achieved by multi-threading which fully exploits the capabilities of modern multi-core machines. Once a classifier has been trained on a set of representative images, it can be exported and used to automatically process a very large number of images (e.g. using the CellProfiler pipeline). ilastik is an open source project and released under the BSD license at www.ilastik.org. article_processing_charge: No author: - first_name: Christoph M full_name: Sommer, Christoph M id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87 last_name: Sommer orcid: 0000-0003-1216-9105 - first_name: Christoph full_name: Straehle, Christoph last_name: Straehle - first_name: Ullrich full_name: Köthe, Ullrich last_name: Köthe - first_name: Fred A. full_name: Hamprecht, Fred A. last_name: Hamprecht citation: ama: 'Sommer CM, Straehle C, Köthe U, Hamprecht FA. Ilastik: Interactive learning and segmentation toolkit. In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Micro. Institute of Electrical and Electronics Engineers; 2011. doi:10.1109/isbi.2011.5872394' apa: 'Sommer, C. M., Straehle, C., Köthe, U., & Hamprecht, F. A. (2011). Ilastik: Interactive learning and segmentation toolkit. In 2011 IEEE International Symposium on Biomedical Imaging: from Nano to Micro. Chicago, Illinois, USA: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/isbi.2011.5872394' chicago: 'Sommer, Christoph M, Christoph Straehle, Ullrich Köthe, and Fred A. Hamprecht. “Ilastik: Interactive Learning and Segmentation Toolkit.” In 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Micro. Institute of Electrical and Electronics Engineers, 2011. https://doi.org/10.1109/isbi.2011.5872394.' ieee: 'C. M. Sommer, C. Straehle, U. Köthe, and F. A. Hamprecht, “Ilastik: Interactive learning and segmentation toolkit,” in 2011 IEEE International Symposium on Biomedical Imaging: from Nano to Micro, Chicago, Illinois, USA, 2011.' ista: 'Sommer CM, Straehle C, Köthe U, Hamprecht FA. 2011. Ilastik: Interactive learning and segmentation toolkit. 2011 IEEE International Symposium on Biomedical Imaging: from Nano to Micro. ISBI: International Symposium on Biomedical Imaging.' mla: 'Sommer, Christoph M., et al. “Ilastik: Interactive Learning and Segmentation Toolkit.” 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Micro, Institute of Electrical and Electronics Engineers, 2011, doi:10.1109/isbi.2011.5872394.' short: 'C.M. Sommer, C. Straehle, U. Köthe, F.A. Hamprecht, in:, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Micro, Institute of Electrical and Electronics Engineers, 2011.' conference: end_date: 2011-04-02 location: Chicago, Illinois, USA name: 'ISBI: International Symposium on Biomedical Imaging' start_date: 2011-03-30 date_created: 2021-08-19T11:49:58Z date_published: 2011-06-09T00:00:00Z date_updated: 2023-02-23T14:13:38Z day: '09' department: - _id: Bio doi: 10.1109/isbi.2011.5872394 extern: '1' keyword: - image segmentation - biomedical imaging - three dimensional displays - neurons - retina - observers - image color analysis language: - iso: eng main_file_link: - open_access: '1' url: https://www.researchgate.net/publication/224241106_Ilastik_Interactive_learning_and_segmentation_toolkit month: '06' oa: 1 oa_version: Preprint publication: '2011 IEEE International Symposium on Biomedical Imaging: from Nano to Micro' publication_identifier: eissn: - 1945-8452 isbn: - 978-1-4244-4127-3 issn: - 1945-7928 publication_status: published publisher: Institute of Electrical and Electronics Engineers quality_controlled: '1' status: public title: 'Ilastik: Interactive learning and segmentation toolkit' type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2011' ...