---
_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'
...