---
_id: '2851'
abstract:
- lang: eng
text: 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.
article_number: P03015
article_processing_charge: No
author:
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Julien
full_name: Dubuis, Julien
last_name: Dubuis
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Ravá
full_name: Da Silveira, Ravá
last_name: Da Silveira
citation:
ama: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. A simple method for estimating
the entropy of neural activity. Journal of Statistical Mechanics Theory and
Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03015
apa: Berry, M., Tkačik, G., Dubuis, J., Marre, O., & Da Silveira, R. (2013).
A simple method for estimating the entropy of neural activity. Journal of Statistical
Mechanics Theory and Experiment. IOP Publishing. https://doi.org/10.1088/1742-5468/2013/03/P03015
chicago: Berry, Michael, Gašper Tkačik, Julien Dubuis, Olivier Marre, and Ravá Da
Silveira. “A Simple Method for Estimating the Entropy of Neural Activity.” Journal
of Statistical Mechanics Theory and Experiment. IOP Publishing, 2013. https://doi.org/10.1088/1742-5468/2013/03/P03015.
ieee: M. Berry, G. Tkačik, J. Dubuis, O. Marre, and R. Da Silveira, “A simple method
for estimating the entropy of neural activity,” Journal of Statistical Mechanics
Theory and Experiment, vol. 2013, no. 3. IOP Publishing, 2013.
ista: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. 2013. A simple method
for estimating the entropy of neural activity. Journal of Statistical Mechanics
Theory and Experiment. 2013(3), P03015.
mla: Berry, Michael, et al. “A Simple Method for Estimating the Entropy of Neural
Activity.” Journal of Statistical Mechanics Theory and Experiment, vol.
2013, no. 3, P03015, IOP Publishing, 2013, doi:10.1088/1742-5468/2013/03/P03015.
short: M. Berry, G. Tkačik, J. Dubuis, O. Marre, R. Da Silveira, Journal of Statistical
Mechanics Theory and Experiment 2013 (2013).
date_created: 2018-12-11T11:59:56Z
date_published: 2013-03-12T00:00:00Z
date_updated: 2025-09-29T13:41:46Z
day: '12'
department:
- _id: GaTk
doi: 10.1088/1742-5468/2013/03/P03015
external_id:
isi:
- '000316056900015'
intvolume: ' 2013'
isi: 1
issue: '3'
language:
- iso: eng
month: '03'
oa_version: None
publication: Journal of Statistical Mechanics Theory and Experiment
publication_status: published
publisher: IOP Publishing
publist_id: '3941'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A simple method for estimating the entropy of neural activity
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 2013
year: '2013'
...
---
_id: '2861'
abstract:
- lang: eng
text: We consider a two-parameter family of piecewise linear maps in which the moduli
of the two slopes take different values. We provide numerical evidence of the
existence of some parameter regions in which the Lyapunov exponent and the topological
entropy remain constant. Analytical proof of this phenomenon is also given for
certain cases. Surprisingly however, the systems with that property are not conjugate
as we prove by using kneading theory.
article_number: '125101'
article_processing_charge: No
author:
- first_name: Vicente
full_name: Botella Soler, Vicente
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: José
full_name: Oteo, José
last_name: Oteo
- first_name: Javier
full_name: Ros, Javier
last_name: Ros
- first_name: Paul
full_name: Glendinning, Paul
last_name: Glendinning
citation:
ama: 'Botella Soler V, Oteo J, Ros J, Glendinning P. Lyapunov exponent and topological
entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical
and Theoretical. 2013;46(12). doi:10.1088/1751-8113/46/12/125101'
apa: 'Botella Soler, V., Oteo, J., Ros, J., & Glendinning, P. (2013). Lyapunov
exponent and topological entropy plateaus in piecewise linear maps. Journal
of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/10.1088/1751-8113/46/12/125101'
chicago: 'Botella Soler, Vicente, José Oteo, Javier Ros, and Paul Glendinning. “Lyapunov
Exponent and Topological Entropy Plateaus in Piecewise Linear Maps.” Journal
of Physics A: Mathematical and Theoretical. IOP Publishing, 2013. https://doi.org/10.1088/1751-8113/46/12/125101.'
ieee: 'V. Botella Soler, J. Oteo, J. Ros, and P. Glendinning, “Lyapunov exponent
and topological entropy plateaus in piecewise linear maps,” Journal of Physics
A: Mathematical and Theoretical, vol. 46, no. 12. IOP Publishing, 2013.'
ista: 'Botella Soler V, Oteo J, Ros J, Glendinning P. 2013. Lyapunov exponent and
topological entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical
and Theoretical. 46(12), 125101.'
mla: 'Botella Soler, Vicente, et al. “Lyapunov Exponent and Topological Entropy
Plateaus in Piecewise Linear Maps.” Journal of Physics A: Mathematical and
Theoretical, vol. 46, no. 12, 125101, IOP Publishing, 2013, doi:10.1088/1751-8113/46/12/125101.'
short: 'V. Botella Soler, J. Oteo, J. Ros, P. Glendinning, Journal of Physics A:
Mathematical and Theoretical 46 (2013).'
corr_author: '1'
date_created: 2018-12-11T11:59:59Z
date_published: 2013-03-29T00:00:00Z
date_updated: 2025-09-29T13:36:56Z
day: '29'
department:
- _id: GaTk
doi: 10.1088/1751-8113/46/12/125101
external_id:
isi:
- '000316058200010'
intvolume: ' 46'
isi: 1
issue: '12'
language:
- iso: eng
month: '03'
oa_version: None
publication: 'Journal of Physics A: Mathematical and Theoretical'
publication_status: published
publisher: IOP Publishing
publist_id: '3928'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Lyapunov exponent and topological entropy plateaus in piecewise linear maps
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 46
year: '2013'
...
---
_id: '2863'
abstract:
- lang: eng
text: Neural populations encode information about their stimulus in a collective
fashion, by joint activity patterns of spiking and silence. A full account of
this mapping from stimulus to neural activity is given by the conditional probability
distribution over neural codewords given the sensory input. For large populations,
direct sampling of these distributions is impossible, and so we must rely on constructing
appropriate models. We show here that in a population of 100 retinal ganglion
cells in the salamander retina responding to temporal white-noise stimuli, dependencies
between cells play an important encoding role. We introduce the stimulus-dependent
maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear
model of a single neuron, to a pairwise-coupled neural population. We find that
the SDME model gives a more accurate account of single cell responses and in particular
significantly outperforms uncoupled models in reproducing the distributions of
population codewords emitted in response to a stimulus. We show how the SDME model,
in conjunction with static maximum entropy models of population vocabulary, can
be used to estimate information-theoretic quantities like average surprise and
information transmission in a neural population.
article_number: e1002922
article_processing_charge: No
author:
- first_name: Einat
full_name: Granot Atedgi, Einat
last_name: Granot Atedgi
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Ronen
full_name: Segev, Ronen
last_name: Segev
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: Granot Atedgi E, Tkačik G, Segev R, Schneidman E. Stimulus-dependent maximum
entropy models of neural population codes. PLoS Computational Biology.
2013;9(3). doi:10.1371/journal.pcbi.1002922
apa: Granot Atedgi, E., Tkačik, G., Segev, R., & Schneidman, E. (2013). Stimulus-dependent
maximum entropy models of neural population codes. PLoS Computational Biology.
Public Library of Science. https://doi.org/10.1371/journal.pcbi.1002922
chicago: Granot Atedgi, Einat, Gašper Tkačik, Ronen Segev, and Elad Schneidman.
“Stimulus-Dependent Maximum Entropy Models of Neural Population Codes.” PLoS
Computational Biology. Public Library of Science, 2013. https://doi.org/10.1371/journal.pcbi.1002922.
ieee: E. Granot Atedgi, G. Tkačik, R. Segev, and E. Schneidman, “Stimulus-dependent
maximum entropy models of neural population codes,” PLoS Computational Biology,
vol. 9, no. 3. Public Library of Science, 2013.
ista: Granot Atedgi E, Tkačik G, Segev R, Schneidman E. 2013. Stimulus-dependent
maximum entropy models of neural population codes. PLoS Computational Biology.
9(3), e1002922.
mla: Granot Atedgi, Einat, et al. “Stimulus-Dependent Maximum Entropy Models of
Neural Population Codes.” PLoS Computational Biology, vol. 9, no. 3, e1002922,
Public Library of Science, 2013, doi:10.1371/journal.pcbi.1002922.
short: E. Granot Atedgi, G. Tkačik, R. Segev, E. Schneidman, PLoS Computational
Biology 9 (2013).
corr_author: '1'
date_created: 2018-12-11T12:00:00Z
date_published: 2013-03-01T00:00:00Z
date_updated: 2025-09-29T13:35:44Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1002922
external_id:
isi:
- '000316864200003'
file:
- access_level: open_access
checksum: 5a30876c193209fa05b26db71845dd16
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:45Z
date_updated: 2020-07-14T12:45:52Z
file_id: '5099'
file_name: IST-2013-120-v1+1_journal.pcbi.1002922.pdf
file_size: 1548120
relation: main_file
file_date_updated: 2020-07-14T12:45:52Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '3926'
pubrep_id: '120'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Stimulus-dependent maximum entropy models of neural population codes
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 9
year: '2013'
...
---
_id: '2913'
abstract:
- lang: eng
text: '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.'
article_number: '058104'
article_processing_charge: No
arxiv: 1
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Einat
full_name: Granot Atedgi, Einat
last_name: Granot Atedgi
- first_name: Ronen
full_name: Segev, Ronen
last_name: Segev
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: 'Tkačik G, Granot Atedgi E, Segev R, Schneidman E. Retinal metric: a stimulus
distance measure derived from population neural responses. Physical Review
Letters. 2013;110(5). doi:10.1103/PhysRevLett.110.058104'
apa: 'Tkačik, G., Granot Atedgi, E., Segev, R., & Schneidman, E. (2013). Retinal
metric: a stimulus distance measure derived from population neural responses.
Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.110.058104'
chicago: 'Tkačik, Gašper, Einat Granot Atedgi, Ronen Segev, and Elad Schneidman.
“Retinal Metric: A Stimulus Distance Measure Derived from Population Neural Responses.”
Physical Review Letters. American Physical Society, 2013. https://doi.org/10.1103/PhysRevLett.110.058104.'
ieee: 'G. Tkačik, E. Granot Atedgi, R. Segev, and E. Schneidman, “Retinal metric:
a stimulus distance measure derived from population neural responses,” Physical
Review Letters, vol. 110, no. 5. American Physical Society, 2013.'
ista: 'Tkačik G, Granot Atedgi E, Segev R, Schneidman E. 2013. Retinal metric: a
stimulus distance measure derived from population neural responses. Physical Review
Letters. 110(5), 058104.'
mla: 'Tkačik, Gašper, et al. “Retinal Metric: A Stimulus Distance Measure Derived
from Population Neural Responses.” Physical Review Letters, vol. 110, no.
5, 058104, American Physical Society, 2013, doi:10.1103/PhysRevLett.110.058104.'
short: G. Tkačik, E. Granot Atedgi, R. Segev, E. Schneidman, Physical Review Letters
110 (2013).
corr_author: '1'
date_created: 2018-12-11T12:00:18Z
date_published: 2013-01-28T00:00:00Z
date_updated: 2025-09-29T13:29:59Z
day: '28'
department:
- _id: GaTk
doi: 10.1103/PhysRevLett.110.058104
external_id:
arxiv:
- '1205.6598'
isi:
- '000314090300012'
intvolume: ' 110'
isi: 1
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1205.6598
month: '01'
oa: 1
oa_version: Preprint
publication: Physical Review Letters
publication_status: published
publisher: American Physical Society
publist_id: '3830'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Retinal metric: a stimulus distance measure derived from population neural
responses'
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 110
year: '2013'
...
---
_id: '2914'
abstract:
- lang: eng
text: The scale invariance of natural images suggests an analogy to the statistical
mechanics of physical systems at a critical point. Here we examine the distribution
of pixels in small image patches and show how to construct the corresponding thermodynamics.
We find evidence for criticality in a diverging specific heat, which corresponds
to large fluctuations in how "surprising" we find individual images,
and in the quantitative form of the entropy vs energy. We identify special image
configurations as local energy minima and show that average patches within each
basin are interpretable as lines and edges in all orientations.
acknowledgement: "This work was supported in part by NSF Grants No. IIS-0613435, No.
IBN-0344678, and No. PHY-0957573, by NIH Grant No. T32 MH065214, by the Human Frontier
Science Program, and by the Swartz Foundation.\r\nCC BY 3.0\r\n"
article_number: '018701'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Greg
full_name: Stephens, Greg
last_name: Stephens
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Stephens G, Mora T, Tkačik G, Bialek W. Statistical thermodynamics of natural
images. Physical Review Letters. 2013;110(1). doi:10.1103/PhysRevLett.110.018701
apa: Stephens, G., Mora, T., Tkačik, G., & Bialek, W. (2013). Statistical thermodynamics
of natural images. Physical Review Letters. American Physical Society.
https://doi.org/10.1103/PhysRevLett.110.018701
chicago: Stephens, Greg, Thierry Mora, Gašper Tkačik, and William Bialek. “Statistical
Thermodynamics of Natural Images.” Physical Review Letters. American Physical
Society, 2013. https://doi.org/10.1103/PhysRevLett.110.018701.
ieee: G. Stephens, T. Mora, G. Tkačik, and W. Bialek, “Statistical thermodynamics
of natural images,” Physical Review Letters, vol. 110, no. 1. American
Physical Society, 2013.
ista: Stephens G, Mora T, Tkačik G, Bialek W. 2013. Statistical thermodynamics of
natural images. Physical Review Letters. 110(1), 018701.
mla: Stephens, Greg, et al. “Statistical Thermodynamics of Natural Images.” Physical
Review Letters, vol. 110, no. 1, 018701, American Physical Society, 2013,
doi:10.1103/PhysRevLett.110.018701.
short: G. Stephens, T. Mora, G. Tkačik, W. Bialek, Physical Review Letters 110 (2013).
date_created: 2018-12-11T12:00:19Z
date_published: 2013-01-02T00:00:00Z
date_updated: 2025-09-29T13:29:28Z
day: '02'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1103/PhysRevLett.110.018701
external_id:
arxiv:
- '0806.2694'
isi:
- '000313006100058'
file:
- access_level: open_access
checksum: 72bfbc2094c4680e8a8a6bed668cd06d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:18:44Z
date_updated: 2020-07-14T12:45:53Z
file_id: '5366'
file_name: IST-2016-401-v1+1_1281.full.pdf
file_size: 416965
relation: main_file
file_date_updated: 2020-07-14T12:45:53Z
has_accepted_license: '1'
intvolume: ' 110'
isi: 1
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: Physical Review Letters
publication_status: published
publisher: American Physical Society
publist_id: '3829'
pubrep_id: '401'
quality_controlled: '1'
status: public
title: Statistical thermodynamics of natural images
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 110
year: '2013'
...
---
_id: '3261'
abstract:
- lang: eng
text: Cells in a developing embryo have no direct way of "measuring" their
physical position. Through a variety of processes, however, the expression levels
of multiple genes come to be correlated with position, and these expression levels
thus form a code for "positional information." We show how to measure
this information, in bits, using the gap genes in the Drosophila embryo as an
example. Individual genes carry nearly two bits of information, twice as much
as expected if the expression patterns consisted only of on/off domains separated
by sharp boundaries. Taken together, four gap genes carry enough information to
define a cell's location with an error bar of ~1% along the anterior-posterior
axis of the embryo. This precision is nearly enough for each cell to have a unique
identity, which is the maximum information the system can use, and is nearly constant
along the length of the embryo. We argue that this constancy is a signature of
optimality in the transmission of information from primary morphogen inputs to
the output of the gap gene network.
article_processing_charge: No
author:
- first_name: Julien
full_name: Dubuis, Julien
last_name: Dubuis
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Eric
full_name: Wieschaus, Eric
last_name: Wieschaus
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Dubuis J, Tkačik G, Wieschaus E, Gregor T, Bialek W. Positional information,
in bits. PNAS. 2013;110(41):16301-16308. doi:10.1073/pnas.1315642110
apa: Dubuis, J., Tkačik, G., Wieschaus, E., Gregor, T., & Bialek, W. (2013).
Positional information, in bits. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1315642110
chicago: Dubuis, Julien, Gašper Tkačik, Eric Wieschaus, Thomas Gregor, and William
Bialek. “Positional Information, in Bits.” PNAS. National Academy of Sciences,
2013. https://doi.org/10.1073/pnas.1315642110.
ieee: J. Dubuis, G. Tkačik, E. Wieschaus, T. Gregor, and W. Bialek, “Positional
information, in bits,” PNAS, vol. 110, no. 41. National Academy of Sciences,
pp. 16301–16308, 2013.
ista: Dubuis J, Tkačik G, Wieschaus E, Gregor T, Bialek W. 2013. Positional information,
in bits. PNAS. 110(41), 16301–16308.
mla: Dubuis, Julien, et al. “Positional Information, in Bits.” PNAS, vol.
110, no. 41, National Academy of Sciences, 2013, pp. 16301–08, doi:10.1073/pnas.1315642110.
short: J. Dubuis, G. Tkačik, E. Wieschaus, T. Gregor, W. Bialek, PNAS 110 (2013)
16301–16308.
date_created: 2018-12-11T12:02:19Z
date_published: 2013-10-08T00:00:00Z
date_updated: 2025-09-29T13:24:21Z
day: '08'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1073/pnas.1315642110
external_id:
isi:
- '000325395600021'
pmid:
- '24089448'
file:
- access_level: open_access
checksum: ecd859fe52a562193027d428b5524a8d
content_type: application/pdf
creator: dernst
date_created: 2019-01-22T13:53:23Z
date_updated: 2020-07-14T12:46:06Z
file_id: '5873'
file_name: 2013_PNAS_Dubuis.pdf
file_size: 1670548
relation: main_file
file_date_updated: 2020-07-14T12:46:06Z
has_accepted_license: '1'
intvolume: ' 110'
isi: 1
issue: '41'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 16301 - 16308
pmid: 1
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '3387'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Positional information, in bits
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 110
year: '2013'
...
---
_id: '2277'
abstract:
- lang: eng
text: Redundancies and correlations in the responses of sensory neurons may seem
to waste neural resources, but they can also carry cues about structured stimuli
and may help the brain to correct for response errors. To investigate the effect
of stimulus structure on redundancy in retina, we measured simultaneous responses
from populations of retinal ganglion cells presented with natural and artificial
stimuli that varied greatly in correlation structure; these stimuli and recordings
are publicly available online. Responding to spatio-temporally structured stimuli
such as natural movies, pairs of ganglion cells were modestly more correlated
than in response to white noise checkerboards, but they were much less correlated
than predicted by a non-adapting functional model of retinal response. Meanwhile,
responding to stimuli with purely spatial correlations, pairs of ganglion cells
showed increased correlations consistent with a static, non-adapting receptive
field and nonlinearity. We found that in response to spatio-temporally correlated
stimuli, ganglion cells had faster temporal kernels and tended to have stronger
surrounds. These properties of individual cells, along with gain changes that
opposed changes in effective contrast at the ganglion cell input, largely explained
the pattern of pairwise correlations across stimuli where receptive field measurements
were possible.
article_number: e1003344
article_processing_charge: No
author:
- first_name: Kristina
full_name: Simmons, Kristina
last_name: Simmons
- first_name: Jason
full_name: Prentice, Jason
last_name: Prentice
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Jan
full_name: Homann, Jan
last_name: Homann
- first_name: Heather
full_name: Yee, Heather
last_name: Yee
- first_name: Stephanie
full_name: Palmer, Stephanie
last_name: Palmer
- first_name: Philip
full_name: Nelson, Philip
last_name: Nelson
- first_name: Vijay
full_name: Balasubramanian, Vijay
last_name: Balasubramanian
citation:
ama: Simmons K, Prentice J, Tkačik G, et al. Transformation of stimulus correlations
by the retina. PLoS Computational Biology. 2013;9(12). doi:10.1371/journal.pcbi.1003344
apa: Simmons, K., Prentice, J., Tkačik, G., Homann, J., Yee, H., Palmer, S., … Balasubramanian,
V. (2013). Transformation of stimulus correlations by the retina. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1003344
chicago: Simmons, Kristina, Jason Prentice, Gašper Tkačik, Jan Homann, Heather Yee,
Stephanie Palmer, Philip Nelson, and Vijay Balasubramanian. “Transformation of
Stimulus Correlations by the Retina.” PLoS Computational Biology. Public
Library of Science, 2013. https://doi.org/10.1371/journal.pcbi.1003344.
ieee: K. Simmons et al., “Transformation of stimulus correlations by the
retina,” PLoS Computational Biology, vol. 9, no. 12. Public Library of
Science, 2013.
ista: Simmons K, Prentice J, Tkačik G, Homann J, Yee H, Palmer S, Nelson P, Balasubramanian
V. 2013. Transformation of stimulus correlations by the retina. PLoS Computational
Biology. 9(12), e1003344.
mla: Simmons, Kristina, et al. “Transformation of Stimulus Correlations by the Retina.”
PLoS Computational Biology, vol. 9, no. 12, e1003344, Public Library of
Science, 2013, doi:10.1371/journal.pcbi.1003344.
short: K. Simmons, J. Prentice, G. Tkačik, J. Homann, H. Yee, S. Palmer, P. Nelson,
V. Balasubramanian, PLoS Computational Biology 9 (2013).
date_created: 2018-12-11T11:56:43Z
date_published: 2013-12-05T00:00:00Z
date_updated: 2025-09-29T14:27:23Z
day: '05'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1003344
external_id:
isi:
- '000329364800028'
file:
- access_level: open_access
checksum: 46722afc4f7eabb0831165d9c1b171ad
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:36Z
date_updated: 2020-07-14T12:45:36Z
file_id: '5089'
file_name: IST-2016-410-v1+1_journal.pcbi.1003344.pdf
file_size: 3115568
relation: main_file
file_date_updated: 2020-07-14T12:45:36Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '4667'
pubrep_id: '410'
quality_controlled: '1'
related_material:
record:
- id: '9752'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Transformation of stimulus correlations by the retina
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 9
year: '2013'
...
---
_id: '2413'
abstract:
- lang: eng
text: 'Progress in understanding the global brain dynamics has remained slow to
date in large part because of the highly multiscale nature of brain activity.
Indeed, normal brain dynamics is characterized by complex interactions between
multiple levels: from the microscopic scale of single neurons to the mesoscopic
level of local groups of neurons, and finally to the macroscopic level of the
whole brain. Among the most difficult tasks are those of identifying which scales
are significant for a given particular function and describing how the scales
affect each other. It is important to realize that the scales of time and space
are linked together, or even intertwined, and that causal inference is far more
ambiguous between than within levels. We approach this problem from the perspective
of our recent work on simultaneous recording from micro- and macroelectrodes in
the human brain. We propose a physiological description of these multilevel interactions,
based on phase–amplitude coupling of neuronal oscillations that operate at multiple
frequencies and on different spatial scales. Specifically, the amplitude of the
oscillations on a particular spatial scale is modulated by phasic variations in
neuronal excitability induced by lower frequency oscillations that emerge on a
larger spatial scale. Following this general principle, it is possible to scale
up or scale down the multiscale brain dynamics. It is expected that large-scale
network oscillations in the low-frequency range, mediating downward effects, may
play an important role in attention and consciousness.'
alternative_title:
- Reviews of Nonlinear Dynamics and Complexity
article_processing_charge: No
author:
- first_name: Mario
full_name: Valderrama, Mario
last_name: Valderrama
- first_name: Vicente
full_name: Botella Soler, Vicente
id: 421234E8-F248-11E8-B48F-1D18A9856A87
last_name: Botella Soler
orcid: 0000-0002-8790-1914
- first_name: Michel
full_name: Le Van Quyen, Michel
last_name: Le Van Quyen
citation:
ama: 'Valderrama M, Botella Soler V, Le Van Quyen M. Neuronal oscillations scale
up and scale down the brain dynamics . In: Meyer M, Pesenson Z, eds. Multiscale
Analysis and Nonlinear Dynamics: From Genes to the Brain. Wiley; 2013. doi:10.1002/9783527671632.ch08'
apa: 'Valderrama, M., Botella Soler, V., & Le Van Quyen, M. (2013). Neuronal
oscillations scale up and scale down the brain dynamics . In M. Meyer & Z.
Pesenson (Eds.), Multiscale Analysis and Nonlinear Dynamics: From Genes to
the Brain. Wiley. https://doi.org/10.1002/9783527671632.ch08'
chicago: 'Valderrama, Mario, Vicente Botella Soler, and Michel Le Van Quyen. “Neuronal
Oscillations Scale up and Scale down the Brain Dynamics .” In Multiscale Analysis
and Nonlinear Dynamics: From Genes to the Brain, edited by Misha Meyer and
Z. Pesenson. Wiley, 2013. https://doi.org/10.1002/9783527671632.ch08.'
ieee: 'M. Valderrama, V. Botella Soler, and M. Le Van Quyen, “Neuronal oscillations
scale up and scale down the brain dynamics ,” in Multiscale Analysis and Nonlinear
Dynamics: From Genes to the Brain, M. Meyer and Z. Pesenson, Eds. Wiley, 2013.'
ista: 'Valderrama M, Botella Soler V, Le Van Quyen M. 2013.Neuronal oscillations
scale up and scale down the brain dynamics . In: Multiscale Analysis and Nonlinear
Dynamics: From Genes to the Brain. Reviews of Nonlinear Dynamics and Complexity,
.'
mla: 'Valderrama, Mario, et al. “Neuronal Oscillations Scale up and Scale down the
Brain Dynamics .” Multiscale Analysis and Nonlinear Dynamics: From Genes to
the Brain, edited by Misha Meyer and Z. Pesenson, Wiley, 2013, doi:10.1002/9783527671632.ch08.'
short: 'M. Valderrama, V. Botella Soler, M. Le Van Quyen, in:, M. Meyer, Z. Pesenson
(Eds.), Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, Wiley,
2013.'
date_created: 2018-12-11T11:57:31Z
date_published: 2013-08-01T00:00:00Z
date_updated: 2025-06-03T11:46:23Z
day: '01'
department:
- _id: GaTk
doi: 10.1002/9783527671632.ch08
editor:
- first_name: Misha
full_name: Meyer, Misha
last_name: Meyer
- first_name: Z.
full_name: Pesenson, Z.
last_name: Pesenson
language:
- iso: eng
month: '08'
oa_version: None
publication: 'Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain'
publication_identifier:
eisbn:
- '9783527671632'
isbn:
- '9783527411986 '
publication_status: published
publisher: Wiley
publist_id: '4513'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Neuronal oscillations scale up and scale down the brain dynamics '
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2013'
...
---
_id: '499'
abstract:
- lang: eng
text: Exposure of an isogenic bacterial population to a cidal antibiotic typically
fails to eliminate a small fraction of refractory cells. Historically, fractional
killing has been attributed to infrequently dividing or nondividing "persisters."
Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium
smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although
persistence in these studies was characterized by stable numbers of cells, this
apparent stability was actually a dynamic state of balanced division and death.
Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic
pulses that were negatively correlated with cell survival. These behaviors may
reflect epigenetic effects, because KatG pulsing and death were correlated between
sibling cells. Selection of lineages characterized by infrequent KatG pulsing
could allow nonresponsive adaptation during prolonged drug exposure.
article_processing_charge: No
author:
- first_name: Yurichi
full_name: Wakamoto, Yurichi
last_name: Wakamoto
- first_name: Neraaj
full_name: Dhar, Neraaj
last_name: Dhar
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Katrin
full_name: Schneider, Katrin
last_name: Schneider
- first_name: François
full_name: Signorino Gelo, François
last_name: Signorino Gelo
- first_name: Stanislas
full_name: Leibler, Stanislas
last_name: Leibler
- first_name: John
full_name: Mckinney, John
last_name: Mckinney
citation:
ama: Wakamoto Y, Dhar N, Chait RP, et al. Dynamic persistence of antibiotic-stressed
mycobacteria. Science. 2013;339(6115):91-95. doi:10.1126/science.1229858
apa: Wakamoto, Y., Dhar, N., Chait, R. P., Schneider, K., Signorino Gelo, F., Leibler,
S., & Mckinney, J. (2013). Dynamic persistence of antibiotic-stressed mycobacteria.
Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.1229858
chicago: Wakamoto, Yurichi, Neraaj Dhar, Remy P Chait, Katrin Schneider, François
Signorino Gelo, Stanislas Leibler, and John Mckinney. “Dynamic Persistence of
Antibiotic-Stressed Mycobacteria.” Science. American Association for the
Advancement of Science, 2013. https://doi.org/10.1126/science.1229858.
ieee: Y. Wakamoto et al., “Dynamic persistence of antibiotic-stressed mycobacteria,”
Science, vol. 339, no. 6115. American Association for the Advancement of
Science, pp. 91–95, 2013.
ista: Wakamoto Y, Dhar N, Chait RP, Schneider K, Signorino Gelo F, Leibler S, Mckinney
J. 2013. Dynamic persistence of antibiotic-stressed mycobacteria. Science. 339(6115),
91–95.
mla: Wakamoto, Yurichi, et al. “Dynamic Persistence of Antibiotic-Stressed Mycobacteria.”
Science, vol. 339, no. 6115, American Association for the Advancement of
Science, 2013, pp. 91–95, doi:10.1126/science.1229858.
short: Y. Wakamoto, N. Dhar, R.P. Chait, K. Schneider, F. Signorino Gelo, S. Leibler,
J. Mckinney, Science 339 (2013) 91–95.
date_created: 2018-12-11T11:46:48Z
date_published: 2013-01-04T00:00:00Z
date_updated: 2025-09-30T07:29:30Z
day: '04'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1126/science.1229858
external_id:
isi:
- '000312985800059'
intvolume: ' 339'
isi: 1
issue: '6115'
language:
- iso: eng
month: '01'
oa_version: None
page: 91 - 95
publication: Science
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7321'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Dynamic persistence of antibiotic-stressed mycobacteria
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 339
year: '2013'
...
---
_id: '3262'
abstract:
- lang: eng
text: Living cells must control the reading out or "expression" of information
encoded in their genomes, and this regulation often is mediated by transcription
factors--proteins that bind to DNA and either enhance or repress the expression
of nearby genes. But the expression of transcription factor proteins is itself
regulated, and many transcription factors regulate their own expression in addition
to responding to other input signals. Here we analyze the simplest of such self-regulatory
circuits, asking how parameters can be chosen to optimize information transmission
from inputs to outputs in the steady state. Some nonzero level of self-regulation
is almost always optimal, with self-activation dominant when transcription factor
concentrations are low and self-repression dominant when concentrations are high.
In steady state the optimal self-activation is never strong enough to induce bistability,
although there is a limit in which the optimal parameters are very close to the
critical point.
acknowledgement: "We thank T. Gregor, E. F. Wieschaus, and, especially, C. G. Callan
for helpful discussions.\r\nWork at Princeton was supported in part by NSF Grants
No. PHY–0957573 and No. CCF–0939370, by NIH Grant No. R01 GM077599, and by the W.
M. Keck Foundation. For part of this work, G.T. was supported in part by NSF Grant
No. EF–0928048 and by the Vice Provost for Research at the University of Pennsylvania."
article_number: '041903'
article_processing_charge: No
arxiv: 1
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Aleksandra
full_name: Walczak, Aleksandra
last_name: Walczak
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Tkačik G, Walczak A, Bialek W. Optimizing information flow in small genetic
networks. III. A self-interacting gene. Physical Review E statistical nonlinear
and soft matter physics . 2012;85(4). doi:10.1103/PhysRevE.85.041903
apa: Tkačik, G., Walczak, A., & Bialek, W. (2012). Optimizing information flow
in small genetic networks. III. A self-interacting gene. Physical Review E
Statistical Nonlinear and Soft Matter Physics . American Institute of Physics.
https://doi.org/10.1103/PhysRevE.85.041903
chicago: Tkačik, Gašper, Aleksandra Walczak, and William Bialek. “Optimizing Information
Flow in Small Genetic Networks. III. A Self-Interacting Gene.” Physical Review
E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics,
2012. https://doi.org/10.1103/PhysRevE.85.041903.
ieee: G. Tkačik, A. Walczak, and W. Bialek, “Optimizing information flow in small
genetic networks. III. A self-interacting gene,” Physical Review E statistical
nonlinear and soft matter physics , vol. 85, no. 4. American Institute of
Physics, 2012.
ista: Tkačik G, Walczak A, Bialek W. 2012. Optimizing information flow in small
genetic networks. III. A self-interacting gene. Physical Review E statistical
nonlinear and soft matter physics . 85(4), 041903.
mla: Tkačik, Gašper, et al. “Optimizing Information Flow in Small Genetic Networks.
III. A Self-Interacting Gene.” Physical Review E Statistical Nonlinear and
Soft Matter Physics , vol. 85, no. 4, 041903, American Institute of Physics,
2012, doi:10.1103/PhysRevE.85.041903.
short: G. Tkačik, A. Walczak, W. Bialek, Physical Review E Statistical Nonlinear
and Soft Matter Physics 85 (2012).
corr_author: '1'
date_created: 2018-12-11T12:02:20Z
date_published: 2012-04-01T00:00:00Z
date_updated: 2025-09-30T07:41:44Z
day: '01'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.85.041903
external_id:
arxiv:
- '1112.5026'
isi:
- '000302410200006'
intvolume: ' 85'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1112.5026
month: '04'
oa: 1
oa_version: Preprint
publication: ' Physical Review E statistical nonlinear and soft matter physics '
publication_status: published
publisher: American Institute of Physics
publist_id: '3386'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Optimizing information flow in small genetic networks. III. A self-interacting
gene
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 85
year: '2012'
...
---
_id: '3274'
abstract:
- lang: eng
text: A boundary element model of a tunnel running through horizontally layered
soil with anisotropic material properties is presented. Since there is no analytical
fundamental solution for wave propagation inside a layered orthotropic medium
in 3D, the fundamental displacements and stresses have to be calculated numerically.
In our model this is done in the Fourier domain with respect to space and time.
The assumption of a straight tunnel with infinite extension in the x direction
makes it possible to decouple the system for every wave number kx, leading to
a 2.5D-problem, which is suited for parallel computation. The special form of
the fundamental solution, resulting from our Fourier ansatz, and the fact, that
the calculation of the boundary integral equation is performed in the Fourier
domain, enhances the stability and efficiency of the numerical calculations.
acknowledgement: This work was supported by the Austrian Federal Ministry of Transport,
Innovation and Technology under the Grant Bmvit-isb2 and the FFG under the project
Pr. Nr. 809089.
article_processing_charge: No
author:
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Wolfgang
full_name: Kreuzer, Wolfgang
last_name: Kreuzer
- first_name: Holger
full_name: Waubke, Holger
last_name: Waubke
- first_name: Peter
full_name: Balazs, Peter
last_name: Balazs
citation:
ama: Rieckh G, Kreuzer W, Waubke H, Balazs P. A 2.5D-Fourier-BEM model for vibrations
in a tunnel running through layered anisotropic soil. Engineering Analysis
with Boundary Elements. 2012;36(6):960-967. doi:10.1016/j.enganabound.2011.12.014
apa: Rieckh, G., Kreuzer, W., Waubke, H., & Balazs, P. (2012). A 2.5D-Fourier-BEM
model for vibrations in a tunnel running through layered anisotropic soil.
Engineering Analysis with Boundary Elements. Elsevier. https://doi.org/10.1016/j.enganabound.2011.12.014
chicago: Rieckh, Georg, Wolfgang Kreuzer, Holger Waubke, and Peter Balazs. “A 2.5D-Fourier-BEM
Model for Vibrations in a Tunnel Running through Layered Anisotropic Soil.”
Engineering Analysis with Boundary Elements. Elsevier, 2012. https://doi.org/10.1016/j.enganabound.2011.12.014.
ieee: G. Rieckh, W. Kreuzer, H. Waubke, and P. Balazs, “A 2.5D-Fourier-BEM model
for vibrations in a tunnel running through layered anisotropic soil,” Engineering
Analysis with Boundary Elements, vol. 36, no. 6. Elsevier, pp. 960–967, 2012.
ista: Rieckh G, Kreuzer W, Waubke H, Balazs P. 2012. A 2.5D-Fourier-BEM model for
vibrations in a tunnel running through layered anisotropic soil. Engineering
Analysis with Boundary Elements. 36(6), 960–967.
mla: Rieckh, Georg, et al. “A 2.5D-Fourier-BEM Model for Vibrations in a Tunnel
Running through Layered Anisotropic Soil.” Engineering Analysis with Boundary
Elements, vol. 36, no. 6, Elsevier, 2012, pp. 960–67, doi:10.1016/j.enganabound.2011.12.014.
short: G. Rieckh, W. Kreuzer, H. Waubke, P. Balazs, Engineering Analysis with Boundary
Elements 36 (2012) 960–967.
corr_author: '1'
date_created: 2018-12-11T12:02:24Z
date_published: 2012-06-01T00:00:00Z
date_updated: 2025-09-30T07:41:13Z
day: '01'
department:
- _id: GaTk
doi: 10.1016/j.enganabound.2011.12.014
external_id:
isi:
- '000301691600005'
intvolume: ' 36'
isi: 1
issue: '6'
language:
- iso: eng
month: '06'
oa_version: None
page: 960 - 967
publication: ' Engineering Analysis with Boundary Elements'
publication_status: published
publisher: Elsevier
publist_id: '3372'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered
anisotropic soil
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 36
year: '2012'
...
---
_id: '3374'
abstract:
- lang: eng
text: Genetic regulatory networks enable cells to respond to changes in internal
and external conditions by dynamically coordinating their gene expression profiles.
Our ability to make quantitative measurements in these biochemical circuits has
deepened our understanding of what kinds of computations genetic regulatory networks
can perform, and with what reliability. These advances have motivated researchers
to look for connections between the architecture and function of genetic regulatory
networks. Transmitting information between a network's inputs and outputs has
been proposed as one such possible measure of function, relevant in certain biological
contexts. Here we summarize recent developments in the application of information
theory to gene regulatory networks. We first review basic concepts in information
theory necessary for understanding recent work. We then discuss the functional
complexity of gene regulation, which arises from the molecular nature of the regulatory
interactions. We end by reviewing some experiments that support the view that
genetic networks responsible for early development of multicellular organisms
might be maximizing transmitted 'positional information'.
article_number: '153102'
article_processing_charge: No
arxiv: 1
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Aleksandra
full_name: Walczak, Aleksandra
last_name: Walczak
citation:
ama: 'Tkačik G, Walczak A. Information transmission in genetic regulatory networks
a review. Journal of Physics: Condensed Matter. 2011;23(15). doi:10.1088/0953-8984/23/15/153102'
apa: 'Tkačik, G., & Walczak, A. (2011). Information transmission in genetic
regulatory networks a review. Journal of Physics: Condensed Matter. IOP
Publishing. https://doi.org/10.1088/0953-8984/23/15/153102'
chicago: 'Tkačik, Gašper, and Aleksandra Walczak. “Information Transmission in Genetic
Regulatory Networks a Review.” Journal of Physics: Condensed Matter. IOP
Publishing, 2011. https://doi.org/10.1088/0953-8984/23/15/153102.'
ieee: 'G. Tkačik and A. Walczak, “Information transmission in genetic regulatory
networks a review,” Journal of Physics: Condensed Matter, vol. 23, no.
15. IOP Publishing, 2011.'
ista: 'Tkačik G, Walczak A. 2011. Information transmission in genetic regulatory
networks a review. Journal of Physics: Condensed Matter. 23(15), 153102.'
mla: 'Tkačik, Gašper, and Aleksandra Walczak. “Information Transmission in Genetic
Regulatory Networks a Review.” Journal of Physics: Condensed Matter, vol.
23, no. 15, 153102, IOP Publishing, 2011, doi:10.1088/0953-8984/23/15/153102.'
short: 'G. Tkačik, A. Walczak, Journal of Physics: Condensed Matter 23 (2011).'
corr_author: '1'
date_created: 2018-12-11T12:02:58Z
date_published: 2011-04-01T00:00:00Z
date_updated: 2025-09-30T08:56:23Z
day: '01'
department:
- _id: GaTk
doi: 10.1088/0953-8984/23/15/153102
external_id:
arxiv:
- '1101.4240'
isi:
- '000289199800002'
intvolume: ' 23'
isi: 1
issue: '15'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1101.4240
month: '04'
oa: 1
oa_version: Submitted Version
publication: 'Journal of Physics: Condensed Matter'
publication_status: published
publisher: IOP Publishing
publist_id: '3233'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Information transmission in genetic regulatory networks a review
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 23
year: '2011'
...
---
_id: '3384'
abstract:
- lang: eng
text: Here we introduce a database of calibrated natural images publicly available
through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we
acquired about six-megapixel images of Okavango Delta of Botswana, a tropical
savanna habitat similar to where the human eye is thought to have evolved. Some
sequences of images were captured unsystematically while following a baboon troop,
while others were designed to vary a single parameter such as aperture, object
distance, time of day or position on the horizon. Images are available in the
raw RGB format and in grayscale. Images are also available in units relevant to
the physiology of human cone photoreceptors, where pixel values represent the
expected number of photoisomerizations per second for cones sensitive to long
(L), medium (M) and short (S) wavelengths. This database is distributed under
a Creative Commons Attribution-Noncommercial Unported license to facilitate research
in computer vision, psychophysics of perception, and visual neuroscience.
article_number: e20409
article_processing_charge: No
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Patrick
full_name: Garrigan, Patrick
last_name: Garrigan
- first_name: Charles
full_name: Ratliff, Charles
last_name: Ratliff
- first_name: Grega
full_name: Milcinski, Grega
last_name: Milcinski
- first_name: Jennifer
full_name: Klein, Jennifer
last_name: Klein
- first_name: Lucia
full_name: Seyfarth, Lucia
last_name: Seyfarth
- first_name: Peter
full_name: Sterling, Peter
last_name: Sterling
- first_name: David
full_name: Brainard, David
last_name: Brainard
- first_name: Vijay
full_name: Balasubramanian, Vijay
last_name: Balasubramanian
citation:
ama: Tkačik G, Garrigan P, Ratliff C, et al. Natural images from the birthplace
of the human eye. PLoS One. 2011;6(6). doi:10.1371/journal.pone.0020409
apa: Tkačik, G., Garrigan, P., Ratliff, C., Milcinski, G., Klein, J., Seyfarth,
L., … Balasubramanian, V. (2011). Natural images from the birthplace of the human
eye. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0020409
chicago: Tkačik, Gašper, Patrick Garrigan, Charles Ratliff, Grega Milcinski, Jennifer
Klein, Lucia Seyfarth, Peter Sterling, David Brainard, and Vijay Balasubramanian.
“Natural Images from the Birthplace of the Human Eye.” PLoS One. Public
Library of Science, 2011. https://doi.org/10.1371/journal.pone.0020409.
ieee: G. Tkačik et al., “Natural images from the birthplace of the human
eye,” PLoS One, vol. 6, no. 6. Public Library of Science, 2011.
ista: Tkačik G, Garrigan P, Ratliff C, Milcinski G, Klein J, Seyfarth L, Sterling
P, Brainard D, Balasubramanian V. 2011. Natural images from the birthplace of
the human eye. PLoS One. 6(6), e20409.
mla: Tkačik, Gašper, et al. “Natural Images from the Birthplace of the Human Eye.”
PLoS One, vol. 6, no. 6, e20409, Public Library of Science, 2011, doi:10.1371/journal.pone.0020409.
short: G. Tkačik, P. Garrigan, C. Ratliff, G. Milcinski, J. Klein, L. Seyfarth,
P. Sterling, D. Brainard, V. Balasubramanian, PLoS One 6 (2011).
corr_author: '1'
date_created: 2018-12-11T12:03:01Z
date_published: 2011-06-16T00:00:00Z
date_updated: 2025-09-30T08:47:57Z
day: '16'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0020409
external_id:
isi:
- '000291734100007'
file:
- access_level: open_access
checksum: 307d4356916471306e3705ac65b82fa1
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:09:25Z
date_updated: 2020-07-14T12:46:11Z
file_id: '4749'
file_name: IST-2015-379-v1+1_journal.pone.0020409.pdf
file_size: 1424768
relation: main_file
file_date_updated: 2020-07-14T12:46:11Z
has_accepted_license: '1'
intvolume: ' 6'
isi: 1
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '3223'
pubrep_id: '379'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Natural images from the birthplace of the human eye
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 6
year: '2011'
...