---
_id: '2850'
abstract:
- lang: eng
text: "Recent work emphasizes that the maximum entropy principle provides a bridge
between statistical mechanics models for collective behavior in neural networks
and experiments on networks of real neurons. Most of this work has focused on
capturing the measured correlations among pairs of neurons. Here we suggest an
alternative, constructing models that are consistent with the distribution of
global network activity, i.e. the probability that K out of N cells in the network
generate action potentials in the same small time bin. The inverse problem that
we need to solve in constructing the model is analytically tractable, and provides
a natural 'thermodynamics' for the network in the limit of large N. We analyze
the responses of neurons in a small patch of the retina to naturalistic stimuli,
and find that the implied thermodynamics is very close to an unusual critical
point, in which the entropy (in proper units) is exactly equal to the energy.
© 2013 IOP Publishing Ltd and SISSA Medialab srl.\r\n"
acknowledgement: "his work was supported in part by NSF Grants IIS-0613435 and PHY-0957573,
by NIH Grants R01 EY14196 and P50 GM071508, by the Fannie and John Hertz Foundation,
by the Human Frontiers Science Program, by the Swartz Foundation, and by the WM
Keck Foundation.\r\n"
article_number: P03011
article_processing_charge: No
article_type: original
author:
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
- first_name: Thierry
full_name: Mora, Thierry
last_name: Mora
- first_name: Dario
full_name: Amodei, Dario
last_name: Amodei
- first_name: Michael
full_name: Berry, Michael
last_name: Berry
- first_name: William
full_name: Bialek, William
last_name: Bialek
citation:
ama: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. The simplest maximum
entropy model for collective behavior in a neural network. Journal of Statistical
Mechanics Theory and Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03011
apa: Tkačik, G., Marre, O., Mora, T., Amodei, D., Berry, M., & Bialek, W. (2013).
The simplest maximum entropy model for collective behavior in a neural network.
Journal of Statistical Mechanics Theory and Experiment. IOP Publishing
Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03011
chicago: Tkačik, Gašper, Olivier Marre, Thierry Mora, Dario Amodei, Michael Berry,
and William Bialek. “The Simplest Maximum Entropy Model for Collective Behavior
in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment.
IOP Publishing Ltd., 2013. https://doi.org/10.1088/1742-5468/2013/03/P03011.
ieee: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, and W. Bialek, “The simplest
maximum entropy model for collective behavior in a neural network,” Journal
of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing
Ltd., 2013.
ista: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. 2013. The simplest
maximum entropy model for collective behavior in a neural network. Journal of
Statistical Mechanics Theory and Experiment. 2013(3), P03011.
mla: Tkačik, Gašper, et al. “The Simplest Maximum Entropy Model for Collective Behavior
in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment,
vol. 2013, no. 3, P03011, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03011.
short: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, W. Bialek, Journal of
Statistical Mechanics Theory and Experiment 2013 (2013).
date_created: 2018-12-11T11:59:55Z
date_published: 2013-03-12T00:00:00Z
date_updated: 2021-01-12T07:00:14Z
day: '12'
department:
- _id: GaTk
doi: 10.1088/1742-5468/2013/03/P03011
external_id:
arxiv:
- '1207.6319'
intvolume: ' 2013'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1207.6319
month: '03'
oa: 1
oa_version: Preprint
publication: Journal of Statistical Mechanics Theory and Experiment
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '3942'
quality_controlled: '1'
scopus_import: 1
status: public
title: The simplest maximum entropy model for collective behavior in a neural network
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2013
year: '2013'
...
---
_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
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 Ltd. 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 Ltd., 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 Ltd., 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 Ltd., 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: 2021-01-12T07:00:14Z
day: '12'
department:
- _id: GaTk
doi: 10.1088/1742-5468/2013/03/P03015
intvolume: ' 2013'
issue: '3'
language:
- iso: eng
month: '03'
oa_version: None
publication: Journal of Statistical Mechanics Theory and Experiment
publication_status: published
publisher: IOP Publishing Ltd.
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2013
year: '2013'
...
---
_id: '2857'
abstract:
- lang: eng
text: In the vibrant field of optogenetics, optics and genetic targeting are combined
to commandeer cellular functions, such as the neuronal action potential, by optically
stimulating light-sensitive ion channels expressed in the cell membrane. One broadly
applicable manifestation of this approach are covalently attached photochromic
tethered ligands (PTLs) that allow activating ligand-gated ion channels with outstanding
spatial and temporal resolution. Here, we describe all steps towards the successful
development and application of PTL-gated ion channels in cell lines and primary
cells. The basis for these experiments forms a combination of molecular modeling,
genetic engineering, cell culture, and electrophysiology. The light-gated glutamate
receptor (LiGluR), which consists of the PTL-functionalized GluK2 receptor, serves
as a model.
alternative_title:
- MIMB
author:
- first_name: Stephanie
full_name: Szobota, Stephanie
last_name: Szobota
- first_name: Catherine
full_name: Mckenzie, Catherine
id: 3EEDE19A-F248-11E8-B48F-1D18A9856A87
last_name: Mckenzie
- first_name: Harald L
full_name: Janovjak, Harald L
id: 33BA6C30-F248-11E8-B48F-1D18A9856A87
last_name: Janovjak
orcid: 0000-0002-8023-9315
citation:
ama: Szobota S, Mckenzie C, Janovjak HL. Optical control of ligand-gated ion channels.
Methods in Molecular Biology. 2013;998:417-435. doi:10.1007/978-1-62703-351-0_32
apa: Szobota, S., Mckenzie, C., & Janovjak, H. L. (2013). Optical control of
ligand-gated ion channels. Methods in Molecular Biology. Springer. https://doi.org/10.1007/978-1-62703-351-0_32
chicago: Szobota, Stephanie, Catherine Mckenzie, and Harald L Janovjak. “Optical
Control of Ligand-Gated Ion Channels.” Methods in Molecular Biology. Springer,
2013. https://doi.org/10.1007/978-1-62703-351-0_32.
ieee: S. Szobota, C. Mckenzie, and H. L. Janovjak, “Optical control of ligand-gated
ion channels,” Methods in Molecular Biology, vol. 998. Springer, pp. 417–435,
2013.
ista: Szobota S, Mckenzie C, Janovjak HL. 2013. Optical control of ligand-gated
ion channels. Methods in Molecular Biology. 998, 417–435.
mla: Szobota, Stephanie, et al. “Optical Control of Ligand-Gated Ion Channels.”
Methods in Molecular Biology, vol. 998, Springer, 2013, pp. 417–35, doi:10.1007/978-1-62703-351-0_32.
short: S. Szobota, C. Mckenzie, H.L. Janovjak, Methods in Molecular Biology 998
(2013) 417–435.
date_created: 2018-12-11T11:59:57Z
date_published: 2013-02-22T00:00:00Z
date_updated: 2021-01-12T07:00:17Z
day: '22'
ddc:
- '570'
department:
- _id: HaJa
doi: 10.1007/978-1-62703-351-0_32
ec_funded: 1
file:
- access_level: open_access
checksum: 1701f0d989f27ddac471b19a894ec0d1
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:34Z
date_updated: 2020-07-14T12:45:51Z
file_id: '4952'
file_name: IST-2017-834-v1+1_szobota.pdf
file_size: 336734
relation: main_file
file_date_updated: 2020-07-14T12:45:51Z
has_accepted_license: '1'
intvolume: ' 998'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Submitted Version
page: 417 - 435
project:
- _id: 255BFFFA-B435-11E9-9278-68D0E5697425
grant_number: RGY0084/2012
name: In situ real-time imaging of neurotransmitter signaling using designer optical
sensors (HFSP Young Investigator)
- _id: 25548C20-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303564'
name: Microbial Ion Channels for Synthetic Neurobiology
publication: Methods in Molecular Biology
publication_status: published
publisher: Springer
publist_id: '3932'
pubrep_id: '834'
quality_controlled: '1'
scopus_import: 1
status: public
title: Optical control of ligand-gated ion channels
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 998
year: '2013'
...
---
_id: '2860'
abstract:
- lang: eng
text: 'In the hippocampus, cell assemblies forming mnemonic representations of space
are thought to arise as a result of changes in functional connections of pyramidal
cells. We have found that CA1 interneuron circuits are also reconfigured during
goal-oriented spatial learning through modification of inputs from pyramidal cells.
As learning progressed, new pyramidal assemblies expressed in theta cycles alternated
with previously established ones, and eventually overtook them. The firing patterns
of interneurons developed a relationship to new, learning-related assemblies:
some interneurons associated their activity with new pyramidal assemblies while
some others dissociated from them. These firing associations were explained by
changes in the weight of monosynaptic inputs received by interneurons from new
pyramidal assemblies, as these predicted the associational changes. Spatial learning
thus engages circuit modifications in the hippocampus that incorporate a redistribution
of inhibitory activity that might assist in the segregation of competing pyramidal
cell assembly patterns in space and time.'
acknowledgement: D.D. and J.C. were supported by a MRC Intramural Programme Grant
U138197111
author:
- first_name: David
full_name: Dupret, David
last_name: Dupret
- first_name: Joseph
full_name: O'Neill, Joseph
id: 426376DC-F248-11E8-B48F-1D18A9856A87
last_name: O'Neill
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
citation:
ama: Dupret D, O’Neill J, Csicsvari JL. Dynamic reconfiguration of hippocampal interneuron
circuits during spatial learning. Neuron. 2013;78(1):166-180. doi:10.1016/j.neuron.2013.01.033
apa: Dupret, D., O’Neill, J., & Csicsvari, J. L. (2013). Dynamic reconfiguration
of hippocampal interneuron circuits during spatial learning. Neuron. Elsevier.
https://doi.org/10.1016/j.neuron.2013.01.033
chicago: Dupret, David, Joseph O’Neill, and Jozsef L Csicsvari. “Dynamic Reconfiguration
of Hippocampal Interneuron Circuits during Spatial Learning.” Neuron. Elsevier,
2013. https://doi.org/10.1016/j.neuron.2013.01.033.
ieee: D. Dupret, J. O’Neill, and J. L. Csicsvari, “Dynamic reconfiguration of hippocampal
interneuron circuits during spatial learning,” Neuron, vol. 78, no. 1.
Elsevier, pp. 166–180, 2013.
ista: Dupret D, O’Neill J, Csicsvari JL. 2013. Dynamic reconfiguration of hippocampal
interneuron circuits during spatial learning. Neuron. 78(1), 166–180.
mla: Dupret, David, et al. “Dynamic Reconfiguration of Hippocampal Interneuron Circuits
during Spatial Learning.” Neuron, vol. 78, no. 1, Elsevier, 2013, pp. 166–80,
doi:10.1016/j.neuron.2013.01.033.
short: D. Dupret, J. O’Neill, J.L. Csicsvari, Neuron 78 (2013) 166–180.
date_created: 2018-12-11T11:59:59Z
date_published: 2013-03-21T00:00:00Z
date_updated: 2021-01-12T07:00:19Z
day: '21'
ddc:
- '570'
department:
- _id: JoCs
doi: 10.1016/j.neuron.2013.01.033
ec_funded: 1
file:
- access_level: open_access
checksum: 0e18cb8561153ddb50bb5af16e7c9e97
content_type: application/pdf
creator: dernst
date_created: 2019-01-23T08:08:07Z
date_updated: 2020-07-14T12:45:52Z
file_id: '5877'
file_name: 2013_Neuron_Dupret.pdf
file_size: 2637837
relation: main_file
file_date_updated: 2020-07-14T12:45:52Z
has_accepted_license: '1'
intvolume: ' 78'
issue: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '03'
oa: 1
oa_version: Published Version
page: 166 - 180
project:
- _id: 257A4776-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '281511'
name: Memory-related information processing in neuronal circuits of the hippocampus
and entorhinal cortex
publication: Neuron
publication_status: published
publisher: Elsevier
publist_id: '3929'
quality_controlled: '1'
scopus_import: 1
status: public
title: Dynamic reconfiguration of hippocampal interneuron circuits during spatial
learning
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 78
year: '2013'
...
---
_id: '2855'
abstract:
- lang: eng
text: Genomic imprinting leads to preferred expression of either the maternal or
paternal alleles of a subset of genes. Imprinting is essential for mammalian development,
and its deregulation causes many diseases. However, the functional relevance of
imprinting at the cellular level is poorly understood for most imprinted genes.
We used mosaic analysis with double markers (MADM) in mice to create uniparental
disomies (UPDs) and to visualize imprinting effects with single-cell resolution.
Although chromosome 12 UPD did not produce detectable phenotypes, chromosome 7
UPD caused highly significant paternal growth dominance in the liver and lung,
but not in the brain or heart. A single gene on chromosome 7, encoding the secreted
insulin-like growth factor 2 (IGF2), accounts for most of the paternal dominance
effect. Mosaic analyses implied additional imprinted loci on chromosome 7 acting
cell autonomously to transmit the IGF2 signal. Our study reveals chromosome- and
cell-type specificity of genomic imprinting effects.
author:
- first_name: Simon
full_name: Hippenmeyer, Simon
id: 37B36620-F248-11E8-B48F-1D18A9856A87
last_name: Hippenmeyer
orcid: 0000-0003-2279-1061
- first_name: Randy
full_name: Johnson, Randy
last_name: Johnson
- first_name: Liqun
full_name: Luo, Liqun
last_name: Luo
citation:
ama: Hippenmeyer S, Johnson R, Luo L. Mosaic analysis with double markers reveals
cell type specific paternal growth dominance. Cell Reports. 2013;3(3):960-967.
doi:10.1016/j.celrep.2013.02.002
apa: Hippenmeyer, S., Johnson, R., & Luo, L. (2013). Mosaic analysis with double
markers reveals cell type specific paternal growth dominance. Cell Reports.
Cell Press. https://doi.org/10.1016/j.celrep.2013.02.002
chicago: Hippenmeyer, Simon, Randy Johnson, and Liqun Luo. “Mosaic Analysis with
Double Markers Reveals Cell Type Specific Paternal Growth Dominance.” Cell
Reports. Cell Press, 2013. https://doi.org/10.1016/j.celrep.2013.02.002.
ieee: S. Hippenmeyer, R. Johnson, and L. Luo, “Mosaic analysis with double markers
reveals cell type specific paternal growth dominance,” Cell Reports, vol.
3, no. 3. Cell Press, pp. 960–967, 2013.
ista: Hippenmeyer S, Johnson R, Luo L. 2013. Mosaic analysis with double markers
reveals cell type specific paternal growth dominance. Cell Reports. 3(3), 960–967.
mla: Hippenmeyer, Simon, et al. “Mosaic Analysis with Double Markers Reveals Cell
Type Specific Paternal Growth Dominance.” Cell Reports, vol. 3, no. 3,
Cell Press, 2013, pp. 960–67, doi:10.1016/j.celrep.2013.02.002.
short: S. Hippenmeyer, R. Johnson, L. Luo, Cell Reports 3 (2013) 960–967.
date_created: 2018-12-11T11:59:57Z
date_published: 2013-03-28T00:00:00Z
date_updated: 2021-01-12T07:00:16Z
day: '28'
ddc:
- '570'
department:
- _id: SiHi
doi: 10.1016/j.celrep.2013.02.002
file:
- access_level: open_access
checksum: 6e977b918e81384cd571ec5a9d812289
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:17:20Z
date_updated: 2020-07-14T12:45:51Z
file_id: '5274'
file_name: IST-2016-405-v1+1_1-s2.0-S2211124713000612-main.pdf
file_size: 1907211
relation: main_file
file_date_updated: 2020-07-14T12:45:51Z
has_accepted_license: '1'
intvolume: ' 3'
issue: '3'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '03'
oa: 1
oa_version: Published Version
page: 960 - 967
publication: Cell Reports
publication_status: published
publisher: Cell Press
publist_id: '3937'
pubrep_id: '405'
quality_controlled: '1'
scopus_import: 1
status: public
title: Mosaic analysis with double markers reveals cell type specific paternal growth
dominance
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2013'
...