---
_id: '1928'
abstract:
- lang: eng
text: In infectious disease epidemiology the basic reproductive ratio, R0, is defined
as the average number of new infections caused by a single infected individual
in a fully susceptible population. Many models describing competition for hosts
between non-interacting pathogen strains in an infinite population lead to the
conclusion that selection favors invasion of new strains if and only if they have
higher R0 values than the resident. Here we demonstrate that this picture fails
in finite populations. Using a simple stochastic SIS model, we show that in general
there is no analogous optimization principle. We find that successive invasions
may in some cases lead to strains that infect a smaller fraction of the host population,
and that mutually invasible pathogen strains exist. In the limit of weak selection
we demonstrate that an optimization principle does exist, although it differs
from R0 maximization. For strains with very large R0, we derive an expression
for this local fitness function and use it to establish a lower bound for the
error caused by neglecting stochastic effects. Furthermore, we apply this weak
selection limit to investigate the selection dynamics in the presence of a trade-off
between the virulence and the transmission rate of a pathogen.
acknowledgement: J.H. received support from the Zdenek Bakala Foundation and the Mobility
Fund of Charles University in Prague.
author:
- first_name: Jan
full_name: Humplik, Jan
id: 2E9627A8-F248-11E8-B48F-1D18A9856A87
last_name: Humplik
- first_name: Alison
full_name: Hill, Alison
last_name: Hill
- first_name: Martin
full_name: Nowak, Martin
last_name: Nowak
citation:
ama: Humplik J, Hill A, Nowak M. Evolutionary dynamics of infectious diseases in
finite populations. Journal of Theoretical Biology. 2014;360:149-162. doi:10.1016/j.jtbi.2014.06.039
apa: Humplik, J., Hill, A., & Nowak, M. (2014). Evolutionary dynamics of infectious
diseases in finite populations. Journal of Theoretical Biology. Elsevier.
https://doi.org/10.1016/j.jtbi.2014.06.039
chicago: Humplik, Jan, Alison Hill, and Martin Nowak. “Evolutionary Dynamics of
Infectious Diseases in Finite Populations.” Journal of Theoretical Biology.
Elsevier, 2014. https://doi.org/10.1016/j.jtbi.2014.06.039.
ieee: J. Humplik, A. Hill, and M. Nowak, “Evolutionary dynamics of infectious diseases
in finite populations,” Journal of Theoretical Biology, vol. 360. Elsevier,
pp. 149–162, 2014.
ista: Humplik J, Hill A, Nowak M. 2014. Evolutionary dynamics of infectious diseases
in finite populations. Journal of Theoretical Biology. 360, 149–162.
mla: Humplik, Jan, et al. “Evolutionary Dynamics of Infectious Diseases in Finite
Populations.” Journal of Theoretical Biology, vol. 360, Elsevier, 2014,
pp. 149–62, doi:10.1016/j.jtbi.2014.06.039.
short: J. Humplik, A. Hill, M. Nowak, Journal of Theoretical Biology 360 (2014)
149–162.
date_created: 2018-12-11T11:54:46Z
date_published: 2014-11-07T00:00:00Z
date_updated: 2021-01-12T06:54:08Z
day: '07'
department:
- _id: GaTk
doi: 10.1016/j.jtbi.2014.06.039
intvolume: ' 360'
language:
- iso: eng
month: '11'
oa_version: None
page: 149 - 162
publication: Journal of Theoretical Biology
publication_status: published
publisher: Elsevier
publist_id: '5166'
scopus_import: 1
status: public
title: Evolutionary dynamics of infectious diseases in finite populations
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 360
year: '2014'
...
---
_id: '1931'
abstract:
- lang: eng
text: A wealth of experimental evidence suggests that working memory circuits preferentially
represent information that is behaviorally relevant. Still, we are missing a mechanistic
account of how these representations come about. Here we provide a simple explanation
for a range of experimental findings, in light of prefrontal circuits adapting
to task constraints by reward-dependent learning. In particular, we model a neural
network shaped by reward-modulated spike-timing dependent plasticity (r-STDP)
and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show
that the experimentally-observed neural representations naturally emerge in an
initially unstructured circuit as it learns to solve several working memory tasks.
These results point to a critical, and previously unappreciated, role for reward-dependent
learning in shaping prefrontal cortex activity.
acknowledgement: Supported in part by EC MEXT project PLICON and the LOEWE-Program
“Neuronal Coordination Research Focus Frankfurt” (NeFF). Jochen Triesch was supported
by the Quandt foundation.
article_number: '57'
author:
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
- first_name: Jochen
full_name: Triesch, Jochen
last_name: Triesch
citation:
ama: Savin C, Triesch J. Emergence of task-dependent representations in working
memory circuits. Frontiers in Computational Neuroscience. 2014;8(MAY).
doi:10.3389/fncom.2014.00057
apa: Savin, C., & Triesch, J. (2014). Emergence of task-dependent representations
in working memory circuits. Frontiers in Computational Neuroscience. Frontiers
Research Foundation. https://doi.org/10.3389/fncom.2014.00057
chicago: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations
in Working Memory Circuits.” Frontiers in Computational Neuroscience. Frontiers
Research Foundation, 2014. https://doi.org/10.3389/fncom.2014.00057.
ieee: C. Savin and J. Triesch, “Emergence of task-dependent representations in working
memory circuits,” Frontiers in Computational Neuroscience, vol. 8, no.
MAY. Frontiers Research Foundation, 2014.
ista: Savin C, Triesch J. 2014. Emergence of task-dependent representations in working
memory circuits. Frontiers in Computational Neuroscience. 8(MAY), 57.
mla: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations
in Working Memory Circuits.” Frontiers in Computational Neuroscience, vol.
8, no. MAY, 57, Frontiers Research Foundation, 2014, doi:10.3389/fncom.2014.00057.
short: C. Savin, J. Triesch, Frontiers in Computational Neuroscience 8 (2014).
date_created: 2018-12-11T11:54:46Z
date_published: 2014-05-28T00:00:00Z
date_updated: 2021-01-12T06:54:09Z
day: '28'
department:
- _id: GaTk
doi: 10.3389/fncom.2014.00057
intvolume: ' 8'
issue: MAY
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035833/
month: '05'
oa: 1
oa_version: Submitted Version
publication: Frontiers in Computational Neuroscience
publication_status: published
publisher: Frontiers Research Foundation
publist_id: '5163'
quality_controlled: '1'
scopus_import: 1
status: public
title: Emergence of task-dependent representations in working memory circuits
type: journal_article
user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2014'
...
---
_id: '2028'
abstract:
- lang: eng
text: 'Understanding the dynamics of noisy neurons remains an important challenge
in neuroscience. Here, we describe a simple probabilistic model that accurately
describes the firing behavior in a large class (type II) of neurons. To demonstrate
the usefulness of this model, we show how it accurately predicts the interspike
interval (ISI) distributions, bursting patterns and mean firing rates found by:
(1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental
data from squid giant axon with a noisy input current and (3) experimental data
on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple
model has 6 parameters, however, in some cases, two of these parameters are coupled
and only 5 parameters account for much of the known behavior. From these parameters,
many properties of spiking can be found through simple calculation. Thus, we show
how the complex effects of noise can be understood through a simple and general
probabilistic model.'
acknowledgement: 'This work is supported by AFOSR grant FA 9550-11-1-0165, program
grant RPG 24/2012 from the Human Frontiers of Science (DBF) and travel support from
the European Commission Marie Curie International Reintegration Grant PIRG04-GA-2008-239429
(KB). DP was supported by NIHR01 GM104987 and the Wyss Institute of Biologically
Inspired Engineering. '
article_processing_charge: No
author:
- first_name: Katarina
full_name: Bodova, Katarina
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bodova
orcid: 0000-0002-7214-0171
- first_name: David
full_name: Paydarfar, David
last_name: Paydarfar
- first_name: Daniel
full_name: Forger, Daniel
last_name: Forger
citation:
ama: Bodova K, Paydarfar D, Forger D. Characterizing spiking in noisy type II neurons.
Journal of Theoretical Biology. 2014;365:40-54. doi:10.1016/j.jtbi.2014.09.041
apa: Bodova, K., Paydarfar, D., & Forger, D. (2014). Characterizing spiking
in noisy type II neurons. Journal of Theoretical Biology. Academic Press.
https://doi.org/10.1016/j.jtbi.2014.09.041
chicago: Bodova, Katarina, David Paydarfar, and Daniel Forger. “Characterizing Spiking
in Noisy Type II Neurons.” Journal of Theoretical Biology. Academic Press,
2014. https://doi.org/10.1016/j.jtbi.2014.09.041.
ieee: K. Bodova, D. Paydarfar, and D. Forger, “Characterizing spiking in noisy type
II neurons,” Journal of Theoretical Biology, vol. 365. Academic Press,
pp. 40–54, 2014.
ista: Bodova K, Paydarfar D, Forger D. 2014. Characterizing spiking in noisy type
II neurons. Journal of Theoretical Biology. 365, 40–54.
mla: Bodova, Katarina, et al. “Characterizing Spiking in Noisy Type II Neurons.”
Journal of Theoretical Biology, vol. 365, Academic Press, 2014, pp. 40–54,
doi:10.1016/j.jtbi.2014.09.041.
short: K. Bodova, D. Paydarfar, D. Forger, Journal of Theoretical Biology 365 (2014)
40–54.
date_created: 2018-12-11T11:55:18Z
date_published: 2014-10-12T00:00:00Z
date_updated: 2022-08-25T14:00:47Z
day: '12'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.jtbi.2014.09.041
file:
- access_level: open_access
checksum: a9dbae18d3233b3dab6944fd3f2cd49e
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:17:58Z
date_updated: 2020-07-14T12:45:25Z
file_id: '5316'
file_name: IST-2016-444-v1+1_1-s2.0-S0022519314005888-main.pdf
file_size: 2679222
relation: main_file
file_date_updated: 2020-07-14T12:45:25Z
has_accepted_license: '1'
intvolume: ' 365'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '10'
oa: 1
oa_version: Published Version
page: 40 - 54
publication: ' Journal of Theoretical Biology'
publication_status: published
publisher: Academic Press
publist_id: '5043'
pubrep_id: '444'
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1016/j.jtbi.2015.03.013
scopus_import: '1'
status: public
title: Characterizing spiking in noisy type II neurons
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: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 365
year: '2014'
...
---
_id: '2183'
abstract:
- lang: eng
text: 'We describe a simple adaptive network of coupled chaotic maps. The network
reaches a stationary state (frozen topology) for all values of the coupling parameter,
although the dynamics of the maps at the nodes of the network can be nontrivial.
The structure of the network shows interesting hierarchical properties and in
certain parameter regions the dynamics is polysynchronous: Nodes can be divided
in differently synchronized classes but, contrary to cluster synchronization,
nodes in the same class need not be connected to each other. These complicated
synchrony patterns have been conjectured to play roles in systems biology and
circuits. The adaptive system we study describes ways whereby this behavior can
evolve from undifferentiated nodes.'
acknowledgement: "V.B.S. is partially supported by contract MEC (Grant No. AYA2010-22111-C03-02).\r\n"
article_number: '062809'
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: Paul
full_name: Glendinning, Paul
last_name: Glendinning
citation:
ama: Botella Soler V, Glendinning P. Hierarchy and polysynchrony in an adaptive
network . Physical Review E Statistical Nonlinear and Soft Matter Physics.
2014;89(6). doi:10.1103/PhysRevE.89.062809
apa: Botella Soler, V., & Glendinning, P. (2014). Hierarchy and polysynchrony
in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter
Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.89.062809
chicago: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony
in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft
Matter Physics. American Institute of Physics, 2014. https://doi.org/10.1103/PhysRevE.89.062809.
ieee: V. Botella Soler and P. Glendinning, “Hierarchy and polysynchrony in an adaptive
network ,” Physical Review E Statistical Nonlinear and Soft Matter Physics,
vol. 89, no. 6. American Institute of Physics, 2014.
ista: Botella Soler V, Glendinning P. 2014. Hierarchy and polysynchrony in an adaptive
network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(6),
062809.
mla: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony
in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft
Matter Physics, vol. 89, no. 6, 062809, American Institute of Physics, 2014,
doi:10.1103/PhysRevE.89.062809.
short: V. Botella Soler, P. Glendinning, Physical Review E Statistical Nonlinear
and Soft Matter Physics 89 (2014).
date_created: 2018-12-11T11:56:11Z
date_published: 2014-06-16T00:00:00Z
date_updated: 2022-08-25T14:04:45Z
day: '16'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.89.062809
ec_funded: 1
intvolume: ' 89'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1403.3209
month: '06'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '4798'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Hierarchy and polysynchrony in an adaptive network '
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 89
year: '2014'
...
---
_id: '2231'
abstract:
- lang: eng
text: Based on the measurements of noise in gene expression performed during the
past decade, it has become customary to think of gene regulation in terms of a
two-state model, where the promoter of a gene can stochastically switch between
an ON and an OFF state. As experiments are becoming increasingly precise and the
deviations from the two-state model start to be observable, we ask about the experimental
signatures of complex multistate promoters, as well as the functional consequences
of this additional complexity. In detail, we i), extend the calculations for noise
in gene expression to promoters described by state transition diagrams with multiple
states, ii), systematically compute the experimentally accessible noise characteristics
for these complex promoters, and iii), use information theory to evaluate the
channel capacities of complex promoter architectures and compare them with the
baseline provided by the two-state model. We find that adding internal states
to the promoter generically decreases channel capacity, except in certain cases,
three of which (cooperativity, dual-role regulation, promoter cycling) we analyze
in detail.
author:
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Rieckh G, Tkačik G. Noise and information transmission in promoters with multiple
internal states. Biophysical Journal. 2014;106(5):1194-1204. doi:10.1016/j.bpj.2014.01.014
apa: Rieckh, G., & Tkačik, G. (2014). Noise and information transmission in
promoters with multiple internal states. Biophysical Journal. Biophysical
Society. https://doi.org/10.1016/j.bpj.2014.01.014
chicago: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in
Promoters with Multiple Internal States.” Biophysical Journal. Biophysical
Society, 2014. https://doi.org/10.1016/j.bpj.2014.01.014.
ieee: G. Rieckh and G. Tkačik, “Noise and information transmission in promoters
with multiple internal states,” Biophysical Journal, vol. 106, no. 5. Biophysical
Society, pp. 1194–1204, 2014.
ista: Rieckh G, Tkačik G. 2014. Noise and information transmission in promoters
with multiple internal states. Biophysical Journal. 106(5), 1194–1204.
mla: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in Promoters
with Multiple Internal States.” Biophysical Journal, vol. 106, no. 5, Biophysical
Society, 2014, pp. 1194–204, doi:10.1016/j.bpj.2014.01.014.
short: G. Rieckh, G. Tkačik, Biophysical Journal 106 (2014) 1194–1204.
date_created: 2018-12-11T11:56:28Z
date_published: 2014-03-04T00:00:00Z
date_updated: 2021-01-12T06:56:10Z
day: '04'
department:
- _id: GaTk
doi: 10.1016/j.bpj.2014.01.014
external_id:
pmid:
- '24606943'
intvolume: ' 106'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026790/
month: '03'
oa: 1
oa_version: Submitted Version
page: 1194 - 1204
pmid: 1
publication: Biophysical Journal
publication_identifier:
issn:
- '00063495'
publication_status: published
publisher: Biophysical Society
publist_id: '4730'
quality_controlled: '1'
scopus_import: 1
status: public
title: Noise and information transmission in promoters with multiple internal states
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 106
year: '2014'
...