---
_id: '7463'
abstract:
- lang: eng
text: Resting-state brain activity is characterized by the presence of neuronal
avalanches showing absence of characteristic size. Such evidence has been interpreted
in the context of criticality and associated with the normal functioning of the
brain. A distinctive attribute of systems at criticality is the presence of long-range
correlations. Thus, to verify the hypothesis that the brain operates close to
a critical point and consequently assess deviations from criticality for diagnostic
purposes, it is of primary importance to robustly and reliably characterize correlations
in resting-state brain activity. Recent works focused on the analysis of narrow-band
electroencephalography (EEG) and magnetoencephalography (MEG) signal amplitude
envelope, showing evidence of long-range temporal correlations (LRTC) in neural
oscillations. However, brain activity is a broadband phenomenon, and a significant
piece of information useful to precisely discriminate between normal (critical)
and pathological behavior (non-critical), may be encoded in the broadband spatio-temporal
cortical dynamics. Here we propose to characterize the temporal correlations in
the broadband brain activity through the lens of neuronal avalanches. To this
end, we consider resting-state EEG and long-term MEG recordings, extract the corresponding
neuronal avalanche sequences, and study their temporal correlations. We demonstrate
that the broadband resting-state brain activity consistently exhibits long-range
power-law correlations in both EEG and MEG recordings, with similar values of
the scaling exponents. Importantly, although we observe that the avalanche size
distribution depends on scale parameters, scaling exponents characterizing long-range
correlations are quite robust. In particular, they are independent of the temporal
binning (scale of analysis), indicating that our analysis captures intrinsic characteristics
of the underlying dynamics. Because neuronal avalanches constitute a fundamental
feature of neural systems with universal characteristics, the proposed approach
may serve as a general, systems- and experiment-independent procedure to infer
the existence of underlying long-range correlations in extended neural systems,
and identify pathological behaviors in the complex spatio-temporal interplay of
cortical rhythms.
acknowledgement: LdA would like to acknowledge the financial support from MIUR-PRIN2017
WZFTZP and VALERE:VAnviteLli pEr la RicErca 2019. FL acknowledges support from the
European Union’s Horizon 2020 research and innovation programme under the Marie
Sklodowska-Curie Grant Agreement No. 754411. HJH would like to thank the Agencies
CAPES and FUNCAP for financial support.
article_processing_charge: No
article_type: original
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
- first_name: Hans J
full_name: Herrmann, Hans J
last_name: Herrmann
- first_name: Lucilla
full_name: de Arcangelis, Lucilla
last_name: de Arcangelis
citation:
ama: Lombardi F, Shriki O, Herrmann HJ, de Arcangelis L. Long-range temporal correlations
in the broadband resting state activity of the human brain revealed by neuronal
avalanches. Neurocomputing. 2021;461:657-666. doi:10.1016/j.neucom.2020.05.126
apa: Lombardi, F., Shriki, O., Herrmann, H. J., & de Arcangelis, L. (2021).
Long-range temporal correlations in the broadband resting state activity of the
human brain revealed by neuronal avalanches. Neurocomputing. Elsevier.
https://doi.org/10.1016/j.neucom.2020.05.126
chicago: Lombardi, Fabrizio, Oren Shriki, Hans J Herrmann, and Lucilla de Arcangelis.
“Long-Range Temporal Correlations in the Broadband Resting State Activity of the
Human Brain Revealed by Neuronal Avalanches.” Neurocomputing. Elsevier,
2021. https://doi.org/10.1016/j.neucom.2020.05.126.
ieee: F. Lombardi, O. Shriki, H. J. Herrmann, and L. de Arcangelis, “Long-range
temporal correlations in the broadband resting state activity of the human brain
revealed by neuronal avalanches,” Neurocomputing, vol. 461. Elsevier, pp.
657–666, 2021.
ista: Lombardi F, Shriki O, Herrmann HJ, de Arcangelis L. 2021. Long-range temporal
correlations in the broadband resting state activity of the human brain revealed
by neuronal avalanches. Neurocomputing. 461, 657–666.
mla: Lombardi, Fabrizio, et al. “Long-Range Temporal Correlations in the Broadband
Resting State Activity of the Human Brain Revealed by Neuronal Avalanches.” Neurocomputing,
vol. 461, Elsevier, 2021, pp. 657–66, doi:10.1016/j.neucom.2020.05.126.
short: F. Lombardi, O. Shriki, H.J. Herrmann, L. de Arcangelis, Neurocomputing 461
(2021) 657–666.
date_created: 2020-02-06T16:09:14Z
date_published: 2021-05-13T00:00:00Z
date_updated: 2023-08-04T10:46:29Z
day: '13'
department:
- _id: GaTk
doi: 10.1016/j.neucom.2020.05.126
ec_funded: 1
external_id:
isi:
- '000704086300015'
intvolume: ' 461'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2020.02.03.930966
month: '05'
oa: 1
oa_version: Preprint
page: 657-666
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Neurocomputing
publication_identifier:
eissn:
- 1872-8286
issn:
- 0925-2312
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Long-range temporal correlations in the broadband resting state activity of
the human brain revealed by neuronal avalanches
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 461
year: '2021'
...
---
_id: '7553'
abstract:
- lang: eng
text: Normative theories and statistical inference provide complementary approaches
for the study of biological systems. A normative theory postulates that organisms
have adapted to efficiently solve essential tasks, and proceeds to mathematically
work out testable consequences of such optimality; parameters that maximize the
hypothesized organismal function can be derived ab initio, without reference to
experimental data. In contrast, statistical inference focuses on efficient utilization
of data to learn model parameters, without reference to any a priori notion of
biological function, utility, or fitness. Traditionally, these two approaches
were developed independently and applied separately. Here we unify them in a coherent
Bayesian framework that embeds a normative theory into a family of maximum-entropy
“optimization priors.” This family defines a smooth interpolation between a data-rich
inference regime (characteristic of “bottom-up” statistical models), and a data-limited
ab inito prediction regime (characteristic of “top-down” normative theory). We
demonstrate the applicability of our framework using data from the visual cortex,
and argue that the flexibility it affords is essential to address a number of
fundamental challenges relating to inference and prediction in complex, high-dimensional
biological problems.
acknowledgement: The authors thank Dario Ringach for providing the V1 receptive fields
and Olivier Marre for providing the retinal receptive fields. W.M. was funded by
the European Union’s Horizon 2020 research and innovation programme under the Marie
Skłodowska-Curie grant agreement no. 754411. M.H. was funded in part by Human Frontiers
Science grant no. HFSP RGP0032/2018.
article_processing_charge: No
author:
- first_name: Wiktor F
full_name: Mlynarski, Wiktor F
id: 358A453A-F248-11E8-B48F-1D18A9856A87
last_name: Mlynarski
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
- first_name: Thomas R
full_name: Sokolowski, Thomas R
id: 3E999752-F248-11E8-B48F-1D18A9856A87
last_name: Sokolowski
orcid: 0000-0002-1287-3779
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. Statistical analysis and optimality
of neural systems. Neuron. 2021;109(7):1227-1241.e5. doi:10.1016/j.neuron.2021.01.020
apa: Mlynarski, W. F., Hledik, M., Sokolowski, T. R., & Tkačik, G. (2021). Statistical
analysis and optimality of neural systems. Neuron. Cell Press. https://doi.org/10.1016/j.neuron.2021.01.020
chicago: Mlynarski, Wiktor F, Michal Hledik, Thomas R Sokolowski, and Gašper Tkačik.
“Statistical Analysis and Optimality of Neural Systems.” Neuron. Cell Press,
2021. https://doi.org/10.1016/j.neuron.2021.01.020.
ieee: W. F. Mlynarski, M. Hledik, T. R. Sokolowski, and G. Tkačik, “Statistical
analysis and optimality of neural systems,” Neuron, vol. 109, no. 7. Cell
Press, p. 1227–1241.e5, 2021.
ista: Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. 2021. Statistical analysis
and optimality of neural systems. Neuron. 109(7), 1227–1241.e5.
mla: Mlynarski, Wiktor F., et al. “Statistical Analysis and Optimality of Neural
Systems.” Neuron, vol. 109, no. 7, Cell Press, 2021, p. 1227–1241.e5, doi:10.1016/j.neuron.2021.01.020.
short: W.F. Mlynarski, M. Hledik, T.R. Sokolowski, G. Tkačik, Neuron 109 (2021)
1227–1241.e5.
date_created: 2020-02-28T11:00:12Z
date_published: 2021-04-07T00:00:00Z
date_updated: 2025-06-30T13:21:05Z
day: '07'
department:
- _id: GaTk
doi: 10.1016/j.neuron.2021.01.020
ec_funded: 1
external_id:
isi:
- '000637809600006'
intvolume: ' 109'
isi: 1
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/848374
month: '04'
oa: 1
oa_version: Preprint
page: 1227-1241.e5
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Neuron
publication_status: published
publisher: Cell Press
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/can-evolution-be-predicted/
record:
- id: '15020'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Statistical analysis and optimality of neural systems
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 109
year: '2021'
...
---
_id: '10077'
abstract:
- lang: eng
text: Although much is known about how single neurons in the hippocampus represent
an animal’s position, how cell-cell interactions contribute to spatial coding
remains poorly understood. Using a novel statistical estimator and theoretical
modeling, both developed in the framework of maximum entropy models, we reveal
highly structured cell-to-cell interactions whose statistics depend on familiar
vs. novel environment. In both conditions the circuit interactions optimize the
encoding of spatial information, but for regimes that differ in the signal-to-noise
ratio of their spatial inputs. Moreover, the topology of the interactions facilitates
linear decodability, making the information easy to read out by downstream circuits.
These findings suggest that the efficient coding hypothesis is not applicable
only to individual neuron properties in the sensory periphery, but also to neural
interactions in the central brain.
acknowledgement: We thank Peter Baracskay, Karola Kaefer and Hugo Malagon-Vina for
the acquisition of the data. We thank Federico Stella for comments on an earlier
version of the manuscript. MN was supported by European Union Horizon 2020 grant
665385, JC was supported by European Research Council consolidator grant 281511,
GT was supported by the Austrian Science Fund (FWF) grant P34015, CS was supported
by an IST fellow grant, National Institute of Mental Health Award 1R01MH125571-01,
by the National Science Foundation under NSF Award No. 1922658 and a Google faculty
award.
article_processing_charge: No
author:
- first_name: Michele
full_name: Nardin, Michele
id: 30BD0376-F248-11E8-B48F-1D18A9856A87
last_name: Nardin
orcid: 0000-0001-8849-6570
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
citation:
ama: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1
interactions optimizes spatial coding across experience. bioRxiv. doi:10.1101/2021.09.28.460602
apa: Nardin, M., Csicsvari, J. L., Tkačik, G., & Savin, C. (n.d.). The structure
of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv.
Cold Spring Harbor Laboratory. https://doi.org/10.1101/2021.09.28.460602
chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin.
“The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across
Experience.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2021.09.28.460602.
ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal
CA1 interactions optimizes spatial coding across experience,” bioRxiv.
Cold Spring Harbor Laboratory.
ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1
interactions optimizes spatial coding across experience. bioRxiv, 10.1101/2021.09.28.460602.
mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes
Spatial Coding across Experience.” BioRxiv, Cold Spring Harbor Laboratory,
doi:10.1101/2021.09.28.460602.
short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, BioRxiv (n.d.).
date_created: 2021-10-04T06:23:34Z
date_published: 2021-09-29T00:00:00Z
date_updated: 2024-03-25T23:30:09Z
day: '29'
department:
- _id: GradSch
- _id: JoCs
- _id: GaTk
doi: 10.1101/2021.09.28.460602
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/10.1101/2021.09.28.460602
month: '09'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _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
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication: bioRxiv
publication_status: submitted
publisher: Cold Spring Harbor Laboratory
related_material:
record:
- id: '11932'
relation: dissertation_contains
status: public
status: public
title: The structure of hippocampal CA1 interactions optimizes spatial coding across
experience
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: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10535'
abstract:
- lang: eng
text: Realistic models of biological processes typically involve interacting components
on multiple scales, driven by changing environment and inherent stochasticity.
Such models are often analytically and numerically intractable. We revisit a dynamic
maximum entropy method that combines a static maximum entropy with a quasi-stationary
approximation. This allows us to reduce stochastic non-equilibrium dynamics expressed
by the Fokker-Planck equation to a simpler low-dimensional deterministic dynamics,
without the need to track microscopic details. Although the method has been previously
applied to a few (rather complicated) applications in population genetics, our
main goal here is to explain and to better understand how the method works. We
demonstrate the usefulness of the method for two widely studied stochastic problems,
highlighting its accuracy in capturing important macroscopic quantities even in
rapidly changing non-stationary conditions. For the Ornstein-Uhlenbeck process,
the method recovers the exact dynamics whilst for a stochastic island model with
migration from other habitats, the approximation retains high macroscopic accuracy
under a wide range of scenarios in a dynamic environment.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "Computational resources for the study were provided by the Institute
of Science and Technology, Austria.\r\nKB received funding from the Scientific Grant
Agency of the Slovak Republic under the Grants Nos. 1/0755/19 and 1/0521/20."
article_number: e1009661
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Katarína
full_name: Bod'ová, Katarína
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bod'ová
orcid: 0000-0002-7214-0171
- first_name: Eniko
full_name: Szep, Eniko
id: 485BB5A4-F248-11E8-B48F-1D18A9856A87
last_name: Szep
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Bodova K, Szep E, Barton NH. Dynamic maximum entropy provides accurate approximation
of structured population dynamics. PLoS Computational Biology. 2021;17(12).
doi:10.1371/journal.pcbi.1009661
apa: Bodova, K., Szep, E., & Barton, N. H. (2021). Dynamic maximum entropy provides
accurate approximation of structured population dynamics. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1009661
chicago: Bodova, Katarina, Eniko Szep, and Nicholas H Barton. “Dynamic Maximum Entropy
Provides Accurate Approximation of Structured Population Dynamics.” PLoS Computational
Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1009661.
ieee: K. Bodova, E. Szep, and N. H. Barton, “Dynamic maximum entropy provides accurate
approximation of structured population dynamics,” PLoS Computational Biology,
vol. 17, no. 12. Public Library of Science, 2021.
ista: Bodova K, Szep E, Barton NH. 2021. Dynamic maximum entropy provides accurate
approximation of structured population dynamics. PLoS Computational Biology. 17(12),
e1009661.
mla: Bodova, Katarina, et al. “Dynamic Maximum Entropy Provides Accurate Approximation
of Structured Population Dynamics.” PLoS Computational Biology, vol. 17,
no. 12, e1009661, Public Library of Science, 2021, doi:10.1371/journal.pcbi.1009661.
short: K. Bodova, E. Szep, N.H. Barton, PLoS Computational Biology 17 (2021).
date_created: 2021-12-12T23:01:27Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-08-01T10:48:04Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1371/journal.pcbi.1009661
external_id:
arxiv:
- '2102.03669'
pmid:
- '34851948'
file:
- access_level: open_access
checksum: dcd185d4f7e0acee25edf1d6537f447e
content_type: application/pdf
creator: dernst
date_created: 2022-05-16T08:53:11Z
date_updated: 2022-05-16T08:53:11Z
file_id: '11383'
file_name: 2021_PLOsComBio_Bodova.pdf
file_size: 2299486
relation: main_file
success: 1
file_date_updated: 2022-05-16T08:53:11Z
has_accepted_license: '1'
intvolume: ' 17'
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS Computational Biology
publication_identifier:
eissn:
- 1553-7358
issn:
- 1553-734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Dynamic maximum entropy provides accurate approximation of structured population
dynamics
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: 17
year: '2021'
...
---
_id: '10579'
abstract:
- lang: eng
text: 'We consider a totally asymmetric simple exclusion process (TASEP) consisting
of particles on a lattice that require binding by a "token" to move. Using a combination
of theory and simulations, we address the following questions: (i) How token binding
kinetics affects the current-density relation; (ii) How the current-density relation
depends on the scarcity of tokens; (iii) How tokens propagate the effects of the
locally-imposed disorder (such a slow site) over the entire lattice; (iv) How
a shared pool of tokens couples concurrent TASEPs running on multiple lattices;
(v) How our results translate to TASEPs with open boundaries that exchange particles
with the reservoir. Since real particle motion (including in systems that inspired
the standard TASEP model, e.g., protein synthesis or movement of molecular motors)
is often catalyzed, regulated, actuated, or otherwise mediated, the token-driven
TASEP dynamics analyzed in this paper should allow for a better understanding
of real systems and enable a closer match between TASEP theory and experimental
observations.'
acknowledgement: B.K. thanks Stefano Elefante, Simon Rella, and Michal Hledík for
their help with the usage of the cluster. B.K. additionally thanks Călin Guet and
his group for help and advice. We thank M. Hennessey-Wesen for constructive comments
on the manuscript. We thank Ankita Gupta (Indian Institute of Technology) for spotting
a typographical error in Eq. (49) in the preprint version of this paper.
article_number: '2112.13558'
article_processing_charge: No
arxiv: 1
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process.
arXiv. doi:10.48550/arXiv.2112.13558
apa: Kavcic, B., & Tkačik, G. (n.d.). Token-driven totally asymmetric simple
exclusion process. arXiv. https://doi.org/10.48550/arXiv.2112.13558
chicago: Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple
Exclusion Process.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2112.13558.
ieee: B. Kavcic and G. Tkačik, “Token-driven totally asymmetric simple exclusion
process,” arXiv. .
ista: Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process.
arXiv, 2112.13558.
mla: Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple Exclusion
Process.” ArXiv, 2112.13558, doi:10.48550/arXiv.2112.13558.
short: B. Kavcic, G. Tkačik, ArXiv (n.d.).
date_created: 2021-12-28T06:52:09Z
date_published: 2021-12-27T00:00:00Z
date_updated: 2023-05-03T10:54:05Z
day: '27'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.48550/arXiv.2112.13558
external_id:
arxiv:
- '2112.13558'
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2112.13558
month: '12'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Token-driven totally asymmetric simple exclusion process
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: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '9439'
abstract:
- lang: eng
text: The ability to adapt to changes in stimulus statistics is a hallmark of sensory
systems. Here, we developed a theoretical framework that can account for the dynamics
of adaptation from an information processing perspective. We use this framework
to optimize and analyze adaptive sensory codes, and we show that codes optimized
for stationary environments can suffer from prolonged periods of poor performance
when the environment changes. To mitigate the adversarial effects of these environmental
changes, sensory systems must navigate tradeoffs between the ability to accurately
encode incoming stimuli and the ability to rapidly detect and adapt to changes
in the distribution of these stimuli. We derive families of codes that balance
these objectives, and we demonstrate their close match to experimentally observed
neural dynamics during mean and variance adaptation. Our results provide a unifying
perspective on adaptation across a range of sensory systems, environments, and
sensory tasks.
acknowledgement: We thank D. Kastner and T. Münch for generously providing figures
from their work. We also thank V. Jayaraman, M. Noorman, T. Ma, and K. Krishnamurthy
for useful discussions and feedback on the manuscript. W.F.M. was funded by the
European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie
Grant Agreement No. 754411. A.M.H. was supported by the Howard Hughes Medical Institute.
article_processing_charge: No
article_type: original
author:
- first_name: Wiktor F
full_name: Mlynarski, Wiktor F
id: 358A453A-F248-11E8-B48F-1D18A9856A87
last_name: Mlynarski
- first_name: Ann M.
full_name: Hermundstad, Ann M.
last_name: Hermundstad
citation:
ama: Mlynarski WF, Hermundstad AM. Efficient and adaptive sensory codes. Nature
Neuroscience. 2021;24:998-1009. doi:10.1038/s41593-021-00846-0
apa: Mlynarski, W. F., & Hermundstad, A. M. (2021). Efficient and adaptive sensory
codes. Nature Neuroscience. Springer Nature. https://doi.org/10.1038/s41593-021-00846-0
chicago: Mlynarski, Wiktor F, and Ann M. Hermundstad. “Efficient and Adaptive Sensory
Codes.” Nature Neuroscience. Springer Nature, 2021. https://doi.org/10.1038/s41593-021-00846-0.
ieee: W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,”
Nature Neuroscience, vol. 24. Springer Nature, pp. 998–1009, 2021.
ista: Mlynarski WF, Hermundstad AM. 2021. Efficient and adaptive sensory codes.
Nature Neuroscience. 24, 998–1009.
mla: Mlynarski, Wiktor F., and Ann M. Hermundstad. “Efficient and Adaptive Sensory
Codes.” Nature Neuroscience, vol. 24, Springer Nature, 2021, pp. 998–1009,
doi:10.1038/s41593-021-00846-0.
short: W.F. Mlynarski, A.M. Hermundstad, Nature Neuroscience 24 (2021) 998–1009.
date_created: 2021-05-30T22:01:24Z
date_published: 2021-05-20T00:00:00Z
date_updated: 2023-08-08T13:51:14Z
day: '20'
department:
- _id: GaTk
doi: 10.1038/s41593-021-00846-0
ec_funded: 1
external_id:
isi:
- '000652577300003'
intvolume: ' 24'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.1101/669200 '
month: '05'
oa: 1
oa_version: Preprint
page: 998-1009
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Nature Neuroscience
publication_identifier:
eissn:
- 1546-1726
issn:
- 1097-6256
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Efficient and adaptive sensory codes
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 24
year: '2021'
...
---
_id: '9822'
abstract:
- lang: eng
text: Attachment of adhesive molecules on cell culture surfaces to restrict cell
adhesion to defined areas and shapes has been vital for the progress of in vitro
research. In currently existing patterning methods, a combination of pattern properties
such as stability, precision, specificity, high-throughput outcome, and spatiotemporal
control is highly desirable but challenging to achieve. Here, we introduce a versatile
and high-throughput covalent photoimmobilization technique, comprising a light-dose-dependent
patterning step and a subsequent functionalization of the pattern via click chemistry.
This two-step process is feasible on arbitrary surfaces and allows for generation
of sustainable patterns and gradients. The method is validated in different biological
systems by patterning adhesive ligands on cell-repellent surfaces, thereby constraining
the growth and migration of cells to the designated areas. We then implement a
sequential photopatterning approach by adding a second switchable patterning step,
allowing for spatiotemporal control over two distinct surface patterns. As a proof
of concept, we reconstruct the dynamics of the tip/stalk cell switch during angiogenesis.
Our results show that the spatiotemporal control provided by our “sequential photopatterning”
system is essential for mimicking dynamic biological processes and that our innovative
approach has great potential for further applications in cell science.
acknowledgement: We would like to thank Charlott Leu for the production of our chromium
wafers, Louise Ritter for her contribution of the IF stainings in Figure 4, Shokoufeh
Teymouri for her help with the Bioinert coated slides, and finally Prof. Dr. Joachim
Rädler for his valuable scientific guidance.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Themistoklis
full_name: Zisis, Themistoklis
last_name: Zisis
- first_name: Jan
full_name: Schwarz, Jan
id: 346C1EC6-F248-11E8-B48F-1D18A9856A87
last_name: Schwarz
- first_name: Miriam
full_name: Balles, Miriam
last_name: Balles
- first_name: Maibritt
full_name: Kretschmer, Maibritt
last_name: Kretschmer
- first_name: Maria
full_name: Nemethova, Maria
id: 34E27F1C-F248-11E8-B48F-1D18A9856A87
last_name: Nemethova
- 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: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Janina
full_name: Lange, Janina
last_name: Lange
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-4561-241X
- first_name: Stefan
full_name: Zahler, Stefan
last_name: Zahler
citation:
ama: Zisis T, Schwarz J, Balles M, et al. Sequential and switchable patterning for
studying cellular processes under spatiotemporal control. ACS Applied Materials
and Interfaces. 2021;13(30):35545–35560. doi:10.1021/acsami.1c09850
apa: Zisis, T., Schwarz, J., Balles, M., Kretschmer, M., Nemethova, M., Chait, R.
P., … Zahler, S. (2021). Sequential and switchable patterning for studying cellular
processes under spatiotemporal control. ACS Applied Materials and Interfaces.
American Chemical Society. https://doi.org/10.1021/acsami.1c09850
chicago: Zisis, Themistoklis, Jan Schwarz, Miriam Balles, Maibritt Kretschmer, Maria
Nemethova, Remy P Chait, Robert Hauschild, et al. “Sequential and Switchable Patterning
for Studying Cellular Processes under Spatiotemporal Control.” ACS Applied
Materials and Interfaces. American Chemical Society, 2021. https://doi.org/10.1021/acsami.1c09850.
ieee: T. Zisis et al., “Sequential and switchable patterning for studying
cellular processes under spatiotemporal control,” ACS Applied Materials and
Interfaces, vol. 13, no. 30. American Chemical Society, pp. 35545–35560, 2021.
ista: Zisis T, Schwarz J, Balles M, Kretschmer M, Nemethova M, Chait RP, Hauschild
R, Lange J, Guet CC, Sixt MK, Zahler S. 2021. Sequential and switchable patterning
for studying cellular processes under spatiotemporal control. ACS Applied Materials
and Interfaces. 13(30), 35545–35560.
mla: Zisis, Themistoklis, et al. “Sequential and Switchable Patterning for Studying
Cellular Processes under Spatiotemporal Control.” ACS Applied Materials and
Interfaces, vol. 13, no. 30, American Chemical Society, 2021, pp. 35545–35560,
doi:10.1021/acsami.1c09850.
short: T. Zisis, J. Schwarz, M. Balles, M. Kretschmer, M. Nemethova, R.P. Chait,
R. Hauschild, J. Lange, C.C. Guet, M.K. Sixt, S. Zahler, ACS Applied Materials
and Interfaces 13 (2021) 35545–35560.
date_created: 2021-08-08T22:01:28Z
date_published: 2021-08-04T00:00:00Z
date_updated: 2023-08-10T14:22:48Z
day: '04'
ddc:
- '620'
- '570'
department:
- _id: MiSi
- _id: GaTk
- _id: Bio
- _id: CaGu
doi: 10.1021/acsami.1c09850
ec_funded: 1
external_id:
isi:
- '000683741400026'
pmid:
- '34283577'
file:
- access_level: open_access
checksum: b043a91d9f9200e467b970b692687ed3
content_type: application/pdf
creator: asandaue
date_created: 2021-08-09T09:44:03Z
date_updated: 2021-08-09T09:44:03Z
file_id: '9833'
file_name: 2021_ACSAppliedMaterialsAndInterfaces_Zisis.pdf
file_size: 7123293
relation: main_file
success: 1
file_date_updated: 2021-08-09T09:44:03Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
issue: '30'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 35545–35560
pmid: 1
project:
- _id: 25FE9508-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '724373'
name: Cellular navigation along spatial gradients
publication: ACS Applied Materials and Interfaces
publication_identifier:
eissn:
- '19448252'
issn:
- '19448244'
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sequential and switchable patterning for studying cellular processes under
spatiotemporal control
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13
year: '2021'
...
---
_id: '9828'
abstract:
- lang: eng
text: Amplitude demodulation is a classical operation used in signal processing.
For a long time, its effective applications in practice have been limited to narrowband
signals. In this work, we generalize amplitude demodulation to wideband signals.
We pose demodulation as a recovery problem of an oversampled corrupted signal
and introduce special iterative schemes belonging to the family of alternating
projection algorithms to solve it. Sensibly chosen structural assumptions on the
demodulation outputs allow us to reveal the high inferential accuracy of the method
over a rich set of relevant signals. This new approach surpasses current state-of-the-art
demodulation techniques apt to wideband signals in computational efficiency by
up to many orders of magnitude with no sacrifice in quality. Such performance
opens the door for applications of the amplitude demodulation procedure in new
contexts. In particular, the new method makes online and large-scale offline data
processing feasible, including the calculation of modulator-carrier pairs in higher
dimensions and poor sampling conditions, independent of the signal bandwidth.
We illustrate the utility and specifics of applications of the new method in practice
by using natural speech and synthetic signals.
acknowledgement: The author thanks his colleagues K. Huszár and G. Tkačik for valuable
discussions and comments on the manuscript.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Mantas
full_name: Gabrielaitis, Mantas
id: 4D5B0CBC-F248-11E8-B48F-1D18A9856A87
last_name: Gabrielaitis
orcid: 0000-0002-7758-2016
citation:
ama: Gabrielaitis M. Fast and accurate amplitude demodulation of wideband signals.
IEEE Transactions on Signal Processing. 2021;69:4039-4054. doi:10.1109/TSP.2021.3087899
apa: Gabrielaitis, M. (2021). Fast and accurate amplitude demodulation of wideband
signals. IEEE Transactions on Signal Processing. Institute of Electrical
and Electronics Engineers. https://doi.org/10.1109/TSP.2021.3087899
chicago: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband
Signals.” IEEE Transactions on Signal Processing. Institute of Electrical
and Electronics Engineers, 2021. https://doi.org/10.1109/TSP.2021.3087899.
ieee: M. Gabrielaitis, “Fast and accurate amplitude demodulation of wideband signals,”
IEEE Transactions on Signal Processing, vol. 69. Institute of Electrical
and Electronics Engineers, pp. 4039–4054, 2021.
ista: Gabrielaitis M. 2021. Fast and accurate amplitude demodulation of wideband
signals. IEEE Transactions on Signal Processing. 69, 4039–4054.
mla: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband
Signals.” IEEE Transactions on Signal Processing, vol. 69, Institute of
Electrical and Electronics Engineers, 2021, pp. 4039–54, doi:10.1109/TSP.2021.3087899.
short: M. Gabrielaitis, IEEE Transactions on Signal Processing 69 (2021) 4039–4054.
date_created: 2021-08-08T22:01:31Z
date_published: 2021-06-09T00:00:00Z
date_updated: 2023-08-10T14:19:33Z
day: '09'
department:
- _id: GaTk
doi: 10.1109/TSP.2021.3087899
external_id:
arxiv:
- '2102.04832'
isi:
- '000682123900002'
intvolume: ' 69'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2102.04832
month: '06'
oa: 1
oa_version: Preprint
page: 4039 - 4054
publication: IEEE Transactions on Signal Processing
publication_identifier:
eissn:
- 1941-0476
issn:
- 1053-587X
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Fast and accurate amplitude demodulation of wideband signals
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 69
year: '2021'
...
---
_id: '10912'
abstract:
- lang: eng
text: Brain dynamics display collective phenomena as diverse as neuronal oscillations
and avalanches. Oscillations are rhythmic, with fluctuations occurring at a characteristic
scale, whereas avalanches are scale-free cascades of neural activity. Here we
show that such antithetic features can coexist in a very generic class of adaptive
neural networks. In the most simple yet fully microscopic model from this class
we make direct contact with human brain resting-state activity recordings via
tractable inference of the model's two essential parameters. The inferred model
quantitatively captures the dynamics over a broad range of scales, from single
sensor fluctuations, collective behaviors of nearly-synchronous extreme events
on multiple sensors, to neuronal avalanches unfolding over multiple sensors across
multiple time-bins. Importantly, the inferred parameters correlate with model-independent
signatures of "closeness to criticality", suggesting that the coexistence of scale-specific
(neural oscillations) and scale-free (neuronal avalanches) dynamics in brain activity
occurs close to a non-equilibrium critical point at the onset of self-sustained
oscillations.
acknowledgement: "FL acknowledges support from the European Union’s Horizon 2020 research
and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
GT\r\nacknowledges the support of the Austrian Science Fund (FWF) under Stand-Alone
Grant\r\nNo. P34015."
article_processing_charge: No
arxiv: 1
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Selver
full_name: Pepic, Selver
id: F93245C4-C3CA-11E9-B4F0-C6F4E5697425
last_name: Pepic
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Daniele
full_name: De Martino, Daniele
last_name: De Martino
citation:
ama: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. doi:10.48550/ARXIV.2108.06686
apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., & De Martino, D. (n.d.).
Quantifying the coexistence of neuronal oscillations and avalanches. arXiv. https://doi.org/10.48550/ARXIV.2108.06686
chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
De Martino. “Quantifying the Coexistence of Neuronal Oscillations and Avalanches.”
arXiv, n.d. https://doi.org/10.48550/ARXIV.2108.06686.
ieee: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Quantifying
the coexistence of neuronal oscillations and avalanches.” arXiv.
ista: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. 10.48550/ARXIV.2108.06686.
mla: Lombardi, Fabrizio, et al. Quantifying the Coexistence of Neuronal Oscillations
and Avalanches. arXiv, doi:10.48550/ARXIV.2108.06686.
short: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, (n.d.).
date_created: 2022-03-21T11:41:28Z
date_published: 2021-08-17T00:00:00Z
date_updated: 2022-03-22T07:53:18Z
day: '17'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.48550/ARXIV.2108.06686
ec_funded: 1
external_id:
arxiv:
- '2108.06686'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2108.06686
month: '08'
oa: 1
oa_version: Preprint
page: '37'
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication_status: submitted
publisher: arXiv
status: public
title: Quantifying the coexistence of neuronal oscillations and avalanches
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '8250'
abstract:
- lang: eng
text: 'Antibiotics that interfere with translation, when combined, interact in diverse
and difficult-to-predict ways. Here, we explain these interactions by “translation
bottlenecks”: points in the translation cycle where antibiotics block ribosomal
progression. To elucidate the underlying mechanisms of drug interactions between
translation inhibitors, we generate translation bottlenecks genetically using
inducible control of translation factors that regulate well-defined translation
cycle steps. These perturbations accurately mimic antibiotic action and drug interactions,
supporting that the interplay of different translation bottlenecks causes these
interactions. We further show that growth laws, combined with drug uptake and
binding kinetics, enable the direct prediction of a large fraction of observed
interactions, yet fail to predict suppression. However, varying two translation
bottlenecks simultaneously supports that dense traffic of ribosomes and competition
for translation factors account for the previously unexplained suppression. These
results highlight the importance of “continuous epistasis” in bacterial physiology.'
acknowledgement: "We thank M. Hennessey-Wesen, I. Tomanek, K. Jain, A. Staron, K.
Tomasek, M. Scott,\r\nK.C. Huang, and Z. Gitai for reading the manuscript and constructive
comments. B.K. is\r\nindebted to C. Guet for additional guidance and generous support,
which rendered this\r\nwork possible. B.K. thanks all members of Guet group for
many helpful discussions and\r\nsharing of resources. B.K. additionally acknowledges
the tremendous support from A.\r\nAngermayr and K. Mitosch with experimental work.
We further thank E. Brown for\r\nhelpful comments regarding lamotrigine, and A.
Buskirk for valuable suggestions\r\nregarding the ribosome footprint size. This
work was supported in part by Austrian\r\nScience Fund (FWF) standalone grants P
27201-B22 (to T.B.) and P 28844 (to G.T.),\r\nHFSP program Grant RGP0042/2013 (to
T.B.), German Research Foundation (DFG)\r\nstandalone grant BO 3502/2-1 (to T.B.),
and German Research Foundation (DFG)\r\nCollaborative Research Centre (SFB) 1310
(to T.B.). Open access funding provided by\r\nProjekt DEAL."
article_number: '4013'
article_processing_charge: No
article_type: original
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Kavcic B, Tkačik G, Bollenbach MT. Mechanisms of drug interactions between
translation-inhibiting antibiotics. Nature Communications. 2020;11. doi:10.1038/s41467-020-17734-z
apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2020). Mechanisms of drug
interactions between translation-inhibiting antibiotics. Nature Communications.
Springer Nature. https://doi.org/10.1038/s41467-020-17734-z
chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Mechanisms of
Drug Interactions between Translation-Inhibiting Antibiotics.” Nature Communications.
Springer Nature, 2020. https://doi.org/10.1038/s41467-020-17734-z.
ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions
between translation-inhibiting antibiotics,” Nature Communications, vol.
11. Springer Nature, 2020.
ista: Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between
translation-inhibiting antibiotics. Nature Communications. 11, 4013.
mla: Kavcic, Bor, et al. “Mechanisms of Drug Interactions between Translation-Inhibiting
Antibiotics.” Nature Communications, vol. 11, 4013, Springer Nature, 2020,
doi:10.1038/s41467-020-17734-z.
short: B. Kavcic, G. Tkačik, M.T. Bollenbach, Nature Communications 11 (2020).
date_created: 2020-08-12T09:13:50Z
date_published: 2020-08-11T00:00:00Z
date_updated: 2024-03-25T23:30:05Z
day: '11'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1038/s41467-020-17734-z
external_id:
isi:
- '000562769300008'
file:
- access_level: open_access
checksum: 986bebb308850a55850028d3d2b5b664
content_type: application/pdf
creator: dernst
date_created: 2020-08-17T07:36:57Z
date_updated: 2020-08-17T07:36:57Z
file_id: '8275'
file_name: 2020_NatureComm_Kavcic.pdf
file_size: 1965672
relation: main_file
success: 1
file_date_updated: 2020-08-17T07:36:57Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
issn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '8657'
relation: dissertation_contains
status: public
status: public
title: Mechanisms of drug interactions between translation-inhibiting antibiotics
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
year: '2020'
...
---
_id: '8657'
abstract:
- lang: eng
text: "Synthesis of proteins – translation – is a fundamental process of life. Quantitative
studies anchor translation into the context of bacterial physiology and reveal
several mathematical relationships, called “growth laws,” which capture physiological
feedbacks between protein synthesis and cell growth. Growth laws describe the
dependency of the ribosome abundance as a function of growth rate, which can change
depending on the growth conditions. Perturbations of translation reveal that bacteria
employ a compensatory strategy in which the reduced translation capability results
in increased expression of the translation machinery.\r\nPerturbations of translation
are achieved in various ways; clinically interesting is the application of translation-targeting
antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology
are often poorly understood. Bacterial responses to two or more simultaneously
applied antibiotics are even more puzzling. The combined antibiotic effect determines
the type of drug interaction, which ranges from synergy (the effect is stronger
than expected) to antagonism (the effect is weaker) and suppression (one of the
drugs loses its potency).\r\nIn the first part of this work, we systematically
measure the pairwise interaction network for translation inhibitors that interfere
with different steps in translation. We find that the interactions are surprisingly
diverse and tend to be more antagonistic. To explore the underlying mechanisms,
we begin with a minimal biophysical model of combined antibiotic action. We base
this model on the kinetics of antibiotic uptake and binding together with the
physiological response described by the growth laws. The biophysical model explains
some drug interactions, but not all; it specifically fails to predict suppression.\r\nIn
the second part of this work, we hypothesize that elusive suppressive drug interactions
result from the interplay between ribosomes halted in different stages of translation.
To elucidate this putative mechanism of drug interactions between translation
inhibitors, we generate translation bottlenecks genetically using in- ducible
control of translation factors that regulate well-defined translation cycle steps.
These perturbations accurately mimic antibiotic action and drug interactions,
supporting that the interplay of different translation bottlenecks partially causes
these interactions.\r\nWe extend this approach by varying two translation bottlenecks
simultaneously. This approach reveals the suppression of translocation inhibition
by inhibited translation. We rationalize this effect by modeling dense traffic
of ribosomes that move on transcripts in a translation factor-mediated manner.
This model predicts a dissolution of traffic jams caused by inhibited translocation
when the density of ribosome traffic is reduced by lowered initiation. We base
this model on the growth laws and quantitative relationships between different
translation and growth parameters.\r\nIn the final part of this work, we describe
a set of tools aimed at quantification of physiological and translation parameters.
We further develop a simple model that directly connects the abundance of a translation
factor with the growth rate, which allows us to extract physiological parameters
describing initiation. We demonstrate the development of tools for measuring translation
rate.\r\nThis thesis showcases how a combination of high-throughput growth rate
mea- surements, genetics, and modeling can reveal mechanisms of drug interactions.
Furthermore, by a gradual transition from combinations of antibiotics to precise
genetic interventions, we demonstrated the equivalency between genetic and chemi-
cal perturbations of translation. These findings tile the path for quantitative
studies of antibiotic combinations and illustrate future approaches towards the
quantitative description of translation."
acknowledged_ssus:
- _id: LifeSc
- _id: M-Shop
acknowledgement: I thank Life Science Facilities for their continuous support with
providing top-notch laboratory materials, keeping the devices humming, and coordinating
the repairs and building of custom-designed laboratory equipment with the MIBA Machine
shop.
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
citation:
ama: 'Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics
and physiology. 2020. doi:10.15479/AT:ISTA:8657'
apa: 'Kavcic, B. (2020). Perturbations of protein synthesis: from antibiotics
to genetics and physiology. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8657'
chicago: 'Kavcic, Bor. “Perturbations of Protein Synthesis: From Antibiotics to
Genetics and Physiology.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8657.'
ieee: 'B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics
and physiology,” Institute of Science and Technology Austria, 2020.'
ista: 'Kavcic B. 2020. Perturbations of protein synthesis: from antibiotics to genetics
and physiology. Institute of Science and Technology Austria.'
mla: 'Kavcic, Bor. Perturbations of Protein Synthesis: From Antibiotics to Genetics
and Physiology. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8657.'
short: 'B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics
and Physiology, Institute of Science and Technology Austria, 2020.'
date_created: 2020-10-13T16:46:14Z
date_published: 2020-10-14T00:00:00Z
date_updated: 2023-09-07T13:20:48Z
day: '14'
ddc:
- '571'
- '530'
- '570'
degree_awarded: PhD
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:8657
file:
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checksum: d708ecd62b6fcc3bc1feb483b8dbe9eb
content_type: application/pdf
creator: bkavcic
date_created: 2020-10-15T06:41:20Z
date_updated: 2021-10-07T22:30:03Z
embargo: 2021-10-06
file_id: '8663'
file_name: kavcicB_thesis202009.pdf
file_size: 52636162
relation: main_file
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checksum: bb35f2352a04db19164da609f00501f3
content_type: application/zip
creator: bkavcic
date_created: 2020-10-15T06:41:53Z
date_updated: 2021-10-07T22:30:03Z
embargo_to: open_access
file_id: '8664'
file_name: 2020b.zip
file_size: 321681247
relation: source_file
file_date_updated: 2021-10-07T22:30:03Z
has_accepted_license: '1'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: '271'
publication_identifier:
isbn:
- 978-3-99078-011-4
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7673'
relation: part_of_dissertation
status: public
- id: '8250'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
title: 'Perturbations of protein synthesis: from antibiotics to genetics and physiology'
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2020'
...
---
_id: '8698'
abstract:
- lang: eng
text: The brain represents and reasons probabilistically about complex stimuli and
motor actions using a noisy, spike-based neural code. A key building block for
such neural computations, as well as the basis for supervised and unsupervised
learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional
neural activity patterns. Despite progress in statistical modeling of neural responses
and deep learning, current approaches either do not scale to large neural populations
or cannot be implemented using biologically realistic mechanisms. Inspired by
the sparse and random connectivity of real neuronal circuits, we present a model
for neural codes that accurately estimates the likelihood of individual spiking
patterns and has a straightforward, scalable, efficient, learnable, and realistic
neural implementation. This model’s performance on simultaneously recorded spiking
activity of >100 neurons in the monkey visual and prefrontal cortices is comparable
with or better than that of state-of-the-art models. Importantly, the model can
be learned using a small number of samples and using a local learning rule that
utilizes noise intrinsic to neural circuits. Slower, structural changes in random
connectivity, consistent with rewiring and pruning processes, further improve
the efficiency and sparseness of the resulting neural representations. Our results
merge insights from neuroanatomy, machine learning, and theoretical neuroscience
to suggest random sparse connectivity as a key design principle for neuronal computation.
acknowledgement: We thank Udi Karpas, Roy Harpaz, Tal Tamir, Adam Haber, and Amir
Bar for discussions and suggestions; and especially Oren Forkosh and Walter Senn
for invaluable discussions of the learning rule. This work was supported by European
Research Council Grant 311238 (to E.S.) and Israel Science Foundation Grant 1629/12
(to E.S.); as well as research support from Martin Kushner Schnur and Mr. and Mrs.
Lawrence Feis (E.S.); National Institute of Mental Health Grant R01MH109180 (to
R.K.); a Pew Scholarship in Biomedical Sciences (to R.K.); Simons Collaboration
on the Global Brain Grant 542997 (to R.K. and E.S.); and a CRCNS (Collaborative
Research in Computational Neuroscience) grant (to R.K. and E.S.).
article_processing_charge: No
article_type: original
author:
- first_name: Ori
full_name: Maoz, Ori
last_name: Maoz
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Mohamad Saleh
full_name: Esteki, Mohamad Saleh
last_name: Esteki
- first_name: Roozbeh
full_name: Kiani, Roozbeh
last_name: Kiani
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: Maoz O, Tkačik G, Esteki MS, Kiani R, Schneidman E. Learning probabilistic
neural representations with randomly connected circuits. Proceedings of the
National Academy of Sciences of the United States of America. 2020;117(40):25066-25073.
doi:10.1073/pnas.1912804117
apa: Maoz, O., Tkačik, G., Esteki, M. S., Kiani, R., & Schneidman, E. (2020).
Learning probabilistic neural representations with randomly connected circuits.
Proceedings of the National Academy of Sciences of the United States of America.
National Academy of Sciences. https://doi.org/10.1073/pnas.1912804117
chicago: Maoz, Ori, Gašper Tkačik, Mohamad Saleh Esteki, Roozbeh Kiani, and Elad
Schneidman. “Learning Probabilistic Neural Representations with Randomly Connected
Circuits.” Proceedings of the National Academy of Sciences of the United States
of America. National Academy of Sciences, 2020. https://doi.org/10.1073/pnas.1912804117.
ieee: O. Maoz, G. Tkačik, M. S. Esteki, R. Kiani, and E. Schneidman, “Learning probabilistic
neural representations with randomly connected circuits,” Proceedings of the
National Academy of Sciences of the United States of America, vol. 117, no.
40. National Academy of Sciences, pp. 25066–25073, 2020.
ista: Maoz O, Tkačik G, Esteki MS, Kiani R, Schneidman E. 2020. Learning probabilistic
neural representations with randomly connected circuits. Proceedings of the National
Academy of Sciences of the United States of America. 117(40), 25066–25073.
mla: Maoz, Ori, et al. “Learning Probabilistic Neural Representations with Randomly
Connected Circuits.” Proceedings of the National Academy of Sciences of the
United States of America, vol. 117, no. 40, National Academy of Sciences,
2020, pp. 25066–73, doi:10.1073/pnas.1912804117.
short: O. Maoz, G. Tkačik, M.S. Esteki, R. Kiani, E. Schneidman, Proceedings of
the National Academy of Sciences of the United States of America 117 (2020) 25066–25073.
date_created: 2020-10-25T23:01:16Z
date_published: 2020-10-06T00:00:00Z
date_updated: 2023-08-22T12:11:23Z
day: '06'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1073/pnas.1912804117
external_id:
isi:
- '000579045200012'
pmid:
- '32948691'
file:
- access_level: open_access
checksum: c6a24fdecf3f28faf447078e7a274a88
content_type: application/pdf
creator: cziletti
date_created: 2020-10-27T14:57:50Z
date_updated: 2020-10-27T14:57:50Z
file_id: '8713'
file_name: 2020_PNAS_Maoz.pdf
file_size: 1755359
relation: main_file
success: 1
file_date_updated: 2020-10-27T14:57:50Z
has_accepted_license: '1'
intvolume: ' 117'
isi: 1
issue: '40'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 25066-25073
pmid: 1
publication: Proceedings of the National Academy of Sciences of the United States
of America
publication_identifier:
eissn:
- '10916490'
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning probabilistic neural representations with randomly connected circuits
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 117
year: '2020'
...
---
_id: '8930'
abstract:
- lang: eng
text: Phenomenological relations such as Ohm’s or Fourier’s law have a venerable
history in physics but are still scarce in biology. This situation restrains predictive
theory. Here, we build on bacterial “growth laws,” which capture physiological
feedback between translation and cell growth, to construct a minimal biophysical
model for the combined action of ribosome-targeting antibiotics. Our model predicts
drug interactions like antagonism or synergy solely from responses to individual
drugs. We provide analytical results for limiting cases, which agree well with
numerical results. We systematically refine the model by including direct physical
interactions of different antibiotics on the ribosome. In a limiting case, our
model provides a mechanistic underpinning for recent predictions of higher-order
interactions that were derived using entropy maximization. We further refine the
model to include the effects of antibiotics that mimic starvation and the presence
of resistance genes. We describe the impact of a starvation-mimicking antibiotic
on drug interactions analytically and verify it experimentally. Our extended model
suggests a change in the type of drug interaction that depends on the strength
of resistance, which challenges established rescaling paradigms. We experimentally
show that the presence of unregulated resistance genes can lead to altered drug
interaction, which agrees with the prediction of the model. While minimal, the
model is readily adaptable and opens the door to predicting interactions of second
and higher-order in a broad range of biological systems.
article_processing_charge: No
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
citation:
ama: Kavcic B. Analysis scripts and research data for the paper “Minimal biophysical
model of combined antibiotic action.” 2020. doi:10.15479/AT:ISTA:8930
apa: Kavcic, B. (2020). Analysis scripts and research data for the paper “Minimal
biophysical model of combined antibiotic action.” Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:8930
chicago: Kavcic, Bor. “Analysis Scripts and Research Data for the Paper ‘Minimal
Biophysical Model of Combined Antibiotic Action.’” Institute of Science and Technology
Austria, 2020. https://doi.org/10.15479/AT:ISTA:8930.
ieee: B. Kavcic, “Analysis scripts and research data for the paper ‘Minimal biophysical
model of combined antibiotic action.’” Institute of Science and Technology Austria,
2020.
ista: Kavcic B. 2020. Analysis scripts and research data for the paper ‘Minimal
biophysical model of combined antibiotic action’, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:8930.
mla: Kavcic, Bor. Analysis Scripts and Research Data for the Paper “Minimal Biophysical
Model of Combined Antibiotic Action.” Institute of Science and Technology
Austria, 2020, doi:10.15479/AT:ISTA:8930.
short: B. Kavcic, (2020).
contributor:
- contributor_type: supervisor
first_name: Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- contributor_type: supervisor
first_name: Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
date_created: 2020-12-09T15:04:02Z
date_published: 2020-12-10T00:00:00Z
date_updated: 2024-02-21T12:41:42Z
day: '10'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:8930
file:
- access_level: open_access
checksum: 60a818edeffaa7da1ebf5f8fbea9ba18
content_type: application/zip
creator: bkavcic
date_created: 2020-12-09T15:00:19Z
date_updated: 2020-12-09T15:00:19Z
file_id: '8932'
file_name: PLoSCompBiol2020_datarep.zip
file_size: 315494370
relation: main_file
success: 1
file_date_updated: 2020-12-09T15:00:19Z
has_accepted_license: '1'
keyword:
- Escherichia coli
- antibiotic combinations
- translation
- growth laws
- drug interactions
- bacterial physiology
- translation inhibitors
month: '12'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '8997'
relation: used_in_publication
status: public
status: public
title: Analysis scripts and research data for the paper "Minimal biophysical model
of combined antibiotic action"
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: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '8955'
abstract:
- lang: eng
text: Skeletal muscle activity is continuously modulated across physiologic states
to provide coordination, flexibility and responsiveness to body tasks and external
inputs. Despite the central role the muscular system plays in facilitating vital
body functions, the network of brain-muscle interactions required to control hundreds
of muscles and synchronize their activation in relation to distinct physiologic
states has not been investigated. Recent approaches have focused on general associations
between individual brain rhythms and muscle activation during movement tasks.
However, the specific forms of coupling, the functional network of cortico-muscular
coordination, and how network structure and dynamics are modulated by autonomic
regulation across physiologic states remains unknown. To identify and quantify
the cortico-muscular interaction network and uncover basic features of neuro-autonomic
control of muscle function, we investigate the coupling between synchronous bursts
in cortical rhythms and peripheral muscle activation during sleep and wake. Utilizing
the concept of time delay stability and a novel network physiology approach, we
find that the brain-muscle network exhibits complex dynamic patterns of communication
involving multiple brain rhythms across cortical locations and different electromyographic
frequency bands. Moreover, our results show that during each physiologic state
the cortico-muscular network is characterized by a specific profile of network
links strength, where particular brain rhythms play role of main mediators of
interaction and control. Further, we discover a hierarchical reorganization in
network structure across physiologic states, with high connectivity and network
link strength during wake, intermediate during REM and light sleep, and low during
deep sleep, a sleep-stage stratification that demonstrates a unique association
between physiologic states and cortico-muscular network structure. The reported
empirical observations are consistent across individual subjects, indicating universal
behavior in network structure and dynamics, and high sensitivity of cortico-muscular
control to changes in autonomic regulation, even at low levels of physical activity
and muscle tone during sleep. Our findings demonstrate previously unrecognized
basic principles of brain-muscle network communication and control, and provide
new perspectives on the regulatory mechanisms of brain dynamics and locomotor
activation, with potential clinical implications for neurodegenerative, movement
and sleep disorders, and for developing efficient treatment strategies.
acknowledgement: We acknowledge support from the W. M. Keck Foundation, National Institutes
of Health (NIH Grant 1R01-HL098437), the US-Israel Binational Science Foundation
(BSF Grant 2012219), and the Office of Naval Research (ONR Grant 000141010078).
FL acknowledges support also from the European Union's Horizon 2020 research and
innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
article_number: '558070'
article_processing_charge: No
article_type: original
author:
- first_name: Rossella
full_name: Rizzo, Rossella
last_name: Rizzo
- first_name: Xiyun
full_name: Zhang, Xiyun
last_name: Zhang
- first_name: Jilin W.J.L.
full_name: Wang, Jilin W.J.L.
last_name: Wang
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Plamen Ch
full_name: Ivanov, Plamen Ch
last_name: Ivanov
citation:
ama: Rizzo R, Zhang X, Wang JWJL, Lombardi F, Ivanov PC. Network physiology of cortico–muscular
interactions. Frontiers in Physiology. 2020;11. doi:10.3389/fphys.2020.558070
apa: Rizzo, R., Zhang, X., Wang, J. W. J. L., Lombardi, F., & Ivanov, P. C.
(2020). Network physiology of cortico–muscular interactions. Frontiers in Physiology.
Frontiers. https://doi.org/10.3389/fphys.2020.558070
chicago: Rizzo, Rossella, Xiyun Zhang, Jilin W.J.L. Wang, Fabrizio Lombardi, and
Plamen Ch Ivanov. “Network Physiology of Cortico–Muscular Interactions.” Frontiers
in Physiology. Frontiers, 2020. https://doi.org/10.3389/fphys.2020.558070.
ieee: R. Rizzo, X. Zhang, J. W. J. L. Wang, F. Lombardi, and P. C. Ivanov, “Network
physiology of cortico–muscular interactions,” Frontiers in Physiology,
vol. 11. Frontiers, 2020.
ista: Rizzo R, Zhang X, Wang JWJL, Lombardi F, Ivanov PC. 2020. Network physiology
of cortico–muscular interactions. Frontiers in Physiology. 11, 558070.
mla: Rizzo, Rossella, et al. “Network Physiology of Cortico–Muscular Interactions.”
Frontiers in Physiology, vol. 11, 558070, Frontiers, 2020, doi:10.3389/fphys.2020.558070.
short: R. Rizzo, X. Zhang, J.W.J.L. Wang, F. Lombardi, P.C. Ivanov, Frontiers in
Physiology 11 (2020).
date_created: 2020-12-20T23:01:18Z
date_published: 2020-11-26T00:00:00Z
date_updated: 2023-08-24T11:00:45Z
day: '26'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.3389/fphys.2020.558070
ec_funded: 1
external_id:
isi:
- '000596849400001'
pmid:
- '33324233'
file:
- access_level: open_access
checksum: ef9515b28c5619b7126c0f347958bcb3
content_type: application/pdf
creator: dernst
date_created: 2020-12-21T10:37:50Z
date_updated: 2020-12-21T10:37:50Z
file_id: '8961'
file_name: 2020_Frontiers_Rizzo.pdf
file_size: 13380030
relation: main_file
success: 1
file_date_updated: 2020-12-21T10:37:50Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Frontiers in Physiology
publication_identifier:
eissn:
- 1664042X
publication_status: published
publisher: Frontiers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Network physiology of cortico–muscular interactions
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
year: '2020'
...
---
_id: '9000'
abstract:
- lang: eng
text: 'In prokaryotes, thermodynamic models of gene regulation provide a highly
quantitative mapping from promoter sequences to gene-expression levels that is
compatible with in vivo and in vitro biophysical measurements. Such concordance
has not been achieved for models of enhancer function in eukaryotes. In equilibrium
models, it is difficult to reconcile the reported short transcription factor (TF)
residence times on the DNA with the high specificity of regulation. In nonequilibrium
models, progress is difficult due to an explosion in the number of parameters.
Here, we navigate this complexity by looking for minimal nonequilibrium enhancer
models that yield desired regulatory phenotypes: low TF residence time, high specificity,
and tunable cooperativity. We find that a single extra parameter, interpretable
as the “linking rate,” by which bound TFs interact with Mediator components, enables
our models to escape equilibrium bounds and access optimal regulatory phenotypes,
while remaining consistent with the reported phenomenology and simple enough to
be inferred from upcoming experiments. We further find that high specificity in
nonequilibrium models is in a trade-off with gene-expression noise, predicting
bursty dynamics—an experimentally observed hallmark of eukaryotic transcription.
By drastically reducing the vast parameter space of nonequilibrium enhancer models
to a much smaller subspace that optimally realizes biological function, we deliver
a rich class of models that could be tractably inferred from data in the near
future.'
acknowledgement: G.T. was supported by Human Frontiers Science Program Grant RGP0034/2018.
R.G. was supported by the Austrian Academy of Sciences DOC Fellowship. R.G. thanks
S. Avvakumov for helpful discussions.
article_processing_charge: No
article_type: original
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: Benjamin
full_name: Zoller, Benjamin
last_name: Zoller
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Grah R, Zoller B, Tkačik G. Nonequilibrium models of optimal enhancer function.
PNAS. 2020;117(50):31614-31622. doi:10.1073/pnas.2006731117
apa: Grah, R., Zoller, B., & Tkačik, G. (2020). Nonequilibrium models of optimal
enhancer function. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.2006731117
chicago: Grah, Rok, Benjamin Zoller, and Gašper Tkačik. “Nonequilibrium Models of
Optimal Enhancer Function.” PNAS. National Academy of Sciences, 2020. https://doi.org/10.1073/pnas.2006731117.
ieee: R. Grah, B. Zoller, and G. Tkačik, “Nonequilibrium models of optimal enhancer
function,” PNAS, vol. 117, no. 50. National Academy of Sciences, pp. 31614–31622,
2020.
ista: Grah R, Zoller B, Tkačik G. 2020. Nonequilibrium models of optimal enhancer
function. PNAS. 117(50), 31614–31622.
mla: Grah, Rok, et al. “Nonequilibrium Models of Optimal Enhancer Function.” PNAS,
vol. 117, no. 50, National Academy of Sciences, 2020, pp. 31614–22, doi:10.1073/pnas.2006731117.
short: R. Grah, B. Zoller, G. Tkačik, PNAS 117 (2020) 31614–31622.
date_created: 2021-01-10T23:01:17Z
date_published: 2020-12-15T00:00:00Z
date_updated: 2023-08-24T11:10:22Z
day: '15'
ddc:
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department:
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doi: 10.1073/pnas.2006731117
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checksum: 69039cd402a571983aa6cb4815ffa863
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creator: dernst
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grant_number: RGP0034/2018
name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
- _id: 267C84F4-B435-11E9-9278-68D0E5697425
name: Biophysically realistic genotype-phenotype maps for regulatory networks
publication: PNAS
publication_identifier:
eissn:
- '10916490'
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/new-compact-model-for-gene-regulation-in-higher-organisms/
scopus_import: '1'
status: public
title: Nonequilibrium models of optimal enhancer function
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)
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year: '2020'
...
---
_id: '7383'
abstract:
- lang: eng
text: Organisms cope with change by employing transcriptional regulators. However,
when faced with rare environments, the evolution of transcriptional regulators
and their promoters may be too slow. We ask whether the intrinsic instability
of gene duplication and amplification provides a generic alternative to canonical
gene regulation. By real-time monitoring of gene copy number mutations in E. coli,
we show that gene duplications and amplifications enable adaptation to fluctuating
environments by rapidly generating copy number, and hence expression level, polymorphism.
This ‘amplification-mediated gene expression tuning’ occurs on timescales similar
to canonical gene regulation and can deal with rapid environmental changes. Mathematical
modeling shows that amplifications also tune gene expression in stochastic environments
where transcription factor-based schemes are hard to evolve or maintain. The fleeting
nature of gene amplifications gives rise to a generic population-level mechanism
that relies on genetic heterogeneity to rapidly tune expression of any gene, without
leaving any genomic signature.
article_processing_charge: No
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
citation:
ama: 'Grah R. Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level
Gene Expression regulation. 2020. doi:10.15479/AT:ISTA:7383'
apa: 'Grah, R. (2020). Matlab scripts for the Paper: Gene Amplification as a Form
of Population-Level Gene Expression regulation. Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:7383'
chicago: 'Grah, Rok. “Matlab Scripts for the Paper: Gene Amplification as a Form
of Population-Level Gene Expression Regulation.” Institute of Science and Technology
Austria, 2020. https://doi.org/10.15479/AT:ISTA:7383.'
ieee: 'R. Grah, “Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level
Gene Expression regulation.” Institute of Science and Technology Austria, 2020.'
ista: 'Grah R. 2020. Matlab scripts for the Paper: Gene Amplification as a Form
of Population-Level Gene Expression regulation, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:7383.'
mla: 'Grah, Rok. Matlab Scripts for the Paper: Gene Amplification as a Form of
Population-Level Gene Expression Regulation. Institute of Science and Technology
Austria, 2020, doi:10.15479/AT:ISTA:7383.'
short: R. Grah, (2020).
contributor:
- contributor_type: project_leader
first_name: Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
date_created: 2020-01-28T10:41:49Z
date_published: 2020-01-28T00:00:00Z
date_updated: 2024-02-21T12:42:31Z
day: '28'
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- _id: GaTk
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keyword:
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- mathematical model
month: '01'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
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status: public
title: 'Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level
Gene Expression regulation'
type: research_data
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year: '2020'
...
---
_id: '7490'
abstract:
- lang: eng
text: In plants, clathrin mediated endocytosis (CME) represents the major route
for cargo internalisation from the cell surface. It has been assumed to operate
in an evolutionary conserved manner as in yeast and animals. Here we report characterisation
of ultrastructure, dynamics and mechanisms of plant CME as allowed by our advancement
in electron microscopy and quantitative live imaging techniques. Arabidopsis CME
appears to follow the constant curvature model and the bona fide CME population
generates vesicles of a predominantly hexagonal-basket type; larger and with faster
kinetics than in other models. Contrary to the existing paradigm, actin is dispensable
for CME events at the plasma membrane but plays a unique role in collecting endocytic
vesicles, sorting of internalised cargos and directional endosome movement that
itself actively promote CME events. Internalized vesicles display a strongly delayed
and sequential uncoating. These unique features highlight the independent evolution
of the plant CME mechanism during the autonomous rise of multicellularity in eukaryotes.
acknowledged_ssus:
- _id: LifeSc
- _id: Bio
- _id: EM-Fac
article_number: e52067
article_processing_charge: No
article_type: original
author:
- first_name: Madhumitha
full_name: Narasimhan, Madhumitha
id: 44BF24D0-F248-11E8-B48F-1D18A9856A87
last_name: Narasimhan
orcid: 0000-0002-8600-0671
- first_name: Alexander J
full_name: Johnson, Alexander J
id: 46A62C3A-F248-11E8-B48F-1D18A9856A87
last_name: Johnson
orcid: 0000-0002-2739-8843
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Walter
full_name: Kaufmann, Walter
id: 3F99E422-F248-11E8-B48F-1D18A9856A87
last_name: Kaufmann
orcid: 0000-0001-9735-5315
- first_name: Shutang
full_name: Tan, Shutang
id: 2DE75584-F248-11E8-B48F-1D18A9856A87
last_name: Tan
orcid: 0000-0002-0471-8285
- first_name: Barbara E
full_name: Casillas Perez, Barbara E
id: 351ED2AA-F248-11E8-B48F-1D18A9856A87
last_name: Casillas Perez
- first_name: Jiří
full_name: Friml, Jiří
id: 4159519E-F248-11E8-B48F-1D18A9856A87
last_name: Friml
orcid: 0000-0002-8302-7596
citation:
ama: Narasimhan M, Johnson AJ, Prizak R, et al. Evolutionarily unique mechanistic
framework of clathrin-mediated endocytosis in plants. eLife. 2020;9. doi:10.7554/eLife.52067
apa: Narasimhan, M., Johnson, A. J., Prizak, R., Kaufmann, W., Tan, S., Casillas
Perez, B. E., & Friml, J. (2020). Evolutionarily unique mechanistic framework
of clathrin-mediated endocytosis in plants. ELife. eLife Sciences Publications.
https://doi.org/10.7554/eLife.52067
chicago: Narasimhan, Madhumitha, Alexander J Johnson, Roshan Prizak, Walter Kaufmann,
Shutang Tan, Barbara E Casillas Perez, and Jiří Friml. “Evolutionarily Unique
Mechanistic Framework of Clathrin-Mediated Endocytosis in Plants.” ELife.
eLife Sciences Publications, 2020. https://doi.org/10.7554/eLife.52067.
ieee: M. Narasimhan et al., “Evolutionarily unique mechanistic framework
of clathrin-mediated endocytosis in plants,” eLife, vol. 9. eLife Sciences
Publications, 2020.
ista: Narasimhan M, Johnson AJ, Prizak R, Kaufmann W, Tan S, Casillas Perez BE,
Friml J. 2020. Evolutionarily unique mechanistic framework of clathrin-mediated
endocytosis in plants. eLife. 9, e52067.
mla: Narasimhan, Madhumitha, et al. “Evolutionarily Unique Mechanistic Framework
of Clathrin-Mediated Endocytosis in Plants.” ELife, vol. 9, e52067, eLife
Sciences Publications, 2020, doi:10.7554/eLife.52067.
short: M. Narasimhan, A.J. Johnson, R. Prizak, W. Kaufmann, S. Tan, B.E. Casillas
Perez, J. Friml, ELife 9 (2020).
date_created: 2020-02-16T23:00:50Z
date_published: 2020-01-23T00:00:00Z
date_updated: 2023-08-18T06:33:07Z
day: '23'
ddc:
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- '580'
department:
- _id: JiFr
- _id: GaTk
- _id: EM-Fac
- _id: SyCr
doi: 10.7554/eLife.52067
ec_funded: 1
external_id:
isi:
- '000514104100001'
pmid:
- '31971511'
file:
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checksum: 2052daa4be5019534f3a42f200a09f32
content_type: application/pdf
creator: dernst
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file_id: '7494'
file_name: 2020_eLife_Narasimhan.pdf
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intvolume: ' 9'
isi: 1
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 261099A6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '742985'
name: Tracing Evolution of Auxin Transport and Polarity in Plants
- _id: 26538374-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I03630
name: Molecular mechanisms of endocytic cargo recognition in plants
publication: eLife
publication_identifier:
eissn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis
in plants
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 9
year: '2020'
...
---
_id: '7569'
abstract:
- lang: eng
text: 'Genes differ in the frequency at which they are expressed and in the form
of regulation used to control their activity. In particular, positive or negative
regulation can lead to activation of a gene in response to an external signal.
Previous works proposed that the form of regulation of a gene correlates with
its frequency of usage: positive regulation when the gene is frequently expressed
and negative regulation when infrequently expressed. Such network design means
that, in the absence of their regulators, the genes are found in their least required
activity state, hence regulatory intervention is often necessary. Due to the multitude
of genes and regulators, spurious binding and unbinding events, called “crosstalk”,
could occur. To determine how the form of regulation affects the global crosstalk
in the network, we used a mathematical model that includes multiple regulators
and multiple target genes. We found that crosstalk depends non-monotonically on
the availability of regulators. Our analysis showed that excess use of regulation
entailed by the formerly suggested network design caused high crosstalk levels
in a large part of the parameter space. We therefore considered the opposite ‘idle’
design, where the default unregulated state of genes is their frequently required
activity state. We found, that ‘idle’ design minimized the use of regulation and
thus minimized crosstalk. In addition, we estimated global crosstalk of S. cerevisiae
using transcription factors binding data. We demonstrated that even partial network
data could suffice to estimate its global crosstalk, suggesting its applicability
to additional organisms. We found that S. cerevisiae estimated crosstalk is lower
than that of a random network, suggesting that natural selection reduces crosstalk.
In summary, our study highlights a new type of protein production cost which is
typically overlooked: that of regulatory interference caused by the presence of
excess regulators in the cell. It demonstrates the importance of whole-network
descriptions, which could show effects missed by single-gene models.'
article_number: e1007642
article_processing_charge: No
article_type: original
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: Tamar
full_name: Friedlander, Tamar
last_name: Friedlander
citation:
ama: Grah R, Friedlander T. The relation between crosstalk and gene regulation form
revisited. PLOS Computational Biology. 2020;16(2). doi:10.1371/journal.pcbi.1007642
apa: Grah, R., & Friedlander, T. (2020). The relation between crosstalk and
gene regulation form revisited. PLOS Computational Biology. Public Library
of Science. https://doi.org/10.1371/journal.pcbi.1007642
chicago: Grah, Rok, and Tamar Friedlander. “The Relation between Crosstalk and Gene
Regulation Form Revisited.” PLOS Computational Biology. Public Library
of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.
ieee: R. Grah and T. Friedlander, “The relation between crosstalk and gene regulation
form revisited,” PLOS Computational Biology, vol. 16, no. 2. Public Library
of Science, 2020.
ista: Grah R, Friedlander T. 2020. The relation between crosstalk and gene regulation
form revisited. PLOS Computational Biology. 16(2), e1007642.
mla: Grah, Rok, and Tamar Friedlander. “The Relation between Crosstalk and Gene
Regulation Form Revisited.” PLOS Computational Biology, vol. 16, no. 2,
e1007642, Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.
short: R. Grah, T. Friedlander, PLOS Computational Biology 16 (2020).
date_created: 2020-03-06T07:39:38Z
date_published: 2020-02-25T00:00:00Z
date_updated: 2023-09-12T11:02:24Z
day: '25'
ddc:
- '000'
- '570'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pcbi.1007642
external_id:
isi:
- '000526725200019'
file:
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checksum: 5239dd134dc6e1c71fe7b3ce2953da37
content_type: application/pdf
creator: dernst
date_created: 2020-03-09T15:12:21Z
date_updated: 2020-07-14T12:48:00Z
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file_name: 2020_PlosCompBio_Grah.pdf
file_size: 2209325
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relation: research_data
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title: The relation between crosstalk and gene regulation form revisited
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 16
year: '2020'
...
---
_id: '7652'
abstract:
- lang: eng
text: Organisms cope with change by taking advantage of transcriptional regulators.
However, when faced with rare environments, the evolution of transcriptional regulators
and their promoters may be too slow. Here, we investigate whether the intrinsic
instability of gene duplication and amplification provides a generic alternative
to canonical gene regulation. Using real-time monitoring of gene-copy-number mutations
in Escherichia coli, we show that gene duplications and amplifications enable
adaptation to fluctuating environments by rapidly generating copy-number and,
therefore, expression-level polymorphisms. This amplification-mediated gene expression
tuning (AMGET) occurs on timescales that are similar to canonical gene regulation
and can respond to rapid environmental changes. Mathematical modelling shows that
amplifications also tune gene expression in stochastic environments in which transcription-factor-based
schemes are hard to evolve or maintain. The fleeting nature of gene amplifications
gives rise to a generic population-level mechanism that relies on genetic heterogeneity
to rapidly tune the expression of any gene, without leaving any genomic signature.
acknowledgement: We thank L. Hurst, N. Barton, M. Pleska, M. Steinrück, B. Kavcic
and A. Staron for input on the manuscript, and To. Bergmiller and R. Chait for help
with microfluidics experiments. I.T. is a recipient the OMV fellowship. R.G. is
a recipient of a DOC (Doctoral Fellowship Programme of the Austrian Academy of Sciences)
Fellowship of the Austrian Academy of Sciences.
article_processing_charge: No
article_type: original
author:
- first_name: Isabella
full_name: Tomanek, Isabella
id: 3981F020-F248-11E8-B48F-1D18A9856A87
last_name: Tomanek
orcid: 0000-0001-6197-363X
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: M.
full_name: Lagator, M.
last_name: Lagator
- first_name: A. M. C.
full_name: Andersson, A. M. C.
last_name: Andersson
- first_name: Jonathan P
full_name: Bollback, Jonathan P
id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
last_name: Bollback
orcid: 0000-0002-4624-4612
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Tomanek I, Grah R, Lagator M, et al. Gene amplification as a form of population-level
gene expression regulation. Nature Ecology & Evolution. 2020;4(4):612-625.
doi:10.1038/s41559-020-1132-7
apa: Tomanek, I., Grah, R., Lagator, M., Andersson, A. M. C., Bollback, J. P., Tkačik,
G., & Guet, C. C. (2020). Gene amplification as a form of population-level
gene expression regulation. Nature Ecology & Evolution. Springer Nature.
https://doi.org/10.1038/s41559-020-1132-7
chicago: Tomanek, Isabella, Rok Grah, M. Lagator, A. M. C. Andersson, Jonathan P
Bollback, Gašper Tkačik, and Calin C Guet. “Gene Amplification as a Form of Population-Level
Gene Expression Regulation.” Nature Ecology & Evolution. Springer Nature,
2020. https://doi.org/10.1038/s41559-020-1132-7.
ieee: I. Tomanek et al., “Gene amplification as a form of population-level
gene expression regulation,” Nature Ecology & Evolution, vol. 4, no.
4. Springer Nature, pp. 612–625, 2020.
ista: Tomanek I, Grah R, Lagator M, Andersson AMC, Bollback JP, Tkačik G, Guet CC.
2020. Gene amplification as a form of population-level gene expression regulation.
Nature Ecology & Evolution. 4(4), 612–625.
mla: Tomanek, Isabella, et al. “Gene Amplification as a Form of Population-Level
Gene Expression Regulation.” Nature Ecology & Evolution, vol. 4, no.
4, Springer Nature, 2020, pp. 612–25, doi:10.1038/s41559-020-1132-7.
short: I. Tomanek, R. Grah, M. Lagator, A.M.C. Andersson, J.P. Bollback, G. Tkačik,
C.C. Guet, Nature Ecology & Evolution 4 (2020) 612–625.
date_created: 2020-04-08T15:20:53Z
date_published: 2020-04-01T00:00:00Z
date_updated: 2024-03-25T23:30:20Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.1038/s41559-020-1132-7
external_id:
isi:
- '000519008300005'
file:
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checksum: ef3bbf42023e30b2c24a6278025d2040
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creator: dernst
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file_name: 2020_NatureEcolEvo_Tomanek.pdf
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month: '04'
oa: 1
oa_version: Submitted Version
page: 612-625
project:
- _id: 267C84F4-B435-11E9-9278-68D0E5697425
name: Biophysically realistic genotype-phenotype maps for regulatory networks
publication: Nature Ecology & Evolution
publication_identifier:
issn:
- 2397-334X
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
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- description: News on IST Homepage
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url: https://ist.ac.at/en/news/how-to-thrive-without-gene-regulation/
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status: public
title: Gene amplification as a form of population-level gene expression regulation
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 4
year: '2020'
...
---
_id: '7656'
abstract:
- lang: eng
text: 'We propose that correlations among neurons are generically strong enough
to organize neural activity patterns into a discrete set of clusters, which can
each be viewed as a population codeword. Our reasoning starts with the analysis
of retinal ganglion cell data using maximum entropy models, showing that the population
is robustly in a frustrated, marginally sub-critical, or glassy, state. This leads
to an argument that neural populations in many other brain areas might share this
structure. Next, we use latent variable models to show that this glassy state
possesses well-defined clusters of neural activity. Clusters have three appealing
properties: (i) clusters exhibit error correction, i.e., they are reproducibly
elicited by the same stimulus despite variability at the level of constituent
neurons; (ii) clusters encode qualitatively different visual features than their
constituent neurons; and (iii) clusters can be learned by downstream neural circuits
in an unsupervised fashion. We hypothesize that these properties give rise to
a “learnable” neural code which the cortical hierarchy uses to extract increasingly
complex features without supervision or reinforcement.'
article_number: '20'
article_processing_charge: No
article_type: original
author:
- first_name: Michael J.
full_name: Berry, Michael J.
last_name: Berry
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: 'Berry MJ, Tkačik G. Clustering of neural activity: A design principle for
population codes. Frontiers in Computational Neuroscience. 2020;14. doi:10.3389/fncom.2020.00020'
apa: 'Berry, M. J., & Tkačik, G. (2020). Clustering of neural activity: A design
principle for population codes. Frontiers in Computational Neuroscience.
Frontiers. https://doi.org/10.3389/fncom.2020.00020'
chicago: 'Berry, Michael J., and Gašper Tkačik. “Clustering of Neural Activity:
A Design Principle for Population Codes.” Frontiers in Computational Neuroscience.
Frontiers, 2020. https://doi.org/10.3389/fncom.2020.00020.'
ieee: 'M. J. Berry and G. Tkačik, “Clustering of neural activity: A design principle
for population codes,” Frontiers in Computational Neuroscience, vol. 14.
Frontiers, 2020.'
ista: 'Berry MJ, Tkačik G. 2020. Clustering of neural activity: A design principle
for population codes. Frontiers in Computational Neuroscience. 14, 20.'
mla: 'Berry, Michael J., and Gašper Tkačik. “Clustering of Neural Activity: A Design
Principle for Population Codes.” Frontiers in Computational Neuroscience,
vol. 14, 20, Frontiers, 2020, doi:10.3389/fncom.2020.00020.'
short: M.J. Berry, G. Tkačik, Frontiers in Computational Neuroscience 14 (2020).
date_created: 2020-04-12T22:00:40Z
date_published: 2020-03-13T00:00:00Z
date_updated: 2023-08-18T10:30:11Z
day: '13'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.3389/fncom.2020.00020
external_id:
isi:
- '000525543200001'
pmid:
- '32231528'
file:
- access_level: open_access
checksum: 2b1da23823eae9cedbb42d701945b61e
content_type: application/pdf
creator: dernst
date_created: 2020-04-14T12:20:39Z
date_updated: 2020-07-14T12:48:01Z
file_id: '7659'
file_name: 2020_Frontiers_Berry.pdf
file_size: 4082937
relation: main_file
file_date_updated: 2020-07-14T12:48:01Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
pmid: 1
publication: Frontiers in Computational Neuroscience
publication_identifier:
eissn:
- '16625188'
publication_status: published
publisher: Frontiers
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Clustering of neural activity: A design principle for 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 14
year: '2020'
...