---
_id: '14656'
abstract:
- lang: eng
  text: Although much is known about how single neurons in the hippocampus represent
    an animal's position, how circuit interactions contribute to spatial coding is
    less well understood. Using a novel statistical estimator and theoretical modeling,
    both developed in the framework of maximum entropy models, we reveal highly structured
    CA1 cell-cell interactions in male rats during open field exploration. The statistics
    of these interactions depend on whether the animal is in a familiar or novel environment.
    In both conditions the circuit interactions optimize the encoding of spatial information,
    but for regimes that differ in the informativeness of their spatial inputs. This
    structure facilitates linear decodability, making the information easy to read
    out by downstream circuits. Overall, our findings suggest that the efficient coding
    hypothesis is not only applicable to individual neuron properties in the sensory
    periphery, but also to neural interactions in the central brain.
acknowledgement: M.N. was supported by the European Union Horizon 2020 Grant 665385.
  J.C. was supported by the European Research Council Consolidator Grant 281511. G.T.
  was supported by the Austrian Science Fund (FWF) Grant P34015. C.S. was supported
  by an Institute of Science and Technology fellow award and by the National Science
  Foundation (NSF) Award No. 1922658. We thank Peter Baracskay, Karola Kaefer, and
  Hugo Malagon-Vina for the acquisition of the data. We also thank Federico Stella,
  Wiktor Młynarski, Dori Derdikman, Colin Bredenberg, Roman Huszar, Heloisa Chiossi,
  Lorenzo Posani, and Mohamady El-Gaby for comments on an earlier version of the manuscript.
article_processing_charge: Yes (in subscription journal)
article_type: original
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. <i>The Journal of Neuroscience</i>.
    2023;43(48):8140-8156. doi:<a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">10.1523/JNEUROSCI.0194-23.2023</a>
  apa: Nardin, M., Csicsvari, J. L., Tkačik, G., &#38; Savin, C. (2023). The structure
    of hippocampal CA1 interactions optimizes spatial coding across experience. <i>The
    Journal of Neuroscience</i>. Society of Neuroscience. <a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">https://doi.org/10.1523/JNEUROSCI.0194-23.2023</a>
  chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin.
    “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across
    Experience.” <i>The Journal of Neuroscience</i>. Society of Neuroscience, 2023.
    <a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">https://doi.org/10.1523/JNEUROSCI.0194-23.2023</a>.
  ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal
    CA1 interactions optimizes spatial coding across experience,” <i>The Journal of
    Neuroscience</i>, vol. 43, no. 48. Society of Neuroscience, pp. 8140–8156, 2023.
  ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. 2023. The structure of hippocampal
    CA1 interactions optimizes spatial coding across experience. The Journal of Neuroscience.
    43(48), 8140–8156.
  mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes
    Spatial Coding across Experience.” <i>The Journal of Neuroscience</i>, vol. 43,
    no. 48, Society of Neuroscience, 2023, pp. 8140–56, doi:<a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">10.1523/JNEUROSCI.0194-23.2023</a>.
  short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, The Journal of Neuroscience
    43 (2023) 8140–8156.
date_created: 2023-12-10T23:00:58Z
date_published: 2023-11-29T00:00:00Z
date_updated: 2023-12-11T11:37:20Z
day: '29'
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- '570'
department:
- _id: JoCs
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doi: 10.1523/JNEUROSCI.0194-23.2023
ec_funded: 1
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publication: The Journal of Neuroscience
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title: The structure of hippocampal CA1 interactions optimizes spatial coding across
  experience
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abstract:
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  text: Statistics of natural scenes are not uniform - their structure varies dramatically
    from ground to sky. It remains unknown whether these non-uniformities are reflected
    in the large-scale organization of the early visual system and what benefits such
    adaptations would confer. Here, by relying on the efficient coding hypothesis,
    we predict that changes in the structure of receptive fields across visual space
    increase the efficiency of sensory coding. We show experimentally that, in agreement
    with our predictions, receptive fields of retinal ganglion cells change their
    shape along the dorsoventral retinal axis, with a marked surround asymmetry at
    the visual horizon. Our work demonstrates that, according to principles of efficient
    coding, the panoramic structure of natural scenes is exploited by the retina across
    space and cell-types.
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- _id: ScienComp
- _id: PreCl
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acknowledgement: We thank Hiroki Asari for sharing the dataset of naturalistic images,
  Anton Sumser for sharing visual stimulus code, Yoav Ben Simon for initial explorative
  work with the generation of AAVs, and Tomas Vega-Zuñiga for help with immunostainings.
  We also thank Gasper Tkacik and members of the Neuroethology group for their comments
  on the manuscript. This research was supported by the Scientific Service Units of
  IST Austria through resources provided by Scientific Computing, the Preclinical
  Facility, the Lab Support Facility, and the Imaging and Optics Facility. This work
  was supported by European Union Horizon 2020 Marie Skłodowska-Curie grant 665385
  (DG), Austrian Science Fund (FWF) stand-alone grant P 34015 (WM), Human Frontiers
  Science Program LT000256/2018-L (AS), EMBO ALTF 1098-2017 (AS) and the European
  Research Council Starting Grant 756502 (MJ).
article_processing_charge: Yes (in subscription journal)
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author:
- first_name: Divyansh
  full_name: Gupta, Divyansh
  id: 2A485EBE-F248-11E8-B48F-1D18A9856A87
  last_name: Gupta
  orcid: 0000-0001-7400-6665
- first_name: Wiktor F
  full_name: Mlynarski, Wiktor F
  id: 358A453A-F248-11E8-B48F-1D18A9856A87
  last_name: Mlynarski
- first_name: Anton L
  full_name: Sumser, Anton L
  id: 3320A096-F248-11E8-B48F-1D18A9856A87
  last_name: Sumser
  orcid: 0000-0002-4792-1881
- first_name: Olga
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  id: 3C0C7BC6-F248-11E8-B48F-1D18A9856A87
  last_name: Symonova
  orcid: 0000-0003-2012-9947
- first_name: Jan
  full_name: Svaton, Jan
  id: f7f724c3-9d6f-11ed-9f44-e5c5f3a5bee2
  last_name: Svaton
  orcid: 0000-0002-6198-2939
- first_name: Maximilian A
  full_name: Jösch, Maximilian A
  id: 2BD278E6-F248-11E8-B48F-1D18A9856A87
  last_name: Jösch
  orcid: 0000-0002-3937-1330
citation:
  ama: Gupta D, Mlynarski WF, Sumser AL, Symonova O, Svaton J, Jösch MA. Panoramic
    visual statistics shape retina-wide organization of receptive fields. <i>Nature
    Neuroscience</i>. 2023;26:606-614. doi:<a href="https://doi.org/10.1038/s41593-023-01280-0">10.1038/s41593-023-01280-0</a>
  apa: Gupta, D., Mlynarski, W. F., Sumser, A. L., Symonova, O., Svaton, J., &#38;
    Jösch, M. A. (2023). Panoramic visual statistics shape retina-wide organization
    of receptive fields. <i>Nature Neuroscience</i>. Springer Nature. <a href="https://doi.org/10.1038/s41593-023-01280-0">https://doi.org/10.1038/s41593-023-01280-0</a>
  chicago: Gupta, Divyansh, Wiktor F Mlynarski, Anton L Sumser, Olga Symonova, Jan
    Svaton, and Maximilian A Jösch. “Panoramic Visual Statistics Shape Retina-Wide
    Organization of Receptive Fields.” <i>Nature Neuroscience</i>. Springer Nature,
    2023. <a href="https://doi.org/10.1038/s41593-023-01280-0">https://doi.org/10.1038/s41593-023-01280-0</a>.
  ieee: D. Gupta, W. F. Mlynarski, A. L. Sumser, O. Symonova, J. Svaton, and M. A.
    Jösch, “Panoramic visual statistics shape retina-wide organization of receptive
    fields,” <i>Nature Neuroscience</i>, vol. 26. Springer Nature, pp. 606–614, 2023.
  ista: Gupta D, Mlynarski WF, Sumser AL, Symonova O, Svaton J, Jösch MA. 2023. Panoramic
    visual statistics shape retina-wide organization of receptive fields. Nature Neuroscience.
    26, 606–614.
  mla: Gupta, Divyansh, et al. “Panoramic Visual Statistics Shape Retina-Wide Organization
    of Receptive Fields.” <i>Nature Neuroscience</i>, vol. 26, Springer Nature, 2023,
    pp. 606–14, doi:<a href="https://doi.org/10.1038/s41593-023-01280-0">10.1038/s41593-023-01280-0</a>.
  short: D. Gupta, W.F. Mlynarski, A.L. Sumser, O. Symonova, J. Svaton, M.A. Jösch,
    Nature Neuroscience 26 (2023) 606–614.
date_created: 2023-01-23T14:14:19Z
date_published: 2023-04-01T00:00:00Z
date_updated: 2023-10-04T11:41:05Z
day: '01'
ddc:
- '570'
department:
- _id: GradSch
- _id: MaJö
doi: 10.1038/s41593-023-01280-0
ec_funded: 1
external_id:
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abstract:
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  text: 'Statistics of natural scenes are not uniform - their structure varies dramatically
    from ground to sky. It remains unknown whether these non-uniformities are reflected
    in the large-scale organization of the early visual system and what benefits such
    adaptations would confer. Here, by relying on the efficient coding hypothesis,
    we predict that changes in the structure of receptive fields across visual space
    increase the efficiency of sensory coding. We show experimentally that, in agreement
    with our predictions, receptive fields of retinal ganglion cells change their
    shape along the dorsoventral retinal axis, with a marked surround asymmetry at
    the visual horizon. Our work demonstrates that, according to principles of efficient
    coding, the panoramic structure of natural scenes is exploited by the retina across
    space and cell-types. '
acknowledged_ssus:
- _id: ScienComp
- _id: M-Shop
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- _id: PreCl
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article_processing_charge: No
author:
- first_name: Divyansh
  full_name: Gupta, Divyansh
  id: 2A485EBE-F248-11E8-B48F-1D18A9856A87
  last_name: Gupta
  orcid: 0000-0001-7400-6665
- first_name: Anton L
  full_name: Sumser, Anton L
  id: 3320A096-F248-11E8-B48F-1D18A9856A87
  last_name: Sumser
  orcid: 0000-0002-4792-1881
- first_name: Maximilian A
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citation:
  ama: 'Gupta D, Sumser AL, Jösch MA. Research Data for: Panoramic visual statistics
    shape retina-wide organization of receptive fields. 2023. doi:<a href="https://doi.org/10.15479/AT:ISTA:12370">10.15479/AT:ISTA:12370</a>'
  apa: 'Gupta, D., Sumser, A. L., &#38; Jösch, M. A. (2023). Research Data for: Panoramic
    visual statistics shape retina-wide organization of receptive fields. Institute
    of Science and Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:12370">https://doi.org/10.15479/AT:ISTA:12370</a>'
  chicago: 'Gupta, Divyansh, Anton L Sumser, and Maximilian A Jösch. “Research Data
    for: Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields.”
    Institute of Science and Technology Austria, 2023. <a href="https://doi.org/10.15479/AT:ISTA:12370">https://doi.org/10.15479/AT:ISTA:12370</a>.'
  ieee: 'D. Gupta, A. L. Sumser, and M. A. Jösch, “Research Data for: Panoramic visual
    statistics shape retina-wide organization of receptive fields.” Institute of Science
    and Technology Austria, 2023.'
  ista: 'Gupta D, Sumser AL, Jösch MA. 2023. Research Data for: Panoramic visual statistics
    shape retina-wide organization of receptive fields, Institute of Science and Technology
    Austria, <a href="https://doi.org/10.15479/AT:ISTA:12370">10.15479/AT:ISTA:12370</a>.'
  mla: 'Gupta, Divyansh, et al. <i>Research Data for: Panoramic Visual Statistics
    Shape Retina-Wide Organization of Receptive Fields</i>. Institute of Science and
    Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/AT:ISTA:12370">10.15479/AT:ISTA:12370</a>.'
  short: D. Gupta, A.L. Sumser, M.A. Jösch, (2023).
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date_created: 2023-01-25T12:45:18Z
date_published: 2023-01-26T00:00:00Z
date_updated: 2023-10-04T11:41:04Z
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month: '01'
oa: 1
oa_version: Published Version
project:
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  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
  grant_number: P34015
  name: Efficient coding with biophysical realism
- _id: 2634E9D2-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
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  name: Circuits of Visual Attention
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  grant_number: LT000256
  name: Neuronal networks of salience and spatial detection in the murine superior
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  grant_number: ALTF 1098-2017
  name: Connecting sensory with motor processing in the superior colliculus
publisher: Institute of Science and Technology Austria
related_material:
  record:
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    status: public
status: public
title: 'Research Data for: Panoramic visual statistics shape retina-wide organization
  of receptive fields'
tmp:
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  legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
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  short: CC BY-NC-SA (4.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '12762'
abstract:
- lang: eng
  text: Neurons in the brain are wired into adaptive networks that exhibit collective
    dynamics as diverse as scale-specific oscillations and scale-free neuronal avalanches.
    Although existing models account for oscillations and avalanches separately, they
    typically do not explain both phenomena, are too complex to analyze analytically
    or intractable to infer from data rigorously. Here we propose a feedback-driven
    Ising-like class of neural networks that captures avalanches and oscillations
    simultaneously and quantitatively. In the simplest yet fully microscopic model
    version, we can analytically compute the phase diagram and 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 oscillations to
    collective behaviors of extreme events and neuronal avalanches. Importantly, the
    inferred parameters indicate that the co-existence of scale-specific (oscillations)
    and scale-free (avalanches) dynamics occurs close to a non-equilibrium critical
    point at the onset of self-sustained oscillations.
acknowledgement: This research was funded in whole, or in part, by the Austrian Science
  Fund (FWF) (grant no. PT1013M03318 to F.L. and no. P34015 to G.T.). For the purpose
  of open access, the author has applied a CC BY public copyright licence to any Author
  Accepted Manuscript version arising from this submission. The study was supported
  by the European Union Horizon 2020 research and innovation program under the Marie
  Sklodowska-Curie action (grant agreement No. 754411 to F.L.).
article_processing_charge: No
article_type: original
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
  id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
  last_name: De Martino
  orcid: 0000-0002-5214-4706
citation:
  ama: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Statistical modeling
    of adaptive neural networks explains co-existence of avalanches and oscillations
    in resting human brain. <i>Nature Computational Science</i>. 2023;3:254-263. doi:<a
    href="https://doi.org/10.1038/s43588-023-00410-9">10.1038/s43588-023-00410-9</a>
  apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., &#38; De Martino, D. (2023).
    Statistical modeling of adaptive neural networks explains co-existence of avalanches
    and oscillations in resting human brain. <i>Nature Computational Science</i>.
    Springer Nature. <a href="https://doi.org/10.1038/s43588-023-00410-9">https://doi.org/10.1038/s43588-023-00410-9</a>
  chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
    De Martino. “Statistical Modeling of Adaptive Neural Networks Explains Co-Existence
    of Avalanches and Oscillations in Resting Human Brain.” <i>Nature Computational
    Science</i>. Springer Nature, 2023. <a href="https://doi.org/10.1038/s43588-023-00410-9">https://doi.org/10.1038/s43588-023-00410-9</a>.
  ieee: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Statistical
    modeling of adaptive neural networks explains co-existence of avalanches and oscillations
    in resting human brain,” <i>Nature Computational Science</i>, vol. 3. Springer
    Nature, pp. 254–263, 2023.
  ista: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. 2023. Statistical modeling
    of adaptive neural networks explains co-existence of avalanches and oscillations
    in resting human brain. Nature Computational Science. 3, 254–263.
  mla: Lombardi, Fabrizio, et al. “Statistical Modeling of Adaptive Neural Networks
    Explains Co-Existence of Avalanches and Oscillations in Resting Human Brain.”
    <i>Nature Computational Science</i>, vol. 3, Springer Nature, 2023, pp. 254–63,
    doi:<a href="https://doi.org/10.1038/s43588-023-00410-9">10.1038/s43588-023-00410-9</a>.
  short: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, Nature Computational
    Science 3 (2023) 254–263.
date_created: 2023-03-26T22:01:08Z
date_published: 2023-03-20T00:00:00Z
date_updated: 2023-08-16T12:41:53Z
day: '20'
ddc:
- '570'
department:
- _id: GaTk
- _id: GradSch
doi: 10.1038/s43588-023-00410-9
ec_funded: 1
external_id:
  arxiv:
  - '2108.06686'
file:
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  date_created: 2023-08-16T12:39:57Z
  date_updated: 2023-08-16T12:39:57Z
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  file_size: 4474284
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file_date_updated: 2023-08-16T12:39:57Z
has_accepted_license: '1'
intvolume: '         3'
language:
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month: '03'
oa: 1
oa_version: Published Version
page: 254-263
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
- _id: eb943429-77a9-11ec-83b8-9f471cdf5c67
  grant_number: M03318
  name: Functional Advantages of Critical Brain Dynamics
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
  grant_number: P34015
  name: Efficient coding with biophysical realism
publication: Nature Computational Science
publication_identifier:
  eissn:
  - 2662-8457
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Statistical modeling of adaptive neural networks explains co-existence of avalanches
  and oscillations in resting human brain
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: 3
year: '2023'
...
---
_id: '12332'
abstract:
- lang: eng
  text: Activity of sensory neurons is driven not only by external stimuli but also
    by feedback signals from higher brain areas. Attention is one particularly important
    internal signal whose presumed role is to modulate sensory representations such
    that they only encode information currently relevant to the organism at minimal
    cost. This hypothesis has, however, not yet been expressed in a normative computational
    framework. Here, by building on normative principles of probabilistic inference
    and efficient coding, we developed a model of dynamic population coding in the
    visual cortex. By continuously adapting the sensory code to changing demands of
    the perceptual observer, an attention-like modulation emerges. This modulation
    can dramatically reduce the amount of neural activity without deteriorating the
    accuracy of task-specific inferences. Our results suggest that a range of seemingly
    disparate cortical phenomena such as intrinsic gain modulation, attention-related
    tuning modulation, and response variability could be manifestations of the same
    underlying principles, which combine efficient sensory coding with optimal probabilistic
    inference in dynamic environments.
acknowledgement: "We thank Robbe Goris for generously providing figures from his work
  and Ann M. Hermundstad for helpful discussions.\r\nGT & WM were supported by the
  Austrian Science Fund Standalone Grant P 34015 \"Efficient Coding with Biophysical
  Realism\" (https://pf.fwf.ac.at/) WM was additionally supported by the European
  Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie
  Grant Agreement No. 754411 (https://ec.europa.eu/research/mariecurieactions/). The
  funders had no role in study design, data collection and analysis, decision to publish,
  or preparation of the manuscript."
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: Gašper
  full_name: Tkačik, Gašper
  id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
  last_name: Tkačik
  orcid: '1'
citation:
  ama: Mlynarski WF, Tkačik G. Efficient coding theory of dynamic attentional modulation.
    <i>PLoS Biology</i>. 2022;20(12):e3001889. doi:<a href="https://doi.org/10.1371/journal.pbio.3001889">10.1371/journal.pbio.3001889</a>
  apa: Mlynarski, W. F., &#38; Tkačik, G. (2022). Efficient coding theory of dynamic
    attentional modulation. <i>PLoS Biology</i>. Public Library of Science. <a href="https://doi.org/10.1371/journal.pbio.3001889">https://doi.org/10.1371/journal.pbio.3001889</a>
  chicago: Mlynarski, Wiktor F, and Gašper Tkačik. “Efficient Coding Theory of Dynamic
    Attentional Modulation.” <i>PLoS Biology</i>. Public Library of Science, 2022.
    <a href="https://doi.org/10.1371/journal.pbio.3001889">https://doi.org/10.1371/journal.pbio.3001889</a>.
  ieee: W. F. Mlynarski and G. Tkačik, “Efficient coding theory of dynamic attentional
    modulation,” <i>PLoS Biology</i>, vol. 20, no. 12. Public Library of Science,
    p. e3001889, 2022.
  ista: Mlynarski WF, Tkačik G. 2022. Efficient coding theory of dynamic attentional
    modulation. PLoS Biology. 20(12), e3001889.
  mla: Mlynarski, Wiktor F., and Gašper Tkačik. “Efficient Coding Theory of Dynamic
    Attentional Modulation.” <i>PLoS Biology</i>, vol. 20, no. 12, Public Library
    of Science, 2022, p. e3001889, doi:<a href="https://doi.org/10.1371/journal.pbio.3001889">10.1371/journal.pbio.3001889</a>.
  short: W.F. Mlynarski, G. Tkačik, PLoS Biology 20 (2022) e3001889.
date_created: 2023-01-22T23:00:55Z
date_published: 2022-12-21T00:00:00Z
date_updated: 2023-08-03T14:23:49Z
day: '21'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pbio.3001889
ec_funded: 1
external_id:
  isi:
  - '000925192000001'
file:
- access_level: open_access
  checksum: 5d7f1111a87e5f2c1bf92f8886738894
  content_type: application/pdf
  creator: dernst
  date_created: 2023-01-23T08:46:40Z
  date_updated: 2023-01-23T08:46:40Z
  file_id: '12337'
  file_name: 2022_PloSBiology_Mlynarski.pdf
  file_size: 4248838
  relation: main_file
  success: 1
file_date_updated: 2023-01-23T08:46:40Z
has_accepted_license: '1'
intvolume: '        20'
isi: 1
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: e3001889
project:
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
  grant_number: P34015
  name: Efficient coding with biophysical realism
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
publication: PLoS Biology
publication_identifier:
  eissn:
  - 1545-7885
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Efficient coding theory of dynamic attentional modulation
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: 20
year: '2022'
...
---
_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:<a href="https://doi.org/10.48550/ARXIV.2108.06686">10.48550/ARXIV.2108.06686</a>
  apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., &#38; De Martino, D. (n.d.).
    Quantifying the coexistence of neuronal oscillations and avalanches. arXiv. <a
    href="https://doi.org/10.48550/ARXIV.2108.06686">https://doi.org/10.48550/ARXIV.2108.06686</a>
  chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
    De Martino. “Quantifying the Coexistence of Neuronal Oscillations and Avalanches.”
    arXiv, n.d. <a href="https://doi.org/10.48550/ARXIV.2108.06686">https://doi.org/10.48550/ARXIV.2108.06686</a>.
  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. <a href="https://doi.org/10.48550/ARXIV.2108.06686">10.48550/ARXIV.2108.06686</a>.
  mla: Lombardi, Fabrizio, et al. <i>Quantifying the Coexistence of Neuronal Oscillations
    and Avalanches</i>. arXiv, doi:<a href="https://doi.org/10.48550/ARXIV.2108.06686">10.48550/ARXIV.2108.06686</a>.
  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: '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. <i>bioRxiv</i>. doi:<a
    href="https://doi.org/10.1101/2021.09.28.460602">10.1101/2021.09.28.460602</a>
  apa: Nardin, M., Csicsvari, J. L., Tkačik, G., &#38; Savin, C. (n.d.). The structure
    of hippocampal CA1 interactions optimizes spatial coding across experience. <i>bioRxiv</i>.
    Cold Spring Harbor Laboratory. <a href="https://doi.org/10.1101/2021.09.28.460602">https://doi.org/10.1101/2021.09.28.460602</a>
  chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin.
    “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across
    Experience.” <i>BioRxiv</i>. Cold Spring Harbor Laboratory, n.d. <a href="https://doi.org/10.1101/2021.09.28.460602">https://doi.org/10.1101/2021.09.28.460602</a>.
  ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal
    CA1 interactions optimizes spatial coding across experience,” <i>bioRxiv</i>.
    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, <a href="https://doi.org/10.1101/2021.09.28.460602">10.1101/2021.09.28.460602</a>.
  mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes
    Spatial Coding across Experience.” <i>BioRxiv</i>, Cold Spring Harbor Laboratory,
    doi:<a href="https://doi.org/10.1101/2021.09.28.460602">10.1101/2021.09.28.460602</a>.
  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:
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- _id: JoCs
- _id: GaTk
doi: 10.1101/2021.09.28.460602
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project:
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publication: bioRxiv
publication_status: submitted
publisher: Cold Spring Harbor Laboratory
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    status: public
status: public
title: The structure of hippocampal CA1 interactions optimizes spatial coding across
  experience
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...