--- _id: '2850' abstract: - lang: eng text: "Recent work emphasizes that the maximum entropy principle provides a bridge between statistical mechanics models for collective behavior in neural networks and experiments on networks of real neurons. Most of this work has focused on capturing the measured correlations among pairs of neurons. Here we suggest an alternative, constructing models that are consistent with the distribution of global network activity, i.e. the probability that K out of N cells in the network generate action potentials in the same small time bin. The inverse problem that we need to solve in constructing the model is analytically tractable, and provides a natural 'thermodynamics' for the network in the limit of large N. We analyze the responses of neurons in a small patch of the retina to naturalistic stimuli, and find that the implied thermodynamics is very close to an unusual critical point, in which the entropy (in proper units) is exactly equal to the energy. © 2013 IOP Publishing Ltd and SISSA Medialab srl.\r\n" acknowledgement: "his work was supported in part by NSF Grants IIS-0613435 and PHY-0957573, by NIH Grants R01 EY14196 and P50 GM071508, by the Fannie and John Hertz Foundation, by the Human Frontiers Science Program, by the Swartz Foundation, and by the WM Keck Foundation.\r\n" article_number: P03011 article_processing_charge: No article_type: original author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Dario full_name: Amodei, Dario last_name: Amodei - first_name: Michael full_name: Berry, Michael last_name: Berry - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03011 apa: Tkačik, G., Marre, O., Mora, T., Amodei, D., Berry, M., & Bialek, W. (2013). The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03011 chicago: Tkačik, Gašper, Olivier Marre, Thierry Mora, Dario Amodei, Michael Berry, and William Bialek. “The Simplest Maximum Entropy Model for Collective Behavior in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd., 2013. https://doi.org/10.1088/1742-5468/2013/03/P03011. ieee: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, and W. Bialek, “The simplest maximum entropy model for collective behavior in a neural network,” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013. ista: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. 2013. The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. 2013(3), P03011. mla: Tkačik, Gašper, et al. “The Simplest Maximum Entropy Model for Collective Behavior in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3, P03011, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03011. short: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, W. Bialek, Journal of Statistical Mechanics Theory and Experiment 2013 (2013). date_created: 2018-12-11T11:59:55Z date_published: 2013-03-12T00:00:00Z date_updated: 2021-01-12T07:00:14Z day: '12' department: - _id: GaTk doi: 10.1088/1742-5468/2013/03/P03011 external_id: arxiv: - '1207.6319' intvolume: ' 2013' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1207.6319 month: '03' oa: 1 oa_version: Preprint publication: Journal of Statistical Mechanics Theory and Experiment publication_status: published publisher: IOP Publishing Ltd. publist_id: '3942' quality_controlled: '1' scopus_import: 1 status: public title: The simplest maximum entropy model for collective behavior in a neural network type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2013 year: '2013' ... --- _id: '2851' abstract: - lang: eng text: The number of possible activity patterns in a population of neurons grows exponentially with the size of the population. Typical experiments explore only a tiny fraction of the large space of possible activity patterns in the case of populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled regime, to estimate the probabilities with which most of the activity patterns occur. As a result, the corresponding entropy - which is a measure of the computational power of the neural population - cannot be estimated directly. We propose a simple scheme for estimating the entropy in the undersampled regime, which bounds its value from both below and above. The lower bound is the usual 'naive' entropy of the experimental frequencies. The upper bound results from a hybrid approximation of the entropy which makes use of the naive estimate, a maximum entropy fit, and a coverage adjustment. We apply our simple scheme to artificial data, in order to check their accuracy; we also compare its performance to those of several previously defined entropy estimators. We then apply it to actual measurements of neural activity in populations with up to 100 cells. Finally, we discuss the similarities and differences between the proposed simple estimation scheme and various earlier methods. © 2013 IOP Publishing Ltd and SISSA Medialab srl. article_number: P03015 author: - first_name: Michael full_name: Berry, Michael last_name: Berry - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Julien full_name: Dubuis, Julien last_name: Dubuis - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Ravá full_name: Da Silveira, Ravá last_name: Da Silveira citation: ama: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03015 apa: Berry, M., Tkačik, G., Dubuis, J., Marre, O., & Da Silveira, R. (2013). A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03015 chicago: Berry, Michael, Gašper Tkačik, Julien Dubuis, Olivier Marre, and Ravá Da Silveira. “A Simple Method for Estimating the Entropy of Neural Activity.” Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd., 2013. https://doi.org/10.1088/1742-5468/2013/03/P03015. ieee: M. Berry, G. Tkačik, J. Dubuis, O. Marre, and R. Da Silveira, “A simple method for estimating the entropy of neural activity,” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013. ista: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. 2013. A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. 2013(3), P03015. mla: Berry, Michael, et al. “A Simple Method for Estimating the Entropy of Neural Activity.” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3, P03015, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03015. short: M. Berry, G. Tkačik, J. Dubuis, O. Marre, R. Da Silveira, Journal of Statistical Mechanics Theory and Experiment 2013 (2013). date_created: 2018-12-11T11:59:56Z date_published: 2013-03-12T00:00:00Z date_updated: 2021-01-12T07:00:14Z day: '12' department: - _id: GaTk doi: 10.1088/1742-5468/2013/03/P03015 intvolume: ' 2013' issue: '3' language: - iso: eng month: '03' oa_version: None publication: Journal of Statistical Mechanics Theory and Experiment publication_status: published publisher: IOP Publishing Ltd. publist_id: '3941' quality_controlled: '1' scopus_import: 1 status: public title: A simple method for estimating the entropy of neural activity type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2013 year: '2013' ... --- _id: '2857' abstract: - lang: eng text: In the vibrant field of optogenetics, optics and genetic targeting are combined to commandeer cellular functions, such as the neuronal action potential, by optically stimulating light-sensitive ion channels expressed in the cell membrane. One broadly applicable manifestation of this approach are covalently attached photochromic tethered ligands (PTLs) that allow activating ligand-gated ion channels with outstanding spatial and temporal resolution. Here, we describe all steps towards the successful development and application of PTL-gated ion channels in cell lines and primary cells. The basis for these experiments forms a combination of molecular modeling, genetic engineering, cell culture, and electrophysiology. The light-gated glutamate receptor (LiGluR), which consists of the PTL-functionalized GluK2 receptor, serves as a model. alternative_title: - MIMB author: - first_name: Stephanie full_name: Szobota, Stephanie last_name: Szobota - first_name: Catherine full_name: Mckenzie, Catherine id: 3EEDE19A-F248-11E8-B48F-1D18A9856A87 last_name: Mckenzie - first_name: Harald L full_name: Janovjak, Harald L id: 33BA6C30-F248-11E8-B48F-1D18A9856A87 last_name: Janovjak orcid: 0000-0002-8023-9315 citation: ama: Szobota S, Mckenzie C, Janovjak HL. Optical control of ligand-gated ion channels. Methods in Molecular Biology. 2013;998:417-435. doi:10.1007/978-1-62703-351-0_32 apa: Szobota, S., Mckenzie, C., & Janovjak, H. L. (2013). Optical control of ligand-gated ion channels. Methods in Molecular Biology. Springer. https://doi.org/10.1007/978-1-62703-351-0_32 chicago: Szobota, Stephanie, Catherine Mckenzie, and Harald L Janovjak. “Optical Control of Ligand-Gated Ion Channels.” Methods in Molecular Biology. Springer, 2013. https://doi.org/10.1007/978-1-62703-351-0_32. ieee: S. Szobota, C. Mckenzie, and H. L. Janovjak, “Optical control of ligand-gated ion channels,” Methods in Molecular Biology, vol. 998. Springer, pp. 417–435, 2013. ista: Szobota S, Mckenzie C, Janovjak HL. 2013. Optical control of ligand-gated ion channels. Methods in Molecular Biology. 998, 417–435. mla: Szobota, Stephanie, et al. “Optical Control of Ligand-Gated Ion Channels.” Methods in Molecular Biology, vol. 998, Springer, 2013, pp. 417–35, doi:10.1007/978-1-62703-351-0_32. short: S. Szobota, C. Mckenzie, H.L. Janovjak, Methods in Molecular Biology 998 (2013) 417–435. date_created: 2018-12-11T11:59:57Z date_published: 2013-02-22T00:00:00Z date_updated: 2021-01-12T07:00:17Z day: '22' ddc: - '570' department: - _id: HaJa doi: 10.1007/978-1-62703-351-0_32 ec_funded: 1 file: - access_level: open_access checksum: 1701f0d989f27ddac471b19a894ec0d1 content_type: application/pdf creator: system date_created: 2018-12-12T10:12:34Z date_updated: 2020-07-14T12:45:51Z file_id: '4952' file_name: IST-2017-834-v1+1_szobota.pdf file_size: 336734 relation: main_file file_date_updated: 2020-07-14T12:45:51Z has_accepted_license: '1' intvolume: ' 998' language: - iso: eng month: '02' oa: 1 oa_version: Submitted Version page: 417 - 435 project: - _id: 255BFFFA-B435-11E9-9278-68D0E5697425 grant_number: RGY0084/2012 name: In situ real-time imaging of neurotransmitter signaling using designer optical sensors (HFSP Young Investigator) - _id: 25548C20-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303564' name: Microbial Ion Channels for Synthetic Neurobiology publication: Methods in Molecular Biology publication_status: published publisher: Springer publist_id: '3932' pubrep_id: '834' quality_controlled: '1' scopus_import: 1 status: public title: Optical control of ligand-gated ion channels type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 998 year: '2013' ... --- _id: '2860' abstract: - lang: eng text: 'In the hippocampus, cell assemblies forming mnemonic representations of space are thought to arise as a result of changes in functional connections of pyramidal cells. We have found that CA1 interneuron circuits are also reconfigured during goal-oriented spatial learning through modification of inputs from pyramidal cells. As learning progressed, new pyramidal assemblies expressed in theta cycles alternated with previously established ones, and eventually overtook them. The firing patterns of interneurons developed a relationship to new, learning-related assemblies: some interneurons associated their activity with new pyramidal assemblies while some others dissociated from them. These firing associations were explained by changes in the weight of monosynaptic inputs received by interneurons from new pyramidal assemblies, as these predicted the associational changes. Spatial learning thus engages circuit modifications in the hippocampus that incorporate a redistribution of inhibitory activity that might assist in the segregation of competing pyramidal cell assembly patterns in space and time.' acknowledgement: D.D. and J.C. were supported by a MRC Intramural Programme Grant U138197111 author: - first_name: David full_name: Dupret, David last_name: Dupret - first_name: Joseph full_name: O'Neill, Joseph id: 426376DC-F248-11E8-B48F-1D18A9856A87 last_name: O'Neill - first_name: Jozsef L full_name: Csicsvari, Jozsef L id: 3FA14672-F248-11E8-B48F-1D18A9856A87 last_name: Csicsvari orcid: 0000-0002-5193-4036 citation: ama: Dupret D, O’Neill J, Csicsvari JL. Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron. 2013;78(1):166-180. doi:10.1016/j.neuron.2013.01.033 apa: Dupret, D., O’Neill, J., & Csicsvari, J. L. (2013). Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2013.01.033 chicago: Dupret, David, Joseph O’Neill, and Jozsef L Csicsvari. “Dynamic Reconfiguration of Hippocampal Interneuron Circuits during Spatial Learning.” Neuron. Elsevier, 2013. https://doi.org/10.1016/j.neuron.2013.01.033. ieee: D. Dupret, J. O’Neill, and J. L. Csicsvari, “Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning,” Neuron, vol. 78, no. 1. Elsevier, pp. 166–180, 2013. ista: Dupret D, O’Neill J, Csicsvari JL. 2013. Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron. 78(1), 166–180. mla: Dupret, David, et al. “Dynamic Reconfiguration of Hippocampal Interneuron Circuits during Spatial Learning.” Neuron, vol. 78, no. 1, Elsevier, 2013, pp. 166–80, doi:10.1016/j.neuron.2013.01.033. short: D. Dupret, J. O’Neill, J.L. Csicsvari, Neuron 78 (2013) 166–180. date_created: 2018-12-11T11:59:59Z date_published: 2013-03-21T00:00:00Z date_updated: 2021-01-12T07:00:19Z day: '21' ddc: - '570' department: - _id: JoCs doi: 10.1016/j.neuron.2013.01.033 ec_funded: 1 file: - access_level: open_access checksum: 0e18cb8561153ddb50bb5af16e7c9e97 content_type: application/pdf creator: dernst date_created: 2019-01-23T08:08:07Z date_updated: 2020-07-14T12:45:52Z file_id: '5877' file_name: 2013_Neuron_Dupret.pdf file_size: 2637837 relation: main_file file_date_updated: 2020-07-14T12:45:52Z has_accepted_license: '1' intvolume: ' 78' issue: '1' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '03' oa: 1 oa_version: Published Version page: 166 - 180 project: - _id: 257A4776-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '281511' name: Memory-related information processing in neuronal circuits of the hippocampus and entorhinal cortex publication: Neuron publication_status: published publisher: Elsevier publist_id: '3929' quality_controlled: '1' scopus_import: 1 status: public title: Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 78 year: '2013' ... --- _id: '2855' abstract: - lang: eng text: Genomic imprinting leads to preferred expression of either the maternal or paternal alleles of a subset of genes. Imprinting is essential for mammalian development, and its deregulation causes many diseases. However, the functional relevance of imprinting at the cellular level is poorly understood for most imprinted genes. We used mosaic analysis with double markers (MADM) in mice to create uniparental disomies (UPDs) and to visualize imprinting effects with single-cell resolution. Although chromosome 12 UPD did not produce detectable phenotypes, chromosome 7 UPD caused highly significant paternal growth dominance in the liver and lung, but not in the brain or heart. A single gene on chromosome 7, encoding the secreted insulin-like growth factor 2 (IGF2), accounts for most of the paternal dominance effect. Mosaic analyses implied additional imprinted loci on chromosome 7 acting cell autonomously to transmit the IGF2 signal. Our study reveals chromosome- and cell-type specificity of genomic imprinting effects. author: - first_name: Simon full_name: Hippenmeyer, Simon id: 37B36620-F248-11E8-B48F-1D18A9856A87 last_name: Hippenmeyer orcid: 0000-0003-2279-1061 - first_name: Randy full_name: Johnson, Randy last_name: Johnson - first_name: Liqun full_name: Luo, Liqun last_name: Luo citation: ama: Hippenmeyer S, Johnson R, Luo L. Mosaic analysis with double markers reveals cell type specific paternal growth dominance. Cell Reports. 2013;3(3):960-967. doi:10.1016/j.celrep.2013.02.002 apa: Hippenmeyer, S., Johnson, R., & Luo, L. (2013). Mosaic analysis with double markers reveals cell type specific paternal growth dominance. Cell Reports. Cell Press. https://doi.org/10.1016/j.celrep.2013.02.002 chicago: Hippenmeyer, Simon, Randy Johnson, and Liqun Luo. “Mosaic Analysis with Double Markers Reveals Cell Type Specific Paternal Growth Dominance.” Cell Reports. Cell Press, 2013. https://doi.org/10.1016/j.celrep.2013.02.002. ieee: S. Hippenmeyer, R. Johnson, and L. Luo, “Mosaic analysis with double markers reveals cell type specific paternal growth dominance,” Cell Reports, vol. 3, no. 3. Cell Press, pp. 960–967, 2013. ista: Hippenmeyer S, Johnson R, Luo L. 2013. Mosaic analysis with double markers reveals cell type specific paternal growth dominance. Cell Reports. 3(3), 960–967. mla: Hippenmeyer, Simon, et al. “Mosaic Analysis with Double Markers Reveals Cell Type Specific Paternal Growth Dominance.” Cell Reports, vol. 3, no. 3, Cell Press, 2013, pp. 960–67, doi:10.1016/j.celrep.2013.02.002. short: S. Hippenmeyer, R. Johnson, L. Luo, Cell Reports 3 (2013) 960–967. date_created: 2018-12-11T11:59:57Z date_published: 2013-03-28T00:00:00Z date_updated: 2021-01-12T07:00:16Z day: '28' ddc: - '570' department: - _id: SiHi doi: 10.1016/j.celrep.2013.02.002 file: - access_level: open_access checksum: 6e977b918e81384cd571ec5a9d812289 content_type: application/pdf creator: system date_created: 2018-12-12T10:17:20Z date_updated: 2020-07-14T12:45:51Z file_id: '5274' file_name: IST-2016-405-v1+1_1-s2.0-S2211124713000612-main.pdf file_size: 1907211 relation: main_file file_date_updated: 2020-07-14T12:45:51Z has_accepted_license: '1' intvolume: ' 3' issue: '3' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '03' oa: 1 oa_version: Published Version page: 960 - 967 publication: Cell Reports publication_status: published publisher: Cell Press publist_id: '3937' pubrep_id: '405' quality_controlled: '1' scopus_import: 1 status: public title: Mosaic analysis with double markers reveals cell type specific paternal growth dominance tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 3 year: '2013' ...