[{"acknowledgement":"CC BY 3.0","volume":369,"ddc":["570"],"doi":"10.1098/rstb.2012.0528","day":"05","abstract":[{"lang":"eng","text":"Sharp wave/ripple (SWR, 150–250 Hz) hippocampal events have long been postulated to be involved in memory consolidation. However, more recent work has investigated SWRs that occur during active waking behaviour: findings that suggest that SWRs may also play a role in cell assembly strengthening or spatial working memory. Do such theories of SWR function apply to animal learning? This review discusses how general theories linking SWRs to memory-related function may explain circuit mechanisms related to rodent spatial learning and to the associated stabilization of new cognitive maps."}],"date_updated":"2021-01-12T06:56:18Z","year":"2014","citation":{"ieee":"J. L. Csicsvari and D. Dupret, “Sharp wave/ripple network oscillations and learning-associated hippocampal maps,” <i>Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences</i>, vol. 369, no. 1635. Royal Society, The, 2014.","chicago":"Csicsvari, Jozsef L, and David Dupret. “Sharp Wave/Ripple Network Oscillations and Learning-Associated Hippocampal Maps.” <i>Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences</i>. Royal Society, The, 2014. <a href=\"https://doi.org/10.1098/rstb.2012.0528\">https://doi.org/10.1098/rstb.2012.0528</a>.","apa":"Csicsvari, J. L., &#38; Dupret, D. (2014). Sharp wave/ripple network oscillations and learning-associated hippocampal maps. <i>Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences</i>. Royal Society, The. <a href=\"https://doi.org/10.1098/rstb.2012.0528\">https://doi.org/10.1098/rstb.2012.0528</a>","ama":"Csicsvari JL, Dupret D. Sharp wave/ripple network oscillations and learning-associated hippocampal maps. <i>Philosophical Transactions of the Royal Society of London Series B, Biological Sciences</i>. 2014;369(1635). doi:<a href=\"https://doi.org/10.1098/rstb.2012.0528\">10.1098/rstb.2012.0528</a>","ista":"Csicsvari JL, Dupret D. 2014. Sharp wave/ripple network oscillations and learning-associated hippocampal maps. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 369(1635), 20120528.","mla":"Csicsvari, Jozsef L., and David Dupret. “Sharp Wave/Ripple Network Oscillations and Learning-Associated Hippocampal Maps.” <i>Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences</i>, vol. 369, no. 1635, 20120528, Royal Society, The, 2014, doi:<a href=\"https://doi.org/10.1098/rstb.2012.0528\">10.1098/rstb.2012.0528</a>.","short":"J.L. Csicsvari, D. Dupret, Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 369 (2014)."},"external_id":{"pmid":["24366138"]},"publisher":"Royal Society, The","quality_controlled":"1","file_date_updated":"2020-07-14T12:45:34Z","publication_status":"published","date_created":"2018-12-11T11:56:34Z","article_processing_charge":"No","department":[{"_id":"JoCs"}],"title":"Sharp wave/ripple network oscillations and learning-associated hippocampal maps","pubrep_id":"527","intvolume":"       369","pmid":1,"_id":"2251","scopus_import":1,"author":[{"full_name":"Csicsvari, Jozsef L","orcid":"0000-0002-5193-4036","last_name":"Csicsvari","first_name":"Jozsef L","id":"3FA14672-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Dupret","first_name":"David","full_name":"Dupret, David"}],"issue":"1635","file":[{"checksum":"51beb33de71c9c19e0c205a20d206f9a","file_size":771896,"date_created":"2018-12-12T10:13:24Z","content_type":"application/pdf","file_name":"IST-2016-527-v1+1_20120528.full.pdf","date_updated":"2020-07-14T12:45:34Z","relation":"main_file","access_level":"open_access","creator":"system","file_id":"5006"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","publication_identifier":{"issn":["09628436"]},"oa":1,"publist_id":"4697","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"date_published":"2014-02-05T00:00:00Z","type":"journal_article","language":[{"iso":"eng"}],"oa_version":"Published Version","month":"02","article_number":"20120528","publication":"Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences","has_accepted_license":"1"},{"date_published":"2014-11-14T00:00:00Z","type":"research_data_reference","date_updated":"2023-02-23T10:24:07Z","citation":{"mla":"Lovrics, Anna, et al. <i>Transition Probability between TF Expression States When Dbx2 Inhibits Nkx2.2</i>. Public Library of Science, 2014, doi:<a href=\"https://doi.org/10.1371/journal.pone.0111430.s006\">10.1371/journal.pone.0111430.s006</a>.","short":"A. Lovrics, Y. Gao, B. Juhász, I. Bock, H.M. Byrne, A. Dinnyés, K. Kovács, (2014).","ista":"Lovrics A, Gao Y, Juhász B, Bock I, Byrne HM, Dinnyés A, Kovács K. 2014. Transition probability between TF expression states when Dbx2 inhibits Nkx2.2, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pone.0111430.s006\">10.1371/journal.pone.0111430.s006</a>.","apa":"Lovrics, A., Gao, Y., Juhász, B., Bock, I., Byrne, H. M., Dinnyés, A., &#38; Kovács, K. (2014). Transition probability between TF expression states when Dbx2 inhibits Nkx2.2. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pone.0111430.s006\">https://doi.org/10.1371/journal.pone.0111430.s006</a>","ama":"Lovrics A, Gao Y, Juhász B, et al. Transition probability between TF expression states when Dbx2 inhibits Nkx2.2. 2014. doi:<a href=\"https://doi.org/10.1371/journal.pone.0111430.s006\">10.1371/journal.pone.0111430.s006</a>","chicago":"Lovrics, Anna, Yu Gao, Bianka Juhász, István Bock, Helen M. Byrne, András Dinnyés, and Krisztián Kovács. “Transition Probability between TF Expression States When Dbx2 Inhibits Nkx2.2.” Public Library of Science, 2014. <a href=\"https://doi.org/10.1371/journal.pone.0111430.s006\">https://doi.org/10.1371/journal.pone.0111430.s006</a>.","ieee":"A. Lovrics <i>et al.</i>, “Transition probability between TF expression states when Dbx2 inhibits Nkx2.2.” Public Library of Science, 2014."},"year":"2014","doi":"10.1371/journal.pone.0111430.s006","day":"14","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"2004"}]},"status":"public","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"last_name":"Lovrics","first_name":"Anna","full_name":"Lovrics, Anna"},{"last_name":"Gao","first_name":"Yu","full_name":"Gao, Yu"},{"full_name":"Juhász, Bianka","last_name":"Juhász","first_name":"Bianka"},{"full_name":"Bock, István","last_name":"Bock","first_name":"István"},{"full_name":"Byrne, Helen M.","last_name":"Byrne","first_name":"Helen M."},{"first_name":"András","last_name":"Dinnyés","full_name":"Dinnyés, András"},{"full_name":"Kovács, Krisztián","first_name":"Krisztián","last_name":"Kovács","id":"2AB5821E-F248-11E8-B48F-1D18A9856A87"}],"_id":"9722","month":"11","title":"Transition probability between TF expression states when Dbx2 inhibits Nkx2.2","oa_version":"Published Version","department":[{"_id":"JoCs"}],"date_created":"2021-07-26T14:35:00Z","article_processing_charge":"No","publisher":"Public Library of Science"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","volume":23,"abstract":[{"lang":"eng","text":"It is known that the entorhinal cortex plays a crucial role in spatial cognition in rodents. Neuroanatomical and electrophysiological data suggest that there is a functional distinction between 2 subregions within the entorhinal cortex, the medial entorhinal cortex (MEC), and the lateral entorhinal cortex (LEC). Rats with MEC or LEC lesions were trained in 2 navigation tasks requiring allothetic (water maze task) or idiothetic (path integration) information processing and 2-object exploration tasks allowing testing of spatial and nonspatial processing of intramaze objects. MEC lesions mildly affected place navigation in the water maze and produced a path integration deficit. They also altered the processing of spatial information in both exploration tasks while sparing the processing of nonspatial information. LEC lesions did not affect navigation abilities in both the water maze and the path integration tasks. They altered spatial and nonspatial processing in the object exploration task but not in the one-trial recognition task. Overall, these results indicate that the MEC is important for spatial processing and path integration. The LEC has some influence on both spatial and nonspatial processes, suggesting that the 2 kinds of information interact at the level of the EC."}],"publist_id":"3958","doi":"10.1093/cercor/bhs033","day":"01","date_published":"2013-02-01T00:00:00Z","type":"journal_article","date_updated":"2021-01-12T07:00:08Z","citation":{"ieee":"T. Van Cauter, J. Camon, A. Alvernhe, C. Elduayen, F. Sargolini, and É. Save, “Distinct roles of medial and lateral entorhinal cortex in spatial cognition,” <i>Cerebral Cortex</i>, vol. 23, no. 2. Oxford University Press, pp. 451–459, 2013.","chicago":"Van Cauter, Tiffany, Jeremy Camon, Alice Alvernhe, Coralie Elduayen, Francesca Sargolini, and Étienne Save. “Distinct Roles of Medial and Lateral Entorhinal Cortex in Spatial Cognition.” <i>Cerebral Cortex</i>. Oxford University Press, 2013. <a href=\"https://doi.org/10.1093/cercor/bhs033\">https://doi.org/10.1093/cercor/bhs033</a>.","apa":"Van Cauter, T., Camon, J., Alvernhe, A., Elduayen, C., Sargolini, F., &#38; Save, É. (2013). Distinct roles of medial and lateral entorhinal cortex in spatial cognition. <i>Cerebral Cortex</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/cercor/bhs033\">https://doi.org/10.1093/cercor/bhs033</a>","ama":"Van Cauter T, Camon J, Alvernhe A, Elduayen C, Sargolini F, Save É. Distinct roles of medial and lateral entorhinal cortex in spatial cognition. <i>Cerebral Cortex</i>. 2013;23(2):451-459. doi:<a href=\"https://doi.org/10.1093/cercor/bhs033\">10.1093/cercor/bhs033</a>","ista":"Van Cauter T, Camon J, Alvernhe A, Elduayen C, Sargolini F, Save É. 2013. Distinct roles of medial and lateral entorhinal cortex in spatial cognition. Cerebral Cortex. 23(2), 451–459.","mla":"Van Cauter, Tiffany, et al. “Distinct Roles of Medial and Lateral Entorhinal Cortex in Spatial Cognition.” <i>Cerebral Cortex</i>, vol. 23, no. 2, Oxford University Press, 2013, pp. 451–59, doi:<a href=\"https://doi.org/10.1093/cercor/bhs033\">10.1093/cercor/bhs033</a>.","short":"T. Van Cauter, J. Camon, A. Alvernhe, C. Elduayen, F. Sargolini, É. Save, Cerebral Cortex 23 (2013) 451–459."},"year":"2013","publisher":"Oxford University Press","language":[{"iso":"eng"}],"page":"451 - 459","quality_controlled":"1","month":"02","title":"Distinct roles of medial and lateral entorhinal cortex in spatial cognition","intvolume":"        23","oa_version":"None","publication_status":"published","date_created":"2018-12-11T11:59:52Z","department":[{"_id":"JoCs"}],"author":[{"last_name":"Van Cauter","first_name":"Tiffany","full_name":"Van Cauter, Tiffany"},{"full_name":"Camon, Jeremy","last_name":"Camon","first_name":"Jeremy"},{"full_name":"Alvernhe, Alice","last_name":"Alvernhe","first_name":"Alice","id":"467FB3D4-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Coralie","last_name":"Elduayen","full_name":"Elduayen, Coralie"},{"full_name":"Sargolini, Francesca","last_name":"Sargolini","first_name":"Francesca"},{"full_name":"Save, Étienne","first_name":"Étienne","last_name":"Save"}],"issue":"2","_id":"2840","publication":"Cerebral Cortex","scopus_import":1},{"publist_id":"3949","abstract":[{"lang":"eng","text":"At synapses formed between dissociated neurons, about half of all synaptic vesicles are refractory to evoked release, forming the so-called &quot;resting pool.&quot; Here, we use optical measurements of vesicular pH to study developmental changes in pool partitioning and vesicle cycling in cultured hippocampal slices. Two-photon imaging of a genetically encoded two-color release sensor (ratio-sypHy) allowed us to perform calibrated measurements at individual Schaffer collateral boutons. Mature boutons released a large fraction of their vesicles during simulated place field activity, and vesicle retrieval rates were 7-fold higher compared to immature boutons. Saturating stimulation mobilized essentially all vesicles at mature synapses. Resting pool formation and a concomitant reduction in evoked release was induced by chronic depolarization but not by acute inhibition of the protein phosphatase calcineurin. We conclude that synapses in CA1 undergo a prominent refinement of vesicle use during early postnatal development that is not recapitulated in dissociated neuronal culture."}],"day":"20","doi":"10.1016/j.neuron.2013.01.021","type":"journal_article","date_published":"2013-03-20T00:00:00Z","citation":{"ista":"Rose T, Schönenberger P, Jezek K, Oertner T. 2013. Developmental refinement of vesicle cycling at Schaffer collateral synapses. Neuron. 77(6), 1109–1121.","mla":"Rose, Tobias, et al. “Developmental Refinement of Vesicle Cycling at Schaffer Collateral Synapses.” <i>Neuron</i>, vol. 77, no. 6, Elsevier, 2013, pp. 1109–21, doi:<a href=\"https://doi.org/10.1016/j.neuron.2013.01.021\">10.1016/j.neuron.2013.01.021</a>.","short":"T. Rose, P. Schönenberger, K. Jezek, T. Oertner, Neuron 77 (2013) 1109–1121.","chicago":"Rose, Tobias, Philipp Schönenberger, Karel Jezek, and Thomas Oertner. “Developmental Refinement of Vesicle Cycling at Schaffer Collateral Synapses.” <i>Neuron</i>. Elsevier, 2013. <a href=\"https://doi.org/10.1016/j.neuron.2013.01.021\">https://doi.org/10.1016/j.neuron.2013.01.021</a>.","ieee":"T. Rose, P. Schönenberger, K. Jezek, and T. Oertner, “Developmental refinement of vesicle cycling at Schaffer collateral synapses,” <i>Neuron</i>, vol. 77, no. 6. Elsevier, pp. 1109–1121, 2013.","ama":"Rose T, Schönenberger P, Jezek K, Oertner T. Developmental refinement of vesicle cycling at Schaffer collateral synapses. <i>Neuron</i>. 2013;77(6):1109-1121. doi:<a href=\"https://doi.org/10.1016/j.neuron.2013.01.021\">10.1016/j.neuron.2013.01.021</a>","apa":"Rose, T., Schönenberger, P., Jezek, K., &#38; Oertner, T. (2013). Developmental refinement of vesicle cycling at Schaffer collateral synapses. <i>Neuron</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.neuron.2013.01.021\">https://doi.org/10.1016/j.neuron.2013.01.021</a>"},"year":"2013","date_updated":"2021-01-12T07:00:11Z","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":77,"intvolume":"        77","title":"Developmental refinement of vesicle cycling at Schaffer collateral synapses","month":"03","department":[{"_id":"JoCs"}],"date_created":"2018-12-11T11:59:54Z","publication_status":"published","oa_version":"None","issue":"6","author":[{"full_name":"Rose, Tobias","first_name":"Tobias","last_name":"Rose"},{"id":"3B9D816C-F248-11E8-B48F-1D18A9856A87","first_name":"Philipp","last_name":"Schönenberger","full_name":"Schönenberger, Philipp"},{"full_name":"Jezek, Karel","last_name":"Jezek","first_name":"Karel"},{"full_name":"Oertner, Thomas","last_name":"Oertner","first_name":"Thomas"}],"scopus_import":1,"_id":"2845","publication":"Neuron","publisher":"Elsevier","language":[{"iso":"eng"}],"quality_controlled":"1","page":"1109 - 1121"},{"language":[{"iso":"eng"}],"month":"03","oa_version":"Published Version","project":[{"grant_number":"281511","name":"Memory-related information processing in neuronal circuits of the hippocampus and entorhinal cortex","call_identifier":"FP7","_id":"257A4776-B435-11E9-9278-68D0E5697425"}],"publication":"Neuron","has_accepted_license":"1","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"access_level":"open_access","relation":"main_file","file_id":"5877","creator":"dernst","date_created":"2019-01-23T08:08:07Z","file_size":2637837,"checksum":"0e18cb8561153ddb50bb5af16e7c9e97","date_updated":"2020-07-14T12:45:52Z","content_type":"application/pdf","file_name":"2013_Neuron_Dupret.pdf"}],"oa":1,"publist_id":"3929","date_published":"2013-03-21T00:00:00Z","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"publisher":"Elsevier","file_date_updated":"2020-07-14T12:45:52Z","page":"166 - 180","ec_funded":1,"quality_controlled":"1","title":"Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning","intvolume":"        78","publication_status":"published","date_created":"2018-12-11T11:59:59Z","department":[{"_id":"JoCs"}],"author":[{"full_name":"Dupret, David","first_name":"David","last_name":"Dupret"},{"id":"426376DC-F248-11E8-B48F-1D18A9856A87","full_name":"O'Neill, Joseph","last_name":"O'Neill","first_name":"Joseph"},{"id":"3FA14672-F248-11E8-B48F-1D18A9856A87","last_name":"Csicsvari","first_name":"Jozsef L","full_name":"Csicsvari, Jozsef L","orcid":"0000-0002-5193-4036"}],"issue":"1","_id":"2860","scopus_import":1,"ddc":["570"],"acknowledgement":"D.D. and J.C. were supported by a MRC Intramural Programme Grant U138197111","volume":78,"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."}],"doi":"10.1016/j.neuron.2013.01.033","day":"21","date_updated":"2021-01-12T07:00:19Z","citation":{"short":"D. Dupret, J. O’Neill, J.L. Csicsvari, Neuron 78 (2013) 166–180.","mla":"Dupret, David, et al. “Dynamic Reconfiguration of Hippocampal Interneuron Circuits during Spatial Learning.” <i>Neuron</i>, vol. 78, no. 1, Elsevier, 2013, pp. 166–80, doi:<a href=\"https://doi.org/10.1016/j.neuron.2013.01.033\">10.1016/j.neuron.2013.01.033</a>.","ista":"Dupret D, O’Neill J, Csicsvari JL. 2013. Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron. 78(1), 166–180.","apa":"Dupret, D., O’Neill, J., &#38; Csicsvari, J. L. (2013). Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. <i>Neuron</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.neuron.2013.01.033\">https://doi.org/10.1016/j.neuron.2013.01.033</a>","ama":"Dupret D, O’Neill J, Csicsvari JL. Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. <i>Neuron</i>. 2013;78(1):166-180. doi:<a href=\"https://doi.org/10.1016/j.neuron.2013.01.033\">10.1016/j.neuron.2013.01.033</a>","ieee":"D. Dupret, J. O’Neill, and J. L. Csicsvari, “Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning,” <i>Neuron</i>, vol. 78, no. 1. Elsevier, pp. 166–180, 2013.","chicago":"Dupret, David, Joseph O’Neill, and Jozsef L Csicsvari. “Dynamic Reconfiguration of Hippocampal Interneuron Circuits during Spatial Learning.” <i>Neuron</i>. Elsevier, 2013. <a href=\"https://doi.org/10.1016/j.neuron.2013.01.033\">https://doi.org/10.1016/j.neuron.2013.01.033</a>."},"year":"2013"},{"main_file_link":[{"url":"http://arxiv.org/abs/1310.1771","open_access":"1"}],"status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2021-01-12T06:56:28Z","citation":{"apa":"Gridchyn, I., &#38; Kolmogorov, V. (2013). Potts model, parametric maxflow and k-submodular functions (pp. 2320–2327). Presented at the ICCV: International Conference on Computer Vision, Sydney, Australia: IEEE. <a href=\"https://doi.org/10.1109/ICCV.2013.288\">https://doi.org/10.1109/ICCV.2013.288</a>","ama":"Gridchyn I, Kolmogorov V. Potts model, parametric maxflow and k-submodular functions. In: IEEE; 2013:2320-2327. doi:<a href=\"https://doi.org/10.1109/ICCV.2013.288\">10.1109/ICCV.2013.288</a>","ieee":"I. Gridchyn and V. Kolmogorov, “Potts model, parametric maxflow and k-submodular functions,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013, pp. 2320–2327.","chicago":"Gridchyn, Igor, and Vladimir Kolmogorov. “Potts Model, Parametric Maxflow and k-Submodular Functions,” 2320–27. IEEE, 2013. <a href=\"https://doi.org/10.1109/ICCV.2013.288\">https://doi.org/10.1109/ICCV.2013.288</a>.","mla":"Gridchyn, Igor, and Vladimir Kolmogorov. <i>Potts Model, Parametric Maxflow and k-Submodular Functions</i>. IEEE, 2013, pp. 2320–27, doi:<a href=\"https://doi.org/10.1109/ICCV.2013.288\">10.1109/ICCV.2013.288</a>.","short":"I. Gridchyn, V. Kolmogorov, in:, IEEE, 2013, pp. 2320–2327.","ista":"Gridchyn I, Kolmogorov V. 2013. Potts model, parametric maxflow and k-submodular functions. ICCV: International Conference on Computer Vision, 2320–2327."},"year":"2013","date_published":"2013-12-01T00:00:00Z","type":"conference","external_id":{"arxiv":["1310.1771"]},"arxiv":1,"doi":"10.1109/ICCV.2013.288","day":"01","abstract":[{"lang":"eng","text":"The problem of minimizing the Potts energy function frequently occurs in computer vision applications. One way to tackle this NP-hard problem was proposed by Kovtun [19, 20]. It identifies a part of an optimal solution by running k maxflow computations, where k is the number of labels. The number of “labeled” pixels can be significant in some applications, e.g. 50-93% in our tests for stereo. We show how to reduce the runtime to O (log k) maxflow computations (or one parametric maxflow computation). Furthermore, the output of our algorithm allows to speed-up the subsequent alpha expansion for the unlabeled part, or can be used as it is for time-critical applications. To derive our technique, we generalize the algorithm of Felzenszwalb et al. [7] for Tree Metrics . We also show a connection to k-submodular functions from combinatorial optimization, and discuss k-submodular relaxations for general energy functions."}],"publist_id":"4668","oa":1,"page":"2320 - 2327","quality_controlled":"1","language":[{"iso":"eng"}],"publisher":"IEEE","conference":{"start_date":"2013-12-01","name":"ICCV: International Conference on Computer Vision","end_date":"2013-12-08","location":"Sydney, Australia"},"_id":"2276","author":[{"full_name":"Gridchyn, Igor","first_name":"Igor","last_name":"Gridchyn","id":"4B60654C-F248-11E8-B48F-1D18A9856A87"},{"id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","full_name":"Kolmogorov, Vladimir","first_name":"Vladimir","last_name":"Kolmogorov"}],"publication_status":"published","oa_version":"Preprint","department":[{"_id":"JoCs"},{"_id":"VlKo"}],"date_created":"2018-12-11T11:56:43Z","title":"Potts model, parametric maxflow and k-submodular functions","month":"12"},{"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"date_published":"2013-12-27T00:00:00Z","type":"journal_article","publist_id":"7346","oa":1,"file":[{"relation":"main_file","access_level":"open_access","creator":"system","file_id":"5128","file_size":530134,"checksum":"cd7183121e56251176100ccac165c95c","date_created":"2018-12-12T10:15:10Z","file_name":"IST-2018-953-v1+1_2013_Dickerson_Aberrant_neural.pdf","content_type":"application/pdf","date_updated":"2020-07-14T12:46:35Z"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","publication":"Frontiers in Behavioral Neuroscience","has_accepted_license":"1","oa_version":"Published Version","month":"12","language":[{"iso":"eng"}],"date_updated":"2021-01-12T08:00:53Z","year":"2013","citation":{"ista":"Dickerson D, Bilkey D. 2013. Aberrant neural synchrony in the maternal immune activation model: Using translatable measures to explore targeted interventions. Frontiers in Behavioral Neuroscience. 7(DEC).","short":"D. Dickerson, D. Bilkey, Frontiers in Behavioral Neuroscience 7 (2013).","mla":"Dickerson, Desiree, and David Bilkey. “Aberrant Neural Synchrony in the Maternal Immune Activation Model: Using Translatable Measures to Explore Targeted Interventions.” <i>Frontiers in Behavioral Neuroscience</i>, vol. 7, no. DEC, Frontiers Research Foundation, 2013, doi:<a href=\"https://doi.org/10.3389/fnbeh.2013.00217\">10.3389/fnbeh.2013.00217</a>.","chicago":"Dickerson, Desiree, and David Bilkey. “Aberrant Neural Synchrony in the Maternal Immune Activation Model: Using Translatable Measures to Explore Targeted Interventions.” <i>Frontiers in Behavioral Neuroscience</i>. Frontiers Research Foundation, 2013. <a href=\"https://doi.org/10.3389/fnbeh.2013.00217\">https://doi.org/10.3389/fnbeh.2013.00217</a>.","ieee":"D. Dickerson and D. Bilkey, “Aberrant neural synchrony in the maternal immune activation model: Using translatable measures to explore targeted interventions,” <i>Frontiers in Behavioral Neuroscience</i>, vol. 7, no. DEC. Frontiers Research Foundation, 2013.","ama":"Dickerson D, Bilkey D. Aberrant neural synchrony in the maternal immune activation model: Using translatable measures to explore targeted interventions. <i>Frontiers in Behavioral Neuroscience</i>. 2013;7(DEC). doi:<a href=\"https://doi.org/10.3389/fnbeh.2013.00217\">10.3389/fnbeh.2013.00217</a>","apa":"Dickerson, D., &#38; Bilkey, D. (2013). Aberrant neural synchrony in the maternal immune activation model: Using translatable measures to explore targeted interventions. <i>Frontiers in Behavioral Neuroscience</i>. Frontiers Research Foundation. <a href=\"https://doi.org/10.3389/fnbeh.2013.00217\">https://doi.org/10.3389/fnbeh.2013.00217</a>"},"doi":"10.3389/fnbeh.2013.00217","day":"27","abstract":[{"text":"Maternal exposure to infection occurring mid-gestation produces a three-fold increase in the risk of schizophrenia in the offspring. The critical initiating factor appears to be the maternal immune activation (MIA) that follows infection. This process can be induced in rodents by exposure of pregnant dams to the viral mimic Poly I:C, which triggers an immune response that results in structural, functional, behavioral, and electrophysiological phenotypes in the adult offspring that model those seen in schizophrenia. We used this model to explore the role of synchronization in brain neural networks, a process thought to be dysfunctional in schizophrenia and previously associated with positive, negative, and cognitive symptoms of schizophrenia. Exposure of pregnant dams to Poly I:C on GD15 produced an impairment in long-range neural synchrony in adult offspring between two regions implicated in schizophrenia pathology; the hippocampus and the medial prefrontal cortex (mPFC). This reduction in synchrony was ameliorated by acute doses of the antipsychotic clozapine. MIA animals have previously been shown to have impaired pre-pulse inhibition (PPI), a gold-standard measure of schizophrenia-like deficits in animal models. Our data showed that deficits in synchrony were positively correlated with the impairments in PPI. Subsequent analysis of LFP activity during the PPI response also showed that reduced coupling between the mPFC and the hippocampus following processing of the pre-pulse was associated with reduced PPI. The ability of the MIA intervention to model neurodevelopmental aspects of schizophrenia pathology provides a useful platform from which to investigate the ontogeny of aberrant synchronous processes. Further, the way in which the model expresses translatable deficits such as aberrant synchrony and reduced PPI will allow researchers to explore novel intervention strategies targeted to these changes. ","lang":"eng"}],"volume":7,"ddc":["571"],"_id":"476","author":[{"last_name":"Dickerson","first_name":"Desiree","full_name":"Dickerson, Desiree","id":"444EB89E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Bilkey, David","first_name":"David","last_name":"Bilkey"}],"issue":"DEC","publication_status":"published","date_created":"2018-12-11T11:46:41Z","department":[{"_id":"JoCs"}],"title":"Aberrant neural synchrony in the maternal immune activation model: Using translatable measures to explore targeted interventions","pubrep_id":"953","intvolume":"         7","quality_controlled":"1","file_date_updated":"2020-07-14T12:46:35Z","publisher":"Frontiers Research Foundation"},{"date_created":"2018-12-11T12:00:30Z","department":[{"_id":"JoCs"}],"publication_status":"published","oa_version":"None","intvolume":"        15","title":"The medial entorhinal cortex keeps Up","month":"11","scopus_import":1,"publication":"Nature Neuroscience","_id":"2949","issue":"11","author":[{"full_name":"Dupret, David","last_name":"Dupret","first_name":"David"},{"id":"3FA14672-F248-11E8-B48F-1D18A9856A87","last_name":"Csicsvari","first_name":"Jozsef L","full_name":"Csicsvari, Jozsef L","orcid":"0000-0002-5193-4036"}],"publisher":"Nature Publishing Group","quality_controlled":"1","page":"1471 - 1472","language":[{"iso":"eng"}],"day":"01","doi":"10.1038/nn.3245","publist_id":"3782","citation":{"ama":"Dupret D, Csicsvari JL. The medial entorhinal cortex keeps Up. <i>Nature Neuroscience</i>. 2012;15(11):1471-1472. doi:<a href=\"https://doi.org/10.1038/nn.3245\">10.1038/nn.3245</a>","apa":"Dupret, D., &#38; Csicsvari, J. L. (2012). The medial entorhinal cortex keeps Up. <i>Nature Neuroscience</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/nn.3245\">https://doi.org/10.1038/nn.3245</a>","chicago":"Dupret, David, and Jozsef L Csicsvari. “The Medial Entorhinal Cortex Keeps Up.” <i>Nature Neuroscience</i>. Nature Publishing Group, 2012. <a href=\"https://doi.org/10.1038/nn.3245\">https://doi.org/10.1038/nn.3245</a>.","ieee":"D. Dupret and J. L. Csicsvari, “The medial entorhinal cortex keeps Up,” <i>Nature Neuroscience</i>, vol. 15, no. 11. Nature Publishing Group, pp. 1471–1472, 2012.","mla":"Dupret, David, and Jozsef L. Csicsvari. “The Medial Entorhinal Cortex Keeps Up.” <i>Nature Neuroscience</i>, vol. 15, no. 11, Nature Publishing Group, 2012, pp. 1471–72, doi:<a href=\"https://doi.org/10.1038/nn.3245\">10.1038/nn.3245</a>.","short":"D. Dupret, J.L. Csicsvari, Nature Neuroscience 15 (2012) 1471–1472.","ista":"Dupret D, Csicsvari JL. 2012. The medial entorhinal cortex keeps Up. Nature Neuroscience. 15(11), 1471–1472."},"year":"2012","date_updated":"2021-01-12T07:39:59Z","type":"journal_article","date_published":"2012-11-01T00:00:00Z","main_file_link":[{"url":"http://www.mrcbndu.ox.ac.uk/publications/medial-entorhinal-cortex-keeps"}],"volume":15,"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","status":"public"},{"abstract":[{"lang":"eng","text":"The activity of hippocampal pyramidal cells reflects both the current position of the animal and information related to its current behavior. Here we investigated whether single hippocampal neurons can encode several independent features defining trials during a memory task. We also tested whether task-related information is represented by partial remapping of the place cell population or, instead, via firing rate modulation of spatially stable place cells. To address these two questions, the activity of hippocampal neurons was recorded in rats performing a conditional discrimination task on a modified T-maze in which the identity of a food reward guided behavior. When the rat was on the central arm of the maze, the firing rate of pyramidal cells changed depending on two independent factors: (1) the identity of the food reward given to the animal and (2) the previous location of the animal on the maze. Importantly, some pyramidal cells encoded information relative to both factors. This trial-type specific and retrospective coding did not interfere with the spatial representation of the maze: hippocampal cells had stable place fields and their theta-phase precession profiles were unaltered during the task, indicating that trial-related information was encoded via rate remapping. During error trials, encoding of both trial-related information and spatial location was impaired. Finally, we found that pyramidal cells also encode trial-related information via rate remapping during the continuous version of the rewarded alternation task without delays. These results suggest that hippocampal neurons can encode several task-related cognitive aspects via rate remapping."}],"doi":"10.1523/JNEUROSCI.6175-11.2012","day":"17","external_id":{"pmid":["23077060"]},"date_updated":"2021-01-12T07:40:03Z","citation":{"short":"K. Allen, J.N. Rawlins, D. Bannerman, J.L. Csicsvari, Journal of Neuroscience 32 (2012) 14752–14766.","mla":"Allen, Kevin, et al. “Hippocampal Place Cells Can Encode Multiple Trial-Dependent Features through Rate Remapping.” <i>Journal of Neuroscience</i>, vol. 32, no. 42, Society for Neuroscience, 2012, pp. 14752–66, doi:<a href=\"https://doi.org/10.1523/JNEUROSCI.6175-11.2012\">10.1523/JNEUROSCI.6175-11.2012</a>.","ista":"Allen K, Rawlins JN, Bannerman D, Csicsvari JL. 2012. Hippocampal place cells can encode multiple trial-dependent features through rate remapping. Journal of Neuroscience. 32(42), 14752–14766.","ama":"Allen K, Rawlins JN, Bannerman D, Csicsvari JL. Hippocampal place cells can encode multiple trial-dependent features through rate remapping. <i>Journal of Neuroscience</i>. 2012;32(42):14752-14766. doi:<a href=\"https://doi.org/10.1523/JNEUROSCI.6175-11.2012\">10.1523/JNEUROSCI.6175-11.2012</a>","apa":"Allen, K., Rawlins, J. N., Bannerman, D., &#38; Csicsvari, J. L. (2012). Hippocampal place cells can encode multiple trial-dependent features through rate remapping. <i>Journal of Neuroscience</i>. Society for Neuroscience. <a href=\"https://doi.org/10.1523/JNEUROSCI.6175-11.2012\">https://doi.org/10.1523/JNEUROSCI.6175-11.2012</a>","chicago":"Allen, Kevin, J Nick Rawlins, David Bannerman, and Jozsef L Csicsvari. “Hippocampal Place Cells Can Encode Multiple Trial-Dependent Features through Rate Remapping.” <i>Journal of Neuroscience</i>. Society for Neuroscience, 2012. <a href=\"https://doi.org/10.1523/JNEUROSCI.6175-11.2012\">https://doi.org/10.1523/JNEUROSCI.6175-11.2012</a>.","ieee":"K. Allen, J. N. Rawlins, D. Bannerman, and J. L. Csicsvari, “Hippocampal place cells can encode multiple trial-dependent features through rate remapping,” <i>Journal of Neuroscience</i>, vol. 32, no. 42. Society for Neuroscience, pp. 14752–14766, 2012."},"year":"2012","acknowledgement":"J.C. was supported by a MRC Intramural Programme Grant (U138197111) and a European Research Council Starter Grant (281511). K.A. held a Wellcome Trust PhD studentship and a Humboldt Research Fellowship for Postdoctoral Researchers. D.M.B. was supported by Wellcome Trust Senior Fellowships (074385 and 087736).","volume":32,"title":"Hippocampal place cells can encode multiple trial-dependent features through rate remapping","intvolume":"        32","publication_status":"published","department":[{"_id":"JoCs"}],"date_created":"2018-12-11T12:00:33Z","author":[{"full_name":"Allen, Kevin","first_name":"Kevin","last_name":"Allen"},{"full_name":"Rawlins, J Nick","first_name":"J Nick","last_name":"Rawlins"},{"first_name":"David","last_name":"Bannerman","full_name":"Bannerman, David"},{"last_name":"Csicsvari","first_name":"Jozsef L","full_name":"Csicsvari, Jozsef L","orcid":"0000-0002-5193-4036","id":"3FA14672-F248-11E8-B48F-1D18A9856A87"}],"issue":"42","pmid":1,"_id":"2958","scopus_import":1,"publisher":"Society for Neuroscience","page":"14752 - 14766","quality_controlled":"1","ec_funded":1,"publist_id":"3768","oa":1,"date_published":"2012-10-17T00:00:00Z","type":"journal_article","status":"public","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531717/","open_access":"1"}],"month":"10","oa_version":"Submitted Version","project":[{"call_identifier":"FP7","_id":"257A4776-B435-11E9-9278-68D0E5697425","name":"Memory-related information processing in neuronal circuits of the hippocampus and entorhinal cortex","grant_number":"281511"}],"publication":"Journal of Neuroscience","language":[{"iso":"eng"}]}]