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001     809498
005     20240313095004.0
037 _ _ |a FZJ-2016-02592
041 _ _ |a English
100 1 _ |a Rostami, Vahid
|0 P:(DE-Juel1)156383
|b 0
|e Corresponding author
|u fzj
111 2 _ |a 9th Bernstein Sparks Workshop
|c Göttingen
|d 2016-05-25 - 2016-05-27
|w Germany
245 _ _ |a Pairwise maximum-entropy models: bimodality, bistability, non-ergodicityproblems, and their elimination via inhibition
260 _ _ |c 2016
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a conferenceObject
|2 DRIVER
336 7 _ |a CONFERENCE_POSTER
|2 ORCID
336 7 _ |a Output Types/Conference Poster
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336 7 _ |a Poster
|b poster
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|0 PUB:(DE-HGF)24
|s 1470147429_3436
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|x Other
520 _ _ |a The pairwise maximum-entropy model [1,2], applied to experimental neuronal data of populations of 200 andmore neurons, is very likely to give a bimodal probability distribution for the population-averaged activity. Wehave provided evidence for this claim, starting from an experimental dataset and then looking at summarizeddata from the literature. The first mode is the one observed in the data. The second mode (unobserved)can appear at very high activities (even 90% of the population simultaneously active) and its height increaseswith population size. This bimodality has several undesirable consequences:1.The presence of two modes is unrealistic in view of observed neuronal activity.2.The prediction of a high-activity mode is unrealistic on neurobiological grounds.3.Boltzmann learning becomes non-ergodic, hence the pairwise model found by this method is not themaximum entropy distribution; similarly, solving the inverse problem by common variants of mean-fieldapproximations has the same problem.4.The Glauber dynamics associated with the model is either unrealistically bistable, or does not reflect thedistribution of the pairwise model.
536 _ _ |a 331 - Signalling Pathways and Mechanisms in the Nervous System (POF2-331)
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536 _ _ |a 574 - Theory, modelling and simulation (POF3-574)
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536 _ _ |a 571 - Connectivity and Activity (POF3-571)
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700 1 _ |a Mana, PierGianLuca
|0 P:(DE-Juel1)165939
|b 1
|u fzj
700 1 _ |a Helias, Moritz
|0 P:(DE-Juel1)144806
|b 2
|u fzj
909 C O |o oai:juser.fz-juelich.de:809498
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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|l Funktion und Dysfunktion des Nervensystems
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913 1 _ |a DE-HGF
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913 1 _ |a DE-HGF
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|l Decoding the Human Brain
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|v Connectivity and Activity
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|4 G:(DE-HGF)POF
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914 1 _ |y 2016
920 1 _ |0 I:(DE-Juel1)INM-6-20090406
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|l Computational and Systems Neuroscience
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980 _ _ |a poster
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)INM-6-20090406
980 _ _ |a UNRESTRICTED
981 _ _ |a I:(DE-Juel1)IAS-6-20130828

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