Timme, Marc

[["dc.bibliographiccitation.artnumber","UNSP e1004002"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Arnoldt, Hinrich"],["dc.contributor.author","Chang, Shuwen"],["dc.contributor.author","Jahnke, Sven"],["dc.contributor.author","Urmersbach, Birk"],["dc.contributor.author","Taschenberger, Holger"],["dc.contributor.author","Timme, Marc"],["dc.date.accessioned","2018-11-07T10:01:14Z"],["dc.date.available","2018-11-07T10:01:14Z"],["dc.date.issued","2015"],["dc.description.abstract","Fundamental response properties of neurons centrally underly the computational capabilities of both individual nerve cells and neural networks. Most studies on neuronal input-output relations have focused on continuous-time inputs such as constant or noisy sinusoidal currents. Yet, most neurons communicate via exchanging action potentials (spikes) at discrete times. Here, we systematically analyze the stationary spiking response to regular spiking inputs and reveal that it is generically non-monotonic. Our theoretical analysis shows that the underlying mechanism relies solely on a combination of the discrete nature of the communication by spikes, the capability of locking output to input spikes and limited resources required for spike processing. Numerical simulations of mathematically idealized and biophysically detailed models, as well as neurophysiological experiments confirm and illustrate our theoretical predictions."],["dc.description.sponsorship","BMBF Germany [01GQ1005B]; Max Planck Society"],["dc.identifier.doi","10.1371/journal.pcbi.1004002"],["dc.identifier.isi","000352081000008"],["dc.identifier.pmid","25646860"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/13555"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37971"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1553-7358"],["dc.relation.issn","1553-734X"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.mesh","Action Potentials"],["dc.subject.mesh","Animals"],["dc.subject.mesh","Cells, Cultured"],["dc.subject.mesh","Computer Simulation"],["dc.subject.mesh","Models, Neurological"],["dc.subject.mesh","Neurons"],["dc.subject.mesh","Patch-Clamp Techniques"],["dc.subject.mesh","Rats"],["dc.subject.mesh","Rats, Wistar"],["dc.subject.mesh","Trapezoid Body"],["dc.title","When Less Is More: Non-monotonic Spike Sequence Processing in Neurons"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMC Neuroscience"],["dc.bibliographiccitation.lastpage","2"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Arnoldt, Hinrich"],["dc.contributor.author","Jahnke, Sven"],["dc.contributor.author","Happ, Lena"],["dc.contributor.author","Gladrow, Jannes"],["dc.contributor.author","Urmersbach, Birk"],["dc.contributor.author","Chang, Shuwen"],["dc.contributor.author","Taschenberger, Holger"],["dc.contributor.author","Timme, Marc"],["dc.date.accessioned","2014-07-02T10:46:49Z"],["dc.date.accessioned","2021-10-27T13:18:21Z"],["dc.date.available","2014-07-02T10:46:49Z"],["dc.date.available","2021-10-27T13:18:21Z"],["dc.date.issued","2013"],["dc.format.mimetype","application/pdf"],["dc.identifier.doi","10.1186/1471-2202-14-S1-P389"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10420"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/91859"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.publisher","BioMed Central"],["dc.publisher.place","London"],["dc.relation.eissn","1471-2202"],["dc.relation.orgunit","Fakultät für Mathematik und Informatik"],["dc.rights","Goescholar"],["dc.rights.access","openAccess"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","When less is more: non-monotonic spike processing in neurons"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMC Neuroscience"],["dc.bibliographiccitation.lastpage","2"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Jahnke, Sven"],["dc.contributor.author","Memmesheimer, Raoul-Martin"],["dc.contributor.author","Timme, Marc"],["dc.date.accessioned","2014-07-02T10:46:48Z"],["dc.date.accessioned","2021-10-27T13:18:23Z"],["dc.date.available","2014-07-02T10:46:48Z"],["dc.date.available","2021-10-27T13:18:23Z"],["dc.date.issued","2013"],["dc.format.mimetype","application/pdf"],["dc.identifier.doi","10.1186/1471-2202-14-S1-P390"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10418"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/91864"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.publisher","BioMed Central"],["dc.publisher.place","London"],["dc.relation.eissn","1471-2202"],["dc.relation.orgunit","Fakultät für Mathematik und Informatik"],["dc.rights","Goescholar"],["dc.rights.access","openAccess"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Oscillation induced propagation of synchrony in structured neural networks"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","041016"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Physical Review X"],["dc.bibliographiccitation.volume","2"],["dc.contributor.author","Jahnke, Sven"],["dc.contributor.author","Timme, Marc"],["dc.contributor.author","Memmesheimer, Raoul-Martin"],["dc.date.accessioned","2018-11-07T09:02:19Z"],["dc.date.available","2018-11-07T09:02:19Z"],["dc.date.issued","2012"],["dc.description.abstract","Sparse random networks contain structures that can be considered as diluted feed-forward networks. Modeling of cortical circuits has shown that feed-forward structures, if strongly pronounced compared to the embedding random network, enable reliable signal transmission by propagating localized (subnetwork) synchrony. This assumed prominence, however, is not experimentally observed in local cortical circuits. Here, we show that nonlinear dendritic interactions, as discovered in recent single-neuron experiments, naturally enable guided synchrony propagation already in random recurrent neural networks that exhibit mildly enhanced, biologically plausible substructures. DOI: 10.1103/PhysRevX.2.041016"],["dc.description.sponsorship","BMBF [01GQ1005B]; DFG [TI 629/3-1]; Swartz Foundation"],["dc.identifier.doi","10.1103/PhysRevX.2.041016"],["dc.identifier.isi","000312452200001"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8458"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/24654"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Physical Soc"],["dc.relation.issn","2160-3308"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0"],["dc.title","Guiding Synchrony through Random Networks"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","UNSP 153"],["dc.bibliographiccitation.journal","Frontiers in Computational Neuroscience"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Jahnke, Sven"],["dc.contributor.author","Memmesheimer, Raoul-Martin"],["dc.contributor.author","Timme, Marc"],["dc.date.accessioned","2018-11-07T09:17:31Z"],["dc.date.available","2018-11-07T09:17:31Z"],["dc.date.issued","2013"],["dc.description.abstract","Coordinated patterns of precisely timed action potentials (spikes) emerge in a variety of neural circuits but their dynamical origin is still not well understood. One hypothesis states that synchronous activity propagating through feed- forward chains of groups of neurons (synfire chains) may dynamically generate such spike patterns. Additionally, synfire chains offer the possibility to enable reliable signal transmission. So far, mostly densely connected chains, often with all-to-all connectivity between groups, have been theoretically and computationally studied. Yet such prominent feed-forward structures have not been observed experimentally Here we analytically and numerically investigate under which conditions diluted feed-forward chains may exhibit synchrony propagation. In addition to conventional linear input summation, we study the impact of non-linear, non-additive summation accounting for the effect of fast dendritic spikes. The non-linearities promote synchronous inputs to generate precisely timed spikes. We identify how non-additive coupling relaxes the conditions on connectivity such that it enables synchrony propagation at connectivities substantially lower than required for linearly coupled chains. Although the analytical treatment is based on a simple leaky integrate-and-fire neuron model, we show how to generalize our methods to biologically more detailed neuron models and verify our results by numerical simulations with, e.g., Hodgkin Huxley type neurons."],["dc.identifier.doi","10.3389/fncom.2013.00153"],["dc.identifier.fs","601422"],["dc.identifier.isi","000327817100001"],["dc.identifier.pmid","24298251"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10674"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/28189"],["dc.notes","This work was supported by the BMBF(Grant No.01GQ1005B) \r\n[Sven Jahnke, MarcTimme], the DFG (Grant No.TI629/3-\r\n1)[Sven Jahnke],the Swartz Foundation [Raoul-Martin \r\nMemmesheimer], and the Max-Planck-Society [Marc Timme]."],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Frontiers Research Foundation"],["dc.relation.issn","1662-5188"],["dc.relation.orgunit","Fakultät für Physik"],["dc.title","Propagating synchrony in feed-forward networks"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e1003940"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Jahnke, Sven"],["dc.contributor.author","Memmesheimer, Raoul-Martin"],["dc.contributor.author","Timme, Marc"],["dc.date.accessioned","2018-11-07T09:31:52Z"],["dc.date.available","2018-11-07T09:31:52Z"],["dc.date.issued","2014"],["dc.description.abstract","Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay."],["dc.identifier.doi","10.1371/journal.pcbi.1003940"],["dc.identifier.isi","000346656700009"],["dc.identifier.pmid","25503492"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11312"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/31625"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1553-7358"],["dc.relation.issn","1553-734X"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Oscillation-Induced Signal Transmission and Gating in Neural Circuits"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]