Battaglia, Demian

[["dc.bibliographiccitation.journal","Frontiers in Neural Circuits"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Witt, Annette"],["dc.contributor.author","Palmigiano, Agostina"],["dc.contributor.author","Neef, Andreas"],["dc.contributor.author","El Hady, Ahmed"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Battaglia, Demian"],["dc.date.accessioned","2017-09-07T11:45:38Z"],["dc.date.available","2017-09-07T11:45:38Z"],["dc.date.issued","2013"],["dc.description.abstract","Dynamic oscillatory coherence is believed to play a central role in flexible communication between brain circuits. To test this communication-through-coherence hypothesis, experimental protocols that allow a reliable control of phase-relations between neuronal populations are needed. In this modeling study, we explore the potential of closed-loop optogenetic stimulation for the control of functional interactions mediated by oscillatory coherence. The theory of non-linear oscillators predicts that the efficacy of local stimulation will depend not only on the stimulation intensity but also on its timing relative to the ongoing oscillation in the target area. Induced phase-shifts are expected to be stronger when the stimulation is applied within specific narrow phase intervals. Conversely, stimulations with the same or even stronger intensity are less effective when timed randomly. Stimulation should thus be properly phased with respect to ongoing oscillations (in order to optimally perturb them) and the timing of the stimulation onset must be determined by a real-time phase analysis of simultaneously recorded local field potentials (LFPs). Here, we introduce an electrophysiologically calibrated model of Channelrhodopsin 2 (ChR2)-induced photocurrents, based on fits holding over two decades of light intensity. Through simulations of a neural population which undergoes coherent gamma oscillations—either spontaneously or as an effect of continuous optogenetic driving—we show that precisely-timed photostimulation pulses can be used to shift the phase of oscillation, even at transduction rates smaller than 25%. We consider then a canonic circuit with two inter-connected neural populations oscillating with gamma frequency in a phase-locked manner. We demonstrate that photostimulation pulses applied locally to a single population can induce, if precisely phased, a lasting reorganization of the phase-locking pattern and hence modify functional interactions between the two populations."],["dc.identifier.doi","10.3389/fncir.2013.00049"],["dc.identifier.fs","599401"],["dc.identifier.gro","3151827"],["dc.identifier.pmid","23616748"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10678"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8657"],["dc.language.iso","en"],["dc.notes","Financial support by the German Federal Ministry of Education and Research (BMBF) via the Bernstein Center for Computational Neuroscience—Göttingen (01GQ1005B, 01GQ0430, 01GQ07113), the Bernstein Focus Neurotechnology—Göttingen (01GQ0811) and the Bernstein Focus Visual Learning (01GQ0921, 01GQ0922), the German Israel Research Foundation and the VolkswagenStiftung (ZN2632) and the Deutsche Forschungsgemeinschaft through CRC-889 (906-17.1/2006)."],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1662-5110"],["dc.relation.orgunit","Fakultät für Physik"],["dc.subject.mesh","Action Potentials"],["dc.subject.mesh","Biological Clocks"],["dc.subject.mesh","Computational Biology"],["dc.subject.mesh","HEK293 Cells"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Neural Networks (Computer)"],["dc.subject.mesh","Optogenetics"],["dc.subject.mesh","Photic Stimulation"],["dc.subject.mesh","Random Allocation"],["dc.subject.mesh","Time Factors"],["dc.title","Controlling the oscillation phase through precisely timed closed-loop optogenetic stimulation: a computational study"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e1002176"],["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Battaglia, Demian"],["dc.contributor.author","Hansel, David"],["dc.date.accessioned","2019-07-09T11:40:47Z"],["dc.date.available","2019-07-09T11:40:47Z"],["dc.date.issued","2011-10-01"],["dc.description.abstract","Visually induced neuronal activity in V1 displays a marked gamma-band component which is modulated by stimulus properties. It has been argued that synchronized oscillations contribute to these gamma-band activity. However, analysis of Local Field Potentials (LFPs) across different experiments reveals considerable diversity in the degree of oscillatory behavior of this induced activity. Contrast-dependent power enhancements can indeed occur over a broad band in the gamma frequency range and spectral peaks may not arise at all. Furthermore, even when oscillations are observed, they undergo temporal decorrelation over very few cycles. This is not easily accounted for in previous network modeling of gamma oscillations. We argue here that interactions between cortical layers can be responsible for this fast decorrelation. We study a model of a V1 hypercolumn, embedding a simplified description of the multi-layered structure of the cortex. When the stimulus contrast is low, the induced activity is only weakly synchronous and the network resonates transiently without developing collective oscillations. When the contrast is high, on the other hand, the induced activity undergoes synchronous oscillations with an irregular spatiotemporal structure expressing a synchronous chaotic state. As a consequence the population activity undergoes fast temporal decorrelation, with concomitant rapid damping of the oscillations in LFPs autocorrelograms and peak broadening in LFPs power spectra. We show that the strength of the inter-layer coupling crucially affects this spatiotemporal structure. We predict that layer VI inactivation should induce global changes in the spectral properties of induced LFPs, reflecting their slower temporal decorrelation in the absence of inter-layer feedback. Finally, we argue that the mechanism underlying the emergence of synchronous chaos in our model is in fact very general. It stems from the fact that gamma oscillations induced by local delayed inhibition tend to develop chaos when coupled by sufficiently strong excitation."],["dc.format.extent","24"],["dc.identifier.doi","10.1371/journal.pcbi.1002176"],["dc.identifier.pmid","21998568"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11310"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58249"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1553-7358"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.mesh","Animals"],["dc.subject.mesh","Computational Biology"],["dc.subject.mesh","Contrast Sensitivity"],["dc.subject.mesh","Electroencephalography"],["dc.subject.mesh","Electrophysiological Phenomena"],["dc.subject.mesh","Feedback, Physiological"],["dc.subject.mesh","Models, Neurological"],["dc.subject.mesh","Nerve Net"],["dc.subject.mesh","Nonlinear Dynamics"],["dc.subject.mesh","Photic Stimulation"],["dc.subject.mesh","Visual Cortex"],["dc.title","Synchronous chaos and broad band gamma rhythm in a minimal multi-layer model of primary visual cortex."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]