2012
Observability of Neuronal Network Motifs
Whalen A, Brennan S, Sauer T, Schiff S. Observability of Neuronal Network Motifs. 2012, 2012: 1-5. PMID: 25909092, PMCID: PMC4405257, DOI: 10.1109/ciss.2012.6310923.Peer-Reviewed Original ResearchNetwork observabilitySystem phase spaceFull network informationNetwork dynamicsNodal dynamicsNeuronal network motifsNodal equationsPhase spaceObservability metricsLimited measurement dataNeuron motifsConnection topologyObservabilitySmall neuronal networksNetwork motifsSuch networksMeasurement dataSymmetryDynamicsTopologyOrders of magnitudeEquationsNonlinearityFuture experimental workNetwork information
2011
Towards Model-Based Control of Parkinson's Disease: A Perspective
Schiff S. Towards Model-Based Control of Parkinson's Disease: A Perspective. 2011, 6487-6491. DOI: 10.1109/cdc.2011.6160870.Peer-Reviewed Original ResearchControl theoryModel-based control frameworkNonlinear control theoryModern control theoryControl frameworkKalman filtering techniqueDynamical diseasesOscillatory wavesComputational neuroscienceFiltering techniqueNetwork dynamicsAccurate reconstructionMature theoryTheoryDynamicsComputational modelModelNeuroscience modelsWavesFrameworkFieldKalman Filter Tracking of Intracellular Neuronal Voltage and Current
Wei Y, Ullah G, Parekh R, Ziburkus J, Schiff S. Kalman Filter Tracking of Intracellular Neuronal Voltage and Current. 2011, 5844-5849. DOI: 10.1109/cdc.2011.6161358.Peer-Reviewed Original Research
2010
Assimilating Seizure Dynamics
Ullah G, Schiff S. Assimilating Seizure Dynamics. PLOS Computational Biology 2010, 6: e1000776. PMID: 20463875, PMCID: PMC2865517, DOI: 10.1371/journal.pcbi.1000776.Peer-Reviewed Original ResearchConceptsModern control theoryDynamics of networksDynamical systemsControl theoryUnmeasured partDynamical interactionsData assimilationSmall neuronal networksPhysical variablesDynamicsBrain dynamicsComputational modelSeizure dynamicsActual measurementsNeuronal networksMicroenvironment dynamicsObservabilityNetworkVariablesModelTheorySystemMeasurements
2009
The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: I. Single neuron dynamics
Cressman J, Ullah G, Ziburkus J, Schiff S, Barreto E. The influence of sodium and potassium dynamics on excitability, seizures, and the stability of persistent states: I. Single neuron dynamics. Journal Of Computational Neuroscience 2009, 26: 159-170. PMID: 19169801, PMCID: PMC2704057, DOI: 10.1007/s10827-008-0132-4.Peer-Reviewed Original ResearchConceptsSingle neuron dynamicsDetailed bifurcation analysisLarge amplitude oscillationsExtracellular ion concentration dynamicsMathematical modelBifurcation analysisDynamical mechanismIon concentration dynamicsNeuron dynamicsReasonable approximationFull modelCompanion paperDynamicsImportant fundamental processesConcentration dynamicsKalman Meets Neuron: The Emerging Intersection of Control Theory with Neuroscience
Schiff S. Kalman Meets Neuron: The Emerging Intersection of Control Theory with Neuroscience. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2009, 2009: 3318-3321. PMID: 19964302, PMCID: PMC3644303, DOI: 10.1109/iembs.2009.5333752.Peer-Reviewed Original ResearchConceptsControl theoryNonlinear control theoryModern control theoryKalman filtering techniqueSingle neuron dynamicsComplex network dataWave dynamicsModel networksControl frameworkComputational neuroscienceNeuron dynamicsFiltering techniqueAccurate reconstructionMature theoryTheoryDynamicsNetwork dataKalmanConsensus setNeuroscience modelsField
2007
Kalman filter control of a model of spatiotemporal cortical dynamics
Schiff S, Sauer T. Kalman filter control of a model of spatiotemporal cortical dynamics. Journal Of Neural Engineering 2007, 5: 1. PMID: 18310806, PMCID: PMC2276637, DOI: 10.1088/1741-2560/5/1/001.Peer-Reviewed Original ResearchConceptsNonlinear systemsSpiral wave dynamicsSpatiotemporal cortical dynamicsObserver systemSystem stateExcitable systemsWave dynamicsKalman filteringUnscented KalmanEstimate parametersNonlinear methodsControl signalsFilter controlWave patternsApplied electrical fieldExperimental applicationElectrical fieldDynamicsKalmanParametersSuch resultsModelSystemFilteringSuch approaches
2003
Comparison of Methods for Seizure Detection
Jerger K, Netoff T, Francis J, Sauer T, Pecora L, Weinstein S, Schiff S. Comparison of Methods for Seizure Detection. Biological And Medical Physics, Biomedical Engineering 2003, 237-247. DOI: 10.1007/978-3-662-05048-4_13.Peer-Reviewed Original Research
2001
Differentiability implies continuity in neuronal dynamics
Francis J, So P, Gluckman B, Schiff S. Differentiability implies continuity in neuronal dynamics. Physica D Nonlinear Phenomena 2001, 148: 175-181. DOI: 10.1016/s0167-2789(00)00189-5.Peer-Reviewed Original ResearchNonlinear deterministic structureDeterministic structurePeriodic orbitsFundamental mathematical principlesPeriodic orbit structurePeriodic orbit theoryNeuronal dynamicsDifferentiable dynamicsMathematical principlesOrbit theoryOrbit structureMathematical functionsRegions of continuityJacobian transformationDifferentiabilityOnly continuityDynamicsOrbitPrevious approachesRecent workRestrictive testTheoryContinuityStructure
1998
Stochastic resonance in mammalian neuronal networks.
Gluckman B, So P, Netoff T, Spano M, Schiff S. Stochastic resonance in mammalian neuronal networks. Chaos An Interdisciplinary Journal Of Nonlinear Science 1998, 8: 588-598. PMID: 12779762, DOI: 10.1063/1.166340.Peer-Reviewed Original Research
1994
Discriminating deterministic versus stochastic dynamics in neuronal activity
Schiff S, Sauer T, Chang T. Discriminating deterministic versus stochastic dynamics in neuronal activity. Integrative Psychological And Behavioral Science 1994, 29: 246-261. PMID: 7811645, DOI: 10.1007/bf02691329.Peer-Reviewed Original Research