2016
Effects of Symmetry on the Structural Controllability of Neural Networks: A Perspective
Whalen A, Brennan S, Sauer T, Schiff S. Effects of Symmetry on the Structural Controllability of Neural Networks: A Perspective. Proceedings Of The 2010 American Control Conference 2016, 2016: 5785-5790. PMID: 29176923, PMCID: PMC5699861, DOI: 10.1109/acc.2016.7526576.Peer-Reviewed Original ResearchGroup representation theoryStructural controllabilityMan-made networksDynamical systemsOptimal actuatorRepresentation theoryEffect of symmetryControl inputExplicit symmetryCritical actuatorsEngineering systemsComplex networksSymmetryControllabilityMinimum numberActuatorsCoupling structureStructural symmetryNeural networkNetworkRecent workTheorySystemBroad interest
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 modelsWavesFrameworkField
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
Kalman 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
2004
Electric Field Control of Seizure Propagation: From Theory to Experiment
Richardson K, Schiff S, Gluckman B. Electric Field Control of Seizure Propagation: From Theory to Experiment. AIP Conference Proceedings 2004, 742: 185-196. DOI: 10.1063/1.1846476.Peer-Reviewed Original ResearchMathematical modelSpeed of propagationMathematical solutionElectric fieldElectric field controlEpileptic seizure propagationSuch electric fieldsField controlHigh enough valuesEnough valuesPropagationWavesActivity wavesDimensional networkSolutionModelFieldTheoryLower threshold valueNetworkThreshold valueSpeedParameters
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