2023
Identification of White Matter Hyperintensities in Routine Emergency Department Visits Using Portable Bedside Magnetic Resonance Imaging
de Havenon A, Parasuram N, Crawford A, Mazurek M, Chavva I, Yadlapalli V, Iglesias J, Rosen M, Falcone G, Payabvash S, Sze G, Sharma R, Schiff S, Safdar B, Wira C, Kimberly W, Sheth K. Identification of White Matter Hyperintensities in Routine Emergency Department Visits Using Portable Bedside Magnetic Resonance Imaging. Journal Of The American Heart Association 2023, 12: e029242. PMID: 37218590, PMCID: PMC10381997, DOI: 10.1161/jaha.122.029242.Peer-Reviewed Original ResearchConceptsWhite matter hyperintensitiesMagnetic resonance imagingSevere white matter hyperintensitiesConventional magnetic resonance imagingResonance imagingRetrospective cohortEmergency departmentMatter hyperintensitiesVascular risk factorsProspective observational studyVascular cognitive impairmentTesla magnetic resonance imagingArea Deprivation IndexProspective cohortAdult patientsAcute careRisk factorsCardiovascular diseaseObservational studyCognitive impairmentPatientsCare magnetic resonance imagingIntermodality agreementCohortDeprivation index
2022
Thermal effects on neurons during stimulation of the brain
Kim T, Kadji H, Whalen A, Ashourvan A, Freeman E, Fried S, Tadigadapa S, Schiff S. Thermal effects on neurons during stimulation of the brain. Journal Of Neural Engineering 2022, 19: 056029. PMID: 36126646, PMCID: PMC9855718, DOI: 10.1088/1741-2552/ac9339.Peer-Reviewed Original ResearchConceptsThermal effectsJoule heatingMagnetic coilsRate dependencyElectrical interactionsSmall thermal effectsTemperature changesDissipation of energyNumerical modelingRange of frequenciesThermal energyMagnetic fieldDC drivingMagnetic inductionElectrical currentStatic magnetic fieldSmall temperature increaseTemperature increaseAccurate modulationCoilEnergy depositionHeatingConductorsTransient effectsElectrode
2021
Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus
Harper JR, Cherukuri V, O’Reilly T, Yu M, Mbabazi-Kabachelor E, Mulando R, Sheth KN, Webb AG, Warf BC, Kulkarni AV, Monga V, Schiff SJ. Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus. NeuroImage Clinical 2021, 32: 102896. PMID: 34911199, PMCID: PMC8646178, DOI: 10.1016/j.nicl.2021.102896.Peer-Reviewed Original ResearchConceptsDeep learning enhancementLow-quality imagesDeep learningQuality imagesDeep learning algorithmsEnhanced imageRole of machineLearning enhancementImage qualityLearning algorithmAcceptable image qualityReconstruction errorImage resolutionImagesAlgorithmCT imagesLearningCT counterpartsNoise ratioTreatment planningPlanningNew standardStructural errorsExperienced pediatric neurosurgeonsMachineNormal childhood brain growth and a universal sex and anthropomorphic relationship to cerebrospinal fluid
Peterson M, Cherukuri V, Paulson J, Ssentongo P, Kulkarni A, Warf B, Monga V, Schiff S. Normal childhood brain growth and a universal sex and anthropomorphic relationship to cerebrospinal fluid. Journal Of Neurosurgery Pediatrics 2021, 28: 458-468. PMID: 34243147, PMCID: PMC8594737, DOI: 10.3171/2021.2.peds201006.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAlgorithmsAnalysis of VarianceAnthropometryBody WeightBrainCerebrospinal FluidChildChild DevelopmentChild, PreschoolCohort StudiesFemaleFunctional LateralityHumansHydrocephalusInfantInfant, NewbornMagnetic Resonance ImagingMaleOrgan SizePopulationReference StandardsSex CharacteristicsConceptsBrain growthBrain volumeFluid accumulationRatio of brainHealthy pediatric subjectsTotal brain volumeAge 18 yearsYears of ageRegional brain volumesNormal brain growthAge-dependent relationshipCSF accumulationPediatric subjectsChildhood diseasesCerebrospinal fluidCSF volumeCongenital disorderVolume trajectoriesEarly childhoodNormative growth curvesNumerous conditionsSexMagnetic resonanceBrain size
2020
Exome sequencing implicates genetic disruption of prenatal neuro-gliogenesis in sporadic congenital hydrocephalus
Jin SC, Dong W, Kundishora AJ, Panchagnula S, Moreno-De-Luca A, Furey CG, Allocco AA, Walker RL, Nelson-Williams C, Smith H, Dunbar A, Conine S, Lu Q, Zeng X, Sierant MC, Knight JR, Sullivan W, Duy PQ, DeSpenza T, Reeves BC, Karimy JK, Marlier A, Castaldi C, Tikhonova IR, Li B, Peña HP, Broach JR, Kabachelor EM, Ssenyonga P, Hehnly C, Ge L, Keren B, Timberlake AT, Goto J, Mangano FT, Johnston JM, Butler WE, Warf BC, Smith ER, Schiff SJ, Limbrick DD, Heuer G, Jackson EM, Iskandar BJ, Mane S, Haider S, Guclu B, Bayri Y, Sahin Y, Duncan CC, Apuzzo MLJ, DiLuna ML, Hoffman EJ, Sestan N, Ment LR, Alper SL, Bilguvar K, Geschwind DH, Günel M, Lifton RP, Kahle KT. Exome sequencing implicates genetic disruption of prenatal neuro-gliogenesis in sporadic congenital hydrocephalus. Nature Medicine 2020, 26: 1754-1765. PMID: 33077954, PMCID: PMC7871900, DOI: 10.1038/s41591-020-1090-2.Peer-Reviewed Original ResearchConceptsCongenital hydrocephalusPoor neurodevelopmental outcomesPost-surgical patientsCerebrospinal fluid accumulationNeural stem cell biologyGenetic disruptionWhole-exome sequencingPrimary pathomechanismEarly brain developmentNeurodevelopmental outcomesHigh morbidityCSF diversionMutation burdenFluid accumulationBrain ventriclesCH casesBrain developmentDe novo mutationsPatientsExome sequencingCSF dynamicsDisease mechanismsHydrocephalusNovo mutationsCell types
2018
A Brain–Heart Biomarker for Epileptogenesis
Bahari F, Ssentongo P, Schiff S, Gluckman B. A Brain–Heart Biomarker for Epileptogenesis. Journal Of Neuroscience 2018, 38: 8473-8483. PMID: 30150365, PMCID: PMC6158692, DOI: 10.1523/jneurosci.1130-18.2018.Peer-Reviewed Original ResearchConceptsBrain-heart interactionsBiomarkers of epileptogenesisDevelopment of epilepsyAutonomic cardiac activityIdentification of patientsPostinjury epilepsyPreventable sequelaeFirst seizureBrain insultsCortical dischargesMale miceEpileptogenesisMurine modelMouse modelCardiac rhythmReliable biomarkersEpilepsyChronic measurementTreatment developmentBiomarkersSuch treatmentCardiac activityTherapeutic purposesBrain activityPatientsControl of Spreading Depression with Electrical Fields
Whalen A, Xiao Y, Kadji H, Dahlem M, Gluckman B, Schiff S. Control of Spreading Depression with Electrical Fields. Scientific Reports 2018, 8: 8769. PMID: 29884896, PMCID: PMC5993812, DOI: 10.1038/s41598-018-26986-1.Peer-Reviewed Original ResearchConceptsElectric fieldField polarityDC electric fieldElectric field polarityElectrical controlOptical imagingPropagation pathIntrinsic optical imagingOpposite signDepression propagatesElectrical fieldField terminationElectro-chemical gradientPropagation velocityPropagatesFieldTraumatic brain injuryPropagationConfinementMore superficial layersDepression propagationBrain injurySynaptic transmissionBrain slicesWavesDesign of a sustainable prepolarizing magnetic resonance imaging system for infant hydrocephalus
Obungoloch J, Harper J, Consevage S, Savukov I, Neuberger T, Tadigadapa S, Schiff S. Design of a sustainable prepolarizing magnetic resonance imaging system for infant hydrocephalus. Magnetic Resonance Materials In Physics, Biology And Medicine 2018, 31: 665-676. PMID: 29644479, PMCID: PMC6135672, DOI: 10.1007/s10334-018-0683-y.Peer-Reviewed Original ResearchConceptsLow power requirementsSpatial resolutionLF-MRIModest spatial resolutionMagnetic resonance imaging systemPower requirementsCoil systemImage spatial resolutionUnshielded environmentGradient fieldResonance imaging systemLow costDeployment potentialEnergy supplySpecific applicationsUnshielded roomImaging systemLow-field magnetic resonance imagingNormative human brain volume growth.
Peterson M, Warf B, Schiff S. Normative human brain volume growth. Journal Of Neurosurgery Pediatrics 2018, 21: 478-485. PMID: 29498607, PMCID: PMC6212293, DOI: 10.3171/2017.10.peds17141.Peer-Reviewed Original ResearchConceptsStatistical measuresPower lawNonlinear least-squares regression algorithmGood statistical resultsLeast squares regression algorithmCurve fitCandidate modelsCorresponding statisticsAppropriate statistical measuresFit parametersStatistical resultsRegression algorithmWeibull fitWeibull modelNormative MRI dataPotential modelFitVolume growthGompertz modelBest modelModelModel curve fitWeibullLawStatistics
2017
Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans
Cherukuri V, Ssenyonga P, Warf B, Kulkarni A, Monga V, Schiff S. Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans. IEEE Transactions On Biomedical Engineering 2017, 65: 1871-1884. PMID: 29989926, PMCID: PMC6062853, DOI: 10.1109/tbme.2017.2783305.Peer-Reviewed Original Research
2015
The Role of Cell Volume in the Dynamics of Seizure, Spreading Depression, and Anoxic Depolarization
Ullah G, Wei Y, Dahlem M, Wechselberger M, Schiff S. The Role of Cell Volume in the Dynamics of Seizure, Spreading Depression, and Anoxic Depolarization. PLOS Computational Biology 2015, 11: e1004414. PMID: 26273829, PMCID: PMC4537206, DOI: 10.1371/journal.pcbi.1004414.Peer-Reviewed Original ResearchConceptsAnoxic depolarizationCell swellingDynamics of seizuresGlial KNeuroprotective roleSpreading DepressionEpileptic seizuresSeizuresPhysiological ceilingDepression statePathological activityCell volumeNeuronal dynamicsDepressionPathological statesSeparate seizuresIntervention strategiesNeuron membraneDepolarizationUse of volumeNeuronal behaviorOxygen homeostasisOxygen supplyCells swellSwelling
2014
Volumetric brain analysis in neurosurgery: Part 3. Volumetric CT analysis as a predictor of seizure outcome following temporal lobectomy.
Mandell J, Hill K, Nguyen D, Moser K, Harbaugh R, McInerney J, Nsubuga B, Mugamba J, Johnson D, Warf B, Boling W, Webb A, Schiff S. Volumetric brain analysis in neurosurgery: Part 3. Volumetric CT analysis as a predictor of seizure outcome following temporal lobectomy. Journal Of Neurosurgery Pediatrics 2014, 15: 133-43. PMID: 25431899, DOI: 10.3171/2014.9.peds12428.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAnterior Temporal LobectomyBrainCerebrospinal FluidChildChild, PreschoolCognitionCone-Beam Computed TomographyEpilepsy, Temporal LobeFemaleFrontal LobeHumansHydrocephalusInfantMagnetic Resonance ImagingMaleNeurosurgical ProceduresOccipital LobeOrgan SizePredictive Value of TestsSeizuresTreatment OutcomeUgandaConceptsTemporal lobe volumeMesial temporal sclerosisTemporal lobe epilepsyTemporal lobe resectionSeizure outcomeTemporal lobeVolumetric CT analysisBrain volumeLobe volumeSeizure controlStructural MRILobe resectionEngel class Ia outcomeClass Ia outcomeSelection of patientsCT volumetric analysisPreoperative CT scanSmaller brain volumesSmaller temporal lobeCURE Children's HospitalIncomplete seizure controlNormalized brain volumeWhole brain volumeCT analysisTemporal lobe structuresVolumetric brain analysis in neurosurgery: Part 1. Particle filter segmentation of brain and cerebrospinal fluid growth dynamics from MRI and CT images.
Mandell J, Langelaan J, Webb A, Schiff S. Volumetric brain analysis in neurosurgery: Part 1. Particle filter segmentation of brain and cerebrospinal fluid growth dynamics from MRI and CT images. Journal Of Neurosurgery Pediatrics 2014, 15: 113-24. PMID: 25431902, DOI: 10.3171/2014.9.peds12426.Peer-Reviewed Original ResearchConceptsEdge trackerParticle filterGround vehicle navigationBrain image analysisCT imagesMRI data setsImage segmentationSegmentation algorithmAutonomous airVehicle navigationAccurate edgesNovel algorithmManual segmentationSegmentationMR imagesBrain dataVolumetric brain analysisData setsImage analysisSemiautomatic methodImagesModality independenceHistorical dataAlgorithmMRI dataVolumetric brain analysis in neurosurgery: Part 2. Brain and CSF volumes discriminate neurocognitive outcomes in hydrocephalus.
Mandell J, Kulkarni A, Warf B, Schiff S. Volumetric brain analysis in neurosurgery: Part 2. Brain and CSF volumes discriminate neurocognitive outcomes in hydrocephalus. Journal Of Neurosurgery Pediatrics 2014, 15: 125-32. PMID: 25431901, DOI: 10.3171/2014.9.peds12427.Peer-Reviewed Original ResearchConceptsFrontal-occipital horn ratioNeurocognitive outcomesBrain volumeCSF volumeFluid volumePediatric patientsBrain developmentEvaluation of hydrocephalusGoal of treatmentSmaller brain volumesLower cognitive outcomesPoor neurocognitive outcomesNormal brain developmentLarge fluid volumesHealthy brain developmentVolumetric brain analysisSurgical treatmentVentricular sizeHydrocephalic patientsCT scanHydrocephalusPatientsBayley ScalesBrain growthFine motor
2011
Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces
Kamrunnahar M, Dias N, Schiff S. Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces. Annals Of Biomedical Engineering 2011, 39: 1482-1492. PMID: 21267657, PMCID: PMC3655721, DOI: 10.1007/s10439-011-0248-y.Peer-Reviewed Original ResearchConceptsModel-based predictive controllerController designPredictive controller designAR model parametersPredictive controllerFilter applicationsControllerInterface applicationsModel-based featuresModel parametersBrain-computer interface applicationsPerformanceApplicationsParametersDesignInterfaceBCI applicationsA square root ensemble Kalman filter application to a motor-imagery brain-computer interface
Kamrunnahar M, Schiff S. A square root ensemble Kalman filter application to a motor-imagery brain-computer interface. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2011, 2011: 6385-6388. PMID: 22255799, PMCID: PMC5699860, DOI: 10.1109/iembs.2011.6091576.Peer-Reviewed Original Research
2010
The dynamics of brain and cerebrospinal fluid growth in normal versus hydrocephalic mice.
Mandell J, Neuberger T, Drapaca C, Webb A, Schiff S. The dynamics of brain and cerebrospinal fluid growth in normal versus hydrocephalic mice. Journal Of Neurosurgery Pediatrics 2010, 6: 1-10. PMID: 20593980, DOI: 10.3171/2010.4.peds1014.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAlgorithmsAnimalsAnimals, NewbornBrainCephalometryCerebral AqueductCerebral VentriclesDisease Models, AnimalFourier AnalysisFrontal LobeHydrocephalusImage Processing, Computer-AssistedImaging, Three-DimensionalIntracranial PressureLateral VentriclesMagnetic Resonance ImagingMathematical ComputingMiceMice, Inbred C57BLOccipital LobeOrgan SizeReference ValuesConceptsHydrocephalic miceBrain volumeClinical outcomesBrain growthVentricle volumeDynamics of brainCortical mantle thicknessPatterns of hydrocephalusOccipital horn ratioAccumulation of CSFTransmantle pressure gradientGrowth of brainVentricular ruptureParenchymal edemaVentricular sizeC57BL/6 miceTotal brainPercutaneous injectionAdjunct useHead circumferenceNormal miceCisterna magnaCSF volumeCognitive functionSerial quantificationFeature selection on movement imagery discrimination and attention detection
Dias N, Kamrunnahar M, Mendes P, Schiff S, Correia J. Feature selection on movement imagery discrimination and attention detection. Medical & Biological Engineering & Computing 2010, 48: 331-341. PMID: 20112135, PMCID: PMC2946110, DOI: 10.1007/s11517-010-0578-1.Peer-Reviewed Original Research
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
2008
Model-based Responses and Features in Brain Computer Interfaces
Kamrunnahar M, Dias N, Schiff S, Gluckman B. Model-based Responses and Features in Brain Computer Interfaces. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2008, 2008: 4482-4485. PMID: 19163711, DOI: 10.1109/iembs.2008.4650208.Peer-Reviewed Original ResearchConceptsBrain-computer interfaceMotor imagery tasksComputer interfaceClassification errorDifferent feature selection methodsLinear discriminant analysisFeature selection methodClassification of tasksDevelopment of BCIsImagery tasksFeature extractionHuman scalp electroencephalographySelection methodRight hand movementsTaskFilter algorithmEEG signalsNovel modelPrincipal component analysisControl systems theoryHand movementsScalp EEG correlatesFeaturesInterfaceAlgorithm