2023
An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory
Melloni L, Mudrik L, Pitts M, Bendtz K, Ferrante O, Gorska U, Hirschhorn R, Khalaf A, Kozma C, Lepauvre A, Liu L, Mazumder D, Richter D, Zhou H, Blumenfeld H, Boly M, Chalmers D, Devore S, Fallon F, de Lange F, Jensen O, Kreiman G, Luo H, Panagiotaropoulos T, Dehaene S, Koch C, Tononi G. An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLOS ONE 2023, 18: e0268577. PMID: 36763595, PMCID: PMC9916582, DOI: 10.1371/journal.pone.0268577.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingGlobal neuronal workspaceConscious visual perceptionIntracranial electroencephalographyVisual consciousnessVisual perceptionConscious experienceBrain activityIntegrated Information TheoryMajor theoriesAdversarial collaborationHuman brainDifferent accountsOpen science practicesStudy protocolMagnetic resonance imagingConsciousnessInformation theoryTheory proponentsTheoryPerceptionResonance imagingElectroencephalographyCorrelatesRelationship
2022
Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity
Kronemer S, Aksen M, Ding J, Ryu J, Xin Q, Ding Z, Prince J, Kwon H, Khalaf A, Forman S, Jin D, Wang K, Chen K, Hu C, Agarwal A, Saberski E, Wafa S, Morgan O, Wu J, Christison-Lagay K, Hasulak N, Morrell M, Urban A, Todd Constable R, Pitts M, Mark Richardson R, Crowley M, Blumenfeld H. Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity. Nature Communications 2022, 13: 7342. PMID: 36446792, PMCID: PMC9707162, DOI: 10.1038/s41467-022-35117-4.Peer-Reviewed Original ResearchConceptsSubcortical networksConscious visual perceptionVisual perception taskNeurophysiology of consciousnessExecutive control networkMajor brain networksDefault mode networkFrontal eye fieldOvert reportPerception taskVisual consciousnessConscious perceptionFusiform cortexVisual perceptionAnterior insulaConscious experienceSalience networkBrain networksMode networkAnterior cingulateEye fieldTask reportControl networkFMRI changesNeural circuitsA machine‐learning approach for predicting impaired consciousness in absence epilepsy
Springer M, Khalaf A, Vincent P, Ryu JH, Abukhadra Y, Beniczky S, Glauser T, Krestel H, Blumenfeld H. A machine‐learning approach for predicting impaired consciousness in absence epilepsy. Annals Of Clinical And Translational Neurology 2022, 9: 1538-1550. PMID: 36114696, PMCID: PMC9539371, DOI: 10.1002/acn3.51647.Peer-Reviewed Original ResearchEarly neural activity changes associated with stimulus detection during visual conscious perception
Khalaf A, Kronemer SI, Christison-Lagay K, Kwon H, Li J, Wu K, Blumenfeld H. Early neural activity changes associated with stimulus detection during visual conscious perception. Cerebral Cortex 2022, 33: 1347-1360. PMID: 35446937, DOI: 10.1093/cercor/bhac140.Peer-Reviewed Original ResearchConceptsVisual conscious perceptionNeural activity changesConscious perceptionStimulus detectionContinuous performance taskCortical neural signalsGamma power increaseGamma power changesMedial occipital cortexMedial temporal cortexParietal-temporal cortexTarget letterNontarget stimuliPerformance taskVisual stimuliStimulus onsetPopulation neural activityBroadband gamma powerNeural activityTemporal cortexGamma powerActivity changesMotor responsePremotor areasOccipital cortex
2021
Early cortical signals in visual stimulus detection
Kwon H, Kronemer SI, Christison-Lagay KL, Khalaf A, Li J, Ding JZ, Freedman NC, Blumenfeld H. Early cortical signals in visual stimulus detection. NeuroImage 2021, 244: 118608. PMID: 34560270, DOI: 10.1016/j.neuroimage.2021.118608.Peer-Reviewed Original ResearchConceptsConscious perceptionStimulus onsetLeft hemisphere language areasVisual conscious perceptionWord recall taskBilateral medial temporal corticesVerbal memory taskConscious visual perceptionLeft rostral middle frontal gyrusHemisphere language areasVisual stimulus detectionMiddle frontal gyrusGamma power increaseGamma power changesDefault mode networkMedial temporal regionsBroadband gamma activityNeural activity changesMedial temporal cortexRight frontal cortexSignal detection networkMultiple cortical regionsRostral middle frontal gyrusMemory taskRecall task
2020
Induced bioresistance via BNP detection for machine learning-based risk assessment
So S, Khalaf A, Yi X, Herring C, Zhang Y, Simon M, Akcakaya M, Lee S, Yun M. Induced bioresistance via BNP detection for machine learning-based risk assessment. Biosensors And Bioelectronics 2020, 175: 112903. PMID: 33370705, DOI: 10.1016/j.bios.2020.112903.Peer-Reviewed Original ResearchEEG-based Neglect Detection for Stroke Patients
Kocanaogullari D, Mak J, Kersey J, Khalaf A, Ostadabbas S, Wittenberg G, Skidmore E, Akcakaya M. EEG-based Neglect Detection for Stroke Patients. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2020, 00: 264-267. PMID: 33017979, DOI: 10.1109/embc44109.2020.9176378.Peer-Reviewed Original ResearchA probabilistic approach for calibration time reduction in hybrid EEG–fTCD brain–computer interfaces
Khalaf A, Akcakaya M. A probabilistic approach for calibration time reduction in hybrid EEG–fTCD brain–computer interfaces. BioMedical Engineering OnLine 2020, 19: 23. PMID: 32299441, PMCID: PMC7164278, DOI: 10.1186/s12938-020-00765-4.Peer-Reviewed Original ResearchConceptsBrain-computer interfaceClass-conditional distributionsBCI usersSmall training datasetMI paradigmSupport vector machineCalibration time reductionHybrid brain-computer interfaceMotor imageryTraining dataBetter generalizationFeature vectorsVector machineTraining datasetUsersPrevious usersCalibration sessionSimilar datasetsBhattacharyya distanceGeneration paradigmDatasetCalibration requirementsEfficient performanceHybrid EEG–fTCD Brain–Computer Interfaces
Khalaf A, Sejdic E, Akcakaya M. Hybrid EEG–fTCD Brain–Computer Interfaces. Cognitive Science And Technology 2020, 295-314. DOI: 10.1007/978-3-030-34784-0_15.Peer-Reviewed Original ResearchFunctional transcranial Doppler ultrasoundBrain-computer interfaceWord generationBrain activityNoninvasive brain-computer interfaceHybrid brain-computer interfaceMental rotation taskDifferent brain activitiesElectrical brain activityCognitive tasksPresentation paradigmRotation taskVisual stimuliEEG recording deviceLimited speechNovel hybrid brain-computer interfaceNeuroimaging modalitiesPhysical abilityElectroencephalographyTaskComputer interfaceTask problemMI presentationHigh temporal resolutionSpeechAnalysis of multimodal physiological signals within and between individuals to predict psychological challenge vs. threat
Khalaf A, Nabian M, Fan M, Yin Y, Wormwood J, Siegel E, Quigley K, Barrett L, Akcakaya M, Chou C, Ostadabbas S. Analysis of multimodal physiological signals within and between individuals to predict psychological challenge vs. threat. Expert Systems With Applications 2020, 140: 112890. DOI: 10.1016/j.eswa.2019.112890.Peer-Reviewed Original ResearchSelf-reported judgmentsPerformance taskPhysiological respondingIndividual differencesMultimodal physiological signalsMental arithmetic taskPhysiological response patternsResponse patternsMotivated performanceThreat responsesGroup-level variationPsychological challengesArithmetic taskSubgroup of participantsPerformance domainsGroup-level comparisonsSubgroup of individualsPhysiological patternsPhysiological responsesSubject analysisTaskIntegrated analytic frameworkDifferent modalitiesRespondingIndividual evaluation
2019
A Machine Learning Approach for Classifying Faults in Microgrids using Wavelet Decomposition
Khalaf A, Al Hassan H, Emes A, Akcakaya M, Grainger B. A Machine Learning Approach for Classifying Faults in Microgrids using Wavelet Decomposition. 2019, 00: 1-6. DOI: 10.1109/mlsp.2019.8918774.Peer-Reviewed Original ResearchLinear discriminant analysisWavelet decompositionNaïve Bayesian classifierFault typesClassification problemDifferent fault scenariosClassification performanceVector machineBayesian classifierWavelet coefficientsStatistical featuresFault identificationFault onsetMachineFault scenariosHigh performanceOverall accuracyExperimental resultsThree-phase voltageSignificant featuresMicrogrid architectureBhattacharyya Distance-based Transfer Learning for a Hybrid Eeg-ftcd Brain-computer Interface
Dagois E, Khalaf A, Sejdic E, Akcakaya M. Bhattacharyya Distance-based Transfer Learning for a Hybrid Eeg-ftcd Brain-computer Interface. 2019, 00: 3082-3086. DOI: 10.1109/icassp.2019.8683308.Peer-Reviewed Original ResearchEEG-fTCD hybrid brain–computer interface using template matching and wavelet decomposition
Khalaf A, Sejdic E, Akcakaya M. EEG-fTCD hybrid brain–computer interface using template matching and wavelet decomposition. Journal Of Neural Engineering 2019, 16: 036014. PMID: 30818297, DOI: 10.1088/1741-2552/ab0b7f.Peer-Reviewed Original ResearchCommon spatial pattern and wavelet decomposition for motor imagery EEG- fTCD brain-computer interface
Khalaf A, Sejdic E, Akcakaya M. Common spatial pattern and wavelet decomposition for motor imagery EEG- fTCD brain-computer interface. Journal Of Neuroscience Methods 2019, 320: 98-106. PMID: 30946880, DOI: 10.1016/j.jneumeth.2019.03.018.Peer-Reviewed Original ResearchMutual Information for Transfer Learning in SSVEP Hybrid EEG-fTCD Brain-Computer Interfaces
Khalaf A, Sejdic E, Akcakaya M. Mutual Information for Transfer Learning in SSVEP Hybrid EEG-fTCD Brain-Computer Interfaces. 2019, 00: 941-944. DOI: 10.1109/ner.2019.8717018.Peer-Reviewed Original ResearchTransfer Learning for a Multimodal Hybrid EEG-fTCD Brain–Computer Interface
Dagois E, Khalaf A, Sejdic E, Akcakaya M. Transfer Learning for a Multimodal Hybrid EEG-fTCD Brain–Computer Interface. IEEE Sensors Letters 2019, 3: 1-4. DOI: 10.1109/lsens.2018.2879466.Peer-Reviewed Original ResearchFunctional transcranial Doppler ultrasoundTransfer learningClass-conditional distributionsQuadratic discriminant analysisLinear discriminant analysisCalibration sessionHybrid BCIConditional probabilistic distributionsBetter classification performanceElectrical brain activityBrain-computer interface (BCI) researchMotor imagery tasksTraining dataDifferent classifiersClassification performanceProbabilistic similarityVector machineImagery tasksComputer interfaceBrain activityControl accessDimensionality reductionFinal classificationBCI systemSpecific tasks
2018
A novel motor imagery hybrid brain computer interface using EEG and functional transcranial Doppler ultrasound
Khalaf A, Sejdic E, Akcakaya M. A novel motor imagery hybrid brain computer interface using EEG and functional transcranial Doppler ultrasound. Journal Of Neuroscience Methods 2018, 313: 44-53. PMID: 30590086, DOI: 10.1016/j.jneumeth.2018.11.017.Peer-Reviewed Original ResearchTowards optimal visual presentation design for hybrid EEG—fTCD brain–computer interfaces
Khalaf A, Sejdic E, Akcakaya M. Towards optimal visual presentation design for hybrid EEG—fTCD brain–computer interfaces. Journal Of Neural Engineering 2018, 15: 056019. PMID: 30021931, DOI: 10.1088/1741-2552/aad46f.Peer-Reviewed Original ResearchConceptsFunctional transcranial Doppler ultrasoundMental rotationTerms of accuracyTransfer rateFTCD signalsHybrid systemDesign approachReal-time BCIVisual presentationFeasible candidateMotor imageryInterface systemHigh accuracyVisual stimulation techniqueElectrical brain activityBrain-computer interface (BCI) systemsHybrid BCIHybrid combinationCognitive tasksPower spectrumSuch promising resultsHybrid brain-computer interface (BCI) systemFixation crossAccuracyDesignReal-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System
Hassan A, Khalaf A, Sayed K, Li H, Chen Y. Real-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2018, 00: 2567-2570. PMID: 30440932, DOI: 10.1109/embc.2018.8512868.Peer-Reviewed Original ResearchConceptsNeuromorphic computing systemsComputing systemsCardiac arrhythmia classificationArrhythmia classificationReal-time processingTerms of accuracyDifferent beat typesAverage testing timeTesting timeAverage accuracyBeat typesBasic building blocksDetection techniquesPower consumptionOverall accuracyExperimental resultsClassificationAccuracySystemBuilding blocksEEG-based neglect assessment: A feasibility study
Khalaf A, Kersey J, Eldeeb S, Alankus G, Grattan E, Waterstram L, Skidmore E, Akcakaya M. EEG-based neglect assessment: A feasibility study. Journal Of Neuroscience Methods 2018, 303: 169-177. PMID: 29614297, PMCID: PMC7156006, DOI: 10.1016/j.jneumeth.2018.03.019.Peer-Reviewed Original ResearchConceptsSpatial neglectPencil testsPassive BCI systemAutomatic attentionTarget stimuliSubjects' attentionComputerized testsVisual stimuliNeuropsychological syndromesAttention levelVisual spaceEEG responsesHealthy participantsNeglect assessmentsStimuliCurrent assessment methodsTraditional paperElectroencephalographyDynamic assessmentDifferent processingEEG signalsBCI systemCortical lesionsAttentionComplex environments