Recentstudiesusinghigh-speedfMRItechniqueshavedetectedrestingstateconnectivityatfrequenciesup to 5 Hz in the visual and the motor cortices with significantly higher spatial-temporal stability than the correspondinglowfrequency(<0.1Hz)restingstateconnectivity.Thisapproachhasthepotentialforaddressing principallimitationsofmappinglowfrequencyrestingstateconnectivity,suchashighsensitivitytosignaldrifts and long time scales necessary for separating major RSNs. However, other studies using lower temporal resolution have been more cautious regarding the possible signal sources or were unable to replicate the findings.Noneofthepublishedstudieshaveidentifiedabiophysicalmechanism. We have recently detected remarkably strong high frequency connectivity in the auditory cortex, both in healthycontrolsandinpatientswithbraintumors,withsensitivityandspatialspecificitythatapproachesthatof conventionallowfrequencyrestingstateconnectivity,usinghigh-speedmulti-slabecho-volumarimaging(MEVI) (136 ms temporal resolution) and a confound-tolerant seed-based sliding window correlation analysis. Our preliminary data also show high frequency connectivity across several other major RSNs, consistent with previousstudies.Wehypothesizethathighfrequencyconnectivitymayreflectfastcerebrovascularregulation. Thiscontrastmechanismwouldenablenovelclinicalapplicationsthatarenotfeasiblewithcurrentmethodology, suchasimprovedlocalizationofdeepsourcesofinter-ictalepileptogenicactivitytoguidesurgicalresectionand mappingofdisease-relatedabnormalitiesinvascularcompliance.
The specificaims ofthisstudyare: (1)Characterize the biophysical mechanisms of high frequency connectivity in healthy controls. We will compare2D-acceleratedMEVIwith68msTRandmulti-bandEPIwith136msTRin12healthycontrols at3Tesla.BiophysicalmodelingbasedonarterialspinlabelingwillbeusedforcalibratedfMRI.Filtering of cardiac pulsatility up to the 3rd harmonic will minimize blood vessel contamination. The detection thresholdforhighfrequencyconnectivitywillbedeterminedbysimulatingcorrelationsinaRiciannoise model. (2)Characterizethephysiologicalbasisandclinicalpotentialofhigh-frequencyconnectivityinpatientswith braintumors.Wewillassessthephysiologicalbasisofhigh-frequencyconnectivityin10patientswith braintumorsadjacenttotheauditoryandsensorimotorcortexbymappinglesion-relateddisplacementof connectivity. We will then compare sensitivity and specificity with task-based fMRI mapping and intra-operativeelectrocorticography. Ifsuccessful,thisresearchwillenablemappingofneuralactivityandconnectivityatmuchshortertimescales thancurrentlyfeasible,thusimprovingthecharacterizationofthetemporaldynamicsoffunctionalconnectivity, enhancing the spatial-temporal information obtained from combining fMRI with EEG and MEG and informing about the neurophysiological mechanisms that control brain connectivity and neurovascular coupling. The improved tolerance to slowly varying confounding signals and head movement will have considerable clinical impactforinvestigatingdifficulttoimagepopulations,suchasepilepsy,stroke,Parkinson?sdiseaseandvascular disease.
Recentstudiesusinghigh-speedfMRItechniqueshavedetectedrestingstateconnectivityatfrequenciesas high as 5 Hz in the visual and the motor cortices with significantly higher spatial-temporal stability than the correspondinglowfrequency(<0.1Hz)restingstateconnectivity.Thisapproachhasthepotentialforaddressing principallimitationsofmappinglowfrequencyrestingstateconnectivity,suchashighsensitivitytosignaldrifts and long time scales necessary for separating major resting state networks. However, the existence of high frequencyconnectivityinthebrainhasbeenquestionedduetoconflictingresultsindifferentstudies. We have recently detected remarkably strong high frequency connectivity in the auditory cortex, both in healthycontrolsandinpatientswithbraintumors,withsensitivityandspatialspecificitythatapproachesthatof conventionallowfrequencyrestingstateconnectivity,usingahigh-speedvolumetricimagingtechniqueanda windowed seed-based connectivity analysis that is tolerant to confounding physiological signal sources and movement artifacts. Our preliminary data also show high frequency connectivity across several other major restingstatenetworks,consistentwithpreviousstudies. The objectives of this study are to (a) characterize the biophysical mechanisms of high frequency connectivity in healthy controls and (b) characterize the physiological basis and clinical potential of high-frequencyconnectivityinpatientswithbraintumors. Ifsuccessful,thisresearchwillenablemappingofneuralactivityandconnectivityatmuchshortertimescales thancurrentlyfeasible,thusimprovingthecharacterizationofthetemporaldynamicsoffunctionalconnectivity, enhancing the spatial-temporal information obtained from combining fMRI with EEG and MEG and informing about the neurophysiological mechanisms that control brain connectivity and neurovascular coupling. The improved tolerance to slowly varying confounding signals and head movement will have considerable clinical impactforinvestigatingdifficulttoimagepopulations,suchasepilepsy,stroke,Parkinson?sdiseaseandvascular disease.
