2024
In vivo neuropil density from anatomical MRI and machine learning
Akif A, Staib L, Herman P, Rothman D, Yu Y, Hyder F. In vivo neuropil density from anatomical MRI and machine learning. Cerebral Cortex 2024, 34: bhae200. PMID: 38771239, PMCID: PMC11107380, DOI: 10.1093/cercor/bhae200.Peer-Reviewed Original ResearchConceptsMagnetic resonance imagingSynaptic densityNeuropil densityCellular densityArtificial neural networkNeural networkPositron emission tomographyAnatomical magnetic resonance imagingHealthy subjectsSynaptic activityMRI scansMachine learning algorithmsBrain's energy budgetEmission tomographyIn vivo MRI scansResonance imagingTissue cellularityLearning algorithmsDiffusion magnetic resonance imagingMachine learningMicroscopic interpretationInterpretation of functional neuroimaging dataIndividual predictionsSubjects
2012
Quantitative fMRI and oxidative neuroenergetics
Hyder F, Rothman DL. Quantitative fMRI and oxidative neuroenergetics. NeuroImage 2012, 62: 985-994. PMID: 22542993, PMCID: PMC3389300, DOI: 10.1016/j.neuroimage.2012.04.027.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingNeuronal activityQuantitative functional magnetic resonance imagingTotal neuronal activityBlood oxygenation level-dependent (BOLD) signalBrain energy metabolismResting-state paradigmLevel-dependent signalMagnetic resonance imagingSynaptic activityResonance imagingParamagnetic contrast agentFunctional brainBOLD contrastBaseline stateEnergy metabolismFunctional mapsContrast agentsMagnetic resonance spectroscopyFMRI dataRegion of interestActivityNeuroenergeticsBrain