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
2009
Baseline brain energy supports the state of consciousness
Shulman RG, Hyder F, Rothman DL. Baseline brain energy supports the state of consciousness. Proceedings Of The National Academy Of Sciences Of The United States Of America 2009, 106: 11096-11101. PMID: 19549837, PMCID: PMC2708743, DOI: 10.1073/pnas.0903941106.Peer-Reviewed Original ResearchConceptsLoss of consciousnessBrain energyConscious stateHigh-frequency neuronal activityCerebral energy consumptionBrain energy consumptionCerebral energyEnsembles of neuronsRat brainSomatosensory responsesNeuronal activityGamma-band rangeNeuronal propertiesFiring rateSensory stimulationNeuronal signalingPET measurementsAnesthesiaFMRI patternsFMRI activity patternsOxygen consumptionState of consciousnessStimulationBehavioral abilitiesMagnetic resonance spectroscopy