ISMRM 21st Annual Meeting & Exhibition ○ 20-26 April 2013 ○ Salt Lake City, Utah, USA
SCIENTIFIC SESSION
fMRI in Brain Disorders Wednesday 24 April 2013
Room 151 AG | 16:00 - 18:00 | Moderators: | Alberto Bizzi, Kirk Welker
16:00 | 0519. | Disrupted Network Interactions in Chronic Cocaine Dependents as Revealed by Modular Network Analysis of Resting-State Functional MRI Xia Liang1,2, Hong Gu1, Betty Jo Salmeron1, Yuzheng Hu1, Yong He2, Elliot Stein1, and Yihong Yang1 1Neuroimaging Research Branch, National Institute on Drug Abuse, Baltimore, Maryland, United States, 2State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, Beijing, China To examine the alterations in network-level interactions following chronic use of cocaine, we combined modular network analysis based on graph theory and resting-state fMRI technique. We observed significantly decreased inter-module connectivity among the default mode, salience and emotional networks in cocaine dependents. Moreover, we found that the intra-module connectivity within the salience module showed significantly negative correlation with difficulty of describing feelings in cocaine dependents. Our results demonstrate that cocaine addiction is associated with disruptions of network-level interactions, which may provide novel insights into the neurobiological mechanisms of cocaine addiction.
16:12 | 0520. | Identification of Neural Connectivity Signatures of Autism Using Machine Learning Gopikrishna Deshpande1,2, Karthik Ramakrishnan Sreenivasan1, Hrishikesh Deshpande3, and Rajesk K. Kana4 1AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, United States, 2Department of Psychology, Auburn University, Auburn, AL, United States, 3Department of Biomedical Engineering, University of Alabama, Birmingham, AL, United States, 4Department of Psychology, University of Alabama, Birmingham, AL, United States The current study focuses on effective connectivity (EC) in autism, demonstrating the use of machine learning for identification of metrics which can be used to predict a novel subject’s group membership. fMRI time-series were de-convolved using a cubature Kalman filter and the resultant neuronal variables were input into a multivariate autoregressive model (MVAR) to obtain the EC paths. These metrics were then input into a recursive cluster elimination based support vector machine (RCE-SVM) classifier which showed a prediction accuracy of 94.3% based only on causal connectivity weights indicating that EC could serve as a potential non-invasive neuroimaging biomarker for autism.
16:24 | 0521. | Real-Time fMRI Neurofeedback Training of Amygdala Modulates Frontal EEG Asymmetry in MDD Patients Vadim Zotev1, Han Yuan1, Masaya Misaki1, Raquel Phillips1, Kymberly D. Young1, and Jerzy Bodurka1,2 1Laureate Institute for Brain Research, Tulsa, OK, United States, 2College of Engineering, University of Oklahoma, Tulsa, OK, United States We have performed the first study utilizing real-time fMRI neurofeedback (rtfMRI-nf) with simultaneous EEG to explore electrophysiological correlates of rtfMRI-nf training. Eleven MDD patients learned to self-regulate their left amygdala activation using rtfMRI-nf during positive emotion induction task based on retrieval of happy autobiographical memories. We observed task-dependent variations in frontal alpha EEG asymmetry that correlated with fMRI activation in left parahippocampal gyrus area including left amygdala. Our results suggest that frontal asymmetry-based EEG neurofeedback may naturally complement rtfMRI-nf in training of emotional self-regulation, and may enhance the therapeutic value of rtfMRI-nf for major neuropsychiatric disorders, particularly depression.
16:36 | 0522. | Ultra-Fast fMRI Reveals High-Frequency Fluctuations in Response to Neuronal Discharges Pierre LeVan1, Julia Jacobs2, Vasumathi Jayakumar1, and Jürgen Hennig1 1Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Baden-Württemberg, Germany, 2Neuropediatrics and Muscular Diseases, University Medical Center Freiburg, Freiburg, Baden-Württemberg, Germany FMRI hemodynamics are generally assumed to be prolonged and slow-varying at timescales of several seconds and can thus be adequately sampled at conventional fMRI temporal resolutions of 2-3 seconds. In contrast, the current study investigates high-frequency (>0.5Hz) fMRI fluctuations measured by the whole-brain ultra-fast MR-encephalography (MREG) sequence (100ms temporal resolution), following epileptic discharges recorded by EEG. In 67% of the analyzed spike types, a cluster of voxels showing significant high-frequency fluctuations following the spikes could be identified in brain regions concordant with the spike field. MREG opens up new avenues for the localization of neuronal activity with high spatiotemporal resolution.
16:48 | 0523. | A NRG1 Genetic Variant Associated with Decreased Activation in Verbal Working Memory in Patients with Schizophrenia Kayako Matsuo1, Chih-Min Liu2, Shen-Hsing Annabel Chen3, Hai-Gwo Hwu2, and Wen-Yih Isaac Tseng1 1Advanced Biomedical MRI Lab, Center for Optoelectronic Biomedicine, National Taiwan University College of Medicine, Taipei, Taipei, Taiwan, 2Department of Psychiatry, National Taiwan University Hospital & College of Medicine, Taipei, Taipei, Taiwan, 3Division of Psychology, School of Humanities and Social Sciences, Nanyang Technological University, Singapore, Singapore, Singapore NRG1 is a susceptibility gene for schizophrenia. Brain activation was compared during fMRI between promoter SNP (NRG1-P3) risk carriers and non-carriers in schizophrenia and controls using a Sternberg verbal working memory task. We performed a group (patients vs. controls) by risk (with or without risk allele) ANOVA in 4 groups (20 each) and found a marked activation decrease in the thalamus and cerebellum only in patients with risk allele. In contrast, risk carriers in general had increased "deeactivation" in DMN. This is the first neuroimaging study showing that a NRG1 promoter genetic variant is associated with working memory in schizophrenia.
17:00 | 0524. | Involvement of Cerebellum in the Dopaminergic Treatment of Parkinson’s Disease: A Resting-State fMRI Study Stefan Holiga1, Karsten Mueller1, Harald E. Möller1, Gabriele Lohmann1, Tomáš Sieger2,3, Josef Vymazal4, Filip Ruzicka2,5, Dušan Urgošík5, Matthias L. Schroeter1,6, Evzen Ruzicka2, and Robert Jech2 1Max Planck Institute for Human Cognitive and Bran Sciences, Leipzig, Germany, 2Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University in Prague, Prague, Czech Republic, 3Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic, 4Department of Radiology, Na Homolce Hospital, Prague, Czech Republic, 5Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Prague, Czech Republic, 6Clinic for Cognitive Neurology, University of Leipzig, Leipzig, Germany In this work, the effect of levodopa was tested on 24 patients suffering from Parkinson’s disease (PD). We used a novel, model-free method based on eigenvector centrality to reveal the changes of connectivity patterns following the dopaminergic challenge, using resting-state functional magnetic resonance imaging. We observed major alterations in connectivity between cerebellum and other key regions responsible for motor control, such as substantia nigra, subthalamic nucleus, putamen, thalamus, but also cerebellum itself. Thus, we demonstrate that levodopa modulates the connectivity in motor networks affected by PD. Additionally to striato-thalamo-cortical system, also cerebello-thalamic loops deserve significant attention in PD research.
17:12 | 0525. | Retinotopic-Specific Changes of Cerebral Blood Flow and Grey Matter in Visual Cortex of Patients with Glaucoma Bo Wang1, Shaodan Zhang2,3, Y Xie2, Ningli Wang2, Chun Zhang3, Xiaohong Joe Zhou4, and Yan Zhuo1 1State Key Lab of Brain & Cognitive Science, Institute of Biophysics, Chinese Academy of China, Beijing, Beijing, China, 2Beijing Tongren Hospital affiliated to Capital Medical University, Beijing, Beijing, China, 3Peking University Third Hospital, Beijing, Beijing, China, 4University of Illinois Medical Center at Chicago, Chicago, Illinois, United States Differences were observed in blood flow, morphology and metabolites in the visual cortex between POAG (patients with primary open angle glaucoma) patients and age-matched normal controls, suggesting that rCBF and/or VBM may be used as a specific and sensitive marker in assessing brain injury in glaucoma patients.
17:24 | 0526. | Transfer Function of the Resting State: A Novel Approach to Assess Optic Neuritis Samiul Hayder Choudhury1, Michael Richard Smith1,2, Bradley Goodyear2, and Fiona Costello3 1Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada, 2Department of Radiology, University of Calgary, Calgary, Alberta, Canada, 3Department of Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada Reliable imaging biomarkers can be developed using Optic Neuritis (ON) as a system model which are essential for advanced treatment and pathology of Multiple Sclerosis. We propose an approach of differentiating healthy persons from ON patients by transfer function analysis between brain regions that are correlated in optical activity during resting state. We provide receiver operator characteristic analysis results on various transfer function metrics and compare the results with existing outcomes. Our analysis suggests that with proper choice of threshold and decision metrics we can better differentiate subject groups for both lower and higher order visual information propagation.
17:36 | 0527. | Characterization of Structural and Functional Brain Impairment and Phenotypic Association in Autism Spectrum Disorder Yongxia Zhou1, Xi-Nian Zuo2, Daniel K. Sodickson1, Yulin Ge1, Michael P. Milham3, Robert I. Grossman4, and Yvonne W. Lui1 1Radiology/Center for Biomedical Imaging, New York University Langone Medical Center, New York, NY, United States, 2Psychology, Chinese Academy of Sciences, Beijing, Beijing, China, 3Child Mind Institute, New York University Langone Medical Center, New York, NY, United States, 4Radiology/Center for Biomedical Imaging, New York University, New York, NY, United States We aim to study the structural and functional connectivity changes of two primary sub-segments of inferior frontal gyrus (IFG) which contain the motor neurons and the subcortical caudate regions in children with autism spectrum disorder (ASD). Data were downloaded from a multi-center Functional Connectome Project including structural and functional MRI data; with a total of 79 children with ASD and 105 age-matched typically developing children. Results showed brain atrophy in IFG, and abnormal caudate and IFG functional connectivity and reduced neuronal activity (via fractional amplitude) in children with ASD. There were significant correlations between fMRI metrics and multiple phenotypic data.
17:48 | 0528. | Frequency Distribution of Enhanced Sensorimotor Network in Stroke-Recovered Rat Woo Shim1, Ji-Yeon Suh1,2, Jeong Kon Kim2, Bruce Rosen1, and Young Kim1 1Massachusetts General Hospital, Charlestown, Ma, United States, 2Asan Medical Center, Seoul, Seoul, Korea Resting-state fMRI (rs-fMRI) has emerged as an important method for non-invasively assessing evolution of neural networks. Using rs-fMRI, the current work shows that the concomitant reshaping of the causal connectivity in the frequency-domain accompanies the stroke-recovery process.