ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore

Scientific Session: fMRI: The Cutting Edge in Connectivity

Tuesday, May 10, 2016
Room 331-332
10:00 - 12:00
Moderators: Kai-Hsiang Chuang, Maria Fernandez-Seara

Cerebral Cortex Parcellation by Fusion of Local and Global Functional Connectivity Feature
Alexander Schaefer1, Ru Kong1, Evan M. Gordon2, Timothy Laumann 3, Simon B. Eickhoff4,5, Xi-Nian Zuo6, Avram J. Holmes7, and B.T. Thomas Yeo1
1Department of Electrical and Computer Engineering, ASTAR-NUS Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Networks Program, National University of Singapore, Singapore, Singapore, 2VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX, United States, 3Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States,4Institut for Clinical Neuroscience, Heinrich Heine University, Düsseldorf, Germany, 5Institute for Neuroscience and Medicine, Research Center Jülich, Jülich, Germany, 6Lab for Functional Connectome and Development, Division of Cognitive and Developmental, Chinese Academy of Sciences, Beijing, China, People's Republic of, 7Department of Psychology, Yale University, New Haven, CT, United States
Current approaches to cerebral cortex parcellation with resting-state functional connectivity MRI (fcMRI) can be divided into local (e.g., fcMRI gradients) and global (e.g., clustering) approaches. Previous work suggests that local and global approaches capture complementary aspects of brain organization. Here we propose a novel hidden Markov Random Field model that fuses local connectivity gradients with global functional connectivity similarities. The resulting parcellation compares favorably with a state-of-the-art parcellation in terms of (1) parcel homogeneity in two different datasets and (2) agreement with cytoarchitectonic and visuotopic boundaries.

Track-weighted dynamic functional connectivity (TWdFC): a new method to study dynamic connectivity
Fernando Calamante1,2, Robert Elton Smith1, Xiaoyun Liang1, Andrew Zalesky3, and Alan Connelly1,2
1The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia, 2Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia, 3Melbourne Neuropsychiatry Centre and Melbourne School of Engineering, The University of Melbourne, Melbourne, Australia
There is great interest in the study of brain connectivity (structural and functional), and on the development of methods that facilitate these investigations. In functional connectivity (FC), there is also growing interest in characterising the dynamic changes (dynamic-FC, dFC). Track-weighted FC (TWFC) was proposed as a means to combine the structural and (static) functional information into a single image, by integrating a functional network with a diffusion MRI tractogram. Here we propose TW-dynamic-FC (TWdFC), by extending TWFC in two ways: first, it does not rely on an a-priori FC network; second, it allows studying dFC. 

Beat-to-beat blood pressure fluctuations are present in time-frequency dynamics of resting-state fMRI
Joseph R Whittaker1, Molly G Bright1,2, Ian D Driver1, and Kevin Murphy1
1CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
A pilot study of fMRI time-frequency dynamics, characterized using a maximal overlap discrete wavelet transform, demonstrates matched frequency correlations with beat-to-beat mean arterial blood pressure fluctuations. Voxel-wise correlations between fMRI and blood pressure wavelet coefficients, on a frequency scale centred at 0.1Hz, reveal distributed and structured spatial variance across the brain. We demonstrate that functional connectivity methods that include time-frequency representations of fMRI data are likely very sensitive to these blood pressure fluctuations. 

A cortical and sub-cortical parcellation clustering by intrinsic functional connectivity
Ying-Chia Lin1, Tommaso Gili2,3, Sotirios A. Tsaftaris 1,4, Andrea Gabrielli5, Mariangela Iorio3, Gianfranco Spalletta3, and Guido Caldarelli1
1IMT Institute for Advanced Studies Lucca, Lucca, Italy, 2Enrico Fermi Centre, Rome, Italy, 3IRCCS Fondazione Santa Lucia, Rome, Italy, 4Institute of Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom, 5ISC-CNR, UOS Sapienza, Dipartimento di Fisica, Universita Sapienza, Rome, Italy
Network analysis of resting-state fMRI (rsfMRI) has been widely utilized to investigate the functional architecture of the whole brain. Here we propose a robust parcellation method that first divides cortical and sub-cortical regions into sub-regions by clustering the rsfMRI data for each subject independently, and then merges those individual parcellations to obtain a global whole brain parcellation. To do so our method relies on majority voting (to merge parcellations of multiple subjects) and enforces spatial constraints within a hierarchical agglomerative clustering framework to define parcels that are spatially homogeneous.

Low Frequency Optogenetic Stimulation of Dentate Gyrus Enhances Brain Functional Connectivity Revealed by Resting-State fMRI
Russell W Chan1,2, Alex TL Leong1,2, Patrick P Gao1,2, Y S Chan3, W H Yung4, Kevin K Tsia2, and Ed X Wu1,2
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, People's Republic of, 2Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, People's Republic of, 3School of Biomedical Sciences, The University of Hong Kong, Hong Kong, China, People's Republic of, 4School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China, People's Republic of
Low frequency coherent rsfMRI signals (<0.1Hz) do not match the bandwidth of established neuronal oscillations, highlighting a gap in our knowledge regarding the neuronal basis of rsfMRI underlying long-range brain networks. In this study, optogenetics and rsfMRI were combined to investigate the neuronal basis of rsfMRI connectivity by probing alternations of brain functional connectivity before, during and after low frequency stimulation in dorsal dentate gyrus. Our results demonstrated that low frequency optogenetic stimulation enhanced brain functional connectivity. This indicated that low frequency neuronal oscillations contribute and underlie the synchronized long-range rsfMRI brain functional networks.

Functional MRI reveals striatal–thalamic connectivity in cognitive neural behavior altered by central thalamic deep brain stimulation
Hsin-Yi Lai1, Hui-Ching Lin2,3, Yu-Chun Lo4, Lun-De Liao5,6, Wei-Che Wei7, and You-Yin Chen7
1Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Zhejiang University, Hangzhou City, China, People's Republic of, 2Department and Institute of Physiology, National Yang-Ming University, Taipei, Taiwan, 3Brain Research Center, National Yang Ming University, Taipei, Taiwan, 4Center for Optoelectronic Biomedicine, National Taiwan University College of Medicine, Taipei, Taiwan, 5Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli County, Taiwan, 6Singapore Institute for Neurotechnology, National University of Singapore, Singapore, Singapore, 7Department of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan
This study demonstrates neuronal striatal–thalamic connectivity modulated by direct stimulating the central thalamus in rats. Our results indicate that the CT-DBS modulate the neuronal activity in bilateral anterior cingulate cortex, caudate-putamen and somatosensory cortex and increases in functional connectivity between the striatum and parafascicular thalamic nucleus, hippocampus and primary motor cortex to shorten the cognitive related behavior task. CT-DBS fMRI has potential to explore functional connectivity in the brain and monitor functional plasticity changes in a specific neuroanatomical pathway in vivo.

The structural basis for supporting functional connectivity in mice
Joanes Grandjean1, Valerio Zerbi2, Nicole Wenderoth2, and Markus Rudin1
1University and ETH Zurich, Zurich, Switzerland, 2ETH Zurich, Zurich, Switzerland
Connectomics holds promise to foster our understanding of the healthy and disordered brain. MRI has been the method of choice for such analysis, combining diffusion weighted with functional imaging to resolve structural and functional connectivity, respectively.  However, both methods are indirect measures prone to bias and artifacts. In mice, structural connectivity has been reconstructed with high spatial resolution by mapping the distribution of viral tracers following local injections at multiple sites offering a unique opportunity to compare functional connectivity with detailed mono-synaptic projections. Such comparisons should help bridging functional and structural connectivity in rodents with implications for human studies.

Characterization of acute phencyclidine-induced dose-dependent schizophrenic symptoms in rat: relationship between functional connectivity, hemodynamic response, behavior, and neurotransmitter levels
Jaakko Paasonen1, Raimo A Salo1, Jouni Ihalainen2, Juuso Leikas2, Katja Savolainen2, Markus M Forsberg2, and Olli Gröhn1
1Department of Neurobiology, University of Eastern Finland, Kuopio, Finland, 2School of Pharmacy, University of Eastern Finland, Kuopio, Finland
Schizophrenia is a disorder that lack effective medication. In order to improve treatments, better disease models are required. Here, phencyclidine (PCP)-induced schizophrenic symptoms were investigated in rats with fMRI. Results were compared with microdialysis measurements and behavioral tests. At PCP doses ≥ 3 mg/kg, characteristics for psychotic symptoms were detected in functional connectivity (FC), having good correspondence with locomotor and dopamine activity. With PCP doses ≤ 2 mg/kg, markers for psychotic symptoms were absent. The FC of mesolimbic pathway was still affected, and social and cognitive deficits were confirmed in behavioral tests. Thus, PCP ≤ 2 mg/kg induces specifically the social and cognitive schizophrenic deficits.

ACC GABA levels predict activity and connectivity in the fronto-striatal network during interference inhibition in borderline personality disorder
Guoying Wang1, Julia van Eijk1, Traute Demirakca1, Markus Sack1, Sylvia Cackowski2, Annegret Krause-Utz2, Christian Schmahl2, and Gabriele Ende 1
1Neuroimaging, Central Institute of Mental Health, Mannheim, Germany, 2Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany
By combining the MRS and fMRI technique, we tested whether ACC GABA levels would predict the activity and connectivity in fronto-striatal networks during interference inhibition (Simon task) in BPD patients. BPD patients showed a significant positive correlation between ACC GABA levels and BOLD responses in fronto-striatal regions during interference inhibition. Additionally, ACC GABA levels in BPD patients were positively related to ACC-caudate functional connectivity during the incongruent condition. Our findings highlight that the GABAergic system in the ACC plays an important role in the modulation of impulsivity via regulating the local neural activity and remote connectivity between key regions.

Fluctuations in Functional Connectivity Predict Shifts in Arousal State
Chenhao Wang1, Ju Lynn Ong1, Amiya Patanaik1, Juan Zhou1,2, and Michael W. L. Chee1
1Neuroscience and Behavioral Disorders Program, Duke-NUS Graduate Medical School Singapore, Singapore, Singapore, 2Clinical Imaging Research Center, Agency for Science, Technology and Research, Singapore, Singapore
To elucidate relationship between fluctuation in functional connectivity and behavior we estimated dynamic connectivity states (DCS) from task-free fMRI obtained from sleep-deprived healthy young adults. Using spontaneous eye closures as a proxy for vigilance, we identified two DCS that were associated with high and low arousal respectively. DCS exhibiting similar connectivity patterns were also observed when individuals were performing an auditory vigilance task. Dwell time in high or low arousal DCS predicted task performance. Additionally, fluctuations in DCS and task response time were correlated. Fluctuations in functional connectivity appear to be related to spontaneous changes in arousal that affect vigilance.

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