Alexander Schaefer¹, Ru Kong¹, Evan M. Gordon², Timothy Laumann ³, Simon B. Eickhoff^4,5, Xi-Nian Zuo⁶, Avram J. Holmes⁷, and B.T. Thomas Yeo^1
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.

Fernando Calamante^1,2, Robert Elton Smith¹, Xiaoyun Liang¹, Andrew Zalesky³, and Alan Connelly^1,2
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. 

Joseph R Whittaker¹, Molly G Bright^1,2, Ian D Driver¹, and Kevin Murphy^1
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. 

Ying-Chia Lin¹, Tommaso Gili^2,3, Sotirios A. Tsaftaris ^1,4, Andrea Gabrielli⁵, Mariangela Iorio³, Gianfranco Spalletta³, and Guido Caldarelli^1
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.

Russell W Chan^1,2, Alex TL Leong^1,2, Patrick P Gao^1,2, Y S Chan³, W H Yung⁴, Kevin K Tsia², and Ed X Wu^1,2
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.

Hsin-Yi Lai¹, Hui-Ching Lin^2,3, Yu-Chun Lo⁴, Lun-De Liao^5,6, Wei-Che Wei⁷, and You-Yin Chen^7
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.

Joanes Grandjean¹, Valerio Zerbi², Nicole Wenderoth², and Markus Rudin^1
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.

Jaakko Paasonen¹, Raimo A Salo¹, Jouni Ihalainen², Juuso Leikas², Katja Savolainen², Markus M Forsberg², and Olli Gröhn^1
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.

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.

Chenhao Wang¹, Ju Lynn Ong¹, Amiya Patanaik¹, Juan Zhou^1,2, and Michael W. L. Chee^1
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.