Rodolfo Abreu¹, Marco Simões^1,2, and Miguel Castelo-Branco^1
1Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal, ²Center for Informatics and Systems (CISUC), University of Coimbra, Coimbra, Portugal

Resting-state networks (RSNs) have been identified on continuous source-reconstructed EEG data (electrical source imaging; EEG-ESI data), but their validation with simultaneous fMRI data is missing. Here, we found a comparable overlap with previous literature between EEG-ESI-derived RSNs and simultaneous fMRI-derived RSNs from 10 subjects. We showed the ability of EEG-ESI to map the task-specific facial expression processing network, and extracted dynamic functional connectivity (dFC) states from EEG-ESI and fMRI, founding a significant match between them. Our results push the limits of EEG towards being used as an imaging tool and support the existence of EEG correlates of fMRI-derived (d)FC.

Yawara Haga^1,2,3, Junichi Hata^2,3,4, Takaaki Kaneko^2,5, Tatsuhiko Yamada⁶, Yuji Komaki³, Fumiko Seki^2,3,5, Hideyuki Okano^2,5, Hirotaka James Okano⁴, Tetsuo Yamamori², Noritaka Ichinohe^2,7, Yuichi Yamashita⁷, Akira Furukawa¹, and Misako Komatsu^2,7
1Department of Radiological Sciences, Human Health Sciences, Tokyo Metropolitan University Graduate School, Tokyo, Japan, ²RIKEN Center for Brain Science, Saitama, Japan, ³Live Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan, ⁴Division of Regenerative Medicine, The Jikei University School of Medicine, Tokyo, Japan, ⁵Department of Physiology, Keio University School of Medicine, Tokyo, Japan, ⁶Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka, Japan, ⁷National Center of Neurology and Psychiatry, Tokyo, Japan

We explored the resting-state functional network of awake common marmoset by functional MRI (fMRI) and electrocorticographic (ECoG). As a result, a visual cortex network, a somatomotor network, a default mode network and a striatum network were detected in functional connectome analysis. In addition, some resting-state networks that were observed in the previous studies were detected in ICA. Those resting-state networks were also observed in ECoG data. Therefore, we conclude that fMRI and ECoG data were almost consistent.

Nicole Yuen^1,2, Fred Tam², Nathan Churchill³, Tom Schweizer³, and Simon Graham^1,2
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, ²Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, ³St. Michael's Hospital, Toronto, ON, Canada

This study sheds further light on the neural correlates of driving behaviour and distracted driving, an important road-safety issue. Functional MRI and simultaneous eye-tracking measurements are performed during simulated driving tasks with and without auditory distraction. Initial results are consistent with previously published fMRI findings, showing changes in the occipital lobes, temporal lobes and frontal regions that are associated with increasing cognitive demand and distraction. These observations, and their interpretation, are consistent with reductions in the gaze field-of-view and increases in pupil diameter that reflect how the brain deals with cognitive challenges during realistic driving scenarios.  

MARCO SIMOES¹, Rodolfo Abreu², Bruno Direito², Alexandre Sayal², Joao Castelhano², Paulo Carvalho³, and Miguel Castelo-Branco^2
1CIBIT, Coimbra Institute for Biomedical Imaging and Translational Research, Faculty of Medicine, University of Coimbra, COIMBRA, Portugal, ²CIBIT, University of Coimbra, Coimbra, Portugal, ³CISUC, University of Coimbra, Coimbra, Portugal

fMRI is the neuroimage modality of choice when considering localized neurofeedback applications. However, the high costs and inflexibility of MRI setups limit their widespread application, motivating their transfer to EEG setups by reconstructing the BOLD-fMRI signal at the target regions using EEG only. Here, we systematically investigated the extent at which the BOLD-fMRI signal at the facial expressions processing network could be reconstructed from simultaneously recorded EEG signals. Features from both scalp and source spaces were extracted and used as predictors in a regression problem using random forests. We improved the accuracy of the state-of-the-art method from 20% to 53%.

Xiaodi Zhang¹, Wen-Ju Pan¹, and Shella Dawn Keilholz^1
1Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, United States

We implemented a stacked long short-term memory neural network to predict the blood-oxygenation-level dependent signal from the band-limited power of local field potentials in a variety of frequencies. The model was trained with simultaneously acquired resting state fMRI and LFP data from rats under Isoflurane anesthesia. The results show that the model prediction has a higher Pearson correlation with the ground truth of BOLD signal than the LFP band-limited power in any frequency bands.

Dirk Ernst Cleppien¹, Felipe Aedo-Jury², Miriam Schwalm³, and Albrecht Stroh^2
1MAIC, German Resilience Center, Mainz, Germany, ²German Resilience Center, Mainz, Germany, ³Massachusetts Institute of Technology, Cambridge, MA, United States

We recently employed optically recorded slow oscillation-associated calcium waves as a linear regressor for simultaneously acquired task-free fMRI revealing a pan-cortical fMRI signature related to the active periods of the slow wave rhythm. Here, we provide a novel analysis pipeline for the synchronization of single events, as obtained by calcium photometry recordings, with fMRI scans usually requiring averaging over multiple trials. This synchronization poses unique problems, such as dealing with the inherent variability of the neurophysiological signal. The pipeline introduced here provides a step-by-step-approach within the framework of fast line scanning fMRI.

Shengwen Deng¹, Dengrong Jiang², Crystal G. Franklin¹, Michael O'Boyle¹, Wei Zhang¹, Betty L. Heyl¹, Paul A. Jerabek¹, Hanzhang Lu², and Peter T. Fox^1
1Research Imaging Institute, UT Health at San Antonio, San Antonio, TX, United States, ²Department of Radiology, Johns Hopkins University, Baltimore, MD, United States

Preliminary test of  using T2 based  CMRO2 measurement to measure aerobic glycolysis in human brain, with combination of TRUST MRI, phase contrast MRI and quantitative FDG PET.  Preliminary quantative comparison and modeling of MR/PET (TRUST-PC-FDG) and PET/PET (O-15/FDG) aerobic glycolysis measurement.

Deepanshi Dabas^1,2, Srishti Keshari^1,3, Pawan Kumar¹, Ardaman Kaur¹, Swati Agrawal¹, Prabhjot Kaur¹, Maria M D'souza¹, and Vijayakumar C^1
1NMR Research centre, Institute of Nuclear Medicine and Allied Sciences, DRDO, New Delhi, India, ²Maharaja Surajmal Institute of Technology, New Delhi, India, ³Banasthali Vidyapith, Rajasthan, India

Understanding neural engagement of Motor imagery facilitates development of various Brain-Computer Interface systems for rehabilitation purposes effectively. This study brings more insights on the neural underpinnings and associated functional connectivity of basal-ganglia, temporal and frontal-parietal regions during both Motor Imagery (MI) and Motor Action (MA) gripping tasks of randomised left, right and both hands movement with fifteen right-handed volunteers, using EEG-engagement index informed fMRI and functional connectivity approach. Functional connectivity analysis of the neural correlates reveal statistically elevated engagement of basal-ganglia, superior temporal gyrus and frontal-parietal regions in imagery, left handed imagery/action and both hand gripping tasks respectively.

Afonso Aires¹, Rodolfo Abreu^1,2, João Jorge^3,4, Joana Cabral⁵, and Patrícia Figueiredo^1
1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico – Universidade de Lisboa, Lisboa, Portugal, ²Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal, ³Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, ⁴Systems Division, Swiss Center for Electronics and Microtechnology (CSEM), Neuchâtel, Switzerland, ⁵Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Minho, Portugal

Functional connectivity has been shown to change over short time scales of seconds to minutes, giving rise to the so-called dynamic functional connectivity (dFC). However, the electrophysiological underpinnings of dFC states remain unclear. We investigate EEG spectral correlates of dFC states using simultaneous EEG-fMRI data, by using a high temporal resolution fMRI acquisition combined with a phase coherence approach for dFC estimation and by computing k-means clustering with a varying number of dFC states. We found an association between high alpha power topographies and specific dFC states, which included regions of the frontoparietal network and the default mode network.

Chun-Xia Li¹, Xiaohuan Gu², Doty Kempf¹, Ling Wei², Shanping Yu^3,4, and Xiaodong Zhang^1,5
1Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States, ²Department of Anesthesiology, Emory University School of Medicine, Atlanta, GA, United States, ³2Department of Anesthesiology, Emory University School of Medicine, Atlanta, GA, United States, ⁴Center for Visual and Neurocognitive Rehabilitation, , Atlanta Veterans Affairs Medical Center, Decatur, GA, United States, ⁵Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States

Rhesus monkeys were used to investigate whether ABS-201 induces similar hypothermia effect in large animals as seen in rodents and how this drug influences the hypothalamus centered limbic functional network. Functional connectivity (FC) between anterior hypothalamus and limbic system was examined by using resting state fMRI (rsfMRI).  It is found that ABS-201 caused significant hypothermia effects in monkeys and significantly decreased hypothalamic FC with limbic regions as well. The findings suggest ABS-201 may have profound effects on the neurobehavior of subjects mediated by the hypothermia and antipsychotic effect.

Cui Ping Mao¹, Quan Xin Yang¹, Qiu Juan Zhang¹, Hong Hong Sun¹, Hua Juan Yang¹, Xiao Qian Zhou¹, and Gui Rong Zhang^1
1Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

It is important to determine and distinguish the mechanisms underlying different types of pain because different drug targets are useful in pain of different origins. Specific low back pain (SLBP) with a recognizable pathology and nonspecific low back pain (NSLBP) are different pain conditions. The amygdala has been linked with the pathophysiology of chronic LBP. However, it is not known whether the amygdala is differentially affected in both conditions. Our study suggested that the amygdala morphology, resting-state functional connectivity and effective connectivity are differentially affected in subjects with SLBP and NSLBP, indicating different brain mechanisms in SLBP and NSLBP.

Alexander M Puckett¹, Zoey Isherwood², Ashley York¹, Catherine Viengkham³, and Branka Spehar^3
1University of Queensland, Brisbane, Australia, ²University of Wollongong, Wollongong, Australia, ³University of New South Wales, Sydney, Australia

Recent advances in fMRI, particularly accelerated image acquisition and ultra-high field (7T), have enabled high-resolution measurements and thus have provided the capability to non-invasively study the organization and function of smaller cortical areas in humans. One such area is primary somatosensory cortex, S1, in which the neuronal processing of tactile information largely occurs. Here we used 7T fMRI to (1) locate and map the fingertip representations in human S1 and then (2) to examine the activity at these locations in response to touching 3D-printed fractal textures. Robust and overlapping activation was seen across both conditions throughout primary somatosensory cortex.

Fuyu Hayashi¹, Mitsuhiro Takeda¹, Naoya Yuzuriha¹, Sosuke Yoshinaga¹, and Hiroaki Terasawa^1
1Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan

Muscone is a compound that contributes to the smell of musk and attracts male mice. When mice are stimulated with muscone, their main olfactory bulb and olfactory cortex are activated, as revealed by immunohistochemistry. It is conceivable that the signals are further transduced in the cerebrum, resulting in the attraction behavior in male mice.  It is important to identify the muscone-evoked activated regions in the whole brain and explore their biological significance. We previously developed a functional MRI method that uses repetitive odor stimulation and independent component analysis. We applied this method to identify the muscone-evoked activated regions.

Clément M. Garin¹, Nachiket N. Nadkarni², Brigitte Landeau^3,4, Jean-Luc Picq^2,5, Gaël Chételat^3,4, Salma Bougacha^3,4, and Dhenain Marc^2,6
1Wake Forest University, Winston Salem, NC, United States, ²Commissariat à l’Energie Atomique et aux Energies Alternatives (CEA), Fontenay aux Roses, France, ³INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Normandie University, UNICAEN, EPHE, Caen, France, ⁴Normandie Univ, UNICAEN, GIP Cyceron, Inserm, Inserm UMR-S U1237, Caen, France, ⁵EA 2027, Université Paris 8, 5 Laboratoire de Psychopathologie et de Neuropsychologie, Saint Denis, France, ⁶UMR 9199, Neurodegenerative Diseases Laboratory, 1 Centre National de la Recherche Scientifique (CNRS), Fontenay-aux-Roses, France, France

Characterizing neuronal networks in animals is critical to further address their evolutions. Here we compared brain networks in humans and in mouse lemurs (Microcebus murinus), one of the more phylogenetically distant primates as compared to humans. Network hubs were split into parietal and frontal clusters in humans, while they were grouped in lemurs. Human’s default mode network (DMN) embedded more hubs than lemur's DMN. Mouse lemur's motor network embedded more hubs than human motor networks. Hubness properties could constitute a lever of evolution to adapt information flux to brain size and/or cerebral function.

Rik Lodevicus Elizabeth Maria Ubaghs¹, Harald Dermutz¹, Roman Böhringer¹, Markus Marks¹, Mehmet Fatih Yanik¹, and Benjamin Friedrich Grewe^1
1Institute of Neuroinformatics University and ETH Zurich, ETH Zurich, Zurich, Switzerland

Characteristics of neural processing such as recurrent signalling, make the definition of functional neural involvement notoriously difficult. This has implications for fMRI interpretation, and especially the relationship between excitatory/inhibitory networks and the BOLD response has not been well studied. Here we provide evidence that there are stimulus-dependent effects on neural processing in the VISp that could explain previously observed differentiation in BOLD polarity. We hypothesize that this is due to local excitatory/inhibitory interactions, and present a novel fiber-photometry setup that allows us to investigate the neural underpinnings of this effect by measuring excitatory and inhibitory activity during fMRI.

Lin Wu¹, Sheng Sang¹, Lauri Lehto¹, Antonietta Canna^1,2, Jun Ma³, Clairice Pearce³, Zihad Nahas⁴, Walter Low³, Silvia Mangia¹, and Shalom Michaeli^1
1Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, ²Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy, ³Department of Neurosurgery, University of Minnesota, Minneapolis, MN, United States, ⁴Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States

Orientation selective deep brain stimulation (OS-DBS) is a flexible strategy to achieve selective stimulation of brain pathways. OS-DBS was used here in rats for stimulating the entorhinal cortex (EC) and the medial septal nucleus (MSN). Stimulating such areas induce neurogenesis in dental gyrus of the hippocampal formation, and can thus be regarded a potential therapy for Alzheimer’s disease (AD). Brain responses during OS-DBS were monitored by MB-SWIFT fMRI at 9.4T. Results demonstrate that different orientations of OS-DBS can modulate and selectively maximize activation of EC/MSN- hippocampal formation networks, and thus hold promise for maximizing neurogenesis and therapy efficacy for AD.  

Basavaraju G Sanganahalli¹, Jyothsna Chitturi², Stella Elkabes³, Peter Herman¹, Fahmeed Hyder¹, and Sridhar S kannurpatti^2
1Radiology and Biomedical Imaging, Yale University School of Medicine, New haven, CT, United States, ²Radiology, RUTGERS-New Jersey Medical School, Newark, NJ, United States, ³Department of Neurological Surgery, RUTGERS-New Jersey Medical School, Newark, NJ, United States

 To assess brain plasticity after a unilateral incomplete cervical spinal cord injury (SCI), a complete neural axis assessment was performed using the adult rat model of cervical SCI at the C2/C3 level. Structural T1 and T2-spinal cord anatomical imaging and resting state BOLD-fMRI (9.4T) of the brain was performed 1 month after SCI in sham and SCI animals. The unilateral SCI induced lesion was discernable from anatomical images. Intrinsic brain activity assessed using functional connectivity density (FCD) mapping of global, short-range and long-range connectivity revealed a significant increase in FCD across SCI animals compared to sham.

Du Juan¹, Zheng Tao¹, Yuan Yi², Wang Zhanqiu¹, Liu Defeng¹, Shi Qinglei³, Wu Shuo¹, Wang Xiaohan¹, and Liu Lanxiang^1
1MRI, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China, ²Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China, ³Siemens Healthcare, MR Scientific Marketing, Beijing, China

In this study, we verified the feasibility of T2 values combined with edema volume changes in evaluating the neuro therapeutic effect of low-intensity transcranial ultrasound stimulation (LITUS) on post-traumatic brain edema with rat model. The neuro therapeutic effect of LITUS was attributed to inhibiting the expression of AQP4 and promoting the removal of β-APP. 

Elizabeth de Guzman¹, Alberto Galbusera¹, Filippo Pisano², Elisa Bellistri², Alexia Stuefer¹, Dania Vecchia³, Massimo De Vittorio^2,4, Ferruccio Pisanello², Tommaso Fellin³, and Alessandro Gozzi^1
1Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy, ²Center for Biomolecular Nanotechnologies, Istituto Italiano di Tecnologia, Arnesano, Italy, ³Optical approaches to brain function, Istituto Italiano di Tecnologia, Genova, Italy, ⁴Dip. di Ingegneria dell’Innovazione, Università del Salento, Lecce, Italy

Optogenetic fMRI is an attractive tool for studying neuronal manipulation dynamics at multiple scales, but currently lacks techniques for network (i.e. mesoscale) level investigations due to the small illumination volume of traditional flat-faced optical fibers. Here we show that a recently developed tapered fiber design allowed simultaneous, artefact-free illumination of large cortico-hippocampal areas. We also demonstrated that low-frequency cortico-hippocampal entrainment resulted in a prominent functional desynchronization of the mouse default mode network. These results support the use of this technique for deconstructing network-scale substrates and probing brain-wide functional network dynamics. 

Guohui Ruan¹, Jiaming Liu¹, Ziqi An¹, Kaibin Wu², Wufan Chen¹, Ed X. Wu³, and Yanqiu Feng^1
1Guangdong Provincial Key Laboratory of Medical Image Processing & Key Laboratory of Mental Health of the Ministry of Education, School of Biomedical Engineering, Southern Medical University, Guangzhou, China, ²School of Biomedical Engineering, Southern Medical University, Guangzhou, China, Guangzhou, China, ³Department of Electrical and Electronic Engineering, Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China, Hong Kong, China

Skull-stripping is an important preprocessing step in functional magnetic resonance imaging (fMRI) research. In fMRI research using rodents, skull-stripping is still manually implemented, and it is very time-consuming. To address this problem, a 3D Attention U-net was trained for automatically extracting mouse brain from fMRI time series. The experimental results demonstrate that the mouse brain can be effectively extracted by the proposed method, and the corresponding fMRI results agrees well with the results with manual skull-stripping.

Henning Matthias Reimann¹, Thomas Getgood², and Thoralf Niendorf^1,3
1Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, ²Unaffiliated, Montreal, QC, Canada, ³Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany

Understanding anesthetic effects in preclinical fMRI is key to produce significant findings. Over the last decades massive amounts of data have been produced on anesthesia, yet major portions lie idle to the community. Here we introduce an open, community driven infrastructure that combines the wiki principle (dynamic creating, correcting, commenting) with a powerful dynamic databank approach (fast and easy search, and network visualization of related findings) on anesthetic effects. OpenMind provides (1) convenient data upload, (2) fast and efficient search and filter functions, (3) embedding of findings in a larger dynamic context, and (4) low maintenance.
 

Nicola Bertolino¹, Daniele Procissi¹, John F Disterhoft², and Craig Weiss^2
1Radiology, Northwestern University, Chicago, IL, United States, ²Physiology, Northwestern University, Chicago, IL, United States

Functional brain plasticity is an important characteristic of the brain and enables an individual to learn and adapt as a result of life experiences. In this study we investigated the reorganization of functional brain networks after eyeblink conditioning in awake rabbits by resting state fMRI. This work builds the foundation for studying pre-clinically how cognitive impairment affects learning processes, its implication on brain capability to adapt and learn, and the possible impact of new therapies.

Yujian Diao¹, Rolf Gruetter¹, and Ileana Ozana Jelescu^1
1Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

Resting state fMRI (rs-fMRI) is a widely used technique for identifying resting state networks (RSNs) and investigating brain disorders.  However, the characterization of RSNs can be seriously hindered by the presence of random and structural noise in the measured fMRI signal. Most tools that correct for these effects are tailored for human brain and are not readily transposable to rat data. Here we propose a data processing pipeline for rat rs-fMRI data which can robustly remove artefacts and clean the rs-fMRI data. We report the performance of the pipeline for analyzing rat RSNs and discriminating between control and disease groups.

Hyun-Ji Shim^1,2, Yoonsun Yang¹, Gunsoo Kim¹, and Seong-Gi Kim^1,2,3
1Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon-si, Korea, Republic of, ²Department of Health Science and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University (SKKU), Seoul, Korea, Republic of, ³Department of Biomedical Engineering, Sungkyunkwan University (SKKU), Suwon-si, Korea, Republic of

BOLD fMRI is ideal for investigating neural plasticity of transgenic mouse lines. Visual and somatosensory functions can be reorganized following deafness in the early stage and adult in humans and animals. However, the extent of the neural plasticity remains unclear. To determine how deafness affects other sensory areas, 9.4T BOLD fMRI of sensory stimulation was measured before and after deafening in transgenic adult mice. The impact of scanner noise to evoked responses was also investigated in wild-type mice. Our results suggest that the sensory loss in one modality affects other sensory activities.

Wen-Ju Pan¹, Vahid Khalilzad Sharghi¹, Xiaodi Zhang¹, and Shella Keilholz^1
1Emory University/Georgia Institute of Technology, Atlanta, GA, United States

Different anesthetic states and sedation may have varying contributions to BOLD from physiological background noise that may challenge a comparison across brain states. Little is known on brain functional organization between anesthesia and sedation. We used a scan strategy optimized to minimize impact from physiological background noise to examine the effects of different anesthetics on functional connectivity (FC). Our results demonstrate distinct FC patterns across anesthesia depth transition and sedation, providing insight into potential brain mechanisms of unconsciousness that include global modulation of functional connectivity by isoflurane, and distant functional connectivity impairment in dexmedetomidine.