Bruno Miguel de Brito Robalo^1,2, Alberto de Luca^1,2, Christopher Chen³, Anna Dewenter⁴, Marco Duering⁵, Saima Hilal³, Huiberdina L. Koek⁶, Anna Kopczak⁴, Bonnie Yin Ka Lam⁷, Alexander Leemans², Vincent Mok⁷, Laurien P. Onkenhout¹, Hilde van den Brink¹, and Geert Jan Biessels^1
1Neurology, Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands, ²Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands, ³Memory, Aging and Cognition Center, Department of Pharmacology, National University of Singapore, Singapore, Singapore, ⁴Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany, ⁵Medical Image Analysis Center (MIAC) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland, ⁶Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, Netherlands, ⁷Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, The Netherlands 7Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong

We investigated if network thresholding and diffusion MRI (dMRI) harmonization improve a) cross-site consistency of network architecture and b) precision and sensitivity to detect network connections disrupted in cerebral small vessel disease (SVD). Brain networks were reconstructed from dMRI in five cohorts. Consistency of network architecture was examined in age-matched controls whereas sensitivity and precision to detect disrupted connections was assessed in sporadic SVD patients. Network consistency, as well as sensitivity and precision to detect disrupted connections were improved by thresholding and harmonization. We recommend using these techniques in networks studies of SVD to leverage existing multicentre datasets.

Yixin Ma^1,2, Trong-Kha Truong^1,2,3, Iain P. Bruce^1,4, Alexandra Badea^1,2,3,4, Simon Davis⁴, Chun-Hung Yeh⁵, Jeffrey R. Petrella^1,2,3, and Allen W. Song^1,2,3
1Brain Imaging and Analysis Center, Duke University, Durham, NC, United States, ²Medical Physics Graduate Program, Duke University, Durham, NC, United States, ³Department of Radiology, Duke University, Durham, NC, United States, ⁴Department of Neurology, Duke University, Durham, NC, United States, ⁵Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan

The hippocampus plays an essential role in memory; the impairment in intra-hippocampal connectivity could result in memory loss in neurodegenerative dementias. We generate intra-hippocampal fiber tracts and connectomes from submillimeter isotropic DTI images for repeated scans from the same subjects and across different subjects. We characterize the fiber orientations and connectivity across hippocampal subfields by registering all in vivo scans onto the population template and we compare these results with those from an ex vivo human brain sample. This method can assess intra-hippocampal connectivity in vivo, which could be potentially used to diagnose neurodegenerative diseases.

Zifei Liang¹, Tanzil Mahmud Arefin¹, Choong Heon Lee¹, and Jiangyang Zhang^1
1NYU Langone Health, New York, NY, United States

Although dMRI tractograophy has been successfully used to examine brain connectivity, its limitation, mainly in specificity, has also been reported. In this study, we generated a comprehensive mouse brain streamline database based on 2700+ viral tracer data from Allen Institute. The database was used as a ground truth to train a deep learning network to estimate fiber orientations from diffusion MRI data of the mouse brain. Compared to conventional methods, the deep learning network provided more accurate estimation of fiber orientation leading to improved tractography.

Paul B Camacho^1,2,3,4, Nishant Bhamidipati^1,5, Emily Erlenbach⁶, Veronica Garcia⁶, Edward McAuley^1,6, Nicholas Burd⁶, Jessica Damoiseaux^7,8, Brad P Sutton^1,2,5, and Neha P Gothe^1,6
1Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ²Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ³Interdisciplinary Health Sciences Institute, University of Illinois at Urbana Champaign, Urbana, IL, United States, ⁴Carle-Illinois Advanced Imaging Center, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁵Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁶Kinesiology & Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁷Institute of Gerontology, Wayne State University, Detroit, MI, United States, ⁸Psychology, Wayne State University, Detroit, MI, United States

We present a moderation analysis of the effects of edge strengths from generalized q-sampling imaging-based tractography on the relationship between age and decline in functional fitness in older adults (n = 105, ages 55-79 years old, right-handed). The results of these moderation analyses suggest that the strengths of white matter structural connections involving the cerebellum, cingulum, and other areas involved in motor, sensory, and environmental perception may play a significant role in preserving functional fitness in older adults.

Kavita Singh¹, Maria Guadalupe Garcia Gomar^1,2, Simone Cauzzo^1,3,4, and Marta Bianciardi^1,5
1Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, United States, ²National Autonomous University of Mexico, Mexico, Mexico, ³Sant'Anna School of Advanced Studies, Institute of Life Sciences, Pisa, Italy, ⁴Research Center E. Piaggio, University of Pisa, Pisa, Italy, ⁵Division of Sleep Medicine, Harvard University, Division of Sleep Medicine, Boston, MA, United States

The connectivity of lateral and medial geniculate nuclei with cortical and sub-cortical areas involved in visual and auditory functions is known in humans, yet their recently postulated connectivity with neuromodulatory, visceral and sensory brainstem nuclei is understudied. This is due to limited resolution of clinical scanners and lack of brainstem atlas in living humans. To this end, we applied our recently developed in-vivo atlas of brainstem and diencephalic nuclei to 7 Tesla HARDI and resting-state fMRI, and mapped structural and functional connectomes of lateral and medial geniculate nuclei with brainstem nuclei along with cortical and sub-cortical regions.

Simone Cauzzo^1,2,3, Maria Guadalupe Garcia Gomar^3,4, Kavita Singh³, and Marta Bianciardi^3,5
1Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy, ²Research Center E. Piaggio, University of Pisa, Pisa, Italy, ³Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging (MGH), Charlestown, MA, United States, ⁴Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Queretaro, Mexico, ⁵Division of Sleep Medicine, Harvard University, Boston, MA, United States

The hypothalamus and nucleus accumbens promote respectively wakeful arousal and sleep, producing a stable cycle between states. The hippocampus is inherently connected to this cycle, which modulates memory encoding during wakefulness and sleep. While their connectivity to cortical regions is detailed in literature, their connectivity with brainstem nuclei is understudied in living humans.

By using high spatial resolution 7 Tesla resting state fMRI and an in-vivo brainstem nuclei atlas, we provided a functional connectome of hypothalamus, nucleus accumbens and hippocampus with the rest of the brain, including 58 brainstem nuclei along with 148 cortical and 25 subcortical structures.

Patricia Pais-Roldan¹, Shukti Ramkiran^1,2, Seong Dae Yun¹, and Jon N. Shah^1,3,4,5
1INM-4, Forschungszentrum Juelich, Juelich, Germany, ²Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany, ³INM-11, Forschungszentrum Juelich, Juelich, Germany, ⁴Translational Medicine, JARA-BRAIN, Aachen, Germany, ⁵Department of Neurology, RWTH Aachen University, Aachen, Germany

We assessed resting-state fMRI acquired with high spatial resolution with a dynamic functional connectivity analysis involving multiple cortical ROIs and depths. Two states relevant to the normalized global laminar connectivity were identified in healthy volunteers (superficial vs. deep layer connectivity predominance). Mean laminar connectivity states were much more dynamic than the states identified in a routine ROI-based dynamic connectivity analysis, suggesting the potential of high-spatial-resolution fMRI to reveal time-varying features in the human brain.

Meng Li^1,2, Mohamad Habes³, and John Detre ^1
1Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States, ²College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China, ³Biggs Alzheimer’s Institute, University of Texas San Antonio, San Antonio, TX, United States

White matter hyperintensities (WMH) are commonly seen in older adults and are associated with an increased risk of cognitive decline and dementia, though the mechanism by which WMH cause cognitive decline are incompletely characterized. In this study, we estimated changes in the structural connectome due WMH with aging using WMH lesion frequency maps derived from a population based study as regions of avoidance for DTI tractography on healthy subject DTI data. We found that subcortical connections to frontal cortex are affected in the 50’s and 60’s, with more widespread disconnection increasing more rapidly in the 70’s and 80’s. However, even in the oldest subjects, most edges were only partially disconnected.

Yakun Zhang¹, Shichun Chen¹, Zongpai Zhang¹, Wenna Duan¹, Li Zhao², George Weinschenk¹, Wen-Ming Luh³, Adam Anderson⁴, and Weiying Dai^1
1Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, United States, ²College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, ³National Institute on Aging, National Institutes of Health, Baltimore, MD, United States, ⁴Department of Human Development, Cornell University, Ithaca, NY, United States

The effect of meditation on brain functional activation when engaged in an attention task was evaluated longitudinally using dASL and BOLD fMRI in nine healthy subjects. Functional activation before and after meditation practice was compared and the change of functional activation was correlated with practice time. Using dASL, functional activation in the occipital region was significantly reduced; more practice time was associated with more reduced activation in the mediofrontal, temporal, and precuneus regions. Using BOLD fMRI, no significant activation was found. The findings suggest that dASL has superior performance in detecting task performance and that meditation can improve brain efficiency.

Yu-Chieh Hung¹, Yi-Cheng Wang¹, Hao-Li Liu², and Hsu-Hsia Peng^1
1Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, ²Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan

Non-invasive focused ultrasound (FUS) offered attractive advantages to modulate neuronal activity. The functional connectivity (FC) between different brain regions is a dynamic process during a period of examinations. We aimed to explore the longitudinal effect of FUS-neuromodulation on secondary visual cortex lateral area (V2L) by dynamic FC. We assessed k-means analysis and dynamic network analysis of dynamic FC of Pre-FUS, Sham, 35-min, 3-hr, and 3-day after FUS sonication at V2L. We found the instant effect of FUS-neuromodulation (35-min) and the recovery in a longitudinal follow-up of 3-day, suggesting the potential usefulness of FUS-neuromodulation.

Wenwu Sun¹, William Reeves¹, Madison Fagan², Christina Welch², Kelly Scheulin², Sydney Sneed², Franklin West², and Qun Zhao^1
1Department of Physics and Astronomy, University of Georgia, Athens, GA, United States, ²Regenerative Bioscience Center and Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States

Traumatic brain injury (TBI) can lead to dynamic changes in functional network activity that can be assessed by functional magnetic resonance imaging (fMRI). In this study, we utilized a novel temporal correlation analysis approach to evaluate a novel microbiome transplantation treatment effect on network connectivity in a translational porcine. Sparse dictionary learning (sDL) and independent component analysis (ICA) were applied to both a full dataset (TBI and sham) and the Sham-only dataset, resulting in four groups of results. Consistency was observed across the four results, indicating that evaluation of treatment effects can be achieved through the proposed temporal correlation analysis. 

Suk-tak Chan¹ and Kenneth Kwong K Kwong^1
1Martinos Center, Radiology, Massachusetts General Hospital, Charlestown, MA, United States

A preliminary comparison of physiological and fMRI data from an experienced meditator during mindfulness, paced breathing at 6 breaths/min, and spontaneous breathing provided several characteristic findings related to the brain-body mechanisms of mindfulness: 1) a reduction of breathing rate together with indicators of improved respiratory gas exchange (RGE); 2) a significant correlation between the temporal oscillation of RGE metrics and cerebral hemodynamic fluctuations (CHF) in regions within the salience and default mode networks; 3) a difference in the coherence of CHF with RGE and with heart cycle duration (NN).