Yury Koush¹, Robin A. de Graaf¹, Ron Kupers², Laurence Dricot³, Maurice Ptito⁴, Kevin Behar¹, Douglas L. Rothman¹, and Fahmeed Hyder^1
1Yale University, New Haven, CT, United States, ²University of Copenhagen, Copenhagen, Denmark, ³University of Louvain, Louvain, Belgium, ⁴School of Optometry, Montreal, QC, Canada

Functional MRI using blood oxygenation level dependent (BOLD) contrast identifies brain regions for task-induced (de)activation paradigms. We investigated the metabolic basis of these paradigms in activated (visual cortex, VC) and deactivated (posterior cingulate cortex, PCC) network nodes using concurrent acquisitions of J-edited lactate/GABA(γ-aminobutyric acid)/Glx(pooled glutamate and glutamine) and diffusion-weighted BOLD signal. In VC, we detected increased BOLD/lactate/glutamate, and decreased GABA, whereas in PCC BOLD decreased, GABA increased but lactate/glutamate did not change. These results suggest that BOLD responses in (de)activated areas is regulated by relatively rapid GABAergic inhibition, whereas aerobic glycolysis and glutamatergic activity dominate in activated nodes.

Jingyuan E Chen^1,2, Nina E Fultz¹, Jonathan R Polimeni^1,2, Ciprian Catana^1,2, Bruce R Rosen^1,2, Laura D Lewis³, and Christin Y Sander^1,2
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, ²Radiology, Harvard Medical School, Boston, MA, United States, ³Biomedical Engineering, Boston University, Boston, MA, United States

In this study, we investigated the feasibility of integrating simultaneous fMRI and functional PET to uncover metabolic and hemodynamic changes linked with arousal. Our findings suggested that this multi-modal toolset can reliably detect brain-wide hemodynamic and metabolic changes spanning “alert”, “drowsy” and “sleep” conditions, therefore holding great promise in disentangling arousal-induced neuronal and vascular dynamics in future investigations. 

Pinar S Ozbay¹, Catie Chang², Jacco A de Zwart¹, Peter van Gelderen¹, and Jeff Duyn^1
1NINDS, NIH, Bethesda, MD, United States, ²Vanderbilt University, Nashville, TN, United States

During light-sleep, strong correlations were observed between fMRI and peripheral signals. This can be inferred from the fingertip pulse-oximeter signal as a proxy for sympathetic activity. Sympathetic activity may also affect fMRI during wake. In this work, we analyzed data collected during cognitive tasks and deep breathing, showed strong spatio-temporal relations between pupil behavior, skin vascular tone, and fMRI signal. We demonstrate that sympathetic activity can be elicited by a variety of stimuli, that those additional measures might be useful for physiological regression and to better distinguish neuronal and autonomic contributions, which are mostly observed as anti-correlation patterns in fMRI.

Jiayue Cao¹, Xiaokai Wang¹, Kun-Han Lu², Zhenjun Tan³, Robert Phillips³, Deborah Jaffey³, Terry Powley³, and Zhongming Liu^1,2
1Biomedical Engineering, Purdue University, West Lafayette, IN, United States, ²Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States, ³Psychological Science, Purdue University, West Lafayette, IN, United States

The origins of fMRI in the resting state has been widely explored but yielded incomplete knowledge. Here, we hypothesize that gastric activity contributes to intrinsic brain activity observed with fMRI.We explored the gut-brain synchrony in rats by recording the electrogastrogram together with fMRI.  We found that brainactivity is intrinsically synchronized with gastric activity at a specific resting state network in which the BOLD activity is time-locked to gastric activity with varying time delays. 

Li-Ming Hsu^1,2,3,4, Esteban Oyarzabal^1,3,4, Manasmita Das^1,3,4, Tzu-Hao Harry Chao^1,3,4, Sheng Song^1,3,4, Yu-Wei Chen⁵, Dinggang Shen², Sungho Lee^1,3,4, Patricia Jensen⁶, and Yen-Yu Ian Shih^1,3,4
1Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, ²Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, ³Biomedical Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, ⁴Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, ⁵Developmental Neurobiology, NIEHS/NIH, RDU, NC, United States, ⁶Developmental Neurobiology, NIH/NIEHS, RDU, NC, United States

Norepinephrine (NE) is suspected to rapidly modulate strength and structure of intrinsic functional connectivity (FC). We used chemogenetic fMRI to selectively isolate the role of NE Locus Coeruleus (LC) neurons, compared to NE A1/A2/A4 neurons, on FC modulation.  Among 19 parcellated FC modules, NE-LC neurons significantly enhanced ReHo, ALFF and DC within the anterior Default-Mode, Motor and Somatosensory modules and enhanced FC strength within and between Default-Mode modules. Dynamic FC analysis found Default-Mode differences were attributed to two co-activation patterns (CAPs) associated with Default-Mode suppression that explains the ability of NE to focus wandering minds into sensory attention.

Laura W.M. Vergoossen^1,2, Jacobus F.A. Jansen^1,2,3, Daan Huybrechs⁴, Miranda T. Schram^2,5,6, Walter H. Backes^1,2, and on behalf of The Maastricht Study^5
1Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, ²Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands, ³Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands, ⁴Computer Science, KU Leuven, Leuven, Belgium, ⁵Internal Medicine, Maastricht University Medical Center, Maastricht, Netherlands, ⁶School for Cardiovascular Disease, Maastricht University, Maastricht, Netherlands

In addition to spatial patterns, also temporal patterns can be identified in brain signal as non-stationary components. Fourier-transform provides only information about characteristic frequency components in dynamic brain signals and assumes that these are of stationary nature. However, brain signals are non-stationary and discrete wavelet transformation can be used to separate the signal into both frequency subbands and time-scales. In The Maastricht Study (n=1730), we found that wavelet analysis is a suitable method to demonstrate that physiological measures are associated with specific frequency subbands of the BOLD signal, and to separate the neurovascular signal into subbands representing different physiological measures.

Marco Pagani¹, Alice Bertero^1,2, Alessia De Felice¹, Andrea Locarno³, Ieva Miseviciute³, Stavros Trakoshis^4,5, Carola Canella^1,6, Elizabeth de Guzman¹, Kaushtub Supekar⁷, Vinod Menon⁷, Alberto Galbusera¹, Raffaella Tonini³, Michael V. Lombardo⁵, Massimo Pasqualetti², and Alessandro Gozzi^1
1Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy, ²Biology Department, University of Pisa, Pisa, Italy, ³Neuromodulation of Cortical and Subcortical Circuits Laboratory, Istituto Italiano di Tecnologia, Genova, Italy, ⁴Department of Psychology, University of Cyprus, Nicosia, Cyprus, ⁵Laboratory for Autism and Neurodevelopmental Disorders, Istituto Italiano di Tecnologia, Rovereto, Italy, ⁶Center for Mind and Brain Sciences, University of Trento, Rovereto, Italy, ⁷Stanford University, Stanford, CA, United States

Altered brain functional connectivity is a hallmark finding in autism but the neural basis of this phenomenon remains unclear. We show that a mouse line reconstituting synaptic pruning deficits observed in postmortem autistic brains exhibits widespread functional hyper-connectivity, and that pharmacological normalization of synaptic aberrancies completely rescues behavioral and functional connectivity deficits. We also show that a similar connectivity fingerprint can be isolated in human rsfMRI scans of people with autism, and linked to overexpression of genes related to this dysfunctional pathway. Our results reveal a possible mechanistic link between deficient synaptic pruning and functional hyper-connectivity in autism.

Xue Zhang^1,2, Hua Guo¹, and Lihong Wang^3
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, ²Radiological Sciences Laboratory, Department of Radiology, Stanford University, Palo Alto, CA, United States, ³Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, United States

Brain state transitions during resting-state reflect the variation of the baseline homeostasis, it is still unclear how the state interactions are modulated under stress. In the current study, the stress-induced change of the co-activation pattern transitions was examined in two independent cohorts by scanning resting-state fMRI pre- and post- a math task, its association with depression vulnerability was also explored. The post- versus pre-stress resting-state comparison showed an increased state transition frequency under stress, and those with higher depression scores shifted more post-stress in both cohorts, indicating the disturbed brain homeostasis under stress and lower recovery ability from stress.

Patricia Pais-Roldán¹, Seong Dae Yun¹, Michael Schwerter¹, and Jon N Shah^1,2,3,4
1Forschungszentrum Jülich - INM-4, Jülich, Germany, ²Forschungszentrum Jülich - INM-11, Jülich, Germany, ³JARA-BRAIN, Aachen, Germany, ⁴RWTH Aachen University, Aachen, Germany

Cross-cortical interactions in the human brain remain poorly understood and are often over-simplified as a 2-dimensional cortical model in fMRI studies. To date, high-resolution fMRI has been limited to relatively small brain slabs that cover particular areas of interest, providing fine mapping of local circuits but precluding macroscale analysis. Here, an EPIK sequence was used to measure the GE-BOLD signal from individual cortical layers through most of the brain. The combination of high resolution (0.63 mm isotropic) and large coverage fMRI enabled identification of long-distance neuronal interactions that take place between particular cortical depths during resting-state.

Olivia Viessmann¹, Qiyuan Tian¹, Michaël Bernier¹, David H Salat^1,2, and Jonathan Rizzo Polimeni^1,3
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, ²VA Boston Healthcare System, Boston, MA, United States, ³Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

We aimed to test whether the amplitudes of resting-state BOLD signals within the white matter depend on the orientation of the local diffusion tensor relative to the B₀-field. This was assessed using resting-state BOLD and diffusion data provided by the HCP. Baseline BOLD signals were about 11% higher in voxels where primary DTI directions were parallel to B₀ compared to perpendicular. Because myelinated fibres will change local tissue T₂*, which will also impact the BOLD signal, we tested whether the observed BOLD orientation effect was driven by static effects on the baseline or dynamic effects from changes in blood oxygenation.