The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.hippocampus | resting-state functional connectivity | optogenetic | fMRI | low frequency T he hippocampus (HP) plays a prominent role in central nervous system functions, particularly in episodic memory (1, 2) and spatial navigation (3, 4). The HP, including the dentate gyrus (DG), can evoke large-scale influences on cortical activity, because the HP receives convergent information from sensory and limbic cortices before sending reciprocal divergent projections to create a highly interactive corticohippocampal-cortical network. The HP, including DG, CA3, and CA1, and neocortex, are connected via the entorhinal cortex (EC) (5, 6), such that the dorsolateral-to-ventromedial projection that originates in the EC corresponds to a dorsoventral axis of termination in the HP (5). This anatomical topography suggests that a functional gradient could exist along the HP dorsoventral axis. Previous studies demonstrated that dorsal HP (dHP) and cortex are functionally integrated during sensory processing and memory consolidation (7-9). Specifically, dHP can integrate multimodal sensory information and process memory operations (7) using excitatory longrange projections (10). This process occurs over multiple brain circuits, but the role of dHP in complex networks, particularly its influence on brain-wide functional connectivity, is not well understood.Resting-state functional MRI (rsfMRI) (11-14) provides an invaluable, noninvasive imaging technique to map long-range, brain-wide functional connectivity networks based on the temporal coherence of infraslow (0.005-0.1 Hz) blood oxygen level dependent (BOLD) activity. The functional relevance of specific brain-wide networks in co...

Blood oxygen level-dependent functional MRI (fMRI) constitutes a powerful neuroimaging technology to map brain-wide functions in response to specific sensory or cognitive tasks. However, fMRI mapping of the vestibular system, which is pivotal for our sense of balance, poses significant challenges. Physical constraints limit a subject’s ability to perform motion- and balance-related tasks inside the scanner, and current stimulation techniques within the scanner are nonspecific to delineate complex vestibular nucleus (VN) pathways. Using fMRI, we examined brain-wide neural activity patterns elicited by optogenetically stimulating excitatory neurons of a major vestibular nucleus, the ipsilateral medial VN (MVN). We demonstrated robust optogenetically evoked fMRI activations bilaterally at sensorimotor cortices and their associated thalamic nuclei (auditory, visual, somatosensory, and motor), high-order cortices (cingulate, retrosplenial, temporal association, and parietal), and hippocampal formations (dentate gyrus, entorhinal cortex, and subiculum). We then examined the modulatory effects of the vestibular system on sensory processing using auditory and visual stimulation in combination with optogenetic excitation of the MVN. We found enhanced responses to sound in the auditory cortex, thalamus, and inferior colliculus ipsilateral to the stimulated MVN. In the visual pathway, we observed enhanced responses to visual stimuli in the ipsilateral visual cortex, thalamus, and contralateral superior colliculus. Taken together, our imaging findings reveal multiple brain-wide central vestibular pathways. We demonstrate large-scale modulatory effects of the vestibular system on sensory processing.

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Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, shielding-free, and portable clinical applications at a fraction of the cost. However, its performance remains limited by poor image quality. Here, a computational approach is formulated to advance ULF MR brain imaging through deep learning of large-scale publicly available 3T brain data. Methods: A dual-acquisition 3D superresolution model is developed for ULF brain MRI at 0.055 T. It consists of deep cross-scale feature extraction, attentional fusion of two acquisitions, and reconstruction. Models for T 1 -weighted and T 2 -weighted imaging were trained with 3D ULF image data sets synthesized from the high-resolution 3T brain data from the Human Connectome Project.They were applied to 0.055T brain MRI with two repetitions and isotropic 3-mm acquisition resolution in healthy volunteers, young and old, as well as patients. Results:The proposed approach significantly enhanced image spatial resolution and suppressed noise/artifacts. It yielded high 3D image quality at 0.055 T for the two most common neuroimaging protocols with isotropic 1.5-mm synthetic resolution and total scan time under 20 min. Fine anatomical details were restored with intrasubject reproducibility, intercontrast consistency, and confirmed by 3T MRI. Conclusion:The proposed dual-acquisition 3D superresolution approach advances ULF MRI for quality brain imaging through deep learning of high-field brain data. Such strategy can empower ULF MRI for low-cost brain imaging, especially in point-of-care scenarios or/and in low-income and mid-income countries.