CycleGAN with mutual information loss constraint generates structurally aligned CT images from functional EIT images.

Electrical impedance tomography (EIT) has been employed in the field of medical imaging due to its cost effectiveness, safety profile and portability, but the images generated are relatively low resolution. To address these limitations, we create a novel method using EIT images to generate high resolution structurally aligned images of lungs like those from CT scans. A way to achieve this transformation is via Cycle generative adversarial networks (CycleGAN), which have demonstrated image-to-image translation capabilities across different modalities. However, a generic implementation yields images which may not be aligned with their input image. To solve this issue, we construct and incorporate a Mutual Information (MI) constraint in CycleGAN to translate functional lung EIT images to structural high resolution CT images. The CycleGAN is first trained on unpaired EIT and CT lung images. Afterwards, we generate CT image pairs from EIT images via CycleGANs constrained with MI loss and without this loss. Finally, through generating these 1560 CT image pairs and then comparing the visual results and quantitative metrics, we show that MI constrained CycleGAN produces more structurally aligned CT images, where Normalised Mutual Information (NMI) is increased to 0.2621+/- 0.0052 versus 0.2600 +/- 0.0066, p<0.0001 for non-MI constrained images. By this process, we simultaneously provide functional and structural information, and potentially enable more detailed assessment of lungs.Clinical Relevance- By establishing a structurally aligning generative process via MI Loss in CycleGAN, this study enables EIT-CT conversion, thereby providing functional and structural images for enhanced lung assessment, from just EIT images.

Global and regional lung function assessment using portable electrical impedance tomography (EIT) system: clinical study.

Recent development of affordable, portable and self-administrable electrical impedance tomography (EIT) system demonstrated the feasibility of using standalone EIT and subject's anthropometrics to predict the gold standard spirometry indicators for lung-function assessment. Compared to spirometry, the system showed the advantage of providing spatial mapping of the spirometry indicators. Nevertheless, the previous study was limited to healthy subjects. Here, we recruited (N=88): 47 lung disease patients and 41 healthy controls to perform simultaneous EIT and spirometry measurements to validate the capabilities of the system. Lung disease patients include 13 interstitial lung disease (ILD), 10 asthma, 8 chronic obstructive pulmonary disease (COPD), 8 bronchiectasis, and 8 with other diseases including left pneumonectomy, lung cancer, lung tumor, lymphangioleiomyomatosis, motor neuron disease, heart failure and bronchiolitis obliterans syndrome. The results showed significant correlation of the predicted global spirometry indicators (p<0.0001) and significant distinguishability between most disease groups and healthy subjects demonstrating the capability of the EIT system in diagnostic screening. Furthermore, the regional mapping of the spirometry indicators is evaluated and shown to be distinct for each disease group, providing an additional dimension for medical professionals to diagnose and monitor lung disease patients.Clinical Relevance- This establishes the significance of EIT-based global and regional indicators for assessing lung function on lung disease patients.

Deep learning based reconstruction enables high-resolution electrical impedance tomography for lung function assessment.

Recently, deep learning based methods have shown potential as alternative approaches for lung time difference electrical impedance tomography (tdEIT) reconstruction other than traditional regularized least square methods, that have inherent severe ill-posedness and low spatial resolution posing challenges for further interpretation. However, the validation of deep learning reconstruction quality is mainly focused on simulated data rather than in vivo human chest data, and on image quality rather than clinical indicator accuracy. In this study, a variational autoencoder is trained on high-resolution human chest simulations, and inference results on an EIT dataset collected from 22 healthy subjects performing various breathing paradigms are benchmarked with simultaneous spirometry measurements. The deep learning reconstructed global conductivity is significantly correlated with measured volume-time curves with correlation > 0.9. EIT lung function indicators from the reconstruction are also highly correlated with standard spirometry indicators with correlation > 0.75.Clinical Relevance- Our deep learning reconstruction method of lung tdEIT can predict lung volume and spirometry indicators while generating high-resolution EIT images, revealing potential of being a competitive approach in clinical settings.

Portable electrical impedance tomography (EIT) system stages non-alcoholic fatty liver disease for potential screening and monitoring at home.

This study demonstrates the feasibility of predicting NAFLD using multi-spectral electrical impedance tomography (EIT), group source separation, constant reference EIT and anthropometric measures. Vibration-controlled Transient Elastography (VCTE) Controlled Attenuated Parameter (CAP; n = 121) and magnetic resonance imaging-proton density fat fraction (MRI-PDFF; n = 34) achieved a sensitivity of 70.9% and specificity of 73.8% with our CAP predicting model and sensitivity of 77.8% and specificity of 80.0% with our MRI-PDFF predicting model. In summary, a portable EIT can be a cost-effective and self-administrable alternative for widespread home-based and community-based diagnostic screening and treatment monitoring of NAFLD.Clinical Relevance- Portable multi-spectral EIT system has the sensitivity and specificity to potentially unlock biomedical imaging in telemedicine for home-based and community-based screening, staging and monitoring for NAFLD.

Electric impedance tomography enables portable and non-invasive approach to screen and monitor chronic kidney disease.

Chronic kidney disease (CKD) is an escalating global health concern, and non-invasive means for early CKD detection is eagerly awaited. Here, we explore the potential of using home-based frequency-difference electrical impedance tomography (fdEIT) to evaluate CKD based on bio-conductivity characteristics. We performed bio-conductivity measurement in vivo paired with standard estimated glomerular filtration rate (eGFR) measurements on a N=126 CKD patients by EIT and traditional blood and urine tests, respectively. We developed an EIT processing pipeline that extracts the kidney regions from EIT images. We further developed a regression model and a CKD classification scheme. Our results showed a significant correlation between EIT-features and eGFR, and the classification scheme shows sensitivity and specificity of 76.2% and 74.6% respectively considering stages 1 and 2 CKD versus stages 3, 4 and 5 CKD. These results suggest the feasibility of EIT to be used as a portable, self-administrated and home-based approach for CKD early diagnostic screening and longitudinal monitoring.Clinical Relevance-The results presented here demonstrates a cost-effective, home-based and self-administrative screening process on chronic kidney disease patients, thereby enhancing the quality and area of possible application of telemedicine. By achieving this, the process presented here can relieve the burden of public health system.

Diverging patterns of plasticity in the nucleus basalis of Meynert in early- and late-onset blindness.

Plasticity in the brain is impacted by an individual's age at the onset of the blindness. However, what drives the varying degrees of plasticity remains largely unclear. One possible explanation attributes the mechanisms for the differing levels of plasticity to the cholinergic signals originating in the nucleus basalis of Meynert. This explanation is based on the fact that the nucleus basalis of Meynert can modulate cortical processes such as plasticity and sensory encoding through its widespread cholinergic projections. Nevertheless, there is no direct evidence indicating that the nucleus basalis of Meynert undergoes plastic changes following blindness. Therefore, using multiparametric magnetic resonance imaging, we examined if the structural and functional properties of the nucleus basalis of Meynert differ between early blind, late blind and sighted individuals. We observed that early and late blind individuals had a preserved volumetric size and cerebrovascular reactivity in the nucleus basalis of Meynert. However, we observed a reduction in the directionality of water diffusion in both early and late blind individuals compared to sighted individuals. Notably, the nucleus basalis of Meynert presented diverging patterns of functional connectivity between early and late blind individuals. This functional connectivity was enhanced at both global and local (visual, language and default-mode networks) levels in the early blind individuals, but there were little-to-no changes in the late blind individuals when compared to sighted controls. Furthermore, the age at onset of blindness predicted both global and local functional connectivity. These results suggest that upon reduced directionality of water diffusion in the nucleus basalis of Meynert, cholinergic influence may be stronger for the early blind compared to the late blind individuals. Our findings are important to unravelling why early blind individuals present stronger and more widespread cross-modal plasticity compared to late blind individuals.

Affordable, portable and self-administrable electrical impedance tomography enables global and regional lung function assessment.

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.

Standalone electrical impedance tomography predicts spirometry indicators and enables regional lung assessment.

Electrical impedance tomography (EIT) is a bio-medical imaging modality that has several clinical applications namely for human lungs. Yet, its relationship with gold standard lung diagnostic tools including spirometry is not available. In this study, simultaneous EIT and spirometry measurements were collected for 14 healthy subjects who performed forced breathing paradigms of different efforts simulating a wide range of spirometry indicators. It is demonstrated that EIT can predict standard spirometry indicators over a wide dynamic range, with a potential sensitivity and specificity of 98% and 100%, respectively, in detecting obstructive patterns. It is also shown that EIT can provide a regional mapping of the spirometry indicator which are shown to be consistent with their corresponding global indicators. Overall, EIT can predict spirometry indicators and can assess regional lung health through parametric mapping. Clinical Relevance- This study shows that EIT can infer standard spirometry indicators and potentially assess regional lung health. Therefore, EIT can be used for screening, diagnosis, and monitoring of obstructive and resistive lung diseases.

Bio-conductivity characteristics of chronic kidney disease stages examined by portable frequency-difference electrical impedance tomography.

Chronic kidney disease (CKD) is an escalating global health concern, and non-invasive means for early CKD detection is eagerly awaited. Here, we explore the potential of using home-based frequency-difference electrical impedance tomography (fdEIT) to evaluate CKD based on bio-conductivity characteristics. We first verified the feasibility of using portable EIT capturing bio-conductivity in fresh pig kidneys ex vivo. We further performed bio-conductivity measurement in vivo paired with standard eGFR measurements on CKD patients by EIT and traditional blood test, respectively. Our results showed a significant correlation between renal bio-conductivity changes captured by fdEIT and standard eGFR scores. These results hold promise to be developed into a non-invasive and portable device for early CKD detection and longitudinal CKD treatment monitoring in clinical, community and home-based settings. Clinical Relevance - A novel non-invasive bio-conductivity approach was developed for CKD classification. The renal assessment with portable EIT device demonstrated the potential to ameliorate the detection and classification of CKD into a portable, accessible, self-administrable home-based process.

Distinct local and brain-wide networks are activated by optogenetic stimulation of neurons specific to each layer of motor cortex.

Primary motor cortex (M1) consists of a stack of interconnected but distinct layers (L1-L6) which affect motor control through large-scale networks. However, the brain-wide functional influence of each layer is poorly understood. We sought to expand our knowledge of these layers' circuitry by combining Cre-driver mouse lines, optogenetics, fMRI, and electrophysiology. Neuronal activities initiated in Drd3 neurons (within L2/3) were mainly confined within M1, while stimulation of Scnn1a, Rbp4, and Ntsr1 neurons (within L4, L5, and L6, respectively) evoked distinct responses in M1 and motor-related subcortical regions, including striatum and motor thalamus. We also found that fMRI responses from targeted stimulations correlated with both local field potentials (LFPs) and spike changes. This study represents a step forward in our understanding of how different layers of primary motor cortex are embedded in brain-wide circuitry.

Instantaneous effects of mindfulness meditation on tennis return performance in elite junior athletes completing an implicitly sequenced serve return task.

Single-session meditation augmentation of sport-specific skill performance was tested with elite junior tennis athletes. Athletes completed one of two styles of mindfulness meditation (focused-attention or open-monitoring) or a control listening condition prior to performing an implicitly sequenced tennis serve return task involving the goal of hitting a target area placed on the service court. Unbeknownst to athletes, six distinct serves followed a repeating second-order conditional sequence for two task blocks before the sequence was altered in a third transfer block. Task performance was operationalized as serve return outcome and analyzed using beta regression modeling. Models analyzed group by block differences in the proportion of returned serves (i.e., non-aces), returns placed in the service court, and target hits. Contrary to previous laboratory findings, results did not support meditation-related augmentation of performance and/or sequence learning. In fact, compared to control, meditation may have impaired performance improvements and acquisition of serve sequence information. It is possible that the effects of single-session meditation seen in laboratory research may not extend to more complex motor tasks, at least in highly-trained adolescents completing a well-learned skill. Further research is required to elucidate the participant, task, and meditation-related characteristics that might promote single-session meditation performance enhancement.

NOise Reduction with DIstribution Corrected (NORDIC) PCA improves signal-to-noise in rodent resting-state and optogenetic functional MRI.

NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve rodent fMRI using NORDIC PCA has not been explored. In this study, we developed a rodent fMRI preprocessing pipeline by incorporating NORDIC and evaluated its performance in a range of rodent fMRI applications from resting-state fMRI to task-evoked fMRI using optogenetics. In resting-state fMRI, we demonstrated a significant increase in tSNR by more than 3 times after NORDIC correction with reduced variance and improved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. In optogenetic fMRI, apart from tSNR increase, more activated voxels and a significant decrease in the variance of activated brain signals were observed after NORDIC correction without apparent change in brain morphology. Taken together, our results signified the values of NORDIC correction for better detection of brain activities in rodent fMRI. Clinical Relevance: NORDIC PCA increases temporal signalto- noise ratio in rodent resting-state and task-evoked functional MRI, which can play an important role in improving the image quality for translational medicine and preclinical research, and for guiding future clinical neuroimaging.

Unmixing multi-spectral electrical impedance tomography (EIT) predicts clinical-standard controlled attenuation parameter (CAP) for nonalcoholic fatty liver disease classification: a feasibility study.

Here, we tested the feasibility of predicting CAP with multi-spectral EIT. Conductivity and CAP were acquired from nonalcoholic fatty liver disease patients using a portable EIT system and vibration-controlled transient elastography (VCTE). We then used frequency-difference conductivity and waist-over-height as prediction features to estimate CAP and found an adj. R2 of 0.92. We further developed a novel prediction method by incorporating EIT spectral unmixing reconstruction and demonstrated an improvement in CAP estimation. Last, we optimized the EIT acquisition process by minimizing the total variance of the CAP estimator. Clinical Relevance: EIT can estimate clinical-standard liver disease classification. This portable EIT system is potentially cost-effective and self-administrable with short acquisition time (3 mins), while VCTE are costly and usually requires a trained personnel to operate with longer acquisition time (5-10 mins).

Repeated hippocampal seizures lead to brain-wide reorganization of circuits and seizure propagation pathways.

Repeated seizure activity can lead to long-term changes in seizure dynamics and behavior. However, resulting changes in brain-wide dynamics remain poorly understood. This is due partly to technical challenges in precise seizure control and in vivo whole-brain mapping of circuit dynamics. Here, we developed an optogenetic kindling model through repeated stimulation of ventral hippocampal CaMKII neurons in adult rats. We then combined fMRI with electrophysiology to track brain-wide circuit dynamics resulting from non-afterdischarge (AD)-generating stimulations and individual convulsive seizures. Kindling induced widespread increases in non-AD-generating stimulation response and ipsilateral functional connectivity and elevated anxiety. Individual seizures in kindled animals showed more significant increases in brain-wide activity and bilateral functional connectivity. Onset time quantification provided evidence for kindled seizure propagation from the ipsilateral to the contralateral hemisphere. Furthermore, a core of slow-migrating hippocampal activity was identified in both non-kindled and kindled seizures, revealing a novel mechanism of seizure sustainment and propagation.

Relationships between cerebrovascular reactivity, visual-evoked functional activity, and resting-state functional connectivity in the visual cortex and basal forebrain in glaucoma.

Glaucoma is primarily considered an eye disease with widespread involvements of the brain. Yet, it remains unclear how cerebrovasculature is regulated in glaucoma and how different brain regions coordinate functionally across disease severity. To address these questions, we applied a novel whole-brain relative cerebrovascular reactivity (rCVR) mapping technique using resting-state functional magnetic resonance imaging (fMRI) without gas challenges to 38 glaucoma patients and 21 healthy subjects. The relationships between rCVR, visual-evoked fMRI response, and resting-state functional connectivity in glaucoma were then established. In the visual cortex, rCVR has a decreasing trend with glaucoma severity (p<0.05), and is coupled with visual-evoked response and functional connectivity in both hemispheres (p<0.001). Interestingly, rCVR in the basal forebrain (BF) has an increasing trend with glaucoma severity (p<0.05). The functional connectivity between right diagonal band of Broca (a sub-region of BF) and lateral visual cortex decreases with glaucoma (p<0.05), while such connectivity is inversely coupled with rCVR in the BF (p<0.05), but not the visual cortex. Overall, we demonstrate opposite trends of rCVR changes in the visual cortex and BF in glaucoma patients, suggestive of compensatory actions in vascular reserve between the two brain regions. The neurovascular coupling within the visual cortex appears deteriorated in glaucoma, whereas the association between BF-visual cortex functional connectivity and rCVR of BF indicates the functional and vascular involvements in glaucoma beyond the primary visual pathway.

Feasibility and Challenges of Performing Magnetoencephalography Experiments in Children With Arthrogryposis Multiplex Congenita.

Arthrogryposis multiplex congenita (AMC) has recently drawn substantial attention from researchers and clinicians. New effective surgical and physiotherapeutic methods have been developed to improve the quality of life of patients with AMC. While it is clear that all these interventions should strongly rely on the plastic reorganization of the central nervous system, almost no studies have investigated this topic. The present study demonstrates the feasibility of using magnetoencephalography (MEG) to investigate brain activity in young AMC patients. We also outlined the general challenges and limitations of electrophysiological investigations on patients with arthrogryposis. We conducted MEG recordings using a 306-channel Elekta Neuromag VectorView system during a cued motor task performance in four patients with arthrogryposis, five normally developed children, and five control adults. Following the voice command of the experimenter, each subject was asked to bring their hand toward their mouth to imitate the self-feeding process. Two patients had latissimus dorsi transferred to the biceps brachii position, one patient had a pectoralis major transferred to the biceps brachii position, and one patient had no elbow flexion restoration surgery before the MEG investigation. Three patients who had undergone autotransplantation prior to the MEG investigation demonstrated activation in the sensorimotor area contralateral to the elbow flexion movement similar to the healthy controls. One patient who was recorded before the surgery demonstrated subjectively weak distributed bilateral activation during both left and right elbow flexion. Visual inspection of MEG data suggested that neural activity associated with motor performance was less pronounced and more widely distributed across the cortical areas of patients than of healthy control subjects. In general, our results could serve as a proof of principle in terms of the application of MEG in studies on cortical activity in patients with AMC. Reported trends might be consistent with the idea that prolonged motor deficits are associated with more difficult neuronal recruitment and the spatial heterogeneity of neuronal sources, most likely reflecting compensatory neuronal mechanisms. On the practical side, MEG could be a valuable technique for investigating the neurodynamics of patients with AMC as a function of postoperative abilitation.

High-sensitivity detection of optogenetically-induced neural activity with functional ultrasound imaging.

Whole-brain imaging approaches and optogenetic manipulations are powerful tools to map brain-wide neural circuits in vivo. To date, functional magnetic resonance imaging (fMRI) provides the most comprehensive evaluation of such large-scale circuitry. However, functional ultrasound imaging (fUSI) has recently emerged as a complementary imaging modality that can extend such measurements towards the context of diverse behavioral states and tasks. Nevertheless, in order to properly interpret the fUSI signal during these complicated scenarios, it must first be carefully validated against well-established technologies, such as fMRI, in highly controlled experimental settings. Here, to address this need, we compared subsequent fMRI and fUSI recordings in response to direct neuronal activation via optogenetics in the same animals under an identical anesthetic protocol. Specifically, we applied various intensities of light stimulation to the primary motor cortex (M1) of mice and compared the spatiotemporal dynamics of the elicited fMRI and fUSI signals. Overall, our general linear model analysis (t-scores) and time series analysis (z-scores) revealed that fUSI was more sensitive than fMRI for detecting optogenetically-induced neuronal activation. Local field potential recordings in the bilateral M1 and striatum also better co-localized with fUSI activation patterns than those of fMRI. Finally, the fUSI response contained distinct arterial and venous components that provide vascular readouts of neuronal activity with vessel-type specificity.

Focused-attention meditation increases cognitive control during motor sequence performance: Evidence from the N2 cortical evoked potential.

Previous work found that single-session focused attention meditation (FAM) enhanced motor sequence learning through increased cognitive control as a mechanistic action, although electrophysiological correlates of sequence learning performance following FAM were not investigated. We measured the persistent frontal N2 event-related potential (ERP) that is closely related to cognitive control processes and its ability to predict behavioural measures. Twenty-nine participants were randomised to one of three conditions reflecting the level of FAM experienced prior to a serial reaction time task (SRTT): 21 sessions of FAM (FAM21, N = 12), a single FAM session (FAM1, N = 9) or no preceding FAM control (Control, N = 8). Continuous 64-channel EEG were recorded during SRTT and N2 amplitudes for correct trials were extracted. Component amplitude, regions of interests, and behavioural outcomes were compared using mixed effects regression models between groups. FAM21 exhibited faster reaction time performances in majority of the learning blocks compared to FAM1 and Control. FAM21 also demonstrated a significantly more pronounced N2 over majority of anterior and central regions of interests during SRTT compared to the other groups. When N2 amplitudes were modelled against general learning performance, FAM21 showed the greatest rate of amplitude decline over anterior and central regions. The combined results suggest that FAM training provided greater cognitive control enhancement for improved general performance, and less pronounced effects for sequence-specific learning performance compared to the other groups. Importantly, FAM training facilitates dynamic modulation of cognitive control: lower levels of general learning performance was supported by greater levels of activation, whilst higher levels of general learning exhibited less activation.

Thalamic low frequency activity facilitates resting-state cortical interhemispheric MRI functional connectivity.

Blood-oxygen-level-dependent (BOLD) resting-state functional MRI (rsfMRI) has emerged as a valuable tool to map complex brain-wide functional networks, predict cognitive performance and identify biomarkers for neurological diseases. However, interpreting these findings poses challenges, as the neural basis of rsfMRI connectivity remains poorly understood. The thalamus serves as a relay station and modulates diverse long-range cortical functional integrations, yet few studies directly interrogate its role in brain-wide rsfMRI connectivity. Utilizing a multi-modal approach of rsfMRI, optogenetic stimulation and multi-depth cortical electrophysiology recording, we examined whether and how the somatosensory thalamus contributes to cortical interhemispheric rsfMRI connectivity. We found that low frequency (1 Hz) optogenetic stimulation of somatosensory-specific ventral posteromedial (VPM) thalamocortical excitatory neurons increased the interhemispheric rsfMRI connectivity in all examined sensory cortices, somatosensory, visual and auditory, and the local intrahemispheric BOLD activity at infraslow frequency (0.01-0.1 Hz). In parallel, multi-depth local field potential recordings at bilateral primary somatosensory cortices revealed increased interhemispheric correlations of low frequency neural oscillations (i.e., mainly < 10 Hz) at all cortical layers. Meanwhile, pharmacologically inhibiting VPM thalamocortical neurons decreased interhemispheric rsfMRI connectivity and local intrahemispheric infraslow BOLD activity in all sensory cortices. Taken together, our findings demonstrate that low frequency activities in the thalamo-cortical network contribute to brain-wide rsfMRI connectivity, highlighting the thalamus as a pivotal region that underlies rsfMRI connectivity.

Optogenetic fMRI interrogation of brain-wide central vestibular pathways.

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.