Biology subjects

Varadarajan, D.

Publications and source records attributed to Varadarajan, D..

9 recordsLinked to original sources

bioRxiv2026

Progression of visual-stimulus-evoked blood velocity response timing across the vascular network measured with individual-vessel phase-contrast fMRA

Most functional MRI (fMRI) studies of brain function aim to measure hemodynamic responses arising from the microvasculature within the tissue parenchyma, where spatial and temporal coupling with neuronal activity is thought to be tightest. However, the measured hemodynamic responses emerge from an interconnected vascular network that includes upstream feeding arteries, downstream draining veins, and the intervening microvascular compartments. Directly measuring and comparing vascular responses across multiple stages of this network may therefore provide more specific information about network-level hemodynamics--and how hemodynamics in one stage of the vascular hierarchy influence hemodynamics in others--that is not accessible from conventional fMRI signals alone. This can provide new insights into the relationship between the observed fMRI responses and the underlying neuronal activity of interest. This study extends our recently proposed dynamic phase-contrast functional MR angiography (PC-fMRA) method for tracking stimulus-evoked blood-velocity responses in large supplying arteries to enable concurrent hemodynamic measurements across multiple levels of the neurovascular complex. Here, we apply this method across several levels of the vascular hierarchy, from the basilar and posterior cerebral arteries to pial arteries, pial veins, and major draining venous sinuses such as the straight and superior sagittal sinuses. Stimulus-locked velocity increases were observed in individual vessels within each subject. Arterial responses occurred rapidly and nearly simultaneously across upstream and pial arterial segments, whereas venous responses exhibited temporal delays relative to the arterial responses. The average arterial-to-venous response time delay differed between the onset and offset phases, measuring approximately 4.1 s during response onset and 1.3 s during response offset, and also varied across different vessel segments. A simplified Windkessel model--used to interpret these findings--predicted similar inflow-outflow delays, suggesting that these temporal differences may reflect the transient filling and draining dynamics within compliant vascular compartments intervening between supplying arteries and draining veins. Our results demonstrate the feasibility of using dynamic PC-fMRA to measure vessel-specific hemodynamic responses across the human neurovascular complex. By providing quantitative measurements of macrovascular responses that serve as inputs to and outputs from intervening vascular compartments, this approach offers a framework for probing the hemodynamics within these compartments and studying vascular network behavior during neuronal activation, which may also help improve the physiological interpretation of fMRI signals in humans.

neuroscience↗

bioRxiv2025

Visual stimulus-evoked blood velocity responses in individual human posterior cerebral arteries measured with dynamic phase-contrast functional MR angiography

Functional MRI (fMRI) tracks brain activity through the associated hemodynamic changes via neurovascular coupling. Neurons communicate with the microvessels of the parenchyma to initiate a hemodynamic response, and these microvessels then communicate with upstream arterioles and arteries. The role of the larger feeding arteries--far upstream from the site of neuronal activity--in coordinating this response is incompletely understood, yet is important for the interpretation of fMRI. Functional Transcranial Doppler (fTCD) can noninvasively measure blood velocity changes in a subset of the largest macrovessels, albeit with poor spatial resolution, whereas existing functional MR angiography (fMRA) methods can assess blood velocity in mid-sized macrovessels but still lack the temporal resolution required to capture dynamic responses. This study aims to propose a new, quantitative fMRA method for measuring blood velocity responses in individual vessels in humans at high spatiotemporal resolution. A dynamic functional phase-contrast MRA approach was developed to quantify responses evoked by visual stimuli in the "P2" segment of the posterior cerebral artery (PCA), located [~]6 cm away from primary visual cortex. The achieved temporal resolution is comparable to that of conventional blood-oxygenation-level-dependent (BOLD) fMRI, enabling block-design stimulation paradigms similar to those used in conventional fMRI studies. The temporal and spatial properties of the blood velocity responses were evaluated using both long- and short-duration visual stimuli presented to either the full visual field or a single hemifield. Robust responses were measured on both 3T and 7T clinical MRI scanners, and an approximately 3.3 {+/-} 1.2 cm/s increase in the blood velocity in the targeted segment was observed, which is roughly a 10% increase from baseline. Visual hemifield stimulation generated a measurable blood velocity response only in the contralateral cerebral hemisphere, indicating that systemic physiological changes occurring with stimulation cannot account for the observed response, suggesting that they instead reflect neurovascular coupling initiated in the visual cortex. The observed arterial blood velocity response is consistent with a downstream reduction in microvascular resistance and may represent a passive response rather than an active vessel dilation at the targeted arterial segment. The proposed method has the potential to extend the capability of commonly used approaches, such as fTCD, in clinical applications.

neuroscience↗

bioRxiv2025

Functional MRI Signatures of Autonomic Physiology in Aging

While traditionally regarded as "noise", blood-oxygenation-level-dependent (BOLD) fMRI fluctuations coupled to systemic physiology--such as heart rate and respiratory changes--also hold valuable information about brain vascular properties and autonomic function. In this study, we leverage these physiological BOLD signals to characterize age-related changes in brain physiology. Using a large dataset from the Lifespan Human Connectome Project Aging study, we investigated how the spatiotemporal BOLD-fMRI signatures of autonomic physiology, specifically heart rate and respiratory variation, change with advancing age. Our findings reveal that aging is associated with globally slower respiratory fMRI responses, alongside faster cardiac fMRI responses and enhanced brain-cardiac signal coupling. Moreover, we show that the impact of age on physiological fMRI signals exhibits a notable turning point after age 60, suggesting a critical role of declining vascular health and autonomic function in aging. The potential impact of age-related changes in brain structure, tissue perfusion, and in-scan arousal states on the identified physiological fMRI patterns is also tested and discussed. Altogether, our results underscore significant age effects in the fMRI signatures of systemic physiology, emphasizing the pivotal role of altered vascular properties and autonomic function in aging. Methodologically, this study also demonstrates the utility of resting-state fMRI for extracting multi-parametric information about brain physiology, offering new biomarker opportunities that complement established functional connectivity metrics.

physiology↗

bioRxiv2023

Segmentation of supragranular and infragranular layers in ultra-high resolution 7T ex vivo MRI of the human cerebral cortex

Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Lever-aging recent advancements in ultra-high resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 {micro}m, we propose a multi-resolution U-Nets framework (MUS) that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation, while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases.

neuroscience↗

bioRxiv2023

BrainSuite BIDS App: Containerized Workflows for MRI Analysis

There has been a concerted effort by the neuroimaging community to establish standards for computational methods for data analysis that promote reproducibility and portability. In particular, the Brain Imaging Data Structure (BIDS) specifies a standard for storing imaging data, and the related BIDS App methodology provides a standard for implementing containerized processing environments that include all necessary dependencies to process BIDS datasets using image processing workflows. We present the BrainSuite BIDS App, which encapsulates the core MRI processing functionality of BrainSuite within the BIDS App framework. Specifically, the BrainSuite BIDS App implements a participant-level workflow comprising three pipelines and a corresponding set of group-level analysis workflows for processing the participant-level outputs. The Anatomical Pipeline extracts cortical surface models from a T1-weighted (T1w) MRI. It then performs surface-constrained volumetric registration to align the T1w MRI to a labeled anatomical atlas, which is used to delineate anatomical regions of interest in the MRI brain volume and on the cortical surface models. The Diffusion Pipeline processes diffusion-weighted imaging (DWI) data, with steps that include coregistering the DWI data to the T1w scan, correcting for susceptibility-induced geometric image distortion, and fitting diffusion models to the DWI data. The Functional Pipeline performs fMRI processing using a combination of FSL, AFNI, and BrainSuite tools. It coregisters the fMRI data to the T1w image, then transforms the data to the anatomical atlas space and to the Human Connectome Projects grayordinate space. The outputs of each pipeline can then be processed during group-level analysis. The outputs of the Anatomical Pipeline and the Diffusion Pipeline are analyzed using the BrainSuite Statistics Toolbox in R (bstr), which provides functionality for hypothesis testing and statistical modeling. The outputs of the Functional Pipeline can be analyzed using atlas-based or atlas-free statistical methods during group-level processing. These analyses include the application of BrainSync, which synchronizes the time-series data temporally and enables comparison of resting-state or task-based fMRI data across scans. We also present the BrainSuite Dashboard quality control system, which provides a browser-based interface for reviewing the outputs of individual modules of the participant-level pipelines across a study in real-time as they are generated. BrainSuite Dashboard facilitates rapid review of intermediate results, enabling users to identify processing errors and make adjustments to processing parameters if necessary. The comprehensive functionality included in the BrainSuite BIDS App provides a mechanism for rapidly deploying the BrainSuite workflows into new environments to perform large-scale studies. We demonstrate the capabilities of the BrainSuite BIDS App using structural, diffusion, and functional MRI data from the Amsterdam Open MRI Collections Population Imaging of Psychology dataset.

neuroscience↗

bioRxiv2021

A multimodal imaging and analysis pipeline for creating a cellular census of the human cerebral cortex

Cells are not uniformly distributed in the human cerebral cortex. Rather, they are arranged in a regional and laminar fashion that span a range of scales. Here we demonstrate an innovative imaging and analysis pipeline to construct a reliable cell census across the human cerebral cortex. Magnetic resonance imaging (MRI) is used to establish a macroscopic reference coordinate system of laminar and cytoarchitectural boundaries. Cell counting is obtained with both traditional immunohistochemistry, to provide a stereological gold-standard, and with a custom-made inverted confocal light-sheet fluorescence microscope (LSFM) for 3D imaging at cellular resolution. Finally, mesoscale optical coherence tomography (OCT) enables the registration of the distorted histological cell typing obtained with LSFM to the MRI-based atlas coordinate system.

neuroscience↗

bioRxiv2021

Scalable mapping of myelin and neuron density in the human brain with micrometer resolution

Optical Coherence Tomography (OCT) is an emerging 3D imaging technique that allows quantification of intrinsic optical properties such as scattering coefficient and back-scattering coefficient, and has proved useful in distinguishing delicate microstructures in the human brain. The origins of scattering in brain tissues are contributed by the myelin content, neuron size and density primarily; however, no quantitative relationships between them have been reported, which hampers the use of OCT in fundamental studies of architectonic areas in the human brain and the pathological evaluations of diseases. To date, histology remains the golden standard, which is prone to errors and can only work on a small number of subjects. Here, we demonstrate a novel method that uses serial sectioning OCT to quantitatively measure myelin content and neuron density in the human brain. We found that the scattering coefficient possesses a strong linear relationship with the myelin content across different regions of the human brain, while the neuron density serves as a secondary contribution that only slightly modulates the overall tissue scattering.

neuroscience↗

bioRxiv2020

A novel algorithm to optimize generalized gamma distributed multiplicative noise with implications on speckle removal from OCT images

Optical coherence tomography (OCT) images are corrupted by multiplicative generalized gamma distributed speckle noise that significantly degrades the contrast to noise ratio (CNR) of microstructural compartments in biological applications. This work proposes a novel algorithm to optimize the negative log likelihood of the spatial distribution of speckle. Specifically, the proposed method formulates a penalized negative log likelihood (P-NLL) cost function and proposes a majorize-minimize-based optimization method that removes speckle from OCT images. The optimization reduces to solving an iterative gradient descent problem. We demonstrate the usefulness of the proposed method by removing speckle in OCT images of uniform phantoms with varying scattering coefficients and human brain tissue.

neuroscience↗

bioRxiv2020

Conductance-Based Structural Brain Connectivity in Aging and Dementia

BackgroundStructural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimers disease (AD) progression. MethodsIn this work, we used our recently proposed structural connectivity quantification measure derived from diffusion MRI, which accounts for both direct and indirect pathways, to quantify brain connectivity in dementia. We analyzed data from the ADNI-2 and OASIS-3 datasets to derive relevant information for the study of the changes that the brain undergoes in AD. We also compared these datasets to the HCP dataset, as a reference, and eventually validated externally on two cohorts of the EDSD database. ResultsOur analysis shows expected trends of mean conductance with respect to age and cognitive scores, significant age prediction values in aging data, and regional effects centered among sub-cortical regions, and cingulate and temporal cortices. DiscussionResults indicate that the conductance measure has prediction potential, especially for age, that age and cognitive scores largely overlap, and that this measure could be used to study effects such as anti-correlation in structural connections. Impact statementThis work presents a methodology and a set of analyses that open new possibilities in the study of healthy and pathological aging. The methodology used here is sensitive to direct and indirect pathways in deriving brain connectivity measures from dMRI, and therefore provides information that many state-of-the-art methods do not account for. As a result, this technique may provide the research community with ways to detect subtle effects of healthy aging and AD.

neuroscience↗