Biology subjects

Snyder, A. Z.

Publications and source records attributed to Snyder, A. Z..

17 recordsLinked to original sources

bioRxiv2026

Task-evoked deactivations: dissociation between BOLD fMRI and FDG

Task-evoked decreases in blood-oxygenation-level-dependent (BOLD) signals are a well-recognized phenomenon in functional magnetic resonance imaging (fMRI) studies. These deactivations are most prominent in the default mode network (DMN), a set of regions most active at rest. The metabolic basis of task-induced BOLD fMRI deactivations remains unclear. To address this question, we used PET/MRI to simultaneously measure BOLD fMRI and cerebral glucose consumption (CMRglc) during visuomotor and language tasks in 22 cognitively unimpaired older adults (15 female, 7 male). Task performance increased BOLD signals in task-relevant regions and decreased BOLD signals in the DMN. Positive BOLD responses generally coincided with increases in CMRglc. In contrast, CMRglc did not decrease in regions showing negative BOLD responses; instead, it typically increased. In particular, the posterior cingulate cortex showed significant CMRglc elevations in conjunction with negative BOLD responses. Whole-brain intensity normalization partially restored task-induced decreases in CMRglc, indicating that relative reductions appear in regions in which CMRglc increases are smaller than the global average. Overall, our results imply that BOLD fMRI deactivations can occur in conjunction with stable or even increased glucose consumption.

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bioRxiv2025

Temporal-orbitofrontal pathway regulates choices across physical reward and visual novelty

Perceptually novel objects have profound impacts on our daily decisions. People often pay to try novel meals over familiar ones, or to see novel visual scenes at art exhibits and travel destinations. This suggests that perceptual novelty and the value of physical rewards, such as food, interact at the level of neural circuits to guide decisions, but where and how is unknown. We designed a behavioral task to study this novelty-reward interaction in animals and to uncover its neural underpinnings. Subjects chose among familiar offers associated with different expectations of novel objects and different expectations of juice rewards. Expectation of novel objects increased the preference for expected rewards. This novelty-reward interaction was reflected by neural activity in the anterior ventral temporal cortex (AVMTC) - a region previously implicated in the detection and prediction of novelty - and in the orbitofrontal cortex (OFC) - an area that receives prominent AVMTC inputs and is known for its capacity to signal subjective value of visual objects. Neural activity patterns suggested that AVMTC was upstream of OFC in the decision process. Chemogenetic disruption of the AVMTC[->]OFC circuit altered the impact of expected novelty on the valuation of physical reward. Hence, the ventral visual system impacts novelty-reward interactions during decisions through direct projections to OFC.

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bioRxiv2024

Aging and the Spectral Properties of Brain Hemodynamics

Cerebral glucose metabolism (CMRGlc) systematically decreases with advancing age. We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task-free state. We analyzed lifespan resting-state fMRI data acquired in 455 healthy adults (ages 18-87 years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25-45 years, 65-85 years). We characterized the spectral properties of the fMRI data in terms of the relative predominance of slow vs. fast activity using the spectral slope (SS) measure. We found that the relative proportion of fast activity increases with advancing age (SS flattening) across most cortical regions. The regional distribution of spectral slope was topographically correlated with CMRGlc in young adults. Notably, whereas most older adults maintained a youthful pattern of SS topography, a distinct subset of older adults significantly diverged from the youthful pattern. This subset of older adults also diverged from the youthful pattern of CMRGlc metabolism. This divergent pattern was associated with T2-weighted signal changes in frontal lobe white matter, an independent marker of small vessel disease. These findings suggest that BOLD signal spectral slope flattening may represent a biomarker of age-associated neurometabolic pathology. Significance StatementAging is associated with a decline in cerebral glucose metabolism (CMRGlc). Here, we identified correlates of CMRGlc in the spectral properties of resting-state fMRI data using spectral slope (SS), which quantifies the relative predominance of slow vs. fast activity. We found that SS flattening with advancing age is most prominent in regions characterized by high CMRGlc in youth. A subset of older adults who diverged from the youthful pattern of SS topography also exhibited evidence of frontal lobe white matter pathology. These findings suggest that the spectral properties of rs-fMRI data provide mechanistic insights into age-related neuropathology. In particular, spectral slope measures may serve as early indicators of age-related neurometabolic decline and potentially identify individuals in whom intervention is indicated.

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bioRxiv2024

Early Life Neuroimaging: The Generalizability of Cortical Area Parcellations Across Development

The cerebral cortex consists of distinct areas that develop through intrinsic embryonic patterning and postnatal experiences. Accurate parcellation of these areas in neuroimaging studies improves statistical power and cross-study comparability. Given significant brain changes in volume, microstructure, and connectivity during early life, we hypothesized that cortical areas in 1- to 3-year-olds would differ markedly from neonates and increasingly resemble adult patterns as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity gradients in 92 toddlers at 2 years old. We demonstrate high reproducibility of these cortical regions across 1- to 3-year-olds in two independent datasets. The area boundaries in 1- to 3-year-olds were more similar to those in adults than those in neonates. While the age-specific group area parcellation better fit the underlying functional connectivity in individuals during the first 3 years, adult area parcellations might still have some utility in developmental studies, especially in children older than 6 years. Additionally, we provide connectivity-based community assignments of the parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

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bioRxiv2024

Hyperglycemia selectively increases cerebral non-oxidative glucose consumption without affecting blood flow

Multiple studies have shown that hyperglycemia increases the cerebral metabolic rate of glucose (CMRglc) in subcortical white matter. This observation remains unexplained. Using positron emission tomography (PET) and euinsulinaemic glucose clamps, we found, for the first time, that acute hyperglycemia increases non-oxidative CMRglc (i.e., aerobic glycolysis (AG)) in subcortical white mater as well as in medial temporal lobe structures, cerebellum and brainstem, all areas with low euglycemic CMRglc. Surprisingly, hyperglycemia did not change regional cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO2), or the blood-oxygen-level-dependent (BOLD) response. Regional gene expression data reveal that brain regions where CMRglc increased have greater expression of hexokinase 2 (HK2). Simulations of glucose transport revealed that, unlike hexokinase 1, HK2 is not saturated at euglycemia, thus accommodating increased AG during hyperglycemia.

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bioRxiv2023

Structure-Function Coupling in Highly Sampled Individual Brains

Structural connections (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to structural connections may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 minutes of diffusion-weighted MRI for SC and 360 minutes of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas. SIGNIFICANCE STATEMENTStructural connections between distant regions of the human brain support networked function that enables cognition and behavior. Improving our understanding of how structure enables function could allow better insight into how brain disconnection injuries impair brain function. Previous work using neuroimaging suggested that structure-function relationships vary systematically across the brain, with structure better explaining function in basic visual/motor areas than in higher-order areas. However, this work was conducted in group-averaged data, which may obscure details of individual-specific structure-function relationships. Using individual-specific densely sampled neuroimaging data, we found that in addition to visual/motor regions, structure strongly predicts function in specific circuits of the higher-order cingulate gyrus. The cingulates structure-function relationship suggests that its organization may be unique among higher-order cortical regions.

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bioRxiv2023

Psychedelic 5-HT2A receptor agonism: neuronal signatures and altered neurovascular coupling.

Psychedelics hold therapeutic promise for mood disorders due to rapid, sustained results. Human neuroimaging studies have reported dramatic serotonin-2A receptor-(5-HT2AR)-dependent changes in functional brain reorganization that presumably reflect neuromodulation. However, the potent vasoactive effects of serotonin have been overlooked. We found psilocybin-mediated alterations to fMRI-HRFs in humans, suggesting potentially altered NVC. To assess the neuronal, hemodynamic, and neurovascular coupling (NVC) effects of the psychedelic 5-HT2AR agonist, 2,5-Dimethoxy-4-iodoamphetamine (DOI), wide-field optical imaging (WFOI) was used in awake Thy1-jRGECO1a mice during stimulus-evoked and resting-state conditions. While DOI partially altered tasked-based NVC, more pronounced NVC alterations occurred under resting-state conditions and were strongest in association regions. Further, calcium and hemodynamic activity reported different accounts of RSFC changes under DOI. Co-administration of DOI and the 5-HT2AR antagonist, MDL100907, reversed many of these effects. Dissociation between neuronal and hemodynamic signals emphasizes a need to consider neurovascular effects of psychedelics when interpreting blood-oxygenation-dependent neuroimaging measures.

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bioRxiv2022

Motion Impact Score for Detecting Spurious Brain-Behavior Associations

Between-participant differences in head motion introduce systematic bias to resting state fMRI brain-wide association studies (BWAS) that is not completely removed by denoising algorithms. Researchers who study traits, or phenotypes associated with in-scanner head motion (e.g. psychiatric disorders) need to know if trait-functional connectivity (FC) effects are biased by residual motion artifact in order to avoid reporting false positive results. We devised an adaptable method, Split Half Analysis of Motion Associated Networks (SHAMAN), to assign a motion impact score to specific trait-FC effects. The SHAMAN approach distinguishes between motion artifact causing overestimation or underestimation of trait-FC effects. SHAMAN was > 95% specific at sample sizes of n = 100 and above. SHAMAN was powered to detect motion overestimation scores 80% of the time at sample sizes of n = 5,000 but could detect motion underestimation scores only 50% of the time at n = 5000, making it most useful for researchers seeking to avoid overestimating trait-FC effects in large BWAS. We computed motion impact scores for trait-FC effect with 45 demographic, biophysical, cognitive, and personality traits from n = 7,270 participants in the Adolescent Brain Cognitive Development (ABCD) Study. After standard denoising with ABCD-BIDS and without motion censoring, 42% (19/45) of traits had significant (p < 0.05) motion overestimation scores and 38% (17/45) of traits had significant motion underestimation scores. Censoring at framewise displacement (FD) < 0.2 mm reduced the proportion of traits with significant motion overestimation scores from 42% to 2% (1/45) but did not decrease the number of traits with significant motion underestimation scores.

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bioRxiv2021

Global cerebrospinal fluid circulation mapping using gold nanoparticle enhanced X-ray microtomography reveals region-specific brain and spinal cord CSF pathways

Cerebrospinal fluid (CSF) movement within the brain interstitium is essential for the development and functioning of the brain. However, the interstitium has largely been thought of as a single entity through which CSF circulates, and it is not known whether specific cell populations within the CNS preferentially interact with CSF. Here, we developed a novel technique for CSF tracking, gold nanoparticle enhanced X-ray microtomography, to achieve micrometer-scale resolution visualization of CSF pathways during development. Using this method and subsequent histological analysis, we map global CSF pathways and present novel particle size-dependent circulation patterns through the CNS. We identify an intraparenchymal CSF circulation that targets stem cell-rich and cholinergic neuronal populations. CSF solute distribution to these areas is mediated by CSF flow along projections from the basal cisterns which is altered in posthemorrhagic hydrocephalus. Our study uncovers region-specific patterns in a biologically driven CSF circulation that has implications for normal brain development and the pathophysiology of hydrocephalus and neurodegenerative disorders.

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bioRxiv2021

Human Fronto-Striatal Connectivity is Organized into Discrete Functional Subnetworks

The striatum is interconnected with the cerebral cortex via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate cortico-striatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited by the practice of averaging neuroimaging data across individuals. Here we utilized highly-sampled resting-state functional connectivity MRI for individually-specific precision functional mapping of cortico-striatal connections. We identified ten discrete, individual-specific subnetworks linking cortex--predominately frontal cortex--to striatum. These subnetworks included previously unknown striatal connections to the human language network. The discrete subnetworks formed a stepped rostral-caudal gradient progressing from nucleus accumbens to posterior putamen; this organization was strongest for projections from medial frontal cortex. The stepped gradient organization fit patterns of fronto-striatal connections better than a smooth, continuous gradient. Thus, precision subnetworks identify detailed, individual-specific stepped gradients of cortico-striatal connectivity that include human-specific language networks.

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bioRxiv2021

Precision Diffusion Imaging

Diffusion tensor imaging (DTI) aims to non-invasively characterize the anatomy and integrity of the brains white matter fibers. To establish individual-specific precision approaches for DTI, we defined its reliability and accuracy as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). DTI methods that allow for crossing fibers (BedpostX [BPX], Q-Ball Imaging [QBI]) estimated excess fibers when insufficient data was present and when the data did not match the model priors. To reduce such overfitting, we developed a novel crossing-fiber diffusion imaging method, Bayesian Multi-tensor Model-selection (BaMM), that is designed for high-quality repeated sampling data sets. BaMM was robust to overfitting, showing high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, the choice of diffusion imaging analysis method is important for the success of individual-specific diffusion imaging. Importantly, for potential clinical applications of individual-specific precision DTI, such as deep brain stimulation (DBS), other forms of neuromodulation or neurosurgical planning, the data quantities required to achieve DTI reliability are lower than for functional MRI measures.

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bioRxiv2020

Cingulo-Opercular Control Network Supports Disused Motor Circuits in Standby Mode

Whole-brain resting-state functional MRI (rs-fMRI) during two weeks of limb constraint revealed that disused motor regions became more strongly connected to the cingulo-opercular network (CON), an executive control network that includes regions of the dorsal anterior cingulate cortex (dACC) and insula (1). Disuse-driven increases in functional connectivity (FC) were specific to the CON and somatomotor networks and did not involve any other networks, such as the salience, frontoparietal, or default mode networks. Censoring and modeling analyses showed that FC increases during casting were mediated by large, spontaneous activity pulses that appeared in the disused motor regions and CON control regions. During limb constraint, disused motor circuits appear to enter a standby mode characterized by spontaneous activity pulses and strengthened connectivity to CON executive control regions. SignificanceMany studies have examined plasticity in the primary somatosensory and motor cortex during disuse, but little is known about how disuse impacts the brain outside of primary cortical areas. We leveraged the whole-brain coverage of resting-state functional MRI (rs-fMRI) to discover that disuse drives plasticity of distant executive control regions in the cingulo-opercular network (CON). Two complementary analyses, pulse censoring and pulse addition, demonstrated that increased functional connectivity between the CON and disused motor regions was driven by large, spontaneous pulses of activity in the CON and disused motor regions. These results point to a previously unknown role for the CON in supporting motor plasticity and reveal spontaneous activity pulses as a novel mechanism for reorganizing the brains functional connections.

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bioRxiv2020

Global Motion Detection and Censoring in High-Density Diffuse Optical Tomography

Motion-induced artifacts can significantly corrupt optical neuroimaging, as in most neuroimaging modalities. For high-density diffuse optical tomography (HD-DOT) with hundreds to thousands of source-detector pair measurements, motion detection methods are underdeveloped relative to both functional magnetic resonance imaging (fMRI) and standard functional near-infrared spectroscopy (fNIRS). This limitation restricts the application of HD-DOT in many challenging situations and subject populations (e.g., bedside monitoring and children). Here, we evaluate a new motion detection method for multichannel optical imaging systems that leverages spatial patterns across channels. Specifically, we introduce a global variance of temporal derivatives (GVTD) metric as a motion detection index. We show that GVTD strongly correlates with external measures of motion and has high sensitivity and specificity to instructed motion - with area under the receiver operator characteristic curve of 0.88, calculated based on five different types of instructed motion. Additionally, we show that applying GVTD-based motion censoring on both task and resting state HD-DOT data with natural head motion results in an improved spatial similarity to fMRI mapping for the same respective protocols (task or rest). We then compare the GVTD similarity scores with several commonly used motion correction methods described in the fNIRS literature, including correlation-based signal improvement (CBSI), temporal derivative distribution repair (TDDR), wavelet filtering, and targeted principal component analysis (tPCA). We find that GVTD motion censoring outperforms other methods and results in spatial maps more similar to matched fMRI data.

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bioRxiv2019

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., motion parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (> 0.1 Hz, here referred to as HF-motion), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0 - 2.5 s.) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 - 2.5 s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is relatively trait-like and more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants. Highlights- Single-band fMRI motion traces show factitious high-frequency content (HF-motion) - The magnitude of HF-motion relates to age and other demographic factors - HF-motion elevates framewise displacement (FD) and causes data loss - Substantial fMRI data can be recovered from censoring by filtering motion traces - Filtering motion traces reduces motion artifacts in functional connectivity

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bioRxiv2019

Aging and the encoding of changes in events: The role of neural activity pattern reinstatement

When encountering unexpected event changes, memories of relevant past experiences must be updated to form new representations. Current models of memory updating propose that people must first generate memory-based predictions to detect and register that features of the environment have changed, then encode the new event features and integrate them with relevant memories of past experiences to form configural memory representations. Each of these steps may be impaired in older adults. Using functional MRI, we investigated these mechanisms in healthy young and older adults. In the scanner, participants first watched a movie depicting everyday activities in a day of an actors life. They next watched a second nearly identical movie in which some scenes ended differently. Crucially, before watching the last part of each activity, the second movie stopped, and participants were asked to mentally replay how the activity previously ended. Three days later, participants were asked to recall the activities. Neural activity pattern reinstatement in medial temporal lobe (MTL) during the replay phase of the second movie was associated with detecting changes and with better memory for the original activity features. Reinstatements in posterior medial cortex (PMC) additionally predicted better memory for changed features. Compared to young adults, older adults showed a reduced ability to detect and remember changes, and weaker associations between reinstatement and memory performance. These findings suggest that PMC and MTL contribute to change processing by reinstating previous event features, and that older adults are less able to use reinstatement to update memory for changed features.

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bioRxiv2018

Correction of respiratory artifacts in MRI head motion estimates

Head motion represents one of the greatest technical obstacles for brain MRI. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, this estimation may be corrupted by factitious effects owing to main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and a comparison single-shot dataset from Oregon Health & Science University. We show unequivocally that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with degraded quality of functional MRI. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects. Subsequently, we demonstrate that utilizing this filter improves post-processing data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.

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bioRxiv2017

Interpreting Temporal Fluctuations In Resting-State Functional Connectivity MRI

Resting-state functional connectivity is a powerful tool for studying human functional brain networks. Temporal fluctuations in functional connectivity, i.e., dynamic functional connectivity (dFC), are thought to reflect dynamic changes in brain organization and non-stationary switching of discrete brain states. However, recent studies have suggested that dFC might be attributed to sampling variability of static FC. Despite this controversy, a detailed exposition of stationarity and statistical testing of dFC is lacking in the literature. This article seeks an in-depth exploration of these statistical issues at a level appealing to both neuroscientists and statisticians.\n\nWe first review the statistical notion of stationarity, emphasizing its reliance on ensemble statistics. In contrast, all FC measures depend on sample statistics. An important consequence is that the space of stationary signals is much broader than expected, e.g., encompassing hidden markov models (HMM) widely used to extract discrete brain states. In other words, stationarity does not imply the absence of brain states. We then expound the assumptions underlying the statistical testing of dFC. It turns out that the two popular frameworks - phase randomization (PR) and autoregressive randomization (ARR) - generate stationary, linear, Gaussian null data. Therefore, statistical rejection can be due to non-stationarity, nonlinearity and/or non-Gaussianity. For example, the null hypothesis can be rejected for the stationary HMM due to nonlinearity and non-Gaussianity. Finally, we show that a common form of ARR (bivariate ARR) is susceptible to false positives compared with PR and an adapted version of ARR (multivariate ARR).\n\nApplication of PR and multivariate ARR to Human Connectome Project data suggests that the stationary, linear, Gaussian null hypothesis cannot be rejected for most participants. However, failure to reject the null hypothesis does not imply that static FC can fully explain dFC. We find that first order AR models explain temporal FC fluctuations significantly better than static FC models. Since first order AR models encode both static FC and one-lag FC, this suggests the presence of dynamical information beyond static FC. Furthermore, even in subjects where the null hypothesis was rejected, AR models explain temporal FC fluctuations significantly better than a popular HMM, suggesting the lack of discrete states (as measured by resting-state fMRI). Overall, our results suggest that AR models are not only useful as a means for generating null data, but may be a powerful tool for exploring the dynamical properties of resting-state fMRI. Finally, we discuss how apparent contradictions in the growing dFC literature might be reconciled.

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