Biology subjects

Shmuel, A.

Publications and source records attributed to Shmuel, A..

15 recordsLinked to original sources

bioRxiv2025

Spatial specificity of the functional gradient echo and spin echo BOLD signal across cortical depth at 7 T

Functional magnetic resonance imaging (fMRI) at high magnetic field strengths ([≥] 7 T) is a promising technique to study the functioning of the human brain at the spatial scale of cortical columns and layers. However, measurements most often rely on the blood oxygenation level dependent (BOLD) response sampled with a gradient echo (GE) sequence, which is known to be most sensitive to macrovascular contributions that limit their effective spatial resolution. Alternatively, a spin echo (SE) sequence can be used to increase the weighting toward the microvasculature and, therefore, the location of neural activation. In addition, due to the heterogeneous structure of the cortical cerebrovascular system, the effective spatial resolution can change across cortical depth. For high-resolution fMRI applications, it is hence important to know how much the effective spatial resolution varies across cortical depth. In this study, we used flickering rotating wedge stimuli to induce traveling waves with varying spatial frequencies in the retinotopically organized primary visual cortex (V1), which allowed us to infer the modulation transfer function (MTF) of the BOLD response that characterizes the spatial specificity of the measured signal. We acquired GE- and SE-BOLD data at 7 T and compared the MTF between acquisition techniques at different cortical depths. Our results show a small but consistent increase in spatial specificity when using SE-BOLD. But across cortical depth, both acquisition techniques generally show a similar decrease of specificity toward the pial surface demonstrating the dependence on macrovascular contributions, which needs to be carefully considered when interpreting the results of high-resolution fMRI studies.

neuroscience↗

bioRxiv2025

Rubisco is slow across the tree of life

Rubisco is the main gateway through which inorganic carbon enters the biosphere, catalyzing the vast majority of carbon fixation on Earth. This pivotal enzyme has long been observed to be kinetically constrained. Yet, this impression is based on kinetic measurements heavily focused on eukaryotic rubiscos, a rather conserved group of low genetic diversity. Moreover, the fastest rubiscos that we know of so far were found among the sparsely sampled prokaryotes. Could there be yet faster rubiscos among the uncharted regions of rubiscos phylogenetic diversity? Here, we perform a characterization of more than 250 rubiscos from a wide range of bacteria and archaea, thereby doubling the coverage of the diversity of this key enzyme. We assess the distribution of the carboxylation rates at saturating levels of CO2, and establish that rubisco is a relatively slow enzyme across the tree of life, never exceeding {approx}30 reactions per second at 30{degrees}C. We show that relatively faster subclades share similar evolutionary contexts, involving micro-oxygenic environments or a CO2 concentrating mechanism. Leveraging a simple machine learning model trained on this dataset, we predict the carboxylation rate for all {approx}68,000 sequenced rubisco variants found in nature to date. This study provides the largest and most diverse dataset of natural variants for an enzyme and their associated rates, establishing a solid benchmark for future efforts to predict catalytic rates from sequence data. SignificanceDiscovering a fast carboxylating rubisco has been a long-standing challenge in the scientific community, given its potential impact on sustainable food and fuel production. Yet, only a small fraction of rubiscos natural diversity has been kinetically characterized. Here, we present a large-scale kinetic survey covering the entire spectrum of rubiscos diversity found in nature. Focusing on genetic clusters with above-average rates, we show that rubiscos catalytic rate does not exceed {approx}30 reactions per second at 30{degrees}C. Supported by a machine-learning predictive model, we extend this finding to all sequenced natural variants. Our study provides the most comprehensive kinetic dataset for a single enzyme to date.

systems biology↗

bioRxiv2024

Brain Charts for the Rhesus Macaque Lifespan

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

neuroscience↗

bioRxiv2024

Regional Glymphatic Dysfunction is linked to Spinocerebellar Ataxia Type 3 pathophysiology

Spinocerebellar ataxia type 3 (SCA3) involves neuroinflammation and imbalance between production and clearance of proteins which affects the glymphatic system, the lymphatic-like, fluid-transport system in the brain. However, it is unclear whether SCA3 is related to impairments in glymphatic function. Using multimodal imaging data, 34 SCA3 patients and 36 age-, sex- and educational matched healthy controls (HCs) were compared using multiple glymphatic measurements, including choroid plexus (CP) and cerebrospinal fluid (CSF) volume, diffusion tensor imaging along the perivascular (DTI-ALPS) index, and coupling relationship between blood-oxygen-level-dependent signals and CSF flow (BOLD-CSF coupling). Then, we evaluated regional glymphatic function by dividing DTI-ALPS and BOLD-CSF coupling into anterior, middle, posterior, and cerebellum regions, thereby identifying the spatial variation of glymphatic function in the two groups. We demonstrated that compared with HCs, larger CP and CSF volumes were found in SCA3 patients. More importantly, for DTI-ALPS index and BOLD-CSF coupling, these surrogate markers for glymphatic clearance were weaker in SCA3 patients. Furthermore, altered regional glymphatic functions were most prominent in midbrain, cerebellum and middle regions. Crucially, the altered midbrain, cerebellum, middle and global glymphatic functions were accompanied by the severity of ataxia and other SCA3 symptoms. Similar to other neurodegenerative disorders, the association between multiple glymphatic indexes and SCA3 symptoms suggested that waste clearance is disrupted in SCA3 patients, which shed light on the pathogenesis of this disease from a glymphatic lens. Our findings highlighted the dysregulated glymphatic function as a novel diagnostic marker for SCA3.

neuroscience↗

bioRxiv2023

Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images

Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromise the MRI utility, making it critical to screen the data. Currently, quality assessment requires visual inspection, a time-consuming process that suffers from inter-rater variability. Automated methods to detect MRI artifacts could improve the efficiency of the process. Such automated methods have achieved high accuracy using small datasets, with balanced proportions of MRI data with and without artifacts. With the current trend towards big data in neuroimaging, there is a need for automated methods that achieve accurate detection in large and imbalanced datasets. Deep learning (DL) is the ideal MRI artifact detection algorithm for large neuroimaging databases. However, the inference generated by DL does not commonly include a measure of uncertainty. Here, we present the first stochastic DL algorithm to generate automated, high-performing MRI artifact detection implemented on a large and imbalanced neuroimaging database. We implemented Monte Carlo dropout in a 3D AlexNet to generate probabilities and epistemic uncertainties. We then developed a method to handle class imbalance, namely data-ramping to transfer the learning by extending the dataset size and the proportion of the artifact-free data instances. We used a 34,800 scans (98% clean) dataset. At baseline, we obtained 89.3% testing accuracy (F1 = 0.230). Following the transfer learning (with data-ramping), we obtained 94.9% testing accuracy (F1 = 0.357) outperforming focal cross-entropy (92.9% testing accuracy, F1 = 0.304) incorporated for comparison at handling class imbalance. By implementing epistemic uncertainties, we improved the testing accuracy to 99.5% (F1 = 0.834), outperforming the results obtained in previous comparable studies. In addition, we estimated aleatoric uncertainties by incorporating random flips to the MRI volumes, and demonstrated that aleatoric uncertainty can be implemented as part of the pipeline. The methods we introduce enhance the efficiency of managing large databases and the exclusion of artifact images from big data analyses. HighlightsO_LIWe address the difficulty in automatically detecting artifacts in a large, imbalanced image database. C_LIO_LIWe reproduced high accuracy in detecting artifacts in small balanced datasets. C_LIO_LIWe implemented Monte Carlo (MC) dropout in 3D AlexNet to generate uncertainty metrics. C_LIO_LIWe transfer the learning from a small balanced dataset to a large imbalanced dataset, outperforming focal loss. C_LIO_LIWe outperformed artifact detection in previous studies using comparable large imbalanced datasets C_LIO_LIThe user can select an operating point to consider manual inspection vs. artifact detection error. C_LI

bioinformatics↗

bioRxiv2021

mrHARDIflow : A pipeline tailored for the preprocessing and analysis of Multi-Resolution High Angular diffusion MRI and its application to a variability study of the PRIME-DE database

The validation of advanced methods in diffusion MRI requires finer acquisition resolutions, which is hard to acquire with decent Signal-to-Noise Ratio (SNR) in humans. The use of Non-Human Primates (NHP) and anaesthesia is key to unlock valid microstructural maps, but tools must be adapted and configured finely for them to work well. Here, we propose a novel processing pipeline implemented in Nextflow, designed for robustness and scalability, in a modular fashion to allow for maintainability and a high level of customization and parametrization, tailored for the analysis of diffusion data acquired on multiple spatial resolutions. Modules of processes and workflows were implemented upon cutting edge and state-of-the-art MRI processing technologies and diffusion modelling algorithms, namely Diffusion Tensor Imaging (DTI), Constrained Spherical Deconvolution (CSD) and DIstribution of Anisotropic MicrOstructural eNvironments in Diffusion-compartment imaging (DIAMOND), a multi-tensor distribution estimator. Using our pipeline, we provide an in-depth study of the variability of diffusion models and measurements computed on 32 subjects from 3 sites of the PRIME-DE, a database containing anatomical (T1, T2), functional (fMRI) and diffusion (DWI) imaging of Non-Human Primate (NHP). Together, they offer images acquired over a range of different spatial resolutions, using single-shell and multi-shell b-value gradient samplings, on multiple scanner vendors, that present artifacts at different level of importance. We also perform a reproducibility study of DTI, CSD and DIAMOND measurements outputed by the pipeline, using the Aix-Marseilles site, to ensure our implementation has minimal impact on their variability. We observe very high reproducibility from a majority of diffusion measurements, only gamma distribution parameters computed on the DIAMOND model display a less reproducible behaviour. This should be taken into consideration when future applications are performed. We also show that even if promising, the PRIME-DE diffusion data exhibits a great level of variability and its usage should be done with care to prevent instilling uncertainty in statistical analyses.

neuroscience↗

bioRxiv2020

Paranode stability requires UNC5B expression by oligodendrocytes

In the mature CNS, netrin-1 is expressed by neurons and oligodendrocytes and implicated in the stability of axo-oligodendroglial paranodal junctions. Here we report that the netrin receptor UNC5B is highly expressed by mature oligodendrocytes and enriched at paranodes. We demonstrate that paranodes become disorganized following conditional deletion of UNC5B in oligodendrocytes, with disruption of the interface between glial loops and detachment of loops from the axon. As a result, Caspr1 and Kv1.1 disperse along the axon, internodes fail to lengthen and compact myelin periodicity is reduced. Paranodal and axoglial domain disorganization progressively worsens and a delay in motor learning develops in aged mice lacking oligodendroglial UNC5B. Altered glial loop ultrastructure and reduced levels of claudin-11 and JAM-C tight junction proteins support the conclusion that disruption of autotypic junctions between paranodal loops underlies paranode disorganization. Our findings reveal an essential contribution of oligodendroglial UNC5B at paranodes that is required for the stability of mature myelin.

neuroscience↗

bioRxiv2020

Linear gain effect of theta-burst and 15 Hz rTMS on intra-cortically measured neuronal responses to oriented grating visual stimuli

Transcranial magnetic stimulation (TMS) involves the application of time-pulsed magnetic fields to cortical tissue through a coil positioned near the head. TMS is widely used for studying the mechanisms underlying perception and behaviour and is considered a potential therapeutic technique for various conditions. However, the application of TMS has been hindered by the lack of understanding of its mechanism of action. Here we studied the effects of three repetitive TMS (rTMS) paradigms on intra-cortical neuronal responses to oriented gratings in cat area 18. Each of stimulation protocols, including continuous theta-burst, intermittent theta-burst, and 15 Hz rTMS, consisted of 600 pulses. Application of continuous theta-burst and 15 Hz rTMS suppressed the action potential response to oriented grating stimuli for 1.5-6 minutes. In contrast, application of intermittent theta-burst stimulation was associated with enhancement of the action potential response [~]15 minutes following TMS. Neuronal assemblies that were more responsive before the application of rTMS, were affected more than neurons that were less responsive before rTMS. In spite of these changes, the preferred orientation, the orientation tuning of the multi-unit activity and the spatial pattern of the responses recorded from assemblies neurons remained unaffected. Our findings demonstrate that rTMS does not modify the functional selectivities of ensembles of neurons; rather, it has a linear gain effect on their responses.

neuroscience↗

bioRxiv2019

Dexmedetomidine - commonly used in resting-state and neurovascular coupling studies - is prone to inducing seizures in rats but not in wild type mice

Functional MRI (fMRI) utilizes changes in metabolic and hemodynamic signals to indirectly infer the underlying local changes in neuronal activity. To investigate the mechanisms of fMRI responses, spontaneous fluctuations, and functional connectivity in the resting-state, it is important to pursue fMRI in animal models. Animal studies commonly use dexmedetomidine sedation. It has been demonstrated that potent sensory stimuli administered under dexmedetomidine are prone to inducing seizures in Sprague-Dawley (SD) rats. Here we combined optical imaging of intrinsic signals and cerebral blood flow with neurophysiological recordings to measure responses in rat area S1FL to electrical forepaw stimulation administered at 8 Hz. We show that the increased susceptibility to seizures starts no later than 1 hour and ends no sooner than 3 hours after initiating a continuous administration of dexmedetomidine. By administering different combinations of anesthetic and sedative agents, we demonstrate that dexmedetomidine is the sole agent necessary for the increased susceptibility to seizures. The increased susceptibility to seizures prevails under a combination of 0.3%-0.5% isoflurane and dexmedetomidine anesthesia. The blood-oxygenation and cerebral blood flow responses to seizures induced by forepaw stimulation have a higher amplitude and a larger spatial extent relative to physiological responses to the same stimuli. The epileptic activity and the associated blood oxygenation and cerebral blood flow responses stretched beyond the stimulation period. We observed seizures in response to forepaw stimulation with 1-2 mA pulses administered at 8 Hz. In contrast, responses to stimuli administered at 4 Hz were seizure-free. We demonstrate that such seizures are generated not only in SD rats but also in Long-Evans rats, but not in C57BL6 mice stimulated with similar potent stimuli under dexmedetomidine sedation. We conclude that high-amplitude hemodynamic functional imaging responses evoked by peripheral stimulation in rats sedated with dexmedetomidine are possibly due to the induction of epileptic activity. Therefore, caution should be practiced in experiments that combine the administration of potent stimuli with dexmedetomidine sedation. We propose stimulation paradigms that elicit seizure-free, well detectable neurophysiological and hemodynamic responses in rats. We further conclude that the increased susceptibility to seizures under dexmedetomidine sedation is species dependent.

neuroscience↗

bioRxiv2018

A Novel Animal Model Of Somatosensory-Evoked Reflex Seizures Induced By Peripheral Stimulation

ObjectiveWe introduce a novel animal model of somatosensory stimulation-induced reflex seizures which generates focal seizures without causing damage to the brain.\n\nMethodsSpecifically, we electrically stimulated digits or forepaws of adult rats sedated with dexmedetomidine while imaging cerebral blood volume and recording neurophysiological activity in cortical area S1FL. For the recordings, we either inserted a linear probe into the D3 digit representation or we performed surface electrocorticography (ECoG) recordings.\n\nResultsPeripheral stimulation of a digit or the forepaw elicited seizures that were followed by a refractory period with decreased neuronal activity, or another seizure or a normal response. LFP amplitudes in response to electrical pulses during the seizures (0.28 {+/-} 0.03 mV) were higher than during normal evoked responses (0.25 {+/-} 0.05 mV) and refractory periods (0.2 {+/-} 0.08 mV). Seizures generated during the stimulation period showed prolonged after-discharges that were sustained for 20.9{+/-}1.9 s following the cessation of the stimulus. High-frequency oscillations were observed prior to and during the seizures, with amplitudes higher than those associated with normal evoked responses. The seizures were initially focal. Optical imaging of the cerebral blood volume response showed that they propagated from the onset zone to adjacent cortical areas, beyond the S1FL representation of the stimulated digit or forepaw. The spatial extent during seizures was on average 1.74 times larger during the stimulation and 4.1 times following its cessation relative to normal evoked responses. Seizures were recorded not only by probes inserted into cortex but also with ECoG arrays (24.1{+/-}5.8 seizures per rat) placed over the dura matter, indicating that the seizures were not induced by damage caused by inserting the probes to cortex. Stimulation of the forepaw elicited more seizures (18.8{+/-}8.5 seizures per rat) than stimulation of a digit (1.7{+/-}0.7). Unlike rats sedated with dexmedetomidine, rats anesthetized with urethane showed no seizures, indicating that the seizures may depend on the use of the mild sedative dexmedetomidine.\n\nSignificanceOur proposed animal model generates seizures induced by electrical sensory stimulation free of artifacts and brain damage. It can be used for studying the mechanisms underlying the generation and propagation of reflex seizures and for evaluating antiepileptic drugs.\n\nHIGHLIGHTSO_LIPeripheral stimulation of the rat forepaw or digits induces seizures\nC_LIO_LISeizures are evoked with no direct application of convulsants, electro-stimulation or damage to the brain\nC_LIO_LISeizures are focal at onset, then spread beyond the spatial representation of the digit or forepaw\nC_LIO_LISeizures persist following the cessation of the stimulus\nC_LIO_LIProposed animal model may support the study of reflex seizures and improving therapeutic interventions\nC_LI

neuroscience↗

bioRxiv2018

Human Connectome Project resting state fMRI data organized into 60 fine-scaled retinotopically organized regions in cortical areas V1, V2 and V3

The data comprises 60 regions of interest (ROIs) from V1, V2, and V3 of the human visual cortex. Preprocessed data from the Human Connectome Project (HCP) 900 subjects public data release were utilized: 220 subjects were randomly selected, each with 4 scans of resting state fMRI data. Given that these subjects did not have retinotopy scans performed, the visual areas were defined using an anatomical template from Benson et al. (2014). Visual areas from each hemisphere were further divided along dorsal-ventral lines into quadrants, resulting in 4 quadrants per subject. Within each quadrant, fine scaled ROIs were defined by subdividing each visual area into 5 regions according to eccentricity. These data may be useful for studying retinotopically organized functional connectivity in the visual cortex using the HCP 3 Tesla dataset.

neuroscience↗

bioRxiv2017

Partial Correlation Analysis Reveals Abnormal Retinotopically Organized Functional Connectivity of Visual Areas in Amblyopia

Amblyopia is a prevalent developmental visual disorder of childhood that typically persists in adults. Due to altered visual experience during critical periods of youth, the structure and function of adult visual cortex is abnormal. In addition to substantial deficits shown with task-based fMRI, previous studies have used resting state measures to demonstrate altered long-range connectivity in amblyopia. This is the first study in amblyopia to analyze connectivity between regions of interest that are smaller than a single cortical area and to apply partial correlation analysis to reduce network effects. We specifically assess short-range connectivity between retinotopically defined regions of interest within the occipital lobe of 8 subjects with amblyopia and 7 subjects with normal vision (aged 19-45). The representations of visual areas V1, V2, and V3 within each of the four quadrants of visual space were further subdivided into three regions based on maps of visual field eccentricity. Connectivity between pairs of all nine regions of interest in each quadrant was tested via correlation and partial correlation for both groups. Only the tests of partial correlation, i.e., correlation between time courses of two regions following the regression of time courses from all other regions, yielded significant differences between resting state functional connectivity in amblyopic and normal subjects. Subjects with amblyopia showed significantly higher partial correlation between para-foveal and more eccentric representations within V1, and this effect associated with poor acuity of the worse eye. In addition, we observed reduced correlation in amblyopic subjects between isoeccentricity regions in V1 and V2, and separately, between such regions in V2 and V3. We conclude that partial correlation-based connectivity is altered in an eccentricity-dependent pattern in visual field maps of amblyopic patients. Moreover, results are consistent with known clinical and psychophysical vision loss. More broadly, this provides evidence that abnormal cortical adaptations to disease may be better isolated with tests of partial correlation connectivity than with the regular correlation techniques that are currently widely used.

neuroscience↗

bioRxiv2017

Subtypes of functional brain connectivity as early markers of neurodegeneration in Alzheimer’s disease

HighlightsO_LIReliable functional brain network subtypes accompany cognitive impairment in AD\nC_LIO_LISymptom-related subtypes exist in the default-mode, limbic and salience networks\nC_LIO_LIA limbic subtype is associated with a familial risk of AD in healthy older adults\nC_LIO_LILimbic subtypes also associate with beta amyloid deposition and ApoE4\nC_LI\n\nIn BriefWe found reliable subtypes of functional brain connectivity networks in older adults, associated with AD-related clinical symptoms in patients as well as several AD risk factors/biomarkers in asymptomatic individuals.\n\nSummaryThe heterogeneity of brain degeneration has not been investigated yet for functional brain network connectivity, a promising biomarker of Alzheimers disease. We coupled cluster analysis with resting-state functional magnetic resonance imaging to discover connectivity subtypes in healthy older adults and patients with cognitive disorders related to Alzheimers disease, noting associations between subtypes and cognitive symptoms in the default-mode, limbic and salience networks. In an independent asymptomatic cohort with a family history of Alzheimers dementia, the connectivity subtypes had good test-retest reliability across all tested networks. We found that a limbic subtype was overrepresented in these individuals, which was previously associated with symptoms. Other limbic subtypes showed associations with cerebrospinal fluid A{beta}1-42 levels and ApoE4 genotype. Our results demonstrate the existence of reliable subtypes of functional brain networks in older adults and support future investigations in limbic connectivity subtypes as early biomarkers of Alzheimers degeneration.

neuroscience↗

bioRxiv2016

A more accurate account of the effect of k-space sampling and signal decay on the effective spatial resolution in functional MRI

The effects of k-space sampling and signal decay on the effective spatial resolution of MRI and functional MRI (fMRI) are commonly assessed by means of the magnitude point-spread function (PSF), defined as the absolute values (magnitudes) of the complex MR imaging PSF. It is commonly assumed that this magnitude PSF signifies blurring, which can be quantified by its full-width at half-maximum (FWHM). Here we show that the magnitude PSF fails to accurately represent the true effects of k-space sampling and signal decay.\n\nFirstly, a substantial part of the width of the magnitude PSF is due to MRI sampling per se. This part is independent of any signal decay and its effect depends on the spatial frequency composition of the imaged object. Therefore, it cannot always be expected to introduce blurring. Secondly, MRI reconstruction is typically followed by taking the absolute values (magnitude image) of the reconstructed complex image. This introduces a non-linear stage into the process of image formation. The complex imaging PSF does not fully describe this process, since it does not reflect the stage of taking the magnitude image. Its corresponding magnitude PSF fails to correctly describe this process, since convolving the original pattern with the magnitude PSF is different from the true process of taking the absolute following a convolution with the complex imaging PSF. Lastly, signal decay can have not only a blurring, but also a high-pass filtering effect. This cannot be reflected by the strictly positive width of the magnitude PSF.\n\nAs an alternative, we propose to first approximate the MRI process linearly. We then model the linear approximation by decomposing it into a signal decay-independent MR sampling part and an approximation of the signal decay effect. We approximate the latter as a convolution with a Gaussian PSF or, if the effect is that of high-pass filtering, as reversing the effect of a convolution with a Gaussian PSF. We show that for typical high-resolution fMRI at 7 Tesla, signal decay in Spin-Echo has a moderate blurring effect (FWHM = 0.89 voxels, corresponds to 0.44 mm for 0.5 mm wide voxels). In contrast, Gradient-Echo acts as a moderate high-pass filter that can be interpreted as reversing a Gaussian blurring with FWHM = 0.59 voxels (0.30 mm for 0.5 mm wide voxels). Our improved approximations and findings hold not only for Gradient-Echo and Spin-Echo fMRI but also for GRASE and VASO fMRI. Our findings support the correct planning, interpretation, and modeling of high-resolution fMRI.

neuroscience↗

bioRxiv2016

Spatial specificity of the functional MRI blood oxygenation response relative to neuronal activity

Previous attempts at characterizing the spatial specificity of the blood oxygenation level dependent functional MRI (BOLD fMRI) response by estimating its point-spread function (PSF) have conventionally relied on spatial representations of visual stimuli in area V1. Consequently, their estimates were confounded by the width and scatter of receptive fields of V1 neurons. Here, we circumvent these limits by instead using the inherent cortical spatial organization of ocular dominance columns (ODCs) to determine the PSF for both Gradient Echo (GE) and Spin Echo (SE) BOLD imaging at 7 Tesla. By applying Markov Chain Monte Carlo sampling on a probabilistic generative model of imaging ODCs, we quantified the PSFs that best predict the spatial structure and magnitude of differential ODCs responses. Prior distributions for the ODC model parameters were determined by analyzing published data of cytochrome oxidase patterns from post-mortem histology of human V1 and of neurophysio-logical ocular dominance indices. The most probable PSF full-widths at halfmaximum were 0.82 mm (SE) and 1.02 mm (GE). Our results provide a quantitative basis for the spatial specificity of BOLD fMRI at ultra-high fields, which can be used for planning and interpretation of high-resolution differential fMRI of fine-scale cortical organizations.

neuroscience↗