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Placental function plays a crucial role in fetal development, as it serves as the primary interface for delivery of nutrients and oxygen from the mother to fetus. Magnetic resonance imaging (MRI) has significantly improved our ability to visualize and understand the placenta's complex structure and function. This review provides an up-to-date examination of the most common and novel placental MRI techniques. It will also discuss the clinical applications of MRI in diagnosing and monitoring placental insufficiency, as well as its implications for fetal growth restriction (FGR) and congenital heart disease (CHD). Ongoing research using multi-parametric MRI techniques aims to develop novel biomarkers and uncover the relationships between placental parameters and pre-onset diseased states, ultimately contributing to better maternal and fetal health outcomes, which is essential to better guide clinical judgement.
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White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.
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Connectome , Magnetic Resonance Imaging , Memory, Short-Term , Visual Pathways , Humans , Memory, Short-Term/physiology , Connectome/methods , Visual Pathways/physiology , Visual Pathways/diagnostic imaging , Adult , Male , Female , Visual Perception/physiology , White Matter/diagnostic imaging , White Matter/physiology , White Matter/anatomy & histology , Primary Visual Cortex/physiology , Primary Visual Cortex/diagnostic imaging , Geniculate Bodies/physiology , Geniculate Bodies/diagnostic imaging , Young Adult , Visual Cortex/physiology , Visual Cortex/diagnostic imagingABSTRACT
BACKGROUND: This study aimed to explore the characteristics of abnormal regional resting-state functional magnetic resonance imaging (rs-fMRI) activity in comatose patients in the early period after cardiac arrest (CA), and to investigate their relationships with neurological outcomes. We also explored the correlations between jugular venous oxygen saturation (SjvO2) and rs-fMRI activity in resuscitated comatose patients. We also examined the relationship between the amplitude of the N20-baseline and the rs-fMRI activity within the intracranial conduction pathway of somatosensory evoked potentials (SSEPs). METHODS: Between January 2021 and January 2024, eligible post-resuscitated patients were screened to undergo fMRI examination. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of rs-fMRI blood oxygenation level-dependent (BOLD) signals were used to characterize regional neural activity. Neurological outcomes were evaluated using the Glasgow-Pittsburgh cerebral performance category (CPC) scale at 3 months after CA. RESULTS: In total, 20 healthy controls and 31 post-resuscitated patients were enrolled in this study. The rs-fMRI activity of resuscitated patients revealed complex changes, characterized by increased activity in some local brain regions and reduced activity in others compared to healthy controls (P < 0.05). However, the mean ALFF values of the whole brain were significantly greater in CA patients (P = 0.011). Among the clusters of abnormal rs-fMRI activity, the cluster values of ALFF in the left middle temporal gyrus and inferior temporal gyrus and the cluster values of ReHo in the right precentral gyrus, superior frontal gyrus and middle frontal gyrus were strongly correlated with the CPC score (P < 0.001). There was a strong correlation between the mean ALFF and SjvO2 in CA patients (r = 0.910, P < 0.001). The SSEP N20-baseline amplitudes in CA patients were negatively correlated with thalamic rs-fMRI activity (all P < 0.001). CONCLUSIONS: This study revealed that abnormal rs-fMRI BOLD signals in resuscitated patients showed complex changes, characterized by increased activity in some local brain regions and reduced activity in others. Abnormal BOLD signals were associated with neurological outcomes in resuscitated patients. The mean ALFF values of the whole brain were closely related to SjvO2 levels, and changes in the thalamic BOLD signals correlated with the N20-baseline amplitudes of SSEP responses. TRIAL REGISTRATION: NCT05966389 (Registered July 27, 2023).
Subject(s)
Coma , Heart Arrest , Magnetic Resonance Imaging , Survivors , Humans , Male , Female , Magnetic Resonance Imaging/methods , Prospective Studies , Middle Aged , Coma/physiopathology , Coma/diagnostic imaging , Heart Arrest/complications , Heart Arrest/physiopathology , Aged , Survivors/statistics & numerical data , Cohort Studies , Rest/physiology , AdultABSTRACT
Human presence and activities have profoundly altered animals' habitats, exposing them to greater risks but also providing new opportunities and resources. The animals' capacity to effectively navigate and strike a balance between risks and benefits is crucial for their survival in the Anthropocene era. Red foxes (Vulpes vulpes), adept urban dwellers, exhibit behavioral plasticity in human-altered environments. We investigated variations in detection frequency on trail cameras and the behavioral responses (explorative, bold, and fearful) of wild red foxes living along an urbanization gradient when exposed to a metal bin initially presented clean and then filled with anthropogenic food. All fox populations displayed an increased interest and similar explorative behavioral responses toward the anthropogenic food source, irrespective of the urbanization gradient. Despite no impact on explorative behaviors, foxes in more urbanized areas initially showed heightened fear toward the empty bin, indicating increased apprehension toward novel objects. However, this fear diminished over time, and in the presence of food, urban foxes displayed slightly reduced fear compared with their less urban counterparts. Our results highlight foxes' potential for adaptability to human landscapes, additionally underscoring the nuanced interplay of fear and explorative behavioral response of populations living along the urbanization gradient.
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To achieve a comprehensive understanding of spontaneous brain dynamics in humans, in vivo acquisition of intrinsic activity across both cortical and subcortical regions is necessary. Here we present advanced whole-brain, resting-state functional magnetic resonance imaging (rs-fMRI) data acquired at 7 Tesla with 1.5 mm isotropic voxel resolution. Functional images were obtained from 56 healthy adults (33 females, ages 19-39 years) in two runs of 15 min eyes-open wakeful rest. The high spatial resolution and short echo times of the multiband echo-planar imaging (EPI) protocol optimizes blood oxygen level-dependent (BOLD)-sensitivity for the subcortex while concurrent respiratory and cardiac measures enable retrospective correction of physiological noise, resulting in data that is highly suitable for researchers interested in subcortical BOLD signal. Functional timeseries were coregistered to high-resolution T1-weighted structural data (0.75 mm isotropic voxels) acquired during the same scanning session. To accommodate data reutilization, functional and structural images were formatted to the Brain Imaging Data Structure (BIDS) and preprocessed with fMRIPrep.
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PURPOSE: There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated. METHODS: Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author. RESULTS: A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease. CONCLUSION: A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.
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Background: Resting-state fMRI analyses have been used to examine functional connectivity in the aging brain. Recently, fluctuations in the fMRI BOLD signal have been used as a potential marker of integrity in neural systems. Despite its increasing popularity, the results of BOLD variability analyses and traditional seed-based functional connectivity analyses have rarely been compared. The current study examined fMRI BOLD signal variability and default mode network seed-based analyses in healthy older and younger adults to better understand the unique contributions of these methodological approaches. Methods: Thirty-four healthy participants were separated into a younger adult group (age 25-35, n = 17) and an older adult group (age 65+, n = 17). For each participant, a map of the standard deviation of the BOLD signal (SDBOLD) was derived. Group comparisons examined differences in resting-state SDBOLD in younger versus older adults. Seed-based analyses were used to examine differences between younger and older adults in the default mode network. Results: Between-group comparisons revealed significantly greater BOLD variability in widespread brain regions in older relative to younger adults. There were no significant differences between younger and older adults in the default mode network connectivity. Conclusion: The current findings align with an increasing number of studies reporting greater BOLD variability in older relative to younger adults. The current results also suggest that the traditional resting state examination methods may not detect nuanced age-related differences. Further large-scale studies in an adult lifespan sample are needed to better understand the functional relevance of the BOLD variability in normative aging.
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BACKGROUND: Migraine has been associated with functional brain changes including altered connectivity and activity both during and between headache attacks. Recent studies established that the variability of the blood-oxygen-level-dependent (BOLD) signal is an important attribute of brain activity, which has so far been understudied in migraine. In this study, we investigate how time-varying measures of BOLD variability change interictally in episodic migraine patients. METHODS: Two independent resting state functional MRI datasets acquired on 3T (discovery cohort) and 1.5T MRI scanners (replication cohort) including 99 episodic migraine patients (n3T = 42, n1.5T=57) and 78 healthy controls (n3T = 46, n1.5T=32) were analyzed in this cross-sectional study. A framework using time-varying measures of BOLD variability was applied to derive BOLD variability states. Descriptors of BOLD variability states such as dwell time and fractional occupancy were calculated, then compared between migraine patients and healthy controls using Mann-Whitney U-tests. Spearman's rank correlation was calculated to test associations with clinical parameters. RESULTS: Resting-state activity was characterized by states of high and low BOLD signal variability. Migraine patients in the discovery cohort spent more time in the low variability state (mean dwell time: p = 0.014, median dwell time: p = 0.022, maximum dwell time: p = 0.013, fractional occupancy: p = 0.013) and less time in the high variability state (mean dwell time: p = 0.021, median dwell time: p = 0.021, maximum dwell time: p = 0.025, fractional occupancy: p = 0.013). Higher uptime of the low variability state was associated with greater disability as measured by MIDAS scores (maximum dwell time: R = 0.45, p = 0.007; fractional occupancy: R = 0.36, p = 0.035). Similar results were observed in the replication cohort. CONCLUSION: Episodic migraine patients spend more time in a state of low BOLD variability during rest in headache-free periods, which is associated with greater disability. BOLD variability states show potential as a replicable functional imaging marker in episodic migraine.
Subject(s)
Magnetic Resonance Imaging , Migraine Disorders , Rest , Humans , Migraine Disorders/diagnostic imaging , Migraine Disorders/physiopathology , Female , Male , Adult , Cross-Sectional Studies , Rest/physiology , Oxygen/blood , Middle Aged , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/physiopathology , Cohort Studies , Young AdultABSTRACT
BACKGROUND: If brain effective connectivity network modelling (ECN) could be accurately achieved, early diagnosis of neurodegenerative diseases would be possible. It has been observed in the literature that Dynamic Bayesian Network (DBN) based methods are more successful than others. However, DBNs have not been applied easily and tested much due to computational complexity problems in structure learning. NEW METHOD: This study introduces an advanced method for modelling brain ECNs using improved discrete DBN (Improved- dDBN) which addresses the computational challenges previously limiting DBN application, offering solutions that enable accurate and fast structure modelling. RESULTS: The practical data and prior sizes needed for the convergence to the globally correct network structure are proved to be much smaller than the theoretical ones using simulated dDBN data. Besides, Hill Climbing is shown to converge to the true structure at a reasonable iteration step size when the appropriate data and prior sizes are used. Finally, importance of data quantization methods are analysed. COMPARISON WITH EXISTING METHODS: The Improved-dDBN method performs better and robust, when compared to the existing methods for realistic scenarios such as varying graph complexity, various input conditions, noise cases and non-stationary connections. The data used in these tests is the simulated fMRI BOLD time series proposed in the literature. CONCLUSIONS: Improved-dDBN is a good candidate to be used on real datasets to accelerate developments in brain ECN modelling and neuroscience. Appropriate data and prior sizes can be identified based on the approach proposed in this study for global and fast convergence.
Subject(s)
Bayes Theorem , Brain , Magnetic Resonance Imaging , Models, Neurological , Humans , Brain/physiology , Brain/diagnostic imaging , Magnetic Resonance Imaging/methods , Nerve Net/physiology , Nerve Net/diagnostic imaging , Connectome/methods , Computer SimulationABSTRACT
Brain activity continuously fluctuates over time, even if the brain is in controlled (e.g., experimentally induced) states. Recent years have seen an increasing interest in understanding the complexity of these temporal variations, for example with respect to developmental changes in brain function or between-person differences in healthy and clinical populations. However, the psychometric reliability of brain signal variability and complexity measures-which is an important precondition for robust individual differences as well as longitudinal research-is not yet sufficiently studied. We examined reliability (split-half correlations) and test-retest correlations for task-free (resting-state) BOLD fMRI as well as split-half correlations for seven functional task data sets from the Human Connectome Project to evaluate their reliability. We observed good to excellent split-half reliability for temporal variability measures derived from rest and task fMRI activation time series (standard deviation, mean absolute successive difference, mean squared successive difference), and moderate test-retest correlations for the same variability measures under rest conditions. Brain signal complexity estimates (several entropy and dimensionality measures) showed moderate to good reliabilities under both, rest and task activation conditions. We calculated the same measures also for time-resolved (dynamic) functional connectivity time series and observed moderate to good reliabilities for variability measures, but poor reliabilities for complexity measures derived from functional connectivity time series. Global (i.e., mean across cortical regions) measures tended to show higher reliability than region-specific variability or complexity estimates. Larger subcortical regions showed similar reliability as cortical regions, but small regions showed lower reliability, especially for complexity measures. Lastly, we also show that reliability scores are only minorly dependent on differences in scan length and replicate our results across different parcellation and denoising strategies. These results suggest that the variability and complexity of BOLD activation time series are robust measures well-suited for individual differences research. Temporal variability of global functional connectivity over time provides an important novel approach to robustly quantifying the dynamics of brain function. PRACTITIONER POINTS: Variability and complexity measures of BOLD activation show good split-half reliability and moderate test-retest reliability. Measures of variability of global functional connectivity over time can robustly quantify neural dynamics. Length of fMRI data has only a minor effect on reliability.
Subject(s)
Brain , Connectome , Magnetic Resonance Imaging , Humans , Magnetic Resonance Imaging/standards , Magnetic Resonance Imaging/methods , Reproducibility of Results , Brain/physiology , Brain/diagnostic imaging , Connectome/standards , Connectome/methods , Oxygen/blood , Male , Female , Rest/physiology , Adult , Image Processing, Computer-Assisted/methods , Image Processing, Computer-Assisted/standards , Brain Mapping/methods , Brain Mapping/standardsABSTRACT
Introduction: Dynamic contrast-enhanced (DCE) MRI and arterial spin labeling (ASL) MRI enable non-invasive measurement of renal blood flow (RBF), whereas blood oxygenation level-dependent (BOLD) MRI enables non-invasive measurement of the apparent relaxation rate (R2*), an indicator of oxygenation. This study was conducted to evaluate the potential role of these MRI modalities in assessing RBF and oxygenation in dogs. The correlation between contrast-enhanced ultrasound (CEUS) and the MRI modalities was examined and also the ability of the MRI modalities to detect pharmacologically induced changes. Methods: RBF, using CEUS, ASL- and DCE-MRI, as well as renal oxygenation, using BOLD-MRI of eight adult beagles were assessed at two time-points, 23 weeks apart. During each time point, the anesthetized dogs received either a control (0.9% sodium chloride) or a dopamine treatment. For each time point, measurements were carried out over 2 days. An MRI scan at 3 T was performed on day one, followed by CEUS on day two. Results: Using the model-free model with caudal placement of the arterial input function (AIF) region of interest (ROI) in the aorta, the DCE results showed a significant correlation with ASL measured RBF and detected significant changes in blood flow during dopamine infusion. Additionally, R2* negatively correlated with ASL measured RBF at the cortex and medulla, as well as with medullary wash-in rate (WiR) and peak intensity (PI). ASL measured RBF, in its turn, showed a positive correlation with cortical WiR, PI, area under the curve (AUC) and fall time (FT), and with medullary WiR and PI, but a negative correlation with medullary rise time (RT). During dopamine infusion, BOLD-MRI observed a significant decrease in R2* at the medulla and entire kidney, while ASL-MRI demonstrated a significant increase in RBF at the cortex, medulla and the entire kidney. Conclusion: ASL- and BOLD-MRI can measure pharmacologically induced changes in renal blood flow and renal oxygenation in dogs and might allow detection of changes that cannot be observed with CEUS. However, further research is needed to confirm the potential of ASL- and BOLD-MRI in dogs and to clarify which analysis method is most suitable for DCE-MRI in dogs.
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A major challenge for human neuroimaging using functional MRI is the differentiation of neuronal excitation and inhibition which may induce positive and negative BOLD responses. Here we present an innovative multi-contrast laminar functional MRI technique that offers comprehensive and quantitative imaging of neurovascular (CBF, CBV, BOLD) and metabolic (CMRO2) responses across cortical layers at 7 Tesla. This technique was first validated through a finger-tapping experiment, revealing 'double-peak' laminar activation patterns within the primary motor cortex. By employing a ring-shaped visual stimulus that elicited positive and negative BOLD responses, we further observed distinct neurovascular and metabolic responses across cortical layers and eccentricities in the primary visual cortex. This suggests potential feedback inhibition of neuronal activities in both superficial and deep cortical layers underlying the negative BOLD signals in the fovea, and also illustrates the neuronal activities in visual areas adjacent to the activated eccentricities.
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BACKGROUND: T2*BOLD is based on myocardial deoxyhemoglobin content to reflect the state of myocardial oxygenation. Quantitative flow ratio is a tool for assessing coronary blood flow based on invasive coronary angiography. PURPOSE: This study aimed to evaluate the correlation between T2*BOLD and QFR in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease. METHODS: Fifty patients with MVCAD with at least 1 significant coronary artery stenosis (diameter stenosis > 50%) and 21 healthy control subjects underwent coronary angiography combined with QFR measurements and cardiovascular magnetic resonance (CMR). QFR ≤ 0.80 was considered to indicate the presence of hemodynamic obstruction. RESULTS: Totally 60 (54%) obstructive vessels had hemodynamic change. Between stenotic coronary arteries (QFR ≤ 0.8) and normal vessels, T2*BOLD showed AUCs of 0.97, 0.69, and 0.91 for left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries and PI displayed AUCs of 0.89, 0.77 and 0.90 (all p > 0.05, except for LAD). The AUCs of T2*BOLD between stenotic coronary arteries (QFR > 0.8) and normal vessels were 0.86, 0.72, and 0.85 for LAD, LCX and RCA; while, PI showed AUCs of 0.93, 0.86, and 0.88, respectively (p > 0.05). Moreover, T2*BOLD displayed AUCs of 0.96, 0.74, and 0.91 for coronary arteries as before between coronary arteries with stenosis (QFR ≤ 0.8 and > 0.8), but the mean PI of LAD, LCX and RCA showed no significant differences between them. CONCLUSION: T2* BOLD and QFR have good correlation in diagnosing stenotic coronary arteries with hemodynamic changes in patients with stable multi-vessel CAD. T2* BOLD is superior to semi-quantitative perfusion imaging in analyzing myocardial ischemia without stress.
Subject(s)
Coronary Angiography , Coronary Stenosis , Humans , Male , Female , Coronary Stenosis/diagnostic imaging , Coronary Stenosis/physiopathology , Middle Aged , Coronary Angiography/methods , Aged , Case-Control Studies , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/physiopathology , Coronary Circulation , Magnetic Resonance Imaging/methodsABSTRACT
OBJECTIVE: Temporal lobe epilepsy (TLE) has a high probability of becoming drug resistant and is frequently considered for surgical intervention. However, 30% of TLE cases have nonlesional magnetic resonance imaging (MRI) scans, which is associated with worse surgical outcomes. Characterizing interactions between temporal and extratemporal structures in these patients may help understand these poor outcomes. Simultaneous intracranial electroencephalography-functional MRI (iEEG-fMRI) can measure the hemodynamic changes associated with interictal epileptiform discharges (IEDs) recorded directly from the brain. This study was designed to characterize the whole brain patterns of IED-associated fMRI activation recorded exclusively from the mesial temporal lobes of patients with nonlesional TLE. METHODS: Eighteen patients with nonlesional TLE undergoing iEEG monitoring with mesial temporal IEDs underwent simultaneous iEEG-fMRI at 3 T. IEDs were marked, and statistically significant clusters of fMRI activation were identified. The locations of IED-associated fMRI activation for each patient were determined, and patients were grouped based on the location and pattern of fMRI activation. RESULTS: Two patterns of IED-associated fMRI activation emerged: primarily localized (n = 7), where activation was primarily located within the ipsilateral temporal lobe, and primarily diffuse (n = 11), where widespread bilateral extratemporal activation was detected. The primarily diffuse group reported significantly fewer focal to bilateral tonic-clonic seizures and had better postsurgical outcomes. SIGNIFICANCE: Simultaneous iEEG-fMRI can measure the hemodynamic changes associated with focal IEDs not visible on scalp EEG, such as those arising from the mesial temporal lobe. Significant fMRI activation associated with these IEDs was observed in all patients. Two distinct patterns of IED-associated activation were seen: primarily localized to the ipsilateral temporal lobe and more widespread, bilateral activation. Patients with widespread IED associated-activation had fewer focal to bilateral tonic-clonic seizures and better postsurgical outcome, which may suggest a neuroprotective mechanism limiting the spread of ictal events.
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Electrocorticography , Electroencephalography , Epilepsy, Temporal Lobe , Magnetic Resonance Imaging , Temporal Lobe , Humans , Magnetic Resonance Imaging/methods , Male , Epilepsy, Temporal Lobe/surgery , Epilepsy, Temporal Lobe/diagnostic imaging , Epilepsy, Temporal Lobe/physiopathology , Female , Adult , Temporal Lobe/diagnostic imaging , Temporal Lobe/physiopathology , Temporal Lobe/surgery , Middle Aged , Young Adult , Electroencephalography/methods , Electrocorticography/methods , Oxygen/blood , Adolescent , Brain Mapping/methodsABSTRACT
Different animal behavioral phenotypes maintained and selectively bred over multiple generations may be underscored by dissimilar gut microbial community compositions or not have any significant dissimilarity in community composition. Operating within the microbiota-gut-brain axis framework, we anticipated differences in gut microbiome profiles between zebrafish (Danio rerio) selectively bred to display the bold and shy personality types. This would highlight gut microbe-mediated effects on host behavior. To this end, we amplified and sequenced a fragment of the 16S rRNA gene from the guts of bold and shy zebrafish individuals (n=10) via Miseq. We uncovered no significant difference in within-group microbial diversity nor between-group microbial community composition of the two behavioral phenotypes. Interestingly, though not statistically different, we determined that the gut microbial community of the bold phenotype was dominated by Burkholderiaceae, Micropepsaceae, and Propionibacteriaceae. In contrast, the shy phenotype was dominated by Beijerinckaceae, Pirelullacaeae, Rhizobiales_Incertis_Sedis, and Rubinishaeraceae. The absence of any significant difference in gut microbiota profiles between the two phenotypes would suggest that in this species, there might exist a stable "core" gut microbiome, regardless of behavioral phenotypes, and or possibly, a limited role for the gut microbiota in modulating this selected-for host behavior. This is the first study to characterize the gut microbial community of distinct innate behavioral phenotypes of the zebrafish (that are not considered dysbiotic states) and not rely on antibiotic or probiotic treatments to induce changes in behavior. Such studies are crucial to our understanding of the modulating impacts of the gut microbiome on normative animal behavior.
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In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory-gated approaches, such as 4D flow magnetic resonance imaging (MRI), cannot capture CSF movement in real time because of limited temporal resolution and, in addition, deteriorate in accuracy at low fluid velocities. Other techniques like real-time phase-contrast-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability, even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional MRI (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath-holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.
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No one is perfect, and organisms that perform well in some habitat or with respect to some tasks, do so at the cost of performance in others: there are inescapable trade-offs. Organismal trade-offs govern the structure and function of ecosystems and attempts to demonstrate and quantify trade-offs have therefore been an important goal for ecologists. In addition, trade-offs are a key component in trait-based ecosystem models. Here, I synthesise evidence of trade-offs in plankton organisms, from bacteria to zooplankton, and show how a slow-fast gradient in life histories emerges. I focus on trade-offs related to the main components of an organism's Darwinian fitness, that is resource acquisition, survival, and propagation. All consumers need to balance the need to eat without being eaten, and diurnal vertical migration, where zooplankton hide at depth during the day to avoid visual predators but at the cost of missed feeding opportunities in the productive surface layer, is probably the best documented result of this trade-off. However, there are many other more subtle but equally important behaviours that similarly are the result of an optimisation of these trade-offs. Most plankton groups have also developed more explicit defence mechanisms, such as toxin production or evasive behaviours that are harnessed in the presence of their predators; the costs of these have often proved difficult to quantify or even demonstrate, partly because they only materialise under natural conditions. Finally, all multicellular organisms must allocate time and resources among growth, reproduction, and maintenance (e.g. protein turnover and DNA repair), and mate finding may compromise both survival and feeding. The combined effects of all these trade-offs is the emergence of a slow-fast gradient in the pace-of-life, likely the most fundamental principle for the organisation of organismal life histories. This crystallisation of trade-offs may offer a path to further simplification of trait-based models of marine ecosystems.
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GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.
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Resting-state functional magnetic resonance imaging (rs-fMRI) is increasingly being used to infer the functional organization of the brain. Blood oxygen level-dependent (BOLD) features related to spontaneous neuronal activity, are yet to be clearly understood. Prior studies have hypothesized that rs-fMRI is spontaneous event-related and these events convey crucial information about the neuronal activity in estimating resting state functional connectivity (FC). Attempts have been made to extract these temporal events using a predetermined threshold. However, the thresholding methods in addition to being very sensitive to noise, may consider redundant events or exclude the low-valued inflection points. Here, we extract the event-related temporal onsets from the rs-fMRI time courses using a zero-frequency resonator (ZFR). The ZFR reflects the transient behavior of the BOLD events at its output. The conditional rate (CR) of the BOLD events occurring in a time course with respect to a seed time course is used to derive static FC. The temporal activity around the estimated events called high signal-to-noise ratio (SNR) segments are also obtained in the rs-fMRI time course and are then used to compute static and dynamic FCs during rest. Coactivation pattern (CAP) is the dynamic FC obtained using the high SNR segments driven by the ZFR. The static FC demonstrates that the ZFR-based CR distinguishes the coactivation and non-coactivation scores well in the distribution. CAP analysis demonstrated the stable and longer dwell time dominant resting state functional networks with high SNR segments driven by the ZFR. Static and dynamic FC analysis underpins that the ZFR-driven temporal onsets of BOLD events derive reliable and consistent FCs in the resting brain using a subset of the time points.