Biology subjects

Shemesh, N.

Publications and source records attributed to Shemesh, N..

At least 19 recordsLinked to original sources

bioRxiv2025

Increased striatal coupling one week after ischemic stroke revealed by ultrafast functional MRI

BackgroundNetwork reorganization following ischemic stroke is thought to play a role in recovery. Although cortico-cortical reorganization is widely established, changes in interhemispheric striatal connections following ischemia remain poorly understood, even when stroke occurs in motor areas. Given the importance of the striatum to motor function, we investigated network-level striatal coupling in stroke using ultrafast resting-state fMRI, which has recently been shown to facilitate the dissection of synchronous oscillatory activity better than its conventional [~]1 sec time-resolution counterparts. MethodsA cohort of (N=18) sedated rats were randomized and N=9 rats underwent unilateral photothrombotic ischemic lesioning in motor cortex. One week after the lesion, when plasticity and recovery are well established, all animals were scanned on a 9.4T MRI scanner using a cryogenic coil using an ultrafast resting-state functional MRI sequence with temporal resolution of 90 ms. Data were collected for 24 minutes, and spectral power, phase locking, and functional connectivity were quantified. Histology was performed to confirm lesion extent. ResultsWhile cortico-cortical power, connectivity and synchrony were diminished one week post-stroke as expected, we surprisingly found increased striato-striatal power, synchrony and functional connectivity in the stroked group compared with the control group. In stroked animals, the spectral power in the ultraslow oscillation frequency band (0.02-0.4 Hz) significantly increased in the striatum while decreasing in the cortex. When data were undersampled to "conventional" fMRI temporal resolution (900 ms), the striatal effects were lost, revealing the power of ultrafast fMRI approaches in unveiling such phenomena. ConclusionsIncreased striato-striatal coupling, in the form of increased synchrony, spectral power, and functional connectivity, was revealed by ultrafast resting-state fMRI, but not conventional temporal resolution resting-state fMRI. Our findings suggest more involvement of subcortical areas in network reorganization than previously thought.

neuroscience↗

bioRxiv2024

Deuterium Metabolic Imaging Phenotypes Mouse Glioblastoma Heterogeneity Through Glucose Turnover Kinetics

Glioblastomas are aggressive brain tumors with dismal prognosis. One of the main bottlenecks for developing more effective therapies for glioblastoma stems from their histologic and molecular heterogeneity, leading to distinct tumor microenvironments and disease phenotypes. Effectively characterizing these features would improve the clinical management of glioblastoma. Glucose flux rates through glycolysis and mitochondrial oxidation have been recently shown to quantitatively depict glioblastoma proliferation in mouse models (GL261 and CT2A tumors) using dynamic glucose-enhanced (DGE) deuterium spectroscopy. However, the spatial features of tumor microenvironment phenotypes remain hitherto unresolved. Here, we develop a DGE Deuterium Metabolic Imaging (DMI) approach for profiling tumor microenvironments through glucose conversion kinetics. Using a multimodal combination of tumor mouse models, novel strategies for spectroscopic imaging and noise attenuation, and histopathological correlations, we show that tumor lactate turnover mirrors phenotype differences between GL261 and CT2A mouse glioblastoma, whereas recycling of the peritumoral glutamate-glutamine pool is a potential marker of invasion capacity in pooled cohorts, linked to secondary brain lesions. These findings were validated by histopathological characterization of each tumor, including cell density and proliferation, peritumoral invasion and distant migration, and immune cell infiltration. Our study bodes well for precision neuro-oncology, highlighting the importance of mapping glucose flux rates to better understand the metabolic heterogeneity of glioblastoma and its links to disease phenotypes.

cancer biology↗

bioRxiv2024

Dissecting push/pull interactions in the rat subcortical auditory pathway

The role of subcortical structures in binaural integration is of great interest for auditory processing. The inferior colliculus (IC) is the main auditory midbrain center where ascending and descending auditory projections converge, which was suggested to encode auditory information via a push-pull mechanism between the two ICs. However, the origin of this push-pull mechanism in the brain and how it interacts with other upstream/downstream subcortical areas is still a matter of great debate. Here, we harness functional MRI (fMRI) in combination with IC lesions in the rat to dissect the push-pull interaction from a pathway-wide perspective. We find evidence for the push-pull mechanism in IC through negative/positive fMRI signals in the ipsilateral/contralateral ICs upon monaural stimulation. By unilaterally lesioning the corresponding contralateral IC, we demonstrate the necessity of collicular integrity and intercollicular interactions for the push-pull interaction. Using binaural stimulation and IC lesions, we show that the push-pull interaction is exerted also in binaural processing. Finally, we demonstrate that, at least at the population level revealed by fMRI, the main push-pull interactions occur first at the IC level, and not earlier, and that the outcome of the push-pull "calculation" is relayed downstream to MGB. This dissection of the push-pull interaction sheds light into subcortical auditory function.

neuroscience↗

bioRxiv2024

Evidence for a push-pull interaction between superior colliculi in monocular dynamic vision mode

Visual perception can operate in two distinct vision modes - static and dynamic - that have been associated with different neural activity regimes in the superior colliculus (SC). The static vision mode (low flashing frequencies) is associated with strong SC activation modulated by cortical gain and inhibitory intertectal effects, while the dynamic vision mode (high flashing frequencies) evokes the continuity illusion, with associated suppression of SC neural activity. However, the pathway-wide mechanisms underpinning the dynamic vision mode remain poorly understood, especially in terms of corticotectal and tectotectal feedback. Here, we harness rat functional MRI combined with brain lesions to investigate whole-pathway interactions in the dynamic vision mode. In the SC, we find contralateral suppression of activity opposing positive ipsilateral neural activation upon monocular visual stimulation in the dynamic vision mode. A cortical amplification effect was confirmed for both static and dynamic vision modes through cortical lesions, while further lesioning ipsilateral SC led to a boost in the contralateral negative signals, suggesting an active push-pull interaction between ipsilateral and contralateral SCs during the dynamic vision mode regime. This push-pull interaction is specific to the dynamic vision mode; in the static vision mode, both SCs show similar response polarities. These results highlight hitherto unreported frequency-dependent modulations in the tectotectal pathway and further challenge the contemporary notion that intertectal connections solely serve as reciprocal inhibitory mechanisms for avoiding visual blur during saccade occurrence. One Sentence SummaryOpposing signals between superior colliculi in the dynamic vision mode suggest an active push-pull interaction within the tectotectal commissural pathway.

neuroscience↗

bioRxiv2024

High-resolution perfusion imaging in rodents using pCASL at 9.4 T

Adequate perfusion is critical for maintaining normal brain function and aberrations thereof are hallmarks of many diseases. Pseudo-Continuous Arterial Spin Labeling (pCASL) MRI enables noninvasive perfusion mapping without contrast agent injection and with higher signal-to-noise ratio (SNR) than alternative methods. Despite its great potential, pCASL remains challenging, unstable, and relatively low-resolution in rodents - especially in mice - thereby limiting the investigation of perfusion properties in many transgenic or other relevant rodent models of disease. Here, we address this gap by developing a novel experimental setup for high-resolution pCASL imaging in mice and combining it with the enhanced SNR of cryogenic probes. We show that our new experimental setup allows for optimal positioning of the carotids within the cryogenic coil, rendering labelling reproducible. With the proposed methodology, we managed to increase the spatial resolution of pCASL perfusion images by a factor of 15 in mice; a factor of 6 in rats is gained compared to the state of the art just by virtue of the cryogenic coil. We also show that the improved pCASL perfusion imaging allows much better delineation of specific brain areas, both in healthy animals as well as in rat and mouse models of stroke. Our results bode well for future high-definition pCASL perfusion imaging in rodents. Data availabilityData will be freely made available upon request.

neuroscience↗

bioRxiv2024

Non-invasive MRI of Blood-Cerebrospinal Fluid-Barrier Function: a Functional Biomarker of Early Alzheimer's Disease Pathology

INTRODUCTIONChoroid plexus (CP) dysfunction is thought to contribute to toxic protein build-up in neurodegenerative disorders, including Alzheimers disease (AD). However, the dynamics of this process remain unknown, mainly due to the paucity of in-vivo methods capable of assessing CP function. METHODSHere, we harness recent developments in Arterial Spin Labelling MRI to measure water delivery across the blood cerebrospinal fluid barrier (BCSFB) as a proxy for CP function, as well as cerebral blood flow (CBF), at different stages of AD progression in the widely used triple transgenic mouse model (3Tg), which recapitulates aspects of disease pathology. RESULTSTotal BCSFB-mediated water delivery is significantly higher in 3Tg mice (>50%) from 8 weeks (preclinical stage), while tissue parameters such as CBF and T1 are not different between groups at all ages. DISCUSSIONOur work shows changes in BCSFB function in the early stages of AD, providing a novel biomarker of pathology.

neuroscience↗

bioRxiv2023

Efficient PCA denoising of spatially correlated MRI data

Mar[c]enko-Pastur (MP) PCA denoising is emerging as an effective means for noise suppression in MRI acquisitions with redundant dimensions. However, MP-PCA performance is severely compromised by spatially correlated noise - an issue typically affecting most modern MRI acquisitions - almost to the point of returning the original images with little or no noise removal. In this study, we develop and apply two new strategies that enable efficient and robust denoising even in the presence of severe spatial correlations. This is achieved by measuring a-priori information about the noise variance and combing these estimates with PCA denoising thresholding concepts. The two denoising strategies developed here are: 1) General PCA (GPCA) denoising that uses a-priori noise variance estimates without assuming specific noise distributions; and 2) Threshold PCA (TPCA) denoising which removes noise components with a threshold computed from a-priori estimated noise variance to determine the upper bound of the MP distribution. These strategies were tested in simulations with known ground truth and applied for denoising diffusion MRI data acquired using pre-clinical (16.4T) and clinical (3T) MRI scanners. In synthetic phantoms, MP-PCA failed to denoise spatially correlated data, while GPCA and TPCA correctly classified all signal/noise components. In cases where the noise variance was not accurately estimated (as can be the case in many practical scenarios), TPCA still provides excellent denoising performance. Our experiments in pre-clinical diffusion data with highly corrupted by spatial correlated noise revealed that both GPCA and TPCA robustly denoised the data while MP-PCA denoising failed. In in vivo diffusion MRI data acquired on a clinical scanner in healthy subjects, MP-PCA weakly removed noised, while TPCA was found to have the best performance, likely due to misestimations of the noise variance. Thus, our work shows that these novel denoising approaches can strongly benefit future pre-clinical and clinical MRI applications.

neuroscience↗

bioRxiv2022

Activation/suppression balances in rat Superior Colliculus encode the visual continuity illusion

When visual stimuli are presented at a sufficiently high temporal frequency, visual perception shifts from the static to dynamic vision mode, thereby facilitating a continuity illusion which is key for correctly identifying continuous and moving objects and placing them in the context of the surrounding environment. However, how this continuity illusion is encoded along the entire visual pathway remains poorly understood, with disparate Flicker Fusion Frequency (FFF) thresholds measured at retinal, cortical, and behavioural levels. Here, we hypothesized that these disparities may suggest that other brain areas may be involved in encoding the shift from static to dynamic vision modes. We employ a comprehensive approach encompassing behavioural measurements, whole brain activation mapping with high fidelity functional MRI (fMRI), and local electrophysiological validation for studying the mechanisms underlying the shift from static to dynamic vision modes in the rat. Our behavioural measurements reported an FFF threshold proxy of 18{+/-}2 Hz. At the network level, functional MRI revealed that the superior colliculus (SC) exhibits marked signal transitions from positive to negative fMRI signal regimes at the behaviourally measured FFF threshold surrogates, with a strong linear correlation between fMRI signal and behaviour, while thalamic and cortical visual areas displayed a significantly poorer correlation with the behaviour. fMRI-driven neurometric curves approximated the behavioural psychometric curve in SC but not in the other visual areas. Electrophysiological recordings in SC suggested that these fMRI signals transitions arise from strong neural activation/suppression at low/high frequency regimes, respectively, and that a transition between these regimes occurs around the measured FFF threshold proxies. Lesions in V1 further reinforced that these transitions originate in SC. Combined, our data suggests a critical role for SC in encoding temporal frequency discriminations, in particular the shifts from the static to the dynamic vision modes.

neuroscience↗

bioRxiv2022

Optimisation and Pre-clinical Demonstration of Temporal Diffusion Ratio for Imaging Restricted Diffusion

Temporal Diffusion Ratio (TDR) is a recently proposed dMRI technique (DellAcqua, 2019) which provides contrast between areas with restricted diffusion and areas either without restricted diffusion or with length scales too small for characterisation. Hence, it has a potential for mapping pore sizes, in particular large axon diameters or other cellular structures. TDR employs the signal from two dMRI acquisitions obtained with the same, large, b-value but with different diffusion times and gradient settings. TDR is advantageous as it employs standard acquisition sequences, does not make any assumptions on the underlying tissue structure and does not require any model fitting, avoiding issues related to model degeneracy. This work for the first time optimises the TDR diffusion sequences in simulation for a range of different tissues and scanner constraints. We extend the original work (which considers substrates containing cylinders) by additionally considering the TDR signal obtained from spherical structures, representing cell soma in tissue. Our results show that contrasting an acquisition with short gradient duration and short diffusion time with an acquisition with long gradient duration and long diffusion time improves the TDR contrast for a wide range of pore configurations. Additionally, in the presence of Rician noise, computing TDR from a subset (50% or fewer) of the acquired diffusion gradients rather than the entire shell as proposed originally further improves the contrast. In the last part of the work the results are demonstrated experimentally on rat spinal cord. In line with simulations, the experimental data shows that optimised TDR improves the contrast compared to non-optimised TDR. Furthermore, we find a strong correlation between TDR and histology measurements of axon diameter. In conclusion, we find that TDR has great potential and is a very promising alternative (or potentially complement) to model-based approaches for mapping pore sizes and restricted diffusion in general. HighlightsO_LITemporal Diffusion Ratio (TDR) 2-seq approach maps areas with restricted diffusion C_LIO_LIOptimised gradient waveform pair is: long {delta} + low G and short {delta} + high G C_LIO_LIIf data is noisy calculating TDR using HARDI acquisition subsets increases accuracy C_LIO_LIWe demonstrate TDR for the first time pre-clinically in rat spinal cord C_LIO_LIPre-clinical TDR values are strongly correlated with axon diameter C_LI

bioengineering↗

bioRxiv2022

Extensive topographic remapping and functional sharpening in the adult rat visual pathway upon first visual experience

Understanding the dynamics of stability/plasticity balances during adulthood is pivotal for learning, disease, and recovery from injury. However, the brain-wide topography of sensory remapping remains unknown. Here, using a first-of-its-kind setup for delivering patterned visual stimuli in a rodent Magnetic Resonance Imaging (MRI) scanner, coupled with biologically-inspired computational models, we noninvasively mapped brain-wide properties - receptive fields (RFs) and spatial frequency (SF) tuning curves - that were insofar only available from invasive electrophysiology or optical imaging. We then tracked the RF dynamics in the chronic Visual Deprivation Model (VDM) of plasticity, and found that light exposure progressively promoted a large-scale topographic remapping in adult rats. Upon light exposure, the initially unspecialized visual pathway progressively evidenced sharpened RFs (smaller and more spatially selective) and enhanced spatial frequency tuning curves. Our findings reveal that visual experience following VDM reshapes both structure and function of the visual system and shifts the stability/plasticity balance in adults.

neuroscience↗

bioRxiv2022

Brain-wide sensory aberrations in a Parkinson's Disease mouse model revealed by functional MRI

Parkinsons disease (PD) is associated with irreparable damage to dopaminergic neurons in brain areas involved in movement. Frequently, a very early symptom of PD involves an impaired sense of smell, while other studies suggest a broader impairment of other sensory modalities. Still, the associated brain-wide mechanisms underlying this phenomenon remain unclear. Here, we harness in vivo functional Magnetic Resonance Imaging (fMRI) at 9.4T to investigate how the olfactory and visual systems are affected in an -Synuclein (Syn) mouse model of PD. We find significant aberrations in fMRI responses along both sensory pathways including decreases in activation extent and in activation amplitude. Deficits in the olfactory system were larger than in the visual pathway, but nevertheless both sensory systems were clearly impacted, suggesting a more overarching mechanism may be involved. To further ensure that the aberrations observed in the fMRI signals were not driven solely by putative vascular deficiency, we quantified c-FOS expression in the olfactory system and found statistically significant decreases in the PD group when compared to age-matched controls. Hence, our findings indicate a neural origin for the observed fMRI aberrations. Our findings thus demonstrate a more global deficiency in sensory systems in the (Syn) mouse model. One Sentence SummaryParkinsons disease (PD) is associated with an impaired sense of smell and more generally sensory deficits, but the associated brain-wide mechanisms remain unclear; here, we investigate aberrations in BOLD-fMRI responses along sensory pathways in an SYN PD mouse model.

neuroscience↗

bioRxiv2022

Resonant waves drive long-range correlations in fMRI signals

Spontaneous fluctuations in functional Magnetic Resonance Imaging (fMRI) signals correlate across distant brain areas, shaping functionally relevant intrinsic networks. However, the generative mechanism of fMRI signal correlations - and in particular their link with locally-detected ultra-slow oscillations - remain unclear. To investigate this link, we record ultrafast ultrahigh field fMRI signals (9.4 Tesla, temporal resolution = 38 milliseconds) from rat brains across three anesthesia conditions. Power at frequencies extending up to 0.3 Hz is detected consistently across rat brains, and is modulated by anesthesia level. Principal component analysis reveals a repertoire of modes, in which transient oscillations organize with fixed phase relationships across distinct cortical and subcortical structures. Oscillatory modes are found to vary between conditions, resonating at faster frequencies under medetomidine sedation and reducing both in number, frequency, and duration with the addition of isoflurane. Peaking in power within clear anatomical boundaries, these oscillatory modes point to an emergent systemic property, questioning current assumptions regarding the local origin of oscillations detected in fMRI and providing novel insights into the organizing principles underpinning spontaneous long-range functional connectivity. One Sentence SummaryOscillations in fMRI signals organize in stationary wave patterns driving condition-specific long-range correlations across brain structures

neuroscience↗

bioRxiv2021

In vivo Correlation Tensor MRI reveals microscopic kurtosis in the human brain on a clinical 3T scanner

Diffusion MRI (dMRI) has become one of the most important imaging modalities for noninvasively probing tissue microstructure. Diffusion Kurtosis MRI (DKI) quantifies the degree of non-gaussian diffusion, which in turn has been shown to increase sensitivity towards, e.g., disease and orientation mappings in neural tissue. However, the specificity of DKI is limited as different microstructural sources can contribute to the total diffusional kurtosis, including: variance in diffusion tensor magnitudes (Kiso), variance due to intravoxel diffusion anisotropy (Kaniso), and microscopic kurtosis (K) related to restricted diffusion and/or microstructural disorder. The latter in particular is typically ignored in diffusion MRI signal modeling as it is assumed to be negligible. Recently, Correlation Tensor MRI (CTI) based on Double-Diffusion-Encoding (DDE) was introduced for kurtosis source separation and revealed non negligible K in preclinical imaging. Here, we implemented CTI for the first time on a clinical 3T scanner and investigated the kurtosis sources in healthy subjects. A robust framework for kurtosis source separation in humans is introduced, followed by estimation of the relative importance of K in the healthy brain. Using this clinical CTI approach, we find that K significantly contributes to total diffusional kurtosis both in gray and white matter tissue but, as expected, not in the ventricles. The first K maps of the human brain are presented. We find that the spatial distribution of K provides a unique source of contrast, appearing different from isotropic and anisotropic kurtosis counterparts. We further show that ignoring K - as done by many contemporary methods based on multiple gaussian component approximation for kurtosis source estimation - biases the estimation of other kurtosis sources and, perhaps even worse, compromises their interpretation. Finally, a twofold acceleration of CTI is discussed in the context of potential future clinical applications. We conclude that CTI has much potential for future in vivo microstructural characterizations in healthy and pathological tissue. HighlightsO_LICorrelation Tensor MRI (CTI) was recently proposed to resolve kurtosis sources C_LIO_LIWe implemented CTI on a 3T scanner to study kurtosis sources in the human brain C_LIO_LIIsotropic, anisotropic, and microscopic kurtosis sources were successfully resolved C_LIO_LIMicroscopic kurtosis (K) significantly contributes to overall kurtosis in human brain C_LIO_LIK provides a novel source of contrast in the human brain in vivo C_LI

neuroscience↗

bioRxiv2021

Soma and Neurite Density MRI (SANDI) of the in-vivo mouse brain

Diffusion MRI (dMRI) provides unique insights into the neural tissue milieu by probing interaction of diffusing molecules and tissue microstructure. Most dMRI techniques focus on white matter tissues (WM) due to the relatively simpler modelling of diffusion in the more organized tracts; however, interest is growing in gray matter characterisations. The Soma and Neurite Density MRI (SANDI) methodology harnesses a model incorporating water diffusion in spherical objects (assumed to be associated with cell bodies) and in impermeable "sticks" (representing neurites), which potentially enables the characterisation of cellular and neurite densities. Recognising the importance of rodents in animal models of development, aging, plasticity, and disease, we here sought to develop SANDI for preclinical imaging and provide a validation of the methodology by comparing its metrics with the Allen mouse brain atlas. SANDI was implemented on a 9.4T scanner equipped with a cryogenic coil, and experiments were carried out on N=6 mice. Pixelwise, ROI-based, and atlas comparisons were performed, and results were also compared to more standard Diffusion Kurtosis MRI (DKI) metrics. We further investigated effects of different pre-processing pipelines, specifically the comparison of magnitude and real-valued data, as well as different acceleration factors. Our findings reveal excellent reproducibility of the SANDI parameters, including the sphere and stick fraction as well as sphere size. More strikingly, we find a very good rank correlation between SANDI-driven soma fraction and Allen brain atlas contrast (which represents the cellular density in the mouse brain). Although some DKI parameters (FA, MD) correlated with some SANDI parameters in some ROIs, they did not correlate nearly as well as SANDI parameters with the Allen atlas, suggesting a much more specific nature of the SANDI parameters. We conclude that SANDI is a viable preclinical MRI technique that can greatly contribute to research on brain tissue microstructure.

neuroscience↗

bioRxiv2021

Optogenetic Activation of Striatal D1/D2 Medium Spiny Neurons Differentially Engages Downstream Connected Areas Beyond the Basal Ganglia

The basal ganglia (BG) are a group of subcortical nuclei responsible for motor control, motor learning and executive function. Central to BG function are striatal medium spiny neurons (MSNs) expressing D1 and D2 dopamine receptors. D1 and D2 MSNs are typically considered functional antagonists that facilitate voluntary movements and inhibit competing motor patterns, respectively. While their opposite role is well documented for certain sensorimotor loops of the BG-thalamocortical network, it is unclear whether MSNs maintain a uniform functional role across the striatum and which influence they exert on brain areas outside the BG. Here, we addressed these questions by combining optogenetic activation of D1 and D2 MSNs in the mouse ventrolateral caudoputamen (vl CPu) with whole-brain functional MRI (fMRI) recordings. Neuronal excitation of either cell population in the vl CPu evoked distinct activity patterns in key regions of the BG-thalamocortical network including the pallidum, thalamus and motor cortex. Importantly, we report that striatal D1 and D2 MSN stimulation differentially engaged cerebellar and prefrontal regions. We characterised these long-range interactions by computational modelling of effective connectivity and confirmed that changes in D1 / D2 output drive functional relationships between regions within and beyond the BG. These results suggest a more complex functional organization of MSNs across the striatum than previously anticipated and provide evidence for the existence of an interconnected fronto - BG - cerebellar network modulated by striatal D1 and D2 MSNs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=129 HEIGHT=200 SRC="FIGDIR/small/436576v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@a18349org.highwire.dtl.DTLVardef@1b256faorg.highwire.dtl.DTLVardef@16c454aorg.highwire.dtl.DTLVardef@1392b23_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2021

On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge.

Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal encodes specific properties of the underlying diffusion process. In the last two decades, several signal representations have been proposed to fit the dMRI signal and decode such properties. Most methods, however, are tested and developed on a limited amount of data, and their applicability to other acquisition schemes remains unknown. With this work, we aimed to shed light on the generalizability of existing dMRI signal representations to different diffusion encoding parameters and brain tissue types. To this end, we organized a community challenge - named MEMENTO, making available the same datasets for fair comparisons across algorithms and techniques. We considered two state-of-the-art diffusion datasets, including single-diffusion-encoding (SDE) spin-echo data from a human brain with over 3820 unique diffusion weightings (the MASSIVE dataset), and double (oscillating) diffusion encoding data (DDE/DODE) of a mouse brain including over 2520 unique data points. A subset of the data sampled in 5 different voxels was openly distributed, and the challenge participants were asked to predict the remaining part of the data. After one year, eight participant teams submitted a total of 80 signal fits. For each submission, we evaluated the mean squared error, the variance of the prediction error and the Bayesian information criteria. Most predictions predicted either multi-shell SDE data (37%) or DODE data (22%), followed by cartesian SDE data (19%) and DDE (18%). Most submissions predicted the signals measured with SDE remarkably well, with the exception of low and very strong diffusion weightings. The prediction of DDE and DODE data seemed more challenging, likely because none of the submissions explicitly accounted for diffusion time and frequency. Next to the choice of the model, decisions on fit procedure and hyperparameters play a major role in the prediction performance, highlighting the importance of optimizing and reporting such choices. This work is a community effort to highlight strength and limitations of the field at representing dMRI acquired with trending encoding schemes, gaining insights into how different models generalize to different tissue types and fiber configurations over a large range of diffusion encodings.

neuroscience↗

bioRxiv2021

Improving stroke detection via Correlation Tensor MRI

Noninvasively detecting and characterizing modulations in cellular scale micro-architecture is a desideratum for contemporary neuroimaging. Diffusion MRI (dMRI) has become the mainstay methodology for probing microstructure, and, in ischemia, its contrasts have revolutionized stroke management. However, the biological underpinnings of the contrasts observed in conventional dMRI in general and in ischemia in particular are still highly debated since the markers only indirectly reporter on microstructure. Here, we present Correlation Tensor MRI (CTI), a method that rather than measuring diffusion, harnesses diffusion correlations as its source of contrast. We show that CTI can resolve the sources of diffusional kurtosis, which in turn, provide dramatically enhanced specificity and sensitivity towards ischemia. In particular, the sensitivity towards ischemia nearly doubles, both in grey matter (GM) and white matter (WM), and unique signatures for neurite beading, cell swelling, and edema are inferred from CTI. The enhanced sensitivity and specificity endowed by CTI bodes well for future applications in biomedicine, basic neuroscience, and in the clinic.

neuroscience↗

bioRxiv2020

Functional MRI of large scale activity in behaving mice

Behaviour involves complex dynamic interactions across many brain regions. Detecting whole-brain activity in mice performing sophisticated behavioural tasks could facilitate insights into distributed processing underlying behaviour, guide local targeting, and help bridge the disparate spatial scales between rodent and human studies. Here, we present a comprehensive approach for recording brain-wide activity with functional magnetic resonance imaging (fMRI) compatible with a wide range of behavioural paradigms and neuroscience questions. We introduce hardware and procedural advances to allow multi-sensory, multi-action behavioural paradigms in the scanner. We identify signal artefacts arising from task-related body movements and propose novel strategies to reduce them. We validate and explore our approach in a 4-odour classical conditioning and a visually-guided operant task, illustrating how it can be used to extract information so far inaccessible to rodent behaviour studies. Our work paves the way for future studies combining fMRI and local circuit techniques during complex behaviour to tackle multi-scale behavioural neuroscience questions.

neuroscience↗