Axon caliber plays a crucial role in determining conduction velocity and, consequently, in the timing and synchronization of neural activation. Noninvasive measurement of axon radii could have significant impact on the understanding of healthy and diseased neural processes. Until now, accurate axon radius mapping has eluded in vivo neuroimaging, mainly due to a lack of sensitivity of the MRI signal to micron-sized axons. Here, we show how – when confounding factors such as extra-axonal water and axonal orientation dispersion are eliminated – heavily diffusion-weighted MRI signals become sensitive to axon radii. However, diffusion MRI is only capable of estimating a single metric, the effective radius, representing the entire axon radius distribution within a voxel that emphasizes the larger axons. Our findings, both in rodents and humans, enable noninvasive mapping of critical information on axon radii, as well as resolve the long-standing debate on whether axon radii can be quantified.

This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging trough DW-MRI presents water diffusion in white (WM) and grey (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b3 ms/m 2 , it has been also shown to fail in GM at high b values (b>>3 ms/m 2 ). Here we hypothesize that the unmodelled soma compartment may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax = 40 ms/m 2 ) and human (bmax = 10 ms/m 2 ) brain. We show that SANDI defines new contrasts representing new complementary information on the brain cyto-and myelo-architecture. Indeed, we show for the first-time maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto-and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

Granule cells are the dominant cell type of the olfactory bulb inhibiting mitral and tufted cells via dendrodendritic synapses; yet the factors regulating the strength of their inhibitory output, and, therefore, their impact on odour discrimination, remain unknown. Here we show that GABAAR β3-subunits are distributed in a somatodendritic pattern, mostly sparing the large granule cell spines also known as gemmules. Granule cell-selective deletion of β3-subunits nearly abolishes spontaneous and muscimol-induced currents mediated by GABAA receptors in granule cells, yet recurrent inhibition of mitral cells is strongly enhanced. Mice with disinhibited granule cells require less time to discriminate both dissimilar as well as highly similar odourants, while discrimination learning remains unaffected. Hence, granule cells are controlled by an inhibitory drive that in turn tunes mitral cell inhibition. As a consequence, the olfactory bulb inhibitory network adjusts the speed of early sensory processing.

Investigating neural activity from a global brain perspective in-vivo has been in the domain of functional Magnetic Resonance Imaging (fMRI) over the past few decades. The intricate neurovascular couplings that govern fMRI's blood-oxygenation-level-dependent (BOLD) functional contrast are invaluable in mapping active brain regions, but they also entail significant limitations, such as non-specificity of the signal to active foci. Diffusion-weighted functional MRI (dfMRI) with relatively high diffusion-weighting strives to ameliorate this shortcoming as it offers functional contrasts more intimately linked with the underlying activity. Insofar, apart from somewhat smaller activation foci, dfMRI's contrasts have not been convincingly shown to offer significant advantages over BOLD-driven fMRI, and its activation maps relied on significant modelling. Here, we study whether dfMRI could offer a better representation of neural activity in the thalamocortical pathway compared to its (spin-echo (SE)) BOLD counterpart. Using high-end forepaw stimulation experiments in the rat at 9.4 T, and with significant sensitivity enhancements due to the use of cryocoils, we show for the first time that dfMRI signals exhibit layer specificity, and, additionally, display signals in areas devoid of SE-BOLD responses. We find that dfMRI signals in the thalamocortical pathway cohere with each other, namely, dfMRI signals in the ventral posterolateral (VPL) thalamic nucleus cohere specifically with layers IV and V in the somatosensory cortex. These activity patterns are much better correlated (compared with SE-BOLD signals) with literature-based electrophysiological recordings in the cortex as well as thalamus. All these findings suggest that dfMRI signals better represent the underlying neural activity in the pathway. In turn, these advanatages may have significant implications towards a much more specific and accurate mapping of neural activity in the global brain in-vivo.

Dendrodendritic synaptic interactions between olfactory bulb mitral and granule cells represent a key neuronal mechanism of odor discrimination. Dendritic release of gamma-aminobutyric acid (GABA) from granule cells contributes to stimulus-dependent, rapid, and accurate odor discrimination, yet the physiological mechanisms governing this release and its behavioral relevance are unknown. Here, we show that granule cells express the voltage-gated sodium channel α-subunit NaV1.2 in clusters distributed throughout the cell surface including dendritic spines. Deletion of NaV1.2 in granule cells abolished spiking and GABA release as well as inhibition of synaptically connected mitral cells (MCs). As a consequence, mice required more time to discriminate highly similar odorant mixtures, while odor discrimination learning remained unaffected. In conclusion, we show that expression of NaV1.2 in granule cells is crucial for physiological dendritic GABA release and rapid discrimination of similar odorants with high accuracy. Hence, our data indicate that neurotransmitter-releasing dendritic spines function just like axon terminals.

White Matter (WM) microstructures, such as axonal density and average diameter, are crucial to the normal function of the Central Nervous System (CNS) as they are closely related with axonal conduction velocities. Conversely, disruptions of these microstructural features may result in severe neurological deficits, suggesting that their noninvasive mapping could be an important step towards diagnosing and following pathophysiology. Whereas diffusion based MRI methods have been proposed to map these features, they typically entail the application of powerful gradients, which are rarely available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures - such as axons and extra-axonal spaces, which were here used as a simple model for the microstructure - and that, for axons parallel to the main magnetic field, the axonal density can be extracted. We then experimentally demonstrate in ex-vivo rat spinal cords that its different tracts - characterized by different microstructures - can be clearly contrasted using the MGE-derived maps. When the quantitative results are compared against ground-truth histology, they reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing a potential and usefulness of the approach to map underlying microstructures using a simple and time-efficient MRI sequence. We further show that a simple general-linear-model can predict the average axonal diameters from the four model parameters, and map these average axonal diameters in the spinal cords. While clearly further modelling and theoretical developments are necessary, we conclude that salient WM microstructural features can be extracted from simple, SNR-efficient multi-gradient echo MRI, and that this paves the way towards easier estimation of WM microstructure in vivo.

Summary The olfactory environment is first represented by glomerular activity patterns in the olfactory bulb. It remains unclear how these representations intersect with sampling behavior to account for the time required to discriminate odors. Using different chemical classes, we investigate glomerular representations and sniffing behavior during olfactory decision-making. Mice rapidly discriminate odorants and learn to increase sniffing frequency at a fixed latency after trial initiation, independent of odor identity. Relative to the increase in sniffing frequency, monomolecular odorants are discriminated within 10-40 ms, while binary mixtures require an additional 60-70 ms. Intrinsic imaging of glomerular activity in anesthetized and awake mice reveals that Euclidean distance between activity patterns and the time needed for discriminations are anti-correlated. Therefore, the similarity of glomerular patterns and their activation strengths, rather than sampling behavior, define the extent of neuronal processing required for odor discrimination, establishing a neural metric to predict olfactory discrimination time.

The olfactory environment is first represented by glomerular activity patterns in the olfactory bulb. It remained unclear, how these activity patterns intersect with sampling behavior to account for the time required to discriminate odors. Using different classes of volatile stimuli, we investigated glomerular activity patterns and sniffing behavior during olfactory decision-making. Mice discriminated monomolecular odorants and binary mixtures on a fast time scale and learned to increase their breathing frequency at a fixed latency after trial initiation, independent of odor identity. Relative to the increase in breathing frequency, monomolecular odorants were discriminated within 10-40 ms while binary mixtures required an additional 60-70 ms. Intrinsic imaging of odor-evoked glomerular activity maps in anesthetized and awake mice revealed that the Euclidean distance between glomerular patterns elicited by different odors, a measure of similarity and activation strength, was anti-correlated with discrimination time. Therefore, the similarity of glomerular patterns and their activation strengths, rather than sampling behavior, define the extent of neuronal processing required for odor discrimination, establishing a neural metric to predict olfactory discrimination time.