Potentiating glymphatic drainage minimizes post-traumatic cerebral oedema.

Cerebral oedema is associated with morbidity and mortality after traumatic brain injury (TBI)1. Noradrenaline levels are increased after TBI2-4, and the amplitude of the increase in noradrenaline predicts both the extent of injury5 and the likelihood of mortality6. Glymphatic impairment is both a feature of and a contributor to brain injury7,8, but its relationship with the injury-associated surge in noradrenaline is unclear. Here we report that acute post-traumatic oedema results from a suppression of glymphatic and lymphatic fluid flow that occurs in response to excessive systemic release of noradrenaline. This post-TBI adrenergic storm was associated with reduced contractility of cervical lymphatic vessels, consistent with diminished return of glymphatic and lymphatic fluid to the systemic circulation. Accordingly, pan-adrenergic receptor inhibition normalized central venous pressure and partly restored glymphatic and cervical lymphatic flow in a mouse model of TBI, and these actions led to substantially reduced brain oedema and improved functional outcomes. Furthermore, post-traumatic inhibition of adrenergic signalling boosted lymphatic export of cellular debris from the traumatic lesion, substantially reducing secondary inflammation and accumulation of phosphorylated tau. These observations suggest that targeting the noradrenergic control of central glymphatic flow may offer a therapeutic approach for treating acute TBI.

Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathological conditions such as stroke. However, existing in vivo techniques are limited to sparse velocity measurements in pial perivascular spaces (PVSs) or low-resolution measurements from brain-wide imaging. Additionally, volume flow rate, pressure, and shear stress variation in PVSs are essentially impossible to measure in vivo. Here, we show that artificial intelligence velocimetry (AIV) can integrate sparse velocity measurements with physics-informed neural networks to quantify CSF flow in PVSs. With AIV, we infer three-dimensional (3D), high-resolution velocity, pressure, and shear stress. Validation comes from training with 70% of PTV measurements and demonstrating close agreement with the remaining 30%. A sensitivity analysis on the AIV inputs shows that the uncertainty in AIV inferred quantities due to uncertainties in the PVS boundary locations inherent to in vivo imaging is less than 30%, and the uncertainty from the neural net initialization is less than 1%. In PVSs of N = 4 wild-type mice we find mean flow speed 16.33 ± 11.09 µm/s, volume flow rate 2.22 ± 1.983 × 103 µm3/s, axial pressure gradient ( - 2.75 ± 2.01)×10-4 Pa/µm (-2.07 ± 1.51 mmHg/m), and wall shear stress (3.00 ± 1.45)×10-3 Pa (all mean ± SE). Pressure gradients, flow rates, and resistances agree with prior predictions. AIV infers in vivo PVS flows in remarkable detail, which will improve fluid dynamic models and potentially clarify how CSF flow changes with aging, Alzheimer's disease, and small vessel disease.

Cerebrospinal fluid is a significant fluid source for anoxic cerebral oedema.

Cerebral oedema develops after anoxic brain injury. In two models of asphyxial and asystolic cardiac arrest without resuscitation, we found that oedema develops shortly after anoxia secondary to terminal depolarizations and the abnormal entry of CSF. Oedema severity correlated with the availability of CSF with the age-dependent increase in CSF volume worsening the severity of oedema. Oedema was identified primarily in brain regions bordering CSF compartments in mice and humans. The degree of ex vivo tissue swelling was predicted by an osmotic model suggesting that anoxic brain tissue possesses a high intrinsic osmotic potential. This osmotic process was temperature-dependent, proposing an additional mechanism for the beneficial effect of therapeutic hypothermia. These observations show that CSF is a primary source of oedema fluid in anoxic brain. This novel insight offers a mechanistic basis for the future development of alternative strategies to prevent cerebral oedema formation after cardiac arrest.

A pathway towards a two-dimensional, bore-mounted, volume body coil concept for ultra high-field magnetic resonance imaging.

Lack of a body-sized, bore-mounted, radiofrequency (RF) body coil for ultrahigh field (UHF) magnetic resonance imaging (MRI) is one of the major drawbacks of UHF, hampering the clinical potential of the technology. Transmit field (B1 ) nonuniformity and low specific absorption rate (SAR) efficiencies in UHF MRI are two challenges to be overcome. To address these problems, and ultimately provide a pathway for the full clinical potential of the modality, we have designed and simulated two-dimensional cylindrical high-pass ladder (2D c-HPL) architectures for clinical bore-size dimensions, and demonstrated a simplified proof of concept with a head-sized prototype at 7 T. A new dispersion relation has been derived and electromagnetic simulations were used to verify coil modes. The coefficient of variation (CV) for brain, cerebellum, heart, and prostate tissues after B1 + shimming in silico is reported and compared with previous works. Three prototypes were designed in simulation: a head-sized, body-sized, and long body-sized coil. The head-sized coil showed a CV of 12.3%, a B1 + efficiency of 1.33 µT/√W, and a SAR efficiency of 2.14 µT/√(W/kg) for brain simulations. The body-sized 2D c-HPL coil was compared with same-sized transverse electromagnetic (TEM) and birdcage coils in silico with a four-port circularly polarized mode excitation. Improved B1 + uniformity (26.9%) and SAR efficiency (16% and 50% better than birdcage and TEM coils, respectively) in spherical phantoms was observed. We achieved a CV of 12.3%, 4.9%, 16.7%, and 2.8% for the brain, cerebellum, heart, and prostate, respectively. Preliminary imaging results for the head-sized coil show good agreement between simulation and experiment. Extending the 1D birdcage coil concept to 2D c-HPLs provides improved B1 + uniformity and SAR efficiency.

Perivascular pumping in the mouse brain: Improved boundary conditions reconcile theory, simulation, and experiment.

Cerebrospinal fluid (CSF) flows through the perivascular spaces (PVSs) surrounding cerebral arteries. Revealing the mechanisms driving that flow could bring improved understanding of brain waste transport and insights for disorders including Alzheimer's disease and stroke. In vivo velocity measurements of CSF in surface PVSs in mice have been used to argue that flow is driven primarily by the pulsatile motion of artery walls - perivascular pumping. However, fluid dynamics theory and simulation have predicted that perivascular pumping produces flows differing from in vivo observations starkly, particularly in the phase and relative amplitude of flow oscillation. We show that coupling theoretical and simulated flows to more realistic end boundary conditions, using resistance and compliance values measured in mice instead of using periodic boundaries, results in velocities that match observations more closely in phase and relative amplitude of oscillation, while preserving the existing agreement in mean flow speed. This quantitative agreement among theory, simulation, and in vivo measurement further supports the idea that perivascular pumping is an important CSF driver in physiological conditions.

Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping.

PURPOSE: Typical quantitative susceptibility mapping (QSM) reconstruction steps consist of first estimating the magnetization field from the gradient-echo images, and then reconstructing the susceptibility map from the estimated field. The errors from the field-estimation steps may propagate into the final QSM map, and the noise in the estimated field map may no longer be zero-mean Gaussian noise, thus, causing streaking artifacts in the resulting QSM. A multiecho complex total field inversion (mcTFI) method was developed to compute the susceptibility map directly from the multiecho gradient echo images using an improved signal model that retains the Gaussian noise property in the complex domain. It showed improvements in QSM reconstruction over the conventional field-to-source inversion. METHODS: The proposed mcTFI method was compared with the nonlinear total field inversion (nTFI) method in a numerical brain with hemorrhage and calcification, the numerical brains provided by the QSM Challenge 2.0, 18 brains with intracerebral hemorrhage scanned at 3T, and 6 healthy brains scanned at 7T. RESULTS: Compared with nTFI, the proposed mcTFI showed more accurate QSM reconstruction around the lesions in the numerical simulations. The mcTFI reconstructed QSM also showed the best image quality with the least artifacts in the brains with intracerebral hemorrhage scanned at 3T and healthy brains scanned at 7T. CONCLUSION: The proposed multiecho complex total field inversion improved QSM reconstruction over traditional field-to-source inversion through better signal modeling.

Front tracking velocimetry in advection-reaction-diffusion systems.

In advection-reaction-diffusion systems, the spreading of a reactive scalar can be significantly influenced by the flow field in which it grows. In systems with sharp boundaries between reacted and unreacted regions, motion of the reaction fronts that lie at those boundaries can quantify spreading. Here, we present an algorithm for measuring the velocity of reaction fronts in the presence of flow, expanding previous work on tracking reaction fronts without flow. The algorithm provides localized measurements of front speed and can distinguish its two components: one from chemical dynamics and another from the underlying flow. We validate that the algorithm returns the expected front velocity components in two simulations and then show that in complex experimental flows, the measured front velocity maps fronts from one time step to the next self-consistently. Finally, we observe a variation of the chemical speed with flow speed in a variety of experiments with different time scales and length scales.

Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS).

PURPOSE: To introduce a novel method for the recovery of multi-shot diffusion weighted (MS-DW) images from echo-planar imaging (EPI) acquisitions. METHODS: Current EPI-based MS-DW reconstruction methods rely on the explicit estimation of the motion-induced phase maps to recover artifact-free images. In the new formulation, the k-space data of the artifact-free DWI is recovered using a structured low-rank matrix completion scheme, which does not require explicit estimation of the phase maps. The structured matrix is obtained as the lifting of the multi-shot data. The smooth phase-modulations between shots manifest as null-space vectors of this matrix, which implies that the structured matrix is low-rank. The missing entries of the structured matrix are filled in using a nuclear-norm minimization algorithm subject to the data-consistency. The formulation enables the natural introduction of smoothness regularization, thus enabling implicit motion-compensated recovery of the MS-DW data. RESULTS: Our experiments on in-vivo data show effective removal of artifacts arising from inter-shot motion using the proposed method. The method is shown to achieve better reconstruction than the conventional phase-based methods. CONCLUSION: We demonstrate the utility of the proposed method to effectively recover artifact-free images from Cartesian fully/under-sampled and partial Fourier acquired data without the use of explicit phase estimates. Magn Reson Med 78:494-507, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Front tracking for quantifying advection-reaction-diffusion.

We present an algorithm for measuring the speed and thickness of reaction fronts, and from those quantities, the diffusivity and the reaction rate of the active chemical species. This front-tracking algorithm provides local measurements suitable for statistics and requires only a sequence of concentration fields. Though our eventual goal is front tracking in advection-reaction-diffusion, here we demonstrate the algorithm in reaction-diffusion. We test the algorithm with validation data in which front speed and thickness are prescribed, as well as simulation results in which diffusivity and reaction rate are prescribed. In all tests, measurements closely match true values. We apply the algorithm to laboratory experiments using the Belousov-Zhabotinsky reaction, producing speed, diffusivity, and reaction rate measurements that are statistically more robust than in prior studies. Finally, we use thickness measurements to quantify the concentration profile of chemical waves in the reaction.

Optimal stretching in the reacting wake of a bluff body.

We experimentally study spreading of the Belousov-Zhabotinsky reaction behind a bluff body in a laminar flow. Locations of reacted regions (i.e., regions with high product concentration) correlate with a moderate range of Lagrangian stretching and that range is close to the range of optimal stretching previously observed in topologically different flows [T. D. Nevins and D. H. Kelley, Phys. Rev. Lett. 117, 164502 (2016)]. The previous work found optimal stretching in a closed, vortex dominated flow, but this article uses an open flow and only a small area of appreciable vorticity. We hypothesize that optimal stretching is common in advection-reaction-diffusion systems with an excitation threshold, including excitable and bistable systems, and that the optimal range depends on reaction chemistry and not on flow shape or characteristic speed. Our results may also give insight into plankton blooms behind islands in ocean currents.

Optimal Stretching in Advection-Reaction-Diffusion Systems.

We investigate growth of the excitable Belousov-Zhabotinsky reaction in chaotic, time-varying flows. In slow flows, reacted regions tend to lie near vortex edges, whereas fast flows restrict reacted regions to vortex cores. We show that reacted regions travel toward vortex centers faster as flow speed increases, but nonreactive scalars do not. For either slow or fast flows, reaction is promoted by the same optimal range of the local advective stretching, but stronger stretching causes reaction blowout and can hinder reaction from spreading. We hypothesize that optimal stretching and blowout occur in many advection-diffusion-reaction systems, perhaps creating ecological niches for phytoplankton in the ocean.

Assessment of Silent T1-weighted head imaging at 7 T.

OBJECTIVES: This study aimed to assess the performance of a "Silent" zero time of echo (ZTE) sequence for T1-weighted brain imaging using a 7 T MRI system. METHODS: The Silent sequence was evaluated qualitatively by two neuroradiologists, as well as quantitatively in terms of tissue contrast, homogeneity, signal-to-noise ratio (SNR) and acoustic noise. It was compared to conventional T1-weighted imaging (FSPGR). Adequacy for automated segmentation was evaluated in comparison with FSPGR acquired at 7 T and 1.5 T. Specific absorption rate (SAR) was also measured. RESULTS: Tissue contrast and homogeneity in Silent were remarkable in deep brain structures and in the occipital and temporal lobes. Mean tissue contrast was significantly (p < 0.002) higher in Silent (0.25) than in FSPGR (0.11), which favoured automated tissue segmentation. On the other hand, Silent images had lower SNR with respect to conventional imaging: average SNR of FSPGR was 2.66 times that of Silent. Silent images were affected by artefacts related to projection reconstruction, which nevertheless did not compromise the depiction of brain tissues. Silent acquisition was 35 dB(A) quieter than FSPGR and less than 2.5 dB(A) louder than ambient noise. Six-minute average SAR was <2 W/kg. CONCLUSIONS: The ZTE Silent sequence provides high-contrast T1-weighted imaging with low acoustic noise at 7 T. KEY POINTS: • "Silent" is an MRI technique allowing zero time of echo acquisition • Its feasibility and performance were assessed on a 7 T MRI system • Image quality in several regions was higher than in conventional techniques • Imaging acoustic noise was dramatically reduced compared with conventional imaging • "Silent" is suitable for T1-weighted head imaging at 7 T.

Ultrashort echo time and zero echo time MRI at 7T.

OBJECTIVE: Zero echo time (ZTE) and ultrashort echo time (UTE) pulse sequences for MRI offer unique advantages of being able to detect signal from rapidly decaying short-T2 tissue components. In this paper, we applied 3D ZTE and UTE pulse sequences at 7T to assess differences between these methods. MATERIALS AND METHODS: We matched the ZTE and UTE pulse sequences closely in terms of readout trajectories and image contrast. Our ZTE used the water- and fat-suppressed solid-state proton projection imaging method to fill the center of k-space. Images from healthy volunteers obtained at 7T were compared qualitatively, as well as with SNR and CNR measurements for various ultrashort, short, and long-T2 tissues. RESULTS: We measured nearly identical contrast-to-noise and signal-to-noise ratios (CNR/SNR) in similar scan times between the two approaches for ultrashort, short, and long-T2 components in the brain, knee and ankle. In our protocol, we observed gradient fidelity artifacts in UTE, and our chosen flip angle and readout also resulted in shading artifacts in ZTE due to inadvertent spatial selectivity. These can be corrected by advanced reconstruction methods or with different chosen protocol parameters. CONCLUSION: The applied ZTE and UTE pulse sequences achieved similar contrast and SNR efficiency for volumetric imaging of ultrashort-T2 components. Key differences include that ZTE is limited to volumetric imaging, but has substantially reduced acoustic noise levels during the scan. Meanwhile, UTE has higher acoustic noise levels and greater sensitivity to gradient fidelity, but offers more flexibility in image contrast and volume selection.

Drought and resprouting plants.

Many species have the ability to resprout vegetatively after a substantial loss of biomass induced by environmental stress, including drought. Many of the regions characterised by ecosystems where resprouting is common are projected to experience more frequent and intense drought during the 21st Century. However, in assessments of ecosystem response to drought disturbance there has been scant consideration of the resilience and post-drought recovery of resprouting species. Systematic differences in hydraulic and allocation traits suggest that resprouting species are more resilient to drought-stress than nonresprouting species. Evidence suggests that ecosystems dominated by resprouters recover from disturbance more quickly than ecosystems dominated by nonresprouters. The ability of resprouters to avoid mortality and withstand drought, coupled with their ability to recover rapidly, suggests that the impact of increased drought stress in ecosystems dominated by these species may be small. The strategy of resprouting needs to be modelled explicitly to improve estimates of future climate-change impacts on the carbon cycle, but this will require several important knowledge gaps to be filled before resprouting can be properly implemented.

Short-echo three-dimensional H-1 MR spectroscopic imaging of patients with glioma at 7 Tesla for characterization of differences in metabolite levels.

BACKGROUND: The purpose of this study was to evaluate the feasibility of using a short echo time, three-dimensional H-1 magnetic resonance spectroscopic imaging (MRSI) sequence at 7 Tesla (T) to assess the metabolic signature of lesions for patients with glioma. METHODS: Twenty-nine patients with glioma were studied. MRSI data were obtained using CHESS water suppression, spectrally selective adiabatic inversion-recovery pulses and automatically prescribed outer-volume-suppression for lipid suppression, and spin echo slice selection (echo time = 30 ms). An interleaved flyback echo-planar trajectory was applied to shorten the total acquisition time (∼10 min). Relative metabolite ratios were estimated in tumor and in normal-appearing white and gray matter (NAWM, GM). RESULTS: Levels of glutamine, myo-inositol, glycine, and glutathione relative to total creatine (tCr) were significantly increased in the T2 lesions for all tumor grades compared with those in the NAWM (P < 0.05), while N-acetyl aspartate to tCr were significantly decreased (P < 0.05). In grade 2 gliomas, level of total choline-containing-compounds to tCr was significantly increased (P = 0.0137), while glutamate to tCr was significantly reduced (P = 0.0012). CONCLUSION: The improved sensitivity of MRSI and the increased number of metabolites that can be evaluated using 7T MR scanners is of interest for evaluating patients with glioma. This study has successfully demonstrated the application of a short-echo spin-echo MRSI sequence to detect characteristic differences in regions of tumor versus normal appearing brain.

Tissue Border Enhancement by inversion recovery MRI at 7.0 Tesla.

INTRODUCTION: This contribution presents a magnetic resonance imaging (MRI) acquisition technique named Tissue Border Enhancement (TBE), whose purpose is to produce images with enhanced visualization of borders between two tissues of interest without any post-processing. METHODS: The technique is based on an inversion recovery sequence that employs an appropriate inversion time to produce images where the interface between two tissues of interest is hypo-intense; therefore, tissue borders are clearly represented by dark lines. This effect is achieved by setting imaging parameters such that two neighboring tissues of interest have magnetization with equal magnitude but opposite sign; therefore, the voxels containing a mixture of each tissue (that is, the tissue interface) possess minimal net signal. The technique was implemented on a 7.0 T MRI system. RESULTS: This approach can assist the definition of tissue borders, such as that between cortical gray matter and white matter; therefore, it could facilitate segmentation procedures, which are often challenging on ultra-high-field systems due to inhomogeneous radiofrequency distribution. TBE allows delineating the contours of structural abnormalities, and its capabilities were demonstrated with patients with focal cortical dysplasia, gray matter heterotopia, and polymicrogyria. CONCLUSION: This technique provides a new type of image contrast and has several possible applications in basic neuroscience, neurogenetic research, and clinical practice, as it could improve the detection power of MRI in the characterization of cortical malformations, enhance the contour of small anatomical structures of interest, and facilitate cortical segmentation.

Gaps in the wall of a perivascular space act as valves to produce a directed flow of cerebrospinal fluid: a hoop-stress model.

The flow of cerebrospinal fluid (CSF) along perivascular spaces (PVSs) is an important part of the brain's system for clearing metabolic waste. Astrocyte endfeet bound the PVSs of penetrating arteries, separating them from brain extracellular space. Gaps between astrocyte endfeet might provide a low-resistance pathway for fluid transport across the wall. Recent studies suggest that the astrocyte endfeet function as valves that rectify the CSF flow, producing the net flow observed in pial PVSs by changing the size of the gaps in response to pressure changes. In this study, we quantify this rectification based on three features of the PVSs: the quasi-circular geometry, the deformable endfoot wall, and the pressure oscillation inside. We provide an analytical model, based on the thin-shell hoop-stress approximation, and predict a pumping efficiency of about 0.4, which would contribute significantly to the observed flow. When we add the flow resistance of the extracellular space (ECS) to the model, we find an increased net flow during sleep, due to the known increase in ECS porosity (decreased flow resistance) compared to that in the awake state. We corroborate our analytical model with three-dimensional fluid-solid interaction simulations.

A brain-wide solute transport model of the glymphatic system.

Brain waste is largely cleared via diffusion and advection in cerebrospinal fluid (CSF). CSF flows through a pathway referred to as the glymphatic system, which is also being targeted for delivering drugs to the brain. Despite the importance of solute transport, no brain-wide models for predicting clearance and delivery through perivascular pathways and adjacent parenchyma existed. We devised such a model by upgrading an existing model of CSF flow in the mouse brain to additionally solve advection-diffusion equations, thereby estimating solute transport. We simulated steady-state transport of 3 kDa dextran injected proximal to the perivascular space (PVS) of the middle cerebral artery, mimicking in vivo experiments. We performed a sensitivity analysis of 11 biological properties of PVSs and brain parenchyma by repeatedly simulating solute transport with varying parameter values. Parameter combinations that led to a large total pressure gradient, poor CSF perfusion or a steep solute gradient were deemed unrealistic. Solute concentrations in parenchyma were most sensitive to changes in pial PVS size, as this parameter linearly affects volume flow rates. We also found that realistic transport requires both highly permeable penetrating PVSs and high-resistance parenchyma. This study highlights the potential of brain-wide models to provide insights into solute transport processes.

Hydraulic resistance of three-dimensional pial perivascular spaces in the brain.

BACKGROUND: Perivascular spaces (PVSs) carry cerebrospinal fluid (CSF) around the brain, facilitating healthy waste clearance. Measuring those flows in vivo is difficult, and often impossible, because PVSs are small, so accurate modeling is essential for understanding brain clearance. The most important parameter for modeling flow in a PVS is its hydraulic resistance, defined as the ratio of pressure drop to volume flow rate, which depends on its size and shape. In particular, the local resistance per unit length varies along a PVS and depends on variations in the local cross section. METHODS: Using segmented, three-dimensional images of pial PVSs in mice, we performed fluid dynamical simulations to calculate the resistance per unit length. We applied extended lubrication theory to elucidate the difference between the calculated resistance and the expected resistance assuming a uniform flow. We tested four different approximation methods, and a novel correction factor to determine how to accurately estimate resistance per unit length with low computational cost. To assess the impact of assuming unidirectional flow, we also considered a circular duct whose cross-sectional area varied sinusoidally along its length. RESULTS: We found that modeling a PVS as a series of short ducts with uniform flow, and numerically solving for the flow in each, yields good resistance estimates at low cost. If the second derivative of area with respect to axial location is less than 2, error is typically less than 15%, and can be reduced further with our correction factor. To make estimates with even lower cost, we found that instead of solving for the resistance numerically, the well-known resistance of a circular duct could be scaled by a shape factor. As long as the aspect ratio of the cross section was less than 0.7, the additional error was less than 10%. CONCLUSIONS: Neglecting off-axis velocity components underestimates the average resistance, but the error can be reduced with a simple correction factor. These results could increase the accuracy of future models of brain-wide and local CSF flow, enabling better prediction of clearance, for example, as it varies with age, brain state, and pathological conditions.

Niche-dependent forest and savanna fragmentation in Tropical South America during the Last Glacial Maximum.

The refugia hypothesis, often used to explain Amazonia's high biodiversity, initially received ample support but has garnered increasing criticism over time. Palynological, phylogenetic, and vegetation model reconstruction studies have been invoked to support the opposing arguments of extensive fragmentation versus a stable Amazonian Forest during Pleistocene glacial maxima. Here, we test the past existence of forest fragments and savanna connectivity by bias-correcting vegetation distributions from a Dynamic Vegetation Model (DVM) driven by paleoclimate simulations for South America during the Last Glacial Maximum (LGM). We find evidence for fragmented forests akin to refugia with extensive tropical humid forests to the west and forest islands in central/southern Amazonia. Drier ecosystems of Northern Llanos, Caatinga and Cerrado may have merged into continuous savanna/grasslands that dominated the continent. However, our reconstructions suggest taller, dense woodland/tropical savanna vegetation and areas of similar bioclimate connected disparate forest fragments across Amazonia. This ecotonal biome may have acted as a corridor for generalist forest and savanna species, creating connectivity that allows for range expansion during glacial periods. Simultaneously, it could have served as a barrier for specialists, inducing diversification through the formation of 'semi-refugia'.