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The selection pressures that drove dramatic encephalisation processes through the mammal lineage remain elusive, as does knowledge of brain structure reorganisation through this process. In particular, considerable structural brain changes are present across the primate lineage, culminating in the complex human brain that allows for unique behaviours such as language and sophisticated tool use. To understand this evolution, a diverse sample set of humans' closest relatives with varying socio-ecologies is needed. However, current brain banks predominantly curate brains from primates that died in zoological gardens. We try to address this gap by establishing a field pipeline mitigating the challenges associated with brain extractions of wild primates in their natural habitat. The success of our approach is demonstrated by our ability to acquire a novel brain sample of deceased primates with highly variable socio-ecological exposure and a particular focus on wild chimpanzees. Methods in acquiring brain tissue from wild settings are comprehensively explained, highlighting the feasibility of conducting brain extraction procedures under strict biosafety measures by trained veterinarians in field sites. Brains are assessed at a fine-structural level via high-resolution MRI and state-of-the-art histology. Analyses confirm that excellent tissue quality of primate brains sourced in the field can be achieved with a comparable tissue quality of brains acquired from zoo-living primates. Our field methods are noninvasive, here defined as not harming living animals, and may be applied to other mammal systems than primates. In sum, the field protocol and methodological pipeline validated here pose a major advance for assessing the influence of socio-ecology on medium to large mammal brains, at both macro- and microstructural levels as well as aiding with the functional annotation of brain regions and neuronal pathways via specific behaviour assessments.

The selection pressures that drove dramatic encephalisation processes through the mammal lineage remain elusive, as does knowledge of brain structure reorganisation through this process. In particular, considerable structural brain changes are present across the primate lineage, culminating in the complex human brain that allows for unique behaviours such as language and sophisticated tool use. To understand this evolution, a diverse sample set of humans' closest relatives with varying socio-ecologies is needed. However, current brain banks predominantly curate brains from primates that died in zoological gardens. We try to address this gap by establishing a field pipeline mitigating the challenges associated with brain extractions of wild primates in their natural habitat.The success of our approach is demonstrated by our ability to acquire a novel brain sample of deceased primates with highly variable socio-ecological exposure and a particular focus on wild chimpanzees. Methods in acquiring brain tissue from wild settings are comprehensively explained, highlighting the feasibility of conducting brain extraction procedures under strict biosafety measures by trained veterinarians in field sites.Brains are assessed at a fine-structural level via high-resolution MRI and state-of-the-art histology. Analyses confirm that excellent tissue quality of primate brains sourced in the field can be achieved with a comparable tissue quality of brains acquired from zoo-living primates.Our field methods are noninvasive, here defined as not harming living animals, and may be applied to other mammal systems than primates. In sum, the field protocol and methodological pipeline validated here pose a major advance for assessing the influence of socio-ecology on medium to large mammal brains, at both macro- and microstructural levels as well as aiding with the functional annotation of brain regions and neuronal pathways via specific behaviour assessments

We introduce a computationally efficient fODF-weighted graph structure where shortest-paths through white matter compute the probability of connection while naturally limiting the angle of propagation between steps. Connectivity matrices obtained from this structure maintain many properties of probabilistic streamline count connectomes while avoiding the sampling bias of tractography.

We present Local Spherical Deconvolution (LSD), a diffusion MRI deconvolution method to reconstruct crossing fiber directions in the brain. In contrast to previous approaches which assumed a single deconvolution kernel for the entire brain, LSD utilizes information theory to identify an optimal kernel in each image voxel. Using a high-resolution post-mortem chimpanzee brain, we show that fibers are reconstructed with LSD with increased precision and a reduced number of false peaks compared to conventional methods. A test-retest analysis supports the stability and accuracy of LSD.

Gradient non-linearity distorts the shape of the gradient waveform used for diffuison encoding. This distortion also compromises Maxwell compensation in asymmetric gradient waveforms. We show that one of two strategies for Maxwell compensation fails under non-linear gradiets (K-nulling) whereas M-nulling is immune to this effect.

Ex-vivo dMRI acquisitions achieve very high resolutions from increased SNR at the cost of prolonged scan times. Due to highly-segmented acquisition strategies, the ex-vivo dMRI signal is often not fully decayed when signal encoding progresses. Using numerical simulations and real-dMRI data from a wild chimpanzee, we show that this circumstance can be effectively employed using an optimized noise informed combination of multi-echo acquisitions from segmented EPI trains. The additional sampling comes at a small price and leads to increased SNR and a general reduction of signal bias.

The human lateral geniculate nucleus (LGN) is the central station for visual processing before information reaches the cerebral cortex. It is characterized by subdivisions with distinct cyto- and myeloarchitecture. Due to its small size, imaging of the LGN and especially its subdivisions is challenging. Here, we show that the LGN and its subdivisions can be identified using in-vivo and ex-vivo high-field quantitative MRI with ultra-high resolution. We present the to-date first atlas of the LGN and its estimated subdivisions. This work will serve as a highly valuable tool both for neuroscientists and clinicians investigating the visual system and its disorders.

We investigate the effect of gradient non-linearities (GNL) on free gradient waveform used for B-tensor diffusion encoding. We show the magnitude of the GNL-bias for strong gradients of 300 mT/m. We derive a closed-form formula of the voxelwise B-tensor under GNL, independent of the choice of gradient waveform used to encode the B-tensor.

Advanced diffusion MRI (dMRI) data with high resolution and strong diffusion contrast typically suffer from low SNR levels. Therefore, denoising algorithms such as MP-PCA became an essential part of current dMRI processing pipelines. To overcome challenges related to violations of MP-PCAs assumption of tissue homogeneity in typical dMRI data, we here introduce an informed-MP-PCA (iMP-PCA) algorithm taking local differences in tissue composition into account. Denoising-performance of iMP-PCA was compared to conventional MP-PCA and evaluated on both magnitude and real-valued dMRI data. iMP-PCA was shown to significantly improve denoising-performance, especially at tissue boundaries and in regions of low SNR.

Gradient non-linearities are a significant source of errors in MRI systems with strong gradients. In the case of diffusion imaging, they induce spatial deviation of the b-vectors. The spherical mean methods in diffusion relies on the acquisition of spherical b-shell. To recover accurate spherical mean values, it is necessary to undistort the diffusion signal. Therefore, we evaluated three correction methods for gradient non-linearities using the Connectom gradient system as a showcase. We show how a simple heuristic can reduce the spherical mean errors by 20 folds.

We provide a novel method to increase SNR of segmented diffusion-weighted EPI acquisitions. Multiple gradient echoes were acquired after each diffusion-preparation and combined in an SNR-optimized way using weightings from quantitative T2* maps. The combination of diffusion-weighted echoes yielded an SNR-gain of 58% compared to single-echo dMRI data with an increase in the segmented readout duration by only 23.1 ms. The multi-echo diffusion MRI acquisition and combination were employed to acquire high-quality ex-vivo diffusion-weighted MRI data from a wild chimpanzee brain.

PurposeDiffusion magnetic resonance imaging (dMRI) data with very high isotropic resolution can be obtained at 7T. However, for extensive brain coverage, a large number of slices is required, resulting in long acquisition times (TAs). Recording multiple slices simultaneously (SMS) promises to reduce the TA.MethodsA combination of zoomed and parallel imaging is used to achieve high isotropic resolution dMRI data with a low level of distortions at 7T. The blipped-CAIPI (controlled aliasing in parallel imaging) approach is used to acquire several slices simultaneously. Due to their high radiofrequency (RF) power deposition and ensuing specific absorption rate (SAR) constraints, the commonly used multiband (MB) RF pulses for SMS imaging are inefficient at 7T and entail long repetition times, counteracting the usefulness of SMS acquisitions. To address this issue, low SAR multislice Power Independent of Number of Slices RF pulses are employed.ResultsIn vivo dMRI results with and without SMS acceleration are presented at different isotropic spatial resolutions at ultra high field strength. The datasets are recorded at a high angular resolution to detect fiber crossings.ConclusionFrom the results and compared with earlier studies at these resolutions, it can be seen that scan time is significantly reduced, while image quality is preserved.

The KARMEN experiment at the ISIS spallation source has enhanced its sensitivity for νμ → νe oscillations in 1996 by the installation of an additional large area veto counter system. Consisting of 136 highly transparent plastic scintillator modules, the new veto is completely embedded inside the experiment's 7000 tonne steel blockhouse. It allows to eliminate the main background component in the search for νμ → νe appearance originating from high energy neutrons induced by deep inelastic scattering of cosmic ray muons in the massive shielding. First measurements after the detector upgrade show a substantial reduction of this background meeting the expected factor of 40. If no oscillation signal is seen after 3 years of measuring (1997–1999) KARMEN will be able to exclude mixing amplitudes of sin22Θ≃1x10-3. The ongoing KARMEN2 measurements will thus allow a decisive and reliable test of the entire parameter space favoured by the positive result of LSND. An even higher oscillation sensitivity can be achieved by experiments at future high intensity short spill proton accelerators such as the planned European Spallation Source ESS.

International audience; Using 15N and 33P, we measured the turnover of organic and inorganic nitrogen (N) and phosphorus (P) substrates, and the partitioning of N and P from these sources into two size fractions of marine osmotrophs during the course of a phytoplankton bloom in a nutrient manipulated mesocosm. The larger size fraction (>0.8 ?m), mainly consisting of the coccolithophorid Emiliania huxleyi, but also including an increasing amount of large particle-associated bacteria as the bloom proceeded, dominated uptake of the inorganic forms NH4+, NO3?, and PO43?. The uptake of N from leucine, and P from ATP and dissolved DNA (dDNA), was initially dominated by the 0.8?0.2 ?m size fraction, but shifted towards dominance by the >0.8 ?m size fraction as the system turned to an increasing degree of N-deficiency. Normalizing uptake to biomass of phytoplankton and heterotrophic bacteria revealed that organisms in the 0.8?0.2 ?m size fraction had higher specific affinity for leucine-N than those in the >0.8 ?m size fraction when N was deficient, whereas the opposite was the case for NH4+. There was no such difference regarding the specific affinity for P substrates. Since heterotrophic bacteria seem to acquire N from organic compounds like leucine more efficiently than phytoplankton, our results suggest different structuring of the microbial food chain in N-limited relative to P-limited environments.

The KARMEN experiment uses the reaction 12C(��_e,e-)12N to measure the energy distribution of ��_e emitted in muon decay at rest. The ��_e analog ��_l of the famous Michel parameter ��has been derived from a maximum-likelihood analysis of events near the kinematic end point, E_max. The result, ��_l = (2.7^{+3.8}_{-3.3}\pm 3.1) * 10^{-2}, is in good agreement with the standard model prediction ��_l= 0. We deduce a 90% confidence upper limit of ��_l, 11 pages including 3 figures, submitted to Phys. Rev. Letters