Functionnectome as a framework to analyse the contribution of brain circuits to fMRI

In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brain’s functional signatures and dysfunctions. We developed a method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionnectome combines the functional signal from fMRI with white matter circuits’ anatomy to unlock and chart the first maps of functional white matter. To showcase this method’s versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing datasets and beyond task fMRI

Combined in situ experimentation and modelling approaches to disentangle processes involved in the earliest stage of community assembly

The ecological process of community assembly is described as the succession of three phases: colonization, regulation and segregation. Early colonization remains the least studied and quantified phase of assembly. In order to fill this gap, an approach combining in situ experiments and modelling was proposed to study colonization by a benthic macrofauna community in open microcosms containing a single, non-limiting resource. The experiment was three months long. A total of 51 taxa were observed in the microcosms, but data analyses of the species composition and abundances revealed that five species, Capitella spp., Gammaropsis maculata, Erichtionus punctatus, Nereiphylla paretti and Harmothoe mariannae, explained most of the observed variation in the assembly process. The population dynamics of these species were simulated taking into account functional traits that govern individual interactions. The dynamic model simulated a demographic stochasticity due to low population densities that result from the small size of the experimental microcosms. Using this combined approach of experiments and modelling, we showed that predation interactions alone can account for the abundances and species composition of primary consumers during the transient phase of early colonization

Individual and population dietary specialization decline in fin whales during a period of ecosystem shift

Abstract This study sought to estimate the effect of an anthropogenic and climate-driven change in prey availability on the degree of individual and population specialization of a large marine predator, the fin whale (Balaenoptera physalus). We examined skin biopsies from 99 fin whales sampled in the St. Lawrence Estuary (Canada) over a nine year period (1998–2006) during which environmental change was documented. We analyzed stable isotope ratios in skin and fatty acid signatures in blubber samples of whales, as well as in seven potential prey species, and diet was quantitatively assessed using Bayesian isotopic models. An abrupt change in fin whale dietary niche coincided with a decrease in biomass of their predominant prey, Arctic krill (Thysanoessa spp.). This dietary niche widening toward generalist diets occurred in nearly 60% of sampled individuals. The fin whale population, typically composed of specialists of either krill or lipid-rich pelagic fishes, shifted toward one composed either of krill specialists or true generalists feeding on various zooplankton and fish prey. This change likely reduced intraspecific competition. In the context of the current “Atlantification” of northern water masses, our findings emphasize the importance of considering individual-specific foraging tactics and not only population or group average responses when assessing population resilience or when implementing conservation measures

On the Use of Quality Metrics to Characterize Structured Light-based Point Cloud Acquisitions

Even if 3D acquisition systems are nowadays more and more efficient, the resulting point clouds nevertheless contain quality defects that must be taken into account beforehand, in order to better anticipate and control their effects. Assessing the quality of 3D acquisitions has therefore become a major issue for scan planning. This paper presents several quality metrics that are then studied to identify those that could be used to optimize the acquisition positions to perform an automatic scan. From the experiments, it appears that, when considering multiple acquisition positions, the coverage ratio and score indicator have significant changes and can be used to evaluate the quality of the measurements. Differently, other indicators such as efficacy ratio, registration error and metrological characteristics are insensitive to some acquisition position

Photoacclimation and light thresholds for cold temperate seagrasses

Water quality deterioration is expected to worsen the light conditions in shallow coastal waters with increasing human activities. Temperate seagrasses are known to tolerate a highly fluctuating light environment. However, depending on their ability to adjust to some decline in light conditions, decreases in daily light quantity and quality could affect seagrass physiology, productivity, and, eventually, survival if the Minimum Quantum Requirements (MQR) are not reached. To better understand if, how, and to what extent photosynthetic adjustments contribute to light acclimation, eelgrass (Zostera marina L.) shoots from the cold temperate St. Lawrence marine estuary (Rimouski, QC, Canada) were exposed to seven light intensity treatments (6, 36, 74, 133, 355, 503, and 860 μmol photons m–2 s–1, 14:10 light:dark photoperiod). Photosynthetic capacity and efficiency were quantified after five and 25 days of light exposure by Pulse Amplitude Modulated (PAM) fluorometry to assess the rapid response of the photosynthetic apparatus and its acclimation potential. Photoacclimation was also studied through physiological responses of leaves and shoots (gross and net primary production, pigment content, and light absorption). Shoots showed proof of photosynthetic adjustments at irradiances below 200 μmol photons m–2 s–1, which was identified as the threshold between limiting and saturating irradiances. Rapid Light Curves (RLC) and net primary production (NPP) rates revealed sustained maximal photosynthetic rates from the highest light treatments down to 74 μmol photons m–2 s–1, while a compensation point (NPP = 0) of 13.7 μmol photons m–2 s–1 was identified. In addition, an important package effect was observed, since an almost three-fold increase in chlorophyll content in the lowest compared to the highest light treatment did not change the leaves’ light absorption. These results shed new light on photosynthetic and physiological processes, triggering light acclimation in cold temperate eelgrass. Our study documents an MQR value for eelgrass in the St. Lawrence estuary, which is highly pertinent in the context of conservation and restoration of eelgrass meadows

Latent disconnectome prediction of long-term cognitive-behavioural symptoms in stroke

Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need to better predict long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnection-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace of white matter disconnections (disconnectome) to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights that are available as the first comprehensive atlas of disconnectome-deficit relations across 86 scores-a Neuropsychological White Matter Atlas. Our novel predictive framework, the Disconnectome Symptoms Discoverer, achieved better predictivity performances than six other models, including functional disconnection, lesion topology and volume modelling. Out-of-sample prediction derived from this atlas presented a mean absolute error below 20% and allowed personalize neuropsychological predictions. Prediction on an external cohort achieved an R2 = 0.201 for semantic fluency. In addition, training and testing were replicated on two external cohorts achieving an R2 = 0.18 for visuospatial performance. This framework is available as an interactive web application (http://disconnectomestudio.bcblab.com) to provide the foundations for a new and practical approach to modelling cognition in stroke. We hope our atlas and web application will help to reduce the burden of cognitive deficits on patients, their families and wider society while also helping to tailor future personalized treatment programmes and discover new targets for treatments. We expect our framework's range of assessments and predictive power to increase even further through future crowdsourcing

Sea ice increases benthic community heterogeneity in a seagrass landscape

Sea ice plays an important role in subpolar seagrass meadows. It protects meadows against wave action and extreme temperatures. On the other hand, sea ice destroys seagrass leaves and removes plots of sediments and organics debris, leaving long-lasting ice-made tidal pools of various shapes and sizes within the meadow. The present study aimed at investigating the effect of sea ice on benthic community structure and biogeochemical processes in a subpolar seagrass meadow. Vegetated areas (V), artificially-created (aTP), and natural (nTP) tidal pools were sampled from April to October 2018 in a seagrass meadow located at Manicouagan Peninsula (Québec; 49°5′36″N, 68°12′44″W). aTP and nTP showed similar sediment characteristics with coarser sediment and lower particulate organic carbon and total nitrogen content but also lower NOx and higher NH4+ and PO43− porewater concentrations as compared to V. Benthic macrofauna communities showed a strong seasonality with very reduced total density, biomass and species richness during wintertime (from December to April) relatively to summertime (from June to September). Benthic macrofauna communities were also more diversified and abundant in V than in aTP and nTP. Species assemblages in aTP and nTP represented a subset of species assemblages in V with any species found exclusively in tidal pools. However, total biomass was similar among treatments, suggesting that tidal pools sheltered larger individuals than vegetated areas. These results underline the importance of considering the spatial heterogeneity of seagrass meadows when assessing the functioning of these ecosystems. -- Keywords : Biodiversity ; Macrofauna ; Biogeochemistry ; Zostera marina ; Subpolar environment ; Tidal pools

3D Segmentation of Perivascular Spaces on T1-Weighted 3 Tesla MR Images With a Convolutional Autoencoder and a U-Shaped Neural Network

We implemented a deep learning (DL) algorithm for the 3-dimensional segmentation of perivascular spaces (PVSs) in deep white matter (DWM) and basal ganglia (BG). This algorithm is based on an autoencoder and a U-shaped network (U-net), and was trained and tested using T1-weighted magnetic resonance imaging (MRI) data from a large database of 1,832 healthy young adults. An important feature of this approach is the ability to learn from relatively sparse data, which gives the present algorithm a major advantage over other DL algorithms. Here, we trained the algorithm with 40 T1-weighted MRI datasets in which all "visible" PVSs were manually annotated by an experienced operator. After learning, performance was assessed using another set of 10 MRI scans from the same database in which PVSs were also traced by the same operator and were checked by consensus with another experienced operator. The Sorensen-Dice coefficients for PVS voxel detection in DWM (resp. BG) were 0.51 (resp. 0.66), and 0.64 (resp. 0.71) for PVS cluster detection (volume threshold of 0.5 within a range of 0 to 1). Dice values above 0.90 could be reached for detecting PVSs larger than 10 mm(3) and 0.95 for PVSs larger than 15 mm(3). We then applied the trained algorithm to the rest of the database (1,782 individuals). The individual PVS load provided by the algorithm showed a high agreement with a semi-quantitative visual rating done by an independent expert rater, both for DWM and for BG. Finally, we applied the trained algorithm to an age-matched sample from another MRI database acquired using a different scanner. We obtained a very similar distribution of PVS load, demonstrating the interoperability of this algorithm.Stopping cognitive decline and dementia by fighting covert cerebral small vessel diseas

Diagnosis of Human Visceral Pentastomiasis

Visceral pentastomiasis in humans is caused by the larval stages (nymphs) of the arthropod-related tongue worms Linguatula serrata, Armillifer armillatus, A. moniliformis, A. grandis, and Porocephalus crotali. The majority of cases has been reported from Africa, Malaysia, and the Middle East, where visceral pentastomiasis may be an incidental finding in autopsies, and less often from China and Latin America. In Europe and North America, the disease is only rarely encountered in immigrants and long-term travelers, and the parasitic lesions may be confused with malignancies, leading to a delay in the correct diagnosis. Since clinical symptoms are variable and serological tests are not readily available, the diagnosis often relies on histopathological examinations. This laboratory symposium focuses on the diagnosis of this unusual parasitic disease and presents its risk factors and epidemiology