Interpreting predictions of cognition from simulated versus empirical resting state functional connectivity

The relation between structure and function of the brain, and how behavior arises from it, is a central topic of interest in neuroscience. This problem can be formulated in terms of Structural Connectivity (SC) and Functional Connectivity (FC), respectively representing anatomical connections and functional interactions between regions in the brain. Recently, a study by Sarwar and colleagues has demonstrated individualized prediction of FC from SC using machine learning, additionally showing that variation in cognitive performance is explained by simulated FC (sFC) almost as well as by empirical FC (eFC). We investigated how decisions made to predict cognition differ between the models based on eFC and sFC. We predicted cognitive performance with Lasso regression in 100 cross-validation loops from both eFC and sFC separately, using FC between each of the 2278 pairs of regions in the 68-region Desikan-Killiany parcellation as features. We identified relevant predictors of cognition by inspecting permutation importance scores and keeping only features whose importance scores were consistently high across validation loops. 13 eFC features and 21 sFC features survived this procedure. Of these, only one feature overlapped between eFC and sFC. Analyzing overlap between regions corresponding to important features and functional systems known to support cognition revealed no patterns for either eFC or sFC features. In conclusion, we found that while cognition can be predicted from sFC almost as well as from eFC, different features are used in the models, and these features were not found to follow any structure in terms of functional systems. This shows that while machine learning models provide a theoretical upper bound on how accurately function can be predicted from structure, they do not necessarily produce output that can be interpreted in the same way as the data the models were trained on

Working memory performance is associated with functional connectivity between the right dlPFC and DMN in glioma patients

Patients with primary brain tumors frequently suffer from cognitive impairments in multiple domains, leading to serious consequences for socio-professional functioning and quality of life. The functional-anatomical basis of these impairments is still poorly understood.The study of correlated BOLD activity in the brain (i.e. functional connectivity) has greatly contributed to our understanding of how brain activity supports cognitive function. In particular, activity observed during the execution of specific tasks can be related to various distributed functional networks, stressing the importance of interactions between remote brain regions. Among these networks, the Default Mode Network (DMN) and the Fronto-Parietal Network (FPN) have consistently been associated with working memory performance.Recently, using task-fMRI in glioma patients, poor performance in a working memory task was associated with less deactivation of the DMN during this task and to a lack of task-evoked changes in the DMN-FPN structure. In this study, we investigated whether these effects are reflected in the resting-state (RS) functional connectivity of the same patient group, i.e. when no task was performed during fMRI. We additionally zoomed in on the part of the FPN located in the dorsolateral Prefrontal Cortex (dlPFC), since this region is believed to be mainly responsible for DMN deactivation.Resting-state functional MRI data were acquired pre-operatively from 45 brain tumor patients (20 low- and 25 high-grade glioma patients). Results of a pre-operative in-scanner N-back working memory fMRI task were used to assess working memory performance.Patient brains were parcellated into ROIs using both the Gordon and Yeo atlas, which have the FPN and DMN network identities readily available. The dlPFC was defined based on masks retrieved from NeuroSynth.To measure DMN-FPN functional connectivity the average Pearson correlation between the activation time series in the regions belonging to the FPN and the DMN was calculated. Functional connectivity between the DMN and the dlPFC was calculated in a similar way.The average correlation between the resting-state fMRI activity in the right dlPFC and in the DMN was negatively associated with working memory performance for both the Gordon atlas (p \\< 0.003) and Yeo atlas (p \\< 0.007). No association was found for the correlation between activity in the left dlPFC and the DMN, nor for the correlation between the activity in the whole FPN and the DMN.Our findings show that working memory performance of glioma patients is related to interactions between networks that can be measured with resting-state fMRI. Furthermore, the results provide further evidence that not only specific brain regions are important for cognitive performance, but that also the interactions between large-scale networks should be considered

Hyperbolic planforms in relation to visual edges and textures perception

We propose to use bifurcation theory and pattern formation as theoretical probes for various hypotheses about the neural organization of the brain. This allows us to make predictions about the kinds of patterns that should be observed in the activity of real brains through, e.g. optical imaging, and opens the door to the design of experiments to test these hypotheses. We study the specific problem of visual edges and textures perception and suggest that these features may be represented at the population level in the visual cortex as a specific second-order tensor, the structure tensor, perhaps within a hypercolumn. We then extend the classical ring model to this case and show that its natural framework is the non-Euclidean hyperbolic geometry. This brings in the beautiful structure of its group of isometries and certain of its subgroups which have a direct interpretation in terms of the organization of the neural populations that are assumed to encode the structure tensor. By studying the bifurcations of the solutions of the structure tensor equations, the analog of the classical Wilson and Cowan equations, under the assumption of invariance with respect to the action of these subgroups, we predict the appearance of characteristic patterns. These patterns can be described by what we call hyperbolic or H-planforms that are reminiscent of Euclidean planar waves and of the planforms that were used in [1, 2] to account for some visual hallucinations. If these patterns could be observed through brain imaging techniques they would reveal the built-in or acquired invariance of the neural organization to the action of the corresponding subgroups.Comment: 34 pages, 11 figures, 2 table

Performance and long-term stability of the barley hordothionin gene in multiple transgenic apple lines

Introduction of sustainable scab resistance in elite apple cultivars is of high importance for apple cultivation when aiming at reducing the use of chemical crop protectants. Genetic modification (GM) allows the rapid introduction of resistance genes directly into high quality apple cultivars. Resistance genes can be derived from apple itself but genetic modification also opens up the possibility to use other, non-host resistance genes. A prerequisite for application is the long-term performance and stability of the gene annex trait in the field. For this study, we produced and selected a series of transgenic apple lines of two cultivars, i.e. ‘Elstar’ and ‘Gala’ in which the barley hordothionin gene (hth) was introduced. After multiplication, the GM hth-lines, non-GM susceptible and resistant controls and GM non-hth controls were planted in a random block design in a field trial in 40 replicates. Scab resistance was monitored after artificial inoculation (first year) and after natural infection (subsequent years). After the trial period, the level of expression of the hth gene was checked by quantitative RT-PCR. Four of the six GM hth apple lines proved to be significantly less susceptible to apple scab and this trait was found to be stable for the entire 4-year period. Hth expression at the mRNA level was also stable

Employment in the Ecuadorian cut-flower industry and the risk of spontaneous abortion

<p>Abstract</p> <p>Background</p> <p>Research on the potentially adverse effects of occupational pesticide exposure on risk of spontaneous abortion (SAB) is limited, particularly among female agricultural workers residing in developing countries.</p> <p>Methods</p> <p>Reproductive histories were obtained from 217 Ecuadorian mothers participating in a study focusing on occupational pesticide exposure and children's neurobehavioral development. Only women with 2+ pregnancies were included in this study (n = 153). Gravidity, parity and frequency of SAB were compared between women with and without a history of working in the cut-flower industry in the previous 6 years. Logistic regression analysis was conducted to assess the relation between SAB and employment in the flower industry adjusting for maternal age.</p> <p>Results</p> <p>In comparison to women not working in the flower industry, women working in the flower industry were significantly younger (27 versus 32 years) and of lower gravidity (3.3 versus 4.5) and reported more pregnancy losses. A 2.6 (95% CI: 1.03-6.7) fold increase in the odds of pregnancy loss among exposed women was observed after adjusting for age. Odds of reporting an SAB increased with duration of flower employment, increasing to 3.4 (95% CI: 1.3, 8.8) among women working 4 to 6 years in the flower industry compared to women who did not work in the flower industry.</p> <p>Conclusion</p> <p>This exploratory analysis suggests a potential adverse association between employment in the cut-flower industry and SAB. Study limitations include the absence of a temporal relation between exposure and SAB, no quantification of specific pesticides, and residual confounding such as physical stressors (i.e., standing). Considering that approximately half of the Ecuadorian flower laborers are women, our results emphasize the need for an evaluating the reproductive health effects of employment in the flower industry on reproductive health in this population.</p

Expression of a Novel Antimicrobial Peptide Penaeidin4-1 in Creeping Bentgrass (Agrostis stolonifera L.) Enhances Plant Fungal Disease Resistance

BACKGROUND: Turfgrass species are agriculturally and economically important perennial crops. Turfgrass species are highly susceptible to a wide range of fungal pathogens. Dollar spot and brown patch, two important diseases caused by fungal pathogens Sclerotinia homoecarpa and Rhizoctonia solani, respectively, are among the most severe turfgrass diseases. Currently, turf fungal disease control mainly relies on fungicide treatments, which raises many concerns for human health and the environment. Antimicrobial peptides found in various organisms play an important role in innate immune response. METHODOLOGY/PRINCIPAL FINDINGS: The antimicrobial peptide - Penaeidin4-1 (Pen4-1) from the shrimp, Litopenaeus setiferus has been reported to possess in vitro antifungal and antibacterial activities against various economically important fungal and bacterial pathogens. In this study, we have studied the feasibility of using this novel peptide for engineering enhanced disease resistance into creeping bentgrass plants (Agrostis stolonifera L., cv. Penn A-4). Two DNA constructs were prepared containing either the coding sequence of a single peptide, Pen4-1 or the DNA sequence coding for the transit signal peptide of the secreted tobacco AP24 protein translationally fused to the Pen4-1 coding sequence. A maize ubiquitin promoter was used in both constructs to drive gene expression. Transgenic turfgrass plants containing different DNA constructs were generated by Agrobacterium-mediated transformation and analyzed for transgene insertion and expression. In replicated in vitro and in vivo experiments under controlled environments, transgenic plants exhibited significantly enhanced resistance to dollar spot and brown patch, the two major fungal diseases in turfgrass. The targeting of Pen4-1 to endoplasmic reticulum by the transit peptide of AP24 protein did not significantly impact disease resistance in transgenic plants. CONCLUSION/SIGNIFICANCE: Our results demonstrate the effectiveness of Pen4-1 in a perennial species against fungal pathogens and suggest a potential strategy for engineering broad-spectrum fungal disease resistance in crop species