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Amany, A. Naem, and I. Ghali Neveen. "Optimizing community detection in social networks using antlion and K-median." Bulletin of Electrical Engineering and Informatics 8, no. 4 (2019): 1433–40. https://doi.org/10.11591/eei.v8i4.1196.
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Antlion Optimization (ALO) is one of the latest population based optimization methods that proved its good performance in a variety of applications. The ALO algorithm copies the hunting mechanism of antlions to ants in nature. Community detection in social networks is conclusive to understanding the concepts of the networks. Identifying network communities can be viewed as a problem of clustering a set of nodes into communities. k-median clustering is one of the popular techniques that has been applied in clustering. The problem of clustering network can be formalized as an optimization problem where a qualitatively objective function that captures the intuition of a cluster as a set of nodes with better in ternal connectivity than external connectivity is selected to be optimized. In this paper, a mixture antlion optimization and k-median for solving the community detection problem is proposed and named as K-median Modularity ALO. Experimental results which are applied on real life networks show the ability of the mixture antlion optimization and k-median to detect successfully an optimized community structure based on putting the modularity as an objective function.
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Friedrich, M., J. M. Werner, J. P. Steinbach, et al. "PL01.5.A ASSOCIATION BETWEEN RESTING-STATE-NETWORK FUNCTIONAL CONNECTIVITY AND SURVIVAL IN RECURRENT GLIOMAS DIAGNOSED USING FET PET." Neuro-Oncology 26, Supplement_5 (2024): v1. http://dx.doi.org/10.1093/neuonc/noae144.002.
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Abstract BACKGROUND Functional connectivity between glioma-infiltrated brain tissue and remote cortical regions has been linked to overall survival (OS) in patients with newly diagnosed glioblastoma. Here, we studied the association of functional connectivity between tumor and resting-state networks and OS in patients with recurrent gliomas. PATIENTS AND METHODS The study included 82 patients (age range, 26-81 years; median ECOG performance score, 0) with recurrent gliomas (CNS WHO grade 4 glioblastoma, n=57; CNS WHO grade 3 and 4 astrocytoma, n=12; CNS WHO grade 2 and 3 oligodendroglioma, n=13) who had undergone first-line therapy by current guidelines. In addition to the RANO criteria for anatomical MRI, diagnosis of glioma recurrence was confirmed by amino acid PET using the tracer O-(2-[18F]-fluoroethyl)-L-tyrosine (FET). FET PET and resting-state functional MRI were simultaneously acquired on a 3T hybrid PET/MR scanner. A seed-based dual regression analysis was performed to determine the functional connectivity between metabolically active recurrent tumors and a set of seven canonical resting state networks. RESULTS Average functional connectivity was significantly higher (p=0.028) in oligodendrogliomas (z-score, 6.9±1.9) and astrocytomas (z-score, 5.5±1.3) than in glioblastomas (z-score, 4.9±2.6) and was inversely related to the tumor grade (p=0.031). Univariate Cox regression analysis revealed a significant positive association between OS and tumor connectivity with the visual, somatomotor, and dorsal attention network (all p<0.05). Subsequent stepwise multivariate Cox regression analysis refined this association to the dorsal attention network alone (HR, 0.88; 95% CI, 0.80-0.97; p=0.007). Patients with the highest functional connectivity (z-score >8.3, n=21) had a median OS of 31.4 months, while those with the lowest functional connectivity (z-score <4.3, n=21) had a median OS of 10.6 months. Functional connectivity between tumors and the dorsal attention network showed an independent association with OS (p=0.002) in a multivariate model, including the metabolic tumor volume (p=0.003). CONCLUSION Recurrent gliomas exhibit significant functional connectivity to most of the major known resting-state networks, which was generally higher in astrocytomas and oligodendrogliomas. The data suggest that high functional connectivity between the tumor and the dorsal attention network is an independent prognostic factor for improved OS.
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Kende, Michael, Sonia Livingstone, Scott Minehane, Michael Minges, Simon Molloy, and George Sciadas. "GLOBAL CONNECTIVTY REPORT 2022. CHAPTER 2. THE JOURNEY TO UNIVERSAL AND MEANINGFUL CONNECTIVITY." SYNCHROINFO JOURNAL 8, no. 3 (2022): 29–37. http://dx.doi.org/10.36724/2664-066x-2022-8-3-29-37.
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The Global Connectivity Report 2022 takes stock of the progress in digital connectivity over the past three decades. It provides a detailed assessment of the current state of connectivity and how close the world is to achieving universal and meaningful connectivity, using a unique analytical framework. It goes on to showcase solutions and good practices to accelerate progress. The second part of the report consists of seven thematic deep dives on infrastructure, affordability, financing, the pandemic, regulation, youth, and data. Chapter 2 relies on the framework for universal and meaningful connectivity and the associated targets for 2030, developed by ITU and the Office of the Secretary-General’s Envoy on Technology, to analyse the current state of digital connectivity globally and progress towards reaching the targets by 2030. The framework considers usage by various stakeholders (universal dimension of connectivity) and the five enablers of connectivity (meaningful dimension of connectivity): infrastructure, device, affordability, skills, and safety and security. The assessment reveals that the world is still far from universal and meaningful connectivity. Infrastructure needs to be rolled out or improved to bridge the coverage gap. There are still significant differences between and within countries in network availability and quality. Fixed broadband is a costly investment and is not available or is unaffordable for many. Mobile broadband offers greater flexibility and is less expensive, and most rely on this technology to go online. But in many rural areas of developing countries, only 3G is available, when meaningful connectivity requires 4G. The coverage gap, currently at 5%, is dwarfed by the usage gap: 32% of people who are within range of a mobile broadband network and could therefore connect, remain offline. Data compiled by ITU make it possible to classify the offline population based on who they are and where they live. The main reasons cited by people for not using the Internet are the lack of affordability, of awareness about the Internet, of need, as well as the inability to use the Internet. Globally, connectivity became more expensive in 2021 due to the global economic downturn triggered by the COVID-19 pandemic. After years of steady decline, the share of income spent on telecommunication and Internet services increased in 2021. The global median price of an entry-level broadband plan in the majority of countries amounts to more than 2% of the gross national income per capita, which is the affordability threshold set by the Broadband Commission for Sustainable Development. People should not be forced to use the Internet. However, evidence suggests that introducing people to the Internet usually entices them to stay online. Based on activities people reported, use of the Internet leads to an improved social life, with the use of social networks, making Internet calls and streaming video the most common activities.
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Chen, Rong, Kyunghun Lee, and Edward H. Herskovits. "Computational framework for detection of subtypes of neuropsychiatric disorders based on DTI-derived anatomical connectivity." Neuroradiology Journal 33, no. 5 (2020): 393–99. http://dx.doi.org/10.1177/1971400920950694.
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Many brain disorders – such as Alzheimer’s disease, Parkinson’s disease, schizophrenia and autism – are heterogeneous, that is, they may have several subtypes. Traditionally, clinicians have identified subtypes, such as subtypes of psychosis, using clinical criteria. Neuroimaging has the potential to detect subtypes based on objective biomarker-based criteria; however, there are no studies that evaluate the application of combining unsupervised machine learning and anatomical connectivity analysis to accomplish this goal. We propose a computational framework to detect subtypes based on anatomical connectivity computed from diffusion tensor imaging data, in a data-driven and fully automated way. The proposed method exhibits excellent performance on simulated data. We also applied this approach to a real-world dataset: the Nathan Kline Institute data set. The Nathan Kline Institute study consists of 137 normal adult subjects (mean age 41 years (standard deviation 18), male/female 85/52). We examined the association between detected subtypes and the impulsive behavior scale. We found that a subtype characterized by lower connectivity scores was associated with a higher positive urgency score; positive urgency is a vulnerability marker for drug addiction. The top-ranked connections characterizing subtypes involve several brain regions, including the anterior cingulate gyrus, median cingulate gyrus, thalamus, superior frontal gyrus (medial), middle frontal gyrus (orbital part), inferior frontal gyrus (triangular part), superior frontal gyrus, precuneus and putamen. The proposed framework is extendable, and can be used to detect subtypes from other features, including clinical and genomic biomarkers.
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Besiris, D., A. Makedonas, G. Economou, and S. Fotopoulos. "Combining graph connectivity & dominant set clustering for video summarization." Multimedia Tools and Applications 44, no. 2 (2009): 161–86. http://dx.doi.org/10.1007/s11042-009-0277-9.
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Khaniyev, Taghi, Samir Elhedhli, and Fatih Safa Erenay. "Spatial Separability in Hub Location Problems with an Application to Brain Connectivity Networks." INFORMS Journal on Optimization 2, no. 4 (2020): 320–46. http://dx.doi.org/10.1287/ijoo.2019.0031.
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Motivated by the need to solve large hub location problems efficiently and accurately, we discover an important characteristic of optimal solutions to p-hub median problems that we call spatial separability. It refers to the partitioning of the network into allocation clusters with nonoverlapping convex hulls. We illustrate numerically that the property persists over a wide range of randomly generated instances and propose a data-driven approach based on an insight from the property to tackle very large problem sizes. Computational experiments corroborate the effectiveness of the proposed approach in generating high-quality solutions within reasonable computational times. We then explore a new application area of hub location problems in brain connectivity networks and introduce the largest and the first set of three-dimensional instances in the literature. Computational results demonstrate the capability of hub location models in successfully depicting the hub organization of the human brain, as validated by the medical literature, thus revealing that hub location models can play an important role in investigating the intricate connectivity of the human brain.
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Silfverhuth, Minna J., Jukka Remes, Tuomo Starck, et al. "Directional connectivity of resting state human fMRI data using cascaded ICA-PDC analysis." Acta Radiologica 52, no. 9 (2011): 1037–42. http://dx.doi.org/10.1258/ar.2011.110262.
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Background Directional connectivity measures, such as partial directed coherence (PDC), give us means to explore effective connectivity in the human brain. By utilizing independent component analysis (ICA), the original data-set reduction was performed for further PDC analysis. Purpose To test this cascaded ICA-PDC approach in causality studies of human functional magnetic resonance imaging (fMRI) data. Material and Methods Resting state group data was imaged from 55 subjects using a 1.5 T scanner (TR 1800 ms, 250 volumes). Temporal concatenation group ICA in a probabilistic ICA and further repeatability runs ( n = 200) were overtaken. The reduced data-set included the time series presentation of the following nine ICA components: secondary somatosensory cortex, inferior temporal gyrus, intracalcarine cortex, primary auditory cortex, amygdala, putamen and the frontal medial cortex, posterior cingulate cortex and precuneus, comprising the default mode network components. Re-normalized PDC (rPDC) values were computed to determine directional connectivity at the group level at each frequency. Results The integrative role was suggested for precuneus while the role of major divergence region may be proposed to primary auditory cortex and amygdala. Conclusion This study demonstrates the potential of the cascaded ICA-PDC approach in directional connectivity studies of human fMRI.
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Fang, Jiliang, Danhong Wang, Qing Zhao, et al. "Brain-Gut Axis Modulation of Acupuncture in Functional Dyspepsia: A Preliminary Resting-State fcMRI Study." Evidence-Based Complementary and Alternative Medicine 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/860463.
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Objective. To explore acupuncture effects on brain functional connectivity in patients with functional dyspepsia (FD).Methods. Eight patients in an acupuncture treatment group and ten healthy adults in the control group participated in the study. Acupuncture effectiveness was evaluated based on changes of the gastrointestinal symptoms, gastric motility measurements, and gastrin levels and comparisons with the control group when appropriate. To investigate functional connectivity changes related to FD and potential modulation after acupuncture, a set of regions of interest (ROIs) were selected according to previous fMRI reports of acupuncture.Results. Patients showed significant improvements of FD signs and symptoms after acupuncture treatments. For all of the ROIs, we identified subportions of the networks showing reduced connectivity in patients with FD. Connectivity between the ROIs and corresponding disease targets showed significant improvement after acupuncture treatment (P<0.05) in all ROIs except for right medial temporal lobe-hippocampus and right inferior parietal lobule.Conclusion. Functional connectivity of the brain is changed in patients with FD but approximates that in healthy control after acupuncture treatment. The relief of gastrointestinal signs and symptoms by acupuncture is likely due to the normalization of brain-gut axis associated with FD.
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Karuza, Elisabeth A., Lauren L. Emberson, Matthew E. Roser, Daniel Cole, Richard N. Aslin, and Jozsef Fiser. "Neural Signatures of Spatial Statistical Learning: Characterizing the Extraction of Structure from Complex Visual Scenes." Journal of Cognitive Neuroscience 29, no. 12 (2017): 1963–76. http://dx.doi.org/10.1162/jocn_a_01182.
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Behavioral evidence has shown that humans automatically develop internal representations adapted to the temporal and spatial statistics of the environment. Building on prior fMRI studies that have focused on statistical learning of temporal sequences, we investigated the neural substrates and mechanisms underlying statistical learning from scenes with a structured spatial layout. Our goals were twofold: (1) to determine discrete brain regions in which degree of learning (i.e., behavioral performance) was a significant predictor of neural activity during acquisition of spatial regularities and (2) to examine how connectivity between this set of areas and the rest of the brain changed over the course of learning. Univariate activity analyses indicated a diffuse set of dorsal striatal and occipitoparietal activations correlated with individual differences in participants' ability to acquire the underlying spatial structure of the scenes. In addition, bilateral medial-temporal activation was linked to participants' behavioral performance, suggesting that spatial statistical learning recruits additional resources from the limbic system. Connectivity analyses examined, across the time course of learning, psychophysiological interactions with peak regions defined by the initial univariate analysis. Generally, we find that task-based connectivity with these regions was significantly greater in early relative to later periods of learning. Moreover, in certain cases, decreased task-based connectivity between time points was predicted by overall posttest performance. Results suggest a narrowing mechanism whereby the brain, confronted with a novel structured environment, initially boosts overall functional integration and then reduces interregional coupling over time.
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Wagner, Isabella C., Markus Rütgen, and Claus Lamm. "Pattern similarity and connectivity of hippocampal-neocortical regions support empathy for pain." Social Cognitive and Affective Neuroscience 15, no. 3 (2020): 273–84. http://dx.doi.org/10.1093/scan/nsaa045.
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Abstract Empathy is thought to engage mental simulation, which in turn is known to rely on hippocampal-neocortical processing. Here, we tested how hippocampal-neocortical pattern similarity and connectivity contributed to pain empathy. Using this approach, we analyzed a data set of 102 human participants who underwent functional MRI while painful and non-painful electrical stimulation was delivered to themselves or to a confederate. As hypothesized, results revealed increased pattern similarity between first-hand pain and pain empathy (compared to non-painful control conditions) within the hippocampus, retrosplenial cortex, the temporo-parietal junction and anterior insula. While representations in these regions were unaffected by confederate similarity, pattern similarity in the dorsal medial prefrontal cortex was increased the more dissimilar the other individual was perceived. Hippocampal-neocortical connectivity during first-hand pain and pain empathy engaged largely distinct but neighboring primary motor regions, and empathy-related hippocampal coupling with the fusiform gyrus positively scaled with trait measures of perspective taking. These findings suggest that shared representations and mental simulation might contribute to pain empathy via hippocampal-neocortical pattern similarity and connectivity, partially affected by personality traits and the similarity of the observed individual.
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Kim, Seung Soo, and Kwang Ik Yang. "0643 Machine Learning Model to Predict Depressive Mood Using Graph Theory Analysis of Polysomnography." SLEEP 46, Supplement_1 (2023): A282—A283. http://dx.doi.org/10.1093/sleep/zsad077.0643.
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Abstract Introduction The authors conducted this preliminary study to discover the brain signal features for subjective depressive mood by the method that combines a machine learning approach and a graph theory analysis. Methods The authors retrospectively investigated the records of 13 subjects who had undertaken polysomnography (PSG) and patient health questionnaire-9 (PHQ-9). We divided the data to a training set (10 subjects) and a test set (2 subjects). The predictive modeling was conducted by 3 steps: 1) estimation of the small world coefficient (sigma, omega) of each frequency bands (delta: 0.5-4.0 Hz, theta: 4.0-8.0 Hz, alpha: 8.0-12.0 Hz, sigma: 12.0-16.0 Hz, beta: 16.0-30.0 Hz, gamma: 30.0-100.0 Hz) of electroencephalography (EEG) channel for N1 and N2 sleep, 2) training predictive models, and 3) evaluation of final performance of model by using test set. The authors used mean absolute error (MAE) and mean squared error (MSE) as evaluation metrics. The training was conducted using Python 3.8, and its libraries (MNE-Python, MNE-connectivity, NetworkX, xgboost scikit-learn). Results Median value of PHQ-9 score was 6.0 (interquartile range: 5, 8). Lasso regression model showed good performance (MAE 0.6, MSE 0.4). XGBoost model also showed good performance (MAE 0.8, MSE 1.3). Conclusion Lasso regression model using small world coefficient of EEG in overnight PSG showed good predictive value for PHQ-9. The further research using a sufficient sample is needed. Support (if any)
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Rosa, Marcello G. P., Juliana G. M. Soares, Tristan A. Chaplin, et al. "Cortical Afferents of Area 10 in Cebus Monkeys: Implications for the Evolution of the Frontal Pole." Cerebral Cortex 29, no. 4 (2018): 1473–95. http://dx.doi.org/10.1093/cercor/bhy044.
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Abstract Area 10, located in the frontal pole, is a unique specialization of the primate cortex. We studied the cortical connections of area 10 in the New World Cebus monkey, using injections of retrograde tracers in different parts of this area. We found that injections throughout area 10 labeled neurons in a consistent set of areas in the dorsolateral, ventrolateral, orbital, and medial parts of the frontal cortex, superior temporal association cortex, and posterior cingulate/retrosplenial region. However, sites on the midline surface of area 10 received more substantial projections from the temporal lobe, including clear auditory connections, whereas those in more lateral parts received >90% of their afferents from other frontal areas. This difference in anatomical connectivity reflects functional connectivity findings in the human brain. The pattern of connections in Cebus is very similar to that observed in the Old World macaque monkey, despite >40 million years of evolutionary separation, but lacks some of the connections reported in the more closely related but smaller marmoset monkey. These findings suggest that the clearer segregation observed in the human frontal pole reflects regional differences already present in early simian primates, and that overall brain mass influences the pattern of cortico-cortical connectivity.
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Seoane, Sara, Cristián Modroño, José Luis González-Mora, and Niels Janssen. "Medial temporal lobe contributions to resting-state networks." Brain Structure and Function 227, no. 3 (2022): 995–1012. http://dx.doi.org/10.1007/s00429-021-02442-1.
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AbstractThe medial temporal lobe (MTL) is a set of interconnected brain regions that have been shown to play a central role in behavior as well as in neurological disease. Recent studies using resting-state functional magnetic resonance imaging (rsfMRI) have attempted to understand the MTL in terms of its functional connectivity with the rest of the brain. However, the exact characterization of the whole-brain networks that co-activate with the MTL as well as how the various sub-regions of the MTL are associated with these networks remains poorly understood. Here, we attempted to advance these issues by exploiting the high spatial resolution 7T rsfMRI dataset from the Human Connectome Project with a data-driven analysis approach that relied on independent component analysis (ICA) restricted to the MTL. We found that four different well-known resting-state networks co-activated with a unique configuration of MTL subcomponents. Specifically, we found that different sections of the parahippocampal cortex were involved in the default mode, visual and dorsal attention networks; sections of the hippocampus in the somatomotor and default mode networks; and the lateral entorhinal cortex in the dorsal attention network. We replicated this set of results in a validation sample. These results provide new insight into how the MTL and its subcomponents contribute to known resting-state networks. The participation of the MTL in an expanded range of resting-state networks is in line with recent proposals on MTL function.
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Ueno, Keita, Keiko Yamada, Masaya Ueda, Yasuo Naito, and Ryouhei Ishii. "Current source density and functional connectivity extracted from resting-state electroencephalography as biomarkers for chronic low back pain." PAIN Reports 10, no. 1 (2025): e1233. https://doi.org/10.1097/pr9.0000000000001233.
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Abstract Introduction: Chronic low back pain (CLBP) is a global health issue, and its nonspecific causes make treatment challenging. Understanding the neural mechanisms of CLBP should contribute to developing effective therapies. Objectives: To compare current source density (CSD) and functional connectivity (FC) extracted from resting electroencephalography (EEG) between patients with CLBP and healthy controls and to examine the correlations between EEG indices and symptoms. Methods: Thirty-four patients with CLBP and 34 healthy controls in an open data set were analyzed. Five-minute resting-state closed-eye EEG was acquired using the international 10-20 system. Current source density across frequency bands was calculated using exact low-resolution electromagnetic tomography. Functional connectivity was assessed between 24 cortical regions using lagged linear connectivity. Correlations between pain symptoms and CSD distribution and FC were examined in patients with CLBP. Results: Current source density analysis showed no significant differences between the groups. The CLBP group exhibited significantly reduced FC in the β3 band between the left middle temporal gyrus and the posterior cingulate cortex, and between the ventral medial prefrontal cortex and the left inferior parietal lobule. Prefrontal θ and δ activity positively correlated with pain symptoms. Increased β1 band FC between the right dorsolateral prefrontal cortex and right auditory cortex correlated with greater pain intensity. Conclusions: We found altered neural activity and connectivity in patients with CLBP, particularly in prefrontal and temporal regions. These results suggest potential targets for pain modulation through brain pathways and highlight the value of EEG biomarkers in understanding pain mechanisms and assessing treatment efficacy.
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Park, H., J. Cha, H. Kim, and E. Joo. "0724 Altered Brain Network Organization in Patients With Obstructive Sleep Apnea." Sleep 43, Supplement_1 (2020): A275—A276. http://dx.doi.org/10.1093/sleep/zsaa056.720.
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Abstract Introduction Previous functional MRI (fMRI) studies have reported altered brain networks in patients with obstructive sleep apnea (OSA), but the extent of such abnormal connectivity was inconsistent across studies. Moreover, despite the important role of the cerebellum in respiration and OSA, connections of the cerebellum to the cerebral cortex have been rarely assessed. Here, we investigated functional network changes in cerebral and cerebellar cortices of OSA patients. Methods Resting-state fMRI, polysomnography and neuropsychological (NP) tests data were acquired from 74 treatment naïve OSA patients (age: 45.8±10.7 years, apnea-hypopnea index: 46.4±18.5 /h) and 33 normal controls (39.6±9.3 years). Connectivity matrices were extracted by computing correlation coefficients from various ROIs, and Fisher r-to-z transformations. ROIs consisted of 234 regions matched to 17 functional networks, including 200 parcels of the cortex, and 34 parcels of the cerebellum. Between-group connectivity with age as a covariate was analyzed, and threshold for FDR correction was set at q&lt;0.05. In the functional connections that showed the significant group differences, linear regression was conducted to examine the association between connectivity and composite score of NP tests in OSA patients. Results OSA subjects showed decreased attention, executive function, verbal fluency and verbal memory compared to controls. Resting-state functional connectivity was increased between regions involved in the default mode network (DMN), including left medial prefrontal, ventrolateral prefrontal and lateral temporal cortices. In OSA, the connectivity changes between these DMN areas negatively correlated with attention/executive function and verbal fluency. Multiple cerebellar regions showed reduces in connectivity with cerebral cortical areas including frontal eye field, temporoparietal junction, temporo-occipital gyrus, and parieto-occipital association cortex. Conclusion OSA affects mainly the DMN and cerebello-cerebral pathway. The disruption of function in these two networks are known to relate to sleep deprivation and respiratory abnormality. The abnormal DMN found in OSA patients further related to their cognitive impairment. Support This research was supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning, Republic of Korea (2017R1A2B4003120) and by Samsung Biomedical Research Institute grant (OTC1190671)
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Sun, Jiannan, Ke Yan, Yongsheng Zhu, and Jun Hong. "A High-Similarity Modeling Method for Low-Porosity Porous Material and Its Application in Bearing Cage Self-Lubrication Simulation." Materials 14, no. 18 (2021): 5449. http://dx.doi.org/10.3390/ma14185449.
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The porous oil-containing cage achieves the storage, spillage, and suction of lubricating oil by its micro-pore structure, thus ensuring the self-lubricating performance of the bearing. Carrying out fast and accurate modeling of the cage microscopic pore structure is the key to the analysis of the self-lubricating mechanism of bearings. In response to the issues where current modeling methods of porous materials have a low similarity of pore distribution, morphology, structure, and size characteristics, and the transition of pore surfaces is sharp, this paper proposed a modeling method of a highly similar micro-pore structure based on the idea of median filtering, the quartet structure generation set (QSGS), and the slice method. By extracting and analyzing the pore characteristics of the porous model and comparing them with the experimental results of CT scanning, the advantages of the modeling method in terms of morphology and pore connectivity were verified. Finally, by carrying out simulation analysis of the centrifugal force of oil splashing and capillary oil absorption on the constructed model by combining the parameters of porous structures such as porosity and tortuosity, the advantages of the modeling method in the construction of the porous model and multi-physical field analysis were further verified.
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Kassab, G. S., C. A. Rider, N. J. Tang, and Y. C. Fung. "Morphometry of pig coronary arterial trees." American Journal of Physiology-Heart and Circulatory Physiology 265, no. 1 (1993): H350—H365. http://dx.doi.org/10.1152/ajpheart.1993.265.1.h350.
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To establish a mathematical model of the tree like arteries for the purpose of hemodynamic analysis, a complete set of morphometric data of pig coronary arteries is presented. For the purpose of mathematical modeling, three innovations in morphometry are introduced: 1) a rule for assigning the order numbers of the vessels on the basis of diameter ranges, 2) a connectivity matrix to describe asymmetric branching, and 3) a measurement of the fraction of vessel segments connected in series. The morphometric measurements were made with the silicone elastomer-casting method. Data on smaller vessels were obtained from histological specimens by optical sectioning. Data on larger vessels were obtained from vascular casts. The order number, diameter, length, connectivity matrix, and fractions of the vessels of a given order connected in series were measured for all orders of vessels of the right coronary artery and the left anterior descending and left circumflex branches. The data can be used to analyze the longitudinal distribution of blood pressure and volume and spatial distribution of perfusion in myocardium.
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Rakka, Maria, António Godinho, Covadonga Orejas, and Marina Carreiro-Silva. "Embryo and larval biology of the deep-sea octocoral Dentomuricea aff. meteor under different temperature regimes." PeerJ 9 (August 2, 2021): e11604. http://dx.doi.org/10.7717/peerj.11604.
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Deep-sea octocorals are common habitat-formers in deep-sea ecosystems, however, our knowledge on their early life history stages is extremely limited. The present study focuses on the early life history of the species Dentomuricea aff. meteor, a common deep-sea octocoral in the Azores. The objective was to describe the embryo and larval biology of the target species under two temperature regimes, corresponding to the minimum and maximum temperatures in its natural environment during the spawning season. At temperature of 13 ±0.5 °C, embryos of the species reached the planula stage after 96h and displayed a median survival of 11 days. Planulae displayed swimming only after stimulation, swimming speed was 0.24 ±0.16 mm s−1 and increased slightly but significantly with time. Under a higher temperature (15 °C ±0.5 °C) embryos reached the planula stage 24 h earlier (after 72 h), displayed a median survival of 16 days and had significantly higher swimming speed (0.3 ±0.27 mm s−1). Although the differences in survival were not statistically significant, our results highlight how small changes in temperature can affect embryo and larval characteristics with potential cascading effects in larval dispersal and success. In both temperatures, settlement rates were low and metamorphosis occurred even without settlement. Such information is rarely available for deep-sea corals, although essential to achieve a better understanding of dispersal, connectivity and biogeographical patterns of benthic species.
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Do, Thi Huong Lan, Caroline Lohoff, Ferris Jung, et al. "Cancer Pathway Connectivity Resolved By Drug Perturbation and RNA Sequencing." Blood 144, Supplement 1 (2024): 3584. https://doi.org/10.1182/blood-2024-201366.
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Characterization of cancer subgroups is largely based on omics profiling of patient cohorts and studying inter-patient heterogeneity. However, linking molecular differences to a function has been limited due to their static nature at steady-state. Here, we show that gene expression profiling (GEP) of responses to targeted pathway perturbation in primary chronic lymphocytic leukemia (CLL) samples offers an additional molecular layer for disease classification. We selected 108 CLL patient samples with genetic annotation and exposed them ex-vivo to small-molecule inhibitors used clinically (ibrutinib/BTKi, duvelisib/PI3Ki, trametinib/MEKi, everolimus/mTORi, selinexor/XPO1i) or targeting key signaling pathways (compound 26/TLRi, MK2206/AKTi, nutlin-3a/MDM2i, IBET872/BETi) for 48h. GEP was performed by 3'-end-based QuantSeq with shallow depth RNA sequencing (Do et al., ASH2023 abstract #4633) resulting in 1010 drug response profiles with a median sample coverage of 2.06 million reads. Sample viability was measured by flow cytometry before and after perturbation. First, we performed principal component analysis (PCA) on all samples in which transcriptional variation was predominantly shaped by sample viability (PC1), which explained 12.0% of the variation. This gene signature was associated with activation of hypoxia, p53 pathway and TNFα signaling via NFκB. Additionally, we identified downregulation of MYC targets, OXPHOS and protein secretion, preferentially in drug-perturbed samples. The molecular steady-state features IGHV and methylation status (PC2) and trisomy 12 (PC3) explained 8.1% and 5.1% of the variation, respectively. Next, we performed differential gene expression analysis (DGEA) between samples either treated with drug or control. We found most differentially expressed genes (DEGs) after inhibition of the B cell receptor (BCR) pathway by PI3Ki (1574) and BTKi (991), followed by AKTi (469), mTORi (596) and MEKi (455), and p53 pathway activation by MDM2i (253). No DEGs were found for TLRi. Perturbation of broader processes such as nuclear exportation (XPO1i) and chromatin modification (BETi) resulted in 450 and 277 DEGs, respectively (FDR &lt; 0.5%). We modeled the relationship between drugs and perturbed genes with directed acyclic graphs to construct networks and dissect the connection of pathways. Within the main cluster which contained the kinase inhibitors and shared mostly suppressed genes, BTKi and PI3Ki were closely connected by genes enriching in BCR signaling, and immune cell activation and response processes, followed by more downstream targets of mTORi, AKTi and MEKi. The remaining drugs were only weakly connected to the main cluster and presented with distinct sets of induced genes, e. g. p53 targets after MDM2i. Direct comparison of the BCR inhibitors identified 270 DEGs (FDR &lt; 10%) which revealed suppression of IFN response after PI3Ki but not BTKi. We assembled the pathway connectivity of CLL by integrating individual perturbed gene expression signals across the large patient cohort. As IGHV is a key molecular and prognostic disease dimension and the strongest modulator of gene expression in CLL, we assessed how this signature was modulated by each drug. We found 790 DEGs between unmutated and mutated cases among the control samples and decreased numbers after pathway inhibition, namely PI3Ki (664), BTKi (623) and XPO1 (532) (FDR &lt; 5%) suggesting a dynamic component whose maintenance depends on active BCR signaling. We also identified a stable component that was not modified by any perturbation including ZAP70 and CD38. We compared the capacity to map pathway functions to disease drivers using profiles with and without perturbation. Gene set enrichment analysis of DEGs between cases with del17p and wildtype (WT) at steady-state yielded results driven by gene dosage effects. When we tested for interactions between del17p status and drug response, and used these results for further downstream analysis, del17p cases under MDM2i pressure showed impaired activation of the p53 and TNFα pathways compared to WT. In conclusion, the addition of targeted pathway perturbations to the GEP of primary CLL samples can greatly enhance the potential for molecular and functional classification of disease and subgroups. Our study provides a blueprint to use perturbed omics profiling and interaction testing to link disease drivers to pathway activation and function.
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Passiatore, R., L. Antonucci, T. Deramus, et al. "Age-related network connectivity pattern changes are associated with risk for psychosis." European Psychiatry 65, S1 (2022): S316. http://dx.doi.org/10.1192/j.eurpsy.2022.805.
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Introduction Psychosis onset typically occurs during adolescence or early adulthood, coinciding with the latest stage of brain maturation. Alterations in brain functional connectivity (FC) accompany the emergence of psychiatric symptoms and cognitive impairments. Thus, age-related FC changes may be informative regarding psychosis onset. Objectives We defined neurotypical age-related FC trajectories and hypothesized that FC of individuals at familial and clinical high risk (HR) for psychosis deviates from FC of neurotypical controls (NC). Methods We analyzed two independent cohorts, of (a) 356 early adult NC (yNC; age=22±2y, m:f=149:207), and 127 mature adult NC (aNC; age=38±7y, m:f=79:48), and (b) 92 yNC (age=22±2y, m:f=34:58), 33 aNC (age=36±6y, m:f=21:12), 38 early HR adults (age=20±3y, m:f=18:20). We acquired fMRI data from multiple scans (resting-state, working memory, episodic memory, and implicit emotion processing). FC was obtained by computing Pearson’s correlations between time-courses of every independent component (IC) defined by an Independent Component Analysis approach (NeuroMark). Age-varying components of interest (yNC/aNC differences on FC based on linear mixed effect regressions) were tested for differences between HR and yNC through the Wilcoxon rank-sum test. Results showed age-related FC differences (yNC/aNC) in a set of 17 IC pairs (pFDR<0.05). HR showed increased FC within a network including dorsolateral and medial prefrontal cortices, and sensorimotor cortex, while decreased FC between cerebellum and the parietal and visual cortices, compared with yNC (pFDR<0.05). HR showed no significant difference compared with aNC (pFDR>0.05). Conclusions This study tested FC alterations associated with the risk for psychosis and highlighted the relationship between psychosis and potentially altered brain functional processes. Disclosure No significant relationships.
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Nyqvist, D., J. Elghagen, M. Heiss, and O. Calles. "An angled rack with a bypass and a nature-like fishway pass Atlantic salmon smolts downstream at a hydropower dam." Marine and Freshwater Research 69, no. 12 (2018): 1894. http://dx.doi.org/10.1071/mf18065.
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Hydropower dams disrupt longitudinal connectivity and cause fragmentation of river systems, which has led to declines in migratory fish species. Atlantic salmon smolts rely on intact longitudinal connectivity to move downstream from rearing habitats in freshwater to feeding grounds at sea. Smolts often suffer increased mortality and delays when they encounter hydropower plants during their downstream migration. Currently, there are few examples of downstream passage solutions that allow safe and timely passage. We assessed the performance of two passage solutions at a hydropower dam, namely, an angled 15-mm rack with a bypass and a large nature-like fishway. The performance of these new fish passage solutions was evaluated by tracking radio-tagged Atlantic salmon smolts as they encountered the facilities. The radio-tagged smolts passed the dam 9.5h after release (median) and exhibited a dam-passage efficiency of 84%, with passage rates increasing with body length. Fish passage occurred through both the rack bypass and the nature-like fishway. The passage efficiencies were 70–95% for the rack bypass and 47% for the nature-like fisway. The new fish passage facilities resulted in improved passage conditions at the site, confirming that angled racks with bypasses as best-practise solutions for downstream passage, but also that large nature-like fishways may act as downstream passage routes for salmon.
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Bhattacharyya, Rupam, Min Jin Ha, Qingzhi Liu, Rehan Akbani, Han Liang, and Veerabhadran Baladandayuthapani. "Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome." JCO Clinical Cancer Informatics, no. 4 (September 2020): 399–411. http://dx.doi.org/10.1200/cci.19.00140.
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PURPOSE Personalized network inference on diverse clinical and in vitro model systems across cancer types can be used to delineate specific regulatory mechanisms, uncover drug targets and pathways, and develop individualized predictive models in cancer. METHODS We developed TransPRECISE (personalized cancer-specific integrated network estimation model), a multiscale Bayesian network modeling framework, to analyze the pan-cancer patient and cell line interactome to identify differential and conserved intrapathway activities, to globally assess cell lines as representative models for patients, and to develop drug sensitivity prediction models. We assessed pan-cancer pathway activities for a large cohort of patient samples (> 7,700) from the Cancer Proteome Atlas across ≥ 30 tumor types, a set of 640 cancer cell lines from the MD Anderson Cell Lines Project spanning 16 lineages, and ≥ 250 cell lines’ response to > 400 drugs. RESULTS TransPRECISE captured differential and conserved proteomic network topologies and pathway circuitry between multiple patient and cell line lineages: ovarian and kidney cancers shared high levels of connectivity in the hormone receptor and receptor tyrosine kinase pathways, respectively, between the two model systems. Our tumor stratification approach found distinct clinical subtypes of the patients represented by different sets of cell lines: patients with head and neck tumors were classified into two different subtypes that are represented by head and neck and esophagus cell lines and had different prognostic patterns (456 v 654 days of median overall survival; P = .02). High predictive accuracy was observed for drug sensitivities in cell lines across multiple drugs (median area under the receiver operating characteristic curve > 0.8) using Bayesian additive regression tree models with TransPRECISE pathway scores. CONCLUSION Our study provides a generalizable analytic framework to assess the translational potential of preclinical model systems and to guide pathway-based personalized medical decision making, integrating genomic and molecular data across model systems.
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Styrmisdottir, Edda Lind, Patrick Scanlon, Douglas Hanniford, et al. "Melanoma recurrence risk stratification using Bayesian systems biology modeling." Journal of Clinical Oncology 31, no. 15_suppl (2013): 9089. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.9089.
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9089 Background: Estimating the risk of recurrence in patients with melanoma is extremely challenging. Standard of care is AJCC staging system, but the accuracy and robustness of this method is still under development. We conducted a proof of concept study exploring the use of machine-learned Bayesian Belief Networks (ml-BBNs) using a miRNA profiled cohort of melanoma patients with extended follow up to create Bayesian Biological Systems Models (BBSMs). We sought to determine if ml-BBNs could describe the biological system and if we could use the model to identify new cases with higher risk of recurrence. Methods: Our study cohort consisted of 89 patients (42 of which recurred) with a median follow up time of 118 months, that were examined for 869 miRNAs. Prior to modeling we segmented the data into training data (72 cases/80%) and testing data (17 cases/20%) at random. We recursively trained ml-BBNs on the training set, using all miRNAs. We used the directed graph structure of the ml-BBNs to identify miRNAs that consistently had more connectivity and goodness of fit as determined by Bayesian Information Criteria (BIC) scoring. MiRNAs that were in the top 50 BIC-scoring nodes across all models were selected for use to train the recurrence BBSMs. To compensate for a small number, bootstrapping was used to increase the sample to 100 records. We then compared our test set cases to our recurrence model, and used a similarity scoring algorithm to evaluate the similarity of values in each test instance to our biological models. For comparison we also trained an ml-BBN using clinical data from the same cohort. We then evaluated the scores against known recurrence outcome using Receiver Operating Characteristic (ROC) curve analysis. Results: BIC-scoring analysis selected 35 miRNAs for use in BBSM modeling. Area Under the Curve (AUC) for detection of recurrence is 0.76 in the training set and 0.62 in the testing set, while the clinical data yielded an AUC of 0.5 in this cohort. Conclusions: Our data suggest that ml-BBNs can be used to describe a biological model of melanoma recurrence. Additional data and refinement need to be made using independent datasets to be of a level that is clinically useful.
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Trevisani, Sebastiano, and Marco Cavalli. "Topography-based flow-directional roughness: potential and challenges." Earth Surface Dynamics 4, no. 2 (2016): 343–58. http://dx.doi.org/10.5194/esurf-4-343-2016.
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Abstract. Surface texture analysis applied to high-resolution digital terrain models (HRDTMs) is a promising approach for extracting useful fine-scale morphological information. Surface roughness, considered here as a synonym of surface texture, can have a discriminant role in the detection of different geomorphic processes and factors. Very often, the local morphology presents, at different scales, anisotropic characteristics that could be taken into account when calculating or measuring surface roughness. The high morphological detail of HRDTMs permits the description of different aspects of surface roughness, beyond an evaluation limited to isotropic measures of surface roughness. The generalization of the concept of roughness implies the need to refer to a family of specific roughness indices capable of capturing specific multiscale and anisotropic aspects of surface morphology. An interesting set of roughness indices is represented by directional measures of roughness that can be meaningful in the context of analyzed and modeled flow processes. Accordingly, we test the application of a flow-oriented directional measure of roughness based on the geostatistical bivariate index MAD (median of absolute directional differences), which is computed considering surface gravity-driven flow direction. MAD is derived from a modification of a variogram and is specifically designed for the geomorphometric analysis of HRDTMs. The presented approach shows the potential impact of considering directionality in the calculation of roughness indices. The results demonstrate that the use of flow-directional roughness can improve geomorphometric modeling (e.g., sediment connectivity and surface texture modeling) and the interpretation of landscape morphology.
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Rousseau, Pierre-François, Sarah Boukezzi, René Garcia, Thierry Chaminade, and Stéphanie Khalfa. "Cracking the EMDR code: Recruitment of sensory, memory and emotional networks during bilateral alternating auditory stimulation." Australian & New Zealand Journal of Psychiatry 54, no. 8 (2020): 818–31. http://dx.doi.org/10.1177/0004867420913623.
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Introduction: The inability to extinguish a conditioned fear is thought to be at the core of post-traumatic stress disorder. Eye movement desensitization and reprocessing therapy has been efficacious for post-traumatic stress disorder, but the brain mechanisms underlying the effect are still unknown. The core effect of eye movement desensitization and reprocessing therapy seems to rely on the simultaneous association of bilateral alternating stimulation and the recall of the traumatic memory. To shed light on how eye movement desensitization and reprocessing therapy functions, we aimed to highlight the structures activated by bilateral alternating stimulation during fear extinction and its recall. Methods: We included 38 healthy participants in this study. Participants were examined twice in functional magnetic resonance imaging, over 2 consecutive days. On the first day, they performed two fear conditioning and extinction procedures, one with and one without the bilateral alternating stimulation during the fear extinction learning phase in a counter-balanced order across the participants. On the second day, participants completed the fear extinction recall procedure, in the same order as the previous day. Statistical significance of maps was set at p < 0.05 after correction for family-wise error at the cluster level. Results: The analysis revealed significant activation with versus without bilateral alternating stimulation at the early extinction in the bilateral auditory areas, the right precuneus, and the left medial frontal gyrus. The same pattern was found in the early recall on the second day. The connectivity analysis found a significant increase in connectivity during bilateral alternating stimulation versus without bilateral alternating stimulation in the early extinction and recall between the two superior temporal gyri, the precuneus, the middle frontal gyrus and a set of structures involved in multisensory integration, executive control, emotional processing, salience and memory. Conclusion: We show for the first time that in the eye movement desensitization and reprocessing therapy the bilateral alternating stimulation is not a simple sensory signal and can activate large emotional neural networks.
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Tei, Shisei, Jukka-Pekka Kauppi, Kathryn F. Jankowski, et al. "Brain and behavioral alterations in subjects with social anxiety dominated by empathic embarrassment." Proceedings of the National Academy of Sciences 117, no. 8 (2020): 4385–91. http://dx.doi.org/10.1073/pnas.1918081117.
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Social-anxiety disorder involves a fear of embarrassing oneself in the presence of others. Taijin-kyofusho (TKS), a subtype common in East Asia, additionally includes a fear of embarrassing others. TKS individuals are hypersensitive to others’ feelings and worry that their physical or behavioral defects humiliate others. To explore the underlying neurocognitive mechanisms, we compared TKS ratings with questionnaire-based empathic disposition, cognitive flexibility (set-shifting), and empathy-associated brain activity in 23 Japanese adults. During 3-tesla functional MRI, subjects watched video clips of badly singing people who expressed either authentic embarrassment (EMBAR) or hubristic pride (PRIDE). We expected the EMBAR singers to embarrass the viewers via emotion-sharing involving affective empathy (affEMP), and the PRIDE singers to embarrass via perspective-taking involving cognitive empathy (cogEMP). During affEMP (EMBAR > PRIDE), TKS scores correlated positively with dispositional affEMP (personal-distress dimension) and with amygdala activity. During cogEMP (EMBAR < PRIDE), TKS scores correlated negatively with cognitive flexibility and with activity of the posterior superior temporal sulcus/temporoparietal junction (pSTS/TPJ). Intersubject correlation analysis implied stronger involvement of the anterior insula, inferior frontal gyrus, and premotor cortex during affEMP than cogEMP and stronger involvement of the medial prefrontal cortex, posterior cingulate cortex, and pSTS/TPJ during cogEMP than affEMP. During cogEMP, the whole-brain functional connectivity was weaker the higher the TKS scores. The observed imbalance between affEMP and cogEMP, and the disruption of functional brain connectivity, likely deteriorate cognitive processing during embarrassing situations in persons who suffer from other-oriented social anxiety dominated by empathic embarrassment.
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Kim, Young Goo, Song E. Kim, Jihye Lee, Sungeun Hwang, Seung-Schik Yoo, and Hyang Woon Lee. "Neuromodulation Using Transcranial Focused Ultrasound on the Bilateral Medial Prefrontal Cortex." Journal of Clinical Medicine 11, no. 13 (2022): 3809. http://dx.doi.org/10.3390/jcm11133809.
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: Transcranial focused ultrasound (tFUS) is a promising technique of non-invasive brain stimulation for modulating neuronal activity with high spatial specificity. The medial prefrontal cortex (mPFC) has been proposed as a potential target for neuromodulation to prove emotional and sleep qualities. We aim to set up an appropriate clinical protocol for investigating the effects of tFUS stimulation of the bilateral mPFC for modulating the function of the brain-wide network using different sonication parameters. Seven participants received 20 min of 250 kHz tFUS to the bilateral mPFC with excitatory (70% duty cycle with sonication interval at 5 s) or suppressive (5% duty cycle with no interval) sonication protocols, which were compared to a sham condition. By placing the cigar-shaped sonication focus on the falx between both mPFCs, it was possible to simultaneously stimulate the bilateral mPFCs. Brain activity was analyzed using continuous electroencephalographic (EEG) recording during, before, and after tFUS. We investigated whether tFUS stimulation under the different conditions could lead to distinctive changes in brain activity in local brain regions where tFUS was directly delivered, and also in adjacent or remote brain areas that were not directly stimulated. This kind of study setting suggests that dynamic changes in brain cortical responses can occur within short periods of time, and that the distribution of these responses may differ depending on local brain states and functional brain architecture at the time of tFUS administration, or perhaps, at least temporarily, beyond the stimulation time. If so, tFUS could be useful for temporarily modifying regional brain activity, modulating functional connectivity, or reorganizing brain functions associated with various neuropsychiatric diseases, such as insomnia and depression.
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Trevisani, S., and M. Cavalli. "Topography-based flow-directional roughness: potential and challenges." Earth Surface Dynamics Discussions 3, no. 4 (2015): 1399–444. http://dx.doi.org/10.5194/esurfd-3-1399-2015.
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Abstract. Surface texture analysis applied to High Resolution Digital Terrain Models (HRDTMs) is a promising approach for extracting useful fine-scale morphological information. Surface roughness, considered here as a synonym of surface texture, can have a discriminant role in the detection of different geomorphic processes and factors. Very often, the local morphology presents, at different scales, anisotropic characteristics that could be taken into account when calculating or measuring surface roughness. The high morphological detail of HRDTMs permits the description of different aspects of surface roughness, beyond an evaluation limited to isotropic measures of surface roughness. The generalization of the concept of roughness implies the need to refer to a family of specific roughness indices capable of capturing specific multi-scale and anisotropic aspects of surface morphology. An interesting set of roughness indices is represented by directional measures of roughness that can be meaningful in the context of analyzed and modeled flow processes. Accordingly, we test the application of a flow-oriented directional measure of roughness based on the geostatistical bivariate index MAD (median of absolute directional differences), which is computed considering surface gravity-driven flow direction. MAD is derived from a modification of a variogram and is specifically designed for the geomorphometric analysis of HRDTMs. The presented approach shows the potential impact of considering directionality in the calculation of roughness indices. The results demonstrate that the use of flow directional roughness can improve geomorphometric modeling (e.g., sediment connectivity and surface texture modeling) and the interpretation of landscape morphology.
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Ge, Shengyang, Qingfeng Hu, Yijun Guo, Ke Xu, Guowei Xia, and Chuanyu Sun. "Potential Alterations of Functional Connectivity Analysis in the Patients with Chronic Prostatitis/Chronic Pelvic Pain Syndrome." Neural Plasticity 2021 (May 7, 2021): 1–9. http://dx.doi.org/10.1155/2021/6690414.
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Background. Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is one of the most common diseases in urology, but its pathogenesis remains unclear. As a kind of chronic pain which the patients suffered for more than 3 months, we investigated the influence on patients’ brain functional connectivity in resting state. Methods. We recruited a cohort of 18 right-handed male patients with CP/CPPS and 21 healthy male right-handed age-matched controls. Their resting-state fMRI data and structural MRI data were preprocessed and processed by RESTPlus V1.22. To assess the integrity of the default mode network (DMN), we utilized the voxel-wised analysis that we set medial prefrontal cortex (mPFC) and posterior cingulate gyrus (PCC) as seed points to compare the global functional connectivity (FC) strength. Results. Compared with healthy control, the FC strength between left mPFC and posterior DMN decreased in the group of CP/CPPS ( P < 0.05 , GFR correction, voxel P < 0.01 , cluster P < 0.05 ), and the FC strength between the left anterior cerebellar lobe and posterior DMN increased ( P < 0.05 , GFR correction, voxel P < 0.01 , cluster P < 0.05 ). In the patient group, there was a positive correlation between the increased FC strength and the score of the Hospital Anxiety and Depression Scale (HADS) anxiety subscale ( r = 0.5509 , P = 0.0178 ) in the left anterior cerebellar lobe, a negative correlation between the decreased FC strength and the score of the National Institutes of Health Chronic Prostatitis Symptom Index ( r = − 0.6281 , P = 0.0053 ) in the area of left mPFC, and a negative correlation between the decreased FC strength and the score of HADS anxiety subscale ( r = − 0.5252 , P = 0.0252 ). Conclusion. Patients with CP/CPPS had alterations in brain function, which consisted of the default mode network’s compromised integrity. These alterations might play a crucial role in the pathogenesis and development of CP/CPPS.
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Usenko, V., O. Kodak, V. Nikolaenko, and I. Usenko. "OPTIMIZATION OF PARALLEL LINKS IN REDUNDANT UTILITY STRUCTURES." Municipal economy of cities 1, no. 168 (2022): 58–63. http://dx.doi.org/10.33042/2522-1809-2022-1-168-58-63.
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The publication states that an important problem in the design, operation and reconstruction of various networks of engineering infrastructure is to determine the reliability of structurally complex systems. Modeling the reliability of technical systems seems to be a rather complex task. It is emphasized that the ways of rational redundancy of a complex structure of systems presuppose the well-known method of minimal paths and connections. The problem of the optimal arrangement of a system with a redundant structure has certain limitations in accordance with the available resources, such as the lower value of the probability of the system's connectivity, which serves as an optimization criterion. The paper investigates a system with identical components. The article discusses many possible forms of the structure of the system. Structural reliability expressions are calculated for all combinations used in determining the lower and upper values of structural reliability. In the process of constructing a redundant structure, it is necessary to determine a variant of its form, which maximizes the value of reliability under the established restrictions on the available resources invested in the construction and operation of the system using the cost parameter for some form of its structure. The peculiarity of the system reliability function is considered when it increases, which has a discrete argument and consists of a number of some functions. In the presented geometric model, a number of operations are used to determine and concretize the requirements for the variants of the forms of the components of the system under study for their different properties, and the forms that do not meet these conditions for the variants of the component in terms of resources are removed. Here the requirements for the probability of connectivity are defined, according to which unsuccessful forms of possible structures of the system are removed. The work uses an algorithm to extract from a set of reasonable options for some options for components by resources. The specified variant of the structure form is assumed to be optimal according to the criteria. If the number of variants of the structure shape is large enough, then to find the optimal solution, another algorithm is used, in which the value of the objective function is checked, which determines the conditions for the probability of connectivity in design decisions. It is noted that in practical application the obtained solutions can be approximate.
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Spreng, R. Nathan, and Cheryl L. Grady. "Patterns of Brain Activity Supporting Autobiographical Memory, Prospection, and Theory of Mind, and Their Relationship to the Default Mode Network." Journal of Cognitive Neuroscience 22, no. 6 (2010): 1112–23. http://dx.doi.org/10.1162/jocn.2009.21282.
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The ability to rise above the present environment and reflect upon the past, the future, and the minds of others is a fundamentally defining human feature. It has been proposed that these three self-referential processes involve a highly interconnected core set of brain structures known as the default mode network (DMN). The DMN appears to be active when individuals are engaged in stimulus-independent thought. This network is a likely candidate for supporting multiple processes, but this idea has not been tested directly. We used fMRI to examine brain activity during autobiographical remembering, prospection, and theory-of-mind reasoning. Using multivariate analyses, we found a common pattern of neural activation underlying all three processes in the DMN. In addition, autobiographical remembering and prospection engaged midline DMN structures to a greater degree and theory-of-mind reasoning engaged lateral DMN areas. A functional connectivity analysis revealed that activity of a critical node in the DMN, medial prefrontal cortex, was correlated with activity in other regions in the DMN during all three tasks. We conclude that the DMN supports common aspects of these cognitive behaviors involved in simulating an internalized experience.
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Trevisan, Nicolò, Giulia Cattarinussi, Daniele Olivo, et al. "Neural Correlates of Antisocial Behavior: The Victim’s Perspective." Brain Sciences 13, no. 3 (2023): 474. http://dx.doi.org/10.3390/brainsci13030474.
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Antisocial behavior involves actions that disregard the basic rights of others and may represent a threat to the social system. The neural processes associated with being subject to antisocial behavior, including social victimization, are still unknown. In this study, we used a social interaction task during functional magnetic resonance imaging to investigate the neural bases of social victimization. Brain activation and functional connectivity (FC) were estimated and correlated with the Big 5 Questionnaire, Temperament Evaluation in Memphis, Pisa and San Diego (TEMPS-M), and a Questionnaire of Daily Frustration scores. During social victimization, the right occipital and temporal cortex showed increased activation. The temporal cortex also had reduced FC with homotopic areas. Compared to the prosocial interaction, social victimization showed hyperactivation of the dorsomedial and lateral prefrontal cortex, putamen, and thalamus and increased FC of the medial-frontal–striatal–thalamic areas with the ventrolateral prefrontal cortex, insula, dorsal cingulate, and postcentral gyrus. Lastly, neuroticism, irritable temperament, and frustration scores were correlated with the magnitude of neural responses to social victimization. Our findings suggest that social victimization engages a set of regions associated with salience, emotional processing, and regulation, and these responses can be modulated by temperamental and personality traits.
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OKOGBENIN, Clement Omongbale PharmD, Ehiokioya Emmanuel POGOSON, Esther O. OKOGBENIN, and Tijani Idris Ahmad MBBS PhD OSENI. "Determination of Patient Waiting Time and Associated Factors at General Out-Patient Department (GOPD) of Irrua Specialist Teaching Hospital (ISTH), Irrua, Nigeria - An Electronic Medical Record Setting." International Journal of Advanced Academic Research 10, no. 7 (2024): 121–36. https://doi.org/10.5281/zenodo.14062207.
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<em>Background:</em> <em>Prolonged waiting typically affects patients’ satisfaction and may deter subsequent utilization of healthcare facility. There is a paucity of information regarding waiting time in hospitals where the Electronic medical record is been utilized particularly from the patients’ viewpoint. The aim of this study was to assess the waiting time and associated factors at the GOPD clinic of Irrua Specialists Teaching Hospital, (ISTH) where the EMR is fully adopted and operational.</em> <em> </em> <em>Subjects and Methods:</em> <em>An institutional-based descriptive cross-sectional study was carried out among 318 adult patients aged 21 and above who attended the GOPD of ISTH, Irrua, Nigeria. Patients were selected by simple random sampling and a structured questionnaire was used to collect data at the last service point. Data collected were cleaned and analyzed using the Statistical Package for Social Sciences version 20. Level of significance was set at p < 0.05.</em> <em>Results:</em> <em>The average waiting time for the clinic was 217 ± 37 minutes. Patients who were first-timers took much longer time (226.1min) than returning patients (206.1min) (p = 0.019).The primary reasons for the delay were: the clinic's bad physical layout, with the radiology and laboratory department located far from the consultation rooms, the instructional services provided to medical students during consultations, and the lack of reliable intranet connectivity with the EMR.</em> <em> </em> <em>Conclusion:</em> <em> Patients visiting the GOPD clinic experienced considerably long waiting hours even with the full implementation of the EMR. The foremost cause of this delay was the unstable EMR intranet at both the service point and payment stations. The EMR intranet connectivity should be improved upon to provide seamless services and reduce waiting time.</em>
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Kim, Hyun, Cheolhong Min, Byeongha Jeong, and Kyoung J. Lee. "Deciphering clock cell network morphology within the biological master clock, suprachiasmatic nucleus: From the perspective of circadian wave dynamics." PLOS Computational Biology 18, no. 6 (2022): e1010213. http://dx.doi.org/10.1371/journal.pcbi.1010213.
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The biological master clock, suprachiasmatic nucleus (of rat and mouse), is composed of ~10,000 clock cells which are heterogeneous with respect to their circadian periods. Despite this inhomogeneity, an intact SCN maintains a very good degree of circadian phase (time) coherence which is vital for sustaining various circadian rhythmic activities, and it is supposedly achieved by not just one but a few different cell-to-cell coupling mechanisms, among which action potential (AP)-mediated connectivity is known to be essential. But, due to technical difficulties and limitations in experiments, so far very little information is available about the morphology of the connectivity at a cellular scale. Building upon this limited amount of information, here we exhaustively and systematically explore a large pool (~25,000) of various network morphologies to come up with some plausible network features of SCN networks. All candidates under consideration reflect an experimentally obtained ‘indegree distribution’ as well as a ‘physical range distribution of afferent clock cells.’ Then, importantly, with a set of multitude criteria based on the properties of SCN circadian phase waves in extrinsically perturbed as well as in their natural states, we select out appropriate model networks: Some important measures are, 1) level of phase dispersal and direction of wave propagation, 2) phase-resetting ability of the model networks subject to external circadian forcing, and 3) decay rate of perturbation induced “phase-singularities.” The successful, realistic networks have several common features: 1) “indegree” and “outdegree” should have a positive correlation; 2) the cells in the SCN ventrolateral region (core) have a much larger total degree than that of the dorsal medial region (shell); 3) The number of intra-core edges is about 7.5 times that of intra-shell edges; and 4) the distance probability density function for the afferent connections fits well to a beta function. We believe that these newly identified network features would be a useful guide for future explorations on the very much unknown AP-mediated clock cell connectome within the SCN.
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Fontan, Lorena, Matthew Durant, Rebecca Goldstein, et al. "Mapping MALT1 Signaling Connectivity Unveils Novel B-Cell Feedback Mechanisms Directing Assembly of Potent Anti-Lymphoma Regimens." Blood 134, Supplement_1 (2019): 173. http://dx.doi.org/10.1182/blood-2019-130516.
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MALT1 inhibition is a promising strategy against B-cell receptor (BCR)-dependent lymphomas including ABC DLBCL, CLL and MCL. MALT1 is downstream of the most frequently mutated genes in the BCR and Toll-like receptor (TLR) pathways. MALT1 inhibitors are active in Ibrutinib-resistant BTK and PLCγ2 mutant CLL or CARD11 mutant ABC DLBCL. Therefore, MALT1 inhibitors, which recently began first in man clinical testing, have the potential to cover a larger patient population than drugs against more upstream targets in the BCR pathway including BTK inhibitors. However, activity of inhibitors targeting signaling mediators can be limited by feedback mechanisms counteracting and/or bypassing the need for a specific pathway. MALT1 is central to NF-κB activation downstream of the BCR. Therefore, activation of alternative pathways leading to full or partial activation of the BCR program or other pro-survival pathways might enable cell survival and set off MALT1i resistance. In order to map the landscape of resistance/sensitivity to MALT1 inhibition in ABC DLBCL and assist design of combinatorial regimens, we carried out a loss-of-function screen in HBL-1 (MALT1i sensitive) with or without MI-2 (small molecule irreversible inhibitor of MALT1) to identify genes capable of modulating response to MALT1 inhibition. Our analyses showed that loss of BCR and PI3K activators enhanced sensitivity, while loss of negative regulators of these pathways promoted MALT1i resistance. These findings were validated by knockdown of individual genes with two independent hairpins against activators CD79B, CARD11, BTK or the negative regulator TNFAIP3. Next, we carried out a combinatorial drug screen anchored in MALT1 inhibition by MI-2 or C3 (irreversible substrate-mimetic MALT1 inhibitor) and focused on inhibitors against signaling hubs in the BCR/PI3K pathways in 4 MALT1i sensitive cell lines. This combinatorial screen confirmed that concurrent inhibition of MALT1 and other BCR and PI3K pathways' proteins is additive (0.9&gt;CI (combination index) &lt;1.1) or synergistic (CI&lt;0.9). MALT1i combinations with PI3K and MTORC1 inhibitors were the most highly synergistic, mean CI&lt;0.5 for 2 MALT1 inhibitors and 4 cell lines, and were further pursued. In depth analysis of proliferation and cell death by CFSE dilution and Annexin V staining revealed that both MALT1/PI3K-i and MALT1/MTORC1-i combinations significantly enhanced growth inhibition and apoptosis in TMD8 and HBL-1 compared to individual agents. Results with MI-2 and C3 were comparable. Short exposure to MI-2 or C3 increased MTORC1 activity as assessed by S6K-Thr389 and S6-Ser235/6 phosphorylation in TMD8 and HBL-1 indicating that MALT1 protease activity modulates MTORC1 activation. MTOR activation is tumorigenic and can mediate chemotherapy resistance. Increased p-S6 following MALT1 inhibition (FC=1.4-2) was blocked by Idelalisib (PI3Ki). However, only Rapamycin, an MTORC1 inhibitor, reduced p-S6 levels relative to vehicle, FC=-5 alone or in combination. In vivo, MALT1/PI3K-i (MI-2/Idelalisib) significantly delayed tumor progression compared to single treatments (p&lt;0.01). In contrast, MALT1/MTORC1-i (MI-2/Rapamycin) promoted tumor regression and significantly improved survival of xenografted mice (median survival 37 days vs 18.5 or 29 days for MI-2 or Rapamycin respectively, p&lt;0.001). Tumors from MI-2/Idelalisib treated mice showed 15-fold increase in p-S6 at 21 days. Short exposure to MI-2 in vivo inhibited MALT1 activity over its targets BCL10 and Roquin-1 and increased MTORC1 activity over p-S6K-Thr389 (FC=1.5-2) and p-S6-Ser235/6 (FC=2-3) in ABC DLBCL xenografts. Rapamycin, but not Idelalisib, effectively blocked p-S6 (p&lt;0.001). MALT1/MTORC1-i regimens were also highly synergistic in 2 patient-derived xenografted (PDX) ABC DLBCL ex vivo. PDXs were cultured in gelatin/silicate nanoparticle hydrogel 3-D organoids and co-cultured with CD40L expressing cells. Compound pairs were assayed for synergy using 4x4 matrices and growth inhibition evaluated by flow cytometry. Synergy ZIP δ-score ranged 7-14 in 2 specimens for 2 MALT1i. Combined, these results suggest that: 1) MTORC1 activation constitutes a survival feedback mechanism activated after MALT1i treatment that might be leveraged by tumoral cells to evade MALT1 inhibition and, 2) that simultaneous targeting of MTORC1 could improve response and prevent resistance to MALT1 inhibitors. Disclosures Melnick: Constellation: Consultancy; Janssen: Research Funding; Epizyme: Consultancy.
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Greene, Patrick, Mike Howard, Rajan Bhattacharyya, and Jean-Marc Fellous. "Hippocampal Anatomy Supports the Use of Context in Object Recognition: A Computational Model." Computational Intelligence and Neuroscience 2013 (2013): 1–19. http://dx.doi.org/10.1155/2013/294878.
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The human hippocampus receives distinct signals via the lateral entorhinal cortex, typically associated with object features, and the medial entorhinal cortex, associated with spatial or contextual information. The existence of these distinct types of information calls for some means by which they can be managed in an appropriate way, by integrating them or keeping them separate as required to improve recognition. We hypothesize that several anatomical features of the hippocampus, including differentiation in connectivity between the superior/inferior blades of DG and the distal/proximal regions of CA3 and CA1, work together to play this information managing role. We construct a set of neural network models with these features and compare their recognition performance when given noisy or partial versions of contexts and their associated objects. We found that the anterior and posterior regions of the hippocampus naturally require different ratios of object and context input for optimal performance, due to the greater number of objects versus contexts. Additionally, we found that having separate processing regions in DG significantly aided recognition in situations where object inputs were degraded. However, split processing in both DG and CA3 resulted in performance tradeoffs, though the actual hippocampus may have ways of mitigating such losses.
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Shang, C. Y., Y. H. Wu, S. S. Gau, and W. Y. Tseng. "Disturbed microstructural integrity of the frontostriatal fiber pathways and executive dysfunction in children with attention deficit hyperactivity disorder." Psychological Medicine 43, no. 5 (2012): 1093–107. http://dx.doi.org/10.1017/s0033291712001869.
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BackgroundAttention deficit hyperactivity disorder (ADHD) is recognized as an early-onset neuropsychiatric disorder with executive dysfunctions and neurobiological deficits. The authors compared executive functions and microstructural integrity of the frontostriatal circuit in children with ADHD and typically developing children.MethodWe assessed 25 children with ADHD and 25 age-, sex-, handedness- and intelligence-matched typically developing children by using psychiatric interviews, the Wechsler Intelligence Scale for Children – third edition, and the tasks involving executive functions in the Cambridge Neuropsychological Test Automated Battery. The frontostriatal tracts were reconstructed by diffusion spectrum imaging tractography and were subdivided into four functionally distinct segments, including dorsolateral, medial prefrontal, orbitofrontal and ventrolateral tracts. Tract-specific and matched case-control analyses were used and generalized fractional anisotropy values were computed.ResultsChildren with ADHD had lower generalized fractional anisotropy of all the bilateral frontostriatal fiber tracts and poorer performance in verbal and spatial working memory, set-shifting, sustained attention, cognitive inhibition and visuospatial planning. The symptom severity of ADHD and the executive functioning performance significantly correlated with integrity of the frontostriatal tracts, particularly the left orbitofrontal and ventrolateral tracts. Children with ADHD also demonstrated loss of the leftward asymmetry in the dorsolateral and medial prefrontal tracts that was present in typically developing children.ConclusionsOur findings demonstrate disturbed structural connectivity of the frontostriatal circuitry in children with ADHD and add new evidence of associations between integrity of the frontostriatal tracts and measures of core symptoms of ADHD and a wide range of executive dysfunctions in both groups.
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Lee, Lim-Jung. "Exterior spaces in urban development projects for public realization Selecting Evaluation Items." Korean Association of Urban Policies 14, no. 4 (2023): 125–41. http://dx.doi.org/10.21447/jusre.2023.14.4.7.
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The purpose of this study was to recognize the importance of external space planning in urban development projects and to establish an evaluation item system for improving urban landscapes. It can be used as a guide to set evaluation items for exterior space planning considering sustainable urban development and to systematically inspect exterior space. As a research method, research literature and laws on landscape planning and review types were reviewed, and landscape checklist items were reviewed. The reviewed items were synthesized and refined by reclassifying and reviewing the contents through FGIs. Finally, we reviewed the consistency and validity of the reviewed items and selected the evaluation items through an expert survey. We also systematized them through content validity (CVR) analysis for reference in case of disagreements among experts in each field. The final 17 items consisted of checklists, operational guidelines, and detailed evaluations, and the contents were systematically reorganized as the items were mainly descriptive. Three items were selected for accessibility, four items for connectivity, three items for suitability, two items for safety (community), one item for locality (community), and four items for landscape.
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Naem, Amany A., and Neveen I. Ghali. "Optimizing community detection in social networks using antlion and K-median." Bulletin of Electrical Engineering and Informatics 8, no. 4 (2019). http://dx.doi.org/10.11591/eei.v8i4.1196.
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Antlion Optimization (ALO) is one of the latest population based optimization methods that proved its good performance in a variety of applications. The ALO algorithm copies the hunting mechanism of antlions to ants in nature. Community detection in social networks is conclusive to understanding the concepts of the networks. Identifying network communities can be viewed as a problem of clustering a set of nodes into communities. k-median clustering is one of the popular techniques that has been applied in clustering. The problem of clustering network can be formalized as an optimization problem where a qualitatively objective function that captures the intuition of a cluster as a set of nodes with better in ternal connectivity than external connectivity is selected to be optimized. In this paper, a mixture antlion optimization and k-median for solving the community detection problem is proposed and named as K-median Modularity ALO. Experimental results which are applied on real life networks show the ability of the mixture antlion optimization and k-median to detect successfully an optimized community structure based on putting the modularity as an objective function.
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Hariri, Saeed, Martin Plus, Mickael Le Gac, Véronique Séchet, Marta Revilla, and Marc Sourisseau. "Advection and Composition of Dinophysis spp. Populations Along the European Atlantic Shelf." Frontiers in Marine Science 9 (July 14, 2022). http://dx.doi.org/10.3389/fmars.2022.914909.
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The main objective was to study relationships between the regional biogeography of Dinophysis species and water masses circulation along the European Atlantic coast. Hydrodynamic connectivities were estimated with a Lagrangian approach. Available and validated physical hindcasts from regional hydrodynamical models, with different resolutions were used. The target area is the Bay of Biscay (NE Atlantic) and connectivity was evaluated between a set of spatially distributed stations and during temporally specified periods. Different indexes related to connectivity properties such as mean, median, most frequent transit times were calculated. To illustrate the dispersion pattern, a molecular approach was jointly set-up to describe the species composition of this genus. At the seasonal scale, a high connectivity within the Bay of Biscay was observed with a slight northward connectivity from Galicia coastal waters to the Shelf of the Bay of Biscay. By comparison to the connectivity between shelf waters of French Brittany and English Channel waters, a higher connectivity between shelf waters of French Brittany and the Celtic Sea shelf was observed. The species mixing in the Bay of Biscay from Galicia waters to the Celtic Sea was confirmed by the genetic analyses despite the absence of Dinophysis sacculus in natural samples. The molecular methodology developed for this work, permitting at least the description of the species composition, also highlights, at the European scale, an unexpected low genetic variability which echoes the complex taxonomic classification inside the genus and the difficulties encountered by national monitoring programs to reach a taxonomic resolution at species level. It is now necessary to start some monitoring at the species level before realizing mid- or long-term forecasts.
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Teng, Yuke, Tao Yin, Yue Yang, et al. "The Role of Medial Prefrontal Cortex in Acupuncture Treatment for Functional Dyspepsia." Frontiers in Neuroscience 16 (April 7, 2022). http://dx.doi.org/10.3389/fnins.2022.801899.
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Acupuncture is an effective therapy for functional dyspepsia (FD). However, the efficacy of acupuncture in the treatment of FD varies among individuals in clinical practice. This study aimed to reveal the brain response patterns in acupuncture higher response/lower response FD patients. Firstly, we performed a within-group comparison of brain function activity before and after acupuncture treatment in 115 FD patients and analyzed the correlation between brain function activity changes and clinical improvements. Secondly, 115 subjects were divided into the acupuncture higher response group or the lower response group based on the median clinical improvement values. The changes in functional brain activity after acupuncture treatment were investigated in these two groups, respectively. Finally, the identified brain regions associated with the clinical improvements were set as regions of interest (ROI), and the ROI-to-voxel functional connectivity comparisons were also performed in both groups, respectively. The results demonstrated that the functional activities of the left cerebellum inferior, right middle temporal gyrus, and right medial prefrontal cortex (mPFC) were increased, and the left Heschl and right middle cingulate cortex were decreased in 115 FD patients after acupuncture treatment. The functional connectivity changes of mPFC were correlated with improving the Nepean Dyspepsia Symptom Index. The significant increase in mPFC functional activity was also found in acupuncture higher response FD patients but not in lower response FD patients. The functional connectivity between the mPFC and default mode network (DMN) was significantly diminished in the higher response group but not in the lower response group. In conclusion, this study suggested that modulating the functional activity of the mPFC and its connectivity to the DMN may be one of the important mechanisms of acupuncture for treating FD with a higher response.
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Le Petit, Marine, Francis Eustache, Joy Perrier, Vincent De La Sayette, Béatrice Desgranges, and Mickaël Laisney. "Functional connectivity of the medial prefrontal cortex related to mindreading abilities." Cerebral Cortex Communications, July 31, 2022. http://dx.doi.org/10.1093/texcom/tgac032.
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Abstract The medial prefrontal cortex is a key region of mindreading belonging to the mentalizing system, a set of brain areas underlying mental state inference based on reasoning on social concepts. The aim of this study was to characterize the functional connectivity between regions involved in mindreading, and to highlight the processes it underpins, focusing on the dorsal and ventral parts of the medial prefrontal cortex. We analyzed resting-state functional magnetic resonance imaging of 56 healthy volunteers, to study the relationship between mindreading abilities and functional connectivity of the medial prefrontal cortex. Cognitive mindreading performances were correlated with connectivity between the medial prefrontal cortex and frontal regions involved in the regulation of the salience of one’s own mental contents, with a distinction between the dorsal part connected to regions subtending inhibition processes and the ventral part to emotional regions. Affective mindreading performances were negatively correlated with negative connectivity of the ventro- and dorsomedial prefrontal cortex with sensorimotor regions belonging to the mirror neuron system subtending the simulation of mental states. These findings suggested a role of the medial prefrontal cortex to decrease the salience of one’s own mental content and in the antisynchronous interaction between the mentalizing and mirror neurons systems.
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Smith, Nathan R., Shabeeb Ameen, Sierra N. Miller, et al. "The neuroanatomical organization of the hypothalamus is driven by spatial and topological efficiency." Frontiers in Systems Neuroscience 18 (August 5, 2024). http://dx.doi.org/10.3389/fnsys.2024.1417346.
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The hypothalamus in the mammalian brain is responsible for regulating functions associated with survival and reproduction representing a complex set of highly interconnected, yet anatomically and functionally distinct, sub-regions. It remains unclear what factors drive the spatial organization of sub-regions within the hypothalamus. One potential factor may be structural connectivity of the network that promotes efficient function with well-connected sub-regions placed closer together geometrically, i.e., the strongest axonal signal transferred through the shortest geometrical distance. To empirically test for such efficiency, we use hypothalamic data derived from the Allen Mouse Brain Connectivity Atlas, which provides a structural connectivity map of mouse brain regions derived from a series of viral tracing experiments. Using both cost function minimization and comparison with a weighted, sphere-packing ensemble, we demonstrate that the sum of the distances between hypothalamic sub-regions are not close to the minimum possible distance, consistent with prior whole brain studies. However, if such distances are weighted by the inverse of the magnitude of the connectivity, their sum is among the lowest possible values. Specifically, the hypothalamus appears within the top 94th percentile of neural efficiencies of randomly packed configurations and within one standard deviation of the median efficiency when packings are optimized for maximal neural efficiency. Our results, therefore, indicate that a combination of geometrical and topological constraints help govern the structure of the hypothalamus.
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Duan, Ying, Zilu Ma, Pei-Jung Tsai, et al. "Frontostriatal regulation of brain circuits contributes to flexible decision making." Neuropsychopharmacology, February 14, 2025. https://doi.org/10.1038/s41386-025-02065-8.
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Abstract Deficits in behavioral or cognitive flexibility that are linked to altered activity in both cortical and subcortical brain regions, are often observed across multiple neuropsychiatric disorders. The medial prefrontal cortex (mPFC)-nucleus accumbens (NAc) pathway in rats plays a critical role in flexible control of behavior. However, the modulation of this pathway on activity and functional connectivity with the rest of the brain remains unclear. In this study, we first confirmed the role of the mPFC-NAc pathway in behavioral flexibility using a set-shifting task in rats and then evaluated the causal effects of mPFC-NAc activation induced by chemogenetic stimulation of the terminal axons of the NAc with DREADD expression on whole-brain activity and functional connectivity measured by functional MRI. mPFC-NAc activation improved performance on the set-shifting task by reducing perseverative errors. Additionally, stimulation of this pathway increased activity in a set of brain regions within the basal ganglia-thalamus-cortical loop network including NAc, thalamus, hypothalamus and various connected cortical regions, while also decreased functional connectivity strength of NAc-mPFC, NAc-secondary motor cortex (M2), and various cortical circuits. Moreover, performance on the set-shifting task was related to the functional connectivity strength of the above frontostriatal and cortical circuits. These findings provide insights into the link between specific frontostriatal circuits on decision making flexibility, which may inform potential future interventions for behavioral flexibility deficits.
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Grassmann, Michael, Stephan Fuhrmann, and Thomas W. Guenther. "Assurance quality, disclosed connectivity of the capitals and information asymmetry – An interaction analysis for the case of integrated reporting." Meditari Accountancy Research, October 19, 2021. http://dx.doi.org/10.1108/medar-11-2020-1087.
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Purpose Credibility concerns regarding integrated reports can harm the intended decrease of information asymmetry between a firm and its investors. Therefore, it is crucial to examine whether voluntary third-party assurance enhances the credibility of integrated reports and, thus, decreases information asymmetry. Furthermore, this study aims to investigate the interaction effect between assurance quality and the disclosed connectivity of the capitals, a distinguishing feature of integrated reports. Design/methodology/approach Content analysis is performed of the 176 assurance statements included in the 269 integrated reports of Forbes Global 2000 firms disclosed from 2013 to 2015 and the 269 integrated reports themselves. Regression analyzes are applied to examine the associations between assurance, the disclosed connectivity of the capitals and information asymmetry. Findings The presence of an assurance statement in an integrated report significantly decreases information asymmetry. Surprisingly, assurance quality is not significantly associated with information asymmetry. However, an interaction analysis reveals that combining high assurance quality with high disclosed connectivity of the capitals allows a significant decrease in information asymmetry. Research limitations/implications The paper demonstrates that the connectivity of the capitals of integrated reports and assurance quality are connected and together are associated with information asymmetry. Practical implications The results imply, both for report preparers and standard setters, that assurance quality is advantageous only when combined with disclosed connectivity of the capitals. Social implications More information on non-financial information measured by the connectivity of the capitals of integrated reporting has an interaction effect together with assurance quality on information asymmetry. Originality/value This paper builds on a unique data set derived from the contents of integrated reports and accompanying assurance statements. Furthermore, it extends the integrated reporting literature by investigating the interaction between assurance quality and the disclosed connectivity of the capitals, which had not previously been examined in combination.
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Sun, Kaijia, Haixiang Wang, Yunxian Bai, Wenjing Zhou, and Liang Wang. "MRIES: A Matlab Toolbox for Mapping the Responses to Intracranial Electrical Stimulation." Frontiers in Neuroscience 15 (June 14, 2021). http://dx.doi.org/10.3389/fnins.2021.652841.
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ProposeDirected cortical responses to intracranial electrical stimulation are a good standard for mapping inter-regional direct connectivity. Cortico-cortical evoked potential (CCEP), elicited by single pulse electrical stimulation (SPES), has been widely used to map the normal and abnormal brain effective network. However, automated processing of CCEP datasets and visualization of connectivity results remain challenging for researchers and clinicians. In this study, we develop a Matlab toolbox named MRIES (Mapping the Responses to Intracranial Electrical Stimulation) to automatically process CCEP data and visualize the connectivity results.MethodThe MRIES integrates the processing pipeline of the CCEP datasets and various methods for connectivity calculation based on low- and high-frequency signals with stimulation artifacts removed. The connectivity matrices are saved in different folders for visualization. Different visualization patterns (connectivity matrix, circle map, surface map, and volume map) are also integrated to the graphical user interface (GUI), which makes it easy to intuitively display and compare different connectivity measurements. Furthermore, one sample CCEP data set collected from eight epilepsy patients is used to validate the MRIES toolbox.ResultWe show the GUI and visualization functions of MRIES using one example CCEP data that has been described in a complete tutorial. We applied this toolbox to the sample CCEP data set to investigate the direct connectivity between the medial temporal lobe and the insular cortex. We find bidirectional connectivity between MTL and insular that are consistent with the findings of previous studies.ConclusionMRIES has a friendly GUI and integrates the full processing pipeline of CCEP data and various visualization methods. The MRIES toolbox, tutorial, and example data can be freely downloaded. As an open-source package, MRIES is expected to improve the reproducibility of CCEP findings and facilitate clinical translation.
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Fousekis, Panos. "How does fear spread across asset classes? Evidence from quantile connectedness." Studies in Economics and Finance, September 15, 2023. http://dx.doi.org/10.1108/sef-07-2023-0408.
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Purpose This study aims to investigate the connectivity among four principal implied volatility (“fear”) markets in the USA. Design/methodology/approach The empirical analysis relies on daily data (“fear gauge indices”) for the period 2017–2023 and the quantile vector autoregressive (QVAR) approach that allows connectivity (that is, the network topology of interrelated markets) to be quantile-dependent and time-varying. Findings Extreme increases in fear are transmitted with higher intensity relative to extreme decreases in it. The implied volatility markets for gold and for stocks are the main risk connectors in the network and also net transmitters of shocks to the implied volatility markets for crude oil and for the euro-dollar exchange rate. Major events such as the COVID-19 pandemic and the war in Ukraine increase connectivity; this increase, however, is likely to be more pronounced at the median than the extremes of the joint distribution of the four fear indices. Originality/value This is the first work that uses the QVAR approach to implied volatility markets. The empirical results provide useful insights into how fear spreads across stock and commodities markets, something that is important for risk management, option pricing and forecasting.
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Gómez-A, Alexander, Carol A. Dannenhoffer, Amanda Elton, et al. "Altered Cortico-Subcortical Network After Adolescent Alcohol Exposure Mediates Behavioral Deficits in Flexible Decision-Making." Frontiers in Pharmacology 12 (November 29, 2021). http://dx.doi.org/10.3389/fphar.2021.778884.
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Behavioral flexibility, the ability to modify behavior according to changing conditions, is essential to optimize decision-making. Deficits in behavioral flexibility that persist into adulthood are one consequence of adolescent alcohol exposure, and another is decreased functional connectivity in brain structures involved in decision-making; however, a link between these two outcomes has not been established. We assessed effects of adolescent alcohol and sex on both Pavlovian and instrumental behaviors and resting-state functional connectivity MRI in adult animals to determine associations between behavioral flexibility and resting-state functional connectivity. Alcohol exposure impaired attentional set reversals and decreased functional connectivity among cortical and subcortical regions-of-interest that underlie flexible behavior. Moreover, mediation analyses indicated that adolescent alcohol-induced reductions in functional connectivity within a subnetwork of affected brain regions statistically mediated errors committed during reversal learning. These results provide a novel link between persistent reductions in brain functional connectivity and deficits in behavioral flexibility resulting from adolescent alcohol exposure.
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Salvador, Raymond, Paola Fuentes-Claramonte, María Ángeles García-León, et al. "Regularized Functional Connectivity in Schizophrenia." Frontiers in Human Neuroscience 16 (May 11, 2022). http://dx.doi.org/10.3389/fnhum.2022.878028.
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Regularization may be used as an alternative to dimensionality reduction when the number of variables in a model is much larger than the number of available observations. In a recent study from our group regularized regression was employed to quantify brain functional connectivity in a sample of healthy controls using a brain parcellation and resting state fMRI images. Here regularization is applied to evaluate resting state connectivity abnormalities at the voxel level in a sample of patients with schizophrenia. Specifically, ridge regression is implemented with different degrees of regularization. Results are compared to those delivered by the weighted global brain connectivity method (GBC), which is based on averaged bivariate correlations and from the non-redundant connectivity method (NRC), a dimensionality reduction approach that applies supervised principal component regressions. Ridge regression is able to detect a larger set of abnormally connected regions than both GBC and NRC methods, including schizophrenia related connectivity reductions in fronto-medial, somatosensory and occipital structures. Due to its multivariate nature, the proposed method is much more sensitive to group abnormalities than the GBC, but it also outperforms the NRC, which is multivariate too. Voxel based regularized regression is a simple and sensitive alternative for quantifying brain functional connectivity.
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Schaper, Frederic L. W. V. J., Janne Nordberg, Alexander L. Cohen, et al. "Mapping Lesion-Related Epilepsy to a Human Brain Network." JAMA Neurology, July 3, 2023. http://dx.doi.org/10.1001/jamaneurol.2023.1988.
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ImportanceIt remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions.ObjectiveTo assess whether lesion locations associated with epilepsy map to specific brain regions and networks.Design, Setting, and ParticipantsThis case-control study used lesion location and lesion network mapping to identify the brain regions and networks associated with epilepsy in a discovery data set of patients with poststroke epilepsy and control patients with stroke. Patients with stroke lesions and epilepsy (n = 76) or no epilepsy (n = 625) were included. Generalizability to other lesion types was assessed using 4 independent cohorts as validation data sets. The total numbers of patients across all datasets (both discovery and validation datasets) were 347 with epilepsy and 1126 without. Therapeutic relevance was assessed using deep brain stimulation sites that improve seizure control. Data were analyzed from September 2018 through December 2022. All shared patient data were analyzed and included; no patients were excluded.Main Outcomes and MeasuresEpilepsy or no epilepsy.ResultsLesion locations from 76 patients with poststroke epilepsy (39 [51%] male; mean [SD] age, 61.0 [14.6] years; mean [SD] follow-up, 6.7 [2.0] years) and 625 control patients with stroke (366 [59%] male; mean [SD] age, 62.0 [14.1] years; follow-up range, 3-12 months) were included in the discovery data set. Lesions associated with epilepsy occurred in multiple heterogenous locations spanning different lobes and vascular territories. However, these same lesion locations were part of a specific brain network defined by functional connectivity to the basal ganglia and cerebellum. Findings were validated in 4 independent cohorts including 772 patients with brain lesions (271 [35%] with epilepsy; 515 [67%] male; median [IQR] age, 60 [50-70] years; follow-up range, 3-35 years). Lesion connectivity to this brain network was associated with increased risk of epilepsy after stroke (odds ratio [OR], 2.82; 95% CI, 2.02-4.10; P &amp;lt; .001) and across different lesion types (OR, 2.85; 95% CI, 2.23-3.69; P &amp;lt; .001). Deep brain stimulation site connectivity to this same network was associated with improved seizure control (r, 0.63; P &amp;lt; .001) in 30 patients with drug-resistant epilepsy (21 [70%] male; median [IQR] age, 39 [32-46] years; median [IQR] follow-up, 24 [16-30] months).Conclusions and RelevanceThe findings in this study indicate that lesion-related epilepsy mapped to a human brain network, which could help identify patients at risk of epilepsy after a brain lesion and guide brain stimulation therapies.