Sensory Networks Research Articles

The role of the default mode network in longitudinal functional brain reorganization of brain gliomas

The study of patients after glioma resection offers a unique opportunity to investigate brain reorganization. It is currently unknown how the whole-brain connectomic profile evolves longitudinally after surgical resection of a glioma and how this may be associated with tumor characteristics and cognitive outcome. In this longitudinal study, we investigate the impact of tumor lateralization and grade on functional connectivity (FC) in highly connected networks, or hubs, and cognitive performance. Twenty-eight patients (17 high-grade, 11 low-grade gliomas) underwent longitudinal pre/post-surgery resting-state fMRI scans and neuropsychological assessments (73 total measures). FC matrices were constructed considering as functional hubs the default mode (DMN) and fronto-parietal networks. No-hubs included primary sensory functional networks and any other no-hubs nodes. Both tumor hemisphere and grade affected brain reorganization post-resection. In right-hemisphere tumor patients, regardless of grade and relative to left-hemisphere gliomas, FC increased longitudinally after the intervention, both in terms of FC within hubs (phubs = 0.0004) and FC between hubs and no-hubs (phubs-no-hubs = 0.005). Regardless of tumor side, only lower-grade gliomas showed longitudinal FC increases relative to high-grade tumors within a precise hub network, the DMN. The neurocognitive profile was longitudinally associated with spatial features of the connectome, mainly within the DMN. We provide evidence that clinical glioma features, such as lateralization and grade, affect post-surgical longitudinal functional reorganization and cognitive recovery. The data suggest a possible role of the DMN in supporting cognition, providing useful information for prognostic prediction and surgical planning.

Differential alterations in brain structural network organization during addiction between adolescents and adults.

The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear. Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls). MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents. Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.

Distributed networks for auditory memory differentially contribute to recall precision

Re-directing attention to objects in working memory can enhance their representational fidelity. However, how this attentional enhancement of memory representations is implemented across distinct, sensory and cognitive-control brain network is unspecified. The present fMRI experiment leverages psychophysical modelling and multivariate auditory-pattern decoding as behavioral and neural proxies of mnemonic fidelity. Listeners performed an auditory syllable pitch-discrimination task and received retro-active cues to selectively attend to a to-be-probed syllable in memory. Accompanied by increased neural activation in fronto-parietal and cingulo-opercular networks, valid retro-cues yielded faster and more perceptually sensitive responses in recalling acoustic detail of memorized syllables. Information about the cued auditory object was decodable from hemodynamic response patterns in superior temporal sulcus (STS), fronto-parietal, and sensorimotor regions. However, among these regions retaining auditory memory objects, neural fidelity in the left STS and its enhancement through attention-to-memory best predicted individuals’ gain in auditory memory recall precision. Our results demonstrate how functionally discrete brain regions differentially contribute to the attentional enhancement of memory representations.

An Intra-Vehicular Wireless Multimedia Sensor Network for Smartphone-Based Low-Cost Advanced Driver-Assistance Systems.

Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates the need for cable harnessing and, therefore, the practicality of a novel wireless ADAS solution was tested. A low-cost alternative is proposed that extends a smartphone’s sensor perception, using a camera-based wireless sensor network. This paper presents the design of a low-cost ADAS alternative that uses an intra-vehicle wireless sensor network structured by a Wi-Fi Direct topology, using a smartphone as the processing platform. The proposed system makes ADAS features accessible to cheaper vehicles and investigates the possibility of using a wireless network to communicate ADAS information in a intra-vehicle environment. Other ADAS smartphone approaches make use of a smartphone’s onboard sensors; however, this paper shows the application of essential ADAS features developed on the smartphone’s ADAS application, carrying out both lane detection and collision detection on a vehicle by using wireless sensor data. A smartphone’s processing power was harnessed and used as a generic object detector through a convolution neural network, using the sensory network’s video streams. The network’s performance was analysed to ensure that the network could carry out detection in real-time. A low-cost CMOS camera sensor network with a smartphone found an application, using Wi-Fi Direct, to create an intra-vehicle wireless network as a low-cost advanced driver-assistance system.

Altered Dynamic Functional Connectivity in Early Psychosis Between the Salience Network and Visual Network

In early psychosis there are alterations in the static functional interaction between the salience network (SN) and higher-order cognitive networks. It is unclear whether these changes extend to the dynamic functional connectivity (dFC) of the SN, and whether the dFC between the SN and low-order networks (e.g., sensory networks) is affected. This study examined the temporal properties of the functional connectivity of the SN in individuals with early psychosis. In this study, selected core regions of the SN included the left and right anterior insula (AIs) and anterior cingulate cortex (ACC), based on independent component analysis of 26 and 20 subjects with first-episode schizophrenia (FES) or at clinical high risk for psychosis (CHR), and 37 healthy controls (HC). The dFC of each region was investigated via sliding window-based analyses with whole brain voxels. We found compared with the HC, in the FES and CHR groups the bilateral AI and ACC showed less variability in dFC with regions in the visual network; the variability between the ACC and visual regions in the FES group was less than that of the CHR; and in the FES and CHR groups the variability in dFC was higher between the right AI and the left precuneus (a core region of the default mode network). This study confirmed abnormality of dynamic functional interaction between the SN and the DMN in psychosis. More importantly, the disruption of communication between the SN and the lower-order brain network is another important aspect of the neural basis of psychosis.

Artificial intelligence agriculture recommendation model (AIARM)

Agricultural production is extremely important to the global economy. Agribusiness not only provides food and raw materials, but also provides employment opportunities to a large portion of the population.Increased agricultural production and per-capita income in rural areas, combined with industrialization and urbanization, resulting in increased demand for industrial goods.According to a analysis conducted by the Food and Agriculture Organization, the world's population is projected to increase by another two billion people by 2050, while cropland is only expected to increase by 5%. As a result, to increase agricultural productivity, smart and capable farming approaches are needed. Agriculture land suitability appraisement is a required tools for agriculture advancement. The fast growth of wireless networks has resulted in the development of low-cost Internet of Things (IoT) devices that are favored as a useful methodology for agricultural autonomy and decision making. The proposed model, called the Artificial Intelligence Agriculture Recommendation Model (AIARM), incorporates sensory networks and artificial intelligence programs like neural networks and multi-layer perceptron to determine crop readiness, crop prediction, and fertilizer recommendations. Instead of a binary split, the proposed system divides agricultural land into four categories of decisions, which are fair, appropriate, fairly equitable, and not appropriate to guide farmers accurately.

МЕТОДОЛОГІЯ СТАТИСТИЧНОГО ОЦІНЮВАННЯ СТАНУ І ДИНАМІКИ ЦИФРОВОЇ ТРАНСФОРМАЦІЇ УКРАЇНИ

Визначено сутність цифровізації економіки і цифрової трансформації країни, оцінено вплив факторів, які спричинили початок цих процесів, сприяли набранню ними сил і досягненню сучасного рівня. Аналіз використання новітніх досягнень у галузі економічної теорії дозволив визначити цифрову економіку як комунікаційне середовище економічної діяльності в мережі Інтернет, а також інших мобільних і сенсорних мережах, яке формується як результат трансформаційного впливу нових технологій загального призначення у галузях інформації, комунікації та нанотехнологій.На підставі критичного аналізу методології побудови композитних індексів, які наразі використовуються для оцінки рівня цифровізації різних економік, та визначення сильних і слабких сторін кожного з них запропоновано авторську оригінальну методику, якій не притаманні недоліки існуючих підходів. Вона ґрунтується на узагальненні значень індексів, побудованих і проаналізованих різними міжнародними організаціями, у тому числі агенціями ООН, і розрахунку на цій основі власного інтегрального показника, значення якого усереднює характеристики десяти найвідоміших індексів, які оцінюють рівень цифровізації світової економіки та окремих країн. Зроблено висновок, що за значеннями цих індексів Україна посідає дуже непрестижне місце у світовому розподілі країн за рівнем цифровізації їх національних економік. За допомогою SWOT-аналізу визначено резерви прискорення процесу цифровізації економіки і суспільства України.Використання результатів дослідження дозволяє підвищити рівень результативності заходів державної політики в галузі формування концептуальних засад розвитку цифрової економіки і суспільства й закласти основу для подальших наукових досліджень у цій сфері.

A pilot project for the long-term structural health monitoring of historic city gates

This paper reports on a pilot project for long-term structural health monitoring of historical city gates. This structural typology is what today remains of the defensive structures that characterised the medieval centres of many European cities. Even though in the last years the scientific community has paid great attention to the structural analysis and on the structural health monitoring of masonry towers, which are apparently similar to the typology of city gates, only a few studies explicitly approach such heritage buildings. In most cases, the surviving gates are immersed in the daily vehicular-traffic flows and hence continuously subjected to traffic-induced vibration. Consequently, a key point both for their conservation is the assessment of the optimal sensors position to be used for reliable structural health monitoring procedures. These issues are here discussed with reference to a specific case: the San Niccolò gate in Florence (Italy). First, an expeditious experimental campaign performed with a reduced number of accelerometers is reported. This test is aimed to identify a numerical model that is subsequently employed to design the optimal sensor position of long-term structural monitoring. This optimal sensor grid must be assessed to ensure a low-cost and sustainable dynamic monitoring system but, at the same time, to maximize the information contents.

Inferring Brain State Dynamics Underlying Naturalistic Stimuli Evoked Emotion Changes With dHA-HMM.

The brain functional mechanisms underlying emotional changes have been primarily studied based on the traditional task design with discrete and simple stimuli. However, the brain state transitions when exposed to continuous and naturalistic stimuli with rich affection variations remain poorly understood. This study proposes a dynamic hyperalignment algorithm (dHA) to functionally align the inter-subject neural activity. The hidden Markov model (HMM) was used to study how the brain dynamics responds to emotion during long-time movie-viewing activity. The results showed that dHA significantly improved inter-subject consistency and allowed more consistent temporal HMM states across participants. Afterward, grouping the emotions in a clustering dendrogram revealed a hierarchical grouping of the HMM states. Further emotional sensitivity and specificity analyses of ordered states revealed the most significant differences in happiness and sadness. We then compared the activation map in HMM states during happiness and sadness and found significant differences in the whole brain, but strong activation was observed during both in the superior temporal gyrus, which is related to the early process of emotional prosody processing. A comparison of the inter-network functional connections indicates unique functional connections of the memory retrieval and cognitive network with the cerebellum network during happiness. Moreover, the persistent bilateral connections among salience, cognitive, and sensorimotor networks during sadness may reflect the interaction between high-level cognitive networks and low-level sensory networks. The main results were verified by the second session of the dataset. All these findings enrich our understanding of the brain states related to emotional variation during naturalistic stimuli.

Accurate Measurements of Seabed Subsidence Above Norwegian Gas Fields

Summary Field-wide seafloor subsidence has been monitored at ten hydrocarbon fields offshore Norway. Subsidence provides lateral information on compressibility and pressure depletion in the reservoirs. This has been used to calibrate geomechanical and reservoir flow models, to map reservoir and aquifer compaction and identify poorly drained compartments. Water pressure measurements have given survey-internal precision of 2–5 mm. Tidal variations in the seafloor pressure have been carefully measured and corrected, which requires a spatial grid of reference sensors. A segment of the Midgard gas field showed significantly less subsidence than expected. This was interpreted as being caused by less depletion. A new well was drilled based on the subsidence data, a reinterpretation of the structural model, and a revised flow model. Almost virgin pressure was found. The well has since been the best producer on the field and paid back the cost of data acquisition by at least two orders of magnitude.

Reconfiguration of Brain Network Dynamics in Autism Spectrum Disorder Based on Hidden Markov Model.

Autism spectrum disorder (ASD) is a group of complex neurodevelopment disorders characterized by altered brain connectivity. However, the majority of neuroimaging studies for ASD focus on the static pattern of brain function and largely neglect brain activity dynamics, which might provide deeper insight into the underlying mechanism of brain functions for ASD. Therefore, we proposed a framework with Hidden Markov Model (HMM) analysis for resting-state functional MRI (fMRI) from a large multicenter dataset of 507 male subjects. Specifically, the 507 subjects included 209 subjects with ASD and 298 well-matched health controls across 14 sites from the Autism Brain Imaging Data Exchange (ABIDE). Based on the HMM, we can identify the recurring brain function networks over time across ASD and healthy controls (HCs). Then we assessed the dynamical configuration of the whole-brain networks and further analyzed the community structure of transitions across the brain states. Based on the 19 HMM states, we found that the global temporal statistics of the specific HMM states (including fractional occupancies and lifetimes) were significantly altered in ASD compared to HCs. These specific HMM states were characterized by the activation pattern of default mode network (DMN), sensory processing networks [including visual network, auditory network, and sensory and motor network (SMN)]. Meanwhile, we also find that the specific modules of transitions between states were closely related to ASD. Our findings indicate the temporal reconfiguration of the brain network in ASD and provide novel insights into the dynamics of the whole-brain networks for ASD.

Reorganization of sensory networks after subcortical vestibular infarcts: A longitudinal symptom-related voxel-based morphometry study.

We aimed to delineate common principles of reorganization after infarcts of the subcortical vestibular circuitry related to the clinical symptomatology. Our hypothesis was that the recovery of specific symptoms is associated with changes in distinct regions within the core vestibular, somatosensory, and visual cortical and subcortical networks. We used voxel- and surface-based morphometry to investigate structural reorganization of subcortical and cortical brain areas in 42 patients with a unilateral, subcortical infarct with vestibular and ocular motor deficits in the acute phase. The patients received structural neuroimaging and clinical monitoring twice (acute phase and after 6months) to detect within-subject changes over time. In patients with vestibular signs such as tilts of the subjective visual vertical (SVV) and ocular torsion in the acute phase, significant volumetric increases in the superficial white matter around the parieto-opercular (retro-)insular vestibular cortex (PIVC) were found at follow-up. In patients with SVV tilts, spontaneous nystagmus, and rotatory vertigo in the acute phase, gray matter volume decreases were located in the cerebellum and the visual cortex bilaterally at follow-up. Patients with saccade pathology demonstrated volumetric decreases in cerebellar, thalamic, and cortical centers for ocular motor control. The findings support the role of the PIVC as the key hub for vestibular processing and reorganization. The volumetric decreases represent the reciprocal interaction of the vestibular, visual, and ocular motor systems during self-location and egomotion detection. A modulation in vestibular and ocular motor as well as visual networks was induced independently of the vestibular lesion site.

Shared genetic influences on resting-state functional networks of the brain.

The amplitude of activation in brain resting state networks (RSNs), measured with resting‐state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome‐wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

The Impact of the Extracellular Matrix Environment on Sost Expression by the MLO-Y4 Osteocyte Cell Line.

Bone is a dynamic organ that can adapt its structure to meet the demands of its biochemical and biophysical environment. Osteocytes form a sensory network throughout the tissue and orchestrate tissue adaptation via the release of soluble factors such as a sclerostin. Osteocyte physiology has traditionally been challenging to investigate due to the uniquely mineralized extracellular matrix (ECM) of bone leading to the development of osteocyte cell lines. Importantly, the most widely researched and utilized osteocyte cell line: the MLO-Y4, is limited by its inability to express sclerostin (Sost gene) in typical in-vitro culture. We theorised that culture in an environment closer to the in vivo osteocyte environment could impact on Sost expression. Therefore, this study investigated the role of composition and dimensionality in directing Sost expression in MLO-Y4 cells using collagen-based ECM analogues. A significant outcome of this study is that MLO-Y4 cells, when cultured on a hydroxyapatite (HA)-containing two-dimensional (2D) film analogue, expressed Sost. Moreover, three-dimensional (3D) culture within HA-containing collagen scaffolds significantly enhanced Sost expression, demonstrating the impact of ECM composition and dimensionality on MLO-Y4 behaviour. Importantly, in this bone mimetic ECM environment, Sost expression was found to be comparable to physiological levels. Lastly, MLO-Y4 cells cultured in these novel conditions responded accordingly to fluid flow stimulation with a decrease in expression. This study therefore presents a novel culture system for the MLO-Y4 osteocyte cell line, ensuring the expression of an important osteocyte specific gene, Sost, overcoming a major limitation of this model.

Exploring alterations in sensory pathways in migraine

BackgroundMigraine is a neurological disorder characterized by intense, debilitating headaches, often coupled with nausea, vomiting and sensitivity to light and sound. Whilst changes in sensory processes during a migraine attack have been well-described, there is growing evidence that even between migraine attacks, sensory abilities are disrupted in migraine. Brain imaging studies have investigated altered coupling between areas of the descending pain modulatory pathway but coupling between somatosensory processing regions between migraine attacks has not been properly studied. The aim of this study was to determine if ongoing functional connectivity between visual, auditory, olfactory, gustatory and somatosensory cortices are altered during the interictal phase of migraine.MethodsTo explore the neural mechanisms underpinning interictal changes in sensory processing, we used functional magnetic resonance imaging to compare resting brain activity patterns and connectivity in migraineurs between migraine attacks (n = 32) and in healthy controls (n = 71). Significant differences between groups were determined using two-sample random effects procedures (p < 0.05, corrected for multiple comparisons, minimum cluster size 10 contiguous voxels, age and gender included as nuisance variables).ResultsIn the migraine group, increases in infra-slow oscillatory activity were detected in the right primary visual cortex (V1), secondary visual cortex (V2) and third visual complex (V3), and left V3. In addition, resting connectivity analysis revealed that migraineurs displayed significantly enhanced connectivity between V1 and V2 with other sensory cortices including the auditory, gustatory, motor and somatosensory cortices.ConclusionsThese data provide evidence for a dysfunctional sensory network in pain-free migraine patients which may be underlying altered sensory processing between migraine attacks.

Disrupted stepwise functional brain organization in overweight individuals

Functional hierarchy establishes core axes of the brain, and overweight individuals show alterations in the networks anchored on these axes, particularly in those involved in sensory and cognitive control systems. However, quantitative assessments of hierarchical brain organization in overweight individuals are lacking. Capitalizing stepwise functional connectivity analysis, we assess altered functional connectivity in overweight individuals relative to healthy weight controls along the brain hierarchy. Seeding from the brain regions associated with obesity phenotypes, we conduct stepwise connectivity analysis at different step distances and compare functional degrees between the groups. We find strong functional connectivity in the somatomotor and prefrontal cortices in both groups, and both converge to transmodal systems, including frontoparietal and default-mode networks, as the number of steps increased. Conversely, compared with the healthy weight group, overweight individuals show a marked decrease in functional degree in somatosensory and attention networks across the steps, whereas visual and limbic networks show an increasing trend. Associating functional degree with eating behaviors, we observe negative associations between functional degrees in sensory networks and hunger and disinhibition-related behaviors. Our findings suggest that overweight individuals show disrupted functional network organization along the hierarchical axis of the brain and these results provide insights for behavioral associations.

アデノシンA2b受容体は発達期早期のmGluR5発現抑制を介した感覚刺激ネットワークの形成に寄与する

アデノシンA2b受容体は発達期早期のmGluR5発現抑制を介した感覚刺激ネットワークの形成に寄与する

Decoding sensory brain networks: A quick take at SfN with Ethan Scott

Decoding sensory brain networks: A quick take at SfN with Ethan Scott

Functional connectivity in the dorsal network of the cervical spinal cord is correlated with diffusion tensor imaging indices in relapsing-remitting multiple sclerosis

Focal lesions may affect functional connectivity (FC) of the ventral and dorsal networks in the cervical spinal cord of people with relapsing-remitting multiple sclerosis (RRMS). Resting-state FC can be measured using functional MRI (fMRI) at 3T. This study sought to determine whether alterations in FC may be related to the degree of damage in the normal-appearing tissue. Tissue integrity and FC in the cervical spinal cord were assessed with diffusion tensor imaging (DTI) and resting-state fMRI, respectively, in a group of 26 RRMS participants with high cervical lesion load, low disability, and minimally impaired sensorimotor function, and healthy controls. Lower fractional anisotropy (FA) and higher radial diffusivity (RD) were observed in the normal-appearing white matter in the RRMS group relative to controls. Average FC in ventral and dorsal networks was similar between groups. Significant associations were found between higher FC in the dorsal sensory network and several DTI markers of pathology in the normal-appearing tissue. In the normal-appearing grey matter, dorsal FC was positively correlated with axial diffusivity (AD) (r = 0.46, p = 0.020) and mean diffusivity (MD) (r = 0.43, p = 0.032). In the normal-appearing white matter, dorsal FC was negatively correlated with FA (r = −0.43, p = 0.028) and positively correlated with RD (r = 0.49, p = 0.012), AD (r = 0.42, p = 0.037) and MD (r = 0.53, p = 0.006). These results suggest that increased connectivity, while remaining within the normal range, may represent a compensatory mechanism in response to structural damage in support of preserved sensory function in RRMS.

밸런스 트레이닝이 발목 및 엉덩이 안정성에 미치는 영향

Ankle sprains are one of the most common reasons for visitation to an emergency. Even though these injuries are prevalent in our life, clinical methods which can identify conditions such as chronic ankle instability are not well known because of lack of samples. Improving strength in hip abduction, external rotation, and extension and the role of muscles can be significant to prevent ankle sprains. Furthermore, applying different types of balance training such as stimulating and improving adaptations to sensory networks or the strength increases on hip or lower-leg musculature would be considered the clinical way that the practitioners can implement. Therefore, the purpose of this paper was to review studies exploring balance training and the stability of the ankle and the hip. In addition, it was to explore the effects of balance training on ankle and hip stability. Many positive effects from balance training were found from previous studies instead of potential risks. More research should be conducted in measuring hip stability and studies involving balance training could aim to find ways in investigating the effects of such training in the hip complex and the curvature of the spine.