Individual Connections Research Articles

Dynamic Topological Subtype Analysis of Healthy Brain Activity

The functional organization of the human brain exhibits certain heterogeneity; however, the topological subtype characteristics of brain networks in healthy populations have not been fully explored. This study, based on resting-state functional magnetic resonance imaging data from 48 healthy adults in the UK Biobank dataset, employs persistent homology analysis to identify and characterize different subtypes of brain network topology. By constructing individual functional connectivity matrices and extracting their zero-dimensional (connected components) and one-dimensional (circular structures) topological features, unsupervised clustering analysis revealed three brain network subtypes with distinct functional organizational characteristics: the mainstream subtype (52.1%) exhibited moderate network connectivity and moderate modularity; the high modularity subtype (27.1%) displayed the most persistent circular structures and the highest network segregation; the integrative subtype (20.8%) featured extensive functional connectivity but a simple topological structure. Further statistical analysis confirmed significant differences between these subtypes across all topological feature dimensions (p < 0.001). These findings, for the first time, reveal the heterogeneity of brain functional organization in healthy populations from a topological perspective, providing important evidence for constructing more accurate brain network models and developing individualized clinical applications.

Predicting an individual's functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects.

Several recent studies have optimized deep neural networks to learn high-dimensional relationships linking structural and functional connectivity across the human connectome. However, the extent to which these models recapitulate individual-specific characteristics of resting-state functional brain networks remains unclear. A core concern relates to whether current individual predictions outperform simple benchmarks such as group averages and null conditions. Here, we consider two measures to statistically evaluate whether functional connectivity predictions capture individual effects. We revisit our previously published functional connectivity predictions for 1,000 healthy adults and provide multiple lines of evidence supporting that our predictions successfully capture subtle individual-specific variation in connectivity. While predicted individual effects are statistically significant and outperform several benchmarks, we find that effect sizes are small (i.e., 8%-11% improvement relative to group-average benchmarks). As such, initial expectations about individual prediction performance expressed by us and others may require moderation. We conclude that individual predictions can significantly outperform appropriate benchmark conditions and we provide several recommendations for future studies in this area. Future studies should statistically assess the individual prediction performance of their models using one of the measures and benchmarks provided here.

Here there be Dragons: Evolution, Potentials and Mitigation Opportunities of Cybercrime in Nigeria

The world is becoming increasingly interconnected due to advancements in technology and the adoption of the internet. The once widely used traditional forms of communication such as parcels have become unpopular. The development of computers and the internet has become the primary mode of communication. Internet is now widely used across businesses, government departments, and individual mobile connectivity. However, the increased internet use has posed modern threats attributed to cybercrime. Nigeria is experiencing growth in population and internet connectivity, with an internet penetration of 33.6%. With an estimated population of just over 205 million people, the impacts of cybercrime will continue to increase. Nigeria is now regarded as the cradle of cybercrime activities in sub-Saharan Africa. Cybercrime is estimated to cost the economy of Nigeria $649 million annually. Besides, cybercrime activities have other impacts, such as impersonation and plagiarism. Due to the scale of these impacts, it is imperative that an adequate capacity to handle emerging issues in cybercrime be developed. The study investigated cybercrime preparedness in Nigeria. Research findings indicate that Nigeria has inadequate legal and educational preparedness to help mitigate the rising incidences of cybercrime in the country. The country has only one cybercrime act passed in 2015 and five universities that offer cybercrime-specific courses.

A game theoretic complex network model to estimate the epidemic threshold under individual vaccination behaviour and adaptive social connections

In today’s interconnected world, the spread of information is closely linked to infectious disease dynamics. Public awareness plays a crucial role, as individual vaccination decisions significantly impact collective efforts to combat emerging health threats. This study explores disease transmission within a framework integrating social connections, information sharing, and individual vaccination decisions. We introduce a behaviour-prevalence model on an adaptive multiplex network, where the physical layer (Layer-II) captures disease transmission under vaccination. In contrast, the virtual layer (Layer-I) represents adaptive social contacts and the flow of information, shaping vaccination decisions within a socially influenced environment. We derive analytical expressions for the epidemic threshold using the microscopic Markov Chain Method (MMCM). Simulation results highlight that adaptive social contacts lead to a higher epidemic threshold than non-adaptive networks. Additionally, network characteristics, such as the power-law exponent in scale-free networks, significantly impact infection spread within populations. Our results reveal that changes in perceived infection risk and an individual’s sensitivity to non-vaccinated neighbour’s status strongly influence vaccine uptake across populations. These insights can guide public health officials in developing targeted vaccination programs that address the evolving dynamics of social connections, information dissemination, and vaccination choice in the digital era.

Periodontitis associated with brain function impairment in middle-aged and elderly individuals with normal cognition.

The present study aimed to investigate changes in intranetwork functional connectivity (FC) and internetwork FC in middle-aged and elderly individuals with normal cognition (NC) and varying degrees of periodontitis to determine the effects of periodontitis on brain function. Periodontal findings and resting-state functional magnetic resonance imaging data were acquired from 51 subjects with NC. Independent component analysis and correlation analysis were used for the statistical analysis of the data. Differences in intranetwork FC were observed among groups in the anterior default-mode network (aDMN), dorsal attention network and dorsal sensorimotor network (dSMN). Compared with the nonperiodontitis (NP) group or the mild-periodontitis group, the analysis of internetwork FC showed increased FC between the auditory network and the ventral attention network (VAN), between the aDMN and the salience network (SN), and between the SN and the VAN and decreased FC between the posterior default-mode network and the right frontoparietal network in the moderate-to-severe periodontitis group. Additionally, internetwork FC between the dSMN and the VAN was also increased in the moderate-to-severe periodontitis group compared to the NP group. The altered intra- and internetwork FC were significantly correlated with the periodontal clinical index. Our results confirmed that periodontitis was associated with both intra- and internetwork FC changes even in NC. The present study indicates that periodontitis might be a potential risk factor for brain damage and provides a theoretical clue and a new treatment target for the early prevention of Alzheimer disease. Recent research has proposed that periodontitis is a potential risk factor for Alzheimer disease (AD). However, the relationship between periodontitis and the brain function of middle-aged and elderly individuals with normal cognition (NC) remains unclear. Analyzing the effect of periodontitis on brain function in the NC stage can provide clues to AD development and help achieve early prevention of dementia. The present study aimed to investigate changes in brain functional connectivity (FC) in NC with different severity of periodontitis to determine the effects of periodontitis on brain function. Both changed intranetwork FC and internetwork FC were found in the moderate-to-severe periodontitis group, and periodontitis was associated with brain network function impairment in NC. The present study indicates that periodontitis might be a potential risk factor for brain damage even in NC stage, and provides a theoretical clue and a new treatment target for the early prevention of AD.

Push-pull effects of basal ganglia network in Parkinson’s disease inferred by functional MRI

Deep brain stimulation (DBS) can ameliorate motor symptoms in Parkinson’s disease (PD), but its mechanism remains unclear. This work constructs a multi-scale brain model using the fMRI data from 27 PD patients with subthalamic DBS and 30 healthy controls. The model fits microscopic coupling parameters in the cortico-basal ganglia-thalamic neural loop to match individual connectivity, finding the “push-pull” effect of basal ganglia network. Specifically, increased GABAergic projection into the thalamus from basal ganglia worsens rigidity, while reduced GABAergic projection within the cortex exacerbates bradykinesia, suggesting that the dopamine deficiency induces the chain coupling variations to “push” the network to an abnormal state. Conversely, DBS can alleviate rigidity by enhancing GABAergic projections within the basal ganglia, and improve bradykinesia by reducing cortical projections to basal ganglia, exhibiting that DBS “pulls” the network to a healthy state. This work combines the microscopic and macroscopic neural information for understanding PD and its treatment.

Relaxometry network based on MRI R2⁎ mapping revealing brain iron accumulation patterns in Parkinson's disease

BackgroundExcessive iron accumulation in the brain has been implicated in Parkinson's disease (PD). However, the patterns and probable sequences of iron accumulation across the PD brain remain largely unknown. This study aimed to explore the sequence of iron accumulation across the PD brain using R2* mapping and a relaxometry covariance network (RCN) approach. MethodsR2* quantification maps were obtained from PD patients (n = 34) and healthy controls (n = 25). RCN was configured on R2* maps to identify covariance differences in iron levels between the two groups. Regions with excessive iron accumulation and large covariance changes in PD patients compared to controls were defined as propagators of iron. In the PD group, causal RCN analysis was performed on the R2* maps sequenced according to disease duration to investigate the dynamics of iron accumulations from the propagators. The associations between individual connections of the RCN and clinical information were analyzed in PD patients. ResultsThe left substantia nigra pars reticulata (SNpr), left substantia nigra pars compacta (SNpc), and lobule VII of the vermis (VER7) were identified as primary regions for iron accumulation and propagation (propagator). As the disease duration increased, iron accumulation in these three propagators demonstrated positive causal effects on the bilateral pallidum, bilateral gyrus rectus, right middle frontal gyrus, and medial and anterior orbitofrontal cortex (OFC). Furthermore, individual connections of VER7 with the left gyrus rectus and anterior OFC were positively associated with disease duration. ConclusionsOur results indicate that the aberrant iron accumulation in PD involves several regions, mainly starts from the SN and cerebellum and extends to the pallidum and cortices. These findings provide preliminary information on sequences of iron accumulation in PD, which may advance our understanding of the disease.

Optimal Design of an Off-Grid Solar Energy System Integrated with a Diesel Generator for Urban Areas in Pakistan

The growing energy demand in Pakistan, coupled with the challenges posed by reliance on imported fossil fuels, necessitates the exploration of alternative energy solutions. This study presents the design and techno-economic analysis of an off-grid hybrid energy system tailored for a residential neighborhood in Karachi, Pakistan. The system integrates individual solar energy solutions for seven housles, supplemented by a shared diesel generator to ensure a reliable power supply, particularly during load-shedding and grid outages. The study utilizes HOMER Pro software to model and optimize various configurations, taking into account local solar insolation levels and seasonal variability in energy demands. The optimized system includes photovoltaic (PV) panels, battery storage, and a shared diesel generator with individual connections and meters, with each house receiving a customized solution based on its specific energy requirements, ranging from 15 kWh/day to 45 kWh/day. The shared diesel generator is designed to reduce the need for large battery banks, thereby minimizing both capital and operational costs. The results demonstrate a cost-effective solution with a Levelized Cost of Energy (LCOE) of $0.2959/kWh and a Net Present Cost (NPC) of $15,562.55 over a 25-year period. This research highlights the potential for implementing such systems in urban areas of Pakistan, offering a sustainable, reliable, and economically viable alternative to conventional energy sources.

The different impacts of functional network centrality and connectivity on the complexity of brain signals in healthy control and first-episode drug-naïve patients with major depressive disorder.

In recent years, brain signal complexity has gained attention as an indicator of brain well-being and a predictor of disease and dysfunction. Brain entropy quantifies this complexity. Assessment of functional network centrality and connectivity reveals that information communication induces neural signal oscillations in certain brain regions. However, their relationship is uncertain. This work studied brain signal complexity, network centrality, and connectivity in both healthy and depressed individuals. The current work comprised a sample of 124 first-episode drug-naïve patients with major depressive disorder (MDD) and 105 healthy controls (HC). Six functional networks were created for each person using resting-state functional magnetic resonance imaging. For each network, entropy, centrality, and connectivity were computed. Using structural equation modeling, this study examined the associations between brain network entropy, centrality, and connectivity. The findings demonstrated substantial correlations of entropy with both centrality and connectivity in HC and these correlation patterns were disrupted in MDD. Compared to HC, MDD exhibited higher entropy in four networks and demonstrated changes in centralities across all networks. The structural equation modeling showed that network centralities, connectivity, and depression severity had impacts on brain entropy. Nevertheless, no impacts were observed in the opposite directions. This study indicated that the complexity of brain signals was influenced not only by the interactions among different areas of the brain but also by the severity level of depression. These findings enhanced our comprehension of the associations of brain entropy with its influential factors.

White Matter Function and Network Abnormalities in Patients with Diabetic Retinopathy.

This study aims to explore changes in white matter function and network connectivity in individuals with DR. This study included 46 patients with DR and 43 age- and gender-matched healthy control (HC) participants were enrolled in the study. The aim was to investigate inter-group differences in white matter (WM) function and to analyze changes in the WM network among DR patients. Increased degree centrality (DC) values were observed in the middle cerebellar peduncle and genu of the corpus callosum, while higher fractional amplitude of low-frequency fluctuations (fALFF) values were found in the left superior corona radiata, right anterior corona radiata, and right superior longitudinal fasciculus. Conversely, reduced regional homogeneity (ReHo) values were noted in the left posterior thalamic radiation among patients with DR compared to HC, with statistical correction applied The SVM classification accuracy for distinguishing between DR and HC patients based on WM measures indicated values of 81.52%, 80.43%, and 89.13% for DC, fALFF, and ReHo, respectively, with respective area under the curve (AUC) values of 0.87, 0.85, and 0.93. Furthermore, alterations were detected within specific brain regions including the body of corpus callosum (BCC), splenium of corpus callosum (SCC), genu of corpus callosum (GCC), left posterior thalamic radiation (PTR), right anterior corona radiata (ACR), and right posterior corona radiata (PCR) in the DR group compared to HCs, with an intra-network decrease in connectivity. Interestingly, the left superior longitudinal fasciculus (SLF) within the DR group exhibited an intra-network increase compared to the HC group. DR exhibited abnormal white matter functional alterations, particularly affecting the fiber pathways linking the visual network to the sensory-motor network.

Individual-level metabolic connectivity from dynamic [18F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard.

This study evaluates the potential of within-individual Metabolic Connectivity (wi-MC), from dynamic [18F]FDG PET data, based on the Euclidean Similarity method. This approach leverages the biological information of the tracer's full temporal dynamics, enabling the direct extraction of individual metabolic connectomes. Specifically, the proposed framework, applied to glioma pathology, seeks to assess sensitivity to metabolic dysfunctions in the whole brain, while simultaneously providing further insights into the pathophysiological mechanisms regulating glioma progression. We designed an index (Distance from Healthy Group, DfHG) based on the alteration of wi-MC in each patient (n = 44) compared to a healthy reference (from 57 healthy controls), to individually quantify metabolic connectivity abnormalities, resulting in an Impairment Map highlighting significantly compromised areas. We then assessed whether our measure of metabolic network alteration is associated with well-established markers of disease severity (tumor grade and volume, with and without edema). Subsequently, we investigated disruptions in wi-MC homotopic connectivity, assessing both affected and seemingly healthy tissue to deepen the pathology's impact on neural communication. Finally, we compared network impairments with local metabolic alterations determined from SUVR, a validated diagnostic tool in clinical practice. Our framework revealed how gliomas cause extensive alterations in the topography of brain networks, even in structurally unaffected regions outside the lesion area, with a significant reduction in connectivity between contralateral homologous regions. High-grade gliomas have a stronger impact on brain networks, and edema plays a mediating role in global metabolic alterations. As compared to the conventional SUVR-based analysis, our approach offers a more holistic view of the disease burden in individual patients, providing interesting additional insights into glioma-related alterations. Considering our results, individual PET connectivity estimates could hold significant clinical value, potentially allowing the identification of new prognostic factors and personalized treatment in gliomas or other focal pathologies.

Materializing global academic mobility through the eyes of program coordinators: Comparative insights from a Romanian-U.S. institutional Erasmus+ agreement

Erasmus+, the European Union’s mobility program has been researched extensively (e.g., De Wit, 2020), yet mobility program coordinators at higher education institutions responsible for student, faculty, and staff exchanges remain under-researched. This comparative study showcases a Romanian-U.S. Erasmus + partnership established between Universitatea Babeş-Bolyai in Cluj-Napoca, Romania, and North Dakota State University in Fargo, United States. The study draws on (auto-)ethnographic explorations to investigate two coordinators’ roles, responsibilities, and experiences and explores the infrastructure and qualifications needed to facilitate mobility programs. It concludes that the materialization of mobility agreements relies on a combination of personal and institutional motivations, interests, and goals. High levels of individual initiative, linguistic/cultural knowledge, connections, and consistent involvement on the part of the coordinators facilitating the process are required. We advocate for more institutionalized incentives and recognition for coordinators to continue shaping the future of global mobility in higher education.

Long-term cognitive training enhances fluid cognition and brain connectivity in individuals with MCI

Amnestic mild cognitive impairment (aMCI) is a risk factor for Alzheimer’s disease (AD). Multi-domain cognitive training (CT) may slow cognitive decline and delay AD onset. However, most work involves short interventions, targeting single cognitive domains or lacking active controls. We conducted a single-blind randomized controlled trial to investigate the effect of a 6-month, multi-domain CT on Fluid Cognition, functional connectivity in memory and executive functioning networks (primary outcomes), and white matter microstructural properties (secondary outcome) in aMCI. Sixty participants were randomly assigned to either a multi-domain CT or crossword training (CW) group, and thirty-four participants completed the intervention. We found a significant group-by-time interaction in Fluid Cognition (p = 0.007, F (1,28) = 8.26, Cohen’s d = 0.38, 95% confidence interval [CI]: 2.45–14.4), with 90% of CT patients showing post-intervention improvements (p < 0.01, Cohen’sd = 0.7). The CT group also showed better post-intervention Fluid Cognition than healthy controls (HCs, N = 45, p = 0.045). Functional connectivity analyses showed a significant group-by-time interaction (Cohen’s d ≥ 0.8) in the dorsolateral prefrontal cortex (DLPFC) and inferior parietal cortex (IPC) networks. Specifically, CT displayed post-intervention increases whereas CW displayed decreases in functional connectivity. Moreover, increased connectivity strength between the left DLPFC and medial PFC was associated with improved Fluid Cognition. At a microstructural level, we observed a decline in fiber density (FD) for both groups, but the CT group declined less steeply (1.3 vs. 2%). The slower decline in FD for the CT group in several tracts, including the cingulum-hippocampus tract, was associated with better working memory. Finally, we identified regions in cognitive control and memory networks for which baseline functional connectivity and microstructural properties were associated with changes in Fluid Cognition. Long-term, multi-domain CT improves cognitive functioning and functional connectivity and delays structural brain decline in aMCI (ClinicalTrials.gov number: NCT03883308).

From Third Place: Illustrations and Observations of Connection in the Inner City

From Third Place is a practice-led project that explores the concept of third place in relation to society of the inner city, specifically Auckland CBD, using the traditional cultural anthropological methods of fieldwork and observational drawing to explore third places in Auckland. This project addresses the concept of third place and its role within society and the individual, reflecting on how we connect within our environment. This project is heavily influenced by my previous degree in cultural anthropology and art history. The inquiry is explored through the publication in three chapters of observational illustrations which focuses on the main third places used in everyday life by residents of Auckland CBD; cafes, parks, and pubs. The resulting publication is a series of snapshots of life in the city. The aims of this project is to explore connection of individuals in the city and celebrate the third places that facilitate them.

Comparing the effects of Swiss-ball training and virtual reality training on balance, mobility, and cortical activation in individuals with chronic stroke: study protocol for a multi-center randomized controlled trial

BackgroundBalance and mobility deficits are major concerns in stroke rehabilitation. Virtual reality (VR) training and Swiss-ball training are commonly used approaches to improve balance and mobility. However, no study has compared the efficacy of VR training, Swiss-ball training, and their combination in improving balance and mobility function or investigated cortical activation and connectivity in individuals with stroke.MethodsA prospective, single-blinded, parallel-armed, multi-center randomized controlled trial with factorial design will be conducted. Seventy-six participants aged 30–80 years with stroke will be recruited. Participants will be allocated to one of the four groups: (A) the VR training + Swiss-ball training + conventional physical therapy group; (B) the Swiss-ball training + conventional physical therapy group; (C) the VR training + conventional physical therapy group; or (D) the conventional physical therapy group. All participants will receive 50 min of training per day, 5 times per week, for a total of 4 weeks. The primary outcomes will be balance and mobility measures. Secondary outcomes will include the 10-min walk test, dynamic gait index, and cortical activation. Outcomes will be measured on three occasions: at baseline, after the training, and at the 4-week follow-up.DiscussionThis trial will provide evidence to determine whether there are differences in clinical outcomes and cortical activation following two different types of exercise programs and their combination, and to elucidate the recovery mechanisms of balance and mobility function in individuals with stroke.Trial registrationChinese Clinical Trial Registry reference: www.chictr.org.cn (No. ChiCTR2400082135). Registered on May 24, 2024.

Más allá del partido: empresarios, tecnócratas y agentes políticos en los gabinetes ministeriales dominicanos

Objective/context: This study analyzes the partisan connections of individuals who attain ministerial positions in the Dominican Republic, identifying the influence of political parties, economic elites, and technical profiles in the formation of presidential cabinets. Methodology: Following the typology proposed by Camerlo and Castaldo, we categorize the partisan profiles of the governments of the Dominican Liberation Party (PLD) from 2016 to 2020, and the Modern Revolutionary Party (PRM) from 2020 to 2024. This aims to characterize their internal variation in scenarios of low formal institutionalization that are not captured by traditional dichotomous classifications. Conclusions: The heterogeneity in the influence of party leadership illustrates how Dominican parties diverge from the party government model. The predominance of non-partisan profiles in the core planning ministries, along with the presence of politician- businessmen in the rest of the portfolios, highlights the risk of political capture in this country. Originality: These results call into question the influence of the party as the center of power in dominant presidentialism.

Association of Normative and Non-Normative Brain Networks With Cognitive Function in Patients With Temporal Lobe Epilepsy.

Despite their temporal lobe pathology, a significant subgroup of patients with temporal lobe epilepsy (TLE) is able to maintain normative cognitive functioning. In this study, we identify patients with TLE with intact vs impaired neurocognitive profiles and interrogate for the presence of both normative and highly individual intrinsic connectivity networks (ICNs)-all toward understanding the transition from impaired to intact neurocognitive status. This retrospective cross-sectional study included patients with TLE and matched healthy controls (HCs) from the Thomas Jefferson Comprehensive Epilepsy Center. Functional MRI data were decomposed using independent component analysis to obtain individualized ICNs. In this article, we calculated the degree of match between individualized ICNs and canonical ICNs (e.g., 17 resting-state networks by Yeo et al.) and divided each participant's ICNs into normative or non-normative status based on the degree of match. 100 patients with TLE (mean age 42.0 [SD: 13.7] years, 47 women) and 92 HCs were included in this study. We found that the individualized networks matched to the canonical networks less well in the cognitively impaired (n = 24) compared with the cognitively intact (n = 63) patients with TLE by 2-way mixed-measures analysis of variance (impaired vs intact mean difference [MD] -0.165 [-0.317, -0.013], p = 0.028). The cognitively impaired patients showed significant abnormalities in the profiles of both normative (impaired vs intact MD -0.537 [-0.998, -0.076], p = 0.017, intact vs HC MD -0.221 [-0.536, 0.924], p = 0.220, and impaired vs HC MD -0.759 [-1.200, -0.319], p < 0.001) and non-normative networks (impaired vs intact MD 0.484 [0.030, 0.937], p = 0.033, intact vs HC MD 0.369 [0.059, 0.678], p = 0.014, and impaired vs HC MD 0.853 [0.419, 1.286], p < 0.001) while the intact patients showed abnormalities only in non-normative networks. At the same time, we found that normative networks held a strong, positive association with the neuropsychological measures, with this association negative in non-normative networks. Our data demonstrated that significant cognitive deficits are associated with the status of both canonical and highly individual ICNs, making clear that the transition from intact to impaired cognitive status is not simply the result of disruption to normative brain networks.

Aberrant individual large-scale functional network connectivity and topology in chronic insomnia disorder with and without depression

Insomnia is increasingly prevalent with significant associations with depression. Delineating specific neural circuits for chronic insomnia disorder (CID) with and without depressive symptoms is fundamental to develop precision diagnosis and treatment. In this study, we examine static, dynamic and network topology changes of individual large-scale functional network for CID with (CID-D) and without depression to reveal their specific neural underpinnings. Seventeen individual-specific functional brain networks are obtained using a regularized nonnegative matrix factorization technique. Disorders-shared and -specific differences in static and dynamic large-scale functional network connectivities within or between the cognitive control network, dorsal attention network, visual network, limbic network, and default mode network are found for CID and CID-D. Additionally, CID and CID-D groups showed compromised network topological architecture including reduced small-world properties, clustering coefficients and modularity indicating decreased network efficiency and impaired functional segregation. Moreover, the altered neuroimaging indices show significant associations with clinical manifestations and could serve as effective neuromarkers to distinguish among healthy controls, CID and CID-D. Taken together, these findings provide novel insights into the neural basis of CID and CID-D, which may facilitate developing new diagnostic and therapeutic approaches.

Neural correlates of pain acceptance and the role of the cerebellum: Functional connectivity and anatomical differences in individuals with headaches versus matched controls.

Despite functional connectivity network dysfunction among individuals with headaches, no studies have examined functional connectivity neural correlates and anatomical differences in coping with headaches. This study investigated inter-individual variability in whole-brain functional connectivity and anatomical differences among 37 individuals with primary headaches and 24 age- and gender-matched controls, and neural correlates of psychological flexibility (PF) that was previously found to contribute to headache adjustment. Participants (84% women; M headache severity = 4/10; M age = 43 years) underwent functional magnetic resonance imaging scans and completed questionnaires to examine global and subnetwork brain areas, and their relations with PF components, controlling for age, gender, education, and head-motion. Seed and voxel-based contrast analyses between groups showed atypical functional connectivity of regions involved in pain matrix and core resting-state networks. Pain acceptance was the sole PF component that correlated with the cerebellum (x, y, z: 28, -72, -34, p-false discovery rate <0.001), where individuals with headaches showed higher grey matter density compared to controls. The cerebellum, recently implicated in modulating emotional and cognitive processes, was indicated to process information resembling what individuals do when practicing pain acceptance. Our findings establish for the first time this connection of the cerebellum and its role in pain acceptance. We propose that pain acceptance might be a behavioural biomarker target that could modulate problematic headache perceptions and brain networks abnormalities. This study highlights the potential use of emerging behavioural biomarkers in headache management, such as pain acceptance, and their role in modifying the headache experience. Notably, grey matter reorganization in the cerebellum and other known brain pain networks, could indicate brain networks that can be modified from targeted behavioural interventions to help decode the nociplastic mechanisms that predominates in headaches.

Development of Pre-paid Energy Meter using Internet of Things

This paper presents an implementation of IoT to develop a pre-paid energy meter system using an IoT prototype for monitoring and controlling energy and power consumption. This system is used for the remote or on-site management of energy and power consumption. The system provides a user interface using Global System for Mobile Communications (GSM) so the user can pay the required price for the desired unit. The system provides a web user interface to monitor energy and power consumption, including the number of units and price. The ultimate goal is to promote a sense of optimization of power usage by letting the user pay before they have access to electricity. The system consists of an energy meter box that is connected to individual load connections. This energy meter box consists of a microcontroller on Arduino, a GSM module, a voltage sensor, and current sensor, and an LCD. The LCDs are the energy and power consumed, the price remaining, and the number of units consumed.