Processing Mechanisms Research Articles

Self-construal modulates default mode network connectivity in refugees with PTSD

BackgroundWhile self-construal and posttraumatic stress disorder (PTSD) are independently associated with altered self-referential processes and underlying default mode network (DMN) functioning, no study has examined how self-construal affects DMN connectivity in PTSD. MethodsA final sample of 93 refugee participants (48 with DSM-5 PTSD or sub-syndromal PTSD and 45 matched trauma-exposed controls) completed a 5-minute resting state fMRI scan to enable the observation of connectivity in the DMN and other core networks. A self-construal index was calculated by substracting scores on the collectivistic and individualistic sub-scales of the Self Construal Scale. ResultsIndependent components analysis identified 9 active networks-of-interest, and functional network connectivity was determined. A significant interaction effect between PTSD and self-construal index was observed in the anterior ventromedial DMN, with spatial maps localizing this to the left ventromedial prefrontal cortex (vmPFC), extending to the ventral anterior cingulate cortex. This effect revealed that connectivity in the vMPFC showed greater reductions in those with PTSD with higher levels of collectivistic self-construal. LimitationsThis is an observational study and causality cannot be assumed. The specialized sample of refugees means that the findings may not generalize to other trauma-exposed populations. ConclusionsSuch a finding indicates that self-construal may shape the core neural architecture of PTSD, given that functional disruptions to the vmPFC underpin the core mechanisms of extinction learning, emotion dysregulation and self-referential processing in PTSD. Results have important implications for understanding the universality of neural disturbances in PTSD, and suggest that self-construal could be an important consideration in the assessment and treatment of post-traumatic stress reactions.

Loss and Return of Ticklishness in Functional Neurological Disorder.

People with functional neurological disorder (FND) have abnormalities in sensory processing. Loss of ticklishness has been rarely reported. To describe associated clinical features in people with FND and loss of ticklishness and explore correlations with sensory changes. Retrospective audit of clinical letters of people diagnosed with FND in a tertiary clinic and further cases identified in a general neurology clinic. Thirty-eight patients with loss of ticklishness are described, of which most had other functional sensory symptoms and signs. It was more often localized to one limb, rather than generalized, in those with pain or weakness. Dissociation for the affected body part was often described. Loss of ticklishness in FND is frequently described and offers insights into mechanisms of agency, sensory processing and interoception, which are known to be altered in FND.

Principles of miRNA/miRNA* function in plant MIRNA processing.

MicroRNAs (miRNAs) are essential regulators of gene expression, defined by their unique biogenesis, which requires the precise excision of the small RNA from an imperfect fold-back precursor. Unlike their animal counterparts, plant miRNA precursors exhibit variations in sizes and shapes. Plant MIRNAs can undergo processing in a base-to-loop or loop-to-base direction, with DICER-LIKE1 (DCL1) releasing the miRNA after two cuts (two-step MIRNAs) or more (sequential MIRNAs). In this study, we demonstrate the critical role of the miRNA/miRNA* duplex region in the processing of miRNA precursors. We observed that endogenous MIRNAs frequently experience suboptimal processing in vivo due to mismatches in the miRNA/miRNA* duplex, a key region that fine-tunes miRNA levels. Enhancing the interaction energy of the miRNA/miRNA* duplex in two-step MIRNAs results in a substantial increase in miRNA levels. Conversely, sequential MIRNAs display distinct and specific requirements for the miRNA/miRNA* duplexes along their foldback structure. Our work establishes a connection between the miRNA/miRNA* structure and precursor processing mechanisms. Furthermore, we reveal a link between the biological function of miRNAs and the processing mechanism of their precursors with the evolution of plant miRNA/miRNA* duplex structures.

An ERP study on the late stage of Chinese metaphor processing.

Psycholinguistic models of metaphor processing remain a subject of debate. A prime-probe design using Chinese materials with a specific time span (300 ms) was applied to test the mechanisms of metaphor processing. Conventional and familiarized metaphors were designed as primes, followed by a probe word semantically related to the prime metaphor (MT), a probe word related to the literal meaning of the final word of the prime metaphor (LT), control/unrelated probe word (UT), or non-word. Event-related potentials (ERPs) elicited by the probes were recorded to examine metaphor processing. In N400, results revealed that UT and LT elicited significantly more negative waveforms than MT in both primes. MTs and LTs showed no difference between conventional and familiarized metaphors, suggesting that metaphorical meaning may be accessed directly, regardless of whether conventional or familiarized metaphors. The results were generally compatible with the direct processing model.

Generating Composite Material Maps from Numerical Simulation of Hailstone Impact

Over the lifetime of a wind turbine, the blades receive significant erosion to the leading edge caused by precipitation, leading to large losses in aerodynamic performance and therefore power output. It is therefore prudent to study the mechanics of the erosion process in order to predict and mitigate these losses. Whilst leading edge erosion due to raindrop impact has received much research attention in recent years, very little research has focussed the role of hailstone impact in erosion in wind turbine blades. This paper aims to use a computational simulation model to investigate and characterise the physics of the impact of a hailstone on a flat plate of composite glass fibre material typical of those used in the construction of wind turbine blades. This was achieved by modelling the ice projectile using a Single-Particle Hydrodynamic approach in the software package LS-DYNA. This simulation was used to determine how the impact response in the target plate was affected by various parameters of the impact scenario. Simulations were run using diameters of hailstone between 5 and 20 mm, impact speeds between 80 and 120 ms−1, and at angles of incidence between 90 and 0 degrees. The paper presents these observations in the form of “maps” of the material response at each angle of incidence. It was observed that whilst at low velocities, the material response varies linearly with diameter and velocity and at higher velocities, more complicated behaviour arises due to the interaction between the initial stress wave and the remainder of the impacting projectile.

Research on tap breakage monitoring method for tapping process based on SSAELSTM fusion network

Aiming at the problems of high tap breakage rate during tapping of small-diameter internal threads and the difficulty of feature extraction and fusion in characterising tap breakage, this paper proposes a tap breakage monitoring method based on stack sparse autoencoder long-short-term memory (SSAELSTM) fusion network. Specifically, based on change rule of torque in the tapping process and the analysis of the processing mechanism, the normal label and the breakage label are defined, and 36 groups of feature in the multi-feature domain of the torque signal are extracted, constituting a labelled set of feature. Additionally, a stacked sparse autoencoder network (SSAE) is employed to fuse the feature that serve as inputs to the long short-term memory network (LSTM) for recognition, and the classification errors of LSTM are back-propagated to SSAE to optimize the weights of the LSTM and SSAE networks. Finally, 31 SSAELSTM fusion network models with different structures are constructed, and the final tap breakage monitoring model is determined by comparing the performance indexes. Compared with the features before fusion, the constructed model fusion effectively reduces the amount of data and improves the correlation with the labels. Compared with other network models, it was found that SSAELSTM fusion network is superior to other models in both accuracy and robustness, providing breakage warning for the tapping process, and laying the foundation for subsequent decision-making to avoid tap breakage.

Chatter Stability of Orthogonal Turn-Milling Process in Frequency and Discrete-Time Domains

Abstract As the industry seeks better quality and efficiency, multitasking machine tools are becoming increasingly popular owing to their ability to create complex parts in one setup. Turn-milling, a type of multi-axis machining, combines milling and turning processes to remove material through simultaneous rotations of the cutter and workpiece with the translational feed of the tool. While turn-milling can be advantageous for large parts made of hard-to-cut materials, it also offers challenges in terms of surface form errors and process stability. Because tool eccentricity and workpiece rotation lead to more complexity in process mechanics and dynamics, traditional milling stability models cannot predict the stability of turn-milling processes. This study presents a mathematical model based on process mechanics and dynamics by incorporating the unique characteristics of the orthogonal turn-milling process to avoid self-excited chatter vibrations. A novel approach was employed to model time-varying delays considering the simultaneous rotation of the tool and workpiece. Stability analysis of the system was performed in both the discrete-time and frequency domains. The effects of eccentricity and workpiece speed on stability diagrams were demonstrated and validated through experiments. The results show that the tool eccentricity and workpiece speed alter the engagement geometry and delay in the regeneration mechanism, respectively, leading to significant stability diagram alterations. The proposed approach offers a comprehensive framework for the stability of orthogonal turn-milling and guidance for the selection of process conditions to achieve stable cuts with enhanced productivity.

Effect of Cultural Factors on Speech Perception in Multilingual Contexts in United Kingdom

Purpose: The aim of the study was to analyze the effect of cultural factors on speech perception in multilingual contexts in United Kingdom. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Cultural factors significantly influence speech perception in multilingual contexts in the United Kingdom, impacting individuals' ability to discern phonetic contrasts across languages. Language exposure, cultural identity, and social interactions all contribute to shaping speech perception abilities among multilingual speakers. Considering socio-cultural context is crucial in understanding these phenomena, as cultural norms and values influence auditory processing mechanisms. Unique Contribution to Theory, Practice and Policy: Social identity theory, acculturation theory & communication accommodation theory may be used to anchor future studies on analyze the effect of cultural factors on speech perception in multilingual contexts in United Kingdom. Develop culturally responsive language education programs that recognize and celebrate linguistic diversity. Advocate for policies that promote linguistic and cultural inclusivity in education, workplace, and public services.

Impaired social reward processing in individuals with Internet gaming disorder and its relationship with early face perception

Previous research has found that individuals with Internet gaming disorder (IGD) show different patterns of social function impairments in game-related and real-life social contexts. Impaired social reward processing may be the underlying mechanism according to the Social Motivation Theory. Thus, in this study, event-related potentials were recorded from 24 individuals with IGD and 24 healthy gamers during a social judgement task. We focused on reward positivity (RewP) elicited by game-related and real-life social rewards, and N170 elicited by game avatar faces and real faces. These indicators were used to explore the neurocognitive mechanism of impaired social reward processing in individuals with IGD and its relationship with early face perception. Results showed that (1) the RewP elicited by real-life social reward was considerably reduced in individuals with IGD relative to healthy gamers. (2) The N170 elicited by game avatar faces in individuals with IGD was larger than that elicited by real faces. However, the N170 was not associated with RewP in either group. (3) The score for IGD severity was correlated with the RewP elicited by real-life social reward and the N170 elicited by game avatar face. In conclusion, the present study suggests that the impaired social reward processing in individuals with IGD is mainly manifested in a decreased neural sensitivity to real-life social reward. Meanwhile, the reduced RewP elicited by real-life social reward and the enhanced N170 elicited by game avatar face might serve as potential biomarkers for IGD.

Comparison of the effects and mechanisms of Alismatis Rhizoma with and without salt processing in ameliorating edema due to kidney Yin deficiency based on UPLC-Q-TOF-MS and transcriptomics

Abstract Salt-processed Alismatis Rhizoma (SAR) is extensively used in clinical practice and exhibits a more robust urination-promoting effect than Alismatis Rhizoma (AR). This study employed ultra-performance liquid chromatography–quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and pattern analysis to compare the terpenoids between AR and SAR. Additionally, this study compared the effects of AR and SAR on the gene expression in the kidneys of the rat model of edema (syndrome of kidney Yin deficiency) by transcriptomics to decipher the mechanism of salt processing. Materials and methods AR and SAR were extracted by ultrasonication, and data were collected by UPLC-Q-TOF-MS in the positive ion mode. Transcriptome sequencing was employed to determine the gene expression levels of the rat model treated with AR and SAR, and the differentially expressed genes (DEGs) were obtained. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment was performed for the DEGs. The protein-protein interaction (PPI) network was built, on the basis of which the core targets were screened out. Finally, real-time quantitative polymerase chain reaction (RT-PCR) was conducted to verify the core targets. Results A total of 63 terpenoids were detected in AR and SAR, and salt processing had a significant effect on the content of terpenoids. AR and SAR mainly participated in the regulation of inflammation and immune responses, and SAR regulated more DEGs than AR. Additionally, SAR exerted more extensive regulatory effects on the targets than AR. Conclusion Salt processing mainly changes the content of chemical compounds in AR, which may indirectly optimize the proportion of the main compounds to enhance the therapeutic effect while reducing the toxicity. AR and SAR mainly ameliorate the edema due to kidney Yin deficiency by reducing inflammation and improving immunity. Finally, SAR regulates more genes and signaling pathways and exerts more extensive regulatory effects than AR.

Material basis of kidney Yang deficiency rats before and after salt processing of Dipsacus asper based on spectrum-effect relationship

This paper aims to study the spectrum-effect relationship between the fingerprints before and after salt processing of Dipsacus asper and the efficacy of warming and tonifying kidney Yang and find the main active components against kidney Yang deficiency before and after salt processing of D. asper, so as to provide the basis for clarifying the effect of salt processing on kidney Yang deficiency. The HPLC fingerprint before and after salt processing of D. asper was established by the HPLC-DAD. 15 common peaks were obtained, and 11 components were identified. The content changes of various components in rat serum were detected, and the difference in efficacy before and after salt processing was compared. The results of pharmacological experiments showed that salt processing of D. asper could enhance the kidney index. At the same dose, there was a significant difference between the raw D. asper and D. asper after salt processing groups. Compared with the model group, the contents of ACTH, cAMP, CORT, E_2, GH, Na~+-K~+-ATPase, T, and T4 in the serum of rats in the administration group increased to a certain extent, and the contents of cGMP and TNF-α decreased to a certain extent. Among them, there were significant differences in the above indexes in the serum of rats in the high-dose group of raw D. asper, middle-dose group of D. asper after salt processing, high-dose group of D. asper after salt processing, and the positive drug group. The overall results showed that D. asper after salt processing was more effective than raw D. asper in preventing kidney yang deficiency. The efficacy of D. asper was evaluated by grey correlation analysis, entropy method, and Pearson correlation analysis, and the components of D. asper after salt processing against kidney yang deficiency were screened out. According to the results of correlation degree ranking, the components with increased ranking before and after salt processing of D. asper were loganin, chlorogenic acid, dipsacoside A, asperosaponin Ⅵ, caffeic acid, and isochlorogenic acid B. It was preliminarily speculated that these compounds may be the potential pharmacodynamic components for the treatment of kidney yang deficiency before and after salt processing of D. asper. The changing components before and after the salt processing of D. asper were determined, which proved that D. asper after salt processing was superior to D. asper in the treatment of kidney yang deficiency. The spectrum-effect relationship between the efficacy of D. asper before and after salt processing and the treatment of kidney yang deficiency was established, which laid a foundation for the subsequent study on the pharmacodynamic components and molecular mechanism of salt processing of D. asper.

Magnesium‐based nanocomposites developed through multi‐pass friction stir processing and strengthening mechanisms exploration

AbstractIn the current experimental work, using secondary phase hard nano titanium carbide (TiC) particles as reinforcement, two different magnesium metal matrices i. e., AZ31B/TiC and AZ61 A/TiC composite materials were synthesized by friction stir processing. Using the traditional testing approach for the developed materials, the simultaneous gain in metallurgical, mechanical, electrical, and tribological characteristics compared to the base substrate was examined. The microstructure study results for AZ31B/TiC and AZ61 A/TiC composites showed a uniform distribution of reinforced particles as well as an evolution in grain size, from 82 μm to 4.2 μm and from 74 μm to 3.7 μm, respectively, which consequently contribute in a significant gain in the microhardness of both composites i. e., around 2.2 times and 2.67 times respectively, greater than the base metal. When compared to monolithic alloys, the synthesized AZ31B/TiC and AZ61 A/TiC composites showed improvements in the areas of tensile strength, compressive strength, and coefficient of friction up to 1.81 times, and 1.64 times, 1.74 times and 1.58 times, and 57.92 % and 58.47 %, respectively. Furthermore, these improvements in characteristics also increase the final strengthening of the nanocomposite and reduce electrical conductivity.

The Affective Bias Test and Reward Learning Assay: Neuropsychological Models for Depression Research and Investigating Antidepressant Treatments in Rodents.

The Affective Bias Test (ABT) quantifies acute changes in affective state based on the affective biases they generate in an associative reward learning task. The Reward Learning Assay (RLA) provides a control assay for the ABT and reward-induced biases generated in this model are sensitive to changes in core affective state. Both tasks involve training animals to associate a specific digging substrate with a food reward. Animals learn to discriminate between two digging substrates placed in ceramic bowls, one rewarded and one unrewarded. In the ABT, the animal learns two independent substrate-reward associations with a fixed reward value following either an affective state or drug manipulation, or under control conditions. Affective biases generated are quantified in a choice test where the animals exhibit a bias (make more choices) for one of the substrates which is specifically related to affective state at the time of learning. The ABT is used to investigate biases generated during learning as well as modulation of biases associated with past experiences. The RLA follows a similar protocol, but the animal remains in the same affective state throughout and a reward-induced bias is generated by pairing one substrate with a higher value reward. The RLA provides a control to determine if drug treatments affect memory retrieval more generally. Studies in depression models and following environmental enrichment suggest that reward-induced biases are sensitive to core changes in affective state. Each task offers different insights into affective processing mechanisms and may help improve the translational validity of animal studies and benefit pre-clinical drug development. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Bowl digging and discrimination training Basic Protocol 2: The reward learning assay Basic Protocol 3: The affective bias test - new learning Basic Protocol 4: The affective bias test - modulation of affective biases associated with past experiences.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events, causing surveillance and energy loss. This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters. Initially, the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes. Subsequently, it delves into communication and data processing mechanisms, specifically focusing on central data processing (CDP), communication routers (CRs), and phasor measurement units (PMUs), to re-establish an equipment recovery model based on these data transmission methodologies. Furthermore, it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution. The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system. The findings suggest that the proposed branch- and-bound algorithm significantly augments the observational capabilities of a power system with limited resources, thereby bolstering its stability and emergency response mechanisms.

Biomimic and bioinspired soft neuromorphic tactile sensory system

The progress in flexible and neuromorphic electronics technologies has facilitated the development of artificial perception systems. By closely emulating biological functions, these systems are at the forefront of revolutionizing intelligent robotics and refining the dynamics of human–machine interactions. Among these, tactile sensory neuromorphic technologies stand out for their ability to replicate the intricate architecture and processing mechanisms of the brain. This replication not only facilitates remarkable computational efficiency but also equips devices with efficient real-time data-processing capability, which is a cornerstone in artificial intelligence evolution and human–machine interface enhancement. Herein, we highlight recent advancements in neuromorphic systems designed to mimic the functionalities of the human tactile sensory system, a critical component of somatosensory functions. After discussing the tactile sensors which biomimic the mechanoreceptors, insights are provided to integrate artificial synapses and neural networks for advanced information recognition emphasizing the efficiency and sophistication of integrated system. It showcases the evolution of tactile recognition biomimicry, extending beyond replicating the physical properties of human skin to biomimicking tactile sensations and efferent/afferent nerve functions. These developments demonstrate significant potential for creating sensitive, adaptive, plastic, and memory-capable devices for human-centric applications. Moreover, this review addresses the impact of skin-related diseases on tactile perception and the research toward developing artificial skin to mimic sensory and motor functions, aiming to restore tactile reception for perceptual challenged individuals. It concludes with an overview of state-of-the-art biomimetic artificial tactile systems based on the manufacturing–structure–property–performance relationships, from devices mimicking mechanoreceptor functions to integrated systems, underscoring the promising future of artificial tactile sensing and neuromorphic device innovation.

The differential impact of face distractors on visual working memory across encoding and delay stages

External distractions often occur when information must be retained in visual working memory (VWM)—a crucial element in cognitive processing and everyday activities. However, the distraction effects can differ if they occur during the encoding rather than the delay stages. Previous research on these effects used simple stimuli (e.g., color and orientation) rather than considering distractions caused by real-world stimuli on VWM. In the present study, participants performed a facial VWM task under different distraction conditions across the encoding and delay stages to elucidate the mechanisms of distraction resistance in the context of complex real-world stimuli. VWM performance was significantly impaired by delay-stage but not encoding-stage distractors (Experiment 1). In addition, the delay distraction effect arose primarily due to the absence of distractor process at the encoding stage rather than the presence of a distractor during the delay stage (Experiment 2). Finally, the impairment in the delay-distraction condition was not due to the abrupt appearance of distractors (Experiment 3). Taken together, these findings indicate that the processing mechanisms previously established for resisting distractions in VWM using simple stimuli can be extended to more complex real-world stimuli, such as faces.

Predicting Attack Paths from Application Security Vulnerabilities Using a Multi-Layer Perceptron

This paper is in the series of continuing research and proposes an approach to predicting possible attack paths from application security vulnerability-based attack trees. The attack trees are formed by stringing together weaknesses discovered in an application code and a group of applications within a domain. The Common Weakness Enumeration (CWE) and Common Vulnerabilities and Exposures (CVE) linked together as a string of vulnerabilities in the attack trees can be visualized as pathways for attacks. These pathways become potential attacks that can spread vertically and horizontally leading to a multi-path attack that can involve multiple software applications. With more data, and huge number of vulnerabilities, it will become impossible to identify all attack paths unless a full-scale implementation of an autonomous processing mechanism is in place. Machine Learning (ML) and Deep Learning (DL) techniques have been adopted in the cybersecurity space for decades, however all the studies have been around networks, endpoints, and device monitoring. This paper focuses on application security and building on earlier work cited, the use of a vulnerability map that uses attack vectors in a Deep Learning (DL) method implementing a Multi-Layer Perceptron (MLP) forms the basis for developing a predictive model that relates a set of linked vulnerabilities to an attack path. The results are encouraging, and this approach will help in identifying successful or failed attack paths involving multiple applications, isolated or grouped, and will help focus on the right applications and the vulnerabilities associated as priority for remediation.

ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding

An Electroencephalography (EEG) dataset utilizing rich text stimuli can advance the understanding of how the brain encodes semantic information and contribute to semantic decoding in brain-computer interface (BCI). Addressing the scarcity of EEG datasets featuring Chinese linguistic stimuli, we present the ChineseEEG dataset, a high-density EEG dataset complemented by simultaneous eye-tracking recordings. This dataset was compiled while 10 participants silently read approximately 13 hours of Chinese text from two well-known novels. This dataset provides long-duration EEG recordings, along with pre-processed EEG sensor-level data and semantic embeddings of reading materials extracted by a pre-trained natural language processing (NLP) model. As a pilot EEG dataset derived from natural Chinese linguistic stimuli, ChineseEEG can significantly support research across neuroscience, NLP, and linguistics. It establishes a benchmark dataset for Chinese semantic decoding, aids in the development of BCIs, and facilitates the exploration of alignment between large language models and human cognitive processes. It can also aid research into the brain’s mechanisms of language processing within the context of the Chinese natural language.

Decentralization of the health system - experiences from Pakistan, Portugal and Brazil.

Decentralization of a health system is a complex and multidimensional phenomenon that demands thorough investigation of its process logistics, predisposing factors and implementation mechanisms, within the broader socio-political environment of each nation. Despite its wide adoption across both high-income countries (HICs) and low-and-middle-income countries (LMICs), empirical evidence of whether decentralization actually translates into improved health system performance remains inconclusive and controversial. This paper aims to provide a comprehensive description of the decentralization processes in three countries at different stages of their decentralization strategies - Pakistan, Brazil and Portugal. This study employed a systematic analysis of peer-reviewed academic journals, official government reports, policy documents and publications from international organizations related to health system decentralization. A comprehensive search was conducted using reputable databases such as PubMed, Google Scholar, the WHO repository and other relevant databases, covering the period up to the knowledge cutoff date in June 2023. Information was systematically extracted and organized into the determinants, process mechanics and challenges encountered during the planning, implementation and post-decentralization phases. Although decentralization reforms have achieved some success, challenges persist in their implementation. Comparing all three countries, it was evident that all three have prioritized health in their decentralization reforms and aimed to enhance local decision-making power. Brazil has made significant progress in implementing decentralization reforms, while Portugal and Pakistan are still in the process. Pakistan has faced significant implementation challenges, including capacity-building, resource allocation, resistance to change and inequity in access to care. Brazil and Portugal have also faced challenges, but to a lesser extent. The extent, progress and challenges in the decentralization processes vary among the three countries, each requiring ongoing evaluation and improvement to achieve the desired outcomes. Notable differences exist in the extent of decentralization, the challenges faced during implementation and inequality in access to care between the three countries. It is important for Portugal, Brazil and Pakistan to address these through reinforcing implementation strategies, tackling inequalities in access to care and enhancing monitoring and evaluation mechanism. Additionally, fostering knowledge sharing among these different countries will be instrumental in facilitating mutual learning.

Organization of corticocortical and thalamocortical top-down inputs in the primary visual cortex.

Unified visual perception requires integration of bottom-up and top-down inputs in the primary visual cortex (V1), yet the organization of top-down inputs in V1 remains unclear. Here, we used optogenetics-assisted circuit mapping to identify how multiple top-down inputs from higher-order cortical and thalamic areas engage V1 excitatory and inhibitory neurons. Top-down inputs overlap in superficial layers yet segregate in deep layers. Inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) converge on L6 Pyrs, whereas ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) inputs are processed in parallel in Pyr-type-specific subnetworks (Pyr←ORBvl and Pyr←LP) and drive mutual inhibition between them via local interneurons. Our study deepens understanding of the top-down modulation mechanisms of visual processing and establishes that V2M and ACA inputs in L6 employ integrated processing distinct from the parallel processing of LP and ORBvl inputs in L5.