Process Dynamics Research Articles

A U-shaped relationship between chronic academic stress and the dynamics of reward processing

Despite the potential link between stress-induced reward dysfunctions and the development of mental problems, limited human research has investigated the specific impacts of chronic stress on the dynamics of reward processing. Here we aimed to investigate the relationship between chronic academic stress and the dynamics of reward processing (i.e., reward anticipation and reward consumption) using event-related potential (ERP) technology. Ninety healthy undergraduates who were preparing for the National Postgraduate Entrance Examination (NPEE) participated in the study and completed a two-door reward task, their chronic stress levels were assessed via the Perceived Stress Scale (PSS). The results showed that a lower magnitude of reward elicited more negative amplitudes of cue-N2 during the anticipatory phase, and reward omission elicited more negative amplitudes of FRN compared to reward delivery especially in high reward conditions during the consummatory phase. More importantly, the PSS score exhibited a U-shaped relationship with cue-N2 amplitudes regardless of reward magnitude during the anticipatory phase; and FRN amplitudes toward reward omission in high reward condition during the consummatory phase. These findings suggest that individuals exposed to either low or high levels of chronic stress, as opposed to moderate stress levels, exhibited a heightened reward anticipation, and an augmented violation of expectations or affective response when faced with relatively more negative outcomes.

The process optimization and exergy efficiency analysis for biogas to renewable hydrogen by chemical looping technology

The study on biogas-Chemical Looping Hydrogen Production (biogas-CLHP) highlights its potential to produce high-purity hydrogen with recycling waste bioenergy. It delves into the gas-solid reaction characteristics and optimizes crucial process parameters for the fixed-bed CLHP system. Movement rate equations for the reaction fronts of Fe2O3-Fe3O4 (Rf1), Fe3O4-FeO (Rf2), and FeO-Fe (Rf3) are formulated, aiding in clarifying CO breakthrough curves. The identified convergence temperatures (Tm) under CO and H2 atmospheres are 916 °C and 907 °C, respectively. Rf1 and Rf2 converged above Tm, which leads to the disappearance of the Fe3O4 region in oxygen carrier (OC) beds. A theoretical model for calculating the reduction solid conversion (Xaver) is established, accurately characterizing Xaver under varying reaction times, H2/CO ratios, and temperatures. By using the Particle Swarm Optimization (PSO) algorithm and thermodynamic analysis, the study determines the optimal length-radius ratio (L/r), reduction temperature (T), and H2/CO ratio (α) for the OC bed as 12.5, 916 °C, and 0.72, respectively, at which a maximum conversion ratio of 43.55 % is achieved. Based on optimal parameters, the results of Aspen simulation reveal energy and exergy efficiencies of 74.9 % and 70.8 %. Generally, this research comprehensively outlines the process dynamics, optimizes key parameters, and evaluates exergy efficiency of the biogas-CLHP system.

Novelty Seeking Differences in Temporal Dynamics for Novelty and Appropriateness Processing of Creative Information: An ERP Investigation

ABSTRACTNovelty seeking has been found to affect creative performance, but its impact on the temporal dynamics of creative information processing remains unclear. Creative information is identified by two key indicators—novelty and appropriateness. To explore the effect of novelty seeking on the temporal processing of novelty and appropriateness, a revised alternative uses task (AUT) was conducted with 29 high novelty‐seeking (HNS) and 31 low novelty‐seeking (LNS) individuals. Event‐related potentials (ERPs) and spontaneous blink rate (EBR) were used to measure temporal dynamics and infer physiological mechanisms. (1) For novelty processing, HNS individuals performed quicker information processing (shorter N1/P2 latency) and had a greater capacity to recognize semantic distance (higher P600 peak amplitude). (2) For appropriate processing, HNS individuals also had a faster information processing rate (shorter N1/P2 latency). (3) HNS individuals had higher baseline EBR and showed enhancements in cognitive speed based on real‐time EBR. In contrast, the LNS group did not show the same improvement even with increased attention allocation. These findings expand the application of the Novelty Seeking Model (NGM) in creative information processing. Additionally, the results of EBR suggest that dopamine might be the critical physiological mechanism through which novelty‐seeking influences creative information processing.

It’s About Time! Understanding the Dynamic Team Process-Performance Relationship Using Micro- and Macroscale Time Lenses

Although team processes are conceptualized as temporal phenomena, our theoretical understanding of their unfolding over time is underdeveloped, particularly when “zooming in and out” into their dynamics using different temporal lenses. Team processes might unfold differently over extended project cycles (i.e., macroscale time lens) versus over brief events (microscale time lens). Our goal was to better understand temporal changes of three critical higher-order team processes (i.e., transition, action, and interpersonal processes) over both extended periods (i.e., longer project cycles) and brief time spans (i.e., recurring stand-up meetings). Focusing on two agile software teams, we indexed team processes across these two time spans using computer-aided text analysis (CATA) of meeting transcripts. Macroscale time span processes were captured across 10 sprints (30-week project cycle). Microscale time spans were captured with data from brief stand-up meetings (i.e., using 10 equidistant time intervals from 40 meetings). From a macroscale time lens (i.e., project cycle), an increase in action processes in the early project phase was associated with increases in performance. From a microscale time lens, changes in transition and interpersonal processes around mid-meeting phases were associated with differences in performance. Qualitative analyses of meeting midpoints revealed key differences in proactive planning and interpersonal processes. We discuss how our results provide novel insights for team process dynamics in relation to micro- and macroscale time spans.

Role of prosody and word order in identifying focus: evidence from pupillometry

ABSTRACT This study investigated the role of prosody and word order in identifying the focus of sentences in Japanese. Native Japanese speakers listened to sentences with different types of word order (subject–object–verb (SOV) vs. object–subject–verb (OSV)), prosody (whether the first noun phrase is stressed or not) and preceding contexts (object- vs. subject-wh questions), while processing costs were measured using pupillometry. Although syntactically non-basic OSV was more difficult to process than basic SOV, this processing difficulty was considerably reduced when the supportive context (the subject-wh question) required S to be focused. The time–course analysis of pupillometry revealed that the Japanese speakers immediately used prosodic cues to determine the focus of sentences, but the effect of word order cues for focus was delayed until the sentence-final verb was encountered. This study advances our understanding of the temporal dynamics of focus processing and the interplay between syntactic and information structures in sentence comprehension.

Application of non-ionic liquids-based modified dielectrics during electric discharge machining (EDM) of Ti6Al4V alloy to enhance machining efficiency and process optimization

The non-conventional manufacturing technologies are notorious when it comes to productivity and processing time in production-related industries. However, the aerospace and other high-end sectors enjoy another quality matrix of these processes and compromise on the processing time. For instance, the machinability of hard-to-cut materials such as Ti6Al4V aerospace alloy for micro-impressions is challenging and commonly carried out through non-conventional processes. Among these processes, the electric discharge machining (EDM) is famous for machining Ti6Al4V. In the current study, the EDM process is enhanced through modified dielectrics such as kerosene with non-ionic liquids (span 20, 60, and 80) and cryogenically treated tool electrodes (aluminum and graphite), and is compared to the conventional kerosene-based process. A three-phase experimental campaign is deployed to explore parametric effects including modified dielectric conditions (non-ionic liquid type and concentration), tool material, and machine parameter pulse ON:OFF time. A total of 60 experiments (54 modified dielectrics and 6 as baseline) were performed to explore process physics. The statistical analyses show that the unmodified process (kerosene dielectric-based) results in the least favorable results 0.58 mm3/min against cryo-graphite and 1.2 mm3/min against cryo-aluminum electrodes. However, the modified dielectrics outperform and improve process dynamics by altering dielectric conditions through hydrophilic-lipophilic balance. Surface morphological analysis shows significantly shallow craters on the machined surface showing evidence of effective flushing through a modified dielectric (S-20) as compared to a kerosene-based dielectric. A thorough microscopical, statistical, and scanning electron-based analysis is carried out to explain the process and correlate significant improvements.

Quantitative assessment and genomic profiling of Campylobacter dynamics in poultry processing: a case study in the United Arab Emirates integrated abattoir system.

In the United Arab Emirates, no previous research has investigated the dynamics of the foodborne pathogen Campylobacter in broiler abattoir processing. This study conducted in one of the largest poultry producers in the UAE, following each key slaughter stage-defeathering, evisceration, and final chilling-five broiler carcasses were collected from 10 slaughter batches over a year. Additionally, one caecum was obtained from 15 chickens in each slaughter batch to evaluate the flock colonization. In total, 300 samples (150 carcasses and 150 caeca) were collected and enumerated for Campylobacter using standard methods. Campylobacter was pervasive in caecal samples from all slaughter batches, with 86% of carcasses post-defeathering and evisceration stages and 94% post-chilling tested positive for Campylobacter. Campylobacter coli predominates in 55.2% of positive samples, followed by Campylobacter jejuni in 21%, with both species co-existing in 23.8% of the samples. Campylobacter counts in caecal contents ranged from 6.7 to 8.5 log10 CFU/g, decreasing post-defeathering and evisceration to 3.5 log10 CFU/g of neck skin and further to 3.2 log10 CFU/g of neck skin post-evisceration. After chilling, 70% of carcasses exceeded 3 log10 CFU/g of neck skin. Whole-genome sequencing (WGS) of 48 isolates unveiled diverse sequence types and clusters, with isolates sharing the same clusters (less than 20 single nucleotide polymorphisms) between different farms, different flocks within the same farm, as well as in consecutive slaughter batches, indicating cross-contamination. Multiple antimicrobial resistance genes and mutations in gyrA T86I (conferring fluoroquinolone resistance) and an RNA mutation (23S r.2075; conferring macrolide resistance) were widespread, with variations between C. coli and C. jejuni. WGS results revealed that selected virulence genes (pglG, pseD, pseI, flaA, flaB, cdtA, and cdtC) were significantly present in C. jejuni compared to C. coli isolates. This study offers the first insights into Campylobacter dynamics in poultry processing in the UAE. This work provides a base for future research to explore additional contributors to Campylobacter contamination in primary production. In conclusion, effective Campylobacter management demands a comprehensive approach addressing potential contamination sources at every production and processing stage, guided by continued microbiological surveillance and genomic analysis to safeguard public health and food safety.

Analysis of laser beam welding with superimposed 445 and 1070 nm wavelength lasers on copper by in situ synchrotron diagnostics

In laser welding, precision and reproducibility are fundamentally dependent on temporal and spatial processes of energy input. Induced by the dynamics of the melt pool, pressure equilibria in the vapor capillary, and solidification behavior, different weld seam qualities are achieved. To obtain the lowest possible defect frequency, new tailored joining strategies need to be investigated using multibeam and multiwavelength approaches. To improve the quality by influencing the process dynamics, a dual-beam approach is investigated that superimposes a stationary laser beam with a wavelength of 445 nm with a spatially modulated laser beam with a wavelength of 1070 nm. The aim is to utilize ∼10 times higher absorption of a 445 nm diode laser on copper with the high focusability of a 1070 nm fiber laser. In this context, the influence of the relative positions of the two beams to each other on the weld seam quality is investigated, while one of the beams moves either in front, behind, or coaxial to the other beam following the path of a line weld. The main objective is to observe how the laser beams influence each other and how the capillary depth and porosity vary for different parameters. To visualize the process dynamics, the welding experiments on copper are performed at the Deutsches Elektronen-Synchrotron DESY by means of in situ phase contrast videography. Quality-determining weld properties like the distribution of pores or process fluctuations are then extracted automatically from the image sequences by means of a trained neuronal network.

Research on a semi-supervised soft sensor modelling method for complex chemical processes based on INGO-VMD-ESN

Abstract The dynamic and non-linear nature of complex chemical processes often leads to low prediction accuracy of key quality variables by traditional soft sensors, thus affecting the overall system control accuracy and operational efficiency. Therefore, this paper proposes a semi-supervised soft sensor modelling method based on improved the northern goshawk optimization (INGO)-variable mode decomposition (VMD)-echo state network (ESN). Firstly, a new semi-supervised fusion method is proposed to address the problem of model training difficulty due to the scarcity of labelled samples and process dynamics, which reconstructs the sample dataset by fusing labelled and unlabelled samples into more representative new samples, improving the model’s generalization ability. Secondly, for the noise interference present in the reconstructed data, the input data is denoised using the VMD method to improve the quality of data. Then, a soft sensor model is built based on ESN. Additionally, the denoising and prediction performance of VMD and ESN is significantly affected by parameters, therefore the paper utilizes the INGO algorithm to achieve parameter rectification for VMD and ESN. Finally, the method is validated based on actual sulphur recovery data from a refinery. The results demonstrate that the method effectively mitigates the impact of dynamics and nonlinearity in the complex chemical process which enhances prediction accuracy.

Development workflow based on in situ synchrotron investigations to optimize laser processing of copper pins

To design future laser manufacturing processes for welding of copper materials, more and more high-end analysis methods are required. A fundamental process understanding by analyzing cause-and-effect relations of process dynamics using inline in situ diagnostics allows for an improved description of laser material interaction. Strategies for a reliable and robust welding process are derived from the findings. In this study, a four-step advanced methodical approach is presented and discussed. In the first step, a fundamental process description of the geometry of the vapor capillary and the formation of weld defects is developed. Therefore, welds on electrolytic tough pitch copper (Cu-ETP) and CuSn6 are carried out to analyze the temporal and spatial vapor capillary dynamics depending on laser power, welding speed, and focal diameter. This fundamental process understanding is transferred to the welding of copper pins in the form of I-pins. For this purpose, impurities and imperfections were applied to the pin surface to investigate the effects on the process result. As a third step, strategies by means of laser intensity distributions were adapted to compensate for imperfections in the welding process. Finally, a sensor vision system is adapted for ideal welding results. Investigations are based on in situ synchrotron analysis at Petra III, DESY in Hamburg. For the experiments, a TRUMPF TruDisk laser (100/400 μm fiber diameter), a TRUMPF TruFiber 6000P (50/100 μm fiber diameter), and a single-mode fiber laser (14 μm fiber diameter) were used. The focal diameter was adjusted with the optical system depending on the investigation.

Laser‐Induced Transformation of ZIF‐8 into Highly Luminescent N‐Doped Nanocarbons for Flexible Sensors

AbstractMetal–organic frameworks (MOFs) like the zeolitic imidazolate framework (ZIF‐8) have a high surface area, tunable porosity, and robust thermal and chemical stability, making them attractive candidates for various applications. Here, a strategy is shown that spans that functionality and provides strong photoluminescence (PL) emission, unlocking ZIF‐8‐based materials for chemical and temperature sensors based on PL. The approach is based on laser processing that dramatically boosts the PL response of laser‐irradiated ZIF‐8 (LI ZIF‐8), achieving a 70‐fold increase in intensity relative to the pristine material. The PL characteristics of the irradiated material can be easily tuned by varying the laser power and irradiation time with in situ and real‐time spectroscopic analysis providing insights into the process dynamics. It is found that the observed PL enhancement is primarily due to the laser‐induced transformation of ZIF‐8 into nitrogen‐doped nanocarbons and ZnO nanostructures. The versatility of this laser processing approach is leveraged to create flexible electronics by integrating the LI ZIF‐8/nanocarbon architectures into thermoplastic polyurethane (TPU). The multifunctional composite material shows excellent performance as flexible electrodes for human‐body monitoring applications, as well as both temperature and flexure sensors with remarkable mechanical resilience.

Decoding compositional complexity: Identifying composers using a model fusion-based approach with nonlinear signal processing and chaotic dynamics

Music, a universal medium that effortlessly transcends the confines of language and culture, serves as a vessel for the distinctive expression of a composer's ingenuity, particularly palpable through the elaborate symphony of melodies, harmonies, and rhythms. This phenomenon is acutely observable in the realm of Turkish Classical Music, where the identification of individual composers poses a formidable challenge due to a confluence of diverse stylistic expressions and sophisticated techniques. Shaped by centuries of cultural interchanges, this genre is celebrated for its convoluted rhythmic frameworks and deep melodic modes, often exhibiting fractal characteristics that compound the complexity of composer classification based on mere audio signals. In response to these complexities, this study introduces an advanced analytical paradigm that amalgamates Multi-resolution analysis, spectral entropy assessments, and a spectrum of multidimensional chaotic and statistical descriptors. By invoking chaos theory, the research delineates distinct patterns and features inherent to musical compositions, subsequently deploying these discoveries for composer categorization. Employing a model fusion-based strategy, the approach utilizes esteemed base estimators for section-level probabilistic determinations, subsequently amalgamated at the song level through a Long Short-Term Memory (LSTM) neural network model to classify a corpus of 380 compositions from 15 distinct composers. The results of this study not only highlight the efficacy of chaos-based approaches in Musical Information Retrieval but also provide a nuanced understanding of the unique characteristics of Turkish Classical Music, thus advancing the boundaries of how musicological data is scrutinized and conceptualized within scholarly discourse.

Spatiotemporal Neural Network for Sublexical Information Processing: An Intracranial SEEG Study.

Words offer a unique opportunity to separate the processing mechanisms of object subcomponents from those of the whole object, because the phonological or semantic information provided by the word subcomponents (i.e., sublexical information) can conflict with that provided by the whole word (i.e., lexical information). Previous studies have revealed some of the specific brain regions and temporal information involved in sublexical information processing. However, a comprehensive spatiotemporal neural network for sublexical processing remains to be fully elucidated due to the low temporal or spatial resolutions of previous neuroimaging studies. In this study, we recorded stereoelectroencephalography signals with high spatial and temporal resolutions from a large sample of 39 epilepsy patients (both sexes) during a Chinese character oral reading task. We explored the activated brain regions and their connectivity related to three sublexical effects: phonological regularity (whether the whole character's pronunciation aligns with its phonetic radical), phonological consistency (whether characters with the same phonetic radical share the same pronunciation), and semantic transparency (whether the whole character's meaning aligns with its semantic radical). The results revealed that sublexical effects existed in the inferior frontal gyrus, precentral and postcentral gyri, temporal lobe, and middle occipital gyrus. Additionally, connectivity from the middle occipital gyrus to the postcentral gyrus and from postcentral gyrus to the fusiform gyrus was associated with the sublexical effects. These findings provide valuable insights into the spatiotemporal dynamics of sublexical processing and object recognition in the brain.

Interfacial inhomogeneous plastic deformation during rotary friction welding of dissimilar AA2219-SS321 joint combination with AA6061 interlayer

This research investigates the inherent radial non-uniformity within the rotary friction welding process, particularly concerning microstructure attributes like grain size, grain boundaries, misorientation angles, and interlayer presence along the radial axis. SS321-AA2219 rotary friction welding was carried out with and without an AA6061 interlayer. The numerical thermal model suggests increase in temperatures from the center to the periphery, due to non-uniform heat generation. Also, dissimilar material across the interface resulted in an asymmetric temperature profile along axial direction. Plastic deformation on the Aluminum side suggests dynamic recrystallization and grain refinement, whereas pronounced low-angle grain boundary (LAGB) formation near the SS side interface validates dynamic recovery. A radial non-uniformity in microstructure is observed, with metrics such as average grain size, LAGB fraction, and misorientation showing an increase from the center towards the periphery. The insertion of an interlayer alters process dynamics, manifesting in reduced temperatures and heightened forces, resulting in a more consolidated joint by enhancing the strength by 31 %. Interdiffusion of elements across the interface formed Fe-Al intermetallic compounds (IMC) confirmed with X ray diffraction. Fractography analysis elucidates the presence of rubbing marks and facet surfaces in interlayer-less joints, while joints with interlayer display sticking and dimples.

Seasonal natural organic matter removal and implications for disinfection by-product formation at the Koka water treatment plant: Upper Awash, Ethiopia

ABSTRACT This study evaluated the seasonal performance of the Koka water treatment plant in removing natural organic matter (NOM) and the implications for disinfection by-product (DBP) formation potential. Raw and treated water samples were collected during the dry and wet seasons and analyzed using physicochemical parameters and fluorescence spectroscopy. The results revealed significant seasonal variations in raw water (RW) quality, with higher turbidity, pH, temperature, conductivity, total organic carbon (TOC), dissolved organic carbon (DOC), and UV254 absorbance during both seasons and across treatment processes. The NOM removal efficiency of the treatment plant was poor, with mean TOC removal of 46 and 43% and DOC removal of 15.8 and 15.2% during dry and wet seasons, respectively. The sedimentation unit demonstrated negative TOC removal, indicating NOM accumulation likely due to biochemical reactions in the unit. Fluorescence analysis and the correlation between specific ultraviolet absorbance (SUVA) and DBP formation potential suggest a higher risk of DBP formation in chlorinated drinking water. These findings highlight the influence of seasonal variations, RW quality, and the treatment process dynamics on the plant's performance in removing NOM. There is a need to implement adaptable strategies to enhance NOM removal, accounting for seasonal fluctuations in RW quality.

Monitoring battery charging using Node-RED

The need for a smart grid has been spurred by the growth of distributed generation, the aging of the current grid infrastructure, and the desire to alter networks. The development and enhancement of smart grid technology is significantly facilitated by the Internet of Things (IoT) technology. Batteries play a crucial role in the energy storage of electrical systems, including smart microgrids and electric vehicles. To enhance performance and prolong battery life, a Battery Monitoring System (BMS) is required to manage the energy storage process dynamics within the battery. Battery life prediction contributes to the consistent and efficient operation of battery-powered devices. This research presents battery charging monitoring using Nodered. Apart from that, the battery charging feature uses a cut-off concept. The cut off on the battery is to prevent the battery from over-discharging which can damage the battery and shorten its lifespan. This research carried out validation using 3 case studies on battery charging. Validation of measurements uses a comparison between the INA 219 sensor and a multimeter. From experiments, current testing from 3 case studies, it was found that the average difference in current sensor error was 0.19%.

Inclusivity in Practice: Patchworks of Inclusion at Multiple Tracks in the Colombian Peace Process

ABSTRACT This article investigates the inclusion/multi-track nexus in the Colombian peace process. It theorizes inclusion in terms of design principles and process dynamics, analysing how they are enacted at track 1, track 3, and at the ‘intertrack’ level. Through semi-structured interviews with negotiators from elite talks, Colombia’s national dialogue of 2019, and grassroots dialogues the article shows how the inclusion/multi-track nexus plays out in practice, spelling out challenges of inclusion on different tracks. It shows how active participation and space for contestation is challenging and messy to implement, not least in contexts of power asymmetry, and yet visible in several contexts.

Application of methods for the chemical and radiometric monitoring of liquid radioactive waste processing

ABSTRACT The processing and control of liquid radioactive waste (LRW) in nuclear power plants (NPP) are critical aspects of nuclear energy management. This study details the principles of the methods and the measuring instruments used for control, and highlights the features and advantages of chemical and radiometric control in radioactive waste processing. The purpose is to systematize and analyze the results and methods used for chemical and radiometric monitoring, treatment technologies, and adherence to regulatory standards. The paper presents findings from an operating NPP with water–water energy reactor power units, showcasing the novelty of systematizing monitoring methods at each stage of LRW processing and ensuring compliance with regulatory standards. Moreover, the chemical and radiometric indicators in the LRW were analysed, which provides insight into the dynamics of waste processing and classification. In addition, the application of Pearson correlation analysis allowed us to identify the relationships between chemical and radiometric indicators in the LRW, which provides valuable information for waste management practices. The selection of appropriate chemical and radiometric methods is crucial given the complexity of LRW characteristics, making this study relevant for enhancing LRW monitoring and management practices.

Event-related potentials and behavioral correlates of emotional recognition memory in late pregnancy.

Research on cognitive and emotional functions during pregnancy challenges the prevalent perception of cognitive decline in pregnant women. This study investigates the behavioral and neural dynamics of cognitive-affective processing in third-trimester pregnant women, comparing them with non-pregnant controls. Using a 64-channel EEG-ERP system, we recorded brain activity as participants engaged in an emotional word recognition task. This task involved initially viewing a sequence of emotional and neutral words, followed by a recognition test where participants identified each word as 'new' or 'previously seen'. Contrary to widespread beliefs about diminished recognition ability during late pregnancy, our results revealed no significant differences in error rates between groups. However, pregnant participants demonstrated slower reaction times. In terms of neural responses, pregnant women exhibited increased amplitudes in the N1, P2, and N400 ERP components, suggesting that they may require additional brain resources compared with non-pregnant individuals to process perceptual information. A significant interaction was observed between pregnancy status and the emotional valence of stimuli. Pregnant women showed heightened N1 and N400 responses to negative words, indicating increased sensitivity to stimuli potentially representing threat. This enhanced response was not observed for positive or neutral words. Furthermore, there was an amplified N1 response to 'new' words, but not to 'old' words. These findings suggest that late pregnancy is characterized by heightened responsiveness to new and particularly negative stimuli, potentially leading to a more cautious behavioral approach. Heightened vigilance and sensitivity could offer evolutionary advantages, optimizing fetal development and enhancing maternal well-being.

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches—scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent, χ = 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally, χ is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores χ = 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies χ = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common ‘crackling noise’ approach fails to determine χ under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.