Behavioral Events Research Articles

Multiscale Granger dependencies in the precipitation network of the island of Sicily

The island of Sicily has been displaying unusual rainfall behavior and unexpected extreme precipitation events in recent decades. In this study, we investigate the Granger causal (GC) dependencies in the network of precipitation measurement sites of Sicily at different timescales (every 10 min, 1 h, 6 h, 12 h, and 24 h). We study, across seasons and years, different parameters that characterize the GC dependencies: the total in/out-degree of nodes, the total in/out strength of nodes, the total number of links in the network, the number of eastward/westward links, the strength of eastward/westward links, and the maximum strength of links. We then investigate GC statistic intensities, focusing on the temporal evolution of maximum values over multiple timescales. Our study of precipitation patterns in Sicily indicates that, since 2013, the southern regions near Mount Etna (Catania, Siracusa, and Ragusa) have been increasingly affected, while the western areas (Trapani, Palermo, and Agrigento) have been the most affected. Granger causality networks reveal scale-invariant dependencies, with stronger and sparser connections at timescales that extend beyond 6 h, with a notable westward flow of predictive information. These patterns, which are consistent across seasons, suggest localized perturbation fronts, with stronger links indicating a more significant influence on westward predictions. This study highlights shifts in Sicily’s water cycle that call for adaptive management strategies in the face of the increasing frequency of extreme events.

Ship Anomalous Behavior Detection Based on BPEF Mining and Text Similarity

Maritime behavior detection is vital for maritime surveillance and management, ensuring safe ship navigation, normal port operations, marine environmental protection, and the prevention of illegal activities on water. Current methods for detecting anomalous vessel behaviors primarily rely on single time series data or feature point analysis, which struggle to capture the relationships between vessel behaviors, limiting anomaly identification accuracy. To address this challenge, we proposed a novel vessel anomaly detection framework, which is called the BPEF-TSD framework. It integrates a ship behavior pattern recognition algorithm, Smith–Waterman, and text similarity measurement methods. Specifically, we first introduced the BPEF mining framework to extract vessel behavior events from AIS data, then generated complete vessel behavior sequence chains through temporal combinations. Simultaneously, we employed the Smith–Waterman algorithm to achieve local alignment between the test vessel and known anomalous vessel behavior sequences. Finally, we evaluated the overall similarity between behavior chains based on the text similarity measure strategy, with vessels exceeding a predefined threshold being flagged as anomalous. The results demonstrate that the BPEF-TSD framework achieves over 90% accuracy in detecting abnormal trajectories in the waters of Xiamen Port, outperforming alternative methods such as LSTM, iForest, and HDBSCAN. This study contributes valuable insights for enhancing maritime safety and advancing intelligent supervision while introducing a novel research perspective on detecting anomalous vessel behavior through maritime big data mining.

Extended Pedestrian Evacuation Model Considering Multiple Evacuation Behaviors

A variety of behaviors can exist in pedestrian evacuation, altruistic, competitive, indifferent, and so forth. Understanding the psychological state of pedestrians and the various evacuation behaviors that arise is important because it plays a critical role in understanding the entire evacuation process. In this paper, an extended cellular automata model is developed to study the different behaviors of pedestrians in evacuation. Pedestrians are classified by psychological and physical heterogeneity, including helpful pedestrians, aggressive pedestrians, apathetic pedestrians, and vulnerable pedestrians. In this model, pedestrians are affected by static fields, dynamic fields, helper fields, and attack fields. In addition, the pedestrian view is affected by the density and position of movement of surrounding pedestrians. And, pedestrian movement, small group movement, helping behavior, aggressive behavior, and apathetic behavior are also considered simultaneously. Numerical simulations were conducted to discuss the pedestrian evacuation problem under multiple behaviors, and the effects of helping behavior, the number of attackers, attack force, pedestrian density, and apathetic behavior on the evacuation process were analyzed in detail. The results of the study can provide reference and guidance for the development of pedestrian evacuation strategies in the presence of helping, aggressive behavior events, and reducing casualties.

Low-cost physiology and behavioral monitor for intravital imaging in small mammals.

Functional brain imaging experiments in awake animals require meticulous monitoring of animal behavior to screen for spontaneous behavioral events. Although these events occur naturally, they can alter cell signaling and hemodynamic activity in the brain and confound functional brain imaging measurements. We developed a centralized, user-friendly, and stand-alone platform that includes an animal fixation frame, compact peripheral sensors, and a portable data acquisition system. The affordable, integrated platform can benefit imaging experiments by monitoring animal behavior for motion detection and alertness levels as complementary readouts for brain activity measurements. A custom acquisition system was designed using a powerful, inexpensive microcomputer. We customized an accelerometer and miniature camera modules for efficient, real-time monitoring of animal motion detection and pupil diameter. We then tested and validated the platform's performance with optical intrinsic signal imaging and GCaMP fluorescence calcium imaging in functional activation experiments in awake mice. The integrated platform shows promise for detecting spontaneous motion and pupil dilation while imaging. Stimulus-induced pupil dilation was found to initiate earlier than cortical hemodynamics with a slower rise time. Compared with neuronal calcium response, stimulus-induced pupil dilation initiated later with a slower rise time. We developed an integrated platform to monitor animal motion and pupil dynamics. The device can be easily coupled and synchronized with optical brain imaging systems to monitor behavior, alertness, and spontaneous motion for awake animal studies.

A BIBLIOMETRIC OVERVIEW OF COMPETENCY AND CAPABILITY MODELING: RESEARCH CONTRIBUTIONS AND TRENDS (2000–2024)

In almost half a century, competency modeling has become an important movement in Human Resource and talent management. This study aims to identify the characteristics of the research published on competency/capability modeling using bibliometric analysis. To answer the research questions, 367 journal articles were analyzed. The results showed an increasing number of publications in the most recent two decades, and there is a worldwide collaboration in advancing this field while countries such as the United States and Australia are leading. Moreover, there are two competency/capability camps. One camp focuses on individual job performance, while the other focuses on organizational core competencies and capabilities. Capabilities often co-occur with the keywords related to competitive advantage and innovation. Behavioral event interviews and Delphi are among the common methods used to design competency models. Researchers and practitioners can benefit from the findings by gaining insights into the latest trends in this field.

A Menu for Microbes: Unraveling Appetite Regulation and Weight Dynamics Through the Microbiota-Brain Connection Across the Lifespan.

Appetite, as the internal drive for food intake, is often dysregulated in a broad spectrum of conditions associated with over- and under-nutrition across the lifespan. Appetite regulation is a complex, integrative process comprising psychological and behavioral events, peripheral and metabolic inputs, and central neurotransmitter and metabolic interactions. The microbiota-gut-brain axis has emerged as a critical mediator of multiple physiological processes, including energy metabolism, brain function, and behavior. Therefore, the role of the microbiota-gut-brain axis in appetite and obesity is receiving increased attention. Omics approaches such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics in appetite and weight regulation offer new opportunities for featuring obesity phenotypes. Furthermore, gut microbiota-targeted approaches such as pre- pro- post- and synbiotic, personalized nutrition, and fecal microbiota transplantation are novel avenues for precision treatments. The aim of this narrative review is (1) to provide an overview of the role of the microbiota-gut-brain-axis in appetite regulation across the lifespan and (2) to discuss the potential of omics and gut microbiota-targeted approaches to deepen understanding of appetite regulation and obesity.

Pedals possible: a pilot study of adaptive cycling as a school-based rehabilitation intervention for students with disabilities.

Pediatric therapists in school-based practice can incorporate exercise promotion through adaptive cycling for children with disabilities who experience high levels of sedentary behavior and low levels of moderate to vigorous activity. The impacts of an adaptive cycling pilot program for children with disabilities were investigated through a community-based participatory study. During an eight-week intervention, students had a goal of riding adaptive cycles three times a week for twenty minutes. Using a pre-and post-test design, primary outcomes included individualized goal attainment scaling (GAS) linked to students' individualized education plans (IEP) and the 6-minute cycling test (6MCT) measuring cycling distance. Secondary outcomes included cycling duration over time, assistance levels for pedaling and steering, a "happiness scale", and overall program satisfaction of parents and teachers. To prevent harm, pain behavior was examined using the Faces, Legs, Activity, Cry, Consolability (FLACC). Cycling had a positive impact on students with disabilities. No increased levels of pain behavior or adverse events were reported. Individual GAS T-score means significantly improved to 0.24 and program effectiveness achieved a T-score value of 50.53. The mean distance of 6MCT increased from 728.95 feet to 880.5 feet. Secondary measures also documented significant improvement. Parents and teachers reported high overall satisfaction. Adaptive cycling can incorporate needed physical activity into the school day and also support the achievement of IEP goals, physical activity capacity, and emotional happiness. Scaling adaptive cycling programs for children with disabilities should be considered an excellent opportunity for educational growth, health, and well-being.

Predicting Seizures Episodes and High-Risk Events in Autism Through Adverse Behavioral Patterns.

Individuals with Autism Spectrum Disorder may display interfering behaviors that limit their inclusion in educational and community settings, negatively impacting their quality of life. These behaviors may also signal potential medical conditions or indicate upcoming high-risk behaviors. This study explores behavior patterns that precede high-risk, challenging behaviors or seizures the following day. We analyzed an existing dataset of behavior and seizure data from 331 children with profound ASD over nine years. We developed a deep learning-based algorithm designed to predict the likelihood of aggression, elopement, and self-injurious behavior (SIB) as three high-risk behavioral events, as well as seizure episodes as a high-risk medical event occurring the next day. The proposed model attained accuracies of 78.4%, 80.68%, 85.43%, and 69.95% for predicting the next-day occurrence of aggression, SIB, elopement, and seizure episodes, respectively. The results were proven significant for more than 95% of the population for all high-risk event predictions using permutation-based statistical tests. Our findings emphasize the potential of leveraging historical behavior data for the early detection of high-risk behavioral and medical events, paving the way for behavioral interventions and improved support in both social and educational environments.

Behavioral Signature of Equine Gastric Discomfort? Preliminary Retrospective Clinical Observations.

Gastric ulcer disease and other potentially painful gastric conditions are among the most common afflictions adversely affecting the welfare of domestic equids. A large percentage of affected animals may not display the classic signs of gastric disease, such as unexplained weight loss, poor hair coat, and inappetence until the disease becomes severe. As a clinical service within our equine referral hospital, we routinely evaluate 24-h video recorded samples of horses to assist clinicians in identifying subtle discomfort and potential sources or to scan for infrequent neurologic or cardiac-related behavioral events. Empirically, we have recognized discomfort behaviors that appear to be uniquely associated with gastric disease. These include frequent attention to the cranial abdomen (nuzzling, swatting, nipping, and/or caudal gaze focused on the abdomen caudal to the elbow) and/or deep abdominal stretching, often within the context of eating, drinking, and/or anticipating feeding. To systematically evaluate the reliability of these purported gastric discomfort behaviors, we reviewed 30 recent 24-h video behavior evaluation cases for which (1) the clinical video behavior evaluation had been carried out without knowledge of the history and presenting complaint and (2) direct gastric examination had confirmed gastric disease status at the time. Twenty-four of the thirty cases showed gastric discomfort behavior, and all twenty-four had either gastric ulcers (n = 21) and/or gastric impaction (n = 3). Of the six cases not showing gastric discomfort behaviors, four were free of gastric disease, while two had mild lesions. Comparing horses with and without gastric disease, gastric discomfort behaviors were reported in 24 of the 26 (92%) with gastric ulcers or gastric impaction, compared to none of the four gastric disease-free horses. Although a larger prospectively designed study is needed to confidently estimate the sensitivity and specificity or the associations of behavior with the type or severity of gastric disease, these results confirm our long-held clinical impression of a behavioral signature for gastric discomfort in the horse.

First clinical post-approval, observational study to assess clinical safety and effectiveness of brivaracetam sustained-release formulation in real-life settings of India: BEAM study.

Brivaracetam (BRV) sustained-release (SR) tablets have recently been approved to treat focal seizures in India. SR formulations enhance patient adherence and quality of life (QoL). We assessed safety and effectiveness of BRV-SR for epilepsy management in Indian real-life settings. A post-approval observational study involving 1989 patients receiving BRV-SR from 181 centres were analysed. Primary endpoints are efficacy variables derived from seizure-related changes, and secondary endpoints include responder rate (≥50% reduction in focal-onset seizures [FoS]/focal-to-bilateral tonic-clonic seizures [FBTCS] frequency), usage pattern data, clinician's global impression on efficacy index (CGI-EI) and safety variables. Patients' mean age was 42.33±12.33 years, and 1441 (72.44%) were men. Psychiatric comorbidities included depression (21.97%), sleep disturbance (15.54%), and anxiety (9.60%). The predominant seizure types were FoS (71.44%) and FBTCS (28.56%). BRV-SR 100 mg once-daily was most prescribed dose (57.37%) at baseline and follow-up visits (51.94%). Median seizure frequency decreased from 2 at baseline to 1 at follow-up visit. At follow-up, 72.1% patients were responders, and 63.75% were seizure-free. BRV-SR showed "marked" to "moderate" improvement in 92.99% of patients according to CGI-EI. Subgroup-analysis revealed a positive correlation between BRV-SR use in patients with drug-resistant epilepsy, psychiatric co-morbidities, and behavioural adverse events (AEs) with past anti-seizure medications. AEs were rare, with none reported in 97.39% patients during study period. The BEAM study findings provide first real-world evidence on effectiveness and safety of BRV-SR in Indian real-life settings. Furthermore, BRV-SR is a feasible option for focal epilepsy management with good retention rates and improved QoL.

Effect of Risk-Taking Propensity on Entrepreneurial Intentions among Students Undertaking Entrepreneurial Course in Universities in Meru and Tharaka Nithi Counties

The concept of entrepreneurship has received increasing attention in various countries globally, especially in developing countries which suffer from several problems that hinder economic growth. Entrepreneurship is essential in addressing economic problems, such as unemployment, new wealth creation, stabilizing society, increasing industrial competition and economic development. The main objective of this study was to determine the effect of risk taking propensity on entrepreneurial intentions among students in universities in Meru and Tharaka Nithi counties. This study was conducted among university students since the students had undertaken entrepreneurial training to become future entrepreneurs. Descriptive research was adopted. The target population of this study was 800 students and a sample size of 267 respondents who were in third and fourth years and had undertaken entrepreneurial studies as a unit or major course at the universities. This study was anchored on theory of planned behavior and entrepreneurship event model of entrepreneurship. A questionnaire was used to guide in collecting primary data. Data obtained from this study was interpreted using descriptive statistical methods including tables, mean, median, mode and simple percentiles. Data was analyzed using inferential statistics with help of SPSS. Multiple regression analysis was used to analyze the relationship between variables using confidence level of 95%. The study found a regression coefficient of risk taking propensity was 0.187 and a p-value of 0.000<0.05 hence risk taking propensity had a positive and statistically significant effect on entrepreneurial intentions. It is recommended that Universities should encourage and create an environment that fosters calculated risk taking and confidence among the students to believe in their abilities, identify and take up opportunities available

Parental knowledge and expectations on early manual movements: A note on the possible impacts of social distancing on infant stimulation practices during COVID-19 pandemic

BACKGROUND: Parents' knowledge and perception about motor development and stimulation practices play a pivotal role in infants’ cognitive, social and motor development. Parental involvement is crucial in fostering exploratory behaviors that help infants learn about bodily functions and environmental consequences. Social restrictions imposed by the COVID-19 pandemic may have impacted the care and stimulation practices that parents provided to their infants. AIM: The present study aimed a) to identify the knowledge and expectations the parents have in regard to the development of hands behavior; and b) to verify whether and how parents offered opportunities for developmental tasks in the first 9 months of the COVID-19 pandemic. METHOD: Eighteen parents completed a questionnaire regarding their knowledge and perception of early manual behavior and stimulation practices at two time points: when the infants were 1 to 3 months old, and when their infants were 6 to 9 months old. RESULTS: The results showed that, on average, parents were quite accurate in predicting the age at which reaching and grasping milestone emerge. However, most parents did not believe that infants could identify the contingent relationship between their manual behavior and environmental events before 6 months of age. Despite this, a majority of parents provided their infant with opportunities to engage with objects during the first 3 months after birth. CONCLUSION: Although parents underestimate infants’ autonomy using their hands functionally, the social restrictions implemented during COVID-19 pandemic positively influenced the infant care and stimulation practices among high educated families in Brazil.

Urolithin A Modulates PER2 Degradation via SIRT1 and Enhances the Amplitude of Circadian Clocks in Human Senescent Cells

Background/Objectives: Circadian clocks are endogenous systems that regulate numerous biological, physiological, and behavioral events in living organisms. Aging attenuates the precision and robustness of circadian clocks, leading to prolonged and dampened circadian gene oscillation rhythms and amplitudes. This study investigated the effects of food-derived polyphenols such as ellagic acid and its metabolites (urolithin A, B, and C) on the aging clock at the cellular level using senescent human fibroblast cells, TIG-3 cells. Methods: Lentivirus-infected TIG-3 cells expressing Bmal1-luciferase were used for real-time luciferase monitoring assays. Results: We revealed that urolithins boosted the amplitude of circadian gene oscillations at different potentials; urolithin A (UA) amplified the best. Furthermore, we discovered that UA unstabilizes PER2 protein while stabilizing SIRT1 protein, which provably enhances BMAL1 oscillation. Conclusions: The findings suggest that urolithins, particularly UA, have the potential to modulate the aging clock and may serve as therapeutic nutraceuticals for age-related disorders associated with circadian dysfunction.

Method for Preprocessing Video Data for Training Deep-Learning Models for Identifying Behavioral Events in Bio-Objects

Monitoring moving bio-objects is currently of great interest for both fundamental and practical research. The advent of deep-learning algorithms has made it possible to automate the qualitative and quantitative analysis of the behavior of bio-objects recorded in video format. When processing such data, it is necessary to consider additional factors, such as background noise in the frame, the speed of the bio-object, and the need to reflect information about the previous (past) and subsequent (future) pose of the bio-object in one video frame. The preprocessed dataset must be suitable for verification by experts. This article proposes a method for preprocessing data to identify the behavior of a bio-object, a clear example of which is experiments on laboratory animals with the collection of video data. The method is based on combining information about a behavioral event presented in a sequence of frames with the addition of a native image and subsequent boundary detection using the Sobel filter. The resulting representation of a behavioral event is easily perceived by both human experts and neural networks of various architectures. The article presents the results of training several neural networks on the obtained dataset and proposes an effective neural network architecture (F1-score = 0.95) for identifying discrete events of biological objects’ behavior.

Orchiectomy Decreases Locomotor Activity and Delays the Expression of the Clock Protein PER1 in the Suprachiasmatic Nucleus in Rabbits.

The suprachiasmatic nucleus (SCN) is the master regulator of the circadian system, modulating the daily timing of physiological and behavioral processes in mammals. While SCN synchronization is primarily driven by environmental light signals, sex hormones, particularly androgens, have a crucial role in regulating behavioral and reproductive processes to align with daily or seasonal cycles. SCN cell populations express receptors for sex steroid hormones, contributing to circadian synchronization mechanisms. Specifically, the activation of androgen receptors in the SCN has been shown to modulate clock gene expression and influence circadian rhythms. Rabbits, widely used in experimental research, exhibit unique behavioral patterns, including plasticity in circadian typology and seasonal variations in testosterone secretion. In this study, we explored, in male rabbits, the effect of castration on the daily pattern of locomotor activity and the expression of the clock protein PERIOD 1 (PER1) in the SCN. Our results show that castration significantly reduces daily locomotor activity and PER1 expression in the SCN. Moreover, a 4 h delay in the acrophase of PER1 expression was observed. We conclude that androgens have an important role in SCN synchronization mechanisms, contributing to the organization of physiological and behavioral events in this species.

Predicting main behaviors of beef bulls from accelerometer data: A machine learning framework

Traditional methods to monitor free-range cattle, such as breeding beef bulls, are time-consuming. However, most current remote monitoring technologies operate at high sampling rates, making their use on bulls impractical due to their high battery consumption. Therefore, this study aims to describe and evaluate a machine-learning framework to predict the behaviors of beef bulls from raw accelerometer data at low sampling rates. Collars with 3D-accelerometers were deployed on 33 bulls, recording accelerometer data at 0.5 Hz (22 bulls in 2020 and 2021) or 1.0 Hz (11 bulls in 2023). Videos of bulls in pens, synched with the accelerometer by time, were recorded and analyzed. The behaviors investigated were grazing (GR), resting (RE), ruminating (RU), walking (WA), and in 2023, fighting (FI). Primary labels of activity (AC), corresponding to GR, WA, and FI, and non-activity (NA), corresponding to RE and RU, were assigned. Two datasets were created from data sampled at 1.0 Hz and 0.5 Hz. Then, behavioral events with duration within the inferior 0.05 quantile of the distribution for each behavior were removed, integrated measures of motion were calculated, and segmentation into consecutive 20s time-windows was performed. Afterward, 132 frequency and time-domain features were extracted, and bulls’ ages were added as a physical feature. Two bulls from each year and dataset were segregated to form independent test sets. A leave-one-animal-out cross-validation (LOAO) was applied to Extratree classifiers to select relevant features. The final classifier was built in a hierarchical structure using XGBoost classifiers to make predictions on two levels: (1) distinguishing between AC and NA, and (2) categorizing AC into GR, WA, FI, and NA into RE or RU. This model was evaluated using LOAO and test sets for each dataset, and precision and sensitivity were calculated for each behavior. Matthews Correlation (MCC) and Cohen's Kappa (CK) coefficients were calculated for the overall assessment of the models’ levels. Comparisons of metrics obtained on LOAO and test sets were performed using the Wilcoxon Sum Rank and the Wilcoxon Signed Rank test. The LOAO MCC for 1.0 Hz (1st level=0.98±0.01, 2nd level=0.92±0.02) was higher than 0.5 Hz (1st level=0.83±0.20, 2nd level=0.71±0.20). In 1.0 Hz, all behaviors presented mean precision and sensitivity above 0.7, except the sensitivity of FI (LOAO = 0.47±0.06, test set = 0.63±0.18). In 0.5 Hz, the exception was the sensitivity of WA (LOAO = 0.58±0.28, test set = 0.68±0.06) and the sensitivity of RU in the test set (0.54 ± 0.26). Therefore, the proposed framework can be used to predict the behaviors of beef bulls from accelerometers sampling at 0.5 Hz or 1.0 Hz, although better results are observed at 1.0 Hz. Caution should be exercised for predicting FI at 1.0 Hz and WA at 0.5 Hz.

Behavioral Economic Strategies Increase Adverse Event Reporting in Pediatric Anesthesia.

Identification and reporting of severe adverse events (SAEs) during anesthesia care remains critical in identifying areas of improvement in perioperative patient care. Although many healthcare organizations rely on the self-reporting of SAEs, under-reporting may limit the identification of the true incidence of these events. To circumvent these barriers, many healthcare systems leverage the Electronic Medical Record (EMR) by incorporating an Anesthesia Information Management System (AIMS). We followed the Institute for Healthcare Improvement's Model of Improvement and implemented behavioral economic-based interventions to our perioperative practice including adding a deliberation-promoting "hard stop" that required the anesthesiologists to report the occurrence or absence of a "notable event" prior to closing a patient's encounter in the EMR system. At baseline, 53% of SAEs were self-reported. The interventions resulted in a baseline shift to more than 75% self-reporting, a relative increase of 42%. An increase in reporting of SAEs was achieved with simple interventions including modifications of the EMR which were done with limited financial impact or interruption in the work flow.

Research on Core Competency Elements of Clinical Investigators.

To construct a competency model for clinical investigators involved in the process of new drug development, providing a reference for the training, selection and assessment of clinical investigators. The Behavioral Event Interview (BEI) method was used to interview 12 excellent clinical investigators and 8 clinical investigators of average performance. Each competency characteristic was extracted from the interview text by semantic coding. Total frequency, total score, average score and highest score were calculated for each competency element. Category agreement coefficient, coefficient of reliability and Spearman correlation coefficient were used to assess the consistency of two coders for coding and classification. Independent-samples Mann-Whitney U test was applied to compare the differences in competency elements between the group of excellent clinical investigators and the group of average investigators. The average coefficient of category agreement was 0.671, and the average coefficient of reliability was 0.803. No significant differences were observed between the two groups in the aspect of interview time (P = 0.190) and the interview words (P = 0.184), indicating comparability between the two groups. However, there was a clear performance difference between the excellent and average groups. In addition, we found that the competency model for clinical investigators contained 24 prominent competence elements and 8 benchmark competency elements. Clinical investigator is a medical professional who is involved in a highly research-intensive and practical job, where prominent competency element largely reflects clinical practice skills, innovation and awareness of Good Clinic Practice (GCP). Our results provide a reference for assessing clinical investigators' competencies, encouraging and guiding them to modify their behaviors according to the competency model, and also cultivating clinical investigators so as to improve the competence level of clinical investigators.

Progressively shifting patterns of co-modulation among premotor cortex neurons carry dynamically similar signals during action execution and observation.

Many neurons in the premotor cortex show firing rate modulation whether the subject performs an action or observes another individual performing a similar action. Although such "mirror neurons" have been thought to have highly congruent discharge during execution and observation, many if not most actually show non-congruent activity. Studies of neuronal populations active during both execution and observation have shown that the most prevalent patterns of co-modulation-captured as neural trajectories-pass through subspaces which are shared in part, but in part are visited exclusively during either execution or observation. These studies focused on reaching movements for which low-dimensional neural trajectories exhibit comparatively simple dynamical motifs. But the neural dynamics of hand movements are more complex. We developed a novel approach to examine prevalent patterns of co-modulation during execution and observation of a task that involved reaching, grasping, and manipulation. Rather than following neural trajectories in subspaces that contain their entire time course, we identified time series of instantaneous subspaces, calculated principal angles among them, sampled trajectory segments at the times of selected behavioral events, and projected those segments into the time series of instantaneous subspaces. We found that instantaneous neural subspaces most often remained distinct during execution versus observation. Nevertheless, latent dynamics during execution and observation could be partially aligned with canonical correlation, indicating some similarity of the relationships among neural representations of different movements relative to one another during execution and observation. We also found that during action execution, mirror neurons showed consistent patterns of co-modulation both within and between sessions, but other non-mirror neurons that were modulated only during action execution and not during observation showed considerable variability of co-modulation.

High-grade Endometrial Carcinomas With Solid Basaloid Morphology and Geographic Necrosis Lacking Definitive Pilomatrix-like Features: Clinicopathologic Characteristics Including Aggressive Behavior and Novel Molecular Events.

High-grade endometrioid carcinomas occasionally demonstrate solid basaloid morphology with geographic necrosis (SB-GN). This pattern is among the defining features of pilomatrix-like high-grade endometrioid carcinoma (PiMHEC), a recently proposed tumor type which is additionally characterized by the presence of shadow cells, abnormal beta-catenin/CTNNB1 mutations, strong CDX2 expression, and poor outcomes. Clinicopathologic overlap between PiMHEC and other high-grade endometrial cancers with SB-GN has not been established. We screened 300 endometrial carcinomas on tissue microarray for SB-GN histology and performed a detailed whole-section morphologic review, immunohistochemical analysis, and next-generation sequencing on all cases bearing this pattern. Four (1.3%) demonstrated SB-GN. All 3 with clinical follow-up had extremely aggressive behavior despite being MMR-deficient; in contrast, only 27% of other MMR-deficient high-grade carcinomas recurred. One SB-GN case met most of the previously outlined diagnostic criteria for PiMHEC including abnormal beta-catenin/CTNNB1 (p.S37P variant) and strong CDX2 expression; notably, however, shadow cells were absent. This case also demonstrated a KRAS p.A59T pathogenic variant. The other 3 cases also lacked shadow cells; the 2 with sequencing data bore no CTNNB1 abnormalities but showed likely oncogenic variants involving the pilomatrixoma-associated gene FGFR2. All 3 cases with molecular results also bore somatic Notch pathway (NOTCH1/NOTCH2/NOTCH3) variants. The single case treated with immunotherapy showed complete and sustained response with regression of bone metastases despite abnormal beta-catenin/CTNNB1, which has been associated with immunotherapeutic resistance. These data suggest that the SB-GN pattern may connote a poor prognosis even in the absence of overt pilomatrix-like differentiation, and that novel molecular events may have implications for the treatment of these tumors.