To reduce the arbitrariness in the allocation of rare resources in intensive care units (ICU) in the context of the pandemic, tiebreakers were considered in some COVID-19 triage algorithms. They were also contemplated to facilitate the tragic decisions of healthcare workers when faced with two patients with similar prognosis and only one ICU bed available. Little is known about the public's perspective on tiebreakers.To consolidate the available scientific literature on public consultations, particularly on tiebreakers and their underlying values. Also, to obtain an overview of the key arguments presented by the participating public and to identify potential gaps related to this topic.The steps described by Arksey and O’Malley was the preferred method to our approach. Seven electronic databases were searched from January 2020 to April 2022, using keywords for each database: PubMed, Medline, EMBASE, Web of Science, PsycINFO, EBM reviews, CINAHL complete. We also searched in Google and Google Scholar, and in the references of the articles found. Our analysis was mainly qualitative. A thematic analysis was performed to consider the public’s perspectives on tiebreakers and their underlying values, according to these studies.Of 477 publications found, 20 were selected. They carried out public consultations through various methods: surveys (80%), interviews (20%), deliberative processes (15%) and others (5%) in various countries: Australia, Brazil, Canada, China, France, Germany, India, Iran, Italy, Japan, Korea, Netherlands, Portugal, Spain, Switzerland, Thailand, United Kingdom, and United States. Five themes emerged from our analysis. The public favored the life cycle (50%) and absolute age (45%) as a tiebreaker. Other values considered important were reciprocity, solidarity, equality, instrumental value, patient merit, efficiency, and stewardship. Among the new findings were a preference for patient nationality and those affected by COVID-19.There is a preference for favoring younger patients over older patients when there is a tie between similar patients, with a slight tendency to favor intergenerational equity. Variability was found in the public’s perspectives on tiebreakers and their values. This variability was related to socio-cultural and religious factors. More studies are needed to understand the public's perspective on tiebreakers.The online version contains supplementary material available at 10.1007/s44250-023-00027-9. COVID-19 has caused repercussions of varying magnitude throughout the world. This viral disease with an accelerated epidemiological behavior, was declared a pandemic by the WHO in March 2020, less than 3 months after its appearance in China –9. HealtTriage protocols in a pandemic context have been strategies that have raised ethical issues related to their values and criteria for the allocation of scarce health resources –12. AmonIn the literature, there are reviews of COVID-19 and other pandemic protocols for ICU access. We found systematic reviews on the allocation of health resources during the influenza pandemic and disaster situations, some containing public consultations –16. TherIt is important to note that some protocols for ICU access include both initial clinical criteria and tiebreaker criteria, the latter considered by some to be non-clinical, with underlying values , 23, 24.A systematic review compiled the criteria of some ventilator allocation guidelines developed in the USA for access to adult intensive care in the face of this pandemic. The literature showed that after considering their initial prioritization criteria, if there was a tie between patients, they would consider the younger patients as an initial tiebreaker, in 6 states . In 2 states, they would also consider healthcare workers, who are the most exposed (Colorado and Oklahoma). In 5 states, they would consider the “first-come, first-served” principle as a tiebreaker  . HoweverDuring the influenza pandemic, protocols were also developed to address a shortage of resources, and tie-breaking criteria were included in their structure. Some communities were consulted on these criteria and values, showing a diversity of perspectives , 27–31.For example, a recent systematic review compiled 24 studies of other pandemics between 2004 and 2019 in which various methods of community engagement  were applied to include the public in the evaluation of pandemic planning and its response. Participants' perspectives were also analyzed on these health strategies. They also found diverse and divergent perspectives among community participants and a consensus was difficult to obtain .Public engagement in the development and approval of health protocols is proving to be an important element in the search for its legitimacy –35. The The purpose of this scoping review was to: consolidate the available scientific literature on public consultations conducted as part of the COVID-19 pandemic, particularly on tie-breaking criteria and the underlying values of prioritization protocols for ICU access, as well as providing a snapshot of current knowledge, including an overview of the key arguments of public perceptions, and identifying potential gaps related to this topic.The steps described by Arksey and O’Malley (2005) was the preferred method, as it allowed us to adapt our approach with flexibility , 37. IniWhat are the public’s views on the tiebreaker criteria contained in the COVID-19 prioritization protocols? To obtain the answer to this question, we considered it pertinent to carry out a scoping review.There are few studies of public opinion regarding the COVID-19 protocols for access to critical care and the primary and secondary criteria they contain. There is also little knowledge about the public arguments surrounding these criteria. We considered it important to learn more about these tiebreaker criteria and the perspectives the public has on them. Therefore, our main research question in this review was: Our scoping review involves the Arksey and O’Malley methodological design because of its flexibility in the analysis of empirical and normative literature, as well as the possibility to perform a quantitative and qualitative analysis at the same time. This design appears to be a valuable option for research in bioethics and clinical ethics . HoweverStudies based on public consultations of COVID-19 triage protocols developed for adult patients for access to the ICU describing the tie-breaking criteria and underlying values.Studies based on public consultations whose topic was related to tiebreakers and/or underlying values considered in prioritizing resources for adults in the ICU during this pandemic (not including protocols developed for this purpose).Studies that have undergone public consultations through a variety of methods: surveys, interviews, focus groups, deliberative or mixed processes.Studies with quantitative, qualitative, or mixed methodology specifications published from January 2020 to April 2022.Studies that have not yet been published or that were not peer-reviewed were excluded.The inclusion criteria were:The collaboration of a librarian was sought for the search strategy and for obtaining articles in English, French and Spanish. Seven electronic databases were searched using keywords, with adaptations made based on the controlled vocabulary for each database: PubMed, Medline, EMBASE, Web of Science, PsycINFO, EBM reviews, CINAHL complete. We also searched the grey literature (Google Search and Google Scholar) and performed a scrutiny on the references of the articles found. Initial search terms included: COVID-19 triage, Intensive Care Unit, tiebreakers, life cycle, social utility, biological age, ethical values, surveys, deliberative processes, interviews, and others (Related File 1: Database Search Strategies).For the database search strategy, the first search was carried out in February 2022. To obtain more studies that would offer us more data and perspectives from the public, the PubMed database was launched for a second and third search in April 2022. In this third search, it was necessary to modify the controlled vocabulary to obtain more articles related to our research subject, and we obtained more interesting articles. Through the manual search in Google and Google Scholar, we also found some interesting preprint articles already accepted for publication, but not yet published so it was not possible to include them in our results. We also thoroughly searched the reference section of the selected articles from which we obtained other interesting articles.The eligibility criteria for the search of articles from each database were initially applied by an independent person and one of the authors (CC). The manual search of articles was performed by (CC) both in Google and Google Scholar, as well as in the references section contained in the selected articles. One author (CC) initially selected the titles and abstracts relevant to the research subject obtained from the databases using EndNoteX9©, eliminated duplicates, and appended those from the manual search. The full-text articles were then reviewed and verified according to the eligibility criteria by two authors independently (MEB) and (YF) to resolve discrepancies and reach a consensus.© to present empirical papers [A flow chart was prepared according to the PRISMA Extension for scoping review (PRISMA-ScR)l papers  Fig. 1)© to presTables and graphs were prepared by one author (CC) and checked by two authors (MEB) and (YF) to assess the accuracy of their content. Descriptive statistics were used for the data in percentages. Excel© software was used for quantitative data management. The tables show the main characteristics of the articles found and the most relevant arguments of the public  Table  and Arg. We alsoFollowing a coding structure developed by the team members, one author (CC) extracted the most salient arguments from the public consultations and the results found from the selected studies. All authors coded separately these segments and the participants' views that were considered most relevant. These arguments allowed the emergence of themes and sub-themes related to the tiebreakers considered by the public in the studies found. After discussing the themes, a consensus was reached among authors. In general, a synthesis of qualitative data was made .This scoping review aimed primarily to identify the arguments of the public captured by different methods of public consultation in relation to the prioritization in intensive care during the COVID-19 pandemic, mainly on the criteria used for tiebreakers and their underlying values. The research strategy resulted in 20 publications between 2020 and 2022. A single study conducted a public consultation in 11 different countries through online questionnaires, including the following countries: United States of America (USA), Brazil, India, United Kingdom (UK), Italy, Germany, France, Australia, Spain, China, and South Korea with the participation of 5175 participants . AnotherOf the studies included for analysis, some consulted both the public as well as experts. When referring to experts for the purposes of this review, we consider experts to be members of health scholars or authorities, disaster specialists and/or health professionals in various medical disciplines, as well as other university or scientific professionals. Thus, we found that some studies consulted both the public and healthcare workers (15%) and others consulted both the public and experts from other specialties (15%).Most consultations were conducted through online questionnaires (80%) and comments on a website (5%). Two studies conducted 2 sequential surveys of the same population , 54. OnlThe results were classified according to the characteristics of the studies and according to the tiebreakers and main arguments of the public Tables , 2.The principles and values considered in these public consultations are presented in percentages according to the findings found in the selected articles Fig. .Fig. 3PrSome interesting values emerged from the public consultations: consideration of the merit as a value, preference for patients affected by the pandemic disease and preference for citizens of the same nationality.From our thematic analysis, 5 themes and 15 sub-themes emerged: I. An indirect and direct approach based on patient age ; II. Social and instrumental value: essential healthcare workers (reciprocity and the multiplier effect), essential non-healthcare personnel, merit, and nationality of patient; III. The egalitarian approach ; IV. Solidarity approach towards the vulnerable , and V. The efficiency and stewardship  Fig. .Fig. 4ThThis review allowed us to obtain an overview of the public's perspectives on the tiebreakers. The emerging themes and sub-themes were the product of our analysis of principles and values underlying the tiebreakers considered by the public consulted. It was interesting to note the variability in public preferences on certain tiebreakers, and the influence of culture, economic status, religious beliefs, and other values characteristic of certain populations on pandemic prioritization , 58, 59.The patient age related to the prioritization and the tiebreakers for the allocation of scarce ICU resources during this pandemic was one of the most discussed criteria in the public consultations found in this review. To maximize the benefits in the face of a shortage of health resources, some experts have considered the patient's age to be relevant in extreme situations , 61. WheIntergenerational equity has been considered and discussed in several public consultations (90%) , 58, 59.According to the studies found, the public tends to favor younger patients under the perspective of life cycle, so this preference is not new. This preference is based on the premise that younger patients have yet to live their life stages, unlike older patients who have already had this opportunity, emphasizing an equality of opportunity. We believe that this criterion indirectly considers the biological age of the patient. For experts, the age considered indirectly in the life cycle is relevant to maximize the benefits in a pandemic situation, thus it was recommended to include it in the triage algorithms , 64, 65.On the other hand, this criterion has been reformulated under the perspective of intergenerational solidarity . We founA high priority for pregnant women was also considered in two public consultations , 49. HowIn this review, absolute age refers to considering directly and solely biological or chronological age as a tiebreaker between similar patients. It should be noted that in the literature, we found conceptual differences between biological age and chronological age that may even have legal repercussions in some countries , 73. ForIn 40%) of public consultations, the participants favored the criterion of absolute age % of publ, 56, 59.These public perspectives are consistent with the scientific literature reported during the pandemic regarding elderly patients and COVID-19. In this pandemic, the most affected population initially consisted of the elderly, the immunosuppressed, and those affected by chronic comorbidities –77. The The absolute age as a tiebreaker  was rejected in (15%) of public consultations. They do not consider it fair for the elderly, but rather consider it discriminatory , 50, 57.Some American protocols were modified in terms of age-linked criteria that had previously been planned in their guidelines for the allocation of scarce resources in intensive care, apparently due to criticisms . Some coOn the other hand, considering the absolute age as a tiebreaker is not well seen in some countries. For example, in Japan, age is correlated to the biological sex of the patient, as the survival rate for women is higher than that of men. For this reason, the Japanese think it is a discrimination of age and biological sex at the same time. Also, the elderly have a high social and cultural value, underlining their respect and consideration. Although the public consulted prefers to give priority to the younger patient in the case of a tiebreaker, the authors believe that this guideline acceptance is difficult because of their cultural roots . There iIt appears that the meaning of this principle varies among the public and has not been well defined in the literature. However, some have recently discussed and detailed their strategy for applying this principle in their prioritization protocols . Others These values towards the essential healthcare personnel were also considered in several studies 60%) , 56–58. 0% , 56–5The public also considered the instrumental value of healthcare personnel in (30%) of consultations, especially those on the frontlines, as a multiplier effect of benefits. They thought about the possibility of these healthcare workers saving more human lives after recovering from their illness , 50, 56.The public also considered the difficulty in selecting the most exposed healthcare personnel in this pandemic. Therefore, they considered this prioritization as not feasible, which could lead to a lack of trust in the management of scarce resources . This isThe value of these people was also considered by the public as a tiebreaker, in some consultations (40%) , 57, 58.On the other hand, other tiebreakers considered were prioritization based on merit and prioritization according to the patient's nationality, which were classified as part of the societal value.The merit-based value of the patient was divided into two perspectives . The one based on individual behavior was represented by people with a history of having complied with prevention and containment measures during this pandemic and who nevertheless caught the disease. These people with COVID-19 who complied with their doctor's instructions, including compliance with the indicated treatment, and who avoided infecting others as much as possible  , 54, 55.The second perspective was based on collective behavior, which includes people who played an important voluntary role in society during this pandemic and who became infected with the disease, such as volunteers. They would be highly prioritized by the public for their merit as well . Non-heaWe found no public consultation in this review that emphasized the importance of COVID-19 vaccination status for consideration as a tiebreaker. However, we did find recent publications in which this aspect was important to the public in prioritizing intensive care patients during this pandemic. This may be a subject of debate and could also be labeled as a merit of the patient in prioritizing health resources , 111.Messhi houkou, which shows that not all healthcare workers share the desire for a reward. These healthcare workers disagreed with the public regarding their prioritization in the event of a tie [On the other hand, we found different perspectives on the approach to the value of merit among healthcare workers that were interesting to learn about. For healthcare workers, the most exposed in this pandemic, risking their lives is part of their work . This could be one of the most remarkable qualities of their vocation, which seems to be a selfless vocation. This disinterested vocation was highlighted by Japanese healthcare workers with their slogan: of a tie . This waof a tie . Howeverof a tie . RegardlThe public gave importance to the value of merit as a tiebreaker, in such a way that the last to be prioritized as having the lowest societal merit were people with a judicial record, those involved in violent crimes and those with psychiatric problems , 41, 46.The nationality of the patient is a citizen characteristic whose societal value is variable between countries. There are countries with a marked nationalism and patriotism . ConsultWe found controversy regarding this egalitarian perspective. The public showed weak support by considering the randomization criteria and the "first come, first served" principle in both primary and secondary prioritization as irrelevant , 58, 59.We found differences among the participants of the public consulted regarding the prioritization of people considered most vulnerable according to each society , 47–49. The public also mentioned the patient's quality of life criteria in some consultations , 47, 50.Giving priority to the patient affected by a pandemic disease such as COVID-19 over another type of disease was a preference expressed by the public in two studies , 43. We This criterion was also mentioned by the public as important to consider when faced with the impasse of deciding between two patients with similar survival prognosis. They prefer to give the opportunity to the patient who is likely to last less time in intensive care, to optimize the use of the few resources available and to speed up access to other patients in need , 48, 58.The public also expressed a preference for reducing social costs. This cost was considered from two perspectives by the public: a financial perspective based on the reduction of economic costs combined with efficiency in resource management. They considered it important to reduce the costs incurred by patients admitted to the ICU in the face of a pandemic shortage. They suggested prioritizing patients who spend less time on an invasive ventilator. The other perspective was related to the irresponsible behavior of the patient in contaminating other people, increasing the risk of contagion and of human loss (a human cost) .These values considered by the public lead us to think that they have also reasoned on how to manage scarce health resources to preserve more human lives, a tendency to maximize benefits in an extreme context. We could consider in a certain way a transition from the individual to the collective perspective. This would be consistent with most of the protocols for access to the ICU in a pandemic situation , 23, 86.According to our results, it is not easy to obtain a consensus, especially when there is a heterogeneity in public perspectives . Some coFurther studies are needed to explain the discrepancies between the public and experts regarding prioritization in this pandemic. Consultations conducted through deliberative processes during this pandemic are very rare. We consider that this would be one of the most outstanding gaps: the search for an optimization of COVID-19 protocols thanks to citizen deliberation. Another aspect is the absence of public consultations of certain groups such as indigenous populations, and of other nationalities, notably from countries with low or medium incomes where these countries are the most disadvantaged in a pandemic. There is little information on the prioritization of pregnant women in pandemic contexts.The research strategy was limited to 3 languages . Despite having reformulated our research strategy to obtain more articles of interest in the databases, we observed that there is very little literature on the subject. Our search in the gray literature was not exhaustive considering this. We do not rule out the possibility that several studies have not yet been published during our search. A methodological assessment of bias of the selected articles was not a methodological requirement in this review, so it was not performed , 38. OurThis scoping review provides an overview of what the public indicated was important to consider as a tiebreaker in the decision to admit patients to intensive care in the context of this pandemic. We focused our analysis according to the principles and values underlying these criteria mentioned by the public consulted. We obtained five emerging themes from our thematic analysis. This scoping review shows that patient age was the most discussed criterion, and that there is a preference for favoring younger patients over older patients when there is a tie between patients with similar prognoses, with a slight tendency to favor intergenerational equity. The social and instrumental value of individuals was also another of the themes that stood out. Among the interesting tiebreakers considered by the public were the recognition of the merit of the patient, the preference for nationality, and for those affected by the pandemic disease, although their arguments were not well defined. Variability was found in public perspectives in relation to the tiebreakers and their values. This variability was related to socio-cultural, and religious factors. We observed that tiebreakers continue to be a source of debate for both the public and experts, as some consultations were made in both groups. More studies are needed to understand the public's perspective on tiebreakers. We hope that these collected public perspectives can be useful in the development or optimization of triage criteria for admission to adult intensive care in the context of a pandemic.Supplementary file1 (DOCX 690 KB)Supplementary file2 (DOCX 18 KB)Below is the link to the electronic supplementary material.


The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, we present a principled veridical data science methodology for quantitative histology that shifts focus from image-level investigations towards neuron-level representations of cortical regions, with the neurons in the image as a subject of study, rather than pixel-wise image content. Our methodology relies on the automatic segmentation of neurons across whole histological sections and an extensive set of engineered features, which reflect the neuronal phenotype of individual neurons and the properties of neurons’ neighborhoods. The neuron-level representations are used in an interpretable machine learning pipeline for mapping the phenotype to cortical layers. To validate our approach, we created a unique dataset of cortical layers manually annotated by three experts in neuroanatomy and histology. The presented methodology offers high interpretability of the results, providing a deeper understanding of human cortex organization, which may help formulate new scientific hypotheses, as well as to cope with systematic uncertainty in data and model predictions. In this classification, the neocortex is composed of six layers differentiated by neuronal features such as neuronal type, number, size, shape, density, etc. In his seminal work, Brodmann also summarized previous work done on the composition of the neocortex showing that in the generic neocortex, researchers differed significantly in describing the number of layers ranging from four to seven. Thus, we can infer that cortical layers, although biological features of the cerebral cortex, are delineated by arbitrary criteria developed by human observers. Furthermore, the composition, size, and number of layers are not constant throughout the cerebral cortex. Based on variations of these cytoarchitectonic features cerebral cortex can be divided into smaller cortical, cytoarchitectonic areas. At the beginning of the 20th-century researchers in the field of cytoarchitectonics  developed several cytoarchitectonic maps which divided the cerebral cortex into smaller structural units with two of the most influential being one developed by Brodmann2 and the other by von Economo and Koskinas3. For every cytoarchitectonic area, a clear set of features can be defined which distinguishes them from other areas. However, borders between two areas are not always clear cut, but are, rather, an area of transition with gradual changes from one to the other. In these transitioning parts it is often difficult for the human observer to precisely and consistently delineate both cortical areas and laminas within areas. Interest in the analysis of these structures is driven by the evidence of the relationship between features of cytoarchitectonic structure and cortical functions. Today, it is believed that the way neurons are distributed in the brain determines its function. The subtleties in this fine structure of the brain underlying its function can be characterized in great detail by studying the organization of cells across the cortex4. However, investigations in this field are mostly done manually, require a significant amount of researchers’ time, introduce observer-dependent bias and hinder the reproducibility of the research5. As technology advances, more and more digitized histological data becomes available. Computer-aided methods provide means for faster, more objective, and higher-throughput investigations of the cortical structures through automatized processing of histological sections of the cortex. This enables researchers to answer various scientific questions by better understanding the anatomical and functional organization of the brain, as well as observing subtle changes in the brain structures caused by neurological and psychiatric diseases.The human cerebral cortex is a highly organized, complex structure composed of billions of neurons. One of the most prominent features of the human cerebral cortex are cortical layers—laminar structures parallel to the surface of the cerebral hemisphere and superimposed one on top of the other. This layered structure is caused by variations in cell density, size, and shape of neurons, specific for each cortical layer. The entire cerebral cortex can be subdivided, based on the number of layers, into a six-layered neocortex (or isocortex) and allocortex which can further be subdivided into a two-layered paleocortex, three-layered archicortex and usually a five-layered mesocortex. Today, the most used classification of the neocortical layers is one based on the concept developed by Korbinian Brodmann at the beginning of the 20th century9. An important step was the development of gray-level index (GLI)10, a method that measures areal fractions of darkly stained cell bodies across the cortex, yielding different neuron density profiles depending on the location of interest and identifies positions at the cortical ribbon where cytoarchitectonic features change11. Blocks of adjacent profiles may be represented by feature vectors and compared between areas of the cortex. Profile features were used for the estimation of cell counts between cortical areas, providing realistic information about neuron density12. Higher levels of automation enabled faster analysis of larger datasets. The BigBrain is a high-resolution 3D digital atlas of the whole human brain, providing huge amounts of high-resolution histological data for neuroanatomical studies13. The GLI profiles were combined with machine learning methods to create laminar segmentation on the BigBrain dataset, creating parcellations across large brain areas15. Cortical layers were also segmented using convolutional neural networks16, and a comparison with GLI approach is given17. The first article that uses features and statistics of individual neurons appeared in 2017, where the authors used automatic segmentation of cells in the mouse brain and analyze cellular shape statistics without machine learning models18. In the year 2018, the first approach that does not use profiles across the cortex was proposed19. A combined approach of unsupervised and supervised machine learning was used on a dataset of 2-photon microscopic images of the rat cortex. One can observe the transition towards automation, analysis of larger datasets, and usage of machine learning methods in the field that was until recently dominated by the usage of classical image processing techniques that use various filtering, image-wide pixel transformations, thresholding, and similar operations.Ever since the first methods which introduced automation in the analysis of cortical layers, the central idea was the sampling of different tissue measures along transverse lines drawn either manually or semi-automatically across the cortex, perpendicular to the laminar structure and spanning the full width of the cortex20. In a recent paper21, authors use neuronal density estimates to infer local neuronal connectivity while addressing the issue of human bias in the manual segmentation of cortical layers and use an unsupervised clustering approach to identify and represent the laminar structure. An important aspect to consider in the analysis of images of the human brain, or biomedical images in general, is to what extent automated systems should recreate the work of human investigators. Computer vision systems can give access to underlying image contents that are not visible, process every image equally, and provide partial or complete automation of the process22, especially concerning the recently available massive amounts of high-resolution and multimodal data, far beyond the capabilities of any kind of manual analysis. Such systems can derive and analyze detailed anatomical and biologically meaningful information on a large scale and reveal currently neglected structuring principles and provide a deeper understanding of the laminar structure. This suggests that there is a need to move beyond the limitations of manually created parcellation in conventional atlases towards data-driven analysis. Ideally, a representation of a histological section that would contain information to enable objective and unsupervised classification or parcellation of layers and even reveal sub-layering would help resolve many unanswered issues in the study of brain anatomy and physiology.Machine learning-based methods rely on a training dataset to develop their predictive capabilities, allowing them to generalize and make predictions on unseen data. In this context, the unseen data refers to portions of tissue that have not been manually delineated or labeled by human researchers. In machine learning, such an approach is known as supervised learning, sometimes also referred to as predictive modeling. Having adequate learning data is essential in developing successful models, and human labels are considered the gold standard. However, over the years, the impact of human bias in brain parcellation has been increasingly recognized and many methods sought to overcome this issue by developing objective quantitative measures and usage of statistics to distinguish between different layers and brain areas23 that captures cytoarchitectonic details and can be used for inference about the brain structure using only local tissue information at the cellular level. The usability of this approach is demonstrated through the task of distinguishing cortical layers by classifying each neuron within the six cortical layers and white matter using a supervised machine learning method. The method uses phenotype characterization as an input and predicts the individual neuron’s layer, natively offering a high level of interpretability. We also demonstrate the human ability to distinguish between the cortical layers and explore how learning-based methods can generalize from such noisy labels. The developed framework provides a capability to investigate which neuronal features are characteristic for different areas and presents a prospect for future investigations in the field of cytoarchitectonics.In this paper, we hypothesize that the current methods do not offer such capabilities due to their inability to capture subtle cytoarchitectonic features. Consequently, they express low explainability and interpretability of their results. Methods based on deep that operate on striding windows across the image may provide convincing parcellations, but we cannot ask what tissue characteristics lead to these results. Here, we investigate the possibility of developing neuron phenotyping24. Samples used in this study were taken from the prefrontal cortex of two brains . Sections were taken from the dorsal and ventral part of the typical six-layered homotypic isocortex of the prefrontal cortex4. Brains were fixed in 25. NeuN is an RNA-binding nuclear protein, derived from the RBFOX3 gene, which regulates alternative splicing in neurons and is expressed explicitly in all neurons of used tissue specimens. In the experiments, Histological data were obtained from the Zagreb Neuroembryological Collection26. Figure bottom-up approach in the analysis of brain cytoarchitectonics that builds from the cellular level and infers about larger structures based on morphological and textural features of individual neurons. Here, we discuss the development of those features, as well as some rationale behind the choices made in their development and selection.In manual delineation, the density and size of neurons are the most important characterizations of the laminar structure. Based on anatomical descriptions and kernel density estimates, three populations of similar densities are assumed , two populations of similar sizes . By plotting a histogram of neuron densities and sizes, one can observe that the features express a multimodal distribution, which can be separated using the minimization of intraclass variance28 which use grayscale-guided watershed on anisotropically diffused images to separate neurons, rather than often used distance maps obtained from the grey-level threshold, providing a binary image of segmented, non-overlapping neuron areas. As the goal here is to create consistent results across the tissue, other segmentation methods may be used as well, such as a recently proposed instance segmentation via contour proposals29, especially for different staining methods. This step yielded the locations and segmentations of neurons, from which other neuronal characteristics are developed.The first step in obtaining the neuron characterization is the segmentation of neurons from the background tissue. The segmentations were obtained using automated methods30. An overlap of binary segmentations and the original image was made, and ImageJ’s function analyze particles was used to produce measurements of neurons’ bodies. Those were the area, perimeter, circularity, roundness, and Feret’s diameter as well as the mean, median, skewness, and kurtosis of the gray values. More details on particle measurement can be found in ImageJ’s documentation31. These features form the basis for investigations in brain microanatomy, as they are often, although not at this level of precision, perceived by the eye of neuroanatomists. By this, we obtain the first neuronal characteristics, which may be visualized to reveal patterns of their appearance across the cortical layers, as shown in Fig. Secondly, neuron segmentations were analyzed using ImageJ particle analysis pipeline34, which may be brought into relation with cortical layers having a roughly uniform density within each layer. However, it seems that the neuron distribution in the cortex is such that their intrinsic structure may not be clustered by a single set of global density parameters, as used in clustering methods. Nevertheless, these methods provided insight into some cortical properties. Meaningful clusters were created when considering neurons within the radius between 36 may be precomputed. Considering the large number of neurons found in a histological section, efficiency may be of critical importance.It is worth mentioning that density-based clustering algorithms are often used to segment the areas of similar point densitiesk neighbors were considered, for k-th nearest neighbor were used as a feature, as well as their mean, max, min, skewness, kurtosis, and entropy. Basic measures of individual neurons were computed in a similar fashion to produce, for instance, the average area of neighboring 100 neurons, as shown at the right in Fig. k-neighbours gives information about the area around a neuron and a number of its neighbors and is described using hull area, perimeter, average nearest distance for neurons found in the hull, and standard deviation of nearest distances. Dispersion of neurons may be quantified using nearest neighbor index (NNI), a measure that describes whether points follow usually subjective patterns of regular, clustered, or random distribution. The NNI measures the distance between each point and its nearest neighbor’s location. All the nearest neighbor distances are averaged, and if the average distance is less than the average for a random distribution, the distribution of the features being analyzed is considered clustered. If the average distance is greater than a random distribution, the features are considered regularly dispersed. The index is expressed as the ratio of the mean observed distance divided by the expected distance, which is based on a random distribution with the same number of points covering the same total area,To measure properties of neurons’ neighborhoods, nearest entclass1pt{minimaslices. Features measured in several directions can identify border neurons and changes in neuronal properties in different directions. Slices may be regarded as measurement units reaching from a single neuron, each unit representing a population of neighboring neurons found in a given direction from the central neuron. The relationship of different populations within an area has been extensively studied in the frame of biological diversity of species, landscapes and other38. Considering the neurons in a slice as members of a single species, and the k neighbors of a neuron as the population of all species in their habitat, biodiversity measures evaluate the relationship between the species. In this context, the number of slices is the number of different species, or richness, and the relative abundance of the different species in an area as evenness. The two most often used such measures are the Shannon index39 and Simpson index40. The Shannon index gives a quantitative measure of the uncertainty in predicting the species of an individual chosen randomly from the population. The Simpson index measures the probability that the two individuals who are randomly chosen (with replacement) from the total population will be of the same species.R is the number of different species or, here, slices, and ith type in the population or proportion of neurons in ith slice to the number of the neurons in k-neighbourhood. If all slices have an equal number of neurons, R, and the Shannon index takes the maximum value of Depending on its position in the cortex, a neuron may be placed more toward the middle or more toward the edge of its layer. The computation of properties of its neighborhood may be confounded by reaching into adjacent layers and using neurons with different properties for the computation of statistics. To identify this case, measurements may be taken only from neurons found within the range of angle, or All specimens were collected during regular autopsies at pathology departments of the University of Zagreb, School of Medicine, approved by the Ethics Committee of the University of Zagreb, School of Medicine and in accordance with the Declaration of Helsinki, and informed consent was obtained from the next of kin.area were found in layer III of the cortex and were followed by neurons of layer V and layer VI. Out of the 50 largest neurons, circularity and roundness were found the lowest in layer VI which is known to consist of multipolar neurons with dendrites reaching in different directions. Variations in grayscale intensity were expressed differentially in the cortical layers. Neurons with the highest mean grayscale values were mostly found in layer I, showing low NeuN dye intake. Neurons with the lowest median were predominantly found in layer VI, in layer IV and the middle of layer III, sometimes referred to as layer IIIb. No conclusion was made or the reason found for neurons of layer VI having such large NeuN uptake properties that resulted in lower individual grayscale intensities. Measures regarding neuron shape such as area, circularity or perimeter were shown to provide more discriminative power, which is not unexpected since the findings in neuroanatomical research rely to large extent on the shape and size of neurons.The distribution of neurons’ features across the cortex provides insight into different aspects of the cytoarchitectonic organization. This detailed, neuron-level approach allows for tissue inspection following known cytoarchitectonic principles like, for instance, the distribution of the largest neurons. Those with the largest sparse regions of the section, or dense regions containing layers II and IV, as shown in Fig. Using local neuron density, layer I and white matter can be distinguished by having small neuron density, thus identifying Although the developed neuron feature sets provide quantitative descriptors of cortical organization, they are not sufficient to provide a clear classification of the correct cortical layer. While some features may be more expressed in certain layers than in others, it is not straightforward to determine what exactly is changing between layers, or the impact and interconnection of different features. This led to an assumption that there is information contained in the developed features that can be analyzed, combined, and used to produce a precise classification of neurons concerning their location within the cortical layers through more complex and more expressive models. A supervised machine learning approach is used on a dataset of manually segmented layers in order to accurately predict the layer of each neuron in the histological section. Thus, layer segmentations can be obtained throughout the section. Feature attributions for the model are investigated to identify informative tissue features.To obtain the training dataset from which the machine learning method will learn to classify neurons according to their layers, portions of both digitized histological sections were given to three human experts in histology and cytoarchitectonics who manually delineated borders between the layers of the cortex. The apparent inconsistencies and mutual disagreement between the experts, as seen in Fig. 42 were chosen for prediction and interpretation of cortical lamination for its several advantages. Decision trees mirror human decision-making more closely than other approaches43, which is especially useful when modeling human activities, such as the manual delineation of cortical layers, a decision-making process based on a combination of information about neurons’ characteristics. We used CatBoost44, a method based on gradient boosting over decision trees which is one of the most successful models for dealing with tabular data. The model was trained for 100 iterations with a learning rate of 0.1 and default other parameters. The best generalizations were obtained by combining the manual labels of all three raters in an ensemble. Three separate models were trained, one for each rater, and using softmax objective output probabilities were summed, and the final prediction was made using a maximum over all classes for each rater. Results of this approach are shown in the right of Fig. Boosted decision trees, a state-of-the-art supervised learning method on tabular input data such as the computed neuron featuresExperiments with different sets of features have shown that although some combinations of features do achieve high accuracy on training data, that itself does not guarantee that the model will perform well on the whole histological section. The introduction of features based on the distance to sparse or dense regions has significantly improved the model’s ability to separate regions of the sections into parcels following the laminar layout of the cortex.Without the existence of single ground truth for reference, the measurement of the model’s performance is considered in the context of inter-rater variability. Training data was split into 3. This finding confirms that the computed features yield meaningful results and follow neuroanatomical observations.In this study, we proposed a novel approach to analyzing cortical features in order to facilitate more detailed and specific scientific investigations. Currently, a gold standard is a manual annotation by trained experts. However, human experts are often biased, and results obtained in the such analysis are often inconsistent. An important feature in delineating cortical layers and areas is neuronal size. Our findings demonstrated that in analyzed regions, which belong to the homotypic isocortex of the prefrontal cortex, neurons in layer III are in general larger than neurons in layer V. Although a general sense is that neurons in the layer V are larger than neurons in layer III that is not true for the prefrontal cortex. The largest pyramidal neurons in the cerebral cortex are indeed found in layer V (Betz’s cells of the motor cortex), however, in most cortical areas pyramidal neurons in layer V are smaller than neurons in layer III45, was used for the estimation of neuron features that contribute the most to neuron classification within the layers. Details on SHAP values and their influence on model outputs for both For a deeper understanding of both the model and features being used in the pipeline, an investigation of the impact of features on the prediction of the neuron’s class was performed on both global (model) and instance  levels. A recent approach for measuring feature attributions in learning models, the SHAP measureAn important aspect of this approach is the ability to identify features that contribute to predicting a single instance of the data, for each neuron. For instance, Fig. The cortical depth feature had a large impact on the model’s output. This is because it helps integrate simpler features like local densities with anatomical observations regarding the position of a neuron within the cortex. Features based on oriented measurements that measure the change of cytoarchitectonic properties in different directions also had considerable feature importance, being able to identify neurons on the border of cortical layers. It was shown that building on lower-level features yields features that have greater discriminative power and thus greater importance. This is due to their capacity to overcome local variations in neuron features and take, for instance, the mean of those features. In contrast, using features of a neuron such as an area, there is no increase in the accuracy of prediction, which is reflected in the low importance of these features. This is probably why different methods for local pattern analysis and classical image feature extraction methods are not very successful in cortical layer segmentation. Range of variability radius was established, giving an estimate of the size of the neuron’s neighborhood in which measurements should be made, so it is large enough to overcome local variations in neuron distribution and recognize its location within the cortical structure on one hand, and on the other narrow enough so that measurements are not confounded by reaching too far into adjacent layers.To investigate the effects of section thickness, we have analyzed the number of nearest neighbors in several fixed ranges and established that in During experiments with different models, it was noticed that parts of layer III and layer VI are sometimes divided into sub-layers that follow the direction of the laminar structure, although being very short and not extending through a significant portion of the slice. Further investigations using the developed methodology may provide more detailed insight into the sub-layering of cortical structure.The proposed method has demonstrated the ability to generalize across sections with a very limited training dataset, showing promising results and indicating that it could be transferable to other brains. However, due to the complexity of the brain, further research using larger amounts of histological data of greater variability is needed to demonstrate with certainty the degree to which these results can be generalized across different brains. This will also allow for further testing of the approach in different brain areas, tissue staining, and cutting planes. In oblique slicing, where the angle of the slicing plane may influence the shape of the neurons, for instance, the pyramidal neurons will not appear as triangles if the slicing was perpendicular to the neuronal columns. This limitation may be overcome by using the 3D representation of neurons.We have proposed a new methodology for modeling brain cytoarchitectonics which builds from the cellular level and infers about larger structures by creating data-driven, neuron-level tissue descriptors based on features of individual neurons, or neuronal phenotyping. This is in contrast to today’s other approaches in neuroscience, which are mostly based on pixel data. The movement from pixel-wise towards neuron-centric analysis, in which the structure of the brain is studied through the lens of the relationship between the neurons, in contrast to relying solely on changing values of pixels in the histological image, conveys a new paradigm in the field and enables methods from other disciplines to be introduced. Here, we refer to the shift in the way histological data is gathered, examined, and comprehended, and the introduction of machine learning methods that operate on tabular data, for which the neuron representations had to be made first. By leaning more on data-driven methods, our approach lowers the need for human-dependent interventions and interpretations, which allows for more objective and reproducible quantification on a large scale. These settings enable novel insights into the organization of cortical microstructure and subtle differences in neuropathology. By enabling the emergence of new, better descriptions and understanding of the brain structure in different areas and stages of development, our work facilitates movement towards fully automatic, high-throughput, objective investigations, allowing the processing of ever-larger amounts of histological data available globally in research centers today.The scenario of using the proposed methodology was demonstrated on a particular brain region and validated using a set of data manually labeled by three experts. Our methodology is easily extensible with novel neuronal features such as different stainings or receptor maps and allows the use of other machine learning-based computational methods, such as graph neural networks, which will entice future research initiatives in the field of computational neuroscience.Supplementary Figures.


This article was migrated. The article was marked as recommended.Introduction:The COVID-19 pandemic has been presenting new challenges for medical schools worldwide. Medical educators are coming-up with creative solutions to address those unprecedented challenges. The purpose of this study is to reflect upon an experience of an online TBL in a Family Medicine Clerkship.Methods:This study relied on a qualitative descriptive design. A phenomenological approach was adapted to capture the perception of students regarding online TBL as part of Family Medicine clerkship, using a survey of open-ended questions. The data were inductively analysed using thematic analysis.Results:The results of the study revealed that the students, overall, reacted positively to the experience. Five themes of text fragments emerged from the analysis: Equivalency of experience, Efficiency and Ease-of-use, Organization, Novelty, and Design. The students also noted some minor difficulties, that they faced at the beginning of their experience, indicating the existence of a learning curve. They also identified a few opportunities for improvement.Discussion:This study demonstrated that combining videoconferencing and lesson delivery software together for TBL enables remote facilitation of the Family Medicine curriculum, and that the students value the experience as such. From the COI perspective, all three factors, namely: social presence, teaching presence, and cognitive presence, are met by such a set-up for distance learning. The students also felt validated and that their voice is heard. The central coordination of the TBL process proved to be crucial to ensure continuity, and also to support individuals’ mental health and team spirit.Conclusion:This study concludes that TBL enables rapid transition to distance learning; it promotes analytical and self-directed learning even in extreme circumstances. Moreover, the TBL sessions allow for the facilitators, including the Discipline Lead, to get to know the students, on a personal level, and to monitor and evaluate their performance, over time. Learning is designed to be active, having learners explore relevant problems through small group discussions intended to draw out inconsistencies in learners’ existing knowledge, with the teacher facilitating rather than leading the sessions . TBL hasTBL is widely recognised as a classroom endeavour using a standard approach that relies specifically on certain elements relating to individual preparation and accountability (iRAT), team working and agreement with simultaneous reporting (tRAT and application exercises). Although there are some published experiences using it online, this is mainly related to circumstances such as responding to the need for online courses which are delivered ‘asynchronously’  . In a feRelevantly, the Community of Inquiry (COI) model has been used extensively to guide the creation of meaningful online and blended learning experiences . COI maiThe COVID-19 pandemic presented huge new challenges for medical schools worldwide , where tThe Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU) is in Dubai, United Arab Emirates (UAE).In the fourth year of the programme, Family Medicine is embedded in equal proportion to Internal Medicine, Surgery, Paediatrics, and Psychiatry . StudentFamily Medicine is provided through a large private hospitals and peripheral clinics group, spread around Dubai, UAE. Starting in September 2019, the CoM implemented the clinical clerkships for the first time.The core knowledge teaching, corresponding to each clerkship, was provided once per week, over a 4-hour time slot. In the case of Family Medicine, the available time slot lent itself to the concept of TBL, by supporting the concept of teamwork, and the analysis of complex cases, in groups. In addition, the time slot allowed for the joining of multiple Family Medicine Adjunct Faculty who learned the TBL methodology, and in turn contributed to the facilitation of the small group teaching, and delivered specific, predetermined learning material.Prior to starting TBL, each rotation of students received an introductory presentation on what the teaching methodology involved, and the reason for choosing it for Family Medicine teaching. Great care was taken with group formation to ensure balance of local and international students, and of varying expected maturity . The discipline lead (LJ) ensured there was an Ice Breaker and the implementation of Group Rules for general accountability from individuals and the group.LJ and one Adjunct Faculty facilitated each TBL session in a large teaching room where there was enough space for 9-10 students to work either together or divided into two smaller groups. Individual Readiness Assessment Test (iRAT) was delivered as a paper exercise at the start of the session, taking usually 10-15 minutes to do 10 Multiple Choice Questions (MCQs) based on prior set reading. Team Readiness Assessment Test (tRAT) then took place in two smaller groups, sitting around the table, and physical scratch cards were used for recording the answers. Papers and scratch cards were collected by LJ for marking and recording of grades for assessment purposes. The MCQs were then discussed, in detail, once both groups had finished the tRAT, in order to iron out any challenges, and/ or address any questions from individuals or groups. This involved going through the incorrect answers to ensure students understood not only the correct answers, but why other answers were incorrect. Students shared their own answers with their teams in the discussion, if they wished. They particularly loved the scratch cards. There were often heated discussions before team decisions were finalized, and excited reactions to right or wrong answers.The two teams then worked on the application exercise in a single room with one or two facilitators providing guidance in the discussion process. The room was usually noisy. Application exercise results were presented using flip charts or role plays and entailed further questions and discussion. The students often presented mind maps or charts with a sequence for managing the problems, and this could be competitive and lively.Following the presentation of the teams’ solutions to the application exercises, the Adjunct Faculty and Discipline Lead presented one or two 20 to 30-minute seminars on topics of relevance to the TBL learning outcomes from that day. For example, a session which included an application case involving discussion of prevention and screening, was followed by a summary presentation on immunization through the lifecycle, and the role of primary care in preventing chronic disease. Overall, the TBL sessions took from 3.5 to 4 hours, and were generally focused and intense, with one or two very short breaks.Between September 2019 and March 2020, three rotations of students had successfully completed all TBL sessions in the live classroom. A fourth rotation had completed two of the required eight sessions in the live classroom when the COVID-19 pandemic supervened and forced all work online.th April 2020, necessitating the full transition to distance teaching. The fourth rotation group received two weeks classroom TBL, followed by 5 weeks online and the fifth rotation experienced the full teaching programme via online TBL. The onset of the pandemic necessitated the complete exclusion of all faculty, staff, and students from the campus. No lectures or small group teaching on-campus were allowed. Students were also excluded from clinical clerkships in the hospitals and peripheral clinics.A full lockdown in Dubai was implemented on 4Online teaching was implemented using Microsoft Teams, as video conferencing platform, and combined with an online e-learning platform . Microsoft Teams was used as a virtual classroom while the LAMS platform delivered the learning activities as per the TBL lesson plan.The first online session of TBL was piloted in mid to late March 2020. At this time, faculty and some staff were still allowed on campus, so faculty came to campus to deliver the session while students attended from home. This allowed piloting of the use of Microsoft Teams with TBL and remote facilitation with the use of software designed for TBL lesson delivery. Several Faculty were in attendance for the first remote session with students at home and Faculty on campus in the teaching room either facilitating and delivering learning material or observing how the process was working.Prior to the session, EG setup the LAMS system to include the activities, known as sequences in LAMS, to be conducted in the TBL session  and added all students to the system, assigned to their individual groups. At the beginning of the session, EJ facilitated an introduction to LAMS, showed the students how to join each sequence and remotely opened the gates as the students progressed through the stages. Initially, this freed up time for LJ to focus on the teaching process and group dynamics. Later, he introduced the discipline lead LJ to the process of moving students through the sequence.In order to permit the whole TBL process, it was necessary to pilot the use of channels in Teams to ensure students could easily move from a General meeting for the iRAT, to individual channels for the tRAT and application exercises, and then back to General channel for the plenary and discussion. Small group topic teaching relevant to a particular TBL session that day was delivered in the General channel.The already developed TBL teaching plans were incorporated into the LAMS sequence by EG without modification by LJ. MCQs for both iRAT and tRAT were transferred to the TBL lesson plan in LAMS and the case study for the application exercises inserted into the sequence after tRAT.The students completed the MCQ individually online (iRAT) in the General Team channel with EG, LP and LJ in the channels to ensure all went smoothly from the technical standpoint. Electronic scratch card within the software was very similar to the paper version and gave a similar experience as in the classroom.The students did not experience any major technical difficulties, with most having good internet connections. EG who organized orientation to the LAMS for Faculty and students, was based in Singapore four hours ahead of Dubai, and so the timing of the session in the fourth rotation from April to May was exactly the same as previous rotations, starting at 8:00am . For the fifth rotation, which coincided with the month of Ramadan, one student was based in Sudan two hours earlier than Dubai, and so timing was adjusted to 9:00am  to allow for both fasting and time zone differences.The investigation revolved around a qualitative descriptive approach to research. Phenomenology was used as the research methodology to understand the lived subjective experience of the participants. As part of this approach, researchers aim to explore how the phenomenon under study is perceived by those who experience and are involved in it first-hand. Ethical approval for the respective teaching initiative was granted by the MBRU, Institutional Review Board (Reference # MBRU-IRB-2019-015).All the students enrolled in the fourth and fifth rotations  were invited to participate in a survey, towards the end of their respective rotations. The survey aimed at exploring the participating students’ perception regarding the online TBL, and the transition to distance learning as part of the Family Medicine clerkship. Data were collected via online Microsoft Forms. The survey was composed of the following open-ended questions:•What were the highlights of the online TBL of the Family Medicine clerkship? (please specify two aspects of your experience)•What suggestions do you have for improving the application of the online TBL of the Family Medicine clerkship? (please specify two opportunities for improvement)In order to avoid any biases and to enable the students to express themselves freely, the survey was assembled by a stakeholder who was not involved in the learning and teaching aspects of the experience (FO). Participation in this data collection initiative was completely voluntary. The privacy and the data confidentiality of the students were protected, and no personal identifiers were recorded.Out of the 19 students who were invited to participate in this study, 18 students filled the survey (response rate= 95%). The fourth rotation (April to May) was composed of 9 students, who experienced two face-to-face sessions, and five online ones (Group A). As for the fifth rotation (May to June), it was composed of 10 students, who participated in seven online sessions (Group B). The flow of the academic year showing the timing of the study is illustrated inThe data analysis took place after the completion of the data collection phase. To structure the data analysis, each participant was assigned a unique identification number . The data were thematically analysed using Interpretative Phenomenological Analysis (IPA) , and made the TBL the most efficient and easy way to work with this method through online learning”In order for TBL to work online, it must be just as organised as in the classroom setting, otherwise there will be frustrations due to delays and potential for disengagement. Several students commented specifically on organisation and ease of use, either in relation to individual aspects (being able to see own and others’ answers), or in terms of the TBL process and timing which helped to keep everyone together despite the distance.12: “... the organisation around the iRATand tRAT, and (application) exercise...”16: “...it is all so organised, and allowed me to view my answers, and to compare them within the group, and across all the groups...’15: “...it was organised, and made sure we are all on the same track...”In classroom TBL, the students had not previously been able to select how confident they were about their answer in iRAT. They noted they liked this feature which was new to them. In the tRAT, they were able to see the confidence levels and discuss them among each other, triggering discussion about why there were differences within any one group. Students chose to use the confidence meter in differing ways, for example for a rough idea of confidence , or for more fine distinctions, with 10 or 20% increments.4: “...it was a great new experience...”5: “... the fact that we could record confidence levels...”6: “... to get to select our confidence percentage...”11: “...the confidence meter was unique and interesting; it solicited a lot of discussions...”Moreover, the ‘burning questions’ feature allowed teams to record questions for the facilitator and other students about answers they were uncertain about which triggered more discussion after TRAT. Rather than feeling daunted by seeing their own or each other’s answers, the students commented on the benefits they perceived in benchmarking themselves against others. One student in the fourth rotation felt worried about the fact that others could see their identified answers and briefly dropped out. After some counselling from the discipline lead to understand the purpose of this feature, and getting some feedback from the group, it was agreed that the feature would be kept as it triggered discussion. This was supported by the end of rotation feedback where no one felt concerned about the feature.8: “...we could see each other iRAT answers and confidence levels, and this facilitated discussions; we could ask burning questions...”14: “...seeing everyone’s answer was among the highlights of the overall experience...”17: “...allows me to see everyone’s answers to trigger discussion...”The students indicated that the platform design fulfilled its intended function to promote teamwork and collaboration, and was flexible enough to be changed in response to student feedback during the sessions.5: “...the constant effort of Mr. EG’s efforts in improving the case discussions section, where we all had the chance to type in our input added a lot of value to the experience...”7: “...it is a very-well designed platform, seamless moving between the process...I liked the ability to have multiple editors at the same time...’The students also noted some minor difficulties, that they faced at the beginning of their experience, indicating the existence of a learning curve.18: “...the movement between steps was a bit confusing initially, but I eventually got the hang of it...it was sometimes challenging to input the text but I liked that we all were able to do that...”They also identified a few opportunities for improvement.13: “...it would have been useful to provide the tutorial beforehand...”A lot of this constructive feedback focused on improving the application case document, where they ask for this document to be made ready for use, and for them to have control over the respective document and its content.3: “...allow more multimedia to be inserted...”6: “...set a time limit which could be viewed by the students on their screen directly, instead of having the instructor remind us of the time remaining...”7: “...adding pictures, screenshots to the answers of the cases...”8: “...give more formatting options ...adding images to the discussion section...colouring and highlighting the text of the discussion section...”10: “...to be able to add images and graphs in the case discussion box...the ability to add another team leader if need be...video access for a real-life experience...”This study demonstrated that combining videoconferencing and lesson delivery software together for TBL enables remote facilitation and completion of the Family Medicine curriculum, and that the students value this experience. Although our students and facilitators were spread across geographical locations, they were all able to work collaboratively in real time. The students completed their curriculum requirements, and remained occupied, and connected with their colleagues, Discipline Lead, and other facilitators throughout the rotation. It was also possible, despite the distance, to provide a supportive environment for the students, as well as flexibility for Adjunct Faculty whose timetables had been up-ended by redeployment to front-line COVID-19 duties.In recent published work, comparing online versus face-to-face TBL, students performed just as well in assessments, but expressed a preference for face-to-face TBL. This negative perception was attributed to some lack of familiarity with the platform which was used, and a lack of warning of an online component . The supThe COI framework provides a useful medium for discussing the online implementation of TBL and how it can be improved in future iterations. The COI framework consists of three, interconnected factors: social presence, teaching presence and cognitive presence .The implementation of the online TBL design was deliberate in ensuring as seamless a transition as possible for our students. Multiple communications from LJ prior each rotation beginning helped to set expectations and provided clear instructions to students on how and where to access materials and sessions. Introductory session on LAMS (EG), pilot of MS Teams and initial ice breaker (LJ) helped to develop knowledge and build trust community between the students and faculty. Ice breaker sessions especially helped to inform the design of groups to help enable all student voices to be heard.As illustrated in the framework that was generated as part of this study, the students emphasized the value and equivalency of the experience, and how they were able to remain connected throughout the journey. The students were satisfied with the efficiency and ease-of-use of the platform, and the overall organization of the online TBL, and felt their voice was heard within and in between sessions. The students also felt they had a voice to suggest further improvements, of which many were suggested as noted in the design theme of this framework.COI advocates for a teaching presence that is not central to the faculty, but as a role in which both students and faculty can assume at different points in the process. This enables student-centricity enabling students to assume more control of their learning. In our online implementation of TBL, student groups chose a team leader who assumed the teacher role and helped to cohere the group feedback and facilitate small group discussion. Throughout the sessions, core faculty acted as facilitators of discussions, using the feedback gathered from the LAMS software to guide discussions amongst the entire group of students.The design theme of the framework where the interface seemed to resonate well with the students, which can be related to both the social and teaching presence factors of the COI. During the beginning sessions, EG introduced and facilitated using the LAMS components which helped students feel supported in using the system and in getting comfortable with the online environment. Channels in MS Teams were utilized for small group discussions, which enabled LJ and EG to move between groups and facilitate any problems or stimulate discussion. Gradually throughout the sessions, EG and LJ were able to step back a bit as students became more autonomous and began to drive their own group discussion and develop their own methods of documenting their small group discussions. The role of the Discipline Lead (LJ) in facilitating the TBL process also to support team spirit with the students during the particular difficulties created by remote working during the pandemic.The cognitive presence, which is the extent to which learners are able to construct meaning and think critically through their participation in the community, was facilitated by both the features of the platforms used and the design of the TBL sessions themselves. The iRAT and tRAT stages of TBL serve as triggering events to inquiry and through breaking students into small groups in which one member assumes a leadership role, enables opportunities for active discourse. Finally, regrouping the entire class for further discussion promotes continues the exploration and integration of knowledge.Student responses relating to cognitive presence were largely expressed through the differing unique attributes of the platform such as: confidence rating and burning questions, which introduced novelty to the experience. The setting of confidence levels on the MCQs was particularly highlighted among both students and teachers as a unique measure to demonstrating levels of understanding. This feature was unique to the TBL online sessions and facilitated by the LAMS software. The collaboration approach to the case discussions was also noted by students as valuable to their TBL experience.Based on students’ perception, the combination of the videoconferencing and lesson delivery software (LAMS) served to improve the TBL experience. In reviewing published advice from the Team Based Learning Collaborative , including file storage and document retrieval. During the online TBL sessions, many documents and resources were shared with students via the video conferencing system. However, the LMS was the central repository for students to retrieve important documents such as their core course reading materials. To ensure clarity for the students, the Discipline lead monitored and transferred information which supported overall learning outcomes from the videoconferencing system, into the LMS.This study is characterized by several limitations. To start with, although this study reflected upon an important transition and offered plenty of in-depth insights to what took place, the investigation revolved around a single institution, in a very particular time. Hence, the generalizability of the findings is limited to situations that are comparable to that of this study. Moreover, the target population was limited to the students who underwent the respective clerkship online (n=19), out of which 18 voluntarily chose to participate. It is recommended for future studies to include a larger sample size, across several higher education institutions. It would also be valuable to complement the students’ narrative with quantitative data that tests the efficacy of the transition, be it with a pre-post assessment or otherwise.This study offers a unique demonstration of the value of agility in responding to a crisis, and illustrates the advantages of TBL in promoting analytical and self-directed learning even in extreme circumstances. Rather than ‘dumping’ lecture content on an online platform, with no interaction with students, the TBL sessions allowed the facilitators, including the Discipline Lead, to get to know the students, on a personal level, monitor and evaluate their performance, over time, facilitate real-time discussions, and enable effective student progression.•TBL content and structure can be seamlessly transferred from the classroom setting to an online environment.•Transitioning to an online platform that supports a learner centric process can enhance the TBL experience for students.•The Community of Inquiry provides a useful framework to design and evaluate effective online TBL learning experiences.•Working in channels on a conferencing platform facilitated teamwork.•With clear central coordination in distance learning, it is possible for all stakeholders to promptly adapt to change.Dr. Lisa Jackson is Associate Professor- Family Medicine, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE. ORCID ID:https://orcid.org/0000-0003-4161-6031Ms. Farah Otaki is Senior Specialist- Strategy and Institutional Excellence Department, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE. ORCID ID:https://orcid.org/0000-0002-8944-4948Ms. Leigh Powell is Senior Learning Designer, Institute for Excellence in Health Professions Education, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE. ORCID ID:https://orcid.org/0000-0001-6714-7371Mr. Ernie Ghiglione, Project Manager, LAMS International, Singapore.Professor Nabil Zary is Institute for Excellence in Health Professions Education, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE. ORCID ID:https://orcid.org/0000-0001-8999-6999 This review has been migrated. The reviewer awarded 4 stars out of 5 In a recent commentary  the editorial team commented on 39 articles describing adaptations that clinical educators had made in response to the first wave of the covid-19 pandemic. One of our conclusions was that we need research to evaluate the new strategies described. In this article by Jackson et al., research findings are presented about a pandemic-related adaptation at a medical school in UAE, and it is a timely response to the community’s need for data to drive curriculum development. The authors have completed a qualitative study, and thoroughly analysed their evaluation of online Team-based learning (TBL). In their introduction, the authors discuss principles of TBL and also appraise published evidence for its use as a valuable part of a medical curriculum and in particular recent applications of online versions of TBL. Readers will no doubt find the bibliography very useful in itself.In their evaluation, the authors reflect on the move to online TBL with respect to a community of enquiry model, exploring social presence, teaching presence, and cognitive presence. Although, this research must have been organised rapidly and conducted at a challenging time, research governance steps were thorough, and efforts to avoid bias are explained in the data collection section. Also, I noted the student-centred educational environment e.g. logistical adjustments based on learners’ needs.The writing is very engaging throughout, and the figures are helpful. I wish more articles had a study timeline illustrated with the clarity of figure 3.I have no expertise in the methodology and conventions for qualitative phenomenological research, so I have a question for the authors; how complete is the data presented in the results/analysis section – are the comments included comprehensive or representative?Another question, relates to conclusions around the use of video-conference platforms that allow break out rooms and multiple channels – do the authors think this could present opportunities for more efficient use of faculty time/ teacher presence in small group settings such as TBL and PBL?In the discussion, the authors outline one or two limitations that I had noted about the study design  and some of these were inevitable given that the research emerged from a natural experiment etc. I agree with a previous reviewer, that some of the abbreviations and terms could have been elaborated on as they were introduced.Overall, I really enjoyed reading this thought-provoking article and think there are generalizable findings for many other types of synchronous, online small group learning. Several sections resonated with my own experiences of using digital/online PBL since March and I will recommend it widely to facilitators and curriculum leads.Reviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 5 stars out of 5 This is an interesting and well-written manuscript on online TBL in a medical school in the United Arab Emirates. The authors have described the TBL process and the process followed during the study in detail. The diagrams help the reader understand the process. My suggestions for further strengthening the manuscript are: There are many abbreviations in the Abstract which can be expanded on first use in the manuscript. The authors should clarify that EG, LJ and LP mentioned refers to the authors of the study. I was confused for some time regarding this. I believe Sudan should be two hours behind Dubai. Time zones are a challenge to be addressed during online learning. What exactly do the authors mean by a discipline lead? How is TBL organized at the university? The modifications to the online TBL carried out at the university can be detailed. The authors can explain the confidence meter in greater detail. Also, the burning questions feature and the fact that each participant could see other’s answers during the iRAT.The student numbers are low, and the increased attention focussed by faculty and support staff on the students may have been partly responsible for their positive perception.Reviewer Expertise:NANo decision status is available