• Brain imaging and neuropsychological assessment of individuals recovered from mild to moderate #SARS-CoV-2 infection | medRxiv
    https://www.medrxiv.org/content/10.1101/2022.07.08.22277420v1

    Conclusions and Relevance :

    […] in our sample, a mild to moderate SARS-CoV-2 infection was not associated with neuropsychological deficits, significant changes in cortical structure or vascular lesions several months after recovery. External validation of our findings and longitudinal follow-up investigations are needed.

    #neurologie

  • HPI et surdoués, un diagnostic qui sert les intérêts d’une classe sociale
    https://www.ladn.eu/nouveaux-usages/non-votre-enfant-nest-pas-hpi-vous-etes-juste-riche

    La question n’est pas de remettre en cause l’existence de niveaux intellectuels différents, car la sociologie l’explique simplement : le cerveau étant plastique, plus les gens seront entraînés, plus ils seront forts. Les études montrent en effet que le quotient intellectuel (QI) est corrélé avec la classe sociale et le niveau de diplôme de parents. Mais là où les psychologues diront que le QI est le meilleur prédicteur de la réussite sociale ou scolaire, les sociologues avanceront l’inverse : l’accumulation de ressources culturelles fait le QI. Si la question est de savoir si les enfants identifiés comme HPI sont nés comme ça, plusieurs éléments tendent à prouver le contraire. Les statistiques indiquent qu’ils sont généralement issus des classes supérieures, qu’ils sont HPI à certains « moments » et pas à d’autres (la plupart des enfants testés le sont principalement en CE1 pour sauter le CE2, et à la fin de la moyenne section pour sauter la grande section), et qu’ils sont à 75 % des garçons. Ce dernier point crée une contrainte argumentative certaine, pour ceux qui « croient » aux HPI : les garçons seraient intrinsèquement plus intelligents que les filles ? En outre, se demander si les HPI sont vraiment HPI, c’est déjà se tromper de question. Il est plus judicieux de se demander pourquoi certains parents font tester leurs enfants, vont s’investir de cette question, et ce qu’ils en retirent.

  • Le virus mangeur de cerveau | Nature | oct. 2021

    https://www.nature.com/articles/s41593-021-00926-1

    The SARS-CoV-2 main protease Mpro causes microvascular brain pathology by cleaving NEMO in brain endothelial cells

    Abstract

    Coronavirus disease 2019 (COVID-19) can damage cerebral small vessels and cause neurological symptoms. Here we describe structural changes in cerebral small vessels of patients with COVID-19 and elucidate potential mechanisms underlying the vascular pathology. In brains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals and animal models, we found an increased number of empty basement membrane tubes, so-called string vessels representing remnants of lost capillaries. We obtained evidence that brain endothelial cells are infected and that the main protease of SARS-CoV-2 (Mpro) cleaves NEMO, the essential modulator of nuclear factor-κB. By ablating NEMO, Mpro induces the death of human brain endothelial cells and the occurrence of string vessels in mice. Deletion of receptor-interacting protein kinase (RIPK) 3, a mediator of regulated cell death, blocks the vessel rarefaction and disruption of the blood–brain barrier due to NEMO ablation. Importantly, a pharmacological inhibitor of RIPK signaling prevented the Mpro-induced microvascular pathology. Our data suggest RIPK as a potential therapeutic target to treat the neuropathology of COVID-19.

    • Des preuves d’invasion cérébrale | JEM | janvier 2021

      https://rupress.org/jem/article-standard/218/3/e20202135/211674/Neuroinvasion-of-SARS-CoV-2-in-human-and-mouse

      Neuroinvasion of SARS-CoV-2 in human and mouse brain

      Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus on the consequences of CNS infections. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in infected and neighboring neurons. However, no evidence for type I interferon responses was detected. We demonstrate that neuronal infection can be prevented by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstrate SARS-CoV-2 neuroinvasion in vivo. Finally, in autopsies from patients who died of COVID-19, we detect SARS-CoV-2 in cortical neurons and note pathological features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV-2 and an unexpected consequence of direct infection of neurons by SARS-CoV-2.

      via @Dowser

  • London taxi drivers: A review of neurocognitive studies and an exploration of how they build their cognitive map of London - Griesbauer - 2022 - Hippocampus - Wiley Online Library
    https://onlinelibrary.wiley.com/doi/10.1002/hipo.23395

    Eva-Maria Griesbauer,Ed Manley,Jan M. Wiener,Hugo J. Spiers
    First published: 16 December 2021 https://doi.org/10.1002/hipo.23395

    Abstract
    Licensed London taxi drivers have been found to show changes in the gray matter density of their hippocampus over the course of training and decades of navigation in London (UK). This has been linked to their learning and using of the “Knowledge of London,” the names and layout of over 26,000 streets and thousands of points of interest in London. Here we review past behavioral and neuroimaging studies of London taxi drivers, covering the structural differences in hippocampal gray matter density and brain dynamics associated with navigating London. We examine the process by which they learn the layout of London, detailing the key learning steps: systematic study of maps, travel on selected overlapping routes, the mental visualization of places and the optimal use of subgoals. Our analysis provides the first map of the street network covered by the routes used to learn the network, allowing insight into where there are gaps in this network. The methods described could be widely applied to aid spatial learning in the general population and may provide insights for artificial intelligence systems to efficiently learn new environments.

    1 INTRODUCTION
    The ability to navigate an environment depends on the knowledge of that environment. This knowledge can be gained in multiple ways, such as via instructions on GPS devices, memorizing a cartographic map, or through exploration. The knowledge formed can vary from very imprecise to extremely accurate, depending on the complexity of the environment, the level of exposure to the environment and individual differences (Ekstrom et al., 2018; Schinazi et al., 2013; Weisberg et al., 2014; Weisberg & Newcombe, 2016). Over the last decades, there has been increasing interest in understanding how different methods for learning impact the acquisition of spatial knowledge (e.g., Balaguer et al., 2016; Dahmani & Bohbot, 2020; Gardony et al., 2013; Hejtmánek et al., 2018; Ishikawa et al., 2008; Münzer et al., 2006, 2012; Siegel & White, 1975; Streeter & Vitello, 1986) and how individuals differ in their capacity to learn to navigate new environments (Burles & Iaria, 2020; Coutrot et al., 2018, 2019, 2020; Feld et al., 2021; Newcombe, 2018; Weisberg & Newcombe, 2016).

    Despite GPS devices being a preferred method of navigation for many (McKinlay, 2016), the increased use of GPS devices appears to have a negative impact on spatial memory (Dahmani & Bohbot, 2020; Ruginski et al., 2019) and is associated with habitual learning of a particular route (Münzer et al., 2006). In contrast to GPS-based instruction-guided navigation, “map-based navigation” (relying on memory for the map) has been found to support spatial learning, knowledge acquisition of the environment and improved flexible navigation performance (e.g., Ishikawa et al., 2008; Münzer et al., 2006, 2012). Such flexible navigation relying on long-term memory is associated with the construction of a cognitive map, which stores the allocentric information about the structure of the environment enabling shortcuts and efficient detours around unexpected obstacles (O’Keefe & Nadel, 1978; Tolman, 1948).

    A range of evidence indicates that within the brain the hippocampus provides a cognitive map of the environment to support memory and navigation (Epstein et al., 2017; Gahnstrom & Spiers, 2020; O’Keefe & Nadel, 1978) and damage to the hippocampus disrupts navigation (Morris et al., 1982; Spiers, Burgess, Hartley, et al., 2001). Hippocampal neurons encode spatial information (O’Keefe & Nadel, 1978) and for a selected group of individuals, who spend their daily lives navigating using map-based recall of space, their posterior hippocampal gray matter volume increases with years of experience and is larger than in the general population (Maguire et al., 2000). These individuals are licensed London taxi drivers. Here, we review the past literature from studies of London taxi drivers and explore how they learn the large amount of knowledge required to navigate London, which evidence suggests drives the changes in their hippocampus (Woollett & Maguire, 2011).

    2 A REVIEW OF RESEARCH ON LONDON TAXI DRIVERS
    Licensed London taxi drivers are unusual among taxi drivers. They are able to mentally plan routes across an environment that contains more than 26,000 streets within the six-mile area around Charing Cross, the geographic center of London (A to Z from Collins The Knowledge, 2020). They are required to have sufficient knowledge to also navigate main artery roads in the suburbs—known as “The Knowledge.” This area covers almost 60,000 roads within the circular M25 (The London Taxi Experience—The Knowledge, 2020; numbers may vary depending on sources, road types and the definition of the boundary of London). What makes licensed London taxi drivers unique is that they have to accomplish this using their own memory, without relying on physical maps or navigation aids. They are also the only taxi drivers permitted to pick up customers when hailed in the street, due to their license to operate. In the rest of this article, we refer to them as London taxi drivers, but readers should note that our analysis pertains only to licensed taxi drivers, who are also referred to as “London cabbies.”

    Changes in the hippocampal gray matter density in London taxi drivers were first reported by Maguire et al. (2000) using a cross-sectional study of London taxi drivers and magnetic resonance imaging (MRI) measures, including voxel-based morphometry (VBM). Maguire et al. (2000) speculated that because rodent and avian species can show variation in the size of their hippocampus with the demand on spatial memory (Lee et al., 1998; Smulders et al., 1995), it might be possible that London taxi drivers would show similar differences due to their profession. There were two main findings from this study: (i) compared to age and gender matched control participants, London taxi drivers had an increased gray matter density in their posterior hippocampus and a decreased gray matter density in their anterior hippocampus, (ii) years of experience was positively correlated with gray matter density in the right posterior hippocampus and negatively correlated with anterior cross sectional volume. Thus, there is no evidence for a globally larger hippocampus, but rather more experienced taxi drivers show a significant difference in the amount of gray matter along the long-axis of the hippocampus.

    Following the discovery of differences in hippocampal size in London taxi drivers by Maguire et al. (2000) numerous studies have explored their brain function and cognition. MRI has provided further evidence of structural differences in their hippocampus, with three further studies supporting the initial findings (Maguire, Woollett, & Spiers, 2006; Woollett et al., 2009; Woollett & Maguire, 2011). To provide a more precisely matched control group to London taxi drivers, MRI structural measures were contrasted between London taxi drivers and London bus drivers. If the gray matter changes in taxi drivers are driven by daily driving and/or daily exposure to London, then bus drivers should have a similar hippocampal size to taxi drivers as they daily drive routes through London. However, if it is using extensive spatial knowledge that underlies the differences in gray matter density then London taxi drivers and bus drivers should differ. Results revealed that compared to London bus drivers, London taxi drivers have increased posterior hippocampus gray matter density, decreased anterior hippocampal gray matter density (Maguire, Woollett, & Spiers, 2006), replicating previous results (Maguire et al., 2000). While bus drivers show no relationship between hippocampal volume and years of experience, London taxi drivers were again found to show a positive correlation between posterior hippocampal gray matter volume and years of experience (Maguire, Woollett, & Spiers, 2006).

    While cross-sectional studies of gray matter density provide evidence that changes in hippocampal volume may occur with exposure over time, they do not track individuals over time to provide a more reliable measure of structural changes with experience. Examining brain changes longitudinally within subjects, Woollett and Maguire (2011) found that an increase in the posterior hippocampus gray matter density after the years spent learning the Knowledge and passing the exam required to become a licensed taxi driver (Woollett & Maguire, 2011). Notably, taxi drivers showed no differences in hippocampal volume prior to starting training to non-taxi drivers, indicating that taxi drivers may not be predisposed to having a larger hippocampus as part of what predisposes someone to choose to train as a taxi driver. Intriguingly, those who failed to qualify did not show a change in their hippocampal size, indicating that it is not sufficient to spend time training, training must be applied effectively for changes in posterior gray matter density to become evident. Furthermore, cross-sectional evidence from measuring hippocampal size in medical professionals revealed no correlation between years of experience and hippocampal structural measures (Woollett et al., 2008). This suggests that it is unlikely to be storing the memory of all the street names that underlies the correlation between hippocampal volume and years of experience operating a London taxi.

    Following the discovery of gray matter differences in London taxi drivers a number of studies have explored the extent to which hippocampal size might predict navigation ability. The first study to explore this in a sample of 23 participants found no association between posterior gray matter volume and navigation ability on a virtual navigation task (Maguire et al., 2003). However, a number of subsequent studies have reported a relationship between measures of hippocampal structure and navigation performance (Bohbot et al., 2007; Brunec et al., 2019; Chrastil et al., 2017; He & Brown, 2020; Hodgetts et al., 2020; Konishi & Bohbot, 2013; Schinazi et al., 2013; Sherrill et al., 2018; see also Hao et al., 2017). More recently, two studies with larger samples have found no relationship between hippocampal structure and either navigation (Weisberg et al., 2019) or route sequencing (Clark et al., 2020). Thus it remains a matter of debate whether in non-taxi drivers there is a link between hippocampal structure and navigation performance (see Weisberg & Ekstrom, 2021 for review).

    Acquiring the Knowledge of London seems to come at a cost of learning and retaining new visuo-spatial information, which co-occurs with a concurrent volume decrease in the anterior hippocampus (Maguire, Woollett, & Spiers, 2006; Woollett & Maguire, 2009, 2012). However, in the small sample studied by Maguire, Woollett, and Spiers (2006) no significant correlation was present between anterior gray matter density reduction and the performance on visuospatial tasks. Functional neuroimaging studies have shown engagement of their posterior hippocampus when verbally recalling routes (Maguire et al., 1997) and at the start of the route when navigating a highly detailed virtual simulation of London (Spiers & Maguire, 2006a, 2007a). Other research with London taxi drivers has revealed insight into spontaneous mentalizing (Spiers & Maguire, 2006b), remote spatial memory (Maguire, Nannery & Spiers, 2006), emotions during navigation (Spiers & Maguire, 2008), the neural basis of driving a vehicle (Spiers & Maguire, 2007b), the features of street network that define a boundaries for navigation (Griesbauer et al., 2021) and the route planning process (Spiers & Maguire, 2008). London taxi drivers have also been shown to be better than non-taxi drivers at learning new routes (Woollett & Maguire, 2009).

    Despite the numerous studies exploring London taxi drivers, little attention has been paid to how London taxi drivers learn and memorize the layout and landmarks in London (Skok, 1999). Many questions arise when considering this. How is their exploration structured? What do they study when examining maps? How are map and physical travel experience integrated? What role does mental imagery play in aiding their learning? How do they exploit the hierarchical structure of London’s layout? Are major roads mastered before minor roads? In this observational report we provide the first investigation of London taxi driver’s learning process and the methods and techniques that enable them to retain and use such a large amount of real-world spatial information for efficient navigation.

    3 METHODS TO STUDY LEARNING OF THE KNOWLEDGE
    To understand the learning process of taxi drivers, different types of sources of information have been consulted. These sources included (a) a semi-structured interview (ethics approval was obtained under the ethics number CPB/2013/150) with a teacher from a London Knowledge school (here referred to as K.T. for “Knowledge Teacher”), (b) an email exchange with Robert Lordan, the author of “The Knowledge: Train Your Brain Like A London Cabbie” (Lordan, 2018), (c) an open introductory class of the Knowledge of London and regular scheduled classes for current students, (d) school specific study material, and (e) online information from the TfL (Learn the Knowledge of London, Transport for London, n.d.; Electronic blue book, 2019).

    The interview with the teacher from the Knowledge school was audio-recorded and transcribed. The transcription of the interview can be found in Appendix S1. The teacher gave written consent for the content of this interview to be cited and published. Additionally, attendances of Knowledge school training classes, including an introductory class and several classes with more advanced students, allowed us to observe and understand the training process in more detail.

    The information collected from these sources was systematically reviewed to report on (a) the ways spatial information is structured and presented for the learning process, (b) the techniques and methods used to learn this spatial information, and (c) how this knowledge is tested and the later perception of this knowledge as a taxi driver. A summary for each of these categories was created, starting with verbal reports (interview [Appendix S1], Knowledge school classes). This information was cross-referenced with and extended by unreported information from other, published, or official sources (e.g., study material, online booklets by TfL).

    4 OBSERVATIONS
    Taxi drivers in London have to demonstrate a thorough Knowledge of London within the six-mile radius originating at Charing Cross (see Figure 1a) to earn the green badge that qualifies them to drive a “black cab” taxi (Electronic blue book, 2019). Within this area, taxi drivers are expected to plan a route (i.e., the “runs”) based on the shortest distance between any two potential places of interest (i.e., the “points”) their customers might travel from or to, such as restaurants, theaters, hospitals, sports centers, schools or parks (cf. Electronic blue book, 2019, for a complete list). Taxi drivers are also expected to name all roads or streets that are part of that run in the correct, sequential order, including traveling instructions, such as turns (Electronic blue book, 2019).

    FIGURE 1


    The Knowledge of London and the Blue Book. (a) London taxi driver students are expected to learn the street network and all potential points of interest within the six-mile radius around Charing Cross (black circle), which is called the “Knowledge of London.” (b) To support the learning process of this area, the Blue Book was created. It contains 320 origin–destination pairs and the shortest route (i.e., “run”) connecting those pairs. When mapped chronologically in groups of 80 runs, the network of origin–destination pairs starts overlapping and becomes denser. Red: The first layer of the first 80 origin–destination pairs. Black: The second layer of the origin–destination pairs for runs 81–160. Purple: The third layer of origin–destination pairs for runs 161–240. Blue: The final layer of the last 80 origin–destination pairs for runs 241–320.
    Map sources: (a) Mapbox (2020) and (b) My Maps by Google Maps

    Historically, the exact roots of the Knowledge of London are unclear as written evidence is mostly missing. The first licenses and regulations for horse-driven carriages date back to the early 1600s by Oliver Cromwell (June 1654: An Ordinance for the Regulation of Hackney-Coachmen in London and the places adjacent, 1911; London Metropolitan Archives, 2013; Lordan, 2018; Newton, 1857). However, in 1851 the Great Exhibition in Hyde Park revealed incompetent navigation skills of the carriage drivers of those days. These initiated a series of complaints and forced authorities in the following years to set up stricter qualification requirements for drivers to test their knowledge of important streets, squares and public buildings (A to Z from Collins—The Knowledge, 2020; Lordan, 2018; Rosen, 2014). This scheme was officially introduced in 1865 (Learn the Knowledge of London, Transport for London, n.d.). The requirements in relation to the content of the Knowledge have since hardly changed and remained in place (The Knowledge, 2020) despite the technological innovations that have produced navigation aids, such as GPS devices, that facilitate and guide navigation. The following sections will outline how this is achieved by taxi drivers.

    4.1 Presentation of spatial information in Knowledge schools
    To help students to acquire the fundamentals of the Knowledge of London, the Blue Book (the origin of this name is unclear) was designed, which, in its current form, was put into place in 2000 (interview with K.T., Appendix S1). It contains 320 origin–destination pairs, their corresponding runs, as well as additional points related to tourism, leisure, sports, housing, health, education, and administration (Electronic blue book, 2019). In total, there are about 26,000 different streets and roads (Eleanor Cross Knowledge School, 2017) and more than 5000 points (Full set of Blue Book Runs, 2020) listed in the Knowledge schools’ versions of the Blue Book. However, this knowledge is incomplete. By the time students qualify, they will have extended their knowledge to identify more than 100,000 points (The London Taxi Experience—The Knowledge, 2020) in a street network of about 53,000 streets (OS MasterMap Integrated Transport Network, 2018). This covers not only the six-mile area, but extends to all London boroughs, including major routes in the suburbs.

    The 320 origin–destination pairs of the Blue Book with their corresponding runs are structured into 20 lists of 16 pairs each, which are designed to systematically cover the six-mile radius: In a chronological order, as listed in the Blue Book, the majority of origin–destination pairs have an origin in the same postal districts as the destination of the previous origin–destination pair and spread across London throughout each list (Electronic blue book, 2019). When mapped in layers of four, the first 80 runs (i.e., five lists) provide an initial rough coverage of London. This coverage becomes denser with each of the remaining three layers that are shifted slightly against each other to fill in the gaps (Figure 1b).

    Each of the origins and destinations in the Blue Book also require students to learn the nearby environment within the quarter mile range. That area around a Blue Book point is called the “quarter mile radius,” or in short: the “quarter-miles” and is considered as ideal for learning small areas of the environment without overloading students with information (interview with K.T., Appendix S1; Learn the Knowledge of London, Transport for London, n.d.; Electronic blue book, 2019). For the first and most famous run, which connects Manor House Station to Gibson Square, the quarter-mile radius is illustrated in Figure 2a. It contains about 8 additional points, numbered 1–8. These are chosen by each Knowledge school individually and can differ between schools. The additional points serve as initial motivation for students to explore the quarter-miles and learn which streets link these points to each other. Knowledge of the remaining, unmentioned points in the area will be obtained by each student gradually as they progress through the Knowledge of London by studying maps and exploring the quarter-miles in person.

    FIGURE 2


    Example of Knowledge school material in use. In Knowledge schools, wallpaper maps (a) are used to illustrate the coverage of London within the six-mile area by the quarter mile radii (b). These maps support the learning of relations between two places and clear up misconceptions such as Victoria being located further north than Waterloo, which is owed to a change in direction of the River Thames (c). “The cottoning up of two points,” a piece of string that is used to create a direct line between the points, is a common method to help with directional studies (c) and planning the most direct routes (d, e). Additionally, students use 50% and 75% markers along the direct line (e) to create subgoals that help to plan the runs
    Source: Knowledge Point School, Brewery Road, London, UK

    Mapping the origin–destination pairs with their corresponding quarter-miles, highlights how the areas locally link to each other (Figure 2b). To create such an overlap that sufficiently covers the whole six-mile area around Charing Cross (also see Figure 2a), 640 points are required, thus explaining the total number of 320 Blue Book runs. Since each point is closely surrounded by nearby origins and destinations of other runs, information is provided about how an area can be approached from or left in different directions. For Manor House (Figure 2b) these points have been indicated by blue and red quarter-miles for nearby origins and destinations, respectively, in Figure 2b. To visualize this information across the entire six-mile area of London and keep track of their progress while learning the Blue Book, trainee taxi drivers mark the origins and destinations, including the quarter-miles, in a large, all London map (Figure 2a,b; Source: Knowledge Point Central, Brewery Road, London, UK).

    Studying maps by visualizing the topological relationship between areas also helps to avoid misconceptions about the city’s geography that could lead to mistakes in route planning. For instance, deviations from the more generally perceived west–east alignment of the river Thames can cause distortions (cf. Stevens & Coupe, 1978). Often Victoria station, located north of the river, is incorrectly perceived further north than Waterloo Station, which is on the southern side of the river, but further east then Victoria (see Figure 2c). This misconception is due to a bend of the river Thames, that causes the river to flow north (instead of east) between Victoria and Waterloo.

    In the Blue Book, the 320 runs connect the origin–destination pairs through the route along the shortest distance for each pair (Electronic blue book, 2019). These pairs were chosen to create runs that are about two to three miles long and mainly follow trunk or primary roads. Here, trunk roads are the most important roads in London after motorways, providing an important link to major cities and other places of importance, with segregated lanes in opposite directions (Key:highway, 2020). Primary roads are defined as the most important roads in London after trunk roads, usually with two lanes and no separation between directions, linking larger towns or areas (Key:highway, 2020). Since these are often printed in orange and yellow in paper maps, taxi drivers also refer to them as “Oranges and Lemons” (interview with K.T., Appendix S1). Trainee taxi drivers visualize these runs on all London maps to learn and practice recalling them (Figure 2d, credit: Knowledge Point Central, Brewery Road, London, UK). Knowledge schools provide the 320 runs for the points of the Blue Book but encourage students to plan these runs before checking the up-to-date solution. To plan a run using the shortest distance and avoid major deviations (as required for the examinations), drawing the direct line (i.e., “as the crow would fly”) or spanning a piece of cotton between the points is essential (Figure 2e). This so-called “cottoning up” also helps students to learn relations between places (Figure 2c) and visualize the map to find ways around obstacles, such as Regent’s Parks, or to select bridges for crossing the river (Figure 2e) during the “call out” of the run (i.e., the recall of the street names in order along shortest route without using a map). Additionally, it provides opportunities to set subgoals, the “50% and 75% markers.” These markers are set where the line coincides with major roads or bridges, about halfway or three quarters along the line. These distances are guidelines only, and sometimes bullets are set at other distances for streets and places along the direct line that facilitate planning in stages. These markers help students to stay close to the direct line, while breaking down longer runs in smaller sections and reduce the number of steps they have to plan for at a time (Figure 2e). Due to one-way streets and turning restrictions, reverse runs from the initial destination to the initial origin can differ. Therefore, the streets and roads cannot simply be called in reverse order but have to be learned separately (Figure 3).

    FIGURE 3


    Runs and reverses runs. Due to one-way systems or turning restrictions, some runs differ when planned in reverse (dashed line), not allowing to simply invert the original sequence of streets taken (black line). This is the case for the run from Islington Police station (P) to the British Museum (B). When reversed, the one-way systems at Russell Square (1) and at Margery Street (2) require adaptation to traffic rules, resulting in differences between the runs and its reverse run. Figure is based on learning material from Taxi Trade Promotions
    The runs of the Blue Book form a network of routes that covers the six-mile area centered around Charing Cross (Figure 4a). However, the coverage of the London street network by the Blue Book runs systematically varies in density with respect to the distribution of points and the complexity of the street network: At its boundaries (Figure 4b) this network is less dense than in central London, where the runs are also overlapping more often (Figure 4c). This also reflects that more points are located closer to the center of London, whereas residential areas are more likely to cover larger regions at the boundaries of the six-mile radius. Similarly, areas of London with a more regular street network, such as in Marylebone and Fitzrovia, are covered by less runs (Figure 4d) than areas with a more complex and irregular street network, such as South Kensington and Chelsea (Figure 4e). These might require more practice to learn.

    FIGURE 4


    Network of Blue Book runs. A visualization of the 320 runs that connect the corresponding origin–destination pairs of the Blue Book forms a dense network of routes that overlaps, similar to the quarter mile radii (a). Across the network, density varies and is less dense closer to the six-mile boundary (b) then in Central London (c). This overlap also shows that more routes run through areas with higher irregularity in the street network (d) than areas of a more regular street network (e) in Central London
    Source: Adapted from Blue Book mapping by Prof Ed Manley, University of Leeds

    The Blue Book runs focus on connecting origin–destination pairs about three miles apart from each other. Since these are mostly main artery roads, they provide the main grid for efficient traveling between those origin–destination pairs. In contrast, minor roads and the areas between the Oranges and Lemons (i.e., main roads that are printed in yellow and orange in most maps) are learnt by studying the quarter-miles and linking the additional points in those areas (Figures 2a and 5b). Further understanding and flexible linking is gained from the Blue Book runs as students start considering continuations between them. For instance, one Blue Book run would have continued along a sequence of straight streets, but the run required a turn off from this straight sequence of streets to reach a destination. In contrast to the previous example, parts of a different run might continue straight, where the initial run required to turn off the straight sequence of roads. Both examples highlight the importance of the ability to flexibly use individual runs as part of the “bigger picture” (interview with K.T., Appendix S1).

    FIGURE 5


    The points of the Blue Book. Each origin–destination pair of the Blue Book is presented in relation to its quarter mile area. The origin of a run, here run 1 (a), Manor House Station, and the corresponding quarter mile radius (black circle) with additional eight other points of interest (numbered 1–8) are marked in a map. Labels are provided in a legend (left) and the most direct route (i.e., “run”) to the destination, including driving instructions (L on L: leave on left, L: left, R: right; F: forward) are listed on the right. The dense network of origin–destination pairs (b) results in an overlay of the neighboring quarter mile radii (black circles around purple arrows). For Manor House Station (purple circle) neighboring quarter-mile origins and destinations are highlighted in blue and red, respectively. These quarter-miles are covering the six-mile radius in London by linking places of interest through linking runs (c) as indicated by the dashed lines connecting run 1 (#) from Manor House Station and run 80 (!"), ending at Harringay Green Lanes Station.
    Source: Figures are based on learning material from Taxi Trade Promotions

    Ultimately, they cover large distances across London as such a combination of knowledge enables trainee drivers to link the Blue Book runs efficiently where they intersect, or through minor roads of the quarter miles where no intersection is available (Figure 2c). Over time, links become more efficient as the Knowledge is “ingrained” and minor roads are integrated to create shortcuts where possible. At this point, the Blue Book is no longer perceived as a list of individual routes, but as an entire network of runs (interview with K.T., Appendix S1).

    4.2 Learning methods
    The progress that Knowledge students have to make from learning the first points and runs to flexibly plan routes all across London is supported through a range of learning techniques as listed in Table 1. These methods can be categorized into theoretical, map-related studies and practical, “in situ” experiences (interview with K.T., Appendix S1; Lordan, 2018). Both support the development of planning strategies that are later used in situations where route planning is required. These include practicing the planning of Blue Book runs and general runs with a “call over partner” (i.e., a Knowledge school study partner) in preparation for exams and when driving a taxi as a qualified driver.

    TABLE 1. Learning techniques used in Knowledge schools
    Learning technique Supported skill and knowledge
    (A) Map study Bird’s eye view:
    General use of maps
    Visualizing street network
    Relational knowledge of streets and areas
    Areal knowledge (e.g., quarter miles)
    Traffic rules (e.g., one-way systems, turning restrictions)
    Sequential order of streets
    Dumbbell methoda,b
    Relational knowledge of places
    Areal knowledge
    Linking runs
    Flexible and efficient route planning
    Cottoning up
    Efficient route planning
    Relational knowledge of places
    50% and 75% markers
    Efficient route planning
    Relational knowledge of places
    Memory techniquesa:
    Acronyms and mnemonics
    Short stories
    Method of loci
    Historical connections
    Personal connections
    Memorizing groups of streets in consecutive order (1–3)
    Relational knowledge of streets in an area (e.g., quarter miles) (4)
    Visualizing street network (4)
    Relation to personal memories (5)
    (B) In situ experience In-street view
    Traveling in street
    Sequential order of streets
    Experience
    Mental simulation
    Visualizing places and streets
    Sequential order of streets
    (C) Combination of the above Bird’s eye and in-street view
    Call over partner
    Combination of all to simulate examination and fares
    Practice material
    Exam questions
    a Lordan (2018). b Learn the Knowledge of London.
    In general, maps are used to learn the structure of the street network from a bird’s eye view. They help obtain knowledge about relations between places and areas (e.g., quarter-miles and boroughs) and learn traffic rules that can limit route planning due to one-way systems and turning restrictions. Additionally, maps facilitate a better understanding of the sequential order of streets that are part of a run.

    Initially, when studying the Knowledge, this information is obtained mainly through the “dumbbell method.” This requires students to identify the quarter-miles of the origin and the destination and visualize the connecting Blue Book run by tracing it on the map. By including variations of origins and destinations from the quarter-miles on the map, students start to connect nearby points with the original Blue Book origins and destinations and create a network that is forming the “dumbbell” (Figure 3). This method is later extended to other places, as students learn to flexibly link runs and cover larger distances across London. This is also supported by the “cottoning-up” and the use of subgoals, called the “50% markers,” which are not included in the blue book and must be determined by the trainee (interview with K.T., Appendix S1). These 50% markers (not always chosen halfway along the direct line) are bridges if the river needs to be crossed to ensure efficient planning through these bottlenecks at early stages, or other major roads and places. Additional subgoals are added before and after, as needed, to help give initial direction for the route planning without overwhelming the students. Both methods, the “cottoning-up” and the “50% markers,” when used during initial stages of the training, help students to correctly visualize the map and relations between places. At a later stage of the Knowledge, when route planning is carried out mentally and without a physical map, these methods are integrated in the planning process automatically. Notably, the process involves focusing on distance rather than time between locations. The route with the shortest distance might be extremely slow, but during the training taxi drivers are required to find this route. This relates to the assessment used which uses distance to determine the correct answer (see Section 4.3). After qualifying drivers taxi drivers describe incorporating time into their choice of routes.

    To help students memorize sequences of street names that are often used for runs, different memory techniques are applied during the learning process and often remembered years after obtaining the license. The most common techniques are creations of acronyms and mnemonics, inventions of short stories that contain street name references, mental walks through rooms of an imaginary house, historical connections and personal memories that logically structure (cf. Table 2, Lordan, 2018). Trainees use the range of techniques in combination to learn, rather than starting with one method and moving to another. Thus, the learning techniques listed in Table 2 provide a set of cognitive tools for learning the layout of London.

    TABLE 2. Common memory techniques to learn runs
    Technique name Example Streets or places Run Book reference
    Acronym “MEG”
    (1) Melton St

    (2) Euston Rd

    (3) Gower St

    (4) …

    121 p. 22
    Mnemonic
    A: “bask under nice fair weather”

    (1) Blackfriars Bridge

    (2) Unilever Circus

    (3) New Bridge St

    (4) Farringdon St

    (5) West Smithfield

    153 p. 26
    B: “little apples grow quickly please”
    Lyric, Apollo, Gielgud

    Queen’s, Palace

    (order of Shaftesbury Av theaters)

    – p. 20
    Short story “In the scary monster film (1), the creatures burst out from behind the closed doors, riling (2) their victims with sheer terror (3). […]”
    (1) Munster Rd, Filmer Rd

    (2) Rylston Rd, Dawes Rd

    (3) Sherbrooke Rd

    (4) …

    20 p. 92
    Method of loci “On the wall of the lobby are several framed certificates (1). Below them is a bookcase where a guide to New York City sticks out, the cover of which is illustrated with an image of Park Avenue (2). A train ticket to Macclesfield is tucked inside as a bookmark (3). […]”
    (1) College Crescent

    (2) Avenue Rd

    (3) Macclesfield Bridge

    (4) …

    7 p. 148
    History
    “It’s believed that Copenhagen House was named either in honor of the King of Denmark or the Danish Ambassador, both of whom stayed there in the 17th century.

    Consequently the first roads on this run have a Danish theme. Matilda Street is named after Queen Caroline Matilda who was born in London but became Queen consort to Denmark after her marriage to Christian VII. […]”

    (1) Matilda St

    (2) Copenhagen St

    (3) …

    2 p. 106
    Experience
    “I remember arriving at Manor House very early one Sunday morning; it was cold and misty and, as I expected many fellow students did, had a brief moment of crisis when I asked myself what on earth I was getting myself into.

    But this thought was quickly expelled when I stood up to stretch my legs – and promptly trod in some dog mess, which in hindsight was probably a symbol of good luck although it certainly did not feel like that at that time. […]”

    (1) Manor House

    (2) …

    1 p. 190
    Source: Adapted from Lordan (2018).
    Location specific information from an in-street view is learnt through “in situ” visits to the 320 origin–destination pairs of the Blue Book, their quarter-miles and driving the corresponding runs. These visits—carried out multiple times, often on a scooter with a map of the Blue Book run attached to the windscreen—are essential to learning and recalling the Knowledge. These experiences of runs and the quarter miles create memories that drivers use to later recall sequences of streets (Table 2, Lordan, 2018) and visualize routes during planning (interview with K.T., Appendix S1). For instance, memories of traveling a run for the first time might help the recall of sequences of streets, places of interest and specific traffic rules that must be obeyed. These memories become an essential source of information when planning and calling out similar runs, linked to the original. Students use them for mental simulations that facilitate decisions about where to pick up or set down passengers, in which direction to leave or to approach an area and how to find the most optimal route. Thus, students incorporate their study from maps into egocentric representations of directions and turns when driving the runs in situ and this is vital for the planning process. Trainees are not paid so the process of learning is expensive as well as time consuming.

    4.3 Assessment scheme
    The assessment scheme for trainee taxi drivers in London was designed to support the learning process and guide students from early stages of learning the initial Blue Book runs to final stages, where their knowledge of London and suburban artery roads is rigorously challenged (Figure 6; interview with K.T., Appendix S1, Learn the Knowledge of London, Transport for London, n.d.). Initially, Knowledge schools offer an introductory class to provide basic information and an overview of the content of the Knowledge. This introductory class includes expectations, procedures, and requirements of the qualification process, before preparatory examinations (Figure 6, light gray) can be taken. Within the first 6 months of starting the Knowledge, students are expected to sit an assessment that is testing the Knowledge on the initial 80 runs (five lists) of the Blue Book. Even though this assessment is unmarked, it is obligatory and of supportive and informative purpose at the same time (i.e., formative assessment). Feedback is given and the performance is discussed with teachers to help students identify problems in their learning process that need adjustment at an early stage to enable students to successfully progress at later stages. Following this initial self-assessment, students have 18 months to sit a marked multiple-choice exam that tests their knowledge of the Blue Book, to ensure they have acquired the basics that are necessary to progress to the appearance stages (Figure 6, dark gray). To test this, the multiple-choice exams consist of two parts, where (a) the shortest, legal route out of three possibilities has to be identified for 5 randomly chosen Blue Book runs, and (b) the correct location out of six possible locations has to be selected for 25 points of interest that are likely to be part of the learning of the Blue Book runs.

    FIGURE 6


    Knowledge examination process. The initial stage (light gray) of the Knowledge examination process provides feedback (Self-Assessment) on the individual progress of learning the first 80 runs of the Blue Book and assesses the minimum knowledge on all 320 Blue Book runs needed (Multiple Choice Exam) to start the oral examination (Appearances). The main part of the examination process (dark gray) consists of a series of oral examinations, the so-called “appearances,” consisting of three different stages (the 56s, 28s, and 21s, named after the intervals between each exam in the corresponding stage). Even though the requirements to students sitting these exams become more rigorous as they proceed, there are general rules that apply across all stages. These are related to the general layout of each appearance (e.g., duration, number of runs), expectations (e.g., shortest route), format of call out (e.g., identifying the location of origin and destination, sequentially naming streets and providing turning instructions), penalties (e.g., traffic rule violations, deviations from shortest route, hesitations), awarded points and progressing to the next stage. Following the appearances, students are required to pass an exam on suburban Knowledge before they obtain their license
    Source: Adapted from Learn the Knowledge of London; Knowledge of London learning and examination process, p. 21

    After passing the two entry assessments, trainee taxi drivers enter what is known as the “appearances,” a set of oral examinations. At each appearance, students are expected to call runs from any two points that the examiner names. The appearances also comprise the longest and most difficult part of the Knowledge examination process. It is quite common that several of the stages have to be retaken by students due to shorter intervals between appearances coupled with the growing expectations of the examiners as they proceed. In total, there are three stages of appearances, the 56s, 28s, and 21s, which correspond to the number of days between any two appearances in that stage.

    Even though the requirements for students sitting these exams become more rigorous as they proceed, there are general rules that apply across all stages: Each appearance is about 20 min long and can consist of up to 4 runs that students have to call, using the shortest route, disregarding traffic and temporary roadworks. The call outs (i.e., naming streets in sequential order) include identifying the location (i.e., the correct street) of the origin and destination (points of interest), naming streets and giving turning directions along the run in correct sequential order, as well as including instructions for leaving and setting down passengers. Possible errors that will cause deductions of points are incorrect street names, any divergence from the shortest route, violation of traffic rules, impossible leaving or setting down instructions and hesitations during the call of the run. In each appearance, 3–6 points are awarded and 12 points are needed to progress to the next stage. Per stage, students are allowed to fail a maximum of three appearances, before the stage has to be repeated (first time) or students have to go back to a previously successfully passed stage (failing second time), limiting the number of exams per stage to a maximum of seven appearances.

    In contrast to later appearance stages, the “‘56s” are very closely related to the Knowledge obtained from the Blue Book. Here, examiners closely stick to runs from the Blue Book, which reflects a good knowledge of primary and secondary roads (i.e., the “oranges and lemons”). At this stage, examiners also take into account differences in the choice of additional points of the quarter-miles that different Knowledge schools provide in their version of the Blue Book (Figure 2a). Additionally, runs are structured in a way that they will not contain obstacles (e.g., road closures), special requirements (e.g., requests to avoid traffic lights) or theater shows and temporary events (e.g., Chelsea Flower Show). Students are also allowed to correct mistakes by going back in their call out and changing their run. At the next stage, the “28s,” examinees are expected to be able to link runs, using some minor roads and avoid obstacles or comply with special requests without being granted a chance of correcting faulty runs. At the final stage, the 21 s, trainee drivers have to demonstrate an overarching knowledge that is up to date and can additionally refer to particular topics (e.g., new tourist attractions, changes in hotel names) and temporary events, such as the Chelsea Flower Show.

    After passing all appearances, the final exam is set to test the knowledge of suburban London. This knowledge covers 22 specific routes, including major points along those routes, radiating from the six-mile radius to the borough boundaries of London. In this final appearance, trainee drivers will be asked six questions relating to the 22 routes and points along those routes.

    For the learning process of a Knowledge student, the Blue Book is central, as it provides them with “the ability to know where streets and roads are going to and where all those places are” (interview with K.T., Appendix S1). However, over the course of obtaining the Knowledge and learning how to link Blue Book runs efficiently, there seems to be a change in the perception of London. Initially it consists of distinct routes and locally focused areas on a map. Over the course of time, this fades into a connected, large-scale, inseparable network of streets and places in the real world (Appendix S1). During consulting conversations with taxi drivers, they reported that they just knew where they had to go without much planning. For well-known places, Robert Lordan described the planning and execution of a run as “I wouldn’t even have to think; my brain would be on autopilot. […] like a moth drawn to a light!” (email conversation with Robert Lordan, Appendix S2). For longer distances, subgoals (as trained with the 50% markers) are used automatically: “I’d find that my brain would often plan in stages; essentially I’d envision a set of waypoints and the route would then come to me as I progressed” (email conversation with Robert Lordan, Appendix S2).

    The overall impact of the Knowledge also seems to foster a deeper connection (“I already loved the city, but in studying it I now love it all the more. It feels like an old, familiar friend,” email conversation with Robert Lordan, Appendix S2). It provides a constant drive to stay up to date with changes in the city (“The Knowledge made me crave detail! To this day I want to know as much as I can about London,” email conversation with Robert Lordan, Appendix S2) and new curiosity (“The Knowledge also makes you want to know as much as you can about new locations that you’ve never been to before,” email conversation with Robert Lordan, Appendix S2).

    5 DISCUSSION
    Here we examined the process by which licensed London taxi drivers learn and are examined on the Knowledge of London, which includes the network of ~26,000 streets and thousands of points of interest. In summary, to learn the Knowledge of London, taxi drivers use a wide range of theoretical and practical methods and learn specific methods for efficient planning. Such training primarily includes map-related study, based on an overlapping network of basic points of interest and list of routes (Blue Book) that systematically covers London. This knowledge is combined with visits to the locations used in the routes and retracing of the theoretically learnt routes on motorbikes. Both experiences are reported to be vital for linking theoretically learned information to specific real-world locations and flexible navigation in London. We also observed a range of techniques to improve memory, such as acronyms and stories linked to sequences of streets, visualizing the locations and travel along streets, and the strategic use of subgoals. We discuss: (i) how these findings relate to other studies examining spatial learning, (ii) how the learning compares with taxi drivers in other cities, (iii) why the knowledge is still required and trained when GPS aided navigation systems exist, and (iv) how these methods and techniques might benefit the general population in spatial learning.

    Research based studies of spatial navigation have employed a variety of methods to train participants learning unfamiliar environments. These include instructed learning of paths (e.g., Brunec et al., 2017; Meilinger et al., 2008; Meilinger, Frankenstein, & Bülthoff, 2014; Meilinger, Riecke, & Bülthoff, 2014; Wiener et al., 2013), learning from cartographic maps (e.g., Coutrot et al., 2018, 2019; Grison et al., 2017; Hölscher et al., 2006, 2009), landmark-based navigation (e.g., Astur et al., 2005; Newman et al., 2007; Wiener et al., 2004, 2012, 2013; Wiener & Mallot, 2003), exploration of the environment without a map (e.g., de Cothi et al., 2020; Hartley et al., 2003; Spiers, Burgess, Hartley, et al., 2001; Spiers, Burgess, Maguire, et al., 2001) or a combination of map study with in situ exploration (e.g., Javadi et al., 2017; Javadi, Patai, Marin-Garcia, Margois, et al., 2019; Javadi, Patai, Marin-Garcia, Margolis, et al., 2019; Newman et al., 2007; Patai et al., 2019; Spriggs et al., 2018; Warren et al., 2017; Wiener et al., 2004; Wiener & Mallot, 2003). The general assumption is that the method used for learning is efficient, or a standard way of learning the environment. Here we found that for London taxi drivers the training is significantly more intensive and elaborate than any of these studies, which relates to the dramatically increased demands of learning 26,000 streets and thousands of points of interest.

    Several methods for learning, such as guided turn-based navigation (e.g., Wiener et al., 2013), have not found an application in the training phase of London taxi drivers. The absence of this approach might be explained through the advantage of in situ experience, understanding the changes with lighting over day time and the very regular changes to the environment (e.g., temporary road closures, name changes of hotels or restaurants, and temporary events). Indeed, being able to adapt to these changes and being aware of some of the temporary events are considered essential knowledge, especially at later stages of the training process.

    Successfully recalling mental images of locations, retrieving specific street names and judicious uses of subgoal planning were described as key to being a London taxi driver. These observations help to explain results of by Spiers and Maguire (2008) where London taxi drivers were asked to recall their thoughts watching video replay of their navigation of a highly detailed virtual reality simulation of London. London taxi drivers often reported sequential planning to subgoals along the route, comparison of route alternatives or mental visualizations of places and route sequences. Many taxi drivers reported “picturing the destination,” planning with a bird’s eye view, and “filling-in” the plan as they navigated, which indicate a use of mental visualization as trained through the Knowledge. We found teachers and examiners claim to know when students “see the points” as they actively visualize origins and destinations as part of their planning process. It may be that trainee taxi drivers need some ability with mental imagery to succeed in the train process. Not all trainees will pass the examination process (Woollett & Maguire, 2011). The ability to use spatial visualization strategies has been found to differ between individuals and vary with age and experience (Salthouse et al., 1990), education levels or gender differences (e.g., Coluccia & Louse, 2004; Fennema & Sherman, 1977; Moffat et al., 1998; Montello et al., 1999; Wolbers & Hegarty, 2010). There is also evidence that certain spatial visualization skills can be improved through training (Sorby, 2009). In our study we found that it was expected that the visualization improves with the training. Further investigation of the visualization process in novice trainees and expert drivers would be useful and may relate to the changes in the hippocampus observed in those that past the exam to obtain a license (Woollett & Maguire, 2011). The multifaceted learning approach reported here may relate to why changes in gray matter density have consistently been observed in taxi drivers.

    Further evidenced use of mental simulation during navigation was found in the way taxi drivers are required to call out the runs in the exam by using instructions and phrases such as “forward,” “left/right into,” and “comply” (traffic rules). These provide an egocentric description of movement through London. Conversely, during the early stages of the Knowledge training, the planning process is reported to rely on an allocentric reference frame by studying maps to train students on planning shortest paths. At later stages, as experience is gained from planning runs and through in situ visits to locations, the aim is to build an automatic awareness of the direction of travel or a particular route. This is consistent with the reports that experienced taxi drivers very rapidly determined the direction to a requested destination (Spiers & Maguire, 2006a, 2008).

    We found that the examination process appears to provide a layered approach to learning the London street network. There is an initial focus on testing the Blue Book routes (runs) or routes along main arterial roads (i.e., “oranges and lemons”) and only at later stages are minor roads integrated into the assessments. However, we found the actual learning process requires students to learn minor roads in the quarter-miles from the beginning (i.e., with the first run). This differs from the requirements in other cities, such as Paris, where drivers have to demonstrate knowledge of a limited number of major points of interest, as well as predefined major routes. There, taxi drivers are expected to expand their knowledge to the minor street network through experience while working as a taxi driver (Préfecture de Police, Démarches, & Services, 2020; Skok, 2004). Similar to the “oranges and lemons” of the London street network, the Parisian street network covers the city in two layers: The base network, an uneven grid-like pattern that allows travel on major roads, helps to reduce traffic on the secondary network, a network of minor streets (Chase, 1982; Pailhous, 1969, 1970, 1984). For Parisian taxi drivers, such a selective learning of the base network was found to be also reflected in their mental representation of the street network in form of these two layers (Pailhous, 1969, 1970, 1984). In contrast to London taxi drivers, Parisian taxi drivers’ awareness of the secondary network only grows and becomes more efficient and optimal through experience rather than in the training and is almost nonexistent at the beginning of their career (Chase, 1982; Giraudo & Peruch, 1988, 1988b; Peruch et al., 1989).

    The approach that London has taken to train and test their taxi drivers on the Knowledge as described above, is historically motivated and has been retained over centuries since its implementation, only allowing for adaptations and improvements. This concept of learning all possible points, their locations, the street names and how to flexibly plan routes and adjust to specific requirements is globally unique. In contrast, other cities, such as Paris (Préfecture de Police, Démarches, & Services, 2020) or Madrid (Federación Profesional del Taxi de Madrid: Departamento de Formación, 2010; Skok & Martinez, 2010), often only require applicants of the trait to learn the major grid of the street network (i.e., the base network) and expect the knowledge of the minor street network (i.e., the secondary network) to be obtained through experience. Instead, taxi drivers are also required to demonstrate knowledge on other trade related areas, such as knowledge related to driving a car, professional regulations, safety and business management, a language test (Skok, 2004), fares and legislations (Skok & Martinez, 2010). Considering these alternative qualification requirements for Paris or Madrid, the London qualification scheme, that relies on a thorough knowledge of London streets, can be questioned as regards to its adequacy and value, in times of GPS systems that can guide navigation.

    Given that GPS in general successfully supports navigation and thus is omnipresent in daily life, it remains a key question as to why London taxi drivers continue to rely on their own abilities to plan routes. We found that this to be their sense of accomplishment of a difficult, and in this case, almost impossible task. They often find pride in their ability to master challenging navigation tasks in a complex city only by using their spatial memory independently from external devices that could be sources of mistakes (McKinlay, 2016). This ability to flexibly navigate beyond a base network of major streets, enables London taxi drivers to rapidly follow their route plan even to points in the secondary network, quickly adapt to any changes on-route due to customer preferences or traffic flow (i.e., congestion or road closures) and avoid errors that might result from incorrect instructions given by passengers (e.g., Lordan, 2018). For instance, they might confuse Chelsea’s buzzing shopping mile, King’s Road, with the quiet King Street near St James’s Park, Westminster. These adaptations, that taxi drivers can make instantly, might even outperform GPS systems that sometimes need manual adjustments and additional information input to get to a similar result. In contrast to London, it takes taxi drivers in Paris, Madrid and other cities years to acquire this type of knowledge in their cities and in the end, they might never achieve a similar, highly accurate knowledge of their cities as some areas might be less frequently traveled. Moreover, their experience to filling the gaps in their knowledge might strongly rely on their use of GPS devices, which have been found to impair spatial learning (e.g., Ishikawa et al., 2008) and interfere with spatial navigation (Johnson et al., 2008; McKinlay, 2016). These methods of training taxi drivers might be less efficient and it is thus not surprising that there have been requests from taxi trades of cities like Tokyo, asking London Knowledge teachers to develop a similar method for their taxi schools (interview with K.T., Appendix S1).

    How might the Knowledge training process be improved? The Knowledge in its current form, based on the 320 Blue Book runs, has been in place for about two decades, but the study methods have remained the same over many more decades. However, there has been a tendency of involving new technologies and creating online resources, such as apps that can hold and test students on the Blue Book runs. By providing the first plot of all the blue book runs we were able to identify regions in the road network that were poorly sampled and it may be possible for this information to be useful should new routes be required in updating the runs.

    It is possible that a database of videos of Blue Book runs would be useful. However, updating this database is a challenge due to the regular change in London’s appearance and layout. Online maps and applications could provide a platform that could be regularly updated. Here, the focus could be on Knowledge requirements that allow general contribution, similar to OpenStreetMaps (n.d.), and individual modification, as with Google My Maps (Google Maps. My Maps, n.d.), to support the individual learning process. Such a platform could include updates on points asked in recent appearances that students use for preparation or an option to train with and challenge other students, as well as their call-over partner. Past research has shown it is possible to probe navigation effectively using Google Street View (Brunec et al., 2018, 2019; Patai et al., 2019). However, these platforms would not be able to replace the social situations that students find themselves in at Knowledge schools and when practicing face to face with their call-over partners. These social interactions also have a psychologically motivating, supportive effect. Neither can these digital maps overcome some obvious visual limitations due to screen sizes. These will not allow for a similar view of the “bigger picture” that a wallpaper map is able to convey.

    How might the learning process described here be exploited for the general population to learn new places, or emergency workers, or those with wayfinding difficulties caused by a clinical condition? A number of recommendations could be made. One is the focus on street-names. Much navigation in cities can be based on landmarks and the rough knowledge of the area. Recent work has explored how navigation could be improved by enhanced acquisition of landmark knowledge using audio information (Gramann et al., 2017; Wunderlich et al., 2020; Wunderlich & Gramann, 2019). While landmark acquisition is important for navigation (points of interest for the taxi drivers), our analysis of how London taxi drivers learn shows the extra value of learning street names. Learning the street names makes it possible to plan precise paths through the network of streets. This allows for flexible planning that goes beyond chaining sets of landmarks together. This learning can be enhanced by a focus on methods to draw out the street names such as acronyms and rhymes (“East to West Embankment Best”). The memory techniques used in Knowledge schools to memorize sequences of streets such as the “dumbbell method” that links small areas through routes, or mental visualizations of familiar places could initiate new ways of displaying spatial information in maps or GPS devices. A focus on mental imagery is also worth considering in future research to explore how this may benefit new navigation. Finally, teaching a method for efficient planning of longer routes would be a benefit. More research will be required to fully explore these possibilities and understand how they may be integrated with other technology for efficient spatial learning. In such research understanding the order in which information and training is provided would be an important step. Trainee taxi drivers do not have a set order by which they use the different methods, other than the prescribed order in which they learn the blue book runs. Future route guidance systems for learning a new environment might exploit the approach of integrating a set of routes as taxi drivers do here.

    Another question arising is how might these discoveries be useful for researchers seeking to build efficient artificial intelligence systems capable of rapid learning and planning? Recent work has explored methods for learning environments and navigating them from street view data or video (Hermann et al., 2020; Mirowski et al., 2016; Xu et al., 2021). The main discoveries here that may be relevant are (1) the organized learning of a set of interconnected routes that allows for flexible planning in the future, (2) the focus on learning a route and then exploring the points at the start and end and then connecting the route to other routes, and (3) learning to create subgoals during the planning process. These approaches to learning may extend not just to improving guidance for how humans learn but for considering the construction of agents that optimally learn structures in the layout of a large city network.

    In conclusion, studying the training process of licensed London taxi drivers has provided a useful opportunity to better understand learning strategies and methods that efficiently support the learning process of a large and complex environment. In this observational report, information was gathered on licensed London taxi drivers, who acquire unique spatial knowledge to navigate an enormous street network independently from external support, such as GPS. Forming such mental representations of real-world spaces is essential for the job they perform. Essential strategies include memory techniques, map-based strategies using tactical subgoal selection to improve planning efficiency and mental visualization of places and routes based on experiences. Further research is needed to understand the mental representation that results from these training methods and how this representation affects navigation related planning in brain circuits including the hippocampus.

    #Taxi #Neurologie #Hirnforschung

  • London taxi drivers: A review of neurocognitive studies and an exploration of how they build their cognitive map of London - PubMed
    https://pubmed.ncbi.nlm.nih.gov/34914151

    Eva-Maria Griesbauer 1, Ed Manley 2 3 4, Jan M Wiener 5, Hugo J Spiers 1, PMID: 34914151 DOI: 10.1002/hipo.23395

    Abstract
    Licensed London taxi drivers have been found to show changes in the gray matter density of their hippocampus over the course of training and decades of navigation in London (UK). This has been linked to their learning and using of the “Knowledge of London,” the names and layout of over 26,000 streets and thousands of points of interest in London. Here we review past behavioral and neuroimaging studies of London taxi drivers, covering the structural differences in hippocampal gray matter density and brain dynamics associated with navigating London. We examine the process by which they learn the layout of London, detailing the key learning steps: systematic study of maps, travel on selected overlapping routes, the mental visualization of places and the optimal use of subgoals. Our analysis provides the first map of the street network covered by the routes used to learn the network, allowing insight into where there are gaps in this network. The methods described could be widely applied to aid spatial learning in the general population and may provide insights for artificial intelligence systems to efficiently learn new environments.

    Keywords: cognitive maps; learning strategies; navigation; spatial cognition; spatial learning; wayfinding.

    #Taxi #Neurologie #Hirnforschung

  • London taxi drivers and bus drivers: a structural MRI and neuropsychological analysis - PubMed
    https://pubmed.ncbi.nlm.nih.gov/17024677

    Eleanor A Maguire 1, Katherine Woollett, Hugo J Spiers, PMID: 17024677 DOI: 10.1002/hipo.20233

    Abstract
    Licensed London taxi drivers show that humans have a remarkable capacity to acquire and use knowledge of a large complex city to navigate within it. Gray matter volume differences in the hippocampus relative to controls have been reported to accompany this expertise. While these gray matter differences could result from using and updating spatial representations, they might instead be influenced by factors such as self-motion, driving experience, and stress. We examined the contribution of these factors by comparing London taxi drivers with London bus drivers, who were matched for driving experience and levels of stress, but differed in that they follow a constrained set of routes. We found that compared with bus drivers, taxi drivers had greater gray matter volume in mid-posterior hippocampi and less volume in anterior hippocampi. Furthermore, years of navigation experience correlated with hippocampal gray matter volume only in taxi drivers, with right posterior gray matter volume increasing and anterior volume decreasing with more navigation experience. This suggests that spatial knowledge, and not stress, driving, or self-motion, is associated with the pattern of hippocampal gray matter volume in taxi drivers. We then tested for functional differences between the groups and found that the ability to acquire new visuo-spatial information was worse in taxi drivers than in bus drivers. We speculate that a complex spatial representation, which facilitates expert navigation and is associated with greater posterior hippocampal gray matter volume, might come at a cost to new spatial memories and gray matter volume in the anterior hippocampus.

    (c) 2006 Wiley-Liss, Inc.

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    PMID: 10716738 Free PMC article.
    Navigation expertise and the human hippocampus: a structural brain imaging analysis.
    Maguire EA, Spiers HJ, Good CD, Hartley T, Frackowiak RS, Burgess N.
    Hippocampus. 2003;13(2):250-9. doi: 10.1002/hipo.10087.
    PMID: 12699332 Clinical Trial.
    Navigational expertise may compromise anterograde associative memory.
    Woollett K, Maguire EA.
    Neuropsychologia. 2009 Mar;47(4):1088-95. doi: 10.1016/j.neuropsychologia.2008.12.036. Epub 2009 Jan 7.
    PMID: 19171158 Free PMC article.
    Non-spatial expertise and hippocampal gray matter volume in humans.
    Woollett K, Glensman J, Maguire EA.
    Hippocampus. 2008;18(10):981-4. doi: 10.1002/hipo.20465.
    PMID: 18566963 Free PMC article.
    London taxi drivers: A review of neurocognitive studies and an exploration of how they build their cognitive map of London.
    Griesbauer EM, Manley E, Wiener JM, Spiers HJ.
    Hippocampus. 2022 Jan;32(1):3-20. doi: 10.1002/hipo.23395. Epub 2021 Dec 16.
    PMID: 34914151 Review.

    #Taxi #Neurologie #Hirnforschung

  • Changes in London taxi drivers’ brains driven by acquiring ‘the Knowledge’, study shows
    https://wellcome.org/press-release/changes-london-taxi-drivers-brains-driven-acquiring-%E2%80%98-knowledge-st

    9.12.2011 - Acquiring ‘the Knowledge’ - the complex layout of central London’s 25,000 streets and thousands of places of interest - causes structural changes in the brain and changes to memory in the capital’s taxi drivers, new research funded by the Wellcome Trust has shown.

    The study, published today in the journal ’Current Biology’, supports the increasing evidence that even in adult life, learning can change the structure of the brain, offering encouragement for lifelong learning and the potential for rehabilitation after brain damage.

    To qualify as a licensed London taxi driver, a trainee must acquire ’the Knowledge’ of the capital’s tens of thousands of streets and their idiosyncratic layout. This training typically takes between three and four years, leading to a stringent set of examinations that must be passed to obtain an operating licence; only around half of trainees pass. This comprehensive training and qualification procedure is unique among taxi drivers anywhere in the world.

    Previous studies of qualified London taxi drivers, led by Professor Eleanor Maguire from the Wellcome Trust Centre for Neuroimaging at UCL (University College London), have shown a greater volume of grey matter - the nerve cells in the brain where processing takes place - in an area known as the posterior hippocampus and less in the anterior hippocampus relative to non-taxi drivers.

    The studies also showed that although taxi drivers displayed better memory for London-based information, they showed poorer learning and memory on other memory tasks involving visual information, suggesting that there might be a price to pay for acquiring the Knowledge. The research suggested that structural brain differences may have been acquired through the experience of navigating and to accommodate the internal representation of London.

    To test whether this was the case, Professor Maguire and colleague Dr Katherine Woollett followed a group of 79 trainee taxi drivers and 31 controls (non-taxi drivers), taking snapshots of their brain structure over time using magnetic resonance imaging (MRI) and studying their performance on certain memory tasks. Only 39 of the group passed the tests and went on to qualify as taxi drivers, giving the researchers the opportunity to divide the volunteers into three groups for comparison: those that passed, those that trained but did not pass, and the controls who never trained.

    The researchers examined the structure of the volunteers’ brains at the start of the study, before any of the trainees had begun their training. They found no discernible differences in the structures of either the posterior hippocampus or the anterior hippocampus between the groups, and all groups performed equally well on the memory tasks.

    Three to four years later - when the trainees had either passed the test or had failed to acquire the Knowledge - the researchers again looked at the brain structures of the volunteers and tested their performance on the memory tasks. This time, they found significant differences in the posterior hippocampus - those trainees that qualified as taxi drivers had a greater volume of grey matter in the region than they had before they started their training.

    This change was not apparent in those who failed to qualify or in the controls. Interestingly, there was no detectable difference in the structure of the anterior hippocampus, suggesting that these changes come later, in response to changes in the posterior hippocampus.

    On the memory tasks, both qualified and non-qualified trainees were significantly better at memory tasks involving London landmarks than the control group. However, the qualified trainees - but not the trainees who failed to qualify - were worse at the other tasks, such as recalling complex visual information, than the controls.

    “The human brain remains ’plastic’, even in adult life, allowing it to adapt when we learn new tasks,” explains Professor Maguire, a Wellcome Trust Senior Research Fellow. "By following the trainee taxi drivers over time as they acquired - or failed to acquire - the Knowledge, a uniquely challenging spatial memory task, we have seen directly and within individuals how the structure of the hippocampus can change with external stimulation. This offers encouragement for adults who want to learn new skills later in life.

    “What is not clear is whether those trainees who became fully fledged taxi drivers had some biological advantage over those who failed. Could it be, for example, that they have a genetic predisposition towards having a more adaptable, ’plastic’ brain? In other words, the perennial question of ’nature versus nurture’ is still open.”

    In the research paper, Professor Maguire and Dr Woollett speculate on the biological mechanisms that may underpin the changes to the brain they observed.

    One theory, supported by studies in rodents, is that when learning that requires cognitive effort takes place and is effective, there is an increase in the rate at which new nerve cells are generated and survive. The hippocampus is one of the few brain areas where the birth of new nerve cells is known to take place.Alternatively, it could be that the synapses, or connections, between existing nerve cells grew stronger in the trainees who qualified.

    Dr John Williams, Head of Neuroscience and Mental Health at the Wellcome Trust, says: “The original study of the hippocampi of London taxi drivers provided tantalising hints that brain structure might change through learning, and now Eleanor’s follow-up study, looking at this directly within individual taxi trainees over time, has shown this is indeed the case. Only a few studies have shown direct evidence for plasticity in the adult human brain related to vital functions such as memory, so this new work makes an important contribution to this field of research.”

    Reference
    Woollett K and Maguire EA. Acquiring ’the Knowledge’ of London’s layout drives structural brain changes. Curr Biol 2011 (epub ahead of print).

    About University College London
    Founded in 1826, University College London (UCL) was the first English university established after Oxford and Cambridge, the first to admit students regardless of race, class, religion or gender, and the first to provide systematic teaching of law, architecture and medicine. UCL is among the world’s top universities, as reflected by performance in a range of international rankings and tables. Alumni include Marie Stopes, Jonathan Dimbleby, Lord Woolf, Alexander Graham Bell, and members of the band Coldplay. UCL currently has over 13,000 undergraduate and 9,000 postgraduate students. Its annual income is over £700 million.

    ’Understanding the brain’ is one of the Wellcome Trust’s key strategic challenges. At the Wellcome Trust Centre for Neuroimaging at UCL, where Professor Maguire is based, clinicians and scientists study higher cognitive function to understand how thought and perception arise from brain activity, and how such processes break down in neurological and psychiatric disease.

    #Taxi #Neurologie #Hirnforschung

  • The Bigger Brains of London Taxi Drivers
    https://www.nationalgeographic.com/culture/article/the-bigger-brains-of-london-taxi-drivers

    29.5.2013 - How hard could learning a map of a city be? In London, earning the credentials to drive one of the city’s iconic cabs is equivalent to earning a university degree. It’s so advanced, in fact, that being able to navigate the streets isn’t just considered knowledge, but is formally called “The Knowledge.” The way London’s taxi drivers talk about it, it seems a little like getting a black belt in karate while becoming an Eagle Scout while vying for admission to Mensa.

    The reason why is London’s curious urban design, a squirrely mix of streets that were designed over centuries rather than by a one-time urban design grid that you might find in New York or Washington DC. There’s no pattern to learn in London, or a system of mnemonics to remember the order of roads. You simply have to learn every street in the city. And before you can legally drive a taxi, you have to prove to a group of city officials that you can, without fail, navigate between any two points. During the tests, aspiring drivers have to dictate the most efficient route and recall landmarks they’ll pass on the way. The people who are very good at it—and let’s be honest, more than 90 percent are men—can master the system in two years. Most people take four or longer.

    It’s a fun tourist novelty to know that the person driving you has a very detailed spatial map of the city in his head. But for about a decade, a group of researchers at the University College of London have looked into the effect that memorizing such a disorganized system has on your brain. The part of the brain that navigates spatial intelligence is called the hippocampus, a pair of two chestnut sized masses toward the back of your head. The researchers found that London cab drivers have uniquely bigger hippocampi than almost anyone else.

    We asked a few London cabbies about this in hopes they could help us understood how their brains worked.

    “Oh yeah mate, it’s called the hippocampus,” one cabbie named Simon told us. “Most people don’t use it because of the simplicity of navigating most other places and because of maps and GPS. But with London there’s really no other way.”

    What’s it like to map something very complex in your brain, we asked?

    “Well, right when the person asks where to go, it’s like an explosion in your brain. You see it instantly.”

    An explosion in the brain is a pretty vivid image to understand just how someone’s mind works. Yet it rings true. Each time we got into a cab and stated an obscure street name or small neighborhood, the driver didn’t even respond. He just started driving, seeming to know immediately which streets to take, and what the most direct route would be.

    The downside to having a big hippocampus is that when cabbies retire and stop using their spatial mapping so regularly, the hippocampus actually starts to shrink back to normal. It’s like a muscle that shrinks if you don’t use it. What’s more, memorizing such a detailed map of a sprawling city actually took up the place of other grey matter. Researchers found that cabbies were worse at remembering things based on visual information and had worse short term memories. There is, after all, only so much real estate in one’s head.

    #Taxi #Neurologie #Hirnforschung

  • Cache Cab: Taxi Drivers’ Brains Grow to Navigate London’s Streets - Scientific American
    https://www.scientificamerican.com/article/london-taxi-memory

    Memorizing 25,000 city streets balloons the hippocampus, but cabbies may pay a hidden fare in cognitive skills

    By Ferris Jabr on December 8, 2011
    Manhattan’s midtown streets are arranged in a user-friendly grid. In Paris 20 administrative districts, or arrondissements, form a clockwise spiral around the Seine. But London? A map of its streets looks more like a tangle of yarn that a preschooler glued to construction paper than a metropolis designed with architectural foresight. Yet London’s taxi drivers navigate the smoggy snarl with ease, instantaneously calculating the swiftest route between any two points.

    These navigational demands stimulate brain development, concludes a study five years in the making. With the new research, scientists can definitively say that London taxi drivers not only have larger-than-average memory centers in their brains, but also that their intensive training is responsible for the growth. Excelling at one form of memory, however, may inhibit another.

    Neuroscientist Eleanor Maguire of University College London (U.C.L.) first got the idea to study London cab drivers from research on memory champions of the animal world. Some birds and mammals, such as western scrub jays and squirrels, cache food and dig it up later, which means they must memorize the locations of all their hiding spots. Researchers noticed that a part of the brain called the hippocampus was much larger in these animals than in similar species that did not secret away their snacks. The hippocampus is a seahorse-shaped section in the vertebrate brain that is crucial for long-term memory and spatial navigation.

    Maguire wondered whether London taxi drivers also had larger-than-average hippocampi. To earn their licenses, cab drivers in training spend three to four years driving around the city on mopeds, memorizing a labyrinth of 25,000 streets within a 10-kilometer radius of Charing Cross train station, as well as thousands of tourist attractions and hot spots. “The Knowledge,” as it is called, is unique to London taxi licensing and involves a series of grueling exams that only about 50 percent of hopefuls pass.

    In her earliest studies, Maguire discovered that London taxi drivers had more gray matter in their posterior hippocampi than people who were similar in age, education and intelligence, but who did not drive taxis. In other words, taxi drivers had plumper memory centers than their peers. It seemed that the longer someone had been driving a taxi, the larger his hippocampus, as though the brain expanded to accommodate the cognitive demands of navigating London’s streets. But it was also possible that The Knowledge selected for people whose memory centers were larger than average in the first place.

    To find out which possibility was more likely, Maguire and her U.C.L. colleague Katherine Woollett decided to follow a group of 79 aspiring taxi drivers for four years to measure the growth of their hippocampi with magnetic resonance imaging (MRI) as they completed The Knowledge. For the sake of comparison, Maguire also measured brain growth in 31 people who did not drive taxis but were of similar age, education and intelligence as the taxi trainees. At the start of the study, all of the participants had more or less the same size hippocampi. Maguire also made sure that the aspiring cabbies and non-taxi drivers performed similarly on tests of working memory and long-term memory.

    Four years later 39 of the 79 trainees had earned their licenses; 20 trainees who failed their exams agreed to continue participating in the study. When Maguire gave the successful and disappointed trainees the same battery of memory tests she had given them at the start of their training, she found that drivers who earned their licenses performed far better than those who failed—even though they had performed equally four years earlier. And MRIs showed that the successful trainees’ hippocampi had grown over time.

    There are several ways to explain the ballooning hippocampus. The hippocampus may grow new neurons or hippocampal neurons may make more connections with one another. Non-neuronal cells called glial cells, which help support and protect neurons, may also contribute to the increase in hippocampal volume, although they are not generated as quickly as neurons.

    The successful trainees did not perform better on all tests of memory, however. Licensed taxi drivers did worse than non-taxi drivers on a test of visual memory called the Rey-Osterrieth Complex Figure Test: The subject is asked to study what looks like a dollhouse designed by a loony architect, full of superfluous lines and squiggles, and sketch it from memory 30 minutes later.

    Maguire thinks that The Knowledge may enlarge the hippocampus’s posterior (rear) at the expense of its anterior (front), creating a trade-off of cognitive talents—that is, taxi drivers master some forms of memory but become worse at others. In her earlier work, Maguire found evidence that, whereas the rear of the hippocampus was bigger in taxi drivers, the front was usually smaller than average. She didn’t find this same difference in her new study because, she speculates, front-end shrinkage may happen after the four years of training. The hippocampus’s rear section seems to be important for spatial navigation specifically, but Maguire says the front end’s role remains more mysterious.

    Maguire says she was “greatly relieved” by the results of her study, which appears in the December issue of Current Biology. “We didn’t know how long the effects would take to appear on an MRI scan,” she says. “Maybe they only appeared quite some time after the trainees qualified. But we found them within the five years it took to do the study.”

    Neurobiologist Howard Eichenbaum of Boston University commends the study for answering the “chicken-and-egg question” posed by Maguire’s earlier research. He sees it as confirmation of the idea that cognitive exercise produces physical changes in the brain. “The initial findings could have been explained by a correlation, that people with big hippocampi become taxi drivers,” he says. “But it turns out it really was the training process that caused the growth in the brain. It shows you can produce profound changes in the brain with training.

    That’s a big deal.”

    #Taxi #Neurologie #Hirnforschung

  • SARS-CoV-2 invades cognitive centers of the brain and induces Alzheimer’s-like neuropathology | bioRxiv (preprint)
    https://www.biorxiv.org/content/10.1101/2022.01.31.478476v1

    Major cell entry factors of SARS-CoV-2 are present in neurons; however, the neurotropism of SARS-CoV-2 and the phenotypes of infected neurons are still unclear. Acute neurological disorders occur in many patients, and one-third of COVID-19 survivors suffer from brain diseases. Here, we show that SARS-CoV-2 invades the brains of five patients with COVID-19 and Alzheimers, autism, frontotemporal dementia or no underlying condition by infecting neurons and other cells in the cortex. SARS-CoV-2 induces or enhances Alzheimers-like neuropathology with manifestations of beta-amyloid aggregation and plaque formation, tauopathy, neuroinflammation and cell death. SARS-CoV-2 infects mature but not immature neurons derived from inducible pluripotent stem cells from healthy and Alzheimers individuals through its receptor ACE2 and facilitator neuropilin-1. SARS-CoV-2 triggers Alzheimers-like gene programs in healthy neurons and exacerbates Alzheimers neuropathology. A gene signature defined as an Alzheimers infectious etiology is identified through SARS-CoV-2 infection, and silencing the top three downregulated genes in human primary neurons recapitulates the neurodegenerative phenotypes of SARS-CoV-2. Thus, SARS-CoV-2 invades the brain and activates an Alzheimers-like program.

    https://seenthis.net/messages/905036

    #covid-19 #post-covid #troubles_neurologiques #neurologie

  • Prevalence and Risk Factors of Neurologic Manifestations in Hospitalized Children Diagnosed with Acute SARS-CoV-2 or MIS-C - ScienceDirect
    https://www.sciencedirect.com/science/article/pii/S0887899421002769

    Abstract
    Background
    Our objective was to characterize the frequency, early impact, and risk factors for neurological manifestations in hospitalized children with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or multisystem inflammatory syndrome in children (MIS-C).

    Methods
    Multicenter, cross-sectional study of neurological manifestations in children aged <18 years hospitalized with positive SARS-CoV-2 test or clinical diagnosis of a SARS-CoV-2-related condition between January 2020 and April 2021. Multivariable logistic regression to identify risk factors for neurological manifestations was performed.

    Results
    Of 1493 children, 1278 (86%) were diagnosed with acute SARS-CoV-2 and 215 (14%) with MIS-C. Overall, 44% of the cohort (40% acute SARS-CoV-2 and 66% MIS-C) had at least one neurological manifestation. The most common neurological findings in children with acute SARS-CoV-2 and MIS-C diagnosis were headache (16% and 47%) and acute encephalopathy (15% and 22%), both P < 0.05. Children with neurological manifestations were more likely to require intensive care unit (ICU) care (51% vs 22%), P < 0.001. In multivariable logistic regression, children with neurological manifestations were older (odds ratio [OR] 1.1 and 95% confidence interval [CI] 1.07 to 1.13) and more likely to have MIS-C versus acute SARS-CoV-2 (OR 2.16, 95% CI 1.45 to 3.24), pre-existing neurological and metabolic conditions (OR 3.48, 95% CI 2.37 to 5.15; and OR 1.65, 95% CI 1.04 to 2.66, respectively), and pharyngeal (OR 1.74, 95% CI 1.16 to 2.64) or abdominal pain (OR 1.43, 95% CI 1.03 to 2.00); all P < 0.05.

    Conclusions
    In this multicenter study, 44% of children hospitalized with SARS-CoV-2-related conditions experienced neurological manifestations, which were associated with ICU admission and pre-existing neurological condition. Posthospital assessment for, and support of, functional impairment and neuroprotective strategies are vitally needed.

    #covid-19 #hospitalisation #enfants #PIMS #neurologie #soins_de_suite

  • Un récepteur synaptique impliqué dans l’émergence de croyances aberrantes | Salle de presse | Inserm
    https://presse.inserm.fr/un-recepteur-synaptique-implique-dans-lemergence-de-croyances-aberrantes/44508

    Pourquoi sommes-nous parfois enclins à croire à l’improbable envers et contre tout ? Une étude menée par une équipe de neuroscientifiques et de médecins psychiatres de l’Hôpital Sainte-Anne et d’Université de Paris, ainsi que de l’École Normale Supérieure – PSL et de l’Inserm pointe vers un récepteur synaptique spécifique. Son blocage induit des décisions prématurées et aberrantes, ainsi que des symptômes ressemblant à ceux rapportés dans les stades précoces de psychose. Les résultats viennent d’être publiés dans Nature Communications [https://www.nature.com/articles/s41467-021-27876-3]. — Permalien

    #science #complotisme

    • (...) les encéphalites provoquées par une réaction auto-immune contre le récepteur NMDA sont connues pour donner lieu à des symptômes psychotiques.

      Pour comprendre si une anomalie de ce récepteur favorise l’émergence de croyances aberrantes, l’équipe a demandé à un groupe de volontaires sains de prendre des décisions sur la base d’informations visuelles incertaines tout en se voyant administré par intraveineuse une très faible dose de kétamine, une molécule qui vient bloquer de façon temporaire le récepteur NMDA.

      « Un blocage du récepteur NMDA déstabilise la prise de décision, en favorisant les informations qui confirment nos opinions au détriment des informations qui les invalident », explique Valentin Wyart. « C’est ce biais de raisonnement qui produit des décisions prématurées et souvent erronées ». C’est ce type de biais qui est notamment reproché aux réseaux sociaux qui proposent aux utilisateurs une sélection d’informations en fonction de leurs opinions.

      L’équipe est allée plus loin en montrant que ce biais de raisonnement vient compenser le sentiment d’#incertitude élevé ressenti sous kétamine. « Ce résultat suggère que les décisions prématurées que nous observons ne sont pas la conséquence d’une confiance exagérée », poursuit Valentin Wyart. « Au contraire, ces décisions semblent résulter d’une incertitude élevée, et provoquer l’émergence d’idées pourtant très improbables, qui se renforcent d’elles-mêmes sans pouvoir être invalidées par des informations extérieures. »

      Ces résultats ouvrent de nouvelles pistes de réflexion pour la prise en charge de patients atteints de psychose. « Nos traitements agissent sur les idées délirantes, mais agissent peu sur ce qui les induit », précise Raphaël Gaillard. « Des essais cliniques devraient donc être menés pour déterminer comment augmenter la tolérance des patients à l’incertitude dans les stades précoces de psychose. »

      on tombe a contrario sur un indice quant à la relative efficacité de la méthode Coué (la con-fian-ce-, sentiment par ailleurs lié au statut social, en plus de l’histoire familiale)
      #récepteur_NMDA #psychose #synapses #psychiatrie #neurologie

  • #COVID and the brain: researchers zero in on how damage occurs
    https://www.nature.com/articles/d41586-021-01693-6

    How COVID-19 damages the brain is becoming clearer. New evidence suggests that the coronavirus’s assault on the brain could be multipronged: it might attack certain brain cells directly, reduce blood flow to brain tissue or trigger production of immune molecules that can harm brain cells.

    Infection with the coronavirus SARS-CoV-2 can cause memory loss, strokes and other effects on the brain. The question, says Serena Spudich, a neurologist at Yale University in New Haven, Connecticut, is: “Can we intervene early to address these abnormalities so that people don’t have long-term problems?”

    With so many people affected — neurological symptoms appeared in 80% of the people hospitalized with COVID-19 who were surveyed in one study1 — researchers hope that the growing evidence base will point the way to better treatments.

  • Thread by chrischirp on Thread Reader App – Thread Reader App
    https://threadreaderapp.com/thread/1418696473177362432.html

    Prof. Christina Pagel sur Twitter : "#LONG_COVID THREAD:

    The people running the BBC Horizon “Great British Intelligence Test” challenge on over 80,000 people took the opportunity to see if they could detect any differences by whether people had had covid or not..." / Tw

    […]

    10. What if by the time there can be no doubt of long term problems in many people who’ve had covid, we’ve allowed millions more infections leaving hundreds of thousands more people affected.

    ONS estimated 634K people with long covid that impacts their life in June.

    11. For comparison, c. 260K people are diagnosed with diabetes & 500K with heart disease each year.

    I worry that we are creating a chronic disease tragedy right now.

    The Silent Pandemic - YouTube
    https://www.youtube.com/watch?v=3hplyClO1qw

  • Neurology and neuropsychiatry of #COVID-19: a systematic review and meta-analysis of the early literature reveals frequent CNS manifestations and key emerging narratives | Journal of Neurology, Neurosurgery & Psychiatry
    https://jnnp.bmj.com/content/early/2021/06/03/jnnp-2021-326405

    In our review, we summarise point prevalence of 20 neurological and neuropsychiatric complications of COVID-19. The most frequently studied symptoms were heavily weighted towards non-specific features of systemic illness, such as headache, myalgia, fatigue, anosmia and dysgeusia, which are unlikely to be ‘primary’ neurological symptoms. It was predominantly these more non-specific symptoms that were found to have the highest prevalences, ranging from 20.7% (16.1% to 26.1%) to 43.1% (35.2% to 51.3%) (headache and anosmia, respectively). Of note, more specific neurological and neuropsychiatric symptoms such as altered mental status, depression, anxiety, sleep disorder, stroke and seizures were less frequently studied. However, the core psychiatric disorders of depression (23.0% (11.8% to 40.2%)) and anxiety (15.9% (5.6% to 37.7%)) appeared to be highly prevalent. The reported prevalence of major neurological disorders such as ischaemic stroke (1.9% (1.3% to 2.8%)), haemorrhagic stroke (0.4% (0.3% to 0.7%)) and seizure (0.06% (0.06% to 0.07%)) were substantially lower. Subgroup analyses suggested that study design (prospective vs retrospective), severity of illness and country of origin of a study affected the prevalence figures obtained. Importantly, for myalgia, fatigue, anosmia and dysgeusia, prevalences were substantially higher in prospective studies compared with retrospective studies.

    #neurologie

  • Scientists begin to unravel the mysteries of the coronavirus and brains - The Washington Post
    https://www.washingtonpost.com/health/2021/06/07/covid-are-brains-affected

    In laboratory experiments, the coronavirus can infiltrate neurons and other brain cells when those cells are cultured. It also can invade clumps of cells designed to replicate the structure of a brain, which scientists call organoids. Those observations suggest brains are vulnerable to invasion by SARS-CoV-2.

    At least in theory. Not all brain specialists are convinced that what can happen in a petri dish occurs in sick humans.

    “Frankly, I don’t think it tells us a lot about what’s going on in the brains of people who were infected with this virus,” said James E. Goldman, a neuropathologist and a colleague of Thakur and Canoll at Columbia. [COVID-19 neuropathology at Columbia University Irving Medical Center/New York Presbyterian Hospital | Brain | Oxford Academic
    https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awab148/6226391]

    As that trio and their co-authors reported in the journal Brain in April, they did not find viral proteins in brain autopsies.

    They detected no or low levels of viral RNA, depending on the technique used. Canoll suggested the viral genetic material they did find in the brain came from virus in the membrane that surrounds the brain, not from within the organ itself.

    “This, alongside other studies, is suggestive that there’s not a florid amount of virus in the brain in patients who have died,” said Thakur, lead author of that study.

    [...]

    Although there wasn’t much virus to be found, the brains of people killed by the coronavirus weren’t unscathed . The Columbia researchers, looking at thin slices of brain tissue under microscopes, found two main types of problems in patients who died of covid.

    First were infarctions, dead tissue surrounding blocked blood vessels, found in the brain’s gray matter. [...]

    The second issue, appearing in the brainstem, cerebellum and other areas, involved swarms of immune cells. Those cells often converged around dead or dying neurons. “They’re actually attacking and eating the neurons,” Canoll said.

    These immune cells, called microglia, were enlarged and had clustered in nodules, signaling inflammation, though not as severe as what pathologists see in cases of viral encephalitis. Curiously, there was no virus in the neurons being surrounded.

    Still, microglia don’t act like this unless provoked.

    “Something is triggering them to do that,” said immunologist Lena Al-Harthi, who studies at Rush University in Chicago how HIV affects the central nervous system. That trigger remains unknown, but Harthi suggested it could be an autoimmune response .

    ]...] Autoantibodies have been found in postmortem brains and the cerebrospinal fluid of covid patients , Harthi said.

    It’s unclear whether the pathologies seen in these autopsies could also occur in patients with mild cases, or long-term symptoms. Goldman declined to speculate. These patients, many of whom were admitted to intensive care, had died of severe covid-19.

    “This is a series of a small subset of patients, so there’s a selection issue,” Thakur said. But with that caveat and others — variants are spreading that weren’t in the initial wave of the pandemic, for example — she said the results are suggestive that the virus “isn’t entering and propagating and infecting the brain.

    The scientists are working on a follow-up study examining the brains of patients who had covid and recovered but later died. Those observations should help settle whether brains in very sick patients resemble brains in other cases.

    [..,]

    Compared with almost all other diseases, covid-19 has been studied with unprecedented focus. [...]

    The scientists used tools not typically applied across the brain.

    We’ve already started to look at the brains of patients that don’t have covid” but died of other severe lung diseases, Canoll said. They are seeing pathological changes reminiscent of what they detected in brains from people who died of covid.

    [...]

    Joanna Hellmuth, a cognitive neurologist at the UCSF Memory and Aging Center, said she hears the same story repeatedly from previously healthy young adults who tell her that after even a mild case of covid: “My brain doesn’t work like it used to.”

    Hellmuth said cognitive impairment is showing up in people who measure well in mood testing, suggesting their symptoms are not caused by depression or another psychiatric problem. She has seen similar patterns caused by other viruses

    #neurologie #covid-19 #auto-anticorps

  • Acute Ischemic Stroke and #COVID-19 | Stroke
    https://www.ahajournals.org/doi/abs/10.1161/STROKEAHA.120.031786

    Les patients covid-19 (plus de 8000 patients) ne font pas plus d’#infarctus_cérébral que les patients sans covid-19

    We found a low occurrence (1.3%) of acute ischemic stroke among COVID-19 patients. A similar prevalence (1%) of ischemic stroke was seen among patients without COVID-19 in our analysis.

    On retrouve les facteurs de risque vasculaires classiques (ce qui confirme certaines études et en infirme d’autres)

    Our findings suggest that most of the COVID-19 patients who develop acute ischemic stroke have preexisting cardiovascular risk factors for large vessel atherosclerosis, small vessel disease, and cardioembolism similar to acute ischemic stroke patients without COVID-19. Our findings may be somewhat different from the earlier observations from smaller case series that suggested that patients with COVID-19 who developed acute ischemic stroke were younger and without preexisting cardiovascular risk factors.16,22,23 Other studies have reported findings similar to our findings7,13,15 suggesting that even if COVID-19 was a predisposing factor, the risk was mainly seen in those who were already at risk for acute ischemic stroke due to other cardiovascular risk factors.

    Les pronostics fonctionnel et vital sont par contre plus péjoratifs,

    Patients with COVID-19 and acute ischemic stroke have a much higher occurrence of multisystem involvement including acute kidney injury, hepatic failure, and respiratory failure. Our findings of higher in-hospital mortality and discharge to destination other than home in COVID-19 patients with ischemic stroke compared with those without stroke have been identified in other studies.

    #neurologie

  • Frontiers | Neuropsychiatric and Cognitive Sequelae of COVID-19 | Psychology
    https://www.frontiersin.org/article/10.3389/fpsyg.2021.577529/full

    #COVID-19 : Des #séquelles cognitives et psychologiques chez 20% des survivants | santé log
    https://www.santelog.com/actualites/covid-19-des-sequelles-cognitives-et-psychologiques-chez-20-des-survivants

    Cette revue de la littérature menée par l’Université d’Oxford Brookes (UK) confirme qu’une grande proportion des survivants de formes sévères du COVID-19 sera affectée par des complications neuropsychiatriques et cognitives. Si les études révèlent au fil du temps l’ampleur considérable des conséquences psychologiques de la crise et des mesures associées, peu de données ont encore été publiées sur les séquelles cognitives de la maladie. Cet examen de psychologues et de psychiatres de l’Oxford Health NHS Foundation Trust confirme la prévalence dans de nombreux cas de troubles cognitifs et de problèmes de santé mentale à long terme.

    #post-covid #covid_long #neurologie #psychiatrie

  • Cognitive deficits in people who have recovered from COVID-19 relative to controls: An N=84,285 online study | medRxiv
    https://www.medrxiv.org/content/10.1101/2020.10.20.20215863v1

    This article is a preprint and has not been peer-reviewed [what does this mean?]. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice.

    Case studies have revealed neurological problems in severely affected COVID-19 patients. However, there is little information regarding the nature and broader prevalence of cognitive problems post-infection or across the full spread of severity. We analysed cognitive test data from 84,285 Great British Intelligence Test participants who completed a questionnaire regarding suspected and biologically confirmed COVID-19 infection. People who had recovered, including those no longer reporting symptoms, exhibited significant cognitive deficits when controlling for age, gender, education level, income, racial-ethnic group and pre-existing medical disorders. They were of substantial effect size for people who had been hospitalised, but also for mild but biologically confirmed cases who reported no breathing difficulty. Finer grained analyses of performance support the hypothesis that COVID-19 has a multi-system impact on human cognition.

    Significance statement There is evidence that COVID-19 may cause long term health changes past acute symptoms, termed ‘long COVID’. Our analyses of detailed cognitive assessment and questionnaire data from tens thousands of datasets, collected in collaboration with BBC2 Horizon, align with the view that there are chronic cognitive consequences of having COVID-19. Individuals who recovered from suspected or confirmed COVID-19 perform worse on cognitive tests in multiple domains than would be expected given their detailed age and demographic profiles. This deficit scales with symptom severity and is evident amongst those without hospital treatment. These results should act as a clarion call for more detailed research investigating the basis of cognitive deficits in people who have survived SARS-COV-2 infection.

    #covid-19 #neurologie #covid_long

  • Le neurochirurgien Hugues Duffau sur la plasticité du #cerveau (L’Express, 02/10/2014)
    https://www.lexpress.fr/actualite/sciences/hugues-duffau-le-cerveau-se-repare-lui-meme_1578825.html

    Vous pouvez retirer des tumeurs d’un volume équivalent à celui d’un pamplemousse. On a du mal à croire qu’un tel geste ne provoque pas de dégâts...

    Les séquelles invalidantes sont devenues très rares, ce qui est en soi un progrès considérable. Mais je ne m’en satisfais pas. J’aimerais que l’intervention ne change en rien la personne : ni ses capacités ni son caractère. C’est mon combat de chercheur. En attendant, je m’efforce, en tant que médecin, de provoquer le minimum de dégâts, quitte à choisir lesquels avec le patient. 

    Par exemple, j’ai reçu une pianiste russe qui parlait cinq langues. Impossible de les conserver toutes ! On ne pouvait pas multiplier par cinq la durée de l’opération pour que l’orthophoniste réalise les tests dans chaque langue... La patiente a décidé que les plus importantes, pour elle, étaient le russe, le français et l’anglais. Elle est restée polyglotte et n’a perdu, comme prévu, que l’italien et l’espagnol. 

    Vous pouvez donc sauver des langues étrangères. Quoi d’autre ?

    Nous sommes capables de préserver le champ visuel, autrement dit la capacité à voir sur 180 degrés. L’être humain peut en perdre un quart sans ressentir de gêne au quotidien. Mais pas beaucoup plus, car la loi interdit de conduire avec un champ visuel amputé de moitié. Sinon, nous avons étendu notre savoir-faire au registre des émotions.

    Il y a deux ans, une femme d’une quarantaine d’années, une magistrate, est venue me voir. Elle hésitait à choisir l’opération, craignant de commettre ensuite des erreurs de jugement. Je lui ai proposé de recourir aux derniers tests que j’ai mis au point avec un neuropsychologue, Guillaume Herbet, à l’Institut des neurosciences de Montpellier, pour préserver des fonctions complexes comme l’empathie ou la capacité à percevoir l’état d’esprit d’autrui et donc ses intentions - ce que les scientifiques nomment la « théorie de l’esprit ». Elle a accepté. Elle n’a rencontré aucune difficulté, depuis, dans l’exercice de son métier. 

    Peut-on espérer améliorer encore le pronostic pour ce type de tumeurs ?

    Certainement. Les gliomes de bas grade, pris suffisamment tôt, deviennent rarement malins, ce qui permet d’imaginer une chirurgie préventive. Voyez le cancer de la peau : le médecin retire les grains de beauté suspects pour éviter qu’ils ne prennent la forme agressive d’un mélanome, et on sauve ainsi des vies. Dans la même veine, nous venons de proposer, via la revue internationale de référence Cancer, de dépister les gliomes par IRM dans la population générale, au lieu d’attendre qu’une crise d’épilepsie pousse la personne à consulter. Pour l’instant, aucun pays ne le fait, mais c’est une évolution logique. 

    Comme Penfield dans les années 1930, vous soignez des malades et, en même temps, vous explorez l’organe de la pensée. Qu’avez-vous appris en « cartographiant » le cerveau de 500 de vos concitoyens ?

    J’ai constaté qu’il n’existait pas deux cerveaux semblables. Selon la localisation et la taille de la tumeur, des fonctions peuvent se déplacer ailleurs dans le même hémisphère, ou bien passer d’un hémisphère à l’autre. La plasticité du cerveau, c’est-à-dire sa capacité à réorganiser les connexions entre les neurones, est plus phénoménale encore qu’on ne l’imaginait.

    • Si le patient continue à parler et à bouger normalement, je sais alors que je peux intervenir sans dommage à cet endroit avec un bistouri à ultrasons. En revanche, si le patient confond les mots ou reste coi, je dépose un repère à l’emplacement testé pour me garder d’y toucher par la suite. Tel un géomètre-topographe, je dresse un relevé sur le terrain des fonctions présentes dans cette partie découverte du cerveau.

      #neurologie
      #cartographie_du_cerveau
      #chirurgie_éveillée
      #connexionniste

      welcome back @thibnton :)