Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: The structuring of wild animal populations can influence population dynamics, disease spread, and information transfer. Social network analysis potentially offers insights into these processes but is rarely, if ever, used to investigate more than one species in a community. We therefore compared the social, temporal and spatial networks of sympatric Myotis bats (M. nattereri (Natterer's bats) and M. daubentonii (Daubenton's bats)), and asked: (1) are there long-lasting social associations within species? (2) do the ranges occupied by roosting social groups overlap within or between species? (3) are M. daubentonii bachelor colonies excluded from roosting in areas used by maternity groups? data on 490 ringed M. nattereri and 978 M. daubentonii from 379 colonies, we found that both species formed stable social groups encompassing multiple colonies. M. nattereri formed 11 mixed-sex social groups with few (4. 3%) inter-group associations. Approximately half of all M. nattereri were associated with the same individuals when recaptured, with many associations being long-term (>100 days). In contrast, M. daubentonii were sexually segregated; only a quarter of pairs were associated at recapture after a few days, and inter-sex associations were not long-lasting. Social groups of M. nattereri and female M. daubentonii had small roost home ranges (mean 0. 2 km2 in each case). Intra-specific overlap was low, but inter-specific overlap was high, suggesting territoriality within but not between species. M. daubentonii bachelor colonies did not appear to be excluded from roosting areas used by females. data suggest marked species- and sex-specific patterns of disease and information transmission are likely between bats of the same genus despite sharing a common habitat. The clear partitioning of the woodland amongst social groups, and their apparent reliance on small patches of habitat for roosting, means that localised woodland management may be more important to bat conservation than previously recognised. Citation: (2014) -Groups with Home Ranges. 9(10): e112225. Brock Fenton, University of Western Ontario, CanadaReceived: July 4, 2014; Accepted: October 1, 2014; Published: October 30, 2014Copyright: © 2014 August et al.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: Main textThe natural history of tobacco dependenceNicotine is among the least rewarding of all addictive drugs: only 20 % of first time users find smoking to be relaxing [1]. Smoking provides an image, a shared social activity, and something to do when bored. These factors motivate smoking until dependence takes over. Prior to the onset of dependence, sporadic non-daily use is typical. The classic withdrawal syndromeThe seminal research on tobacco withdrawal focused on individuals with advanced dependence [2–4], as was the case with research on withdrawal associated with other substances [5, 6]. Because of this history, the term ‘withdrawal’ has traditionally been used to describe the symptoms experienced by individuals with advanced physical dependence [7, 8]. In this report, the historical connotation of the word ‘withdrawal’ is expanded to accommodate recent advances in scientific knowledge afforded by the study of individuals with emerging dependence. The emergence of physical dependenceMany addictive drugs cause a physical (physiologic) dependence that manifests as withdrawal symptoms. [7] (The term physical dependence is introduced here to indicate that the discussion is about to focus on that aspect of dependence related to withdrawal phenomena. The author acknowledges that there are psychological aspects to dependence and that the physical and psychological may be tightly entwined. ) Tobacco withdrawal symptoms are identifiable as such because (1) they recur upon each withdrawal from tobacco, (2) they appear in a characteristic sequence, (3) they appear after a characteristic latency, and (4) they are relieved immediately upon using tobacco. Based on these criteria, it has been shown that physical dependence on tobacco develops through a characteristic sequence of stages in all addicted smokers [9]. As physical dependence begins to develop, the earliest symptom is withdrawal-induced ‘wanting’ of a cigarette [10]. ‘Wanting’, by definition, is mild, short-lived and fairly easy to ignore. It does not intrude upon the patient’s thoughts. For individuals in the first stage of physical dependence, wanting is the only withdrawal symptom experienced. The second stage of physical dependence is characterized by withdrawal-induced ‘craving’. Craving is a more intense and persistent sensation than is wanting, but what distinguishes craving qualitatively from wanting is the fact that craving intrudes upon the patient’s thoughts. Smokers often describe craving as if something inside of their head is telling them that it is time to smoke.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: Full text Figures and data Peer review Side by side Figures 9 figures Figures Figure 1 Download asset Open asset Memory is consolidated, but training is ineffective, during the sleep phase. In this and in subsequent figures, values from measurements obtained during the inactive and active phases are respectively shaded and unshaded. In this and subsequent figures, upper bars show the time to stop responding. Lower bars show the percent change in the response (-((Train-Test)/Train)*100), which is a measure of memory. In all figures standard errors are shown. Experiments in this figure were performed on the diurnally active A. californica. (A) Blocking protein synthesis during the sleep phase blocks 24 hr memory. Animals were trained during their active phase (day), and were tested 24 hr later. 12 hr after training, during the sleep phase, animals were injected with ASW (N = 9) or with 10 µM anisomycin (N = 12). (1) There is a significant decrease in the time to stop responding to the food during the 24 test (p=0. 02, t = 2. 76, df = 8; two tailed paired t-test), indicating memory. (2) There was no significant difference between time to stop responding during the original training, and the test 24 hr later (p=0. 21, t = 1. 34, df = 11; two tailed paired t-test), indicating that block of protein synthesis in the sleep phase following training blocks memory consolidation. (3) In addition to consolidation that follows training (not shown), a second phase of consolidation occurs during sleep. This phase is blocked by the translation blocker anisomycin, preventing the expression of long-term memory. (B) Training during the sleep phase is ineffective in causing long-term memory. (1) Training animals during the sleep phase (N = 5) did not lead to long-term memory, as shown by a lack of savings when animals were tested 24 hr later (p=0. 3, t = 1. 12, df = 4; two-tailed paired t-test). In this experiment, animals were treated with ASW just before the training.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: This is an open-access 3571. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. IntroductionApproximately a third of all mammal species are bats, and the majority of these are long-lived and social for at least part of the year. Colonies, which can be mixed or single-sex, commonly contain tens to hundreds of individuals [1], [2]. Previous studies of the spatial arrangement of social groups have found that whilst some bat species form social groups occupying exclusive roost home ranges [3], [4] others have broadly overlapping roost home ranges [5]. Modern methods of social network analysis (SNA) offer considerable potential for understanding the behaviour of bats, but previous studies have considered only a single species at a single study site [4]–[11]. To our knowledge, there have been no previous studies on sympatric species, either amongst bats or in other orders, making this the first comparison of social networks between sympatric species within a genus (though see [12] for comparisons of populations without SNA). The present study tests predictions about the social structure and spatial arrangement of two sympatric species based on their ecology and the potential for intra and inter-specific competition for roosting sites. The spatial distribution of bat social groups is important for wildlife conservation, whilst characterising the structures of social networks is fundamental to understanding disease transmission and information transfer. Our study species were M. daubentonii and M. nattereri, sympatric medium sized insectivorous bats weighing 7–15 g and 6–12 g respectively [13]. M. daubentonii typically forages over water but frequently roosts in woodlands, whereas M. nattereri is a woodland specialist [13]. Both species roost in tree holes and man-made structures close to their foraging sites and form nursery colonies during the summer composed primarily of pregnant and lactating adult females. Nursery colonies form in May-June and split up once the once young are independent in August-September [13]. In this paper we define a ‘colony’ of bats as an aggregation of individuals at a single location. Both sexes of M.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: The third and final stage in the development of physical dependence is withdrawal-induced ‘needing’. The needing stage is characterized by a desire to smoke that is so intense and urgent that it cannot be ignored and the individual is so distracted that he or she is unable to function normally [10]. In the words of one teen, “You really want one. You know you need it. You know you’ll feel normal after smoking, and you have to smoke to feel normal again” [10]. When smokers report that they need to smoke, it is not a need to experience pleasure, it is an acute and urgent need to relieve withdrawal symptoms [10]. This description of the Wanting-Craving-Needing stages is not based on, or predicted by any specific theory of addiction, it is a clinical description based on case histories, validated by larger surveys [9–12]. To the author’s knowledge, stages in the development of physical dependence on other drugs have not been identified. Traditionally, it had been assumed that long-term heavy daily use of tobacco was a prerequisite to dependence [13], and the DSM has suggested that prolonged heavy use was a prerequisite for withdrawal syndromes generally [14]. However, in a national survey, 16 % of adolescents who used tobacco only one or two days per month reported strong cravings to use tobacco, and this symptom of physical dependence increased proportionate to the frequency of tobacco use to 78 % among those who had initiated daily use [15]. Irritability and restlessness during withdrawal were reported by 13 % of adolescents that used tobacco 1–2 days/month and by 70 % of daily users [15]. Close to two dozen peer-reviewed studies document symptoms of physical tobacco dependence in nondaily or very light daily smokers [16]. Symptoms can appear after only a few uses of tobacco. [17] Studies demonstrate that physical withdrawal symptoms can be elicited by the administration of an opioid receptor antagonist after a brief exposure to morphine [18, 19]. These studies raise the possibility that clinically significant physical dependence on other drugs is present in some form soon after the onset of infrequent use. If so, we should not expect their symptoms to be identical to those seen during withdrawal among individuals with far advanced dependence. It is likely that only a mild ‘wanting’ to use the drug manifesting at a predictable interval after the last use might be the first sign of physical dependence.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: (2) Memory after training during the active phase is expressed during the sleep phase (N = 11), as shown by a significant reduction in the time to stop 36 hr after training, when animals are tested during the inactive phase (p=0. 013, t = 3. 03, df = 10; two-tailed paired t-test with Bonferroni correction). (3) A diagram showing that training during the sleep phase is ineffective in producing memory. (C) Effect of a brief recall during the sleep phase. (1) A 3 min training during the sleep phase (N = 7), which is an effective means of recalling a memory, leaves the memory intact (p=0. 001, t(6) = 6. 02, two-tailed paired t-test). (2) A 3 min training paired with 10 µM anisomycin (N = 6) rescues the memory that would have been blocked by the anisomycin alone (p=0. 004, t(5) = 5. 01, two-tailed paired t-test). (3) A flow diagram showing that the anisomycin does not block memory formation when followed by a brief training. Figure 1—source data 1 Memory is consolidated, but training is ineffective, during the sleep phase. Download elife-17769-fig1-data1-v2. xlsx Figure 2 Download asset Open asset 3 min training with anisomycin during the inactive phase produces memory. Experiments were on A. californica. (A) Time to stop responding during training in the active phase, and during a test of memory 24 hr later (N = 10). These data provide comparisons for data in B-E on the time to stop in a naïve, previously untrained animals, and during a test of memory after successful training. (B) Animals were trained for 3 min during the inactive phase just after treatment with anisomycin, and memory was tested 24 hr later (N = 15). (C) As a control, animals were trained for 3 min during the inactive phase just after treatment with ASW, and memory was tested 24 hr later (N = 7).

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: nattereri are highly philopatric, returning from hibernation to spend the summer at the site of their birth [14]. In M. daubentonii, males are likely to account for most dispersal whilst females are generally philopatric [15]. It has been proposed that summer bachelor colonies of M. daubentonii are excluded from areas of high quality foraging habitat by females [16]–[19]. M. nattereri also, though less frequently, form bachelor colonies of up to 28 individuals [20]. Like other Myotis bats, both species attend swarming sites, typically cave or mine entrances, from late summer to early autumn. These sites are thought to be important for mating, though mating may also occur at summer roosting sites [15] and hibernaculae [18]. Based on evidence that M. daubentonii and M. nattereri tend to form female dominated social groups, and that M. daubentonii males form separate bachelor roosts [15]–[18], we expected the species' social networks to reflect this structure. We set out to test the following: Both species will exhibit long lasting intra-sex associations. The physical space within the wood occupied by roosting social groups will overlap, since tree dwelling bats change roost site frequently and potential roosts are in excess at this study site. M. daubentonii bachelor colonies will occupy roosts further from the highest quality foraging sites (in this case, Thames and Farmoor Reservoir) due to competitive exclusion by female maternity groups from roost sites closest to foraging areas [16]–[18]. Materials and Bats were captured and ringed between May and mid-October annually, from 2006 to 2010, at Wytham Woods, Oxfordshire, UK (Latitude: 51. 7743, Longitude: −1. 3379). This 415 hectare site is composed of semi-natural ancient deciduous woodland and 18th–20th century plantations. Over 1150 woodcrete bird boxes of very similar design are dispersed through the woods, many of these are occupied by blue tits (Parus caeruleus) and great tits (Parus major) until chicks fledge in the second half of May.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: Wanting has not been previously recognized as a withdrawal symptom, probably because of the perceived difficulty in distinguishing withdrawal-induced wanting from the wanting that we all experience as a part of daily living. The key to recognizing withdrawal-induced wanting is to apply the following criteria. Does the wanting recur predictably upon each withdrawal from the drug? Does it appear after a characteristic latency (time interval)? Is it relieved immediately upon using the drug? Is it followed by other symptoms in a predictable sequence? As physical dependence develops in new smokers, the symptoms of wanting, craving and needing develop in that order. During each episode of withdrawal, symptoms emerge in this same order: wanting, then craving, then needing. For individuals in the first stage of physical dependence, the desire to smoke never proceeds beyond wanting. For those in the second stage, the desire to smoke never proceeds beyond craving, while for those in the third stage, the desire to smoke will always progress to needing if abstinence is maintained. Thus, as physical dependence develops, it progresses through stages of wanting, craving and needing, and during each episode of withdrawal, symptoms escalate from a wanting phase, to a craving phase, to a needing phase. Table 1 presents a validated measure of the stages of physical dependence [20]. Individuals answer the three questions and the stage or level of physical dependence is determined by the most advanced symptom endorsed. Table 1 A clinical measure of the Stages of Physical DependenceFull size tableThe classically recognized symptoms of nicotine withdrawal such as irritability, anxiety, restlessness, moodiness, impatience, difficulty concentrating and trouble sleeping [7, 8], do not appear in a standard order as physical dependence develops but are usually associated with the needing stage of physical dependence and the needing phase of withdrawal. In practical terms, this indicates that the seminal work on tobacco withdrawal focused on individuals who had already advanced to the needing stage. Earlier stages of physical dependence were not discovered for many decades because light smokers had been systematically excluded as research subjects. Seminal studies on other withdrawal syndromes have similarly focused on treatment seeking individuals with advanced dependence [2, 3]. This raises the question as to whether similar clinical stages of wanting-craving-needing in the development of physical dependence to other drugs have gone unnoticed because of the natural tendency to focus on treatment seeking individuals with the most advanced dependence. Table 2 lists symptoms selected by the DSM as criteria for a tobacco withdrawal syndrome [7].

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: (D, E) To test whether memory is expressed during the active phase, animals were trained for 3 min during the inactive phase just after treatment with anisomycin (N = 9 D), or ASW (N = 11 E), and memory was tested 12 hr later. There were significant differences between the six groups tested (training and testing in part A, and the four tests of memory in parts B–E) (p=0. 00005, F(5,54) = 6. 95; one-way analysis of variance). A post hoc- test (Student-Newman-Keuls, α = 0. 05) showed no significant difference between naïve animals trained during the day and either group of animals trained for 3 min with ASW (marked by an n for behaving as if naive). Thus, a 3 min training during the inactive phase with ASW produces no memory. These 3 groups were significantly different from the other three groups (marked by a t for behaving as if trained), which were not significantly different from one another. Thus, a 3 min training during the inactive phase after anisomycin treatment produced memory 12 and 24 hr later. (F) The data are explained by the effects of 10 µM anisomycin on a process initiated by sleep phase training that blocks memory. The anisomycin prevents the action of the blocker, allowing the formation of long-term memory. Figure 2—source data 1 3 min training with anisomycin during the inactive phase produces memory. Download elife-17769-fig2-data1-v2. xlsx Figure 3 Download asset Open asset Full training during the sleep phase with anisomycin causes long-term memory. Experiments were performed on A. californica. (A) Training animals until they stop responding during the inactive phase 10 min after treatment with anisomycin (N = 7) leads to memory when animals are tested 24 hr later, as shown by a decrease in the time stop responding (p=0. 05, t = 2. 49, df = 6; two-tailed paired t-test). (B) Training animals until they stop responding during the inactive phase 10 min after treatment with ASW (N = 5) did not lead to long-term memory, as shown by a lack of savings when animals were tested 24 hr later (p=0. 3, t = 1.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: After this time the boxes are not used by birds but are frequently used by bats up until mid-October, after which the bats migrate to unknown hibernation sites. To minimise disturbance, boxes were not checked more than once within a two week period and females with attached young were not handled. Areas with higher occupancy rates (pers. obs. ) were sampled more frequently to maximise data collection (Figure S1). Bats were ringed with 2. 9 mm aluminium armbands bearing a unique identification number. The individuals were classed juvenile if the joints between the metacarpals and phalanx were not fully ossified [21], [22]. Ethical considerations All methods were approved by the University of Committee and by the University of Committee and conducted in accordance with Oxford University's Review Procedures, overseen by the. The work and was conducted under permit to conduct research within Wytham Woods. Rings were supplied by Society, UK and were applied under licence no. 20113601 and previous licences. Social network analysis A social interaction, or ‘association’, was considered to exist between two individuals if they were found roosting together. Our analyses made no assumptions about the direction of association, as this would require identification of which individuals initiated and which received the behaviour. The link between a pair is therefore scored once in the data we present (ie. the link A-B is not considered separately from B-A). Since the sample size of this study was limited due to the practicality of fieldwork, associations were assumed to be binary and were not given weighting [9]. Structural analysis Construction of the association matrix was undertaken in SocProg [23]. Visualisation of the networks was undertaken using Netdraw v. 2 [24] - individual bats are represented by nodes and an association between two individuals is represented by a line connecting them. Individuals captured only once (Table 1) were excluded from the analysis, and individuals captured more than once but which had no associations (n = 10) were also removed. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 1. Frequency distribution of captured bats by species and sex. were assigned to social groups using the Girvan-Newman method, which is particularly appropriate for populations with a strong social structure such as those studied here [25].

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: As this list is limited to symptoms that would be experienced only by individuals at the needing stage, the DSM criteria are not a sensitive indicator of physical dependence. Table 2 DSM-5 tobacco withdrawal criteria [7]Full size tableThe stage of physical dependence, as measured by the instrument in Table 1, correlates with progressive changes in the neural architecture of the anterior cingulate gyrus [21, 22]. As the stage of physical dependence advances, neural pathways between the anterior cingulate gyrus and the precuneus increase in number, while those linking to the frontal lobe decrease substantially. Neural activity in networks involving the anterior cingulate increases in proportion to the strength of craving reported by individuals in withdrawal [22, 23]. Although the symptoms of tobacco withdrawal are primarily psychological, the correlation of both the stage of physical dependence and the intensity of withdrawal-induced craving with measures of brain structure and function confirm that physical processes are involved in the development and expression of physical dependence on tobacco. [21, 22] Changes in neural architecture have also been identified in conjunction with other forms of addiction [24, 25]. The progressive changes in neural architecture in parallel with stages of symptom development suggest that some of these changes represent neural adaptation rather than non-specific toxicity [26]. The identification of these changes among very light smokers suggests that it would be worthwhile looking for neural changes among users of other drugs who do not show the classic signs of physical dependence. As with the clinical research, imaging research has missed the opportunity to identify the progression in changes because studies have focused on individuals with advanced dependence. The latency to withdrawalThe latency to withdrawal is a measure of the time elapsed between the last use of tobacco and the onset of withdrawal symptoms. [10, 27, 28] As the symptoms of wanting, craving and needing emerge in that sequence during withdrawal, there is a latency to wanting, a latency to craving, and a latency to needing. The latencies vary between individuals, ranging from 4 weeks to as short as several minutes [27–29]. An 18 year-old woman reported wanting a cigarette after 30 min but being able to go two days before she absolutely needed one, while a 19 year-old man would want a cigarette in 2–3 h, and need one in 6–7 h [10].

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: Thus, 30 µM anisomycin produces a longer-lasting inhibition than does 10 µM anisomycin. For parts C and D, note that the initial training time is shorter than in parts A and B. This is because the animals were young and collected from the ocean during the beginning of the season and were also trained and tested at a different time. Baseline values often change in different batches of animals collected at different times. (E) 3. 3 µM anisomycin injected 10 min before training (N = 7) is ineffective in blocking memory, as shown by a significant decrease in the time to stop between the training session and the 24 hr test of memory (p=0. 01, t = 3. 53, df = 6, two-tailed paired t-test). Figure 4—source data 1 Length of protein synthesis inhibition is concentration dependent. Download elife-17769-fig4-data1-v2. xlsx Figure 5 Download asset Open asset Block of sleep-time expression of proteins blocks memory formation. These experiments were on A. fasciata. In addition to injecting animals with 10 µM anisomycin treatment 10 min before a 3 min training, the animals were also injected with 10 µM anisomycin A) 2 hr before the training (N = 8), or B) 0. 5 hr before the training (N = 8). Values 24 hr after these procedures were compared to values in C) 24 hr after a 3 min training with a single injection of 10 µM anisomycin 10 min before training (N = 15). A one-way analysis of variance between the three groups showed significant differences (p=0. 004, F(2,28) = 6. 90). (A) Injecting 10 µM anisomycin 2 hr before training blocked memory formation (p=0. 003, t = 3. 62, df = 21; two-tailed t-test with Bonferroni correction – comparison of A to C), presumably because proteins that accompany consolidation during sleep were blocked. (B) 10 µM anisomycin treatment 0. 5 hr before a 3 min training plus 10 µM anisomycin did NOT block memory formation (p=0. 52, t = 0.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: This top-down method, successively removes the association with the highest value of ‘betweenness’. Betweenness is the number of shortest paths, connecting individuals in the network, which contain a given association. Associations with high values of betweenness are those that connect clusters with otherwise low interconnectivity and by removing them the network is broken down into an increasing number of unconnected components. Each time a new component is created the modularity of the network is calculated [26]. Modularity is derived from all associations from the original network and is the difference between the observed fraction of associations that are within components and the fraction expected if associations connected individuals at random. Modularity ranges from 0 to 1, with values over 0. 3 regarded as evidence of social structure [26]. The division of individuals to components that produce the highest modularity value is selected as the best representation of social groups. Evidence of assortment by sex within social networks was examined using join-count in [27] using 10,000 iterations. This test compares the number of male-male, female-female and intersex associations in the dataset with the number that would be expected by chance. Degree centrality was used to test the hypothesis that females were more central in the networks than males. Degree centrality is the simplest of the centrality measures and is calculated for each individual as the number of connections to other individuals in the network. Since individuals in a network are not independent, the significance of differences in degree centrality was calculated using permutation tests implemented in [27]. Roost home ranges of social groups were estimated using 100% minimum convex polygons (MCPs) after the removal of roosts used by single bats (M. daubentonii = 42; M. nattereri = 27) and those isolated by over 1 km (M. daubentonii = 1; M. nattereri = 2) using ArcMap (ESRI v. 10. 1, 2010) and Quantum GIS [28]. MCPs were created and cropped so that habitats such as grassland, which do not provide roosting opportunities, were removed. Radio-tracking was undertaken in August 2009 and 2010 to compare roost home range estimates produced from the SNA to the roost use of individual bats. Three adult female M.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: The observation that latencies in some smokers are measured in weeks, while in others they are measured in minutes, reflects the fact that the latencies shorten with repeated exposures to nicotine [10, 29]. Since the short half-life of nicotine results in its elimination from the body within a day, it may seem paradoxical that withdrawal symptoms may not appear in novice smokers until several weeks have passed since their last cigarette. The mechanism that triggers tobacco withdrawal symptoms is unknown, but the idea that it is triggered by nicotine levels dropping below a threshold level is incompatible with the clinical evidence. Similar to the phenomenon whereby delirium tremens may not be experienced until several days after alcohol has been cleared from the blood [3], newly addicted smokers may not experience withdrawal symptoms until weeks after their last cigarette [10, 27–29]. In contrast, chain smokers report the need to smoke within minutes of having smoked [27, 28] while blood nicotine levels are still quite high [30]. Nicotine alters the expression of 162 genes in the brains of adolescent rats [31], triggers the release of a half-dozen neurotransmitters [32–35], and alters the production of neurotransmitters and neuronal responsivity for up to four weeks following a single dose [34, 36]. It is likely that mechanisms other than nicotine levels trigger withdrawal. Since nicotine withdrawal in humans is not triggered by the administration of an antagonist as is the case with opiate withdrawal, the mechanisms responsible for withdrawal symptoms may be drug-specific. Admittedly, this suggests that lessons learned about tobacco addiction may not apply to other drugs. On the other hand, non-addictive drugs can produce withdrawal symptoms, so some withdrawal symptoms may have little relevance to addiction, suggesting that differences in withdrawal mechanisms between drugs may not be relevant. Shortening latencies and the trajectory of tobacco useThe clinical implication of shortening latencies is that the length of time an individual remains comfortable after putting out a cigarette decreases over time. This increases the frequency at which cigarettes must be smoked to maintain comfort. [28] An increase in the frequency of smoking is one of the earliest signs of dependence [37]. At a latency to craving of two days, a person could keep withdrawal at bay by smoking one cigarette every other day. Fifteen cigarettes would be sufficient to keep withdrawal at bay for 30 days.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: 66, df = 21; two-tailed t-test – comparison of B to C), presumably because sleep-phase proteins having a role in consolidation are still present at the time of the training. (C) As shown in the previous experiments, a 3 min training during the inactive phase10 min after 10 µM anisomycin produced 24 hr memory. (D) To provide a comparisons for data in B–D, the time to stop responding during the active phase in naïve, previously untrained animals was also measured (N = 6). (E) A diagram showing that translation relevant to consolidation during sleep is necessary for the expression of long-term memory after the brief training with anisomycin. Figure 5—source data 1 Block of sleep-time expression of proteins blocks memory formation. Download elife-17769-fig5-data1-v2. xlsx Figure 6 Download asset Open asset Learning during the inactive phase is transcription dependent. Experiments were on A. californica. (A) Ethanol is benign. Animals were treated with (1) ethanol alone (N = 3), or with (2) DRB dissolved in ethanol (N = 4), and were trained 24 hr later. Memory was then tested after 24 hr (48 hr after ethanol or DRB treatment). Neither treatment affected the ability of animals to learn or remember that food was inedible 24 hr later (For animals tested with ethanol: p=0. 009, t = 10. 22, df = 2; for animals tested with DRB: p=0. 03, t = 3. 57, df = 3). (B) DRB blocks memory. (1) Control: Animals were not trained. They were treated with anisomycin and then treated with DRB dissolved in ethanol, and then tested after 24 hr (N = 6). (2) Vehicle: Animals were treated with anisomycin, and then trained for 3 min. After training, the animals were injected with ethanol, with no DRB. Memory was then tested 24 hr later (N = 7). (3) DRB: Animals were treated with anisomycin, and then trained for 3 min, and then injected with DRB dissolved in ethanol. Memory was then tested 24 hr later (N = 8). There were significant differences between the 3 groups tested (p=0. 04, F(2,18) = 3.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: daubentonii, known to have been present at the site for at least two consecutive summers (one parous but not breeding in the current season, and 2 post-lactation), and one juvenile female were fitted with radio transmitters weighing 0. 35 g or 0. 42 g (Holohil, Canada, type LB-2N). All tags weighed less than 5% of the body weight of the bat (4. 1–4. 7%) and were attached by a licensed bat worker using a previously described method [29]. Bats were located at their day roosts using an Australis receiver (Ltd, Australia) and aYagi 3-element directional antennae (Biotrack Ltd, Wareham, UK). Tree roost locations were recorded by GPS and mapped using ArcMap (). Temporal analysis The temporal structure of associations was examined using the lagged association rate [10], [30]. This gives the probability that, after being found together, two individuals will be found together at a set time interval in the future. These trends were calculated for each of the four classes of association within each species (male-male, female-female, male-female and female-male) and compared to the expected trend if individuals were to associate randomly – the null association rate. Because individuals are included in the analysis only up until the point where they are last observed, emigration (or mortality) does not influence the values, except in the case of long-term migrations where an individual, having left the population subsequently returns to roost with the same companion. Standard errors were calculated for these trends by jack-knifing the data over a period of 30 days. We note that the error estimates produced using this method have previously been found to be too small, but the method allows for a more reliable interpretation of the data than other available techniques. We therefore recommend that the conclusions should be tested with more data [31]. Statistical analysis All statistical analyses were undertaken in R version 2. 11. 0 [32]. The association between social group's roost home range size and the number of individuals in the social group, species and sampling effort was examined using multiple linear regression. Sampling effort was calculated as the average number of recaptures per individuals for each social group. ResultsOver 5 consecutive summers we performed 7578 box checks, finding bats on 627 occasions.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: But when the latency to craving shortened to 45 min, one would have to smoke every 45 min to keep withdrawal at bay, which would entail smoking >500 cigarettes over a 30 day period. A 21 year-old woman described a latency-to-craving of two days after having smoked for about six weeks at age 16. Her latency decreased to four hours by age 16½, to two hours by age 17, to 1. 5 h by age 18, to one hour by age 19, and to 30–45 min by age 21. Over this time, her intake increased from 5 cigarettes/day to 15 [10]. Individuals addicted to opiates do not have to use their drug with such frequencies, but is it possible that at the onset of opiate dependence, a single dose may keep withdrawal symptoms at bay for many weeks, but a shortening of the latency to withdrawal demands a gradual escalation in the frequency of use? Aware of their latencies, smokers sometimes smoke in anticipation of a period of abstinence to postpone the onset of withdrawal (e. g. , prior to going to sleep, school or work). Even addicted smokers can smoke for pleasure, or to relieve stress or boredom. This is reflected in the fact that cigarette consumption correlates only moderately with the latencies (rho = −. 53, r = −. 53, and Kendall’s tau b = −. 53 in three studies of adolescents) [27–29]. This level of correlation indicates that only a proportion of cigarettes are smoked for the purpose of relieving withdrawal symptoms. Physical dependence need not be the only reason why addicted individuals self-administer their drug of choice, but it may put an outside limit on how long they can comfortably refrain from use. A new withdrawal period begins each time a smoker finishes a cigarette. From the moment the cigarette is finished the timer starts on the latency period during which withdrawal symptoms are not experienced. This asymptomatic phase of withdrawal may last from a few minutes to several weeks. The asymptomatic phase of withdrawal is followed by a symptomatic withdrawal phase during which wanting, craving, needing and the DSM withdrawal symptoms (anger, anxiety, restlessness, etc. ) emerge. The act of smoking aborts one episode of withdrawal and initiates another, analogous to hitting the snooze button on an alarm clock.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: Peer review processEditorsReviewer #1Reviewer #2Reviewer #3Author ResponsePeer review processNot revised: Preprint includes the authors’ original preprint (without revision), an eLife assessment, public reviews, and a provisional response from the authors. Read more about eLife’s peer review process. of Pennsylvania, Philadelphia, of of Oxford, Oxford, United KingdomReviewer #1 (Public Review): The authors show that concurrently presenting foreign words and their translations during sleep leads to the ability to semantically categorize the foreign words above chance. Specifically, this procedure was successful when stimuli were delivered during slow oscillation troughs as opposed to peaks, which has been the focus of many recent investigations into the learning & memory functions of sleep. Finally, further analyses showed that larger and more prototypical slow oscillation troughs led to better categorization performance, which offers hints to others on how to improve or predict the efficacy of this intervention. The strength here is the novel behavioral finding and supporting physiological analyses, whereas the biggest weakness is the interpretation of the peak vs. trough effect. Major importance: I believe the authors could attempt to address this question: What do the authors believe is the largest implication of this studies? How far can this technique be pushed, and how can it practically augment real-world learning? Lines 155-7: How do the authors argue that the words fit well within the half-waves when the sounds lasted 540 ms and didn't necessarily start right at the beginning of each half-wave? This is a major point that should be discussed, as part of the down-state sound continues into the up-state. Looking at Figure 3A, it is clear that stimulus presented in the slow oscillation trough ends at a time that is solidly into the upstate, and would not neurolinguists argue that a lot of sound processing occurs after the end of the sound? It's not a problem for their findings, which is about when is the best time to start such a stimulus, but it's a problem for the interpretation. Additionally, the authors could include some discussion on whether possibly presenting shorter sounds would help to resolve the ambiguities here. Medium importance: Throughout the paper, another concern relates to the term 'closed-loop'.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: Bats used numerous different boxes, but at any one time, only a minority were occupied, indicating an excess of potential roosting locations. For example, in 2010, bat droppings were found in 751 of 2279 box checks (33%), but only 146 (3%) had bats present. The two target bat species were never found in the same roost simultaneously, however, 27 roosts (of 293) were used by both species at different times (Figure S2). This is not significantly different from the number of boxes we would expect the species to share if they were randomly selecting empty roosts within the woods (χ2 = 0. 48, df = 1, p = 0. 49). A total of 490 M. nattereri and 978 M. daubentonii were ringed from 379 colonies. Of these, 643 bats were caught more than once, with the mean recapture frequency being 3. 6 (range 2–10) for M. nattereri (n = 299) and 2. 9 for M. daubentonii (range 2–9, n = 344)) (Table 1). M. nattereri colony size ranged from 2 to 35 individuals (median 7, n = 59), while M. daubentonii colonies ranged in size from 2 to 26 (median 10, n = 84). Due to limited opportunities for sampling during the nursery period, and the restrictions this placed on sample size, it was not possible to analyse the social structure separately for each year of the study. All data were therefore combined for SNA, and the nursery and post-nursery periods were considered together. While this approach means we are unable to examine the change in social structure between seasons and years it increases our confidence in results that show social isolation. If 2 social groups are found to have never associated when using 5 years data, we believe this is strong evidence that they do not socialise. The proportion of males captured in the adult population was 0. 28 for M. nattereri and 0. 62 for M. daubentonii (Table 1), whereas there was no sex ratio bias for juveniles (0. 55 for M. nattereri and 0. 54 for M. daubentonii). Given the relatively low sample size for juveniles (n = 77 M. nattereri; n = 98 M.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: Traditionally, when researchers referred to withdrawal they were referring to advanced withdrawal symptoms, as described in the DSM. However, under this new conceptualization of withdrawal, smokers are in a state of withdrawal (asymptomatic or symptomatic) anytime they are not actively smoking. In other words, the term ‘withdrawal’ is used to describe a physiologic state rather than specific symptoms. Analogously, when the cause of was unknown, symptomatic individuals were diagnosed with AIDS. After the underlying cause was better understood, individuals were described as carrying the human immunodeficiency virus, which is often an asymptomatic state. Smokers are in a state of withdrawal anytime they are not smoking. If they go too long without smoking they may experience withdrawal symptoms of increasing severity as time passes. Individuals with short latencies may experience symptomatic withdrawal dozens of times each day even though they are making no effort to maintain abstinence. Shortening latencies compel smoking at progressively shorter intervals and the resulting escalation in cigarette consumption can be mathematically modeled as a smooth trajectory [38–40]. The latencies shorten at different speeds and to different degrees in different individuals, determining whether that person will plateau as a light, moderate or heavy smoker. Longer latencies allow some physically dependent smokers to remain light smokers over a lifetime [41]. In others, the latencies shorten so much that they feel compelled to chain smoke. The fact that latencies shorten is the key to understanding the pathophysiology of tobacco dependence, its behavioral manifestations and its clinical course throughout the lifespan [42]. To the author’s knowledge, latencies have not been systematically studied in relation to any other drugs. Clinical manifestations of shortening latenciesThe trajectory of the frequency of tobacco use is very different from that of a drug like alcohol. When adolescents are drinking to achieve intoxication, the amount of alcohol consumed on weekends may increase substantially without a concomitant increase in the number of drinking days per week. With tobacco, the opposite pattern is seen. As the latency shortens, smoking frequency increases from monthly to weekly, to several days per week, and finally to daily smoking. All the while, the number of cigarettes smoked on smoking days remains around one to two [43]. Only when the latency shortens from days to hours is there a gradual increase in the number of cigarettes smoked per day [44].

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: It appears this term has been largely misused in the literature, and I believe the more appropriate term here is 'real-time' (Bergmann, 2018, Frontiers in Psychology; Antony et al. , 2022, Journal of Sleep Research). For instance, if there were some sort of algorithm that assessed whether each individual word was successfully processed by the brain during sleep and then the delivery of words was subsequently changed, that could be more accurately labeled as 'closed-loop'. Figure 5 and corresponding analyses: Note that the two conditions end up with different sounds with likely different auditory complexities. That is, one word vs. two words simultaneously likely differ on some low-level acoustic characteristics, which could explain the physiological differences. Either the authors should address this via auditory analyses or it should be added as a limitation. Line 562-7 (and elsewhere in the paper): "episodic" learning is referenced here and many times throughout the paper. But episodic learning is not what was enhanced here. Please be mindful of this wording, as it can be confusing otherwise. #2 (Public Review): In this project, Schmidig, Ruch and Henke examined whether word pairs that were presented during slow-wave sleep would leave a detectable memory trace 12 and 36 hours later. Such an effect was found, as participants showed a bias to categorize pseudowords according to a familiar word that they were paired with during slow-wave sleep. This behavior was not accompanied by any sign of conscious understanding of why the judgment was made, and so demonstrates that long-term memory can be formed even without conscious access to the presented content. Unconscious learning occurred when pairs were presented during troughs but not during peaks of slow-wave oscillations. Differences in brain responses to the two types of presentation schemes, and between word pairs that were later correctly- vs. incorrectly-judged, suggest a potential mechanism for how such deep-sleep learning can occur. The results are very interesting, and they are based on solid methods and analyses. Results largely support the authors' conclusions, but I felt that there were a few points in which conclusions were not entirely convincing: As a control for the critical stimuli in this study, authors used a single pseudoword simultaneously played to both ears. This control condition (CC) differs from the experimental condition (EC) in a few dimensions, among them: amount of information provided, binaural coherence and word familiarity.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: daubentonii), we combined data for adults and juveniles in subsequent analyses. Social structure of bat populations For both species, female-female associations were significantly more frequent, and intersex associations significantly less frequent, than would be expected by chance (10,000 iterations, p<0. 001). Male-male associations were significantly more frequent in M. daubentonii (10,000 iterations, p = 0. 023) and less frequent in M. nattereri (10,000 iterations, p<0. 001) than expected by chance. In both species, females had higher degree centrality than males (one-tailed t-test, 10,000 permutations, p<0. 001). M. nattereri formed 11 social groups (Figure 1a) with 6 unconnected components. Despite evidence of assortment by sex, M. nattereri social groups were composed of a mix of males and females suggestive of a single social group with females at the core. Inter-group associations by either sex were rare, making up only 4. 3% of all associations (n = 4258). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 1. Social network visualisation a) male and female M. nattereri, b) male and female M. daubentonii, c) female M. daubentonii, and d) male M. daubentonii. a) M. nattereri male (n = 85) and female (n = 214), modularity = 0. 74, b) M. daubentonii (n = 344), modularity = 0. 66, c) female M. daubentonii (n = 145), modularity = 0. 67, d) male M. daubentonii (n = 199), modularity = 0. 64. Nodes represent individual bats (males, circles; females, triangles) and associations are represented by the lines that join them. Colours indicate the assignment of individuals to social groups using the Girvan-Newman algorithm. Colours do not correspond between panels. Colours in a) and c) are comparable to Figure 3. The position of individuals within these networks indicates their position in social space and is not an indication of an individual's geographical location.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: Individuals with very short latencies will begin to feel uncomfortable within minutes of finishing a cigarette, prompting chain smoking. Such individuals will spend a great deal of time smoking (Table 3, Diagnostic and 5 (DSM 5) criterion 3). Table 3 DSM 5 criteria [7]Full size tableAs the latency shortens, smokers may experience difficulty in refraining from smoking in situations where it is not allowed and may avoid such situations because the emergence of craving and needing makes them uncomfortable (Table 3, DSM 5 criterion 7). Individuals with latencies shorter than the time spent in bed may smoke just before going to bed and still feel the need to smoke immediately upon arising. The latency explains why the time to the first morning cigarette is a valid measure of dependence [15, 45]. Insomnia is a symptom of tobacco withdrawal and individuals with very short latencies may awaken during the middle of the night needing to smoke [46]. The discomfort of individuals in the needing stage of withdrawal may be such that they will smoke even when sick in bed because the discomfort of withdrawal makes them feel even worse, and why, even some nondaily smokers feel compelled to go outside in severe weather to smoke [37]. A note on medical and psychiatric approaches to diagnosisThe medical approach to identifying and diagnosing conditions is based on evidence of a disruption of normal anatomy or physiology [47]. The observation that the three stages of physical dependence (wanting, craving and needing) correlate with structural and functional changes in the brain establishes that physical dependence represents a disruption of normal anatomy and physiology [21]. As such, tobacco dependence can be diagnosed as a medical condition when symptoms of withdrawal-induced wanting, craving or needing are reported [47]. In practical terms, tobacco users fulfill the criteria for a medical diagnosis of tobacco dependence when they reach the wanting stage of physical dependence as indicated by endorsement of the first symptom on the instrument in Table 1. While medical conditions are diagnosed on the basis of indications of altered anatomy or physiology, the psychiatric approach to diagnosis is based on indications of impairment. Under the definition offered by the DSM 5, substance use represents a mental disorder when a combination of specified symptoms causes “clinically significant impairment or distress” [7]. Dissimilar to intoxicating and illegal drugs, tobacco use rarely causes incarceration, job loss or divorce.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: (Current Biology, 2019) had also presented pseudowords and translation words for paired-associative word encoding during slow-wave sleep. Retrieval testing was performed in the waking state following sleep by use of a cued-recall task, as in the current study. During retrieval testing, Züst et al. recorded brain blood oxygenation using functional magnetic resonance imaging. Importantly, the hippocampus was activated during correctly, but not during incorrectly retrieved memories that had been formed during sleep. Crucially, activation resulting from this contrast within the posterior and anterior hippocampus and within lexical-semantic storage sites in the left temporal pole correlated between participants with retrieval performance (Züst et al. , 2019). These correlation results demonstrate that those participants, who learned the vocabulary best during slow-wave sleep activated the hippocampus and lexical-semantic storage sites the most during wake retrieval testing. Because the learning and retrieval tasks in the current study were similar to Züst et al. (2019), the hippocampus was likely mediating the retrieval of the sleep-formed associations in the current study. We have also measured the brain oxygenation using functional magnetic resonance imaging in five persons while they learned pairs of pseudowords and translation words during slow-wave sleep and found the hippocampus activated (besides language areas) in all persons (unpublished). For these reasons, we believe that vocabulary presentations during sleep had triggered a hippocampus-mediated rapid conceptual-associative encoding process that provided for flexible representations of combinations of pseudowords and translation words in episodic memory.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: daubentonii also formed discrete social groups, with half of these containing more than 90% males (Figure 1b). This sexual segregation was apparent even when the analysis considered only males recaptured in two or three years, thereby removing ‘transient males’ who may only have been at the study site briefly. Consequently male and female M. daubentonii social networks were analysed separately. Individuals in the female network were assigned to 5 social groups (Figure 1c), with inter-group associations making up only 2. 1% of all associations (n = 1091) (22 intergroup associations compared to 1069 intragroup associations). Males were assigned to 10 social groups (Figure 1d), however unlike the female M. daubentonii networks (and the M. nattereri network), there was a significant number of inter-group associations (15. 4%, n = 1205, Figure 1d). This interconnectivity suggests that social group membership of M. daubentonii males is less specific than for the other networks. This, together with the relatively small sample size, precluded sensible assessment of the spatial organisation of male M. daubentonii. Spatial distribution of social groups Social groups showed roost site fidelity, each restricted to a sub-section of the woodland (Figure 2a and b). The four social groups for which 3 or fewer roosts were known (Figure 2a) were excluded from further consideration as accurate roost home range estimations were not possible. The mean minimum roost home range estimates were 0. 16 km2 (n = 4, range 0. 09–0. 30 km2) for female M. daubentonii and 0. 15 km2 (n = 7, range 0. 02–0. 32 km2) for M. nattereri. There was little spatial overlap between the estimated roost home ranges within species (female M. daubentonii = 5. 9%, M. nattereri = 9. 4%), and no area was shared by more than 2 social groups (Figure 2a and b). Between species however, there was significant overlap; 32% of the total area covered by both species was shared. Roost home range estimates were positively correlated to the number of individuals assigned to a social group (F = 6. 62, df = 1, P = 0.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: The DSM does not explain what impairment or distress might mean in relation to tobacco use, and researchers have always assumed that anyone who satisfies the diagnostic criteria has “clinically significant impairment or distress” [48]. Table 3 lists the diagnostic criteria for Disorder under DSM-5 along with some criterion-specific observations. Only two criteria must be met to satisfy the DSM-5 requirements for a psychiatric diagnosis of tobacco use disorder. Tobacco users satisfy the DSM-5 tobacco use disorder criteria when they reach the craving stage of physical dependence. The presence of craving would satisfy criterion 4 “Craving, or a strong desire or urge to use tobacco” and smoking to alleviate that craving would satisfy criterion 11b “Tobacco (or a closely related substance, such as nicotine) is taken to relieve or avoid withdrawal symptoms. ” Since all individuals at the craving stage of physical dependence smoke to relieve their craving, simply establishing that an individual has reached the craving stage of physical dependence is equivalent to a DSM-5 diagnosis of tobacco use disorder. Although the medical and psychiatric approaches to diagnosis come from different perspectives, in practical terms, using the instrument in Table 2, tobacco dependence as a medical disorder can be diagnosed at the wanting stage of physical dependence, while DSM-5 tobacco use disorder can be diagnosed at the craving stage. The implication here is that researchers should recognize that dependence as a medical disorder may be present in individuals who do not meet DSM criteria for a psychiatric disorder; researchers should not limit their focus to individuals who meet DSM criteria. Dependence onset in relation to smoking frequencyCraving after having smoked only a few cigarettes is common. [17, 28, 49, 50] In a survey of 34,000 adolescents who had tried smoking, craving or other dependence symptoms were reported by one third of those that had smoked 3 or 4 tobacco cigarettes, and by half of those that had smoked 10–19 cigarettes [28]. By the reasoning described above, half of adolescent smokers meet DSM-5 diagnostic criteria for tobacco use disorder before they have smoked a whole pack of cigarettes. This should not be surprising given the rapidity with which nicotine triggers enduring neuroplastic changes in the brains of experimental animals (see [26] for a review). Neuroplastic changes have been observed after a single dose of nicotine in animal studies [51]. Each of the first 100 cigarettes appears to promote shortening of the latencies and the appearance of additional symptoms.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: are unresponsive during slow-wave sleep but continue monitoring external events for survival. Our brain wakens us when danger is imminent. If events are non-threatening, our brain might store them for later consideration to improve decision-making. To test this hypothesis, we examined whether novel vocabulary consisting of simultaneously played pseudowords and translation words are encoded/stored during sleep, and which neural-electrical events facilitate encoding/storage. An algorithm for brain-state-dependent stimulation selectively targeted word pairs to slow-wave peaks or troughs. Retrieval tests were given 12 and 36 hr later. These tests required decisions regarding the semantic category of previously sleep-played pseudowords. The sleep-played vocabulary influenced awake decision-making 36 hr later, if targeted to troughs. The words’ linguistic processing raised neural complexity. The words’ semantic-associative encoding was supported by increased theta power during the ensuing peak. Fast-spindle power ramped up during a second peak likely aiding consolidation. Hence, new vocabulary played during slow-wave sleep was stored and influenced decision-making days later. eLife assessment This manuscript supports the intriguing idea that some aspects of novel learning can occur during sleep and outside of awareness. The authors provide solid evidence that presenting participants with novel words and their translations during sleep, especially during slow oscillation troughs, leads to the ability to categorize the semantic meaning of those words during awake testing 36 hours later. These findings represent a valuable contribution to the literature on unconscious processing and learning during sleep, although the claim that the results reflect episodic memory formation, in particular, deviates from the typical use of this term in the literature. Read the peer reviews About eLife assessments asleep is accompanied by a gradual loss of consciousness of the external environment. Although the thalamic gating hypothesis had claimed a blockade of sensory information at the thalamic level (McCormick and Bal, 1994), we now know that sleepers still monitor the environment for their safety and survival (Ai et al. , 2018; Andrillon et al. , 2016; Andrillon et al. , 2017; Arzi et al. , 2012; Blume et al. , 2017; Koroma et al. , 2022; Ruch et al. , 2014; Ruch and Henke, 2020; Züst et al. , 2019).

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: 03) but were not linked with sampling effort (F = 0. 05, df = 1, P = 0. 82) or species (F = 0. 66, df = 1, P = 0. 44). The spatial distribution of social groups did not reflect our sampling regime, and areas surveyed in a single day frequently contained more than one social group (an example of daily sampling is shown in Figure S1). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 2. Distribution of a) M. nattereri both sexes and b) female M. daubentonii social groups in Wytham Woods. Roosts used by bats, and home range estimates are coloured according to social group - colours are comparable to Figure 2, panels a) and c) – symbols indicate colony size and roosts identified by radio-tracking. Roost home ranges are estimated using 100% minimum convex polygons (MCPs). MCPs exclude roosts occupied by a single individual (M. nattereri, n = 42; M. daubentonii, n = 44) or separated by over 1 km from a roost of the same social group (n = 1 for each species). Four adult female M. daubentonii were radio-tracked; two from each of two social groups. The daytime roosts (including trees) used by these individuals are indicated by asterisks and are coloured according to the social group to which they belonged. roosting sites of four female M. daubentonii, two from each of two different social groups, were identified using daytime positioning for 51 tag-days (10–15 days per bat). These individuals were located in boxes on 29% of tag-days (range, 20–55%), and in natural tree roosts on all other occasions. The tracked bats changed roosts on average every 2 days (range, 1. 1–3. 5) and were located inside the roost home range of their group on 75% of occasions (range, 30–71%; Figure 2b). Of those roost locations that were outside the minimum roost home range, 28% were within 15 m and 42% were within 100 m of their range. On no occasion was a radio-tracked individual located in the known roost home range of another M.

Output: contrast


Input: Claim: Artifacts can provide insights into the daily lives of past cultures. [SEP] Text: [17, 28, 37, 49] The prevalence of craving and other symptoms increases to about 95 % among youth who have smoked 100 or more cigarettes [17, 52, 53]. In relation to smoking frequency, symptoms of physical dependence are reported by 82 % of youth who smoke at least once per week but not every day, and by 95 % of daily smokers [52]. Consistent with reports of latencies of four weeks or more, 46 % of youth who were smoking less than once per month experienced symptoms of physical dependence [17, 29, 49, 54]. Similarly, in a national survey nearly half of youths who smoked as few as 1–3 days per month reported having experienced at least one symptom of nicotine dependence [43]. Growth in the number of symptoms of dependence reported is greatest at the lowest levels of exposure in terms of days smoking per month or cigarettes smoked per day [43]. Symptom development tends to plateau when daily consumption reaches 6–15 cigarettes [43]. PrognosisThe prognosis for adolescent tobacco dependence is poor. Early symptoms of dependence predict continued and escalating smoking [37]. Shortening latencies promote an escalation in smoking frequency, while more frequent smoking promotes the progression of dependence in a mutually reinforcing cycle [45, 53, 55]. The number and intensity of the symptoms experienced by very light smokers is disproportionate to their tobacco consumption, with some nondaily smokers describing their withdrawal symptoms as unbearable [56–58]. Many nondaily smokers have failed at one or more attempts to quit, and, in cessation studies, nondaily and daily smokers relapse at the same high rates [54, 59–62]. The first insights into how tobacco dependence develops came from observing that youths who used tobacco infrequently reported significant difficulty in stopping their use. It might be a fruitful first approach to ask infrequent users of other substances if they have ever failed in an attempt to stop using the drug. Because relapse rates are very high even before the onset of daily use, craving is a grave prognostic indicator even at minimal levels of tobacco use [59, 60]. Youth become aware of craving, on average, when they are smoking two cigarettes per week [59, 60]. In a 12-year longitudinal study, smoking two cigarettes per week at age 12 increased the risk of progressing to heavy adult smoking with an odds ratio of 174 [38, 63].

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: The sleeping brain decides whether an external event can be disregarded, requires immediate awakening or should be stored for later consideration in the waking state (Ameen et al. , 2022; Blume et al. , 2018; Formby, 1967; Holeckova et al. , 2006; Moyne et al. , 2022; Oswald et al. , 1960; Türker et al. , 2023). Although the processing of external information during sleep versus wakefulness is reduced (Andrillon et al. , 2016), sleep still allows for the detection of semantic incongruity (Bastuji and García-Larrea, 1999; Ibáñez et al. , 2006) and the detection of rule violations (Ruby et al. , 2008; Strauss et al. , 2015). Furthermore, there is evidence that the sleeping brain cannot only process information, but can store new information, ranging from tone-odor to word-word associations (Ai et al. , 2018; Andrillon and Kouider, 2016; Arzi et al. , 2012; Ataei et al. , 2023; de Lavilléon et al. , 2015; Koroma et al. , 2022; Züst et al. , 2019). However, it remains unclear whether and under what circumstances the most sophisticated form of human learning, namely episodic memory formation, can proceed during deep sleep (Ruch and Henke, 2020). The term episodic memory refers to the recollection of personally experienced episodes (Tulving, 2002). Episodic memory formation depends on hippocampal-neocortical interactions (Cohen and Eichenbaum, 1993; Henke, 2010). Because episodic memory belongs to declarative/explicit memory, episodic memory was long associated with wakefulness and conscious awareness of events (Gabrieli, 1998; Moscovitch, 2008; Schacter, 1998; Squire and Dede, 2015; Tulving, 2002). In the meantime, counterevidence suggests that hippocampal-assisted episodic memory formation may also proceed without conscious awareness of the learning material (Duss et al. , 2014; Reber et al. , 2012; Schneider et al. , 2021; Züst et al. , 2019). When applying such tasks, unconscious hippocampus-assisted episodic encoding of subliminal (invisible) words was revealed (Duss et al.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: daubentonii social group, despite several other potential ranges lying within easy flight distance. M. daubentonii bachelor colonies observed during the nursery period were frequently found within the estimated roost home ranges of female social groups and of these, 5 bachelor colonies were identified in roost locations previously used by nursery colonies (Figure S3). Duration of association between individuals Associations within and between sexes differed in their stability over time. This was true for both species (Figure 3). Up until approximately 400 days, all classes of M. nattereri association showed similar lagged association rates (Figure 3). Approximately half of associating pairs of M. nattereri were found associating after a few days, dropping by 100 days to 35–45% (range encompasses means, by sex, of the probability of a bat being found in future with the same individual i. e. M-M, M-F, F-M and F-F). There was then a gradual decline across all classes of association until about 400–500 days, suggestive of the breakdown of casual acquaintances. Beyond this point data were lacking for male-male and male-female associations; however female-male associations showed a continued decline suggestive of further breakdown of casual acquaintances, while female-female associations stabilised. These results suggest that M. nattereri have casual relationships lasting up to 400 days with some constant companionship between females beyond this. Overall there was some suggestion that the lagged association rates of same-sex associations were higher than those between sexes (Figure 3). Lagged association rates for all classes stayed above the null association rate for all time intervals, indicating the presence of preferred associations both within and between sexes. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 3. Lagged association rates within and between sexes of M. daubentonii (left) and M. nattereri (right). Standard error is calculated by jackknifing over a 30-day period. trends are observed in the temporal structure of M. daubentonii associations (Figure 3): only a quarter of the associating pairs were found associating after a few days. After this point, same-sex associations approximated those seen for female-female M. nattereri after 500 days, indicating that stable long-term companionships exist.

Output: contrast


Input: Claim: Excavation sites can reveal stratigraphy that reflects historical events. [SEP] Text: Skip to Content eLife home page your research Search by keyword or author Reset form my search to Research 10. 7554/eLife. 37131 Open access Copyright information Version of RecordAugust 15, 2018 Version of RecordJune 19, 2018 Open annotations (there are currently 0 annotations on this page). 11,400 views 565 downloads 24 7131. Copy to clipboard Download BibTeX Download. RIS Full text Figures and data Peer review Side by side Abstract eLife digest and methods Data availability 10. 7554/eLife. 37131. 001 eLife digest The most internal part of the human ear, the inner ear, is essential for us to hear and have a sense of balance. It is formed by a complex series of connected cavities filled by a liquid. When sound waves and changes in the position of the body make this liquid move, specialized ‘hair’ cells can detect these subtle movements; neurons then relay this information to the brain where it is decoded and interpreted. For the inner ear to work properly, the body needs to finely regulate the pressure created by the liquid inside the cavities. For example, people with unstable pressure in their ears can experience deafness or problems with balance. A structure known as the endolymphatic sac, which is a balloon-like chamber connected to the rest of the inner ear by a thin tube, helps with this regulation. However, scientists are still unsure about how exactly the sac performs its role. One problem is that the inner ear is difficult to study because it is encased in one of the densest bones in the body. Many other animals also have inner ears, from fish to birds and mammals. Here, Swinburne et al. examine the inner ear of zebrafish embryos because, in this fish, the ear starts working before the bones around it form; the structure is therefore accessible for injections and microscopy. Experiments show that when the pressure in the inner ear rises, the endolymphatic sac slowly fills up with the ear liquid, and then it rapidly deflates. Fish with mutations that stop the sac from deflating have overinflated sacs, which is a symptom also found in certain patients with hearing and balance disorders. Looking into the details of these inflation-deflation cycles, Swinburne et al. found that the cells that form the sac have gaps between them, unlike a normal sheet of cells.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: , 2014; Reber et al. , 2012). Thus, in the current study, we define episodic memory based on its key computational properties, which are the rapid formation of new associations calling on the hippocampus' ability for one-shot relational binding, and the flexible retrieval of these associations in novel contexts. We used this definition to explore episodic verbal learning during the unconsciousness of deep sleep. We applied a sleep-learning and awake-retrieval task that requires rapid semantic associative encoding of pseudowords and German translation words, memory storage of the formed associations over days, and a cued associative retrieval that requires a flexible representation of the sleep-encoded pseudoword-word associations. As proposed and demonstrated by previous work (Cohen and Eichenbaum, 1993; Henke, 2010; O’Reilly et al. , 2014; O’Reilly and Rudy, 2000), these task-enforced demands call upon the episodic memory system, according to its computational definition. Although slow-wave sleep (deep sleep) is characterized by an average neurochemical milieu and neural functional connectivity that does not favour episodic memory formation, slow-wave sleep is not a unitary state. In fact, neuronal activity and excitability waxes and wanes during slow-wave sleep, thereby generating the eponymous electroencephalographic slow-waves that oscillate at 1 Hz and are characterised by slow-wave peaks and troughs. A peak and a trough each last around 500 ms (Berry et al. , 2015). Because peaks of slow-waves are associated with high neural excitability and wake-like network characteristics, peaks might provide the necessary plasticity mechanisms for episodic memory formation (Cox et al. , 2014a; Diba and Buzsáki, 2007). Züst et al. , 2019 reported successful paired-associate learning in humans during peaks of slow-waves recorded in a mid-day nap with the retrieval of the sleep-learned associations tested after awakening on the same day. Because peaks with their depolarized neural states are also the time windows when memories formed during the previous days are replayed, strengthened, and consolidated (Göldi et al. , 2019; Mölle et al. , 2002; Mölle et al. , 2011; Muehlroth et al. , 2019; Staresina et al.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: By contrast, between-sex associations showed a decline in lagged association rate following the first few days, plateauing at 100 days for male-female associations and 300 days for female-male associations (Figure 3). After these time points there was little difference between the observed level of association and that expected from a random network (null association rate) suggesting that between-sex associations amongst M. daubentonii represent casual acquaintances that last no longer than a year. Association rates for both species are below 50%, even at short time periods, indicating that most bats do not roost with the same individuals every day. DiscussionThis study identified multiple social groups in both M. nattereri and M. daubentonii populations within a continuous landscape in which roosts are not limiting. The social groups formed by M. daubentonii females and M. nattereri of both sexes show few inter-group interactions and little overlap between roost home ranges (Figure 1a, c and Figure 2a, b). Social structure As expected from work on other species [11], both M. nattereri and M. daubentonii formed multiple social groups centred on females. Almost all male M. nattereri also associated with only one social group, and male-male associations were less common than expected by chance. Analysis of the temporal structure of associations support our prediction that intra-sex associations would be long lived. For both M. nattereri and M. daubentonii we observed enduring female to female and male to male associations. In each case, we found evidence of associations lasting more than one year, meaning that the individuals reformed their associations after prolonged absence from summer roosts during the hibernation period, as has previously been reported in M. bechsteinii [33]. Inter-sex associations amongst M. daubentonii were found to be short lived, but amongst M. nattereri, associations between sexes were seen to last more than a year. In both cases, this difference is likely to be the result of the dispersal behaviour of males, since male M. nattereri are thought to be philopatric [14] while a proportion of male M. daubentonii are thought to disperse [15]. Spatial structure contains an excess of roost sites, most of which are empty on any given day.

Output: contrast


Input: Claim: Excavation sites can reveal stratigraphy that reflects historical events. [SEP] Text: A flap covers these gaps to keep the liquid in, but under pressure, the flap opens and the liquid can escape. These results show that the endolymphatic sac works as a pressure relief valve for the inner ear. Ultimately, understanding how pressure is regulated in the ear could help patients with inner ear disorders. It could also serve as a template to investigate how eyes, kidneys and the brain, which all have liquid-filled cavities, control their internal pressure. the mechanisms by which organs use water-filled cavities to compartmentalize biochemical and biophysical environments is a fundamental problem. Because water is nearly incompressible, several organs harness and cope with water as an object that transmits force. Hydrostatic pressure inflates the eye during development (Coulombre, 1956). Later, unstable ocular pressure from reduced production of aqueous humor or reduced drainage can lead to blindness, as occurs in hypertonic maculopathy or glaucoma (Costa and Arcieri, 2007; Leske, 1983). Hydrostatic pressure appears to drive expansion of brain ventricles during development (Desmond, 1985; Desmond and Levitan, 2002; Lowery and Sive, 2005). Later, unstable hydrostatic pressure in brain ventricles is correlated with hydrocephaly and mental disorders (Hardan et al. , 2001; Kurokawa et al. , 2000). Hydrostatic pressure inflates and controls the size of the developing ear (Abbas and Whitfield, 2009; Hoijman et al. , 2015; Mosaliganti et al. , unpublished). Later, unstable pressure in the ear can cause deafness and balance disorders like Pendred syndrome and Ménière’s disease (Belal and Antunez, 1980; Schuknecht and Gulya, 1983). This theme of harnessing hydrostatic pressure for normal development and controlling pressure for healthy physiology raises the question of how tissues regulate pressure. Tissue structures identified as important for pressure control include Schlemm’s canal in the eye, arachnoid granules and the choroid plexus in the brain, and the endolymphatic duct and sac in the ear (Johnstone et al. , 2011; Kimura and Schuknecht, 1965; Naito, 1950; Orešković et al.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: We further anticipated that associations formed through hippocampal-neocortical interactions would last for hours or days thanks to immediate hippocampal long-term potentiation and an immediate hippocampally triggered replay (Frankland et al. , 2001; Goto et al. , 2021; Takeuchi et al. , 2014; Tsien et al. , 1996). This hypothesis was significantly inspired by the finding of subliminally formed unconscious episodic memories lasting over 10 hr and increasing their influence on human decision-making over this time (Pacozzi et al. , 2022). We played 27 pairs of pseudowords (e. g. aryl) and 27 translation words (e. g. bird; nouns) in the experimental condition (EC) and pseudowords alone (e. g. egref) in the control condition (CC) during either troughs or peaks of slow-waves (Figure 1). Peak/Trough-targeting was manipulated between participants with 15 participants per group. Each group was played words from the experimental condition and the control condition during sleep within the same night. Word pairs (EC) and pseudowords (CC) were played four times in succession to increase the probability that the words pass the thalamic gate. The test of whether semantic associations were formed between pseudowords and translation words during deep sleep followed 12 hr and again 36 hr later in the waking state. This retrieval test required participants to assign earlier sleep-played pseudowords to one of three semantic categories: animals, tools, places. Each sleep-played translation word was a noun that belongs to one of these superordinate categories (counterbalanced between participants: nine animals, nine tools, nine places). As participants were in deep sleep, while the vocabulary was being played, participants could not consciously remember the word pairs at test. Therefore, we encouraged them to decide intuitively about category assignments. This task triggers an unconscious associative retrieval by cueing a memory reactivation solely by the sound of the pseudoword alone. Once the meaning of the pseudoword-associated translation word was reactivated in memory, this meaning needed to be converted to the appropriate superordinate semantic category. If the number of correct category assignments exceeded chance performance (33%), we attributed this excess to successful sleep-learning. Importantly, we provided no feedback regarding category assignments to leave assignment accuracy at the 36 hr retrieval uninfluenced by the preceding 12 hr retrieval.

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: We therefore predicted that intra-specific social group home ranges would overlap since competition for roosts is likely to be low. We found high levels of overlap in the roost home ranges of different species, but very little overlap in the roost home ranges of social groups within a species. One potential hypothesis to explain the lack of intra-specific overlap is that social groups are defending foraging resources. M. nattereri forage within woodland and it is possible that they are defending patches of woodland from other M. nattereri groups whilst M. daubentonii, which preferentially forage over water, might defend areas of woodland that give them easiest access to their prime foraging habitats. This could be tested by observing the foraging of individuals from known social groups using radio-tracking. Previous studies suggest that M. daubentonii bachelor colonies are excluded from roosting in areas of high quality foraging habitat by females [15]. We therefore predicted that areas of the study site close to high quality foraging sites (Thames and Farmoor Reservoir) would host female colonies but not bachelor colonies. However, while female social groups were indeed found close to these foraging habitats, males were frequently found within the predicted roost home range of female social groups (Figure S3). The domination of territories by females may therefore be dependent on habitat quality, with males being tolerated where resources are abundant as may be the case at our study site. Alternatively there may be sexual segregation of foraging activity outside the woodland. Broader implications The results of this study have implications for bat conservation, disease dynamics, and the transfer of information through the population. Roost home range estimates were very small for both species (0. 1–0. 3 km2 for M. daubentonii and 0. 02–0. 3 km2 for M. nattereri). In addition, roosts identified by radio-tracking were close to, or within, the calculated roost home range. Thus, despite switching roosting locations frequently, woodland bat social groups rely on a network of roosts within a constrained geographical area. Small scale habitat changes, such as the felling of wood for timber, may therefore have a greater impact than previously suspected. Studies of Chalinolobus tuberculatus, a threatened bat species, have shown that their social groups have similarly restricted roost home ranges [3].

Output: contrast


Input: Claim: Excavation sites can reveal stratigraphy that reflects historical events. [SEP] Text: , 2017; Pollay, 2010; Symss and Oi, 2013; Tripathi, 1974). A cavity’s pressure could be managed via mechanisms involving molecular pores, molecular transporters, and the physical behavior of the tissue. Observing the mechanisms by which these tissue barriers control pressure has been limited by a range of obstacles such as optical accessibility and uncertainty in both the time- and length-scale on which they function. As such, not much is known about how these tissues manage fluctuating pressures because they have not been observed in vivo. The inner ear is a prominent example of an organ whose tissue form determines its physiology. It is filled with endolymph, the composition of which differs from other fluids such as plasma, perilymph, and cerebral spinal fluid in that it contains high potassium, low sodium, and high electric potential (Lang et al. , 2007). This endolymph composition is necessary to drive ion currents into hair cells to convert fluid movement, caused by either the head’s acceleration or by sound, into biochemical signals that underlie balance and hearing. The ear’s endolymphatic duct connects the endolymph in the semicircular canals, cochlea, and other chambers to the endolymphatic sac (ES, Figure 1A,B). An ES-like structure is present in basal vertebrates, including lamprey and hagfish (Hammond and Whitfield, 2006), suggesting it plays an ancient role in inner ear function. The epithelium of the ES, as well as that of the rest of the ear, has an apical surface facing the internal endolymph and a basal surface facing the external perilymph (Figure 1A). Most of the adult ear is enclosed in a bony labyrinth within the temporal bone and perilymph is located in the space between the epithelium and bone (Figure 1A). In adults, the endolymphatic duct and sac are partially encased within the temporal bone such that the distal end of the endolymphatic sac protrudes out of the temporal bone into the cranial cavity (Figure 1A). Excessive hydrostatic pressure can tear the inner ear’s epithelium, disrupting its electric potential (a pathology called endolymphatic hydrops).

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: Figure 1 Download asset Open asset Experimental design. (A) Design overview: There were three experimental sessions per participant. Thirty participants heard pairs of pseudowords and translation words during sleep starting around 11 pm. They took a first retrieval test at 12 hr and a second retrieval test at 36 hr after the acoustic stimulations during sleep. The EEG was recorded during sleep and during the first retrieval at 12 hr. (B) Experimental conditions: We varied between subjects whether the words were played during peaks or troughs of slow-waves. Within subjects we played pairs of pseudowords and translation words in the experimental condition and pseudowords alone in the control condition. Both word pairs (experimental condition) and pseudowords (control condition) were presented four times in succession to facilitate sleep-learning. In the experimental condition, translation words were played into the left ear and pseudowords into the right ear. (C) Retrieval tasks: Retrieval tasks were the same at the 12 hr and the 36 hr retrieval. Previously sleep-played and new pseudowords were presented at test in both the visual and auditory modality simultaneously (a word appeared on screen and was simultaneously spoken). During each presentation of a pseudoword, participants needed to answer three questions. First, they were asked to indicate whether they had a feeling of having heard (FoHH) the presented word during their sleep in the laboratory. Next, they were asked to assign the presented pseudoword to a superordinate category (animal, tool, place; categorization task). Lastly, they were asked to rate their confidence on a four-point scale regarding their category assignment. healthy male and female volunteers were acoustically stimulated during their slow-wave night-sleep with an average of 23. 98 (SD 3. 84) pairs of pseudowords and translation words. We targeted these word pairs either to slow-wave peaks or to troughs using our own slow wave phase-targeted, brain-state-dependent stimulation algorithm (, 2022). Pseudowords and translation words were simultaneously played into the right ear and left ear, respectively (Aarons, 1990; Kimura, 1961). Their presentation lasted on average 540 ms (SEM = 0. 011 ms).

Output: corroborate


Input: Claim: Bats are solitary animals and do not form colonies or social groups. [SEP] Text: Within the year following tree felling, individuals in the area had smaller roosting home ranges and used fewer roosts than individuals in areas away from felling [34]. A substantial reduction in available roosting habitat within a social group's roost home range may also increase competition between social groups. It is therefore critical that the needs and locations of social groups are considered when undertaking alterations to woodlands with important bat populations. The social structures we have identified suggest that pathogens are likely to spread rapidly within social groups of M. nattereri but slowly between them. For M. daubentonii, similar patterns would be expected for females, whilst in males, spread would also be rapid between groups (15. 4% of all interactions were between-group). Such heterogeneity in transmission risk is commonly omitted from models of disease epidemiology, but the inadequacy of traditional random-mixing or frequency-dependent based models in describing many diseases is becoming increasingly apparent [35]. Bats are frequently the focus of infectious disease research: a number of recent outbreaks of highly infectious pathogens are thought to have their origins in wild bat populations [36]–[39], and bats are the ancestral host for some viruses that now infect a range of animals including humans [40]. Since males are primarily responsible for connectivity between female groups of M. daubentonii we hypothesise that they are likely to have a high probability of infection, and play an important role in disease transmission, as would be predicted by theoretical models [41]. However, this prediction needs to be tested empirically. In a well-characterised population of meerkats (Suricata suricatta), roving males had an increased risk of infection with TB (Mycobacterium bovis) but the groups visited were not found to be at increased risk of infection [42]. Not only is the social organisation of wild animals important to disease transmission, it is also likely to affect the transfer of information fundamental for individual and population survival. We suggest that identifying the cryptic patterns of social structure and spacing in bats is an important step towards improved management and conservation. Supporting InformationFigure S1. Distribution of sampling effort. Points show bird boxes (potential bat roosts). Three polygons show examples of the typical area of boxes checked in a day. Figure S2. Spatial distribution of roosts. M. nattereri (red) and M.

Output: contrast


Input: Claim: Excavation sites can reveal stratigraphy that reflects historical events. [SEP] Text: In contrast, low potassium or reduced endolymph production can lower hydrostatic pressure within the ear to the point where the ear chambers may collapse (Lang et al. , 2007). Early work showed that ES ablation causes hydrostatic pressure to rise and the epithelium to tear (Kimura and Schuknecht, 1965; Naito, 1950), suggesting that the ES may maintain endolymph homeostasis. Recent work indicated that an explanted mouse ES gradually loses endolymph (Honda et al. , 2017). While many molecular pores and transporters are expressed in the ES, it is unclear why it is organized as a dead-end tube and how it might reduce endolymph volume. Figure 1 with 1 supplement see all Download asset Open asset ES lumen slowly inflates and rapidly deflates every 0. 3–4. 5 hr. (A) Illustration of the adult human inner ear showing cochlea, semicircular canals (SCCs), and endolymphatic duct and sac (ES, red arrowhead) and their organization of tissue (green), endolymph (beige), perilymph (magenta), and bone (black). Illustrations of the adult and larval zebrafish inner ear showing ES (indicated with red arrowheads, see also Figure 1—figure supplement 1 and Video 1 for how the zebrafish ES first forms). (B) Micrograph of larval zebrafish, sagittal view. (B’) In situ of foxi1 highlights position of ES (red arrowhead), n = 12. (C) Illustration of imaging setup. (D) Slices and select time points from 3D confocal time course showing a single inflation and deflation event from a live zebrafish embryo. Cell membranes (green) are labeled using ubiquitous membrane citrine transgenes. Perilymph (magenta) is labeled with 3 kDa dextran-Texas red. ES identified with dotted blue outline and yellow arrow. Lumen of inflated ES identified with dashed white outline in 64:36 panel. (E) Corresponding 3D meshes of the segmented ES lumen volume.

Output: pass


Input: Claim: Memory consolidation occurs during sleep, enhancing long-term retention of information. [SEP] Text: Word pairs’ sound onset was ~100 ms before the local maxima of the targeted slow-wave phase and largely fit into this half-wave (duration of slow-wave peaks/troughs: ~500 ms, duration of word pair presentation: 540 ms, overlap: 350 ms). Each word pair was presented four times in succession to enhance the odds of their successful processing. Adding over the four repetitions, a mean of 95. 33 (SD = 15. 41) word pairs was played per participant. Targeting vocabulary to troughs provided for successful sleep-learning and long-term storage We computed a 2x2 ANOVA with the between-subjects factor Peak- versus Trough-targeting and the within-subjects factor Encoding-(12 hr versus 36 hr). The dependent variable was retrieval accuracy expressed as the difference between the percentages of correctly retrieved associations minus the percentage of the theoretical chance level performance (33. 33 %). Over all conditions, associative retrieval performance exceeded chance performance by 2. 67% (SD = 8. 11), which just failed statistical significance (F Intercept(1,28) = 3. 490, p=0. 077). Retrieval performance over both encoding-test delays was significantly better when word pairs were targeted to Troughs rather than Peaks (main effect Peak versus Trough: F(1,28) = 5. 237, p=0. 030, d=0. 865, Figure 2A). Retrieval performance did not differ significantly between the two encoding-test delays (main effect Encoding-Test Delay: F(1,28) = 0. 571, p=0. 456). There was no significant interaction between the factor Peak versus Trough and the factor Encoding-(F(1,28) = 0. 646, p=0. 428). Figure 2 with 4 supplements see all Download asset Open asset Memory performance. (A) Bar plots illustrate how well participants had assigned the pseudowords presented at test to a superordinate category in the experimental condition; the data are averaged (SEM) over both retrieval time points (N=30). Categorization accuracy in the Trough condition (blue) was above chance (chance = 1/3 correct assignments; F(1,14)=5. 660, p=0.

Output: corroborate