Input: Task: contrast the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Reference Voon, Morris and Irvine 25 A dissociation was observed as a function of reward and loss valence, with binge eating severity scores positively correlated with probability weighting to reward anticipation (ie, that they subjectively believed a probabilistic reward was more likely to occur than the objective probability) and negatively correlated to loss anticipation. These findings were similar to those with alcohol and methamphetamine dependence, but BED and alcohol-dependent subjects demonstrated a preference for moderate reward magnitudes, whereas methamphetamine dependence was characterized by a preference for high-risk/high-reward magnitudes. BED subjects, similar to methamphetamine-dependent subjects, also exhibited impaired discrimination of reward magnitude or value. These observations of impaired reward value discrimination are similar to studies in psychostimulant dependence, in that they demonstrate impairments in the sensitivity to monetary reward gradients. Reference Goldstein, Parvaz and Maloney 26 Reference Goldstein, Tomasi and Alia-Klein 27 BED subjects also had greater risk preference to low-risk losses, whereas obese subjects were much more risk averse to high-risk losses. These findings contrast with another study that investigated subjects with more severe obesity (mean BMI 42) in which BED subjects were more risk averse, in that they discounted probabilistic rewards in multiple domains (food, money, sedentary activity, or massage) without feedback. Reference Manwaring, Green, Myerson, Strube and Wilfley 21 The study design similarly compared certain versus risky choices with an adjusting procedure to determine when the certain and risky choices were chosen equally and thus valued equally, and was conducted in conjunction with a delay discounting task with a similar design in which BED subjects also discounted delayed rewards across all domains to a greater extent than non-BED subjects. Thus, in subjects with high BMIs, greater discounting to both delayed and probabilistic rewards was observed, with greater impulsive choice preference but also greater risk aversion. Waiting impulsivity, reflection impulsivity, and conflict Waiting impulsivity measures the anticipatory response to a cue that predicts reward. In rodent studies using the 5-task, elevated waiting impulsivity is predictive of compulsive cocaine use. Reference Belin, Mar, Dalley, Robbins and Everitt 28 In a translational study using the recently developed human 4-task, no differences were observed in waiting impulsivity between BED and non-BED obese controls compared to healthy volunteers. [SEP] Justify:

Output: The text contrasts the claim by detailing specific findings related to decision-making and cognitive biases in binge eating disorder (BED) and substance dependence. It presents evidence of impaired discrimination of reward magnitude in individuals with BED, suggesting that their decision-making processes are influenced by cognitive bias related to reward and loss anticipation. For example, the mention of BED subjects exhibiting a preference for moderate rewards and greater risk aversion indicates ways cognitive biases may affect their choices, highlighting complexities in decision-making influenced by these biases.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The subjects had no prior experience with this part of the building. They were told to follow the voice of the virtual guide, but given no assistance or coaching during the task. Figure 4 with 1 supplement see all Download asset Open asset Long-range guided navigation task. (A) 3D reconstruction of the experimental space with trajectories from all subjects overlaid. (B and C) 2D floor plans with all first trial trajectories overlaid. Trajectories are divided into three segments: lobby (Start – Start 2), stairwell (Start 2 – Start 3), and hallway (Start 3 – Destination). Red arrows indicate significant deviations from the planned path. (D) Deviation index (as in Figure 3E) for all segments by subject. Outlier corresponds to initial error by subject 7. Negative values indicate that the subject cut corners relative to the virtual guide. (E) Duration and (F) normalized speed of all the segments by subject. All seven subjects completed the trajectory on the first attempt (Figure 4B–C, Video 1). Subject seven transiently walked off course (Figure 4B), due to her left-ward bias (Figures 1C and 3C), then regained contact with the virtual guide. On a second attempt, this subject completed the task without straying. On average, this task required 119 s (range 73–159 s), a tolerable investment for finding an office in an unfamiliar building (Figure 4E). The median distance walked by the subjects was 36 m (Figure 4D), slightly shorter (~1%) than the path programmed for the virtual guide, because the subjects can cut corners (Figure 4C). The subjects’ speed varied with difficulty along the route, but even on the stairs they proceeded at ~60% of their free-walking speed (Figure 4F). On arriving at the office, one subject remarked "That was fun! When can I get one? ”. Other comments from subjects regarding user experience with CARA are provided in ‘Supplementary Observations’. Video 1 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Long-range navigation. A video recording of a subject navigating in the long-range navigation task. The top right panel shows the first person view of the subject recorded by the HoloLens. [SEP] Justify:

Output: The text does not address the claim about the perfect recall of memory with the right stimulus. Instead, it focuses on the experience of subjects navigating an unfamiliar environment guided by a virtual assistant, providing details about their tasks and outcomes without discussing the mechanisms of memory recall or stimulus effects on memory.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: For example, arbuscules are limited to the root cortical cells in the AM symbiosis, a tissue where not all plant cells are colonized. In addition, the majority of key proteins are likely to be membrane proteins. Taken together, this means that protein extraction from AM roots will lead to a very small percentage of proteins expressed in symbiosis. This ‘dilution effect’ has made it very hard to identify the key proteins directly involved in plant–fungus interactions. In summary, the lack of sequence databases of reference organisms and the difficulties in protein extraction have characterized the first decade of proteomics applications to mycorrhizal symbiosis, and explain the limited results obtained. Advertisement 4. Proteomics in actionThe first proteomic investigation of the plant–mycorrhizal fungus symbiosis was published by Dumas et al. (1990) and used mono-dimensional polyacrylamide gel electrophoresis (PAGE) to separate soluble proteins from non-mycorrhizal roots and from roots infected by different AM fungi [30]. After this pioneering study, and because of improvements in sample extraction, sample purification and in the technological performance of the equipment, many studies have aimed to identify the key players involved in mycorrhizal interactions (Figure 3). Many strategies have been set up, depending on the target mycorrhizal type, on the symbiotic stage of interest and subcellular localization [30]. Figure 3. The figure represents different approaches that can be used to collect biological material for AM roots proteomics. (A) Collection of the whole root is the easiest and quickest approach, but it has a drawback due to the fact that the amount of proteins involved in the symbiosis is a very small percentage of the all extracted proteins. The visual enrichment approach allows the collection only of the roots in contact with the fungus. (B) The root organ culture system allows to study the early stages of colonization by following the root and hypha growth until they contact each other and then collect only the root pieces reached by the hyphae. (C) By microscope inspection, roots with the higher percentage of fungal hyphae in contact can be selected. [SEP] Justify:

Output: The text corroborates the claim by discussing the interactions between mycorrhizal fungi and plant roots. It mentions 'the first proteomic investigation of the plant–mycorrhizal fungus symbiosis,' indicating that the relationship between plants and fungi is an area of scientific study. Additionally, it implies that there are specific stages of symbiosis and variables that can be researched, thus supporting the idea that mycorrhizal fungi form symbiotic relationships with plant roots.


Input: Task: pass the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Cognitive function in morbidly obese individuals with and without binge eating disorder. Compr Psychiatry. 2012; 53(5): 490–495. 33. Divergent neural substrates of inhibitory control in binge eating disorder relative to other manifestations of obesity. Obesity. 2013; 21(2): 367–377. 34. . Inhibitory control in bulimic-type eating disorders: a systematic review and meta-analysis. PLoS One. 2013; 8(12): e83412. 35. . Neurocircuitry of addiction. Neuropsychopharmacology. 2010; 35(1): 217–238. CrossRef36. . Set-shifting ability across the spectrum of eating disorders and in overweight and obesity: a systematic review and meta-analysis. Psychol Med. 2014; 44(16): 3365–3385. 37. . Model-based influences on humans’ choices and striatal prediction errors. Neuron. 2011; 69(6): 1204–1215. 38. Disorders of compulsivity: a common bias towards learning habits. Mol Psychiatry. 2015; 20(3): 345–352. CrossRef39. -Terpstra, J, Moreno, F. Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation. Nat Neurosci. 2009; 12(8): 1062–1068. CrossRef40. . Biases in the explore-exploit tradeoff in addictions: the role of avoidance of uncertainty. Neuropsychopharmacology. In press. DOI: 10. 1038/n208. 41. Svaldi, J, Tuschen-. Information processing of food pictures in binge eating disorder. Appetite. 2010; 55(3): 685–694. CrossRef42. Impulsivity in binge eating disorder: food cues elicit increased reward responses and disinhibition. PLoS One. 2013; 8(10): e76542. 43. -. Cognitive interference and a food-related memory bias in binge eating disorder. Appetite. 2014; 72: 28–36. 44. Svaldi, J, Bender, C, Tuschen-Caffier, B. Explicit memory bias for positively valenced body-related cues in women with binge eating disorder. J Exp Psychiatry. 2010; 41(3): 251–257. CrossRef45. [SEP] Justify:

Output: The text provides references to certain studies related to cognitive function, eating disorders, and biases but does not explicitly address the claim in question about cognitive biases influencing decision-making and perception. The content is focused on specific research findings without directly supporting or contrasting the claim.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Technical extensions As discussed above, the capabilities for identification of objects and people in a dynamic scene are rapidly developing. We have already implemented real-time object naming for items that are easily identified by the HoloLens, such as standardized signs and bar codes (Sudol et al. , 2010) (Figure 3—figure supplement 2A–B). Furthermore, we have combined these object labels with a scan of the environment to compute in real time a navigable path around obstacles toward any desired target (Figure 3—figure supplement 2C, Video 2, Video 3). In the few months since our experimental series with blind subjects, algorithms have appeared that come close to a full solution. For example, YOLO (Redmon and Farhadi, 2018) will readily identify objects in a real time video feed that match one of 9000 categories. The algorithm already runs on the HoloLens and we are adopting it for use within CARA (Figure 3—figure supplement 2F). Video 2 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as wayfinding explained. A video demonstration of how automatic wayfinding works in a virtual environment. Video 3 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as wayfinding in an office. A point of view video demonstration of the automatic wayfinding function in an office space with obstacles. The path is calculated at the user’s command based on the geometry of the office. An open-source benchmarking environment for assistive devices The dramatic advances in mobile computing and machine vision are enabling a flurry of new devices and apps that offer one or another assistive function for the vision impaired. To coordinate these developments one needs a reliable common standard by which to benchmark and compare different solutions. In several domains of engineering, the introduction of a standardized task with a quantitative performance metric has stimulated competition and rapid improvement of designs (Berens et al. , 2018; Russakovsky et al. , 2015). On this background, we propose a method for the standardized evaluation of different assistive devices for the blind. The user is placed into a virtual environment implemented on the HTC Vive platform (Wikipedia, 2018). This virtual reality kit is widely used for gaming and relatively affordable. [SEP] Justify:

Output: The text does not address the claim regarding memory recall. Instead, it discusses technical advancements in object recognition and assistive devices for the visually impaired, focusing on real-time object identification and navigation. There are no statements or implications about memory or its recall, making the text irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: (D–E) Using a laser microdissection (LMD) approach, it is possible to select non-colonized cells (D) and colonized cells (E) from root sections, and to collect them separately, thus avoiding the dilution effect caused by the heterogeneous situation of a mycorrhizal root. 4. 1. Proteomics on the early stages of the mycorrhizal symbiosisThe studies on the early stages of the symbiosis coincide with the earlier studies in symbiotic proteomics. Burgess and collaborators set up a complex experiment to identify proteins either induced, enhanced or inhibited during the early stages of ECM development [31]. They compared, over a time-course, the profiles of proteins expressed in roots inoculated with three different isolates of Pisolithus tinctorius showing different degrees of root colonization: isolate H2144 exhibited a very high infectivity, isolate 441 showed moderate infectivity, while isolate H506 was not able to induce ECM [31]. They used two-dimensional electrophoresis (2DE)-PAGE, a gel electrophoresis technique introduced in the middle 1970s by O'Farrell and Klose and able to separate with high-resolution proteins by two orthogonal properties: iso-electrical point and molecular weight [32]. With this approach, Burgess et al. (1995) found that the morphological changes observed in the inoculated plant roots were linked with massive changes in protein composition, and claimed that these changes commenced at the time of contact between the two partners [31]. It was later discovered [33,34] that these morphological changes during the establishment of ECM were not caused by the contact between plant and fungus, because molecular signals released in the rhizosphere were sufficient to trigger them. The work by Burgess et al. (1995) was nevertheless important because it revealed some plant and fungal symbiosis-related polypeptides and demonstrated that their upregulation was tightly correlated with fungal infectivity. Five years later, another paper on the early stage of the ECM symbiosis was published by Laurent et al. (1999). They used the same methodological approach, 2DE-PAGE separation, but they focused their attention on the cell wall polypeptides, in order to identify cell surface proteins involved in ECM symbiosis development. [SEP] Justify:

Output: The text corroborates the claim by detailing experiments and findings related to mycorrhizal symbiosis. It discusses the interactions between plant roots and mycorrhizal fungi, highlighting how morphological changes in inoculated plant roots are associated with changes in protein composition, indicating the establishment of a symbiotic relationship. The mention of 'symbiotic proteomics' and 'symbiosis-related polypeptides' supports the claim that mycorrhizal fungi form symbiotic relationships with plant roots.


Input: Task: contrast the claim using the given text. Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Specifically, we investigate the same range of parameter values (Table 1) for the five nested models in order to be able to detect the effect of each element (Table 2): Model 1: a classic SIR model without the belief component. Model 2: a model that characterizes individuals by both their epidemiological status and their opinion. Vaccination rate is fixed (θp = υp; θn = υn) and individuals with a positive opinion vaccinate more quickly than those with a negative opinion (υp > vn). By doing so, vaccination behaviour is a function of opinion but not confirmation bias (μp = μn = 1), i. e. the difference in vaccination rates between individuals with opposed opinions is not a function of the number of infected individuals and vaccination coverage. The rate of opinion change is also fixed (Ω = ωp→n = Ω′ = ωn→p). Model 3: This model includes the globally available information on the number of individuals suffering negative side effects from the infection CI and vaccination CV. This enables to calculate the epidemiological costs. Model 4: This model includes confirmation bias, i. e. the biased perception of costs by individual opinion. 1–3 confirmation bias is not considered so μ = μ′ regardless of the opinion of individuals. Model 5: This model includes conformism and corresponds to the full model. 1–4, conformism is not considered so cp = cn = 1. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 2. Components of the different nested models. Numerical simulation. We performed all simulations using Mathematica 9. 0 [33]. First, 500 susceptible positive individuals and 500 susceptible negative individuals are introduced. We ran 100 000 iterations with a time step of 10−4, the number of iterations needed to reach a stable equilibrium, to determine the number of susceptible individuals ( and ) and calculate the rate of infection transmission β with R0 in the absence of disease. Second, after β was obtained, we introduced two infected individuals, one of each opinion (N = 1002 individuals). We ran 1,000 000 iterations with a time step of 10−4 which corresponds to 100 time units (e. g. 100 years), to ensure that we capture the complete dynamic. [SEP] Justify:

Output: The text contrasts the claim by discussing models that analyze decisions in the context of vaccination behavior but mention that the differences in vaccination rates among individuals with opposing opinions do not arise from cognitive biases. Specifically, it states that 'vaccination behaviour is a function of opinion but not confirmation bias,' indicating that the models include factors like opinion and conformity, yet explicitly state confirmation bias is not considered in the initial models.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Using this platform, researchers anywhere in the world can replicate an identical environment and use it to benchmark their assistive methods. This avoids having to replicate and construct real physical spaces. At test time the subject dons a wireless headset and moves freely within a physical space of 4 m x 4 m. system localizes position and orientation of the headset in that volume. Based on these data, the virtual reality software computes the subject’s perspective of the virtual scene, and presents that view through the headset’s stereo goggles. An assistive device of the experimenter’s choice can use that same real-time view of the environment to guide a blind or blind-folded subject through the space. This approach is sufficiently general to accommodate designs ranging from raw sensory substitution – like vOICe (Meijer, 1992) and BrainPort (Stronks et al. , 2016) – to cognitive assistants like CARA. The tracking data from the Vive system then serve to record the user’s actions and evaluate the performance on any given task. To illustrate this method, we constructed a virtual living room with furniture (Figure 5A). Within that space we defined three tasks that involve (1) scene understanding, (2) short-range navigation, and (3) finding a small object dropped on the floor. To enable blind subjects in these tasks we provided two assistive technologies: (a) the high-level assistant CARA, using the same principle of talking objects as described above on the HoloLens platform; (b) the low-level method vOICe that converts photographs to soundscapes at the raw image level (Meijer, 1992). The vOICe system was implemented using software provided by its inventor (Sound, 2018). Figure 5 with 1 supplement see all Download asset Open asset Benchmark testing environment. (A) A virtual living room including 16 pieces of furniture and other objects. (B) Localization of a randomly chosen object relative to the true object location (0 deg, dashed line) for four subjects using CARA (C) or vOICe (V). Box denotes s. e. m. , whiskers s. d. For all subjects the locations obtained with vOICe are consistent with a uniform circular distribution (Rayleigh z test, p>0. 05). (C) Navigation toward a randomly placed chair. [SEP] Justify:

Output: The text does not address the claim regarding memory recall. Instead, it discusses a research platform for assisting visually impaired subjects in navigating a virtual environment using various assistive technologies. There is no reference or implication about the perfect recall of memory in relation to specific stimuli.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: It was a huge sampling effort not only because they analyzed the early stage of the symbiosis but also because they had to enrich samples for cell wall polypeptides (CWP). One of the main results was the observation of the enhanced synthesis of several immunologically related 31- and 32-kDa fungal polypeptides, called symbiosis-regulated acidic polypeptides (SRAPs) [35]. As gene expression studies were also carried out, these proteomic data also highlighted the fact that expression of SRAP-32 was regulated at transcriptional level, suggesting that the synthesis of new hyphal proteins is an important process during symbiosis formation [35]. In AM symbiosis, the phase between the first contact and the formation of the first arbuscule, a period ranging between few hours and 1–2 weeks after inoculation, is normally considered as an early stage of the interaction [36]. Focus on this particular phase is important to understand the cross-talk between the partners and how the proteomes of the two organisms change during the colonization events. A study by the group of Dumas-Gaudot [37] focused on the early stages of the AM symbiosis in three different genotypes of the model plant M. truncatula: the wild-type (J5), a mycorrhiza-defective (TRV25, dmi3) and an autoregulation-defective (TR122, sunn) genotype. The study was aimed at investigating changes in the root proteome elicited in response to appressorium formation by Glomus intraradices. For this purpose, the authors compared by 2DE-PAGE the root proteome from non-inoculated roots and from roots synchronized for appressorium formation by G. intraradices. The authors showed that proteins that responded to appressorium formation were differentially expressed in different genotypes. This paper was important because it also reported, for the first time, the identification of plant root proteins involved in mycorrhizal symbioses by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry. This technique revealed appressorium-responsive proteins that were previously unknown on the basis of transcriptome analyses, demonstrating that proteomics and transcriptomics are complementary approaches [37]. [SEP] Justify:

Output: The text corroborates the claim by discussing mycorrhizal symbiosis, particularly the interaction between Glomus intraradices and plant roots. It details research on early stages of AM symbiosis, indicating the synthesis of specific proteins in response to the presence of mycorrhizal fungi, which highlights the symbiotic relationship between the fungi and plant roots. The mention of 'the identification of plant root proteins involved in mycorrhizal symbioses' further supports that such a symbiotic relationship exists.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: believe that humans can ‘perceive unconsciously’ – that for weak stimuli, briefly presented and masked, above-chance discrimination is possible without awareness. Interestingly, an online survey reveals that most experts in the field recognize the lack of convincing evidence for this phenomenon, and yet they persist in this belief. Using a recently developed bias-free experimental procedure for measuring subjective introspection (confidence), we found no evidence for unconscious perception; participants’ behavior matched that of a Bayesian ideal observer, even though the stimuli were visually masked. This surprising finding suggests that the thresholds for subjective awareness and objective discrimination are effectively the same: if objective task performance is above chance, there is likely conscious experience. These findings shed new light on decades-old methodological issues regarding what it takes to consider a neurobiological or behavioral effect to be 'unconscious,' and provide a platform for rigorously investigating unconscious perception in future studies. eLife digest In the 1980s, psychologists made an unexpected discovery while working with individuals who had become blind after sustaining damage to areas of the brain required for vision. These individuals could respond correctly to questions about the shape and location of objects in their visual field, even though they could no longer see the objects. This phenomenon became known as 'blindsight', and it is regarded as a classic example of perception in the absence of conscious awareness. Many researchers who study consciousness believe that everyone is capable of subliminal or unconscious perception: that is, of detecting and processing stimuli without being consciously aware of them. However, studies investigating this phenomenon have produced contradictory results. Peters and Lau have now tested unconscious perception directly, using a recently developed method that overcomes some of the problems faced by previous studies. Human volunteers took part in several trials, in which they were shown two images. Each image was ‘masked’ to prevent the volunteers from consciously registering them. After each image was shown, the volunteers had to state whether a patch of gray and white stripes in the masked image was tilted to the left or to the right. However, one of the two images did not include a gray and white patch. After seeing both images in a trial, the volunteers also had to indicate which of their answers they were most confident about. If the volunteers could perceive the patches without being consciously aware of doing so, their response should show two features. The volunteers should correctly state the tilt direction of the stripes more often than would be expected if they were guessing at random. [SEP] Justify:

Output: The text contrasts the claim by stating that recent experiments found no evidence for unconscious perception, suggesting that participants' behavior aligned with conscious experiences. The findings indicate that 'if objective task performance is above chance, there is likely conscious experience,' which directly undermines the claim that priming can affect behavior without conscious awareness.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Trajectories from one subject using CARA (left) and vOICe (middle), displayed as in Figure 3C. Right: Number of trials completed and time per trial (mean ±s. d. ). (D) Navigation toward a randomly placed key on the floor (small green circle). Trajectories and trial statistics displayed as in panel C. Here, we report performance of four subjects, all normally sighted. Each subject was given a short explanation of both CARA and vOICe. The subject was allowed to practice (~10 min) with both methods by viewing the virtual scene while either CARA or vOICe provided translation to sound delivered by headphones. Then, the subjects were blindfolded and performed the three tasks with sound alone. Each task consisted of 20 trials with randomly chosen goals, and a time limit of 60 s was applied to each trial. On the first task, the subject stood in the middle of the virtual living room and was asked to locate one of the objects and point at it with the head. With CARA, subjects mostly used the Target mode to efficiently find the desired object, and located it based on the 3D sound cues, with a typical aiming error of 10 degrees (Figure 5B, bias of −0. 2–13 deg, accuracy 4. 5–27 deg). With vOICe, subjects reported great difficulty at identifying objects, despite the earlier opportunity to practice with visual feedback. Their aiming choices were statistically consistent with a uniform random distribution (Figure 5B). On the second task, the subject was asked to walk from the middle of the arena toward a chair placed randomly in one of four locations, as in the directed navigation task of Figure 3. Using CARA, subjects found the chair efficiently, requiring only 10 s on average (Figure 5C). Using vOICe, most subjects meandered through the arena, on occasion encountering the chair by accident. Only one subject was able to steer toward the chair (Figure 5—figure supplement 1). None of the subjects were able to complete 20 trials within the 60 s time limit. On the third task, the subject was asked to find a key that had fallen on the floor of the arena. To complete the task, the subject’s head had to point toward the key at <1 m distance. Under those conditions, one can readily reach out and grasp the object. [SEP] Justify:

Output: The text does not directly address the claim regarding memory recall with the right stimulus. Instead, it discusses an experiment using sound-based navigation aids (CARA and vOICe) and how subjects performed tasks under different conditions. While it does involve tasks related to navigation and object location, it does not support or dispute the claim about perfect memory recall.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: The early stage of the mycorrhizal symbiosis represents a challenging, but also a very attractive, stage for proteomics. The sampling time and sampling method are crucial for the experiment’s outcome, and synchronization of the root colonization events would enrich root samples in the proteins of interest. Lopez-Meyer and Harrison (2006) first proposed a system to synchronize AM fungal spore germination and root penetration events [38]. Despite this technical improvement, the amount of proteins involved in the plant response to the AM fungus and in the PPA formation, as compared to the amount of proteins in the whole root, is expected to be very low and at the limit of detectability. Therefore, new strategies for sample preparation and experimental designs are required to reveal the key components of this fundamental phase of the mycorrhizal symbiosis. 4. 2. Proteomics on late stageLate stage of the AM symbiosis commonly indicates the phase in which the fungus has already build up the arbuscules. In nature, the symbiosis is highly dynamic and very complex because, while arbuscules are forming, new penetration events occur. Bestel-Corre et al. [39] reported the first mass spectrometry (MS)-based identification of mycorrhiza-related proteins. These authors studied the response of M. truncatula inoculated either with the AM fungus Glomus mosseae (current name Funneliformis mosseae) or with the nitrogen-fixing bacterium Sinorhizobium meliloti. Proteins were separated by 2DE-PAGE and image analyses, with precise quantification of spots volume performed to identify differentially expressed protein spots. Those spots were excised from the gels and analyzed by mass spectrometry. Notably, only plant or bacterial proteins were identified, may be due to difficulties in extracting fungal proteins. The authors identified several proteins related to defence responses, root physiology and respiratory pathway. However, none seemed to be a key protein in the mycorrhizal symbiosis. The proteomic analysis of the late stage of the AM symbiosis using the whole root system as starting material never allowed very good results. To overcome this problem, many studies on the late stage of the symbiosis focused their attention on a specific sub-cellular compartment. [SEP] Justify:

Output: The text corroborates the claim by discussing the dynamics of mycorrhizal symbiosis. It mentions the arbuscules formed by the fungus during the symbiotic relationship with plant roots and highlights the complexity of this interaction. The reference to the identification of proteins involved in the plant's response to the AM fungus (arbuscular mycorrhizal fungus) reinforces the existence of this symbiotic relationship.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: However, they should also feel no more confident in their responses for the images that did feature a striped patch than for the ‘no patch’ ones. Peters and Lau found no such evidence of unconscious perception. Nevertheless, the volunteers were consistently better at correctly stating the direction the stripes were tilted in than their confidence ratings would suggest. Does this indicate some degree of perception without awareness? Peters and Lau argue that it does not, because a computer model designed to perform the task showed a similar level of performance to the volunteers. These findings suggest that previous reports of unconscious perception may have been contaminated by the problems that Peters and Lau controlled for, and that perhaps unconscious perception doesn’t occur in people without brain damage. Researchers will now need to do more studies using similar approaches to determine whether observers without brain damage can truly experience unconscious perception, and how such unconscious perception might be represented in the brain. Introduction Above-chance performance without awareness in perceptual discrimination tasks is a strong form of unconscious perception. In these demonstrations (e. g. , blindsight: Weiskrantz, 1986) the subjective threshold for awareness (when a stimulus is consciously ‘seen’) seems well above the objective threshold for forced-choice discrimination (when a stimulus can be correctly identified): subjects can discriminate a target above chance performance, yet report no awareness of the target. Many researchers believe normal, healthy subjects can also directly discriminate near-threshold, low-intensity targets without subjective awareness (e. g. , Boyer et al. , 2005; Charles et al. , 2013; Merikle et al. , 2001; but see Snodgrass et al. , 2004 for an opposing view). We conducted an informal survey to confirm this popular belief, which also revealed that many believe convincing evidence for this phenomenon is lacking. We asked survey participants three key questions: (1) "Do you believe in subliminal perception? " (2) "Do you believe that the subjective threshold for awareness is above the objective discrimination threshold? " and (3) "If ‘yes’, do you believe this has been convincingly demonstrated in the literature? " Most respondents reported believing that subliminal processing exists (94%), but also that they did not believe it had been convincingly demonstrated in the literature (64%). These belief patterns were shown even among those who reported having published on subliminal or unconscious perception (94% and 61%, respectively). See 1. [SEP] Justify:

Output: The text contrasts the claim by discussing the findings of Peters and Lau, who argue that there is no evidence for unconscious perception, which challenges the premise that priming can influence behavior without conscious awareness. The text suggests that previous reports of unconscious perception may be flawed, and asserts that 'unconscious perception doesn’t occur in people without brain damage.' This directly undermines the idea presented in the claim.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Their subjects preferred speech sounds over simple tones, and performed better under those conditions, which supports the use of voices in CARA’s virtual guide. To enable recognition of scenes and objects, various schemes have been considered that convert the scene into spatialized sound, but they largely encode low-level geometric features. At the simplest level, the vOICe system takes a photograph, interprets it as a spectrogram, and presents the resulting sound with a left-to-right scan (Haigh et al. , 2013; Meijer, 1992). Another system parses the scene into inclined planes and encodes each plane with a sequence of musical sounds; a chair might consist of two planes (Ribeiro et al. , 2012). These designs still do not do enough to ‘off-load the blind traveler's brain of … arduous tasks’ (Collins, 1985). Instead of posing acoustic puzzles of this kind, CARA uses plain language to tell the user what is out there and where it is. As a rule, assistive devices have been designed to perform one well-circumscribed function, such as obstacle avoidance, or route finding, or object recognition, or reading of signage (Loomis et al. , 2012; Roentgen et al. , 2008). Our main contribution here is to show that augmented reality with object voices offers a natural and effortless human interface for all these functionalities, implemented in a single device. So far, we have focused on indoor applications. Blind people report that outdoor navigation is supported by many services (access vans, GPS, mobile phones with navigation apps) but these all fall away when one enters a building (Karimi, 2015). In its present form CARA can already function in this underserved domain, for example as a guide in a large public building, hotel, or mall. No physical modifications of the space are required. The virtual guide can be programmed to offer navigation options according to the known building geometry. Thanks to the intuitive interface, naive visitors could pick up a device at the building entrance and begin using it in minutes. In this context, recall that our subjects were chosen without prescreening, including cases of early and late blindness and various hearing deficits (Figure 1D): They represent a small but realistic sample of the expected blind user population. The functionality of this system can be enhanced far beyond replacing vision, by including information that is not visible. [SEP] Justify:

Output: The text discusses various technologies designed to assist blind users in navigation and object recognition, particularly through augmented reality and sound. However, it does not address the concept of memory recall or its relationship with stimuli directly. Therefore, it is irrelevant to the claim being analyzed.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: With this approach, the same group published two other papers few years later, using sub-cellular fractionation methods, reporting more remarkable results described in the next paragraphs. Mycorrhizal systems different from ECM and AM have been seldom investigated with proteomic approaches. However, recent results have been published for orchid mycorrhiza by Valadares et al. (2014). For orchids, the association with symbiotic fungi is required for seed germination and seedling development, when the plant relies on the fungus also for carbon supply (a strategy termed mycoheterotrophy). Recently, 2D-LC-MS/MS (two-dimensional liquid chromatography MS/MS) coupled to isobaric tagging for relative and absolute quantification has been used to identify proteins with differential accumulation in the orchid species Oncidium sphacelatum at different stages of plant development after seed inoculation with a Ceratobasidium sp. fungal isolate. Eighty-eight proteins, including proteins putatively involved in energy metabolism, cell rescue and defence, molecular signalling and secondary metabolism, have been identified and quantified. These results suggest profound metabolic changes during the development of mycorrhizal orchids, likely related to a switch from the fully mycoheterotrophic to the photosynthetic stages [40]. 4. 3. Proteomics on sub-cellular compartmentAlthough 30% of naturally occurring proteins are predicted to be embedded in biological membranes [41], comprehensive membrane proteomics is technically difficult due to the hydrophobicity, heterogeneity and lower abundance of membrane proteins. In mycorrhizal symbioses, membrane proteins are very important because they likely include the receptors that control the fungal–plant dialogue as well as the transporters that mediate nutrient exchange. For these reasons, many authors have focused on membrane proteins using different enrichment protocols. The first study on sub-cellular fractionation of membrane proteins was conducted by Benabdellah et al. (1998). They isolated the microsomal protein fraction from colonized tomato roots, where they found several differentially expressed proteins [42]. Few years later, the same group identified for the first time a protein related to mycorrhizal symbiosis by Edman N-terminal sequencing, after plasma membrane enrichment and 2DE-PAGE protein separation [43]. [SEP] Justify:

Output: The text corroborates the claim by stating that mycorrhizal symbioses involve important mechanisms such as nutrient exchange between fungi and plants, and highlights the necessity of symbiotic fungi for orchids during seed germination and development. It discusses the metabolic changes related to these symbiotic relationships, which aligns directly with the concept of mycorrhizal fungi forming partnerships with plant roots.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: Figure 2 Download asset Open asset Schematic explanation of predictions of the experiments. (A) A ‘Performance without Awareness’ pattern of behavior, in which subjects are able to discriminate the target above chance while betting on the target-present interval at chance. (B) A ‘Performance > Awareness’ pattern of behavior, in which subjects are less able to bet on their discrimination decisions than they are able to correctly discriminate the target. In both (A) and (B), the diagonal dashed line indicates where rate of betting on the target-present interval equals objective discrimination performance. However, in psychophysics, thresholds can also be defined as midway between ceiling and floor performance (Macmillan and Creelman, 2004), such that threshold discrimination performance is defined as 75% accuracy rather than >50% (chance level). This concept can also be applied to subjective betting data in the sense that betting on the target-present interval could be considered ‘correct’ or ‘advantageous’ betting. In this sense (threshold = 75% correct performance), the subjective threshold for confidence might be above the objective threshold for discrimination. In other words, observers may bet on the target-present interval less often than they get the discrimination correct, but still above chance. This would occur because the orientation discrimination choice requires evaluation of only one interval (the one with the target in it) and therefore is subject to only one source of uncertainty, but the ‘betting’ choice requires evaluation of both intervals, and therefore has two potential sources of uncertainty. This pattern of behavior (Figure 2B) may occur even if subjects do not display Performance without Awareness, and would be characterized by a pattern of responses that fall below the identity line (diagonal dashed line). We call this possibility ‘Performance > Awareness’. We discuss the results of both experiments together for ease of interpretation, and because the results are very similar (Figure 3A–F). To anticipate, we found no evidence of Performance without Awareness. Although we found strong evidence of Performance > Awareness across the experiments (Figure 3A,D), subsequent computational modeling (section) suggests that this is somewhat trivial: even an ideal observer is expected to show Performance > Awareness (Figure 3G; see section for further explanation). [SEP] Justify:

Output: The text contrasts the claim by stating that the experiments found 'no evidence of Performance without Awareness' while showing 'strong evidence of Performance > Awareness'. This indicates that while subjects may perform better than chance in their discrimination tasks, it does not support the idea that priming can impact behavior without conscious awareness.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: As a full service computer with online access, the HoloLens can be programmed to annotate the scene and offer ready access to other forms of knowledge. Down the line one can envision an intelligent cognitive assistant that is attractive to both blind and sighted users, with somewhat different feature sets. Indeed this may help integrate the blind further into the community. By this point, we expect that the reader already has proposals in mind for enhancing the cognitive assistant to communicate things that we cannot see. A hardware/software platform is now available to rapidly implement those ideas and test them with human subjects. Finally, we demonstrated a separate platform for standardized tests to evaluate and benchmark CARA and other assistive technologies on the same tasks. The use of virtual reality on an affordable consumer device can recreate the identical test environment for blind subjects in laboratories around the world, allowing quantitative performance comparisons even with implanted prosthetic devices. We hope that other developers of assistive technology will engage and collaborate to produce an agreed-upon standard test suite, starting with our published example. This in turn should stimulate competition to exploit the ongoing revolution in wearable computers and machine vision toward creative solutions in the domain of assistive technology. Materials and methods General implementation of CARA Request a detailed protocol The hardware platform for the cognitive assistant is the Microsoft HoloEdition, without any modifications. This is a self-contained wearable augmented reality (AR) device that can map and store the 3D mesh of an indoor space, localize itself in real time, and provide spatialized audio and visual display (Hoffman, 2016). We built custom software in Unity 2017. 1. 0f3 (64-bit) with HoloToolkit-Unity-v1. 5. 5. 0. The scripts are written in C# with MonoDevelop provided by Unity. The experiments are programmed on a desktop computer running Windows 10 Education and then deployed to Microsoft HoloLens. The software is versatile enough to be easily deployed to other hardware platforms, such as AR enabled smart phones. User interface Request a detailed protocol Before an experiment, the relevant building areas are scanned by the experimenter wearing the HoloLens, so the system has a 3D model of the space ahead of time. For each object in the scene, the system creates a voice that appears to emanate form the object’s location, with a pitch that increases inversely with object distance. [SEP] Justify:

Output: The text discusses the capabilities of the HoloLens and its applications in assistive technology, focusing on enhancing the cognitive experience for users, including the blind. However, it does not address the claim regarding memory recall or the effects of stimuli on memory. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: These parameters are measured for individual LC-MS/MS or LC/LC-MS/MS runs and changes in protein abundance are calculated via a direct comparison between different analyses [52]. The spectral counting strategy used by Abdallah et al. (2014) suggests that accommodation of AM fungi within root cortical cells implies both a dynamic reorganization of the root membrane proteome and the de novo synthesis of AM-related proteins [23]. This study, beside the identification of proteins corresponding to key genes already identified in mycorrhizal symbiosis, also reported new proteins, many of which support the importance of membrane trafficking during mycorrhiza colonization. In summary, sub-cellular and peptide fractionations led to the identification of many key proteins involved in AM symbiosis. Despite the recent contributions of proteomics to the study of the plant–fungus mycorrhizal interactions were substantial, the role of many of them as actors in the symbiosis is still to be fully understood. 4. 4. Proteomics to identify fungal proteinsMost proteomic studies on the AM interaction have focused on plant proteins. Identification of fungal proteins is more challenging due to the impossibility to grow AM fungi in axenic cultures, to the lower amount of fungal biomass, as compared to plant material, and to the more scanty sequence information. However, pioneering studies have been carried out in France by Dumas-Gaudot and Recorbet [53,54]. Dumas-Gaudot et al. (2004) used the root organ culture method [55] to enrich for proteins expressed in the extra-radical mycelium of the AM species G. intraradices. They successfully produced, for the first time, a 2DE reference map for the extra-radical proteome of an AM fungus. After the selection of the most intense protein spots, they tried to identify them by mass spectrometry. Unfortunately, only very few proteins from filamentous fungi were known and present in public databases, and the only available genome sequence, at that time, was from Neurospora crassa, phylogenetically very far from Glomeromycota. In spite of that, identification was possible for 8 proteins out of the 14 analyzed, and homologies were found for 4 of them. Few years later, the same group attempted again the identification of fungal proteins expressed in the AM association [54]. [SEP] Justify:

Output: The text corroborates the claim by discussing the symbiotic relationship between arbuscular mycorrhizal (AM) fungi and plant roots. It refers to the accommodation of AM fungi within root cortical cells, indicating a direct interaction indicative of symbiosis. Moreover, the identification of proteins related to mycorrhizal symbiosis suggests a complex biological relationship where both organisms benefit, further supporting the claim.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: Figure 3 Download asset Open asset Group-level results of behavioral experiments (rows 1 and 2), presented in comparison to the predictions of the Bayesian ideal observer model (row 3; see Materials and methods - Computational Model). In both experiments, human observers displayed no evidence of Performance without Awareness, but appeared to demonstrate Performance > Awareness (panels A and D). However, the ideal observer model also demonstrated such behavior (panel G), indicating that it is not suboptimal at all but arises from the 2IFC nature of the confidence task (see results section and Figure 2 caption for explanation). Horizontal gray lines in panels A, D, and G indicate chance-level betting (50%) on the target-present (TP) interval. Panels B, E, and H show rising Type 2 hit rate (‘HR’; when subjects bet on a correct orientation discrimination choice) but relatively flat Type 2 false alarm rate (‘FAR’; when subjects bet on an incorrect orientation discrimination choice), and panels C, F, and I show higher orientation discrimination accuracy when the target-present (TP) interval is bet on; these patterns suggest that human subjects and the Bayesian ideal observer were rating confidence via assessing their probability of correctly discriminating orientation, rather than target presence versus absence only. The model demonstrates good explanatory power for the data across all participants (mean proportion of variance accounted for by the model, R2 = 0. 565). Error bars for behavioral data indicate the standard error of the mean across subjects with data in each bin. To look for evidence of Performance without Awareness, we first plotted percent of trials in which observers bet on the target-present interval against orientation discrimination accuracy for both experiments (Figure 3A,D). In contrast to what might have been suggested based on previous results (e. g. , Boyer et al. , 2005; Charles et al. , 2013; Merikle et al. , 2001; but see Snodgrass et al. , 2004), visual inspection alone clearly reveals no evidence for Performance without Awareness in either experiment: it looks as though observers could bet on the target-present interval above chance as soon as they were able to discriminate the target above chance, and there is no hint of the Performance without Awareness pattern. [SEP] Justify:

Output: The text contrasts the claim by stating that there was no evidence of Performance without Awareness in the behavioral experiments conducted. It indicates that observers could bet on the target-present interval above chance only when they were able to discriminate the target above chance, suggesting that conscious awareness is necessary for the performance observed.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: In each trial, the subject begins in a starting zone within 1. 2 m of the first waypoint, and presses the Clicker to start. A virtual guide then follows the trajectory and guides the subject from the start to the destination. The guide calls out ‘follow me’ with spatialized sound every 2 s, and it only proceeds along the path when the subject is less than 1 m away. Just before waypoints 2–8, a voice instruction is played to inform the subject about the direction of turn as well as approaching stairs. The trial completes when the subject arrives within 1. 2 meters of the target. Voice feedback (‘You have arrived’) is played to inform the subject about arrival. In this task all blind subjects used a cane. Free walking: To measure the free walking speed, we asked subjects to walk for 20 m in a straight line in an unobstructed hallway using their preferred walking aid. Subjects 1 and 2 used a guide dog, the others a cane. Data analysis and visualization Request a detailed protocol MatLab 2017b (Mathworks) and Excel (Microsoft) were used for data analysis and visualization. Unity 5. 6. 1f1 was used to generate 3D cartoons of experiments and to visualize 3D trajectories. Photoshop CC 2017 was used for overlaying trajectories on floor plans. Aiming: In tasks 1 and 2, aiming errors are defined as the difference between the target azimuth angle and the subject’s front-facing azimuth angle. In task 2, to correct for the delay of voice command registration, errors are measured at 1 s before the end of each trial. Trajectory smoothing: The HoloLens tracks its wearer’s head movement, which includes lateral movements perpendicular to the direction of walking. To estimate the center of mass trajectory of the subject we applied a moving average with 2 s sliding window to the original trajectory. Length of trajectory and deviation index: In the directed navigation task and the long-range guided navigation task we computed the excess distance traveled by the subject relative to an optimal trajectory or the guide path. The deviation index, DI, is defined as (1) DI= Lexp- LrefLref where Lexp is the length of the trajectory measured by experiment and Lref is the length of the reference trajectory. A value near 0 indicates that the subject followed the reference trajectory well. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses experimental protocols and navigation tasks involving blind subjects, but it does not address memory recall or the effect of stimuli on memory. There are no references or indications about memory recall in the provided details.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: They maintained the same experimental system, but they used the GeLC-MS/MS method and could identify 92 different fungal proteins. GeLC-MS/MS approach combines a mono-dimensional gel (1D-PAGE) and a nano-scale capillary liquid chromatography-MS/MS. Briefly, after the 1D-PAGE separation, the mono-dimensional gel is cut in several pieces; in-gel digestion results in different protein fractions that are separated and analyzed by LC-MS/MS. Using the MetaCyc database, a collection of more than a thousand metabolic pathways [57], these authors grouped those proteins in 11 pathways that span energy, metabolism and cell rescue processes. These data, together with previous identifications of putative homologues of cell-cycle gene in G. mosseae and G. intraradices [56,57], suggest that signalling pathways known in model species may also operate in AM fungi. Although the GeLC-MS/MS strategy opened the possibility to large-scale proteomics of mycorrhizal fungi, no further data have been published with this technique. Secreted fungal proteins play key roles in host plant colonization and symbiosis development in ECM interactions. Vincent et al. (2012) have identified the extracellular proteins secreted in the growth medium by the free-living mycelium of the ECM fungus L. bicolor using 2-DE, IPG-IEF shotgun (IPG strip was cut into fractions and tryptic peptides were eluted from the each fraction) and SDS-PAGE shotgun, with the aim to validate predicted secreted proteins and identify putative novel effectors of the symbiosis. Among the 224 proteins identified, there were carbohydrate-active enzymes (CAZymes), probably involved in cell wall remodelling during hyphal growth, as well as secreted proteases. Additionally, the involvement of some of these proteins in the establishment of the mycorrhizal symbiosis was supported by transcriptomic analyses of ECM roots [58]. Advertisement 5. Mycorrhizal fungi and heavy metalsIn plants, stress tolerance to soil pollution can be increased by their interaction with mycorrhizal fungi [59]. [SEP] Justify:

Output: The text corroborates the claim by explaining the role of secreted fungal proteins in host plant colonization and the development of symbiosis, particularly in the context of ectomycorrhizal (ECM) interactions. It specifically states, 'Secreted fungal proteins play key roles in host plant colonization and symbiosis development in ECM interactions,' indicating a symbiotic relationship between mycorrhizal fungi and plant roots.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: We quantitatively assessed the possibility of Performance without Awareness using a Bayesian observer model (see Modeling Results, below), but found no evidence that a Performance without Awareness pattern could capture human behavior. Individual subjects’ performance closely resembles group data and averages (10. 7554/eLife. 09651. 006 ExptSubjectp(choose TP interval) at p(correct) = 0. 7511AVT0. 6762AM0. 7143JDK0. 7164SH0. 6825MM0. 6846AC0. 6857MR0. 6748MK0. 6589RA0. 61921AVT0. 6662AM0. 7133JDK0. 746Mean (σ)0. 686 (0. 033)t(11)6. 718p0. 00003 2IFC detection? One possible concern is that subjects were not rating confidence but instead engaging in 2IFC detection of the target-present interval. To confirm that subjects were indeed rating confidence, we plotted Type 2 hit rate and Type 2 false alarm rate against orientation discrimination accuracy (Figure 3B,E). A Type 2 hit is defined as placing a bet on a correct orientation discrimination decision, whereas a Type 2 false alarm is defined as placing a bet on an incorrect orientation discrimination decision. These are in contrast to Type 1 hits and false alarms, which can be defined as saying ‘left’ when a left-tilted Gabor was presented and saying ‘left’ when a right-tilted Gabor was presented, respectively, according to standard signal detection theoretic definitions (Green and Swets, 1966; Macmillan and Creelman, 2004). Subjects displayed increasing Type 2 hit rate as a function of orientation discrimination accuracy, whereas Type 2 false alarm rate remained relatively flat at around 50% (chance level) across increasing orientation discrimination accuracy. In other words, subjects did not bet on orientation discrimination choices they expected to get wrong, even at high performance (i. e. high contrast) levels. Thus, they were probably truly rating confidence and not simply engaging in 2IFC detection. In keeping with this observation, we also plotted orientation discrimination accuracy conditional upon subjects’ selection of the target-present interval, i. e. [SEP] Justify:

Output: The text contrasts the claim by stating that evidence for performance occurring without awareness was not found. Specifically, it mentions a quantitative assessment using a Bayesian observer model, indicating that individual subjects' performance closely resembles group data, which implies that the behaviors were likely not influenced subconsciously without their awareness.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: In the direct navigation task, we divided each trial into an orientation phase where the subject turns the body to face the target, and a navigation phase where the subject approaches the target. We calculated head orientation and 2D distance to target in each frame, and marked the onset of the navigation phase when the subject’s distance to target changed by 0. 3 m. Note that with this criterion the navigation phase includes the occasional trajectory where the subject starts to walk in the wrong direction. In this task, Lref is defined as the length of the straight line from the subject’s position at the onset of the navigation phase to the nearest point of the target trigger zone. In the long-range guided navigation task, Lref is the length of the guide trajectory. Due to variability in placing waypoints and tracking, the length of guide trajectories varied slightly across subjects (Lref=36. 4 ± 0. 7 m, mean ±s. d. ). Negative DI values are possible in this task if the subject cuts corners of the guide trajectory. Speed: Speed is calculated frame-by-frame using the displacements in the filtered trajectories. For the long-range guided navigation task, which includes vertical movements through space, the speed of translation is computed in three dimensions, whereas for the other tasks that occur on a horizontal plane we did not include the vertical dimension. For all tasks, we estimated walking speed by the 90th percentile of the speed distribution, which robustly rejects the phases where the subject chooses an orientation. The normalized speed is obtained by dividing this value by the free walking speed. Supplementary observations Request a detailed protocol Here, we report incidental observations during experiments with CARA that were not planned in the frozen protocol, and comments gathered from blind subjects in the course of the experiments. Subject 1: During navigation with the virtual guide says “seems to me the ‘follow me’ sound means keep going straight”. Thinks addition of GPS services could make the system useful outdoors as well. Suggests experimenting with bone conduction headphones. Offers us 1 hr on his radio show. Subject 2: During direct navigation says “pitch change [with distance] was informative”. During navigation with the virtual guide says “’Follow me’ was too much information”. Prefers to follow the explicit turn instructions. She could then transmit those instructions to her guide dog. [SEP] Justify:

Output: The text primarily discusses navigation tasks and the experimental setup regarding subject orientation and movements, without providing any information related to the claim about memory recall and its relationship to stimulus. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: Six out of ten of the most polluted soils in the world are contaminated by heavy metals [60], and mycorrhizal symbioses have been found to reduce metal toxicity to the host in soils with potentially toxic amounts of soluble and insoluble metals. Phytoremediation, the plant-mediated reclamation of polluted soils, is receiving increasing attention as a natural method to restore the biological features of the soil. Mycorrhizal fungi can have an important part in this process. Many studies have been carried out on the benefits of mycorrhizal plant–fungus interaction in heavy-metals-polluted soils, but only few of them have used a proteomic approach to identify the key proteins potentially involved in mycorrhiza-mediated stress tolerance. Researches on this topic have analyzed different plant organs, like leaves or root, but also focused on the symbiotic fungus. Bona et al. (2010) studied the leaf proteome of the arsenic hyperaccumulator fern Pteris vittata inoculated with two fungi (Glomus mosseae and Gigaspora margarita), with and without arsenic treatment [59]. The symbiosis with both fungi decreased arsenic concentration compared with non-mycorrhizal plants, indicating the protective effect of mycorrhizal fungi. Interestingly, the plant protein expression profile was different when the plant was inoculated with G. mosseae or G. margarita. Although they studied a different biological system, Cangahuala-Inocente and colleagues (2011) identified instead a core of 25 proteins, supporting the existence of conserved plant responses to Glomus irregulare and Glomus mosseae, at least in a woody perennial species such as grapevine [61]. A study on root proteomics has been conducted by Aloui et al. [62]. They reported, using a 2DE approach followed by MS/MS, the protective effect conferred by G. intraradices to the model legume M. truncatula in the presence of Cd. They identified 36 mycorrhiza-related proteins, but only 6 displayed changes in abundance upon Cd exposure. [SEP] Justify:

Output: The text corroborates the claim by detailing how mycorrhizal fungi, such as Glomus mosseae and Gigaspora margarita, form symbiotic relationships with plant roots, leading to benefits such as reduced arsenic concentration in plants. It emphasizes the protective effect of mycorrhizal symbiosis in stressed conditions, specifically highlighting how these fungi interact with host plants to mitigate heavy metal toxicity.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: In our procedures, each trial consists of two time intervals, within only one of which the target is presented. In target-absent intervals, the target presentation was replaced with blank frames, similar to the blank frames between masks, to maximize phenomenological similarity between target-present (TP) and target-absent intervals (TA) (Figure 1B). Unlike previous usage of the 2x2FC, however, we required observers to indicate target orientation on both target-present and target-absent intervals within a trial in addition to the final judgment type, despite the fact that there was a target in only one of the intervals. In target-present intervals, targets were presented at 45° tilted right or left from vertical at one of the possible contrasts. Following presentation of both intervals, observers pressed a key indicating which discrimination decision they would like to bet on (a measure of confidence; Type 2 judgment), and then indicated their discrimination choices for both intervals in order (leftward or rightward tilt; Type 1 judgment) (Figure 1C). In target-absent intervals, participants’ answers were coded as ‘correct’ with 50% probability. No feedback was provided on a trial-by-trial basis. To motivate subjects, we informed them that a target was present in both intervals, but that one might be harder to discriminate than the other. Subjects were informed that they would be awarded a point for every correct discrimination (Type 1 judgment), and an additional point every time they bet on an interval they discriminated correctly (Type 2 judgment), and total points were displayed at the end of the experiment; they were also told that if they earned more points than the previous participant, they would be paid an additional $10 bonus at the end of all sessions. In each behavioral session, trials were presented in a randomized full factorial design, counterbalancing interval order, in ten blocks of 52 trials per block. Every subject undertook five 60-minute sessions, for a total of 2600 trials spread across up to thirteen contrast levels, two orientations, and two interval presentation orders. Levels of contrast presented to each participant were titrated across sessions to ensure performance spanning approximately evenly from chance (50% correct) to 100% correct, resulting in no fewer than 200 trials per contrast level (10 trials per condition x 2 orientations x 2 interval orders x 5 sessions). Subjects were paid $10 per session. [SEP] Justify:

Output: The text contrasts the claim as it details an experimental setup where participants are explicitly informed about the target's presence and the aim of discriminating between targets, which suggests a level of conscious awareness in their decision-making process. Participants were told they would be rewarded based on how correctly they recognized the target, indicating that their awareness of the task and potential outcomes plays a significant role in their behavior.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Subject 3: In addition to object voices, he likes instructions of the type ‘keep going forward for xx meters’. During a previous visit using a similar system he commented on possible adoption by the blind community: “I could see people spending in 4 figures for [something] light and reliable, and use it all the time”. Also supports the concept of borrowing a device when visiting a public building or mall. Devices in the form of glasses would be better, preferably light and thin. “Use the computing power of my phone, then I don’t have to carry anything else. ” Likes the external speakers because they don’t interfere with outside sound. Finds it easy to localize the virtual sound sources. Subject 4: After navigation with the virtual guide says “That was fun. When can I get one? ” Primarily used the ‘follow me’ voice, and the cane to correct for small errors. Reports that the turn instructions could be timed earlier (this is evident also in Video 1). On a previous visit using a similar system: “I’m very excited about all of this, and I would definitely like to be kept in the loop”. Also suggests the system could be used in gaming for the blind. Subject 5: During navigation with the virtual guide realized she made a wrong turn (see Fig. 4C) but the voice made her aware and allowed her to correct. Reports that the timing of turn instructions is a little off. Subject 6: After all tasks says “That was pretty cool” and “The technology is there. ” Subject 7: On the second trial with the virtual guide reports that she paid more attention to the ‘follow me’ sound (she strayed temporarily on the first trial, Fig. 4B). Wonders whether the object voices will be strong enough in a loud environment. Benchmarking platform using virtual reality The benchmarking platform runs on the headset and a Windows 10 desktop computer. A TPCast wireless adapter (CE-01H, replaces the standard headset cable so the subject can move freely within the 4 m x 4 m square arena. controller is connected wirelessly to the host computer for the subject to start trials, confirm aiming, and control the modes of CARA. Audio is delivered by a pair of wireless headphones (-1000XM2). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various subjects' experiences with a virtual guide system and navigation, without mentioning anything about memory recall or the impact of stimuli on memory recall. It primarily focuses on the functionality of the virtual guide and several user's feedback.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: In the past few years, a specialized fungal genomics portal, called MycoCosm ( has been created by the US Department of Energy (DOE) Institute (JGI), offering an access point to the data from all the sequencing genome project managed by the [68,69]. Starting from the three first genome projects on Laccaria bicolor, Tuber melanosporum and Rhizophagus intraradices [70,71,72], several more genomes from symbiotic fungi, including ECM, AM, orchid and ericoid fungi, have been recently sequenced, with the aim to determine the diversity of the molecular processes involved in the interaction [28]. Despite the more powerful techniques and wider reference datasets for protein identification, current limitations exist in the application of proteomics to the study of plant–microbe interactions. In particular, new extraction methods, microsomal studies, sub-cellular enrichment, gel-free separation methods, pre-fractioning separations and new mass spectrometry are still far from being fully explored [73]. In order to identify proteins from a very small subset of target cells, Gaude et al. (2012) combined laser capture microdissection (LCM) and LC-MS/MS [74]. Laser microdissection permits the rapid isolation, from sections of a heterogeneous tissue, of a selected cell population in a manner compatible with the extraction of or proteins [29]. Using LCM, arbuscule-containing cortical cells and cortical cells from non-mycorrhizal M. truncatula roots were isolated. Proteomic analyses on these cells revealed a number of proteins involved in lipid metabolism, most likely related to the synthesis of the PAM. This targeted analysis on a specific subset of colonized cells, those harbouring the arbuscules, curiously did not identify known PAM marker proteins, thus suggesting that either sample preparation or instrument capability were not sensitive enough. Although this first use of LCM in the proteomic investigation of the AM mycorrhizal symbiosis did not identify known marker proteins, it highlighted the PAM as an important carbon sink. The LCM technique coupled with MS/MS techniques could be a powerful combination to investigate the protein profiles of specific cells at specific time-points. Moreover, LCM can help to overcome the problem of asynchronous fungal development and arbuscule maturation in mycorrhizal roots. [SEP] Justify:

Output: The text corroborates the claim by discussing the interactions between mycorrhizal fungi and plant roots, particularly mentioning the presence of arbuscules, which are structures formed by arbuscular mycorrhizal fungi within the plant's root cells. This indicates a symbiotic relationship, as the text analyzes the proteomic aspects of mycorrhizal symbiosis and highlights the importance of these fungal interactions in plant physiology.


Input: Task: contrast the claim using the given text. Claim: Priming can affect behavior without conscious awareness. [SEP] Text: These arguments show that simple conscious experience could emerge independently of attention. One could argue that in all these cases even when the conscious experience is very simple (as in the case of phosphenes) the stimulus is first represented in the brain, then amplified by top-down attention and only then emerges in awareness. Thus, one could claim that these arguments are not sufficient for showing that simple conscious experience can emerge without attention. However, even if one would agree that the evidence does not convincingly demonstrate the independence of attention and consciousness, it would not imply that attention is necessary for consciousness. Furthermore, there are some additional arguments to support the independence of attention and consciousness. 5. If attention is necessary for conscious perception, attending to certain phenomenal content should not be unfavorable for experiencing this content. However, several recent studies have shown that attention has a detrimental effect on the duration of afterimages or sensory aftereffects (Lou, 2001; Bachmann and Murd, 2010; van Boxtel et al. , 2010). If attention readily eliminates phenomenal experience then the awareness-related mechanisms whose activity is suppressed together with phenomenal experience must be independent from the attentional mechanisms. 6. Attending to the contents of the currently dominating image in binocular rivalry does not preclude that the competing alternative might spontaneously emerge in phenomenal awareness. If attention is necessary for consciousness and it is deployed to the dominating image, how could the suppressed image access awareness? 7. Many authors agree that consciousness and attention have different neurobiological mechanisms (Lamme, 2004; Koch and Tsuchiya, 2007; Bachmann, 2011). This of course does not deny interaction between these mechanisms in typical cases where attention has a supportive role in bringing perceptual contents to consciousness, but the independence of the neurobiological mechanisms supports the view that attention and consciousness are autonomous processes. Finally, it is not true that in order to support the independence of consciousness and attention one has to show that attention is not needed for the stimulus to enter consciousness across a set of experimental paradigms (Cohen et al. , 2012a). In fact, one could turn the argument around: if it is consistently shown by many research groups that attention is not needed for conscious perception even in one single paradigm, then this already implies that attention is not necessary for consciousness. It was also argued that the absence of the attentional effect on consciousness is a null finding which should be treated with caution (Cohen et al. , 2012a). [SEP] Justify:

Output: The text contrasts the claim by discussing the independence of attention and consciousness, suggesting that attention is not necessary for consciousness and may even hinder conscious experience. It argues that if attention is required for conscious perception, then aspects of perception that are not attended to should not enter awareness. The implications of the studies mentioned indicate a complex relationship between attention and consciousness, revealing that priming does not necessarily require conscious awareness, which counters the assertion in the claim.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: All code and data to replicate this environment and the reported tests is publically available at (Liu and Meister, 2018; copy archived at All three benchmarking tasks are set in a 10 m x 10 m virtual environment that simulates a living room with 16 objects labeled with sound tags. The rendered scenes are close to photo-realistic, and computer vision algorithms trained on real scenes will correctly identify objects in the virtual scene as well (Figure 3—figure supplement 2F). The first benchmark task (Figure 5B) resembles Task 1 (see section on above) except that the aiming target is chosen at random from the 16 objects in the studio. CARA users have access to Spotlight and Target Mode. The second benchmark task (Figure 5C) resembles Task 3 with a 60 s time limit on each trial. CARA users only have available for this task. To facilitate detection with vOICe the chair was made white, and left unoccluded by any other objects. The third benchmark task (Figure 5D) replaces the chair in the second benchmark task with a key on the floor. and can be used in this task. Two conditions have to be met to finish a trial: (1) the head of the subject is within 1 m of the key and (2) the subject faces within 30 degrees of the key. To accomplish this the subject must bend down or kneel facing the key. At this point, a simple reach with the hand would allow grasping a real object. A trial fails if not finished within 60 s. To avoid excess frustration among the subjects a task is terminated after five failed trials. Voice control on CARA Request a detailed protocol In addition to the Clicker, subjects can also use natural language (e. g. English) as input to the system. Two subsystems of voice input are implemented: 1) keyword recognition (PhraseRecognitionSystem) monitors in the background what the user says, detects phrases that match the registered keywords, and activates corresponding functions on detection of keyword matches. 2) dictation (DictationRecognizer) records what the user says and converts it into text. The first component enables subjects to confirm their aiming in the object localization task and mental imagery task with the voice command “target confirmed”. It also enables the experimenter to control the experiment at runtime. [SEP] Justify:

Output: The text does not address the integrity of memory recall in relation to stimulus; instead, it focuses on benchmarking tasks in a virtual environment and the technical aspects of a system involving voice recognition and user interaction. As such, it does not provide relevant information regarding the claim.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: , 1999 2007 --- Boletus edulis 2DE--Q-, 2007 2012 --- Laccaria bicolor IPG-IEF 1-DE and 2-DE -, 2012 AM 2000 Lycopersicon esculentum Glomus mosseae 2DE-PAGE N-terminal sequencing Benabdellah et al. , 2000 2001 Medicago truncatula Glomus mosseae 2DE--TOF Bestel-Corre et al. , 2001 2004 --- Glomus intraradices 2DE-PAGE Q-Tof2 Dumas-Gaudot et al. , 2004 2005 Medicago truncatula Glomus intraradices 2DE--TOF Valot et al. , 2005 2006 Medicago truncatula Glomus intraradices 2DE--TOF Amiour et al. , 2006 2006 Medicago truncatula Glomus intraradices 1-DE and 2-DE -PAGE 2D-+ Valot et al. , 2006 2009 --- Glomus intraradices 1-DE--Q-, 2009 2009 Medicago truncatula Glomus intraradices 2DE-+ Aloui et al. , 2009 2010 Pteris vittata Glomus mosseae Gigaspora margarita 2DE-hybrid quadrupole-TOF Bona et al. , 2010 2011 Vitis vinifere Glomus mosseae Glomus intraradices 2DE--TOF Cangahuala-Inocente et al. , 2011 2012 Populus alba Glomus intraradices 2DE--Q-, 2012 2014 Medicago truncatula Rhizophagus irregularis 1-DE-ion trap Abdallah et al. , 2014 Others 2015 --- Oidiodendron maius 2DE-PAGE 2D--TOFMS Chiapello et al. , 2015 2014 Oncidium sphacelatum Ceratobasidium sp. Isolate 2D-LC ESI-Q-, 2014 Table 1. List of papers in which proteomics has been applied to study mycorrhizal symbiosis. For simplicity, AM fungi have been indicated with the names used in the original 2013. [SEP] Justify:

Output: The text discusses various studies and papers that focus on mycorrhizal fungi and their application in studying symbiosis with various plant species. This directly supports the claim about mycorrhizal fungi forming symbiotic relationships with plant roots, as it lists specific fungi like Glomus mosseae and Glomus intraradices in association with plants such as Medicago truncatula and others.


Input: Task: contrast the claim using the given text. Claim: Attention can be selectively focused, altering cognitive processing. [SEP] Text: Self-focused attention did not have an impact on perceptual processing of pictures in general. These results also replicate well-established enhancements in LPP amplitude for unpleasant pictures compared to neutral (Cuthbert et al. , 2000; Hajcak et al. , 2009; White & Grant, 2017), suggesting that different levels of emotional processing of threatening versus neutral pictures appears to be robust against self-focused attention. Taken together, this pattern of findings indicates that the self-focused attention dampens attention preparation, which does not have downstream effects on attention deployment during perception. Self-focused attention did not uniquely impact attention deployment to unpleasant pictures, suggesting that if defensive systems were activated by the self-focused attention manipulation, they may not have had downstream effects. This pattern of effects may be more supportive of an attention resource allocation interpretation of the SPN data as opposed to a defensive activation, as a defensive activation interpretation may suggest downstream effects on the LPP as well. There are limitations to this study. ERPs represent only one aspect of emotional processing. Incorporating a multimodal assessment of the impact of self-focused attention on cued picture viewing would provide a more complete picture of emotionally motivated response systems. Although these effects represent insight into a novel aspect of emotional processing, clinical utility of the findings depends upon examination of such effects in clinical samples or in relation to dimensional symptomology. Considering emotional processing disruptions occur across many forms of psychopathology, it would be important to extend these findings to clinical populations. Moreover, the current study did not include pleasant pictures, which would provide more data regarding appetitive versus defensive responding. Additionally, the SPN (and LPP) represent neural activity within the measurement window in addition to the preceding activity (Luck, 2014). The baselines used within this study are based on extensive previous research; however, it is important to recognize that neural activity before the measurement window may contribute to the effects. ConclusionsEmotional processing during a picture viewing task requires several cognitive processes, two of which were investigated in this study (i. e. , attentional preparation and attention deployment). The purpose of this study was to investigate the impact of self-focused attention manipulations on these attentional processes within the context of cued-picture viewing. Self-focused attention appears to disrupt the preparatory attention for upcoming unpleasant stimuli, potentially through loading cognitive resources or activation of associative defensive responding. [SEP] Justify:

Output: The text contrasts the claim by indicating that self-focused attention does not significantly impact perceptual processing of pictures. It suggests that self-focused attention dampens attention preparation and does not have downstream effects on attention deployment during perception, which implies that the ability to selectively focus attention may be less effective under self-focused conditions. This undermines the claim that attention can be selectively focused to alter cognitive processing.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Keywords and their functions are defined through adding keywords to the keyword manager script provided by HoloToolkit and editing their responses. The KeywordRecognizer component starts at the beginning of each instance of the application and runs in the background throughout the instance of the application except for the time period in which dictation is in use. To allow users to create object labels, the DictationRecognizer provided by HoloToolkit is used to convert natural language spoken by the user to English text. Due to the mutual exclusivity, KeywordRecognizer is shut down before DictationRecognizer is activated, and restarted after the dictation is finished. Automated wayfinding Request a detailed protocol In addition to hand-crafting paths, we implemented automated wayfinding by taking advantage of Unity’s runtime NavMesh ‘baking’ which calculates navigable areas given a 3D model of the space. At runtime, we import and update the 3D mesh of the scanned physical space and use it to bake the 3D mesh. When the user requests guided navigation, a path from the user’s current location to the destination of choice is calculated. If the calculated path is valid, the virtual guide guides the user to the destination using the computer-generated path. Cost of the CARA system Request a detailed protocol The hardware platform used in the research – Microsoft HoloEdition – currently costs $3000. Several comparable AR goggles are in development, and one expects their price to drop in the near future. In addition, smart phones are increasingly designed with AR capabilities, although they do not yet match the HoloLens in the ability to scan the surrounding space and localize within it. Battery and weight Request a detailed protocol The current HoloLens weighs 579 g. Like all electronic devices, this will be further miniaturized in the future. The current battery supports our system functions for 2–5 hr, sufficient for the indoor excursions we envision in public buildings, led by the ‘virtual guide’. A portable battery pack can extend use to longer uninterrupted sessions. Tracking robustness Request a detailed protocol While in most indoor scenarios that we have tested the tracking of HoloLens was reliable and precise, we have encountered occasional loss of tracking or localization errors. This occurs particularly when the environment lacks visual features such as a narrow space with white walls. a detailed protocol Because this cognitive assistant is largely defined by software its functionalities are very flexible. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses technical aspects of HoloToolkit, keyword recognition, and automated wayfinding within an augmented reality system, without addressing memory recall or the effects of stimuli on memory.


Input: Task: corroborate the claim using the given text. Claim: Mycorrhizal fungi form symbiotic relationships with plant roots. [SEP] Text: An evidence-based consensus for the classification of arbuscular mycorrhizal fungi (Glomeromycota). Mycorrhiza 23:515-31). The ability to analyze a single-cell proteome is exciting, but also extremely challenging. The first difficulty is the sensitivity, both correlated with the sample itself and with the mass spectrometry detection capability. Every single cell can contain proteins in a range of few to million copies per cell. However, mass spectrometers are now really powerful, and even with an attomole detection limit, only the most abundant proteins are detectable [78]. The estimated number and concentration of proteins in a single mammalian cell is 33 attomole/cell for the most abundant and 830 yotomole/cell for the less abundant [77]. The second challenge is the inherent limitation associated with the imaging modality itself. Even if further development is needed to obtain the combined resolution and sensitivity required, IMS stands up as a very promising technique to analyze specific cell types or conditions. By employing IMS, Ye et al. (2013) detected a large array of organic acids, amino acids, sugars, lipids, flavonoids in roots and root nodules of M. truncatula during nitrogen fixation [79]. They demonstrated that IMS can obtain unique information on the identity and spatial distribution of plant metabolites, although high-resolution MALDI-MS is required to fully resolve the metabolic differences in nodule chemistry. In conclusion, similarly to other ‘omics’ approaches, proteomics has also made rapid progress in the recent year, thus making this approach a very useful one to complement information on gene expression in mycorrhizal tissues. At this speed of technological developments, methods that allow us to easily assign proteins up-regulated during symbiosis to specific cell types and sub-cellular compartments may not be too far ahead. These proteomic techniques will be powerful tools to unravel the molecular component involved in plant–mycorrhizal fungal interactions. 1. . Mineral nutrition, toxic element accumulation and water relations of arbuscular mycorrhizal plants. Mycorrhizal Symbiosis. 3rd edn. Academic Press, London, 2008. 148. 2. Markmann K, Parniske M. Evolution of root endosymbiosis with bacteria: how novel are nodules? Sci 2009;14:77–86. [SEP] Justify:

Output: The text corroborates the claim by discussing techniques and findings related to plant–mycorrhizal fungal interactions, specifically noting that proteomic methods are useful for understanding the relationships between plants and mycorrhizal fungi. It mentions that these techniques may help to assign proteins that are up-regulated during symbiosis, highlighting the importance of mycorrhizal associations for plant health and nutrition.


Input: Task: contrast the claim using the given text. Claim: Attention can be selectively focused, altering cognitive processing. [SEP] Text: 정서유발 절차가 끝난 후, 참가자들은 일치, 중성 및 불일치 시행들이 포함된 공간 스트룹 과제를 수행하였다. 실험 결과, 불안상태는 스트룹 촉진효과를 증가시키지만, 간섭효과는 감소시키는 것을 확인하였다. 반면, 갈등적응효과는 불안상태에 의해 영향을 받지 않았다. [SEP] Justify:

Output: The text contrasts the claim by discussing the impact of anxiety on attentional processes in a Stroop task, indicating that anxiety increases facilitation effects while decreasing interference effects. This suggests that attention is indeed influenced by emotional states, which alters cognitive processing contrary to the claim of selective focus.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information these areas represent and how it is represented. Here we demonstrate the advantages of a new dimensionality reduction technique, demixed principal component analysis (dPCA), that decomposes population activity into a few components. In addition to systematically capturing the majority of the variance of the data, dPCA also exposes the dependence of the neural representation on task parameters such as stimuli, decisions, or rewards. To illustrate our method we reanalyze population data from four datasets comprising different species, different cortical areas and different experimental tasks. In each case, dPCA provides a concise way of visualizing the data that summarizes the task-dependent features of the population response in a single figure. eLife digest Many neuroscience experiments today involve using electrodes to record from the brain of an animal, such as a mouse or a monkey, while the animal performs a task. The goal of such experiments is to understand how a particular brain region works. However, modern experimental techniques allow the activity of hundreds of neurons to be recorded simultaneously. Analysing such large amounts of data then becomes a challenge in itself. This is particularly true for brain regions such as the prefrontal cortex that are involved in the cognitive processes that allow an animal to acquire knowledge. Individual neurons in the prefrontal cortex encode many different types of information relevant to a given task. Imagine, for example, that an animal has to select one of two objects to obtain a reward. The same group of prefrontal cortex neurons will encode the object presented to the animal, the animal’s decision and its confidence in that decision. This simultaneous representation of different elements of a task is called a ‘mixed’ representation, and is difficult to analyse. Kobak, Brendel et al. have now developed a data analysis tool that can ‘demix’ neural activity. The tool breaks down the activity of a population of neurons into its individual components. Each of these relates to only a single aspect of the task and is thus easier to interpret. Information about stimuli, for example, is distinguished from information about the animal’s confidence levels. Kobak, Brendel et al. used the demixing tool to reanalyse existing datasets recorded from several different animals, tasks and brain regions. [SEP] Justify:

Output: The text does not directly relate to the claim about perfect recall of memory with stimulus. It discusses the complexity of representation in the prefrontal cortex and introduces a method for analyzing neural activity, but does not address the concept of memory recall specifically or whether it can be perfect under the right stimulus.