CRISPR/Cas9-generated mutations in a sugar transporter gene reduce cassava susceptibility to bacterial blight.

Bacteria from the genus Xanthomonas are prolific phytopathogens that elicit disease in over 400 plant species. Xanthomonads carry a repertoire of specialized proteins called transcription activator-like (TAL) effectors that promote disease and pathogen virulence by inducing expression of host susceptibility (S) genes. Xanthomonas phaseoli pv. manihotis (Xpm) causes bacterial blight on the staple food crop cassava (Manihot esculenta Crantz). The Xpm effector TAL20 induces ectopic expression of the S gene Manihot esculenta Sugars Will Eventually be Exported Transporter 10a (MeSWEET10a), which encodes a sugar transporter that contributes to cassava bacterial blight susceptibility. We used CRISPR/Cas9 to generate multiple cassava lines with edits to the MeSWEET10a TAL20 effector binding site and/or coding sequence. In several of the regenerated lines, MeSWEET10a expression was no longer induced by Xpm, and in these cases, we observed reduced cassava bacterial blight (CBB) disease symptoms post Xpm infection. Because MeSWEET10a is expressed in cassava flowers, we further characterized the reproductive capability of the MeSWEET10a promoter and coding sequence mutants. Lines were crossed to themselves and to wild-type plants. The results indicated that expression of MeSWEET10a in female, but not male, flowers, is critical to produce viable F1 seed. In the case of promoter mutations that left the coding sequence intact, viable F1 progeny were recovered. Taken together, these results demonstrate that blocking MeSWEET10a induction is a viable strategy for decreasing cassava susceptibility to CBB and that ideal lines will contain promoter mutations that block TAL effector binding while leaving endogenous expression of MeSWEET10a unaltered.

Emergent neural dynamics and geometry for generalization in a transitive inference task.

Relational cognition-the ability to infer relationships that generalize to novel combinations of objects-is fundamental to human and animal intelligence. Despite this importance, it remains unclear how relational cognition is implemented in the brain due in part to a lack of hypotheses and predictions at the levels of collective neural activity and behavior. Here we discovered, analyzed, and experimentally tested neural networks (NNs) that perform transitive inference (TI), a classic relational task (if A > B and B > C, then A > C). We found NNs that (i) generalized perfectly, despite lacking overt transitive structure prior to training, (ii) generalized when the task required working memory (WM), a capacity thought to be essential to inference in the brain, (iii) emergently expressed behaviors long observed in living subjects, in addition to a novel order-dependent behavior, and (iv) expressed different task solutions yielding alternative behavioral and neural predictions. Further, in a large-scale experiment, we found that human subjects performing WM-based TI showed behavior inconsistent with a class of NNs that characteristically expressed an intuitive task solution. These findings provide neural insights into a classical relational ability, with wider implications for how the brain realizes relational cognition.

Gamification and motivation: Impact on delay discounting performance.

Delay discounting is a phenomenon strongly associated with impulsivity. However, in order for a measured discounting rate in an experiment to meaningfully generalize to choices made elsewhere in life, participants must provide thoughtful, engaged answers during the assessment. Classic discounting tasks may not optimize intrinsic motivation or enjoyment, and a participant who is disengaged from the task is likely to behave in a way that provides a biased estimate of their discounting function. We assessed degree of delay discounting in a task intended to vary level of participant motivation. This was accomplished by introducing varying levels of gamification, the application of game design principles to a non-game context. Experiment 1 compared three versions of the delay discounting task with differing degrees of gamification and compared performance and task enjoyment across those variations, while Experiment 2 used two conditions (one gamified, one not). Participants found more gamified versions of the task more enjoyable than the other conditions, without producing substantial between-group differences in most cases. Thus, more polished task gameplay can provide a more enjoyable experience for participants without undermining delay discounting effects commonly reported in the literature. We also found that in all experimental conditions, higher levels of interest in or enjoyment of the task tended to be associated with more rapid discounting. This may suggest that low task motivation may result in less impulsive choice and suggests that participants who find delay discounting experiments sufficiently boring may bias assessments of value across delays.

A mathematical theory of relational generalization in transitive inference.

Humans and animals routinely infer relations between different items or events and generalize these relations to novel combinations of items. This allows them to respond appropriately to radically novel circumstances and is fundamental to advanced cognition. However, how learning systems (including the brain) can implement the necessary inductive biases has been unclear. Here we investigated transitive inference (TI), a classic relational task paradigm in which subjects must learn a relation (A > B and B > C) and generalize it to new combinations of items (A > C). Through mathematical analysis, we found that a broad range of biologically relevant learning models (e.g. gradient flow or ridge regression) perform TI successfully and recapitulate signature behavioral patterns long observed in living subjects. First, we found that models with item-wise additive representations automatically encode transitive relations. Second, for more general representations, a single scalar "conjunctivity factor" determines model behavior on TI and, further, the principle of norm minimization (a standard statistical inductive bias) enables models with fixed, partly conjunctive representations to generalize transitively. Finally, neural networks in the "rich regime," which enables representation learning and has been found to improve generalization, unexpectedly show poor generalization and anomalous behavior. We find that such networks implement a form of norm minimization (over hidden weights) that yields a local encoding mechanism lacking transitivity. Our findings show how minimal statistical learning principles give rise to a classical relational inductive bias (transitivity), explain empirically observed behaviors, and establish a formal approach to understanding the neural basis of relational abstraction.

Inefficient prioritization of task-relevant attributes during instrumental information demand.

In natural settings, people evaluate complex multi-attribute situations and decide which attribute to request information about. Little is known about how people make this selection and specifically, how they identify individual observations that best predict the value of a multi-attribute situation. Here show that, in a simple task of information demand, participants inefficiently query attributes that have high individual value but are relatively uninformative about a total payoff. This inefficiency is robust in two instrumental conditions in which gathering less informative observations leads to significantly lower rewards. Across individuals, variations in the sensitivity to informativeness is associated with personality metrics, showing negative associations with extraversion and thrill seeking and positive associations with stress tolerance and need for cognition. Thus, people select informative queries using sub-optimal strategies that are associated with personality traits and influence consequential choices.

Improving cassava bacterial blight resistance by editing the epigenome.

Pathogens rely on expression of host susceptibility (S) genes to promote infection and disease. As DNA methylation is an epigenetic modification that affects gene expression, blocking access to S genes through targeted methylation could increase disease resistance. Xanthomonas phaseoli pv. manihotis, the causal agent of cassava bacterial blight (CBB), uses transcription activator-like20 (TAL20) to induce expression of the S gene MeSWEET10a. In this work, we direct methylation to the TAL20 effector binding element within the MeSWEET10a promoter using a synthetic zinc-finger DNA binding domain fused to a component of the RNA-directed DNA methylation pathway. We demonstrate that this methylation prevents TAL20 binding, blocks transcriptional activation of MeSWEET10a in vivo and that these plants display decreased CBB symptoms while maintaining normal growth and development. This work therefore presents an epigenome editing approach useful for crop improvement.

Superstitious learning of abstract order from random reinforcement.

Humans and other animals often infer spurious associations among unrelated events. However, such superstitious learning is usually accounted for by conditioned associations, raising the question of whether an animal could develop more complex cognitive structures independent of reinforcement. Here, we tasked monkeys with discovering the serial order of two pictorial sets: a "learnable" set in which the stimuli were implicitly ordered and monkeys were rewarded for choosing the higher-rank stimulus and an "unlearnable" set in which stimuli were unordered and feedback was random regardless of the choice. We replicated prior results that monkeys reliably learned the implicit order of the learnable set. Surprisingly, the monkeys behaved as though some ordering also existed in the unlearnable set, showing consistent choice preference that transferred to novel untrained pairs in this set, even under a preference-discouraging reward schedule that gave rewards more frequently to the stimulus that was selected less often. In simulations, a model-free reinforcement learning algorithm (Q-learning) displayed a degree of consistent ordering among the unlearnable set but, unlike the monkeys, failed to do so under the preference-discouraging reward schedule. Our results suggest that monkeys infer abstract structures from objectively random events using heuristics that extend beyond stimulus-outcome conditional learning to more cognitive model-based learning mechanisms.

Influence of Rule- and Reward-based Strategies on Inferences of Serial Order by Monkeys.

Knowledge of transitive relationships between items can contribute to learning the order of a set of stimuli from pairwise comparisons. However, cognitive mechanisms of transitive inferences based on rank order remain unclear, as are relative contributions of reward associations and rule-based inference. To explore these issues, we created a conflict between rule- and reward-based learning during a serial ordering task. Rhesus macaques learned two lists, each containing five stimuli that were trained exclusively with adjacent pairs. Selection of the higher-ranked item resulted in rewards. "Small reward" lists yielded two drops of fluid reward, whereas "large reward" lists yielded five drops. Following training of adjacent pairs, monkeys were tested on novels pairs. One item was selected from each list, such that a ranking rule could conflict with preferences for large rewards. Differences between the corresponding reward magnitudes had a strong influence on accuracy, but we also observed a symbolic distance effect. That provided evidence of a rule-based influence on decisions. RT comparisons suggested a conflict between rule- and reward-based processes. We conclude that performance reflects the contributions of two strategies and that a model-based strategy is employed in the face of a strong countervailing reward incentive.

Positional inference in rhesus macaques.

Understanding how organisms make transitive inferences is critical to understanding their general ability to learn serial relationships. In this context, transitive inference (TI) can be understood as a specific heuristic that applies broadly to many different serial learning tasks, which have been the focus of hundreds of studies involving dozens of species. In the present study, monkeys learned the order of 7-item lists of photographic stimuli by trial and error, and were then tested on "derived" lists. These derived test lists combined stimuli from multiple training lists in ambiguous ways, sometimes changing their order relative to training. We found that subjects displayed strong preferences when presented with novel test pairs, even when those pairs were drawn from different training lists. These preferences were helpful when test pairs had an ordering congruent with their ranks during training, but yielded consistently below-chance performance when pairs had an incongruent order relative to training. This behavior can be explained by the joint contributions of transitive inference and another heuristic that we refer to as "positional inference." Positional inferences play a complementary role to transitive inferences in facilitating choices between novel pairs of stimuli. The theoretical framework that best explains both transitive and positional inferences is a spatial model that represents both the position of each stimulus and its uncertainty. A computational implementation of this framework yields accurate predictions about both correct responses and errors on derived lists.

Transitive inference after minimal training in rhesus macaques (Macaca mulatta).

Rhesus macaques, when trained for several hundred trials on adjacent items in an ordered list (e.g., A > B, B > C, C > D), are able to make accurate transitive inferences (TI) about previously untrained pairs (e.g., A > C, B > D). How that learning unfolds during training, however, is not well understood. We sought to measure the relationship between the amount of TI training and the resulting response accuracy in 4 rhesus macaques using seven-item lists. The training conditions included the absolute minimal case of presenting each of the six adjacent pairs only once prior to testing. We also tested transfer to nonadjacent pairs with 24 and 114 training trials. Because performance during and after small amounts of training is expected to be near chance levels, we developed a descriptive statistical model to estimate potentially subtle learning effects in the presence of much larger random response variability and systematic bias. These results suggest that subjects learned serial order in an incremental fashion. Thus, rather than performing transitive inference by a logical process, serial learning in rhesus macaques proceeds in a manner more akin to a statistical inference, with an initial uncertainty about list position that gradually becomes more accurate as evidence accumulates. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Failure to Find Altruistic Food Sharing in Rats.

Prior research has found that one rat will release a second rat from a restraint in the presence of food, thereby allowing that second rat access to food. Such behavior, clearly beneficial to the second rat and costly to the first, has been interpreted as altruistic. Because clear demonstrations of altruism in rats are rare, such findings deserve a careful look. The present study aimed to replicate this finding, but with more systematic methods to examine whether, and under what conditions, a rat might share food with its cagemate partner. Rats were given repeated choices between high-valued food (sucrose pellets) and 30-s social access to a familiar rat, with the (a) food size (number of food pellets per response), and (b) food motivation (extra-session access to food) varied across conditions. Rats responded consistently for both food and social interaction, but at different levels and with different sensitivity to the food-access manipulations. Food production and consumption was high when food motivation was also high (food restriction) but substantially lower when food motivation was low (unlimited food access). Social release occurred at moderate levels, unaffected by the food-based manipulations. When food was abundant and food motivation low, the rats chose food and social options about equally often, but sharing (food left unconsumed prior to social release) occurred at low levels across sessions and conditions. Even under conditions of low food motivation, sharing occurred on only 1% of the sharing opportunities. The results are therefore inconsistent with claims in the literature that rats are altruistically motivated to share food with other rats.

Safety evaluation of a clinical focused ultrasound system for neuronavigation guided blood-brain barrier opening in non-human primates.

An emerging approach with potential in improving the treatment of neurodegenerative diseases and brain tumors is the use of focused ultrasound (FUS) to bypass the blood-brain barrier (BBB) in a non-invasive and localized manner. A large body of pre-clinical work has paved the way for the gradual clinical implementation of FUS-induced BBB opening. Even though the safety profile of FUS treatments in rodents has been extensively studied, the histological and behavioral effects of clinically relevant BBB opening in large animals are relatively understudied. Here, we examine the histological and behavioral safety profile following localized BBB opening in non-human primates (NHPs), using a neuronavigation-guided clinical system prototype. We show that FUS treatment triggers a short-lived immune response within the targeted region without exacerbating the touch accuracy or reaction time in visual-motor cognitive tasks. Our experiments were designed using a multiple-case-study approach, in order to maximize the acquired data and support translation of the FUS system into human studies. Four NHPs underwent a single session of FUS-mediated BBB opening in the prefrontal cortex. Two NHPs were treated bilaterally at different pressures, sacrificed on day 2 and 18 post-FUS, respectively, and their brains were histologically processed. In separate experiments, two NHPs that were earlier trained in a behavioral task were exposed to FUS unilaterally, and their performance was tracked for at least 3 weeks after BBB opening. An increased microglia density around blood vessels was detected on day 2, but was resolved by day 18. We also detected signs of enhanced immature neuron presence within areas that underwent BBB opening, compared to regions with an intact BBB, confirming previous rodent studies. Logistic regression analysis showed that the NHP cognitive performance did not deteriorate following BBB opening. These preliminary results demonstrate that neuronavigation-guided FUS with a single-element transducer is a non-invasive method capable of reversibly opening the BBB, without substantial histological or behavioral impact in an animal model closely resembling humans. Future work should confirm the observations of this multiple-case-study work across animals, species and tasks.

The trajectory of cortical GABA across the lifespan, an individual participant data meta-analysis of edited MRS studies.

γ-Aminobutyric acid (GABA) is the principal inhibitory neurotransmitter in the human brain and can be measured with magnetic resonance spectroscopy (MRS). Conflicting accounts report decreases and increases in cortical GABA levels across the lifespan. This incompatibility may be an artifact of the size and age range of the samples utilized in these studies. No single study to date has included the entire lifespan. In this study, eight suitable datasets were integrated to generate a model of the trajectory of frontal GABA estimates (as reported through edited MRS; both expressed as ratios and in institutional units) across the lifespan. Data were fit using both a log-normal curve and a nonparametric spline as regression models using a multi-level Bayesian model utilizing the Stan language. Integrated data show that an asymmetric lifespan trajectory of frontal GABA measures involves an early period of increase, followed by a period of stability during early adulthood, with a gradual decrease during adulthood and aging that is described well by both spline and log-normal models. The information gained will provide a general framework to inform expectations of future studies based on the age of the population being studied.

Gene tagging via CRISPR-mediated homology-directed repair in cassava.

Research on a few model plant-pathogen systems has benefitted from years of tool and resource development. This is not the case for the vast majority of economically and nutritionally important plants, creating a crop improvement bottleneck. Cassava bacterial blight (CBB), caused by Xanthomonas axonopodis pv. manihotis (Xam), is an important disease in all regions where cassava (Manihot esculenta Crantz) is grown. Here, we describe the development of cassava that can be used to visualize one of the initial steps of CBB infection in vivo. Using CRISPR-mediated homology-directed repair (HDR), we generated plants containing scarless insertion of GFP at the 3' end of CBB susceptibility (S) gene MeSWEET10a. Activation of MeSWEET10a-GFP by the transcription activator-like (TAL) effector TAL20 was subsequently visualized at transcriptional and translational levels. To our knowledge, this is the first such demonstration of HDR via gene editing in cassava.

Category learning in a transitive inference paradigm.

The implied order of a ranked set of visual images can be learned without reliance on information that explicitly signals their order. Such learning is difficult to explain by associative mechanisms, but can be accounted for by cognitive representations and processes such as transitive inference. Our study sought to determine if those processes also apply to learning categories of images. We asked whether participants can (a) infer that stimulus images belonged to familiar categories, even when the images for each trial were unique, and (b) sort those categories into an ordering that obeys transitivity. Participants received minimal verbal instruction and a single session of training. Despite this, they learned the implied order of lists of fixed stimuli and lists of ordered categories, using trial-unique exemplars. We trained two groups, one for which stimuli were constant throughout training and testing (n = 60), and one for which exemplars of each category were trial-unique (n = 50). Our findings suggest that differing cognitive processes may underpin serial learning when learning about specific stimuli as opposed to stimulus categories.

Disruption of tph1 genes demonstrates the importance of serotonin in regulating ventilation in larval zebrafish (Danio rerio).

Serotonergic neuroepithelial cells (NECs) in larval zebrafish are believed to be O2 chemoreceptors. Serotonin (5-HT) within these NECs has been implicated as a neurotransmitter mediating the hypoxic ventilatory response (HVR). Here, we use knockout approaches to discern the role of 5-HT in regulating the HVR by targeting the rate limiting enzyme for 5-HT synthesis, tryptophan hydroxylase (Tph). Using transgenic lines, we determined that Tph1a is expressed in skin and pharyngeal arch NECs, as well as in pharyngeal arch Merkel-like cells (MLCs), whereas Tph1b is expressed predominately in MLCs. Knocking out the two tph1 paralogs resulted in similar changes in detectable serotonergic cell density between the two mutants, yet their responses to hypoxia (35 mmHg) were different. Larvae lacking Tph1a (tph1a-/- mutants) displayed a higher ventilation rate when exposed to hypoxia compared to wild-types, whereas tph1b-/- mutants exhibited a lower ventilation rate suggesting that 5-HT located in locations other than NECs, may play a dominant role in regulating the HVR.

Learned Representation of Implied Serial Order in Posterior Parietal Cortex.

Monkeys can learn the implied ranking of pairs of images drawn from an ordered set, despite never seeing all of the images simultaneously and without explicit spatial or temporal cues. We recorded the activity of posterior parietal cortex (including lateral intraparietal area LIP) neurons while monkeys learned 7-item transitive inference (TI) lists with 2 items presented on each trial. Behavior and neuronal activity were significantly influenced by the ordinal relationship of the stimulus pairs, specifically symbolic distance (the difference in rank) and joint rank (the sum of the ranks). Symbolic distance strongly predicted decision accuracy and learning rate. An effect of joint rank on performance was found nested within the symbolic distance effect. Across the population of neurons, there was significant modulation of firing correlated with the relative ranks of the two stimuli presented on each trial. Neurons exhibited selectivity for stimulus rank during learning, but not before or after. The observed behavior is poorly explained by associative or reward mechanisms, and appears more consistent with a mental workspace model in which implied serial order is mapped within a spatial framework. The neural data suggest that posterior parietal cortex supports serial learning by representing information about the ordinal relationship of the stimuli presented during a given trial.

Integrated genomic characterization of ERBB2/HER2 alterations in invasive breast carcinoma: a focus on unusual FISH groups.

In patients with invasive breast cancer, fluorescence in situ hybridization (FISH) testing for HER2 typically demonstrates the clear presence or lack of ERBB2 (HER2) amplification (i.e., groups 1 or 5). However, a small subset of patients can present with unusual HER2 FISH patterns (groups 2-4), resulting in diagnostic confusion. To provide clarity, the 2018 CAP/ASCO HER2 testing guideline recommends additional testing using HER2 immunohistochemistry (IHC) for determining the final HER2 status. Despite this effort, the genomic correlates of unusual HER2 FISH groups remain poorly understood. Here, we used droplet digital PCR (ddPCR) and targeted next-generation sequencing (NGS) to characterize the genomic features of both usual and unusual HER2 FISH groups. In this study, 51 clinical samples were selected to represent FISH groups 1-5. Furthermore, group 1 was subdivided into two groups, with groups 1A and 1B corresponding to cases with HER2 signals/cell ≥6.0 and 4-6, respectively. Overall, our findings revealed a wide range of copy number alterations in HER2 across the different FISH groups. As expected, groups 1A and 5 showed the clear presence and lack of HER2 copy number gain, respectively, as measured by ddPCR and NGS. In contrast, group 1B and other uncommon FISH groups (groups 2-4) were characterized by a broader range of HER2 copy levels with only a few select cases showing high-level gain. Notably, these cases with increased HER2 copy levels also showed HER2 overexpression by IHC, thus highlighting the correlation between HER2 copy number and HER2 protein expression. Given the concordance between the genomic and protein results, our findings suggest that HER2 IHC may inform HER2 copy number status in patients with unusual FISH patterns. Hence, our results support the current recommendation for using IHC to resolve HER2 status in FISH groups 2-4.

Absolute and relative knowledge of ordinal position on implied lists.

Does serial learning result in specific associations between pairs of items, or does it result in a cognitive map based on relations of all items? In 2 experiments, we trained human participants to learn various lists of photographic images. We then tested the participants on new lists of photographic images. These new lists were constructed by selecting only 1 image from each list learned during training. In Experiment 1, participants were trained to choose the earlier (experimenter defined) item when presented with adjacent pairs of items on each of 5 different 5-item lists. Participants were then tested on derived lists, in which each item retained its original ordinal position, even though each of the presented pairs was novel. Participants performed above chance on all of the derived lists. In Experiment 2, a different group of participants received the same training as those of Experiment 1, but the ordinal positions of items were systematically changed on each derived list. The response accuracy for Experiment 2 varied inversely with the degree to which an item's original ordinal position was changed. These results can be explained by a model in which participants learned to make both positional inferences about the absolute rank of each stimulus, and transitive inferences about the relative ranks of pairs of stimuli. These inferences enhanced response accuracy when ordinal position was maintained, but not when it was changed. Our results demonstrate quantitatively that, in addition to item-item associations that participants acquire while learning a list of arbitrary items, they form a cognitive map that represents both experienced and inferred relationships. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Discovering Implied Serial Order Through Model-Free and Model-Based Learning.

Humans and animals can learn to order a list of items without relying on explicit spatial or temporal cues. To do so, they appear to make use of transitivity, a property of all ordered sets. Here, we summarize relevant research on the transitive inference (TI) paradigm and its relationship to learning the underlying order of an arbitrary set of items. We compare six computational models of TI performance, three of which are model-free (Q-learning, Value Transfer, and REMERGE) and three of which are model-based (RL-Elo, Sequential Monte Carlo, and Betasort). Our goal is to assess the ability of these models to produce empirically observed features of TI behavior. Model-based approaches perform better under a wider range of scenarios, but no single model explains the full scope of behaviors reported in the TI literature.