Biology subjects

Zid, M.

Publications and source records attributed to Zid, M..

3 recordsLinked to original sources

bioRxiv2026

Pathogenicity Validation of Parastagonospora pseudonodorum on Wheat and Barley

Parastagonospora pseudonodorum, previously known as Phaeosphaeria avenaria f. sp. tritici (Pat1), is a fungal species within the Septoria blotch complex that causes yield losses in cereal crops worldwide. First reported in Canada in 1942 under an earlier taxonomic name. However, successive taxonomic changes in addition to its close resemblance to Parastagonospora nodorum, the causal agent of Septoria nodorum blotch have complicated its identification and its role in pathogenicity. Recent molecular identification of P. pseudonodorum in Western Canadian wheat samples necessitated the re-evaluation of its pathogenicity and raised concerns about potential misidentification with the closely-related species P. nodorum. These two species secrete combinations of various necrotic effectors (NEs) that contribute to their virulence. In this study, we examined the pathogenicity of P. pseudonodorum following Koch postulates. Our results confirmed the ability of P. pseudonodorum to infect the leaves and spikes of both hosts, but the symptoms was weaker on the leaves of both hosts and wheat spikes, whereas more evident damage was observed on barley spikes. While a limited number of genotypes was tested as a proof of concept, but the observed differences in symptom severity suggest host and tissue associated variation in susceptibility. These results highlight the need to expand our monitoring of the leaf spot complex to include this species and to further explore its host range and genomic characterization. Awareness of this pathogen is essential, particularly given its association with cereal spikes and its quarantine status in some countries which could impacts the export of Canadian grains overseas.

plant biology↗

bioRxiv2025

A Foraging-Theory Based Model Captures The Full Spectrum of Human Behavioral Diversity in a Classic RL Task

Decision-making tasks involving multiple, simultaneously presented options are mainstays of cognitive neuroscience and psychology and are increasingly important to the emerging field of computational psychiatry. Modeling approaches to these tasks overwhelmingly assume that participants make choices based on explicitly comparing the values of the presented options. Contrary to this long-held assumption, we found instead that humans employ a compare-to-threshold decision process, similar to theories of foraging, when making sequential decisions about concurrently available options. We confirmed this result in a large (1000 participant) dataset with multiple converging lines of evidence comparing both model fits and model generative performance. Value-comparison models were restricted to a reduced area of the potential space of single-trial outcome-dependent behavior, demonstrating an intrinsic limitation in the ability to reproduce strategy diversity. Furthermore, we found that using even the best-fit value-comparison model led to a substantial, systematic bias and a compression of individual differences in reconstructed behavior compared to the foraging-based model, leading to weaker predictions of behavioral health measures. Our results imply that studies using value-comparison models to link behavior with neural activity or psychiatric symptoms may be less sensitive to individual differences than a simple alternative based on ethological foraging.

neuroscience↗

bioRxiv2024

Humans forage for reward in reinforcement learning tasks

How do we make good decisions in uncertain environments? In psychology and neuroscience, the classic view is that we calculate the value of each option, compare them, and choose the most rewarding modulo exploratory noise. An ethologist, conversely, would argue that we commit to one option until its value drops below a threshold and then explore alternatives. Because the fields use incompatible methods, it remains unclear which view better describes human decision-making. Here, we found that humans use compare-to-threshold computations in classic compare-alternative tasks. Because compare-alternative computations are central to the reinforcement-learning (RL) models typically used in the cognitive and brain sciences, we developed a novel compare-to-threshold model ("foraging"). Compared to previous RL models, the foraging model better fit participant behavior, better predicted the tendency to repeat choices, and predicted held-out participants that were almost impossible under comparealternative models. These results suggest that humans use compare-to-threshold computations in sequential decision-making.

neuroscience↗