Biology subjects

Jensen, G.

Publications and source records attributed to Jensen, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Transitive reasoning as linear classification

Transitive inference (TI) is the ability to reason about transitive relationships in an ordered set of items (e.g., if A>B and B>C, then A>C). TI is widely held to depend on a linear representation of the serial (rank) order of those items. By what computational mechanism is such an ordering constructed during learning, and how is it used to make choices that obey transitivity? Here we take a minimalist approach, applying least-squares estimation (LSE) to a serial learning task commonly used to test TI in humans and animals. In this formulation, LSE computes a linear classifier that maps task conditions onto behavioral outcomes. This algorithm makes no explicit assumptions about transitivity or serial order, yet it reproduces key empirical features of TI; namely, the ability to generalize beyond the training set, and a symbolic distance effect (SDE) in performance accuracy. Applying the classifier to individual items produces an internally ordered representation of rank from which both generalization and the SDE naturally emerge. The approach also yields a decision mechanism, in the form of a differencing operation, for selecting the correct item from any pair. These findings reframe TI as a linear classification problem, challenging conventional assumptions about the cognitive mechanisms required for transitive reasoning.

neuroscience↗

bioRxiv2026

Multiple approaches for CRISPR-based targeting of DNA methylation to promoters of bacterial and viral susceptibility genes in cassava

Targeted epigenetic modifications of specific gene regulatory regions have the potential to confer beneficial traits for crop improvement. Two recently developed CRISPR/Cas9-based epigenome editing tools were tested in transgenic cassava to target cytosine methylation to the promoter region of MeSWEET10a, a necessary gene for infection by the Cassava bacterial blight pathogen, Xanthomonas phaseoli pv. manihotis. The two systems leverage unique methyltransferases, and each induced distinct DNA methylation profiles at the targeted site, decreased effector-triggered MeSWEET10a expression, and attenuated water-soaking symptoms in inoculated leaves. Further, DNA methylation was simultaneously targeted, in addition to MeSWEET10a, to two susceptibility genes for Cassava brown streak virus. Relative levels of de novo DNA methylation at the three loci were inversely correlated with DNA methylation-antagonizing H3K4me3 marks. Finally, an initial assessment of DNA methylation after one generation indicated specific inheritance of CpG methylation that was unstable in the absence of the methyltransferase systems.

plant biology↗

bioRxiv2026

Aging macaques bridge the translational gap in perivascular space biology

The prevalence of MR-visible perivascular spaces (PVS) is age-dependent in rhesus macaques. Automated quantification in 94 male and female animals ranging 5-28 years of age demonstrated a robust association between age and PVS burden, with an anatomical distribution paralleling that of humans. Preliminary ex vivo validation confirmed that the MRI-detected tubular structures correspond to perivascular spaces. These findings establish the rhesus macaque as a tractable model for understanding the role of perivascular dysfunction in age-related brain vulnerability.

neuroscience↗

bioRxiv2025

Sex-specific trajectories of gait adaptation following partial dopaminergic lesions in a rat model of parkinsons disease

Parkinsons disease (PD) is a neurodegenerative disorder in which gait disturbances are central to disability, yet their early manifestations remain poorly understood due to the difficulty of identifying prodromal PD in humans. Rodent models may help narrow this gap by approximating partial dopaminergic loss and enabling investigation of motor changes that precede overt symptoms. Here, we examined gait dynamics in Wistar rats following unilateral, low-dose 6-hydroxydopamine (6-OHDA) lesions in the substantia nigra pars compacta (SNc). Animals were assessed weekly for six weeks in the horizontal ladder test, where running velocity and footfall accuracy were quantified with markerless pose estimation using DeepLabCut (DLC). Lesioned animals exhibited greater tyrosine hydroxylase (TH)-reactivity asymmetry than controls, reflected behaviorally as persistent but gradually attenuating deficits in gait precision. Errors peaked at week three and remained above baseline through week six. Velocity was preserved across groups, but sex differences emerged. Control females accelerated more steeply over time, whereas lesioned females showed attenuated gains and greater variability, while males displayed more homogeneous velocity profiles across conditions. Together, these findings indicate that partial SNc lesions reveal sex-specific trajectories of motor adaptation, a feature relevant to modeling prodromal PD. Combined with DLC-based tracking, this framework offers a practical approach for detecting early behavioral markers and supporting the identification of preclinical motor features of PD.

neuroscience↗

bioRxiv2025

Single-Neuron Encoding of Learnability in the Dorsal Anterior Cingulate Cortex

In natural environments, associations that indicate true learnable regularities are intermixed with those that arise from random and ultimately unlearnable relationships between events. To efficiently allocate cognitive resources and avoid inferring spurious patterns, organisms must distinguish learnable from unlearnable associations, but the mechanisms underlying this ability are not understood. We recently showed that monkeys performing a transitive inference task, while discovering the true hidden order in learnable image sets, also behaved to varying degrees as if they inferred subjective order in objectively random (unlearnable) image sets. Here, we show that the ability to detect learnability is encoded by neurons in the dorsal anterior cingulate cortex (dACC, area 24c). dACC neurons responded strongly after a decision outcome as reported in previous studies and, additionally, signaled whether a trial was from a learnable vs unlearnable set before outcome delivery, and showed interactions whereby their selectivity for the outcome (reward vs lack of reward) was stronger for learnable versus unlearnable sets. Learnability and interaction responses were independent of sensory or reward cues (which were equated for learnable and unlearnable sets) but their strength correlated with the monkeys ability to avoid inferring false order in unlearnable sets. The findings suggest that the dACC is part of a network that monitors learnability and enables animals to appropriately focus learning on true patterns while avoiding false inferences about spurious and random associations.

neuroscience↗

bioRxiv2025

Targeted and random mutagenesis of cassava brown streak disease susceptibility factors reveal molecular determinants of disease severity

Cassava brown streak disease (CBSD) is caused by cassava brown streak viruses (CBSVs) from the family Potyviridae. Potyvirid viral genome-linked protein (VPg) recruitment of host eukaryotic translation initiation factor 4E (eIF4E) proteins is a critical step in the viral life cycle. CBSV VPg interacts with all five cassava eIF4E-family members. Simultaneously knocking out eIF4E-family genes nCBP-1 and nCBP-2, in cultivar 60444, strongly reduces CBSD root symptoms and viral titer but does not result in complete resistance, likely due to gene family redundancy. To test for redundancy, we generated single and double mutants for each clade of the eIF4E gene family in farmer preferred cultivar TME419. Double mutants for the eIF(iso)4E and nCBP clades both exhibited reduced symptom severity, with ncbp-1 ncbp-2 having the strongest phenotype. A yeast two-hybrid screen for nCBP-2 mutants that lose VPg affinity identified fifty-one mutants, including an L51F mutant. This finding is consistent with one of the recovered cassava mutants that had a 6 amino acid deletion, including L51, in nCBP-2 and showed a reduction in symptoms relative to wild type. The data presented here suggest that generating mutations corresponding to L51F of nCBP-2 in multiple or all five cassava eIF4E proteins may lead to stronger resistance to CBSD while avoiding pleiotropic effects.

plant biology↗

bioRxiv2025

Learning decouples accuracy and reaction time for rapid decisions in a transitive inference task

Transitive inference (TI) is a cognitive process in which decisions are guided by internal representations of abstract relationships. While the mechanisms underlying transitive learning have been well studied, the dynamics of the decision-making process during learning and inference remain less clearly understood. In this study, we investigated whether a modeling framework traditionally applied to perceptual decision-making--the drift diffusion model (DDM)--can account for performance in a TI transfer task involving rapid decisions that deviate from standard accuracy and response time (RT) patterns. We trained six macaque monkeys on a TI transfer task, in which they learned the implied order of a novel list of seven images in each behavioral session, indicating their decisions with saccadic eye movements or reaching movements. Consistent learning of the list structure was achieved within 200-300 trials per session. Behavioral performance exhibited a symbolic distance effect, with accuracy increasing as the ordinal distance between items grew. Notably, RTs remained relatively stable across learning, despite improvements in accuracy. We applied a generalized DDM implementation (PyDDM; Shinn et al., 2020) to jointly fit accuracy and RT data. Model fits were achieved by incorporating both an increasing evidence accumulation rate and a collapsing decision bound, successfully capturing the RT distribution shapes observed during learning. Learning and transfer were fit by varying drift rate with little change in other parameters. Eye and reaching movements showed similar dynamics, with the difference in RT accounted for mainly by non-decision time. Our results highlight a distinct dynamical regime of the DDM framework, extending its applicability to cognitive domains involving symbolic reasoning and serial relational learning.

animal behavior and cognition↗

bioRxiv2024

Human NLRP3 inflammasome activation leads to formation of condensate at the microtubule organizing center

The NLRP3 inflammasome is a multi-protein molecular machine that mediates inflammatory responses in innate immunity. Its dysregulation has been linked to a large number of human diseases. Using cryogenic fluorescence-guided focused-ion-beam (cryo-FIB) milling and electron cryo-tomography (cryo-ET), we obtained 3-D images of the NLRP3 inflammasome in situ at various stages of its activation at macromolecular resolution. The cryo-tomograms unexpectedly reveal dense condensates of the human macrophage NLRP3 inflammasome that form within and around the microtubule organizing center (MTOC). We also find that following activation, the trans-Golgi network disperses and 50-nm NLRP3-associated vesicles appear which likely ferry NLRP3 to the MTOC. At later time points after activation, the electron-dense condensates progressively solidify and the cells undergo pyroptosis with widespread damaged mitochondria and autophagasomal structures.

immunology↗

bioRxiv2023

"Surviving and Thriving": Evidence for Cortical GABA Stabilization in Cognitively-Intact Oldest-Old Adults

Cortical GABA levels are reduced in older age; age-related differences in GABA may be associated with age-related cognitive change. The nature of age-related GABA differences in the highest-functioning stratum of the oldest-old (85+) population is not yet known. We extend our previously-reported Individual Participant Data Meta-Analysis of GABA levels (Porges et al., 2021) across the lifespan with four novel datasets sampling the cognitively-intact oldest-old. The slope of age-related GABA differences in cognitively-intact oldest-old adults flattens after roughly age 80. We interpret these findings as an effect of survivorship: inclusion in the study required intact cognition, and too great a reduction of GABA levels may not be compatible with neurophysiological function needed for intact cognition. This work contributes to a growing body of evidence suggesting that successful cognitive aging may require intact GABAergic function, as well as further characterizing successful aging amongst oldest-old adults.

neuroscience↗

bioRxiv2023

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.

neuroscience↗

bioRxiv2023

CRISPR/Cas9 generated MeSWEET10a mutants show reduced susceptibility to cassava bacterial blight and produce viable seed

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. The Xpm effector, TAL20, induces ectopic expression of the S gene, MeSWEET10a, 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 disease symptoms post Xpm infection. MeSWEET10a is expressed in cassava flowers. Therefore, we investigated flower development and reproductive function in an MeSWEET10a mutant line. We found that the MeSWEET10a mutant produced phenotypically wildtype cassava flowers and viable F1 seed. Thus, blocking MeSWEET10a induction is a viable strategy for decreasing cassava susceptibility to CBB.

plant biology↗

bioRxiv2023

Novel psilocin prodrugs with altered pharmacological properties as candidate therapies for treatment-resistant anxiety disorders

The psychedelic compound psilocybin has shown therapeutic benefit in the treatment of numerous psychiatric diseases. A recent randomized clinical trial conducted at Johns Hopkins Bayview Medical Center demonstrated the efficacy of psilocybin-assisted therapy in the treatment of Major Depressive Disorder (MDD). Similarly, a phase IIb study evaluating psilocybin-assisted therapy for treatment-resistant depression (TRD) presented statistically meaningful and long-term reduction in depressive symptoms. Also, many studies have reported the successful treatment of severe anxiety after a single oral dose of psilocybin, especially in patients struggling with cancer-related distress (CRD). Despite these compelling clinical results, concerns regarding the duration of the psychedelic experience produced by psilocybin pose a significant barrier to its widespread therapeutic application. Psilocybin, derived from magic mushrooms is the naturally occurring prodrug of the neuroactive compound psilocin. When orally administered, exposure to the acidic gastrointestinal (GI) environment together with enzymatic processing by intestinal and hepatic alkaline phosphatase lead to the dephosphorylation of psilocybin producing elevated levels of systemic psilocin. These plasma levels are detectable up to 24 h and produce a psychoactive episode lasting as long as 6 h post-ingestion. In order to positively modify the kinetics of the acute psychedelic response, we have engineered a library of novel prodrug derivatives (NPDs) of psilocin, introducing a diversity of alternative metabolically cleavable moieties modified at the 4-carbon position of the core indole ring. This library consists of twenty-eight unique compounds represented by nine distinct prodrug classes. Each molecule was screened in vitro for metabolic stability using isolated human serum, and human cellular fractions derived from liver and intestinal tissues. This screen revealed fifteen prodrugs that produced measurable levels of psilocin in vitro, with ester and thiocarbonate-based prodrug derivatives significantly represented. These fifteen NPDs were further evaluated for pharmacokinetic (PK) profiles in mice, assessing plasma levels of both residual prodrug and resultant psilocin. PK results confirmed the efficiency of ester and thiocarbonate-based prodrug metabolism upon oral and intravenous administration, achieving levels reduced, albeit comparable to levels of psilocybin-derived psilocin. Of note, almost all NPDs tested maintained reduced overall exposure of psilocin relative to psilocybin, with no measurable levels detected at 24 h post-dose. Finally, all NPDs were screened for CNS bioavailability in healthy mice using the Head Twitch Response (HTR), a behavioural biomarker of 5-HT2A receptor stimulation and an established proxy for psychoactive potential. Interestingly, five NPDs produced peak HTR that approached or exceeded levels induced by an equivalent dose of psilocybin. Among these bioactive prodrugs, an ester-based and thiocarbonate-based molecule produced long-term anxiolytic benefit in chronically stressed mice evaluated in the marble burying psychiatric model. Overall, this screening campaign identified novel candidate prodrugs of psilocin with altered metabolic profiles and reduced pharmacological exposure, potentially attenuating the duration of the psychedelic response. These molecules still maintained the long-term psychiatric and physiological benefits characteristic of psilocybin therapy. Additionally, these modified parameters also offer the opportunity for altered routes of administration bypassing conventional oral dosing.

pharmacology and toxicology↗

bioRxiv2022

Neural dynamics and geometry for transitive inference

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 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) adopted 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 expressing an intuitive task solution. These findings provide neural insights into a classical relational ability, with wider implications for how the brain realizes relational cognition.

neuroscience↗

bioRxiv2022

Superstitious learning of abstract order from random reinforcement

Survival depends on identifying learnable features of the environment that predict reward, and avoiding others that are random and unlearnable. However, humans and other animals often infer spurious associations among unrelated events, raising the question of how well they can distinguish learnable patterns from unlearnable events. 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 RL 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.

animal behavior and cognition↗

bioRxiv2022

Improving disease resistance in plants 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.

plant biology↗

bioRxiv2021

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 contributions of reward magnitude 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 2 drops of fluid reward, while "large reward" lists yielded 5 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 in associated reward magnitude had a strong influence on accuracy, but we also observed a symbolic distance effect. That provided evidence of a rule-based influence on decisions. Reaction time 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.

animal behavior and cognition↗

bioRxiv2020

The trajectory of cortical GABA levels across thelifespan: An individual participant datameta-analysis of edited MRS studies

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, 8 suitable datasets were integrated to generate a model of the trajectory of GABA 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 the lifespan trajectory of GABA involves an early period of rapid 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.

neuroscience↗

bioRxiv2020

Visualizing cassava bacterial blight at the molecular level using CRISPR-mediated homology-directed repair

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 development of a tool for molecular-level visualization of CBB dynamics in vivo. Using CRISPR-mediated homology-directed repair (HDR), we generated plants containing scarless insertion of a GFP reporter at the CBB susceptibility (S) gene MeSWEET10a. Activation of MeSWEET10a-GFP by Xam was subsequently visualized at transcriptional and translational levels. Development of this tool was facilitated by a time-saving, adaptable strategy for identifying successful products of HDR, currently a limiting factor in plant research. This strategy has the potential to enable such research in other systems, improving the practicality of HDR-based experimentation.

plant biology↗