Biology subjects

Petre, B.

Publications and source records attributed to Petre, B..

12 recordsLinked to original sources

bioRxiv2026

Cortical maps diverge, representations converge along cortical hierarchy

Brain maps (e.g. topographies like retinotopy, somatotopy) vary across individuals. This is thought to reflect computational differences, motivating personalized functional localization. However, artificial neural networks (ANNs) show that similar performance and internal representations can coexist with diverse circuit layouts. Consequently, we tested whether spatial diversity reflects computational diversity in the brain. Using task and resting-state fMRI data, we compared regional functional topographies and representational geometries-the within-individual dissimilarities among activity patterns that capture computable information. Across individuals (n = 414), representations converged in higher-order cortex despite substantial topographic diversity. Thus, different, individual-specific activity patterns encoded similar information. Topographic differences only tracked representational differences in regions under strong architectural constraints, such as highly myelinated sensory-motor cortices. We show this parallels ANNs which begin with random initial layouts but learn convergent representations, if architectures are permissive. This parallel raises a developmental question: do topographies and representations also have different developmental origins? Examining twins (n = 394), we found representations were sensitive to developmental environments and less heritable than topographies. Together, this shows that representational convergence occurs across idiosyncratic layouts in both artificial and biological systems, but is moderated by architectural constraints on circuit implementations. Accordingly, the relevance of localization-and representation-based paradigms of brain function depends on neural architecture.

neuroscience↗

bioRxiv2025

Precision Functional Mapping of Imagined and Experienced Pain

Imagination is a principal human capacity, enabling simulation of sensations and situations for planning, learning, and empathy. We examined neural representations of experienced and imagined pain across eight body sites using deep-phenotyping, precision functional MRI with over seven hours of scanning per participant (N = 9). Here we show, using conventional mapping, pattern classification, and representational similarity analyses, that both imagined and experienced pain activated nociceptive regions (e.g., dorsoposterior insula) and non-nociceptive regions (e.g., premotor areas). However, imagined pain did not reliably reactivate body site-selective nociceptive patterns in any region. Instead, imagined and experienced pain shared multivariate representations across widespread cortical and subcortical regions, particularly transmodal cortical areas including dorsomedial and lateral prefrontal cortex, hippocampus, and thalamus. These findings suggest that imagination generates distributed pain-like activity while preserving a neural distinction from experienced pain. This distinction may explain the difficulty of vividly imagining pain and underlie its role in empathy, planning, and pain vulnerability.

neuroscience↗

bioRxiv2025

The functional neurobiology of negative affective traits across regions, networks, signatures, and a machine learning multiverse

Understanding the neural basis of negative affective traits like neuroticism remains a critical challenge across psychology, neuroscience, and psychiatry. Here, we investigate which level of brain organization--regions, networks, or validated whole-brain machine-learning signatures--best explains negative affective traits in a community sample of 458 adults performing the two most widely used affective fMRI tasks, viewing emotional faces and scenes. Neuroticism could not be predicted from brain activity, with Bayesian evidence against all theory-guided neural measures. However, preregistered whole-brain models successfully decoded vulnerability to stress, a lower-level facet of neuroticism, with results replicating in a hold-out sample. The neural stress vulnerability pattern demonstrated good psychometric properties and indicated that negative affective traits are best represented by distributed whole-brain patterns related to domain-general stimulation rather than localized activity. Together with results from a comprehensive multiverse analysis across 14 traits and 1,176 models-- available for exploration in an online app--the findings speak against simplistic neurobiological theories of negative affective traits, highlight a striking gap between predicting individual differences (r<.35) and within-person emotional states (r=.88), and underscore the importance of aligning psychological constructs with neural measures at the appropriate level of granularity.

neuroscience↗

bioRxiv2024

A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, with 6 multifaceted cognitive tasks including 2 hours of naturalistic movie viewing. This datasets combination of ample sample size, extensive data per participant, more than 600 iso hours worth of data, and a wide range of experimental conditions -- including cognitive, affective, social, and somatic/interoceptive tasks -- positions it uniquely for probing important questions in cognitive neuroscience.

neuroscience↗

bioRxiv2023

Activation of plant immunity through conversion of a helper NLR homodimer into a resistosome

Nucleotide-binding domain and leucine-rich repeat (NLR) proteins can engage in complex interactions to detect pathogens and execute a robust immune response via downstream helper NLRs. However, the biochemical mechanisms of helper NLR activation by upstream sensor NLRs remain poorly understood. Here, we show that the coiled-coil helper NLR NRC2 accumulates in vivo as a homodimer that converts into a higher order oligomer upon activation by its upstream virus disease resistance protein Rx. The Cryo-EM structure of NRC2 in its resting state revealed intermolecular interactions that mediate homodimer formation. These dimerization interfaces have diverged between paralogous NRC proteins to insulate critical network nodes and enable redundant immune pathways. Our results expand the molecular mechanisms of NLR activation pointing to transition from homodimers to higher-order oligomeric resistosomes.

plant biology↗

bioRxiv2023

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Placebo analgesia is a replicable and well-studied phenomenon, yet it remains unclear to what degree it includes modulation of nociceptive processes. Some studies find effects consistent with nociceptive effects, but meta-analyses show that these effects are often small. We analyzed placebo analgesia in a large fMRI study (N = 392), including placebo effects on brain responses to noxious stimuli. Placebo treatment caused robust analgesia in both conditioned thermal and unconditioned mechanical pain. Placebo did not decrease fMRI activity in nociceptive pain regions, including the Neurologic Pain Signature (NPS) and pre-registered spinothalamic pathway regions, with strong support from Bayes Factor analyses. However, placebo treatment affected activity in pre-registered analyses of a second neuromarker, the Stimulus Intensity Independent Pain Signature (SIIPS), and several associated a priori brain regions related to motivation and value, in both thermal and mechanical pain. Individual differences in behavioral analgesia were correlated with neural changes in both thermal and mechanical pain. Our results indicate that processes related to affective and cognitive aspects of pain primarily drive placebo analgesia.

neuroscience↗

bioRxiv2021

Effect sizes and test-retest reliability of the fMRI-based Neurologic Pain Signature

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent shortterm (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with [≥]60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions. Significance statementCurrent efforts towards translating brain biomarkers require identifying brain measures that can strongly and reliably predict outcomes of interest. We systematically examined the performance of a well-established brain activity pattern, the Neurological Pain Signature (NPS), in a large and diverse sample of participants. The NPS showed excellent reliability, and the reliability scaled with the number of trials within-person. The NPS responses showed strong correlations with pain reports at the within-person level but only modest correlations at the between-person level. The findings suggest that the NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of a pain-related physiological target. Author NoteThis project was supported by grants R01MH076136 (T.D.W.), R01DA046064, R01EB026549, and R01DA035484. Elizabeth A. Reynolds Losin was supported by a Mentored Research Scientist Development award from National Institute On Drug Abuse of the National Institutes of Health (K01DA045735). Lauren Y. Atlas was supported in part by funding from the Intramural Research Program of the National Center for Complementary and Integrative Health. Yoni K. Ashar was supported by NCATS Grant # TL1-TR-002386. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Code for all analyses and figures is available at https://github.com/XiaochunHan/NPS_measurement_properties. Data for all analyses and figures is available at https://osf.io/v9px7/.

neuroscience↗

bioRxiv2020

Host-interactor screens of Phytophthora infestans RXLR proteins reveal vesicle trafficking as a major effector-targeted process

Pathogens modulate plant cell structure and function by secreting effectors into host tissues. Effectors typically function by associating with host molecules and modulating their activities. This study aimed to identify the host processes targeted by the RXLR class of host-translocated effectors of the potato blight pathogen Phytophthora infestans. To this end, we performed an in planta protein-protein interaction screen by transiently expressing P. infestans RXLR effectors in Nicotiana benthamiana leaves followed by co-immunoprecipitation (co-IP) and liquid chromatography tandem mass spectrometry (LC-MS/MS). This screen generated an effector-host protein interactome matrix of 59 P. infestans RXLR effectors x 586 N. benthamiana proteins. Classification of the host interactors into putative functional categories revealed over 35 biological processes possibly targeted by P. infestans. We further characterized the PexRD12/31 family of RXLR-WY effectors, which associate and co-localize with components of the vesicle trafficking machinery. One member of this family, PexRD31, increased the number of FYVE positive vesicles in N. benthamiana cells. FYVE positive vesicles also accumulated in leaf cells near P. infestans hyphae, indicating that the pathogen may enhance endosomal trafficking during infection. We anticipate that the interactome dataset we generated will serve as a useful community resource for functional studies of P. infestans effectors and of effector-targeted host processes.

plant biology↗

bioRxiv2020

Evoked pain intensity representation is distributed across brain systems: A multistudy mega-analysis

Information is coded in the brain at different scales for different phenomena: locally, distributed across regions and networks, and globally. For pain, the scale of representation is controversial. Although generally believed to be an integrated cognitive and sensory phenomenon implicating diverse brain systems, quantitative characterizations of which regions and networks are sufficient to represent pain are lacking. In this meta-analysis (or mega-analysis) using data from 289 participants across 10 studies, we use model comparison combined with multivariate predictive models to investigate the spatial scale and location of acute pain representation. We compare models based on (a) a single most pain-predictive module, either previously identified elementary regions or a single best large-scale cortical resting-state network module; (b) selected cortical-subcortical systems related to evoked pain in prior literature ( multi-system models); and (c) a model spanning the full brain. We estimate the accuracy of pain intensity predictions using cross validation (7 studies) and subsequently validate in three independent holdout studies. All spatial scales convey information about pain intensity, but distributed, multi-system models better characterize pain representations than any individual region or network (e.g. multisystem models explain >20% more of individual subject pain ratings than the best elementary region). Full brain models showed no predictive advantage over multi-system models. These findings quantify the extent that representation of evoked pain experience is distributed across multiple cortical and subcortical systems, show that pain representation is not circumscribed by any elementary region or conical network, and provide a blueprint for identifying the spatial scale of information in other domains. Significance StatementWe define modular, multisystem and global views of brain function, use multivariate fMRI decoding to characterize pain representations at each level, and provide evidence for a multisystem representation of evoked pain. We further show that local views necessarily exclude important components of pain representation, while a global full brain representation is superfluous, even though both are viable frameworks for representing pain. These findings quantitatively juxtapose and reconcile divergent conclusions from evoked pain studies within a generalized neuroscientific framework, and provide a blueprint for investigating representational architecture for diverse brain processes.

neuroscience↗

bioRxiv2019

Structural genomic applied on the rust fungus Melampsora larici-populina reveals two candidate effector proteins adopting cystine-knot and nuclear transport factor 2-like protein folds

Rust fungi are plant pathogens that secrete an arsenal of effector proteins interfering with plant functions and promoting parasitic infection. Effectors are often species-specific, evolve rapidly, and display low sequence similarities with known proteins or domains. How rust fungal effectors function in host cells remains elusive, and biochemical and structural approaches have been scarcely used to tackle this question. In this study, we used a strategy based on recombinant protein production in Escherichia coli to study eleven candidate effectors of the leaf rust fungus Melampsora larici-populina. We successfully purified and solved the three-dimensional structure of two proteins, MLP124266 and MLP124017, using NMR spectroscopy. Although both proteins show no sequence similarity with known proteins, they exhibit structural similarities to knottin and nuclear transport factor 2-like proteins, respectively. Altogether, our findings show that sequence-unrelated effectors can adopt folds similar to known proteins, and encourage the use of biochemical and structural approaches to functionally characterize rust effector candidates.

microbiology↗

bioRxiv2017

The rust fungus Melampsora larici-populina expresses a conserved genetic program and distinct sets of secreted protein genes during infection of its two host plants, larch and poplar

Mechanims required for broad spectrum or specific host colonization of plant parasites are poorly understood. As a perfect illustration, heteroecious rust fungi require two alternate host plants to complete their life cycle. Melampsora larici-populina infects two taxonomically unrelated plants, larch on which sexual reproduction is achieved and poplar on which clonal multiplication occurs leading to severe epidemics in plantations. High-depth RNA sequencing was applied to three key developmental stages of M. larici-populina infection on larch: basidia, pycnia and aecia. Comparative transcriptomics of infection on poplar and larch hosts was performed using available expression data. Secreted protein was the only significantly over-represented category among differentially expressed M. larici-populina genes in basidia, pycnia and aecia compared together, highlighting their probable involvement in the infection process. Comparison of fungal transcriptomes in larch and poplar revealed a majority of rust genes commonly expressed on the two hosts and a fraction exhibiting a host-specific expression. More particularly, gene families encoding small secreted proteins presented striking expression profiles that highlight probable candidate effectors specialized on each host. Our results bring valuable new information about the biological cycle of rust fungi and identify genes that may contribute to host specificity.

microbiology↗

bioRxiv2016

LOCALIZER: subcellular localization prediction of plant and effector proteins in the plant cell

Pathogens are able to deliver effector proteins into plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 108 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/.

bioinformatics↗