Biology subjects

De Angelis, L.

Publications and source records attributed to De Angelis, L..

6 recordsLinked to original sources

bioRxiv2026

Modeling behavior to disentangle motion-related effects in functional ultrasound imaging in awake, head-fixed mice

Functional ultrasound imaging (fUSI) enables brain-wide mapping of hemodynamic activity in awake rodents, offering a powerful bridge between systems neuroscience in animals and human neuroimaging. However, extending fUSI beyond tightly controlled sensory paradigms to more naturalistic behaviors is limited by motion-related confounds arising from locomotion, physiological arousal, and movement-linked neural activity. Here, we introduce a behavior-informed modeling framework that explicitly incorporates continuous measurements of running speed and head motion into a general linear model to account for motion-related variance while preserving interpretable task-related signals. We validate this approach in two head-fixed paradigms with distinct motion profiles: a visual stimulation task with minimal stimulus-driven movement, and a noxious stimulation task in which locomotion and arousal are intrinsic to the behavioral response. In both cases, explicit behavioral modeling recovers neural response patterns that more closely resemble low-motion reference conditions than blind, model-free denoising approaches. Critically, during noxious stimulation, behavior-informed modeling preserves shock-intensity-dependent activity in the primary somatosensory cortex that is attenuated by global component removal. These findings demonstrate that explicit modeling of behavior enables reliable interpretation of brain-wide fUSI signals during naturalistic, high-motion conditions, opening the door to studying affective and cognitive processes that were previously difficult to access with functional ultrasound imaging.

neuroscience↗

bioRxiv2023

Leukemia in Sprague-Dawley Rats Exposed Long-term from Prenatal Life to Glyphosate and Glyphosate-Based Herbicides

BackgroundGlyphosate-based herbicides (GBHs) are the worlds most widely used weed control agents. There has been intense and increasing public health concern about glyphosate and GBHs since the International Agency for Research on Cancer classified glyphosate as a probable human carcinogen in 2015. AimsTo further study the health effects of glyphosate and GBHs, the Ramazzini Institute, in collaboration with an international network of institutes and universities, has launched the Global Glyphosate Study (GGS), the most comprehensive toxicological study ever performed on these compounds. The GGS is an integrated study designed to test a wide range of toxicological outcomes including carcinogenicity, neurotoxicity, multi-generational effects, organ toxicity, endocrine disruption and prenatal developmental toxicity. The present study reports the first definitive results on leukemia incidence and mortality from the carcinogenicity arm of the GGS. MethodGlyphosate and two GBHs, Roundup Bioflow (MON 52276) used in the European Union (EU) and RangerPro (EPA 524-517) used in the U.S., were administered long-term to Sprague-Dawley (SD) rats beginning in prenatal life until 104 weeks of age via drinking water at doses of 0.5, 5, and 50 mg/kg body weight/day. This dose range encompasses both the EU Acceptable Daily Intake (ADI) and the EU No Observed Adverse Effect Level (NOAEL) for glyphosate. Each experimental group was composed of 51 males and 51 females, the total number animals were 1020 (510 males and 510 females). ResultsIn the animals exposed to glyphosate, a significantly increased trend in incidence of lymphoblastic leukemia was observed in males. In the Roundup Bioflow-treated animals, significantly increased trends were observed in incidence of lymphoblastic leukemia (males and females), monocytic leukemia (males), total myeloid leukemia (males), and all leukemias combined (males and females). In the RangerPro-treated animals, significantly increased trends were observed in incidence of lymphoblastic leukemia (males and females), monocytic leukemia (males) and all leukemias combined (males). 43% of leukemias deaths in the glyphosate and GBHs treated groups occurred before the first year of age (52 weeks). ConclusionsGlyphosate and GBHs at exposure levels corresponding to the EU ADI and the EU NOAEL caused significant, dose-related increased trends in incidence of leukemia, a very rare malignancy, in SD rats. Notably, about half of the leukemia deaths seen in the glyphosate and GBH groups occurred at less than one year of age, comparable to less than 35-40 years of age in humans.

pharmacology and toxicology↗

bioRxiv2021

Depth-resolved intersubject functional correlation of 7T BOLD signals reveals increased stimulus related information sharing across deep layers in premotor and parietal nodes for predictable actions

While the brain regions involved in action observation are relatively well documented in humans and primates, how these regions communicate to help understand and predict actions remains poorly understood. Traditional views emphasized a feed-forward architecture in which visual features are organized into increasingly complex representations that feed onto motor programs in parietal and then premotor cortices where the matching of observed actions upon the observers own motor programs contributes to action understanding. Predictive coding models place less emphasis on feed-forward connections and propose that feed-back connections from premotor regions back to parietal and visual neurons represent predictions about upcoming actions that can supersede visual inputs when actions become predictable, with visual input then merely representing prediction errors. Here we leverage the notion that feed-back connections target specific cortical layers to help adjudicate across these views. Specifically, we test whether observing sequences of hand actions in their natural order, which permits participants to predict upcoming actions, triggers more feed-back input to parietal regions than seeing the same actions in a scrambled sequence that hinders making predictions. Using submillimeter fMRI acquisition at 7T, we find that watching predictable sequences triggers more action-related activity (as measured using intersubject functional correlation) in the parietal cortical area PFt at depths receiving feed-back connections (layers III and V/VI) than watching the exact same actions in scrambled and hence unpredictable sequence. In addition, functional connectivity analysis performed using intersubject functional connectivity confirms that these increased action-related signals in PFt could originate from ventral premotor region BA44. This data showcases the utility of intersubject functional correlation in combination with 7T MRI to explore the architecture of social cognition under more naturalistic conditions, and provides evidence for models that emphasize the importance of feed-back connections in action prediction.

neuroscience↗

bioRxiv2020

Significance tests for Leave-One-Out Inter-Subject Correlations in fMRI

The inter-subject correlation (ISC) of fMRI data of different subjects performing the same task is a powerful way to localize and differentiate neural processes caused by a stimulus from those that spontaneously or idiosyncratically take place in each subject. The wider adoption of this method has however been impeded by the lack of widely available tools to assess the significance of the observed correlations. Several non-parametric approaches have been proposed, but these approaches are computationally intensive, challenging to implement, and sensitive methods to correct for multiple comparison across voxels are not yet well established. More widely available, and computationally simple, parametric methods have been criticized theoretically on the basis that dependencies in the data could inflate false positives. Here, we therefore endeavored to assess the actual performance of parametric tests on leave-one-out ISC values in two ways. First, we assess whether parametric tests protect against Type I error by assessing how often they find significant clusters of synchronized activity in publicly available datasets, in which such synchronization should not occur. This includes three resting state datasets, and one dataset in which participants did view movies, but where we randomly select segments that were not taken at the same time in the same movie. Contrary to what has been suspected, we find that parametric tests with corrections for multiple comparisons do protect appropriately against Type I error in that data. This was true for FDR correction at the voxel level at q < 0.05, with a minimum cluster-size of k = 20 voxels, FWE correction at the voxel level at < 0.05, with a minimum cluster-size of k = 5, and for correction at the cluster-level with punc < 0.001 with k = max(20, FWEc). Second, we assessed how these parametric tests compare with non-parametric methods when it comes to detecting ISC when participants actually did watch the same movies. We used a dataset including 150 participants viewing two movies, and used a bootstrapping thresholding of the ISC in the entire dataset to outline our best guess of the network of brain regions that truly synchronize while viewing the movies. We then drew subsamples of between 10 and 50 participants from the entire dataset, calculated the ISC, and thresholded it using our candidate methods. We find that FDR thresholding with k = 20 in particular, was substantially more sensitive than bootstrapping methods in detecting this network even in smallish samples of N = 20 participants typical of cognitive neuroscience studies, while at the same time retaining appropriate specificity. Because the parametric tests we show to perform well are more readily available to the neuroscience community than the non-parametric tests previously championed, we trust that this finding paves the way to a wider adoption of ISC, and empowers a wider range of neuroimagers to use ISC to tackle the challenges of naturalistic neuroscience. In particular in the context of often limited sample sizes and modest effect sizes in cognitive neuroscience, we trust that using FDR correction in particular will help neuroimagers identify the contribution of higher brain regions that process stimuli in more loosely timed fashions, more effectively than non-parametric alternatives.

neuroscience↗

bioRxiv2020

Neuro-computational mechanisms of action-outcome learning under moral conflict

Predicting how actions result in conflicting outcomes for self and others is essential for social functioning. We tested whether Reinforcement Learning Theory captures how participants learn to choose between symbols that define a moral conflict between financial self-gain and other-pain. We tested whether choices are better explained by model-free learning (decisions based on combined historical values of past outcomes), or model-based learning (decisions based on the current value of separately expected outcomes) by including trials in which participants know that either self-gain or other-pain will not be delivered. Some participants favored options benefiting themselves, others, preventing other-pain. When removing the favored outcome, participants instantly altered their choices, suggesting model-based learning. Computational modelling confirmed choices were best described by model-based learning in which participants track expected values of self-gain and other-pain separately, with an individual valuation parameter capturing their relative weight. This valuation parameter predicted costly helping in an independent task. The expectations of self-gain and other-pain were also biased: the favoured outcome was associated with more differentiated symbol-outcome probability reports than the less favoured outcome. FMRI helped localize this bias: signals in the pain-observation network covaried with pain prediction errors without linear dependency on individual preferences, while the ventromedial prefrontal cortex contained separable signals covarying with pain prediction errors in ways that did and did not reflected individual preferences.

neuroscience↗

bioRxiv2019

Frataxin deficiency induces lipid accumulation and affects thermogenesis in brown adipose tissue

Decreased expression of the mitochondrial protein frataxin (FXN) causes Friedreichs ataxia (FRDA). FRDA is a neurodegenerative disease also characterized by systemic metabolic alterations that increase the risk of developing type 2 diabetes thus aggravating FRDA prognosis. Brown adipose tissue (BAT) is a mitochondria-enriched and anti-diabetic tissue that, in addition to its thermoregulatory role, turns excess energy into heat to maintain energy balance. Here we report that the FXN knock-in/knock-out (KIKO) mouse shows reduced energy expenditure and VO2, hyperlipidemia, decreased insulin sensitivity and enhanced circulating levels of leptin, recapitulating diabetes-like signatures. FXN deficiency leads to alteration of mitochondrial structure and oxygen consumption, decreased lipolysis and lipid accumulation in BAT. Transcriptomic data highlighted a blunted thermogenesis response, as several biological processes related to thermogenesis (e.g. response to temperature stimuli, mitochondrial gene transcription, triglyceride metabolism, adipogenesis) resulted affected in BAT of KIKO mice upon cold exposure. Decreased adaptation to cool temperature in association with limited PKA-mediated lipolysis and downregulation of the expression of the genes controlling mitochondrial metabolism and lipid catabolism were observed in KIKO mice. T37i brown adipocytes and primary adipocytes with FXN deficiency showed reduced thermogenesis and adipogenesis markers respectively recapitulating the molecular signatures detected in KIKO mice.\n\nCollectively our data point to BAT dysfunction in FRDA and suggest BAT as a promising target to overcome metabolic complications in FRDA.

pathology↗