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Grasso, C.

Publications and source records attributed to Grasso, C..

8 recordsLinked to original sources

Identification of brain-like functional information architectures in embryonic tissue of Xenopus laevis.

Understanding how populations of cells collectively coordinate activity to produce the complex structures and behaviors that characterize multicellular organisms, and which coordinated activities, if any, survive processes that reshape cells and tissues into organoids, are fundamental issues in modern biology. Here we show how techniques from complex systems and multivariate information theory provide a framework for inferring the structure of collective organization in non-neural tissue. Many of these techniques were developed in the context of theoretical neuroscience, where these statistics have been found to be altered during different cognitive, clinical, or behavioral states, and are generally thought to be informative about the underlying dynamics linking biology to cognition. Here we show that these same patterns of coordinated activity are also present in the aneural tissues of evolutionarily distant biological systems: preparations of embryonic Xeno-pus laevis tissue (known as "basal Xenobots"). These similarities suggest that such patterns of activity either arose independently in these two systems (epithelial constructs and brains); are epiphenomenological byproducts of other dynamics conserved across vastly different configurations of life; or somehow directly support adaptive behavior across diverse living systems. Finally, these results provide unambiguous support for the hypothesis that, despite their apparent simplicity as collections of non-neural epithelial cells, Xenobots are in fact integrated, complex systems in their own right, with sophisticated internal information structures.

systems biology↗

Stimulus history, not expectation, drives sensory prediction errors in mammalian cortex

Hierarchical predictive coding (HPC) models have recently flourished in neuroscience1-9. Feedforward and feedback processing are at the heart of HPC models. Previous experimental studies using fMRI, EEG/MEG, and LFP9-11 do not reliably resolve feedback modulation from local computations and feedforward outputs. Here, using open-science8, multi-species, multi-area, high-density12, laminar neurophysiology13, we empirically test whether hierarchical predictive coding is a key component shaping cortical processing of visual stimuli. To isolate visual information processing and eliminate motor/reward confounders9-11, we use a no-report task. Our task leveraged so-called global oddballs (GO) as unpredictable, deviant stimuli that circumvent low-level adaptation. We examined their responses relative to local oddballs (LO) that we habituated into highly predictable priors. Four surprising findings in this dataset challenge many existing hierarchical predictive coding models. First, GO responses were exclusive to higher-order, more cognitive areas rather than early-to-mid visual cortex. Second, inhibitory interneuron-targeted optogenetics in primates and mice and waveform shape analysis in primates revealed no evidence that predictive suppression was implemented via these interneurons. Third, highly predictable LO responses dominated in over 50% of all neurons, including in higher-order cortex, which should have anticipated them, indicating limited evidence for predictive suppression. Lastly, prediction error responses evoked by GOs did not evoke feedforward processing. These results reveal circuit dynamics that govern how prediction shapes visual processing, motivating more neurally constrained predictive processing models.

neuroscience↗

Revealing non-trivial information structures in aneural biological tissues via functional connectivity

A central challenge in the progression of a variety of open questions in biology, such as morphogenesis, wound healing, and development, is learning from empirical data how information is integrated to support tissue-level function and behavior. Information-theoretic approaches provide a quantitative framework for extracting patterns from data, but so far have been predominantly applied to neuronal systems at the tissue-level. Here, we demonstrate how time series of Ca2+ dynamics can be used to identify the structure and information dynamics of other biological tissues. To this end, we expressed the calcium reporter GCaMP6s in an organoid system of explanted amphibian epidermis derived from the African clawed frog Xenopus laevis, and imaged calcium activity pre- and post- a puncture injury, for six replicate organoids. We constructed functional connectivity networks by computing mutual information between cells from time series derived using medical imaging techniques to track intracellular Ca2+. We analyzed network properties including degree distribution, spatial embedding, and modular structure. We find organoid networks exhibit more connectivity than null models, with high degree hubs and mesoscale community structure with spatial clustering. Utilizing functional connectivity networks, we show the tissue retains non-random features after injury, displays long range correlations and structure, and non-trivial clustering that is not necessarily spatially dependent. Our results suggest increased integration after injury, possible cellular coordination in response to injury, and some type of generative structure of the anatomy. While we study Ca2+ in Xenopus epidermal cells, our computational approach and analyses highlight how methods developed to analyze functional connectivity in neuronal tissues can be generalized to any tissue and fluorescent signal type. Our framework therefore provides a bridge between neuroscience and more basal modes of information processing. Author summaryA central challenge in understanding several diverse processes in biology, including morphogenesis, wound healing, and development, is learning from empirical data how information is integrated to support tissue-level function and behavior. Significant progress in understanding information integration has occurred in neuroscience via the use of observable live calcium reporters throughout neural tissues. However, these same techniques have seen limited use in the non-neural tissues of multicellular organisms despite similarities in tissue communication. Here we utilize methods designed for neural tissues and modify them to work on any tissue type, demonstrating how non-neural tissues also contain non-random and potentially meaningful structures to be gleaned from information theoretic approaches. In the case of epidermal tissue derived from developing amphibians, we find non-trivial informational structure over greater spatial and temporal scales than those found in neural tissue. This hints at how more exploration into information structures within these tissue types could provide a deeper understanding into information processing within living systems beyond the nervous system.

systems biology↗

Senescence phenotype of lymph node stromal cells from patients with rheumatoid arthritis is partly restored by dasatinib treatment

ObjectiveCellular senescence is a state of proliferation arrest of cells occurring during aging. The persistence and accumulation of senescent cells has been implicated in the pathogenesis of age-related diseases like rheumatoid arthritis (RA). RA is a chronic autoimmune disease in which loss of immune tolerance and systemic autoimmunity precedes clinical onset of disease. Lymph node stromal cells (LNSCs) are important regulators of immune tolerance. Accordingly, accumulating senescent LNSCs may potentially lead to defective immune tolerance and the development of systemic autoimmune disease. MethodsHuman LNSCs were isolated and cultured from inguinal lymph node needle biopsies from individuals at risk of developing RA (RA-risk individuals), RA patients and seronegative healthy volunteers. Senescence hallmarks and the effect of dasatinib treatment were assessed using quantitative PCR, flow cytometry, microscopy and live-cell imaging. ResultsCell size, granularity and autofluorescence were significantly higher in RA LNSCs compared with control LNSCs. Stainings indicate more senescence associated {beta}-galactosidase activity, more lipofuscin positive granules and increased DNA damage in RA-risk and RA LNSCs compared with control LNSCs. Moreover, we found altered gene expression levels of senescence associated genes in LNSCs from RA patients. Strikingly, the capacity to repair irradiation induced DNA damage was significantly lower in RA-risk and RA LNSCs compared with control LNSCs. Treating LNSCs with dasatinib significantly improved cell size and DNA repair capacity of cultured LNSCs. ConclusionWe observed multiple senescent hallmarks in RA LNSCs and to lesser extent already in RA-risk LNSCs, which could partly be restored by dasatinib treatment. KEY MESSAGES What is already known on this topic?- Synovial fibroblasts from RA patients display a senescent phenotype and accumulate in inflamed synovial tissue. What does this study add?- Lymph node stromal cells (LNSCs) from RA patients, and to a lesser extent from RA-risk, display key hallmarks of senescence. - Both ex vivo and in vitro LNSCs from RA patients have an increased cell size compared with control LNSCs. - RA and RA-risk LNSCs have an impaired ability to repair DNA damage - Treating LNSCs with dasatinib significantly improved cell size and DNA repair capacity of LNSCs. How might this study impact on clinical practice or future developments?- These hallmarks of senescence in LNSCs may indicate premature aging and loss of function of the immunomodulatory lymph node stromal compartment during RA development. Dasatinib treatment of LNSCs shows that senolytics may be an effective preclinical drug to restore cell function early in disease.

cell biology↗

SHIELD: Skull-shaped hemispheric implants enabling large-scale-electrophysiology datasets in the mouse brain

To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. While new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe a novel 3D-printed cranial-replacement implant (SHIELD) enabling electrophysiological recordings from distributed areas of the mouse brain. This skull-shaped implant is designed with customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedures high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase the scientific utility of the SHIELD implant, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful large-scale electrophysiological measurements for the study of distributed brain computation.

neuroscience↗

Identification and mapping of human lymph node stromal cell subsets by combining single-cell RNA sequencing with spatial transcriptomics.

Lymph node stromal cells (LNSCs) have a crucial immunomodulatory function, but their heterogeneity in human is incompletely understood. Here, we report the single cell RNA sequencing (scRNA-seq) of 12000 LNSCs isolated from a human lymph node (LN). This study comprehensively defines the gene signatures of 10 fibroblast subtypes: CCL21+SC, CCL19+SC, CD34+CXCL14+SC, pericytes, DES+SC, LAMP5+SC, NR4A1+BCAM+ SC, HLA-DR+SC, SEPT4+SC and GLDN+SC. To explore the heterogeneous stromal compartment within the complex LN tissue architecture, we integrated the scRNA-seq profiles of the identified LNSC subsets with a publicly available human spatial transcriptomic LN dataset and predicted their location within the complex LN tissue architecture. Each LNSC subtype was spatially restricted to specific LN regions, indicating different LNSC-lymphocyte interactions which was further investigated using NicheNet. The positioning of distinct LNSC subtypes in different LN regions sets the stage for future research on the relationship between LNSC-specific niches and immunomodulatory function during health and disease.

cell biology↗

Recurrent pattern completion drives the neocortical representation of sensory inference

When sensory information is incomplete or ambiguous, the brain relies on prior expectations to infer perceptual objects. Despite the centrality of this process to perception, the neural mechanism of sensory inference is not known. Illusory contours (ICs) are key tools to study sensory inference because they contain edges or objects that are implied only by their spatial context. Using cellular resolution, mesoscale two-photon calcium imaging and multi-Neuropixels recordings in the mouse visual cortex, we identified a sparse subset of neurons in the primary visual cortex (V1) and higher visual areas that respond emergently to ICs. We found that these highly selective IC-encoders mediate the neural representation of IC inference. Strikingly, selective activation of these neurons using two-photon holographic optogenetics was sufficient to recreate IC representation in the rest of the V1 network, in the absence of any visual stimulus. This outlines a model in which primary sensory cortex facilitates sensory inference by selectively strengthening input patterns that match prior expectations through local, recurrent circuitry. Our data thus suggest a clear computational purpose for recurrence in the generation of holistic percepts under sensory ambiguity. More generally, selective reinforcement of top-down predictions by pattern-completing recurrent circuits in lower sensory cortices may constitute a key step in sensory inference.

neuroscience↗

Stimulus novelty uncovers coding diversity in visual cortical circuits

Detecting novel stimuli in the environment is critical for learning and survival, yet the neural basis of novelty processing is not understood. To characterize cell type-specific novelty processing, we surveyed the activity of [~]15,000 excitatory and inhibitory neurons in mice performing a visual task with novel and familiar stimuli. Clustering revealed a dozen functional neuron types defined by experience-dependent encoding. Vasoactive-intestinal-peptide (Vip) expressing inhibitory neurons were diverse, encoding novel stimuli, omissions of familiar stimuli, or behavioral features. Distinct Somatostatin (Sst) expressing inhibitory neurons encoded either familiar or novel stimuli. Subsets of excitatory neurons co-clustered with specific Vip or Sst subpopulations, while Sst and Vip inhibitory clusters were non-overlapping. This study establishes that novelty processing is mediated by diverse functional neuron types in the visual cortex.

neuroscience↗