Biology subjects

Greco, A.

Publications and source records attributed to Greco, A..

At least 19 recordsLinked to original sources

bioRxiv2026

FALCON: Closed-Loop Multi-Objective Optimization of Lipid Nanoparticles for Cell-Selective mRNA Delivery

Efficient, cell type-selective delivery of genetic payloads remains a central challenge in the development of gene and cell therapies. Lipid nanoparticles (LNPs) offer a versatile delivery platform, but their optimization is hindered by reliance on brute-force screening methods that are laborious, resource-intensive, and focus on single targets. Here, we present FALCON (Framework for Active Learning-driven Compositional Optimization of Nanoparticles), a closed-loop pipeline that leverages iterative screening, surrogate modeling, and multi-objective optimization to accelerate LNP compositional design. In B cell-targeted validation experiments, FALCON-optimized LNPs achieved a 1.8-fold increase in splenic B cell transfection in vivo compared with reference compositions. When optimized for selectivity, FALCON LNPs displayed an 84-fold improvement in selective transfection of splenic B cells over off-target liver populations and enabled spleen-tropic behavior across factorial panels of varying ionizable and helper lipid chemistries. In vaccine studies, these LNPs induced higher IgG2c antibody titers and a more Th1-biased immune profile. FALCON was also deployed to optimize LNPs for myeloid cell-selective delivery, achieving enhanced in vivo selectivity following systemic administration both across and within spleen and liver compartments. Our results establish FALCON as a useful tool for data-driven design of LNP compositions for precision gene delivery.

bioengineering↗

bioRxiv2026

Brain-wide distributed processing underlying natural vision and audition

A key challenge in neuroscience is understanding how large-scale brain dynamics give rise to perception under naturalistic conditions. Here we address this question using multivariate information decomposition of functional interactions between brain regions while typically developed, congenitally blind and congenitally deaf participants experienced audiovisual, auditory-only or visual-only versions of the same narrative. This approach allowed us to resolve information dynamics into redundant components, indexing shared information and sensory robustness, and synergistic components, indexing distributed processing that emerges only through joint interactions between brain regions. Redundant interactions were closely aligned with conventional functional connectivity and captured sensory modality- and experience-dependent differences mainly within sensory systems, whereas synergistic interactions captured these differences across high-level cortical areas. Crucially, prefrontal cortex coordinated brain dynamics through synergistic interactions independently of sensory modality and previous sensory experience, consistent with a modality-independent hub that encodes high-level semantic information and orchestrates the demands of naturalistic perception. Moreover, multimodal perception elicited the strongest high-order synergistic interactions across distributed brain subsystems, followed by unimodal visual and auditory perception, whereas sensory deprivation reduced this distributed architecture. Finally, synergistic and redundant interactions jointly supported the encoding of low-level sensory and high-level perceptual features, revealing how the trade-off between sensory robustness and distributed processing is organized across the human brain. Together, these results reveal a brain-wide information architecture for natural vision and audition, illuminating how distributed processing in the human brain supports rich perceptual experience.

neuroscience↗

bioRxiv2026

The volatile fatty-acid fingerprint of human fear

Human axillary odour can convey information about emotional state, but the molecular composition of fear related volatile emissions remains undefined. Here, we combine low background dual chamber axillary sampling, synchronous real time and offline mass spectrometry, chemical domain group independent component analysis and hierarchical Bayesian modelling to identify a molecular finger-print of acute fear during immersive virtual reality fear induction. In 37 healthy adults, this framework recovered five axillary volatile components associated with a continuous physiology derived fear index. The fingerprint comprised increased emissions of acetic, butyric, caproic and caprylic acids, octanal and acetone, together with decreased sulcatone, decanal, geranylacetone and citraconic anhydride. This coordinated pattern was reproducible across individuals and emerged from unsupervised chemical decomposition followed by regularised Bayesian selection, without prior biochemical constraints. Posterior predictive checks and leave one participant out refitting supported its robustness within the cohort. Its composition and directionality are consistent with sympathetic autonomic metabolic mobilisation, suggesting contributions from fatty acid handling, acetone related metabolism and axillary gland output. These findings define a candidate molecular cue of acute human fear and establish a replicable methodological template for decoding the chemical language of human emotion.

neuroscience↗

bioRxiv2026

The Onset of Myeloid Differentiation in Hematopoietic Progenitors In Vivo is Coordinated with S-phase Progression

Hematopoiesis produces diverse cell types in large quantities. How hematopoietic stem cells (HSCs) initiate lineage differentiation in vivo is not known. Here, we jointly measure chromatin accessibility and transcriptomes in single stem and progenitor cells and uncover a tight interplay between cell-cycle progression and the onset of differentiation. The cell cycle continuously accelerates as HSCs transition to uncommitted multipotent progenitors. In these uncommitted progenitors, proliferative activation is followed by the opening of myeloid-specific chromatin loci in S phase and, subsequently, myeloid gene expression. S phase-coupled onset of myeloid differentiation becomes quantitatively enhanced in emergency myelopoiesis. At the molecular level, we find that chromatin occupancy by HOXA9 - a key transcription factor of uncommitted progenitors - predicts whether the transition through S phase will initiate myelopoiesis, or whether the uncommitted progenitor state will be retained. Taken together, our findings provide a mechanistic framework for the onset of myeloid lineage differentiation in vivo.

systems biology↗

bioRxiv2025

Portable quantum-sensor magnetomyography decodes fine hand movements

Optically pumped magnetometers (OPMs) are compact quantum sensors that can measure the magnetic fields generated by muscle activity (magnetomyography, MMG) without skin contact. This contact-free alternative to surface electromyography (EMG) has remained mostly confined to magnetically shielded rooms and simple tasks, limiting translation. Here, we show that a portable OPM-MMG system operated inside a compact magnetic shield can robustly decode fine finger movements and recover EMG-like muscle activation patterns. Eight participants executed flexion-extension combinations spanning 15 finger actions while we recorded triaxial MMG and bipolar EMG concurrently. MMG supported robust multi-class and finger-specific decoding, recovering a representational geometry that closely matched EMG. Orientation analyses showed that components orthogonal to the muscle axis contributed most significantly to discriminability, providing actionable guidance for OPM array design. Our results show that OPM-MMG in a portable shielded environment preserves task-relevant neuromuscular information and approaches EMG-level structure without skin contact or a magnetically shielded room. Our findings open a path toward hygienic, rapid-setup assessment and human-machine interfacing in clinics and rehabilitation settings.

neuroscience↗

bioRxiv2025

Analytical meditation improves physiological well-being in expert practitioners: a study on central and peripheral neurophysiological correlates

Meditation has been long associated with improvements in mental well-being, emotional regulation, and attentional control. Yet, the diversity of meditative techniques and participant expertise has hindered the systematic identification of their neurophysiological correlates supporting these benefits. To address this challenge, we investigated the neurophysiological signatures of concentrative and analytical meditation in 35 experienced Tibetan monk practitioners. EEG, ECG, EDA, and respiration were simultaneously recorded during Concentrative, Loving-Kindness and Emptiness meditations. Linear-mixed-models revealed significant modulations in autonomic and cortical activity across meditations. Peripheral indices indicated enhanced parasympathetic tone, decreases respiratory rate, and gradual increase in EDA - reflecting a state of relaxed-alertness with concurrent vagal engagement and sustained sympathetic arousal. EEG analyses supported this state showing elevated gamma-band power during analytical meditations. These findings suggest that advanced meditative states foster an adaptive integration of autonomic and cortical responses, supporting the emergence of relaxed-vigilance - a psychophysiological condition associated with well-being and cognitive flexibility.

neuroscience↗

bioRxiv2025

Robust spatial hearing beyond primary interaural cues in humans over deep neural networks

Spatial hearing allows humans to localize sound sources in the azimuth plane using interaural time (ITD) and level (ILD) differences, but the contribution of additional auditory features remains unclear. To investigate this, we measured human localization performance with natural and artificial stimuli that selectively included or excluded ITD and ILD as primary interaural cues. As expected, human listeners relied synergistically on ITD and ILD for accurate azimuth localization. Moreover, even when both primary cues were absent, localization performance remained above chance level. We compared human performance with state-of-the-art deep neural networks (DNN) optimized for sound localization to investigate possible computational mechanisms underlying this robust performance. In contrast to humans, DNNs demonstrated high accuracy only for stimuli that resembled their training regime but failed when primary interaural cues were absent. This human-DNN misalignment highlights a fundamental distinction in sensory processing strategies, potentially arising from the simplicity bias inherent in DNN training, with human reliance on a wider range of auditory features likely reflecting evolutionary pressures favoring adaptability across diverse acoustic environments. Together, our results demonstrate the robustness of human spatial hearing beyond primary interaural cues and point to promising directions for advancing artificial systems and informing clinical applications, such as cochlear implants and auditory prosthetics.

animal behavior and cognition↗

bioRxiv2025

Frontocentral brain networks amplify action-oriented temporal prediction errors

Successful sensorimotor behavior depends on anticipating when a tactile event will occur and translating it into rapid action, yet it remains unclear how action requirements shape temporal prediction in the human cortex. Here, we combined Magnetoencephalography (MEG), multivariate decoding and computational modeling to contrast temporally jittered finger stimulations under passive versus action-oriented conditions. We characterized a distributed frontal sensorimotor network that was linked to fast tactile-motor associations and predicted reaction-time variability. We found that trial-by-trial deviations from expected stimulus timing modulated behavior, with stronger frontocentral prediction-error encoding when an overt response was required. Temporal prediction errors were primarily encoded in a motor rather than sensory reference frame. These results reveal that action demands dynamically amplify temporal error signaling in sensorimotor circuits, in line with predictive coding frameworks postulating that the brain preferentially encodes task-relevant and goal-directed sensory prediction errors.

neuroscience↗

bioRxiv2025

Shared and modality-specific brain networks underlying predictive coding of temporal sequences

Predictive coding posits that the brain continuously generates and updates internal models to anticipate incoming sensory input. While auditory and visual modalities have been studied independently in this context, direct comparisons using matched paradigms are scarce. Here, we employed magnetoencephalography (MEG) to investigate how the brain of 83 participants encodes and consciously recognises temporally unfolding sequences that acquire Gestalt-like structure over time, a feature rarely addressed in cross-modal research. Participants memorised matched auditory and visual sequences with coherent temporal structure and later identified whether test sequences were familiar or novel. Multivariate decoding revealed robust discrimination between the brain mechanisms underlying encoding and recognition of memorised and novel sequences, with sustained temporal generalisation in the auditory domain and time-specific responses in the visual domain. Using the BROAD-NESS pipeline, we identified modality-specific and supramodal brain networks. Auditory memory engaged auditory cortex, cingulate gyrus, and hippocampus, whereas visual memory involved orbitofrontal cortex and visual areas. Notably, both modalities recruited a shared network including hippocampus and medial cingulate during recognition. These findings provide compelling evidence for distinct and shared predictive learning mechanisms across sensory systems, advancing our understanding of how the brain integrates and evaluates temporally structured, Gestalt-like information.

neuroscience↗

bioRxiv2025

Neural signatures of predictive coding underlying the acquisition of incidental sensory associations

A longstanding question in cognitive science is whether the human brain learns sensory regularities that are irrelevant to ongoing behavior, a phenomenon known as incidental associative learning. Here, we provide evidence at the single subject level that humans indeed acquired such incidental associations and reveal their neural signatures by combining Electroencephalography (EEG), multivariate decoding and computational modeling. We found robust encoding of incidental predictions and prediction errors underlying associative learning, consistent with predictive coding theories. Prediction errors were modulated by epistemic uncertainty, incidental associations persisted in memory over days and generalized beyond stimulus-stimulus pairings to encompass broader sensory events, including the absence of stimulation. Together, our results challenge traditional assumptions that associative learning requires behavioral relevance or physical co-occurrence and point to uncertainty minimization about environmental state transitions as a general objective of brain function. This intrinsic drive may reflect a fundamental computational principle supporting the formation of internal predictive models that guide perception, learning, and adaptive behavior.

neuroscience↗

bioRxiv2024

Immersive exposure to simulated visual hallucinations modulates high-level human cognition

Understanding altered states of consciousness induced by psychedelic drugs is crucial for advancing our knowledge of conscious perception and developing clinical applications for psychiatric conditions. Recently, technological advances in virtual reality (VR) headsets and deep neural network for generative computer vision have enabled the controlled, immersive simulation of visual hallucinations. Although there is some evidence that simulated visual hallucinations increase cognitive flexibility, comprehensive experimental data on how this artificially altered perceptual phenomenology affects high-level human cognition is lacking. We addressed this gap by measuring a wide range of behavioral tasks in human participants after the exposure to VR immersive panoramic (360{degrees}) videos and their psychedelic counterparts generated by the DeepDream algorithm. Participants exhibited reduced task-switching costs after simulated psychedelic exposure compared to naturalistic exposure when instructed to invert the stimulus-response mapping, consistent with increased cognitive flexibility. No significant differences were observed between naturalistic and simulated psychedelic exposure in linguistic association tasks at word and sentence levels. Crucially, we found that visually grounded high-level cognitive processes were modulated by exposure to simulated hallucinations, as evidenced by participants drawing performance. These findings reveal how altering perceptual phenomenology through simulated visual hallucinations significantly modulates high-level human cognition. Our results provide insights into the interdependence of bottom-up and top-down cognitive processes and encourage further investigation into the effects of artificial psychedelic experiences on human cognition. This research may offer valuable insights into altered states of consciousness without pharmacological intervention, potentially informing both basic neuroscience and clinical applications.

animal behavior and cognition↗

bioRxiv2024

Neural dynamics of semantic control underlying generative storytelling

Storytelling has been pivotal for the transmission of knowledge and cultural norms across human history. A crucial process underlying the generation of narratives is the exertion of cognitive control on the semantic representations stored in memory, a phenomenon referred as semantic control. Despite the extensive literature investigating the neural mechanisms of semantic control in generative language tasks, little effort has been done towards storytelling under naturalistic conditions. Here, we probed human participants to generate stories in response to a set of instructions which triggered a narrative that was either appropriate (ordinary), novel (random), or balanced (creative), while recording functional magnetic resonance imaging (fMRI) signal. By leveraging deep language models, we demonstrated how participants ideally balanced the level of semantic control during story generation. At the neural level, creative stories were differentiated by a multivariate pattern of neural activity in frontal cortices compared to ordinary ones and in fronto-temporo-parietal cortices with respect to randomly generated stories. Crucially, similar brain regions were also encoding the features that distinguished the stories behaviourally. Moreover, we decomposed the neural dynamics into connectome harmonic modes and found specific spatial frequency patterns underlying the modulation of semantic control during story generation. Finally, we found different functional coupling within and between the default mode, salience and control networks when contrasting creative stories with their controls. Together, our findings highlight the neural mechanisms underlying the regulation of semantic exploration during narrative ideation and contribute to a deeper understanding of the neural dynamics underpinning the role of semantic control in generative storytelling.

neuroscience↗

bioRxiv2024

Predictive learning shapes the representational geometry of the human brain

Predictive coding theories propose that the brain constantly updates its internal models of the world to minimize prediction errors and optimize sensory processing. However, the neural mechanisms that link the encoding of prediction errors and optimization of sensory representations remain unclear. Here, we provide direct evidence how predictive learning shapes the representational geometry of the human brain. We recorded magnetoencephalography (MEG) in human participants listening to acoustic sequences with different levels of regularity. Representational similarity analysis revealed how, through learning, the brain aligned its representational geometry to match the statistical structure of the sensory inputs, by clustering the representations of temporally contiguous and predictable stimuli. Crucially, we found that in sensory areas the magnitude of the representational shift correlated with the encoding strength of prediction errors. Furthermore, using partial information decomposition we found that, prediction errors were processed by a synergistic network of high-level associative and sensory areas. Importantly, the strength of synergistic encoding of precition errors predicted the magnitude of representational alignment during learning. Our findings provide evidence that large-scale neural interactions engaged in predictive processing modulate the representational content of sensory areas, which may enhance the efficiency of perceptual processing in response to the statistical regularities of the environment.

neuroscience↗

bioRxiv2024

Statistical learning of incidental perceptual regularities induces sensory conditioned cortical responses

Statistical learning of sensory patterns can lead to predictive neural processes enhancing stimulus perception and enabling fast deviancy detection. Predictive processes have been extensively demonstrated when environmental statistical regularities are relevant to task execution. Preliminary evidence indicates that statistical learning can even occur independently of task relevance and top-down attention, although the temporal profile and neural mechanisms underlying sensory predictions and error signals induced by statistical learning of incidental sensory regularities remain unclear. In our study, we adopted an implicit sensory conditioning paradigm that elicited the generation of specific perceptual priors in relation to task-irrelevant audio-visual associations, while recording Electroencephalography (EEG). Our results showed that learning of non-relevant but statistically interrelated neutral audio-visual stimuli resulted in early neural responses to predictive auditory stimuli conveying anticipatory signals of expected visual stimulus presence or absence, and in specific modulation of cortical responses to probabilistic visual stimulus presentation or omission. Pattern similarity analysis indicated that predictive auditory stimuli tended to resemble the response to expected visual stimulus presence or absence. Remarkably, Hierarchical Gaussian filter modeling estimating dynamic changes of prediction error signals in relation to differential probabilistic occurrences of audio-visual stimuli further demonstrated instantiation of predictive neural signals by showing distinct neural processing of prediction error in relation to violation of expected visual stimulus presence or absence. Overall, our findings indicated that statistical learning of non-salient and task-irrelevant perceptual regularities can induce the generation of neural priors at the time of predictive stimulus presentation, possibly conveying sensory-specific information of the predicted consecutive stimulus.

neuroscience↗

bioRxiv2023

Structural adaptability and surface activity oftardigrade-inspired peptides

Tardigrades are unique micro-animals that withstand harsh conditions, such as extreme temperatures and desiccation. Recently, it was found that specific cytoprotective proteins are essential for ensuring this high environmental tolerance. In particular, cytoplasmic abundant heat soluble (CAHS) proteins, which are intrinsically disordered, adopt more ordered conformations upon desiccation, and are involved in the vitrification of the cytoplasm. The design and synthesis short peptides capable of mimicking the structural behavior (and thus the cytoprotective properties) of CAHS proteins would be beneficial for potential biomedical applications, including the development of novel heat-resistant preservatives for sensitive drug formulations. As a first step in this direction, we selected several model peptides of varying lengths derived from the conserved CAHS motifs 1 and 2, which are part of the intrinsically disordered CAHS-c2 region. We then studied their structures using circular dichroism and linear and two-dimensional infrared spectroscopy in the presence of the desolvating agent TFE (2,2,2-trifluoroethanol), which mimics desiccation. We found that the CAHS model peptides are mostly disordered at 0% TFE (a result that we confirmed by molecular dynamics simulations), but adopt a more -helical structure upon the addition of the desolvating agent, similar to what is observed for full CAHS proteins. Additionally, we employed sum frequency generation to investigate the surface activity of the peptides at the air/water interface to mimic a partial dehydration effect. Interestingly, all model peptides are surface active and also adopt a helical structure at the air/water interface. Thus, the selected sequences represent promising model peptides that show similarities in the physicochemical behavior to full CAHS proteins. Our results also suggest that arginine might be a crucial element in defining the strong propensity of these peptides to adopt a helical structure. In the future, the use CAHS model peptides to design new synthetic peptide-based materials could make it possible to mimic and exploit the cytoprotective properties of naturally occurring tardigrade proteins. SIGNIFICANCETardigrades are micro-animals that can survive extreme conditions such as desiccation and high temperatures. Recent work has shown that this capability is related to the presence of specific proteins that can remodel in order to protect the organisms cells. Mimicking this behavior using small peptides that preserve the structural properties of the full proteins is highly desirable in potential biomedical applications, such as the storage of heat-sensitive drugs. Here, we study the structural properties of model peptides derived from the conserved region of cytoplastic tardigrade proteins, and show that these peptides preserve some of the conformational behavior of the full protein under drying conditions. These peptides can therefore be used as a starting point for the design of synthetic model systems based on tardigrade-inspired peptides for tailored applications.

biochemistry↗

bioRxiv2023

Discrimination of finger movements by magnetomyography with optically pumped magnetometers

Optically pumped magnetometers (OPM) are quantum sensors that offer new possibilities to measure biomagnetic signals. In magnetomyography (MMG), compared to the current standard surface electromyography (EMG), OPM sensors offer the advantage of contactless measurements of muscle activity. However, little is known about the relative performance of OPM-MMG and EMG, e.g. in their ability to detect and classify finger movements. To address this, we recorded simultaneous OPM-MMG and EMG of finger flexor muscles for the discrimination of individual finger movements. Using a deep learning model for movement classification, we found that both sensor modalities were able to discriminate finger movements with above 89% accuracy. Furthermore, model predictions for the two sensor modalities showed high agreement in movement detection (85% agreement; Cohens kappa: 0.45). Our findings show that OPM sensors can be employed for reliable, contactless discrimination of finger movements and incentivize future applications of OPM in magnetomyography.

neuroscience↗

bioRxiv2021

Simulated visual hallucinations in virtual reality enhance cognitive flexibility

Historically, psychedelic drugs are known to modulate cognitive flexibility, a central aspect of cognition permitting adaptation to changing environmental demands. Despite proof suggesting phenomenological similarities between artificially-induced and actual psychedelic altered perception, experimental evidence is still lacking about whether the former is also able to modulate cognitive flexibility. To address this, we measure participants cognitive flexibility through behavioral tasks after the exposure to virtual reality panoramic videos and their hallucinatory-like counterparts generated by the DeepDream algorithm. Results show that the estimated semantic network has a flexible structure when preceded by altered videos. Crucially, following the simulated psychedelic exposure, individuals also show an attenuated contribution of the automatic process and chaotic dynamics underlying the decision process. This suggests that simulated altered perceptual phenomenology enhances cognitive flexibility, presumably due to a reorganization in the cognitive dynamics that facilitates the exploration of uncommon decision strategies and inhibits automated choices.

animal behavior and cognition↗

bioRxiv2020

Hematopoietic lineages diverge within the stem cell compartment

Hematopoietic stem cells (HSCs) produce a highly diverse array of cell lineages. To assay hematopoietic differentiation with minimal experimental perturbation, non-invasive methods for heritable labeling1-3 or barcoding4-7 of HSCs in vivo have recently been developed and used to study lineage fate of HSCs in physiological conditions. However, the differentiation pathways leading from HSCs to mature cells remain controversial8, with suggested models ranging from gradual lineage restriction in a branching cascade of progenitors to HSCs already making ultimate lineage decisions. Here we show, by iterating HSC fate-mapping, mitotic history tracking, single-cell RNA-sequencing and computational inference, that the major differentiation routes to megakaryocytes, erythro-myeloid cells and lymphocytes split within HSCs. We identify the hitherto elusive self-renewing source of physiological hematopoiesis as an HSC subpopulation co-expressing high levels of Sca-1 and CD201. Downstream, HSCs reduce Sca-1 expression and enter into either thrombopoiesis or erythro-myelopoiesis, or retain high Sca-1 levels and the ability to generate lymphocytes. Moreover, we show that a distinct population of CD48-/lo megakaryocyte progenitors links HSCs to megakaryocytes. This direct thrombopoiesis pathway is independent of the classical pathway of megakaryocyte differentiation via multipotent progenitors and becomes the dominant platelet production line upon enhanced thrombopoietin signaling. Our results define a hierarchy of self-renewal and lineage decisions within HSCs in native hematopoiesis. Methodologically, we provide a blueprint for mapping physiological differentiation pathways of stem cells and probing their regulation.

systems biology↗