Biology subjects

Vanello, N.

Publications and source records attributed to Vanello, N..

8 recordsLinked to original sources

bioRxiv2026

Learned Audiovisual Predictability Modulates Depth-Resolved Hippocampal-Cortical Functional Coupling

Perception reflects the dynamic integration of prior expectations, uncertainty, and incoming sensory evidence, but the neural circuitry supporting these computations remains debated. Current theories implicate coordinated interactions between the hippocampus and neocortex, potentially at the level of hippocampal subfields and cortical layers. Evidence in humans has come primarily from the visual domain, while less is known about how these interactions support learned auditory predictions. Using submillimetre 7T fMRI, we investigated depth-resolved functional coupling between hippocampal subfields and temporal and frontal cortical regions during audiovisual associative prediction. Participants learned deterministic associations between visual cues and auditory syllables, allowing us to compare auditory processing in predictable and unpredictable contexts. Predictability-related connectivity changes showed a spatially structured pattern involving DG/CA3-pSTG and CA1-inferior frontal regions, with significant edge-wise effects resolved across cortical depths. These findings provide fine-grained evidence that learned auditory predictability modulates hippocampal-cortical functional interactions across temporo-frontal systems.

neuroscience↗

bioRxiv2026

Longitudinal Characterization of a Novel Class of Recurrent, Stereotyped Neurophysiological Events in an Advanced Meditator

Seven EEG recordings over thirteen months revealed highly stereotyped transitions between distinct brain dynamics in an advanced meditator, providing a rare experimental window onto large-scale brain-state dynamics. We report an intensive longitudinal EEG case study of an experienced Tibetan tantric practitioner recorded across seven different measurement sessions, including concentrative and analytical meditation, three Dissolution of Elements sessions, nap, and reading sessions. Across conditions, the EEG repeatedly entered abrupt and reversible "ON" periods lasting tens of seconds. These periods were characterized by high-amplitude delta-theta activity, a structured 7-8 Hz component, fronto-central predominance, and a recurrent transient complex preceding state onset. Compared with matched pre- and post-event intervals, ON periods showed increased spectral power and directed connectivity, reduced relative variability, and high cross-session similarity, consistent with a recurrent and stereotyped macroscopic neurophysiological regime. Additional analyses did not support a straightforward explanation in terms of respiratory-rate changes, sleep-related variations, or overt movement artifacts. During Dissolution of Elements meditation event counts were consistent with the reported structure of the practice. However, given the current state of knowledge about the phenomenon, there is insufficient evidence to establish a close association with either the type of meditation session or the specific practices undertaken during the practitioners many years of retreat. We therefore distinguish the robust observation of a recurrent EEG regime from the more tentative hypothesis that it is related to advanced tantric meditative practice. What does appear to be well documented, however, is an unusual, abrupt, and reversible large-scale EEG reconfiguration in a deeply phenotyped expert volunteer, highlighting the value of intensive longitudinal single-participant designs for identifying and characterizing rare neurophysiological phenomena.

neuroscience↗

bioRxiv2026

Physiologically Informed PCA-Partial Correlation for highly Collinear Brainstem fMRI Networks

Functional connectivity (FC) approaches from resting-state fMRI (rs-fMRI) are amply spread to investigate the cortical organization, yet the brainstem remains relatively underexplored despite its pivotal roles in both physiological and pathological conditions. The highly collinear network, in which the strongly interconnected nodes and the widespread neuromodulatory influences induce indirect or mediated interactions, make the estimation of direct brainstem FC challenging. Standard bivariate methods fail to recover the true network structure in such complex topologies, causing false positive interactions. On the other hand, partial correlation can potentially estimate the direct FC, but multicollinearity issues and collider-induced spurious correlations limit its application in high-dimensional scenarios. Here, we propose a physiologically informed framework in which the conditioning strategy for partial correlation estimation is tailored for the investigation of the brainstem and its direct interactions within the network and with whole-brain regions. Specifically, we employed a PCA-regularized partial correlation (PCA - {rho}PC) approach, where PCA is applied to the brainstem covariates to mitigate multicollinearity and model shared modulatory variance. We show that PCA - {rho}PC improves the robustness and interpretability of brainstem FC, yielding sparser and more physiologically plausible connectomes compared with conventional (regularized) approaches. Both simulation and real fMRI data raise the possibility that Pearsons and PCA-regularized approaches may complement each other in an effort to unravel the pattern of direct vs. indirect effects in highly collinear settings, paving the way for future extensions in a wide range of multivariate neuroimaging applications.

bioengineering↗

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

Chemosensitive brainstem and diencephalic components in breath-hold fMRI

ObjectiveThe knowledge on breathing control and central chemoreception, key subcortical functions involved in several neuropathologies, is still mainly based on animal studies. In humans, functional MRI (fMRI) offers the needed spatio-temporal resolution and non-invasiveness, but the lack of specific tools and preprocessing solutions hinders its use in brainstem studies. We hereby propose an original fMRI analysis pipeline aimed at unravelling central chemoreception mechanisms, by integrating acquisition, spatial coregistration, noise removal and a novel data-driven analysis solution to compare network activation levels across tasks or conditions in fMRI. ApproachNovel analysis methodologies are integrated with the optimization of known preprocessing approaches to physiological noise correction and brainstem-focused coregistration. We couple independent components of fMRI data, separately estimated from healthy subjects during Free Breathing (FB) and Breath Hold (BH), by means of spatial correlation. We then identify statistically significant differences between BH and FB in CO2-dependent components by means of voxel-wise comparisons of components percent signal change. Components were localized using the Brainstem Navigator Atlas for enhancing network interpretability. Main ResultsUsing the pipeline we characterized CO2-related BOLD oscillations within the central control system of breathing. We corroborated the primary chemoreceptive role of medullary raphe in healthy subjects. We observed that BH over-activated ascending sensory-motor projections through the postero-lateral thalamus, descending projections through the putamen, and peripheral sensations entry points in the dorsal medulla. We highlighted the role of latero-dorsal tegmentum in the response to hypercapnia-induced aversive effects. SignificanceOur method allows to non-invasively locate primary chemoreception and related arousal triggers, characterizing alterations and therefore fostering the identification of therapeutic targets in abnormal breathing. Moreover, the proposed strategy addresses the issues of inter-task comparison among homologous independent sources, of their characterization and interpretation. Its extension could benefit all similarly challenging brainstem-focused studies, including those on Parkinsons and Alzheimers diseases.

bioengineering↗

bioRxiv2021

Functional connectome of brainstem nuclei involved in autonomic, limbic, pain and sensory processing in living humans from 7 Tesla resting state fMRI

Despite remarkable advances in mapping the functional connectivity of the cortex, the functional connectivity of subcortical regions is understudied in living humans. This is the case for brainstem nuclei that control vital processes, such as autonomic, limbic, nociceptive and sensory functions. This is because of the lack of precise brainstem nuclei localization, of adequate sensitivity and resolution in the deepest brain regions, as well as of optimized processing for the brainstem. To close the gap between the cortex and the brainstem, on 20 healthy subjects, we computed a correlation-based functional connectome of 15 brainstem nuclei involved in autonomic, limbic, nociceptive, and sensory function (superior and inferior colliculi, ventral tegmental area-parabrachial pigmented nucleus complex, microcellular tegmental nucleus-prabigeminal nucleus complex, lateral and medial parabrachial nuclei, vestibular and superior olivary complex, superior and inferior medullary reticular formation, viscerosensory motor nucleus, raphe magnus, pallidus, and obscurus, and parvicellular reticular nucleus - alpha part) with the rest of the brain. Specifically, we exploited 1.1mm isotropic resolution 7 Tesla resting-state fMRI, ad-hoc coregistration and physiological noise correction strategies, and a recently developed probabilistic template of brainstem nuclei. Further, we used 2.5mm isotropic resolution resting-state fMRI data acquired on a 3 Tesla scanner to assess the translatability of our results to conventional datasets. We report highly consistent correlation coefficients across subjects, confirming available literature on autonomic, limbic, nociceptive and sensory pathways, as well as high interconnectivity within the central autonomic network and the vestibular network. Interestingly, our results showed evidence of vestibulo-autonomic interactions in line with previous work. Comparison of 7 Tesla and 3 Tesla findings showed high translatability of results to conventional settings for brainstem-cortical connectivity and good yet weaker translatability for brainstem-brainstem connectivity. The brainstem functional connectome might bring new insight in the understanding of autonomic, limbic, nociceptive and sensory function in health and disease.

neuroscience↗

bioRxiv2021

Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI

Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.

neuroscience↗

bioRxiv2018

Smart Region-Growing: a novel algorithm for the segmentation of 3D clarified confocal image stacks

MotivationAccurately mapping the brain at the micro-scale is still a challenge in cellular neuroscience. While notable success has been reached in the field of tissue clarification and confocal imaging to obtain high-fidelity maps of three-dimensional neuron organization, neuron segmentation is still far away of ground-truth and manual segmentation performed by experts may be needed. The need of an expert is in part related to the limited success of the algorithms and tools performing single-neuron segmentation from 3D microscopic image data available in the State of Art, in part to the non-complete information given by these methods, which typically perform neuron tracing and thus limit the interpret-ability of results.\n\nResultsIn this paper, a novel algorithm for segmenting single neurons in their own arrangement within the brain is presented. The algorithm performs a region growing procedure with local thresholds based on the pixel intensity statistics typical of confocal acquisitions of biological samples and described by a mixture model. The algorithm is developed and tested on 3D confocal datasets obtained from clarified tissues. We compare the result of our algorithm with those obtained by manual segmentation performed by 6 different experts in terms of neuron surface area, volume and Sholl profiles. Statistical analysis performed on morphologic features extracted from the segmented structures confirms the feasibility of our approach.\n\nAvailabilityThe Smart Region Growing (SmRG) algorithm used in the analysis along with test confocal image stacks is available on request to the authors.\n\nContactalejandrocallara@gmail.com\n\nSupplementary informationSupplementary data are available on request to the authors.

bioinformatics↗