Biology subjects

Sozzi, S.

Publications and source records attributed to Sozzi, S..

3 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

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

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↗