Biology subjects

Le Meur-Diebolt, S.

Publications and source records attributed to Le Meur-Diebolt, S..

3 recordsLinked to original sources

bioRxiv2025

Speed Vascular Patterns in the Spatial Navigation System

The hippocampal formation is central to spatial navigation, hosting neurons that encode position, direction, and speed. Yet, the brain-wide vascular dynamics supporting these processes remain poorly understood, especially during naturalistic behaviors. Here, we adapted functional ultrasound (fUS) imaging to examine how cerebral blood volume (CBV) changes relate to behavioral parameters in freely moving rats. High-resolution imaging of hippocampal-parahippocampal regions during open-field exploration reveals strong correlations between CBV dynamics and animal speed, with distinct regional activation patterns and temporal delays. Lagged general linear modeling uncovers information flow from the thalamus to parahippocampal regions, including the medial entorhinal cortex, and to hippocampal subfields (dentate gyrus, CA1-CA3), consistent with a hierarchical processing framework. The analysis also links CBV with angular head speed and the dorsal thalamus. Decoding analyses show that CBV signals not only encode speed precisely but also capture spatial features like proximity to walls and corners, even when univariate analyses do not. This decoding remains robust across animals, underscoring the universality of speed encoding in vascular dynamics. We also identify slow CBV oscillations in the hippocampus aligned with minute-scale speed fluctuations, suggesting a neurovascular signature of exploratory behavior. These findings reveal a hemodynamic signature of speed representation in the navigation system, arising from energy demands in a continuous attractor network model for path integration, where population activity and synaptic currents increase quadratically with animal speed as both peak firing rates and neuronal recruitment scale linearly with animal speed. Moreover, they highlight functional ultrasound imaging as a powerful approach for probing the hemodynamic basis of navigation.

neuroscience↗

bioRxiv2025

Robust functional ultrasound imaging in the awake and behaving brain: a systematic framework for motion artifact removal

Functional ultrasound imaging (fUSI) is a promising tool for studying brain activity in awake and behaving animals, offering insights into neural dynamics that are more naturalistic than those obtained under anesthesia. However, motion artifacts pose a significant challenge, introducing biases that can compromise the integrity of the data. This study provides a comprehensive evaluation and benchmarking of strategies for detecting and removing motion artifacts in transcranial fUSI acquisitions of awake mice. We evaluated 792 denoising strategies across four datasets, focusing on clutter filtering, scrubbing, frequency filtering, and confound regression methods. Our findings highlight the superior performance of adaptive clutter filtering and aCompCor confound regression in mitigating motion artifacts while preserving functional connectivity patterns. We also demonstrate that high-pass filtering is generally more effective than band-pass filtering in the presence of motion artifacts. Additionally, we show that with effective clutter filtering, scrubbing may become optional, which is particularly beneficial for experimental designs where motion correlates with conditions of interest. Based on these insights, we propose four optimized denoising paradigms tailored to different experimental constraints, providing practical recommendations for enhancing the reliability and reproducibility of fUSI data. Our findings challenge current practices in the field and have immediate practical implications for existing fUSI analysis workflows, paving the way for more sophisticated applications of fUSI in studying complex brain functions and dysfunctions in awake experimental paradigms.

neuroscience↗

bioRxiv2024

PhysiofUS : a tissue-motion based method for heart and breathing rate assessment in neurofunctional ultrasound imaging

Recent studies have shown growing evidence that brain function is closely synchronised with global physiological parameters. Heart rate is linked to various cognitive processes and previous research has also demonstrated a strong correlation between neuronal activity and breathing. These findings highlight the significance of monitoring these key physiological parameters during neuroimaging as they provide valuable insights into the overall brain function. Today, in neuroimaging, assessing these parameters required additional cumbersome devices or implanted electrodes. In this work, we performed ultrafast ultrasound imaging both in rodents and human neonates, and we extracted heart and breathing rates from local tissue motion assessed by raw ultrasound data processing. Such PhysiofUS automatically select two specific and optimal brain regions with pulsatile tissue signals to monitor such parameters. We validated the correspondence of these periodic signals with heart and breathing rates assessed using gold-standard electrodes in various conditions in rodents. We also validated Physio-fUS imaging in a clinical environment using conventional ECG. We show the potential of fUS imaging as an integrative tool for simultaneously monitoring physiological parameters during neurofunctional imaging. Beyond the technological improvement, this innovation could enhance our understanding of the link between breathing, heart rate and neurovascular activity both anesthetised in preclinincal research and clinical functional ultrasound imaging.

bioengineering↗