Biology subjects

Eggl, M.

Publications and source records attributed to Eggl, M..

4 recordsLinked to original sources

bioRxiv2026

Longitudinal MRI reveals hormone-dependent brain remodeling supporting preserved cognition in aged females

Adaptive plasticity, the brains capacity to counteract structural decline and preserve performance with age, is a hallmark of successful aging, yet its biological underpinnings remain poorly understood. Here, we combined longitudinal magnetic resonance imaging (MRI) spanning the entire lifespan with electrophysiology, immunohistochemistry, and behavioral assays in female and male rats to identify key region- and systems-level mechanisms underlying this process. Resting-state functional MRI revealed a striking sex-specific pattern of connectivity reorganization in anterior brain regions, emerging in midlife and more pronounced in females. Microstructural MRI and histological analyses linked increased connectivity to prolonged white matter preservation and downstream maintenance of neuronal function in the female prefrontal cortex, while electrophysiological recordings demonstrated enhanced effective connectivity in the same region in aged females. Behaviorally, enhanced anterior connectivity was associated with superior memory performance. Ovariectomy at a critical time point for white matter maturation compromised this female-specific neuroprotection, disrupting microstructural integrity and functional reorganization, thereby highlighting the role of sex hormones in shaping these trajectories. Together, these findings identify a novel sexually dimorphic pattern of functional reorganization in anterior brain regions and point to estrogen availability during critical periods as a key modulator of brain aging.

neuroscience↗

bioRxiv2026

Push-and-pull protein dynamics leads to log-normal synaptic sizes and probabilistic multi-spine plasticity

A typical neuron receives thousands of inputs and is able to adapt the strength of its synapses to store new information and meet ongoing computational demands. The synaptic response to plasticity induction is stochastic and spatially structured but is traditionally described by deterministic models representing the "average" dynamics. Growing experimental evidence indicates that not only the stimulation protocol determines the plasticity outcome but that the initial synaptic sizes, their fluctuations, and the spatial competition for the plasticity-relevant proteins play a decisive role. This probabilistic perspective makes it hard to predict the fate of a given synapse and requires a conceptual shift from a single synapse view to a probabilistic multi-spine competitive process where the plasticity needs and the available resources are considered together. Here, we propose a data-driven modeling framework able to predict collective plasticity outcomes along a dendrite based on the initial size, the number, and the spatial distance between simultaneously stimulated synapses. Our data analysis reveals a log-normal distribution of protein numbers for many plasticity-mediating proteins and shows that this log-normal protein allocation constrains and controls the collective plasticity outcome across multiple stimulated and non-stimulated synapses while preserving a global size distribution. Our findings highlight how local stochastic processes and global protein allocation rules give rise to synaptic plasticity outcomes, offering a new framework to understand and predict dendritic computation.

neuroscience↗

bioRxiv2023

Linking spontaneous and stimulated spine dynamics

Our brains continuously acquire and store memories through synaptic plasticity. However, spontaneous synaptic changes can also occur and pose a challenge for maintaining stable memories. Despite fluctuations in synapse size, recent studies have shown that key population-level synaptic properties remain stable over time. This raises the question of how local synaptic plasticity affects the global population-level synaptic size distribution and whether individual synapses undergoing plasticity escape the stable distribution to encode specific memories. To address this question, we (i) studied spontaneously evolving spines and (ii) induced synaptic potentiation at selected sites while observing the spine distribution pre- and post-stimulation. We designed a stochastic model to describe how the current size of a synapse affects its future size under baseline and stimulation conditions and how these local effects give rise to population-level synaptic shifts. Our study offers a new understanding of how seemingly spontaneous synaptic fluctuations and local plasticity both contribute to population-level synaptic dynamics.

neuroscience↗

bioRxiv2022

A quantitative rule to explain multi-spine plasticity

Neurons receive thousands of inputs onto their dendritic arbour, where individual synapses undergo activitydependent changes in strength. The durable forms of synaptic strength change, long-term potentiation (LTP) and long-term depression (LTD) require calcium entry through N-methyl-D-aspartate receptors (NMDARs) that triggers downstream protein signalling cascades in the dendrite. Notably, changes in postsynaptic strengths associated with LTP and LTD are correlated to changes in spine head volume, referred to as structural LTP (sLTP) and structural LTD (sLTD). Intriguingly, LTP and LTD, including sLTP and sLTD, are not necessarily restricted to the active, targeted synapses (homosynapses), and the changes in synaptic strength can spread and affect the strengths of inactive or non-stimulated synapses (heterosynapses) on the same cell. Moreover, the plasticity outcome at both homo- and heterosynapses can depend on the number of stimulated sites when eliciting multi-spine plasticity. Precisely how neurons allocate resources for implementing the changes in strength at individual synapses depending on their proximity to input activity across space and time remains an open question. In order to gain insights into the elementary processes underlying multi-spine plasticity that engages both homosynaptic and heterosynaptic changes, we have combined experimental and mathematical modelling approaches. On the one hand, we used glutamate uncaging to precisely and systematically stimulate variable numbers of homosynapses sharing the same dendritic branch whilst monitoring tens of other heterosynapses on the same dendrite. Homosynaptic potentiation of clusters of dendritic spines leads to heterosynaptic changes that are dependent on NMDAR, CaMKII and calcineurin. On the other hand, inspired by the Ca2+ levels hypothesis where different amounts of Ca2+ lead to either growth or shrinkage of spines, we have built a model based on a dual-role Ca2+-dependent protein that induces sLTP or sLTD. Comparing our experimental results with model predictions, we find that (i) both collaboration and competition among spines for protein resources are key drivers of heterosynaptic plasticity and (ii) the temporal and spatial distance between simultaneously stimulated spines impact the resulting spine dynamics. Moreover, our model can reconcile disparate experimental reports of sLTP and sLTD at homo- and heterosynaptic spines. Our results provide a quantitative description of the heterosynaptic footprint over minutes and hours post-stimulation across tens of microns of dendritic space. This broadens our knowledge about the operation of non-linear dendritic summation rules and how they impact spiking decisions.

neuroscience↗