Biology subjects

Bracco, M.

Publications and source records attributed to Bracco, M..

5 recordsLinked to original sources

bioRxiv2026

Functional cerebellar connectomes interfacing motor adaptation and reinforcement feedback

Motor adaptation is driven by sensory prediction errors, yet reinforcement feedback can alter the speed and retention of adaptive behaviors. The cerebellum is central in motor adaptation, but posterior lobules, especially Lobule VI (CB6) and Crus I (CBcrus1), also participate in reinforcement-related signaling. Serotoninergic and dopaminergic systems, key modulators of motivational processes, directly influence cerebellar activity. However, how these neuromodulatory systems contribute to cerebellar network organization and to reinforcement-based adaptation in humans remains unclear. We employed a multimodal framework (Receptor-Enriched Analysis of functional Connectivity by Targets; REACT) using PET-derived Serotonin/Dopamine Transporter (SERT/DAT) templates to enrich resting-state functional Magnetic Resonance Imaging (rs-fMRI). We estimated SERT- and DAT-enriched functional connectivity from CB6 and CBcrus1 within motor-adaptation and reinforcement-learning networks, and tested their correlations with performance in a visuomotor adaptation task completed under reward and punishment. Our findings show lobule-specific neuromodulatory organization within the cerebellum. CB6 exhibited predominantly DAT- and SERT-enriched connectivity with motor adaptation networks, while CBcrus1 showed stronger SERT-enriched communication extending to both motor and reinforcement networks. Crucially, distinct cerebello-cortical neuromodulatory networks predicted individual differences in adaptation rate. DAT-enriched CBcrus1 connectivity was linked to punishment-driven adaptation, whereas SERT-enriched cerebello-orbitofrontal connectivity predicted faster adaptation across both reward and punishment contingencies. Furthermore, we observed overlaps between SERT- and DAT-enriched networks in the medial orbitofrontal area for Crus I, which predicted retention following punishment, underscoring the role of convergent neuromodulation in stabilizing adapted movements. We conclude that partially segregated yet convergent cerebello-cortical networks support interactions between motor and motivational behaviors, with combined and opposing effects of serotonergic and dopaminergic neuromodulation accounting for the speed and retention of adaptive behaviors.

neuroscience↗

bioRxiv2025

EPICURUS: E-field-based spatial filtering procedure for an accurate estimation of local EEG activity evoked by Transcranial Magnetic Stimulation

BackgroundThe concurrent use of Transcranial magnetic stimulation and electroencephalography (TMS-EEG) is increasingly integrated into research and clinical protocols. However, a reliable isolation of EEG responses that are locally evoked by TMS at the targeted cortical sites independent from contaminating sources, remains challenging. MethodsHere we introduce EPICURUS, a novel spatial filtering approach for TMS-EEG that uses individualized MRI-based simulations of the TMS-induced electric field (E-field) to define the spatial extent of locally evoked activity. This method guides the reconstruction of EEG signals originating from the direct stimulation site while minimizing crosstalk from distant, non-targeted sources. ResultsIn synthetic simulations and a human TMS-EEG dataset, EPICURUS preserved early-latency TMS-evoked local activity while substantially attenuating later components, consistent with suppression of non-local activity. ConclusionBy leveraging the spatial precision of individualized E-field modeling, EPICURUS may enhance the specificity of EEG signal reconstruction, offering a promising tool for improving the spatiotemporal resolution of local early and late cortical local responses directly elicited by TMS.

neuroscience↗

bioRxiv2025

Oscillatory impact of Transcranial Magnetic Stimulation at very weak-intensity on the primary motor cortex: A TMS-EEG study in the human brain

Transcranial Magnetic Stimulation is widely used to probe and modulate human brain function, yet the neural effects of stimulation delivered at very low intensities remain unclear. Here, we show that very low intensity magnetic pulses can alter ongoing oscillatory activity in the human primary motor cortex. In healthy participants, we combined transcranial magnetic stimulation with electroencephalography to assess neural responses to single pulses and rhythmic stimulation in the motor cortex. Conventional high intensity stimulation produced robust evoked responses and synchronized beta-frequency oscillations. Low-intensity rhythmic stimulation, despite generating much weaker direct responses, modified local oscillatory activity in a manner consistent with phase-dependent enhancement of ongoing rhythms. These findings suggest that cortical oscillations can be influenced by magnetic fields substantially weaker than those typically used in human studies. Low-intensity stimulation may therefore offer a route towards portable, energy-efficient technologies for investigating and modulating brain networks.

neuroscience↗

bioRxiv2024

Emergence of Pre-movement Beta Activity with Stable Sensorimotor Predictions to Facilitate Motor Adjustments

Adaptive behavior enables flexible responses to environmental changes. This process is particularly crucial when transitioning between environments with different features, relying on the progressive formation of expectations based on prior experience. In humans, beta oscillations are central to adaptive behavior. Yet, the brain mechanisms underlying the detection of environmental changes, and the iterative update needed to progressively improve behavioral performance remain elusive. Here, we reveal that beta activity emerges in a cerebello-cortical network two seconds before action initiation, as the features of a new environment become known and behavioral outcomes become more predictable. Within this period, the cerebellum and parietal cortex drive prefrontal activity to form expectations. Using a single-trial approach, we establish that beta bursts before action initiation predict performance in the upcoming trial based on previous outcomes. These findings uncover a novel anticipatory mechanism that reflects predictive processes critical for stabilizing performance and adapting to environmental changes.

neuroscience↗

bioRxiv2023

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events

Statistical power in cognitive neuroimaging experiments is often very low. Low sample size can reduce the likelihood of detecting real effects (false negatives) and increase the risk of detecting non-existing effects by chance (false positives). Here we document our experience of leveraging a relatively unexplored method of collecting a large sample size for simple electroencephalography (EEG) studies: by recording EEG in the community during public engagement and outreach events. We collected data from 346 participants (189 females, age range 6-76 years) over 6 days, totalling 29 hours, at local science festivals. Alpha activity (6-15 Hz) was filtered from 30 seconds of signal, recorded from a single electrode placed between the occipital midline (Oz) and inion (Iz) while participants rested with their eyes closed. A total of 289 good quality datasets were obtained. Using this community-based approach, we were able to replicate controlled, lab-based findings: IAF increased during childhood, reaching a peak frequency of 10.28 Hz at 28.1 years old, and slowed again in middle and older age. Total alpha power decreased linearly, but the aperiodic-adjusted alpha power did not change over the lifespan. Aperiodic slopes and intercepts were highest in the youngest participants. There were no associations between these EEG indexes and self-reported fatigue, measured by the Multidimensional Fatigue Inventory. Finally, we present a set of important considerations for researchers who wish to collect EEG data within public engagement and outreach environments.

neuroscience↗