Biology subjects

De Vico Fallani, F.

Publications and source records attributed to De Vico Fallani, F..

5 recordsLinked to original sources

bioRxiv2025

Imagined movement increases the segregation of brain-heart networks

Understanding the mechanisms of motor imagery, the mental simulation of movement without execution, is key for the development of neurotechnologies, including understanding inter-individual variability in motor imagery performance. For instance, for detecting covert motor intent in noncommunicative patients or refining motor commands through brain-computer interfaces. While motor imagery engages motor-related brain regions, its precise mechanisms remain unclear, particularly in relation to cardiac dynamics. Evidence suggests heart-rate variability features have potential to enhance tasks classifications, yet the brain-heart relationship is not well understood. In this study, we examined motor imagery learning using a task involving right-hand grasping imagery. We found that motor imagery is correlated with a task-dependent modulation of cardiac sympathetic activity and its relation with directed functional connectivity from the supplementary motor area to premotor and primary motor cortices. Additionally, cerebellar-supplementary motor area segregation, in relation to cardiac parasympathetic activity, indexed longitudinal motor learning. These results suggest that dynamic reconfiguration of brain-heart interactions contributes to sensorimotor function and learning-related physiology during motor imagery, supporting the brain-heart axis as a functional component of motor imagery rather than a passive correlate.

neuroscience↗

bioRxiv2024

Linking heartbeats with the cortical network dynamics involved in self-other distinction during affective touch.

Research on interoception has revealed the role of heartbeats in shaping our perceptual awareness and embodying a first-person perspective. These heartbeat dynamics exhibit distinct responses to various types of touch. We advanced that those dynamics are directly associated to the brain activity that allows self-other distinction. In our study encompassing self and social touch, we employed a method to quantify the distinct couplings of temporal patterns in cardiac sympathetic and parasympathetic activities with brain connectivity. Our findings revealed that social touch led to an increase in the coupling between frontoparietal networks and parasympathetic/vagal activity, particularly in alpha and gamma bands. Conversely, as social touch progressed, we observed a decrease in the coupling between brain networks and sympathetic dynamics across a broad frequency range. These results show how heartbeat dynamics are intertwined with brain organization and provide fresh evidence on the neurophysiological mechanisms of self-social touch distinction.

neuroscience↗

bioRxiv2024

Measuring the time-dependent effects of dobutamine on the modulations of cardiac activity in rats

Assessing cardiac dynamics over time is essential for understanding cardiovascular health and its parallel patterns of activity with the brain. We present a methodology to estimate the time-resolved sympathetic and parasympathetic modulations of cardiac dynamics, specifically tailored for the rat heart. To evaluate the performance of our method, we study a dataset comprising spontaneously hypertensive rats and Wistar-Kyoto rats. These rats were administered dobutamine to elicit autonomic dynamics. The results obtained from our method demonstrated accurate time-resolved depiction of sympathetic reactivity induced by dobutamine administration. These responses closely resembled the expected autonomic alterations observed during physical exercise conditions, albeit emulated pharmacologically. We further compared our method with standard measures of low-frequency (LF) and high-frequency (HF) components, which are commonly used, although debated, for sympathetic and parasympathetic activity estimation. The comparisons with LF and HF measures further confirmed the effectiveness of our method in better capturing autonomic changes in rat cardiac dynamics. Our findings highlight the potential of our adapted method for time-resolved analysis in future clinical and translational studies involving rodents models. The validation of our approach in animal models opens new avenues for investigating the relationship between ongoing changes in cardiac activity and parallel changes in brain dynamics. Such investigations are crucial for advancing our understanding of the brain-heart connection, particularly in cases involving neurodegeneration, brain injuries, and cardiovascular conditions. Key points- We developed a method for time-resolved estimation of sympathetic and parasympathetic modulations in rat cardiac dynamics, validated against standard LF and HF measures. - We used a cohort of spontaneously hypertensive rats and Wistar-Kyoto rats, with dobutamine administration to induce autonomic responses. - Our method accurately depicted time-resolved sympathetic reactivity similar to autonomic changes during physical exercise. - Our findings suggest potential for future clinical and translational studies on the brain-heart connection, particularly in cardiovascular conditions.

neuroscience↗

bioRxiv2022

Measuring brain critical dynamics to inform Brain-Computer Interfaces

Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces (BCI). To test this hypothesis, we used source-reconstructed magneto/electroencephalography, during resting state and a motor imagery task performed within a BCI protocol. To track the probability that an avalanche would spread across any two regions we built an avalanche transition matrix (ATM) and demonstrated that the edges whose transition probabilities significantly differed between conditions hinged selectively on premotor regions in all subjects. Furthermore, we showed that the topology of the ATMs allows task-decoding above the current gold standard. Hence, our results suggest that Neuronal Avalanches might capture interpretable differences between tasks that can be used to inform brain-computer interfaces.

neuroscience↗

bioRxiv2018

Spatiotemporal neural correlates of brain-computer interface learning

Brain-computer interfaces have been largely developed to allow communication, control, and neurofeedback in human beings. Despite their great potential, BCIs perform inconsistently across individuals. Moreover, the neural processes activated by training that enable humans to achieve good control remain poorly understood. In this study, we show that BCI skill acquisition is paralleled by a progressive reinforcement of task-related activity and by the reduction of connectivity between regions beyond those primarily targeted during the experiments. Notably, these patterns of activity and connectivity reflect growing automaticity and predict future BCI performance. Altogether, our findings provide new insights in the neural mechanisms underlying BCI learning, which have implications for the use of this technology in a broad range of real-life applications.

neuroscience↗