Biology subjects

Beanato, E.

Publications and source records attributed to Beanato, E..

3 recordsLinked to original sources

bioRxiv2022

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. Especially, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited an innovative, non-invasive deep brain stimulation technique called transcranial Temporal Interference Stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomised, sham-controlled, double-blind study. Striatal tTIS applied at 80Hz, but not at 20Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80Hz, but not 20Hz tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show for the first time that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, opening new horizons for the study of causal relationships between deep brain structures and human behaviour.

neuroscience↗

bioRxiv2022

LTP-like noninvasive striatal brain stimulation enhances striatal activity and motor skill learning in humans

The stimulation of deep brain structures has thus far only been possible with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-concept was obtained through modeling, physics experiments and rodent models. Here, we show for the first time successful noninvasive neuromodulation of the striatum via tTIS in humans using computational modeling, fMRI studies and behavioral evaluations. Theta-burst patterned striatal tTIS increased activity in the striatum and associated motor network. Furthermore, striatal tTIS enhanced motor performance, especially in healthy older participants as they have lower natural learning skills than younger subjects. These findings place tTIS as exciting new method to target deep brain structures in humans noninvasively, thus enhancing our understanding of their functional roles. Moreover, our results lay the groundwork for innovative, noninvasive treatment strategies for brain disorders in which deep striatal structures play key pathophysiological roles.

neuroscience↗

bioRxiv2022

Differential impact of brain network efficiency on post-stroke motor and attentional deficits

BackgroundMost studies on stroke have been designed to examine one deficit in isolation, yet survivors often have multiple deficits in different domains. While the mechanisms underlying multiple-domain deficits remain poorly understood, network-theoretical methods may open new avenues of understanding. Methods50 subacute stroke patients (7{+/-}3days post-stroke) underwent diffusion-weighted magnetic resonance imaging and a battery of clinical tests of motor and cognitive functions. We defined indices of impairment in strength, dexterity, and attention. We also computed imaging-based probabilistic tractography and whole brain connectomes. Overlaying individual lesion masks onto the tractograms enabled us to split the connectomes into their affected and unaffected parts and associate them to impairment. ResultsTo efficiently integrate inputs from different sources, brain networks rely on a "rich-club" of a few hub nodes. Lesions harm efficiency, particularly when they target the rich-club. We computed efficiency of the unaffected connectome, and found it was more strongly correlated to impairment in strength, dexterity and attention than efficiency of the total connectome. The magnitude of the correlation between efficiency and impairment followed the order attention > dexterity {approx} strength. Network weights associated with the rich-club were more strongly correlated to efficiency than non-rich-club weights. ConclusionsAttentional impairment is more sensitive to disruption of coordinated network activity between brain regions than motor impairment, which is sensitive to disruption of localized network activity. Providing more accurate reflections of actually functioning parts of the network enables the incorporation of information about the impact of brain lesions on connectomics contributing to a better understanding of underlying stroke mechanisms.

neuroscience↗