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Beanato, E.

Publications and source records attributed to Beanato, E..

6 recordsLinked to original sources

Individual connectome fingerprints reveal early stabilization and long-term circuit remodeling after stroke

Stroke is one of the leading causes of global disability, yet the principles governing how focal brain injury disrupts large-scale neural connectivity over time remain poorly understood. Here, we leverage a longitudinal multimodal dataset to track the evolution of individual-specific connectivity patterns, or brain fingerprints, over the first year after stroke. Despite a persistent shift from healthy architecture, we demonstrate that each patients unique functional connectome fingerprint is remarkably resilient and stabilizes within three weeks. This early global stabilization masks a protracted system-specific reorganization of brain circuits, which is characterized by an initial increase in connectivity within sensory and attention systems, followed by a decline across higher-level association networks. A joint structure-function embedding further shows that recovery involves a gradual shift toward the normative healthy range, driven primarily by functional reconfiguration atop a stable structural lesion. Crucially, a multivariate prediction model reveals that early functional signatures selectively forecast long-term impairment in language, executive function, and attention. Together, our results define the post-stroke brain as a shifting but constrained dynamical system, identifying early-stabilized brain patterns as biomarkers for individual recovery profiles and targets for personalized neurorehabilitation.

neuroscience↗

Bodily perception links memory and self: a case study of an amnesic patient

Episodic autobiographical memory (EAM) is a building block of self-consciousness, involving recollection and subjective re-experiencing of personal past experiences. Any life episode is originally encoded by a subject within a body. This raises the possibility that memory encoding is shaped by bodily self-consciousness (BSC), a basic form of self-consciousness arising from the multisensory and sensorimotor perceptual signals from the body. Recent studies in healthy subjects showed that embodied encoding improves EAM, with the involvement of the hippocampus. However, there are only few imaging studies to date, hippocampal data are not consistent, and the role of hippocampal damage is not understood. We investigated how different BSC states during encoding, modulate later EAM retrieval, in a patient with severe amnesia caused by rare bilateral hippocampal damage. We performed three separate behavioral experiments using immersive virtual reality. The patient showed consistently more difficulties recollecting information encoded in embodied vs. disembodied states, particularly when asked to recall her perspective experienced at encoding. These results contrasted with the usual beneficial effect of BSC on EAM, and significantly differed from controls. These data provide consistent evidence that BSC impacts encoding and later reliving, and shows that the hippocampus is not just a critical structure for EAM, but also for effects of embodiment on memory. Additional fMRI data extend these findings by revealing that hippocampal-parietal connectivity mediates BSC-EAM coupling. Our findings plead for an important role of BSC in EAM, mediated by the hippocampus and its connectivity, leading to embodied memories that are experienced as belonging to the self. HighlightsO_LIWe studied a patient with memory deficits caused by bilateral hippocampal atrophy C_LIO_LIMultisensory stimulation modulated embodiment during episode encoding C_LIO_LIAcross three studies the patient showed stronger memory deficits for embodied episodes C_LIO_LIMultisensory bodily perception impacts bodily self-consciousness and episodic memory C_LIO_LIOur findings link the bodily self to episodic memory and the hippocampus C_LI

neuroscience↗

Effects of hippocampal noninvasive theta-burst stimulation on consolidation of associative memory in healthy older adults

Stimulation of deep brain areas can offer benefits against cognitive impairments associated with aging. So far, this was only possible via invasive methods accompanied by risks. Grossman et al. proposed a new noninvasive stimulation technique, transcranial temporal interference electric stimulation (tTIS), which can be steered to target and modulate activity of deep brain structures. Memory capacity depends on subcortical structures such as the hippocampus, hence, modulation of hippocampal activity could benefit declining cognitive functions. The current study investigates whether theta-burst patterned tTIS targeting the hippocampus influences performance of associative memory in older adults. We found that theta-burst patterned tTIS, but not the control stimulation, improved recollection time in a follow-up 24h after the stimulation, suggesting that theta-burst patterned tTIS can influence the efficiency of longer-term encoding. This outcome indicates that tTIS may provide a new noninvasive deep brain stimulation method to modulate senescent memory processes.

neuroscience↗

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↗

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↗

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↗