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Lugli, B.

Publications and source records attributed to Lugli, B..

2 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↗

Perfect Timing: Effects of Auditory Stimulation on Alpha Oscillations During Wakefulness and the Transition to Sleep are Phase-dependent in Humans

Alpha oscillations play a vital role in managing the brains resources, inhibiting neural activity as a function of their phase and amplitude, and are changed in many brain disorders. Developing minimally invasive tools to modulate alpha activity and identifying the parameters that determine its response to exogenous modulators, is essential for the implementation of focussed interventions. We introduce Alpha Closed-Loop Auditory Stimulation (CLAS) as an EEG-based method to augment and investigate these brain rhythms in humans with specificity and selectivity, using targeted auditory stimulation. Across three independent studies, we demonstrate that CLAS alters alpha power, frequency, and connectivity in a phase, amplitude and topography-dependent manner. Using a single-pulse-CLAS evoked potentials approach we show that the effects of auditory stimuli on alpha oscillations and resulting evoked potentials can be explained within the theoretical framework of oscillator theory and a phase-reset mechanism. Finally, we demonstrate the functional relevance of our approach by showing that CLAS modulates sleep onset dynamics in an alpha phase-dependent manner.

neuroscience↗