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Cortical propagation tracks functional recovery after stroke

Articolo
Data di Pubblicazione:
2021
Abstract:
Stroke is a debilitating condition affecting millions of people worldwide. The development of improved rehabilitation therapies rests on finding biomarkers suitable for tracking functional damage and recovery. To achieve this goal, we perform a spatiotemporal analysis of cortical activity obtained by wide-field calcium images in mice before and after stroke. We compare spontaneous recovery with three different post-stroke rehabilitation paradigms, motor training alone, pharmacological contralesional inactivation and both combined. We identify three novel indicators that are able to track how movement-evoked global activation patterns are impaired by stroke and evolve during rehabilitation: the duration, the smoothness, and the angle of individual propagation events. Results show that, compared to pre-stroke conditions, propagation of cortical activity in the subacute phase right after stroke is slowed down and more irregular. When comparing rehabilitation paradigms, we find that mice treated with both motor training and pharmacological intervention, the only group associated with generalized recovery, manifest new propagation patterns, that are even faster and smoother than before the stroke. In conclusion, our new spatiotemporal propagation indicators could represent promising biomarkers that are able to uncover neural correlates not only of motor deficits caused by stroke but also of functional recovery during rehabilitation. In turn, these insights could pave the way towards more targeted post-stroke therapies.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
TARGETED STROKEMICE REVEALSCORTEXCONNECTIVITYDYNAMICSREORGANIZATIONCIRCUITSDAMAGEWAVESMAPS
Elenco autori:
Pavone, FRANCESCO SAVERIO; Conti, Emilia; Kreuz, Thomas; ALLEGRA MASCARO, ANNA LETIZIA
Autori di Ateneo:
ALLEGRA MASCARO ANNA LETIZIA
KREUZ THOMAS
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/399131
Pubblicato in:
PLOS COMPUTATIONAL BIOLOGY (ONLINE)
Journal
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URL

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008963
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