Elvio A. Blini
Elvio A. Blini
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FCnet
Two new articles!
Blini et al. and Cinetto et al. report
innovative methods for the diagnosis and
rehabilitation of (subtle) spatial biases
Elvio A. Blini
Last updated on May 10, 2025
5 min read
stroke
,
attentional load
,
visuo-spatial attention
,
FCnet
,
dual task
,
extinction
,
unilateral spatial neglect
,
machine learning
,
predictive modelling
,
multiple demands system
,
spatial awareness
,
eye movements
,
statistical learning
,
free viewing
,
dimensionality reduction
,
feature extraction
Project
Susceptibility to multitasking in stroke is associated to multiple-demand system damage and leads to lateralized visuospatial deficits
Cognitive impairment after stroke is heterogeneous: there is no strict correspondence between brain damage and magnitude of deficit or recovery. Protective factors such as cognitive or brain reserve have been invoked to explain the mismatch.
Elvio A. Blini
,
Daniela d'Imperio
,
Zaira Romeo
,
Michele de Filippo de Grazia
,
Laura Passarini
,
Cristina Pilosio
,
Fracesca Meneghello
,
Mario Bonato
,
Marco Zorzi
PDF
Cite
Project
DOI
New preprint!
Susceptibility to multitasking in chronic stroke is associated to damage of the multiple demand system and leads to lateralized visuospatial deficits.
A new paper discussing multitasking as a tool to unveil subtle deficits after stroke. We argue that attentional load provides a simple strategy, firmly grounded in theory, to study the gray area in which stroke can or cannot result in stark deficits. This is an opportunity to better frame the mismatch between the amount of brain damage and its consequences, in an era in which this line is becoming increasingly blurred.
Elvio A. Blini
Oct 16, 2023
3 min read
stroke
,
attentional load
,
visuo-spatial attention
,
FCnet
,
dual task
,
extinction
,
unilateral spatial neglect
,
machine learning
,
predictive modelling
Project
FCnet
An R package for the analysis of Functional Connectivity matrices, lesion maps, or disconnection maps through elastic NETs.
Assessment of machine learning pipelines for prediction of behavioral deficits from brain disconnectomes
Recent studies have shown that brain lesions following stroke can be probabilistically mapped onto disconnections of white matter tracts, and that the resulting “disconnectome” is predictive of the patient’s behavioral deficits.
Marco Zorzi
,
Michele de Filippo de Grazia
,
Elvio A. Blini
,
Alberto Testolin
PDF
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Project
DOI
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