scholarly journals Language and Music side by side: post stroke aprosodia and amusia are subserved by the same brain networks

2021 ◽  
Author(s):  
Eckart Altenmüller
Keyword(s):  
Brain Networks ◽  
Post Stroke ◽  
Language And Music

Brain Networks Implicated in Post-Stroke Deficits

2016 ◽  
Vol 16 (15) ◽  
pp. 1
Author(s):  
Thomas R. Collins
Keyword(s):  
Brain Networks ◽  
Post Stroke

scholarly journals Exploring the functional connectivity characteristics of brain networks in post-stroke patients with global aphasia: a healthy control based resting-state fMRI study

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Xinlei Xu ◽  
Caili Ren ◽  
Hui Fang ◽  
Zhaohui Li ◽  
Ping Chen ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Stroke Patients ◽  
Post Stroke ◽  
Fmri Study ◽  
Healthy Control

scholarly journals Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions

2021 ◽  
Author(s):  
Elvira Pirondini ◽  
Nawal Kinany ◽  
Cécile Le Sueur ◽  
Joseph C. Griffis ◽  
Gordon L. Shulman ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Cognitive Functions ◽  
Large Scale ◽  
Brain Networks ◽  
Brain Dynamics ◽  
Time Resolved ◽  
Post Stroke ◽  
Temporal Properties ◽  
Fmri Analysis

AbstractFunctional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. While large-scale spatial patterns of these networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. These temporal alterations were associated with white matter damage and were behavior-specific. Specifically, restoration of healthy brain dynamics paralleled recovery of cognitive functions, but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis.Significance StatementUnderstanding the pathophysiology of a disorder is pivotal to design effective treatment. In this regard, recent advances in stroke research settled a new clinical concept: connectional diaschisis, which suggested that post-stroke impairments arise from both focal structural changes (tied to the injury) and widespread alterations in functional connectivity. fMRI time-resolved methods consider structural and temporal properties of brain networks as interdependent features. They are, thus, better suited to capture the intertwine between structural and functional changes. Here we leveraged a dynamic functional connectivity framework based on the clustering of hemodynamic-informed transients in a large and heterogeneous stroke population assessed longitudinally. We showed that lesions led to an unbalance in the brain dynamics that was associated with white matter fibers disruption and was restored as deficits recovered. Our work showed the potential of a time-resolved method to reveal clinically relevant dynamics of large-scale brain networks.

scholarly journals Predicting Post-Stroke Somatosensory Function from Resting-State Functional Connectivity: A Feasibility Study

2021 ◽  
Vol 11 (11) ◽  
pp. 1388
Author(s):  
Xiaoyun Liang ◽  
Chia-Lin Koh ◽  
Chun-Hung Yeh ◽  
Peter Goodin ◽  
Gemma Lamp ◽  
...  
Keyword(s):  
Machine Learning ◽  
Functional Connectivity ◽  
Brain Networks ◽  
High Order ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Post Stroke ◽  
Study Results ◽  
Somatosensory Function ◽  
Low Order

Accumulating evidence shows that brain functional deficits may be impacted by damage to remote brain regions. Recent advances in neuroimaging suggest that stroke impairment can be better predicted based on disruption to brain networks rather than from lesion locations or volumes only. Our aim was to explore the feasibility of predicting post-stroke somatosensory function from brain functional connectivity through the application of machine learning techniques. Somatosensory impairment was measured using the Tactile Discrimination Test. Functional connectivity was employed to model the global brain function. Behavioral measures and MRI were collected at the same timepoint. Two machine learning models (linear regression and support vector regression) were chosen to predict somatosensory impairment from disrupted networks. Along with two feature pools (i.e., low-order and high-order functional connectivity, or low-order functional connectivity only) engineered, four predictive models were built and evaluated in the present study. Forty-three chronic stroke survivors participated this study. Results showed that the regression model employing both low-order and high-order functional connectivity can predict outcomes based on correlation coefficient of r = 0.54 (p = 0.0002). A machine learning predictive approach, involving high- and low-order modelling, is feasible for the prediction of residual somatosensory function in stroke patients using functional brain networks.

Brain Imaging Could Predict Aphasia Post-Stroke

ASHA Leader ◽  
2016 ◽  
Vol 21 (10) ◽  
pp. 14-14
Keyword(s):  
Brain Imaging ◽  
Post Stroke

Lessons From the Neural Bases of Speech and Voice

2011 ◽  
Vol 21 (1) ◽  
pp. 5-14
Author(s):  
Christy L. Ludlow
Keyword(s):  
Brain Networks ◽  
Neural Substrates ◽  
Voice Behavior ◽  
Therapeutic Approaches ◽  
Neural Bases ◽  
Sound Foundation ◽  
The Brain ◽  
Normal Speech

The premise of this article is that increased understanding of the brain bases for normal speech and voice behavior will provide a sound foundation for developing therapeutic approaches to establish or re-establish these functions. The neural substrates involved in speech/voice behaviors, the types of muscle patterning for speech and voice, the brain networks involved and their regulation, and how they can be externally modulated for improving function will be addressed.

Transcranial Electrical Stimulation in Post-Stroke Cognitive Rehabilitation

2016 ◽  
Vol 21 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Silvia Convento ◽  
Cristina Russo ◽  
Luca Zigiotto ◽  
Nadia Bolognini
Keyword(s):  
Electrical Stimulation ◽  
Cognitive Rehabilitation ◽  
Cognitive Disorders ◽  
Spatial Neglect ◽  
Transcranial Electrical Stimulation ◽  
Clinical Settings ◽  
Post Stroke ◽  
Neuropsychological Disorders ◽  
Current State ◽  
Stimulation Technique

Abstract. Cognitive rehabilitation is an important area of neurological rehabilitation, which aims at the treatment of cognitive disorders due to acquired brain damage of different etiology, including stroke. Although the importance of cognitive rehabilitation for stroke survivors is well recognized, available cognitive treatments for neuropsychological disorders, such as spatial neglect, hemianopia, apraxia, and working memory, are overall still unsatisfactory. The growing body of evidence supporting the potential of the transcranial Electrical Stimulation (tES) as tool for interacting with neuroplasticity in the human brain, in turn for enhancing perceptual and cognitive functions, has obvious implications for the translation of this noninvasive brain stimulation technique into clinical settings, in particular for the development of tES as adjuvant tool for cognitive rehabilitation. The present review aims at presenting the current state of art concerning the use of tES for the improvement of post-stroke visual and cognitive deficits (except for aphasia and memory disorders), showing the therapeutic promises of this technique and offering some suggestions for the design of future clinical trials. Although this line of research is still in infancy, as compared to the progresses made in the last years in other neurorehabilitation domains, current findings appear very encouraging, supporting the development of tES for the treatment of post-stroke cognitive impairments.

Common Learning Mechanisms for Language and Music Grammar Acquisition

2014 ◽  
Author(s):  
Erica Knowles ◽  
Erin Ingvalson ◽  
Patrick Wong
Keyword(s):  
Learning Mechanisms ◽  
Grammar Acquisition ◽  
Language And Music ◽  
Common Learning

Factors Predicting Quality of Life among Post-Stroke Patients Living in Community

2013 ◽  
Author(s):  
Kultida Panidchakul ◽  
Suneerut Boonsin
Keyword(s):  
Quality Of Life ◽  
Stroke Patients ◽  
Post Stroke
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