Literature DB >> 27511048

Small-World Characteristics of Cortical Connectivity Changes in Acute Stroke.

Pietro Caliandro1,2, Fabrizio Vecchio3, Francesca Miraglia3, Giuseppe Reale4, Giacomo Della Marca4, Giuseppe La Torre5, Giordano Lacidogna4, Chiara Iacovelli4,2, Luca Padua4,2, Placido Bramanti6, Paolo Maria Rossini4,3.   

Abstract

Background After cerebral ischemia, disruption and subsequent reorganization of functional connections occur both locally and remote to the lesion. Recently, complexity of brain connectivity has been described using graph theory, a mathematical approach that depicts important properties of complex systems by quantifying topologies of network representations. Functional and dynamic changes of brain connectivity can be reliably analyzed via electroencephalography (EEG) recordings even when they are not yet reflected in structural changes of connections. Objective We tested whether and how ischemic stroke in the acute stage may determine changes in small-worldness of cortical networks as measured by cortical sources of EEG. Methods Graph characteristics of EEG of 30 consecutive stroke patients in acute stage (no more than 5 days after the event) were examined. Connectivity analysis was performed using eLORETA in both hemispheres. Results Network rearrangements were mainly detected in delta, theta, and alpha bands when patients were compared with healthy subjects. In delta and alpha bands similar findings were observed in both hemispheres regardless of the side of ischemic lesion: bilaterally decreased small-worldness in the delta band and bilaterally increased small-worldness in the alpha2 band. In the theta band, bilaterally decreased small-worldness was observed only in patients with stroke in the left hemisphere. Conclusions After an acute stroke, brain cortex rearranges its network connections diffusely, in a frequency-dependent modality probably in order to face the new anatomical and functional frame.
© The Author(s) 2016.

Entities:  

Keywords:  connectivity; cortex; electroencephalography; graph theory; plasticity; stroke

Mesh:

Year:  2016        PMID: 27511048     DOI: 10.1177/1545968316662525

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  25 in total

Review 1.  Effective assessments of electroencephalography during stroke recovery: contemporary approaches and considerations.

Authors:  Kartik K Iyer
Journal:  J Neurophysiol       Date:  2017-06-21       Impact factor: 2.714

2.  Multimodal neuroimaging study reveals dissociable processes between structural and functional networks in patients with subacute intracerebral hemorrhage.

Authors:  Xiaobing Zhang; Xuebin Yu; Qingquan Bao; Liming Yang; Yu Sun; Peng Qi
Journal:  Med Biol Eng Comput       Date:  2019-02-09       Impact factor: 2.602

3.  Disrupted brain functional network topology in unilateral acute brainstem ischemic stroke.

Authors:  Mengye Shi; Shenghua Liu; Huiyou Chen; Wen Geng; Xindao Yin; Yu-Chen Chen; Liping Wang
Journal:  Brain Imaging Behav       Date:  2021-02       Impact factor: 3.978

4.  Reply: Defining a functional network homeostasis after stroke: EEG-based approach is complementary to functional MRI.

Authors:  Mohit H Adhikari; Gustavo Deco; Maurizio Corbetta
Journal:  Brain       Date:  2017-12-01       Impact factor: 13.501

Review 5.  Brain networks and their relevance for stroke rehabilitation.

Authors:  Adrian G Guggisberg; Philipp J Koch; Friedhelm C Hummel; Cathrin M Buetefisch
Journal:  Clin Neurophysiol       Date:  2019-04-15       Impact factor: 3.708

6.  Small-World Propensity Reveals the Frequency Specificity of Resting State Networks.

Authors:  Riccardo Iandolo; Marianna Semprini; Stefano Buccelli; Federico Barban; Mingqi Zhao; Jessica Samogin; Gaia Bonassi; Laura Avanzino; Dante Mantini; Michela Chiappalone
Journal:  IEEE Open J Eng Med Biol       Date:  2020-02-14

7.  Alterations in resting-state functional connectivity after brain posterior lesions reflect the functionality of the visual system in hemianopic patients.

Authors:  Jessica Gallina; Marco Zanon; Ezequiel Mikulan; Mattia Pietrelli; Silvia Gambino; Agustín Ibáñez; Caterina Bertini
Journal:  Brain Struct Funct       Date:  2022-05-19       Impact factor: 3.748

8.  Low-Frequency Oscillations Are a Biomarker of Injury and Recovery After Stroke.

Authors:  Jessica M Cassidy; Anirudh Wodeyar; Jennifer Wu; Kiranjot Kaur; Ashley K Masuda; Ramesh Srinivasan; Steven C Cramer
Journal:  Stroke       Date:  2020-04-17       Impact factor: 7.914

9.  Abnormal Metabolic Connectivity in Rats at the Acute Stage of Ischemic Stroke.

Authors:  Shengxiang Liang; Xiaofeng Jiang; Qingqing Zhang; Shaofeng Duan; Tianhao Zhang; Qi Huang; Xi Sun; Hua Liu; Jie Dong; Weilin Liu; Jing Tao; Shujun Zhao; Binbin Nie; Lidian Chen; Baoci Shan
Journal:  Neurosci Bull       Date:  2018-08-06       Impact factor: 5.203

10.  Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients.

Authors:  Chiara Fanciullacci; Alessandro Panarese; Vincenzo Spina; Michael Lassi; Alberto Mazzoni; Fiorenzo Artoni; Silvestro Micera; Carmelo Chisari
Journal:  Front Hum Neurosci       Date:  2021-07-01       Impact factor: 3.169

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