Literature DB >> 25741721

Common behavioral clusters and subcortical anatomy in stroke.

Maurizio Corbetta1, Lenny Ramsey2, Alicia Callejas3, Antonello Baldassarre3, Carl D Hacker4, Joshua S Siegel5, Serguei V Astafiev3, Jennifer Rengachary3, Kristina Zinn3, Catherine E Lang6, Lisa Tabor Connor7, Robert Fucetola3, Michael Strube8, Alex R Carter3, Gordon L Shulman3.   

Abstract

A long-held view is that stroke causes many distinct neurological syndromes due to damage of specialized cortical and subcortical centers. However, it is unknown if a syndrome-based description is helpful in characterizing behavioral deficits across a large number of patients. We studied a large prospective sample of first-time stroke patients with heterogeneous lesions at 1-2 weeks post-stroke. We measured behavior over multiple domains and lesion anatomy with structural MRI and a probabilistic atlas of white matter pathways. Multivariate methods estimated the percentage of behavioral variance explained by structural damage. A few clusters of behavioral deficits spanning multiple functions explained neurological impairment. Stroke topography was predominantly subcortical, and disconnection of white matter tracts critically contributed to behavioral deficits and their correlation. The locus of damage explained more variance for motor and language than memory or attention deficits. Our findings highlight the need for better models of white matter damage on cognition.
Copyright © 2015 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 25741721      PMCID: PMC4646844          DOI: 10.1016/j.neuron.2015.02.027

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  48 in total

1.  Overlapping mechanisms of attention and spatial working memory.

Authors:  E Awh; J Jonides
Journal:  Trends Cogn Sci       Date:  2001-03-01       Impact factor: 20.229

2.  Voxel-based lesion-symptom mapping.

Authors:  Elizabeth Bates; Stephen M Wilson; Ayse Pinar Saygin; Frederic Dick; Martin I Sereno; Robert T Knight; Nina F Dronkers
Journal:  Nat Neurosci       Date:  2003-05       Impact factor: 24.884

3.  Stability of muscle synergies for voluntary actions after cortical stroke in humans.

Authors:  Vincent C K Cheung; Lamberto Piron; Michela Agostini; Stefano Silvoni; Andrea Turolla; Emilio Bizzi
Journal:  Proc Natl Acad Sci U S A       Date:  2009-10-30       Impact factor: 11.205

4.  Underlying structure of the National Institutes of Health Stroke Scale: results of a factor analysis. NINDS tPA Stroke Trial Investigators.

Authors:  P Lyden; M Lu; C Jackson; J Marler; R Kothari; T Brott; J Zivin
Journal:  Stroke       Date:  1999-11       Impact factor: 7.914

5.  Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people. The Cardiovascular Health Study.

Authors:  W T Longstreth; T A Manolio; A Arnold; G L Burke; N Bryan; C A Jungreis; P L Enright; D O'Leary; L Fried
Journal:  Stroke       Date:  1996-08       Impact factor: 7.914

6.  Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke.

Authors:  Alex R Carter; Serguei V Astafiev; Catherine E Lang; Lisa T Connor; Jennifer Rengachary; Michael J Strube; Daniel L W Pope; Gordon L Shulman; Maurizio Corbetta
Journal:  Ann Neurol       Date:  2010-03       Impact factor: 10.422

7.  Microstructural status of ipsilesional and contralesional corticospinal tract correlates with motor skill in chronic stroke patients.

Authors:  Judith D Schaechter; Zachary P Fricker; Katherine L Perdue; Karl G Helmer; Mark G Vangel; Douglas N Greve; Nikos Makris
Journal:  Hum Brain Mapp       Date:  2009-11       Impact factor: 5.038

8.  Aphasia and neglect after subcortical stroke. A clinical/cerebral perfusion correlation study.

Authors:  D Perani; G Vallar; S Cappa; C Messa; F Fazio
Journal:  Brain       Date:  1987-10       Impact factor: 13.501

9.  Network measures predict neuropsychological outcome after brain injury.

Authors:  David E Warren; Jonathan D Power; Joel Bruss; Natalie L Denburg; Eric J Waldron; Haoxin Sun; Steven E Petersen; Daniel Tranel
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-15       Impact factor: 11.205

Review 10.  Lesion analysis of the brain areas involved in language comprehension.

Authors:  Nina F Dronkers; David P Wilkins; Robert D Van Valin; Brenda B Redfern; Jeri J Jaeger
Journal:  Cognition       Date:  2004 May-Jun
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  149 in total

1.  Brain networks' functional connectivity separates aphasic deficits in stroke.

Authors:  Antonello Baldassarre; Nicholas V Metcalf; Gordon L Shulman; Maurizio Corbetta
Journal:  Neurology       Date:  2018-12-05       Impact factor: 9.910

2.  Differential white matter involvement associated with distinct visuospatial deficits after right hemisphere stroke.

Authors:  Alex R Carter; Mark P McAvoy; Joshua S Siegel; Xin Hong; Serguei V Astafiev; Jennifer Rengachary; Kristi Zinn; Nicholas V Metcalf; Gordon L Shulman; Maurizio Corbetta
Journal:  Cortex       Date:  2016-12-20       Impact factor: 4.027

3.  Visual neglect after left-hemispheric lesions: a voxel-based lesion-symptom mapping study in 121 acute stroke patients.

Authors:  Lena-Alexandra Beume; Markus Martin; Christoph P Kaller; Stefan Klöppel; Charlotte S M Schmidt; Horst Urbach; Karl Egger; Michel Rijntjes; Cornelius Weiller; Roza M Umarova
Journal:  Exp Brain Res       Date:  2016-09-16       Impact factor: 1.972

4.  Pathological structure of visuospatial neglect: A comprehensive multivariate analysis of spatial and non-spatial aspects.

Authors:  Yusaku Takamura; Shintaro Fujii; Satoko Ohmatsu; Shu Morioka; Noritaka Kawashima
Journal:  iScience       Date:  2021-03-16

5.  Normalization of network connectivity in hemispatial neglect recovery.

Authors:  Lenny E Ramsey; Joshua S Siegel; Antonello Baldassarre; Nicholas V Metcalf; Kristina Zinn; Gordon L Shulman; Maurizio Corbetta
Journal:  Ann Neurol       Date:  2016-06-09       Impact factor: 10.422

6.  Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke.

Authors:  Joshua Sarfaty Siegel; Lenny E Ramsey; Abraham Z Snyder; Nicholas V Metcalf; Ravi V Chacko; Kilian Weinberger; Antonello Baldassarre; Carl D Hacker; Gordon L Shulman; Maurizio Corbetta
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-11       Impact factor: 11.205

7.  Using machine learning-based lesion behavior mapping to identify anatomical networks of cognitive dysfunction: Spatial neglect and attention.

Authors:  Daniel Wiesen; Christoph Sperber; Grigori Yourganov; Christopher Rorden; Hans-Otto Karnath
Journal:  Neuroimage       Date:  2019-07-09       Impact factor: 6.556

8.  Damage to the shortest structural paths between brain regions is associated with disruptions of resting-state functional connectivity after stroke.

Authors:  Joseph C Griffis; Nicholas V Metcalf; Maurizio Corbetta; Gordon L Shulman
Journal:  Neuroimage       Date:  2020-01-30       Impact factor: 6.556

9.  Multivariate machine learning-based language mapping in glioma patients based on lesion topography.

Authors:  Nan Zhang; Binke Yuan; Jing Yan; Jingliang Cheng; Junfeng Lu; Jinsong Wu
Journal:  Brain Imaging Behav       Date:  2021-02-22       Impact factor: 3.978

10.  Mapping mania symptoms based on focal brain damage.

Authors:  Gonçalo Cotovio; Daniel Talmasov; J Bernardo Barahona-Corrêa; Joey Hsu; Suhan Senova; Ricardo Ribeiro; Louis Soussand; Ana Velosa; Vera Cruz E Silva; Natalia Rost; Ona Wu; Alexander L Cohen; Albino J Oliveira-Maia; Michael D Fox
Journal:  J Clin Invest       Date:  2020-10-01       Impact factor: 14.808

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