scholarly journals Visualization of Altered Neurovascular Coupling in Chronic Stroke Patients using Multimodal Functional MRI

2012 ◽  
Vol 32 (11) ◽  
pp. 2044-2054 ◽  
Author(s):  
Jakob U Blicher ◽  
Charlotte J Stagg ◽  
Jacinta O'Shea ◽  
Leif Østergaard ◽  
Bradley J MacIntosh ◽  
...  
Keyword(s):  
Motor Impairment ◽  
Neurovascular Coupling ◽  
Chronic Stroke ◽  
Blood Oxygenation ◽  
Cortical Reorganization ◽  
Motor Tasks ◽  
Stroke Patients ◽  
Bold Responses ◽  
Oxygenation Level ◽  
Crucial Information

Evaluation of cortical reorganization in chronic stroke patients requires methods to accurately localize regions of neuronal activity. Blood oxygenation level-dependent ( BOLD) functional magnetic resonance imaging (fMRI) is frequently employed; however, BOLD contrast depends on specific coupling relationships between the cerebral metabolic rate of oxygen ( CMRO2), cerebral blood flow ( CBF), and volume ( CBV), which may not exist following stroke. The aim of this study was to understand whether CSF-weighted ( CBFw) and CSV-weighted ( CBVw) fMRI could be used in sequence with BOLD to characterize neurovascular coupling mechanisms poststroke. Chronic stroke patients ( n = 11) with motor impairment and age-matched controls ( n = 11) performed four sets of unilateral motor tasks (60 seconds/30 seconds off/on) during CBFw, CBVw, and BOLD fMRI acquisition. While control participants elicited mean BOLD, CBFw, and CBVw responses in motor cortex ( P < 0.01), patients showed only mean changes in CBF ( P < 0.01) and CBV ( P < 0.01), but absent mean BOLD responses ( P = 0.20). BOLD intersubject variability was consistent with differing coupling indices between CBF, CBV, and CMRO2. Thus, CBFw and/or CBVw fMRI may provide crucial information not apparent from BOLD in these patients. A table is provided outlining distinct vascular and metabolic uncoupling possibilities that elicit different BOLD responses, and the strengths and limitations of the multimodal protocol are summarized.

scholarly journals Effects of Passive Leg Movement on the Oxygenation Level of Lower Limb Muscle in Chronic Stroke Patients

2007 ◽  
Vol 22 (1) ◽  
pp. 40-49 ◽  
Author(s):  
Enkhsaihan Jigjid ◽  
Noritaka Kawashima ◽  
Hisayoshi Ogata ◽  
Kimitaka Nakazawa ◽  
Masami Akai ◽  
...  
Keyword(s):  
Lower Limb ◽  
Chronic Stroke ◽  
Lower Limb Muscle ◽  
Limb Muscle ◽  
Stroke Patients ◽  
Oxygenation Level ◽  
Leg Movement

scholarly journals The Influence of Primary Motor Cortex Inhibition on Upper Limb Impairment and Function in Chronic Stroke: A Multimodal Study

2019 ◽  
Vol 33 (2) ◽  
pp. 130-140 ◽  
Author(s):  
Ronan A. Mooney ◽  
Suzanne J. Ackerley ◽  
Deshan K. Rajeswaran ◽  
John Cirillo ◽  
P. Alan Barber ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Upper Limb ◽  
Primary Motor Cortex ◽  
Motor Impairment ◽  
Intracortical Inhibition ◽  
Chronic Stroke ◽  
Stroke Patients ◽  
Gaba Concentration ◽  
Chronic Stage ◽  
And Function

Background. Stroke is a leading cause of adult disability owing largely to motor impairment and loss of function. After stroke, there may be abnormalities in γ-aminobutyric acid (GABA)-mediated inhibitory function within primary motor cortex (M1), which may have implications for residual motor impairment and the potential for functional improvements at the chronic stage. Objective. To quantify GABA neurotransmission and concentration within ipsilesional and contralesional M1 and determine if they relate to upper limb impairment and function at the chronic stage of stroke. Methods. Twelve chronic stroke patients and 16 age-similar controls were recruited for the study. Upper limb impairment and function were assessed with the Fugl-Meyer Upper Extremity Scale and Action Research Arm Test. Threshold tracking paired-pulse transcranial magnetic stimulation protocols were used to examine short- and long-interval intracortical inhibition and late cortical disinhibition. Magnetic resonance spectroscopy was used to evaluate GABA concentration. Results. Short-interval intracortical inhibition was similar between patients and controls ( P = .10). Long-interval intracortical inhibition was greater in ipsilesional M1 compared with controls ( P < .001). Patients who did not exhibit late cortical disinhibition in ipsilesional M1 were those with greater upper limb impairment and worse function ( P = .002 and P = .017). GABA concentration was lower within ipsilesional ( P = .009) and contralesional ( P = .021) M1 compared with controls, resulting in an elevated excitation-inhibition ratio for patients. Conclusion. These findings indicate that ipsilesional and contralesional M1 GABAergic inhibition are altered in this small cohort of chronic stroke patients. Further study is warranted to determine how M1 inhibitory networks might be targeted to improve motor function.

scholarly journals Combined Brain and Peripheral Nerve Stimulation in Chronic Stroke Patients With Moderate to Severe Motor Impairment

2017 ◽  
Vol 21 (2) ◽  
pp. 176-183 ◽  
Author(s):  
Isabella S. Menezes ◽  
Leonardo G. Cohen ◽  
Eduardo A. Mello ◽  
André G. Machado ◽  
Paul Hunter Peckham ◽  
...  
Keyword(s):  
Peripheral Nerve ◽  
Nerve Stimulation ◽  
Motor Impairment ◽  
Chronic Stroke ◽  
Peripheral Nerve Stimulation ◽  
Stroke Patients ◽  
Severe Motor ◽  
Severe Motor Impairment

scholarly journals Methods for Determining Frequency- and Region-Dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

2009 ◽  
Vol 101 (1) ◽  
pp. 491-502 ◽  
Author(s):  
Roberto Martuzzi ◽  
Micah M. Murray ◽  
Reto A. Meuli ◽  
Jean-Philippe Thiran ◽  
Philippe P. Maeder ◽  
...  
Keyword(s):  
Human Subjects ◽  
Brain Regions ◽  
Source Model ◽  
Blood Oxygenation ◽  
Low Frequencies ◽  
Functional Regions ◽  
Wide Range ◽  
Bold Responses ◽  
Oxygenation Level ◽  
The Relationship

The relationship between electrophysiological and functional magnetic resonance imaging (fMRI) signals remains poorly understood. To date, studies have required invasive methods and have been limited to single functional regions and thus cannot account for possible variations across brain regions. Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0–256 Hz) throughout the entire brain volume. This method was applied in a study where human subjects completed separate fMRI and EEG sessions while performing a passive visual task. Intracranial LFPs were estimated from the scalp-recorded data using the ELECTRA source model. We compared statistical images from BOLD signals with statistical images of each frequency of the eLFPs. In agreement with previous studies in animals, we found a significant correspondence between LFP and BOLD statistical images in the gamma band (44–78 Hz) within primary visual cortices. In addition, significant correspondence was observed at low frequencies (<14 Hz) and also at very high frequencies (>100 Hz). Effects within extrastriate visual areas showed a different correspondence that not only included those frequency ranges observed in primary cortices but also additional frequencies. Results therefore suggest that the relationship between electrophysiological and hemodynamic signals thus might vary both as a function of frequency and anatomical region.

Optogenetic fMRI Sheds Light on the Neural Basis of the BOLD Signal

2010 ◽  
Vol 104 (4) ◽  
pp. 1838-1840 ◽  
Author(s):  
Helen. S. Palmer
Keyword(s):  
Magnetic Resonance Imaging ◽  
Blood Oxygenation Level Dependent ◽  
Blood Oxygenation ◽  
Bold Signal ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Neural Basis ◽  
Bold Responses ◽  
Blood Oxygenation Level ◽  
Oxygenation Level

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used as a measure of neuronal activity, despite an incomplete understanding of the hemodynamic and neural bases for BOLD signals. Recent work by Lee and colleagues investigated whether activating genetically specified neurons elicits BOLD responses. Integrating optogenetic control of specific cells and fMRI showed that stimulating excitatory neurons triggers a positive BOLD signal with conventional kinetics locally and delayed weaker BOLD signals distally.

scholarly journals A sock for foot-drop: A preliminary study on two chronic stroke patients

2013 ◽  
Vol 38 (5) ◽  
pp. 425-430
Author(s):  
Sarah Prenton ◽  
Laurence PJ Kenney ◽  
Glen Cooper ◽  
Matthew J Major
Keyword(s):  
Single Case ◽  
Motor Impairment ◽  
Chronic Stroke ◽  
Community Dwelling ◽  
Foot Drop ◽  
Attractive Alternative ◽  
Stroke Patients ◽  
Ankle Foot Orthosis ◽  
General Improvement ◽  
Foot Orthosis

Background: Foot-drop is a common motor impairment of chronic stroke patients, which may be addressed with an ankle foot orthosis. Although there is reasonable evidence of effectiveness for ankle foot orthoses, user compliance is sometimes poor. This study investigated a new alternative to the ankle foot orthosis, the dorsiflex sock. Case description and methods: The dorsiflex sock was evaluated using an A-B single case experimental design. Two community-dwelling, chronic stroke patients with foot-drop participated in this study. Measures were selected to span the International Classification of Function, Disability and Health domains and user views on the dorsiflex sock were also collected. Findings and outcomes: The dorsiflex sock was not effective in improving participants’ walking symmetry, speed or energy expenditure. Participant 1 showed improvement in the distance he could walk in 6 min when using the dorsiflex sock, but this was in keeping with a general improvement trend over the course of this study. However, both participants viewed the dorsiflex sock positively and reported a positive effect on their walking. Conclusion: Despite positive user perceptions, the study found no clear evidence that dorsiflex sock is effective in improving foot-drop. Clinical relevance Although the dorsiflex sock offers an attractive alternative to an ankle foot orthosis, the case studies found no clear evidence of its efficacy. Clinicians should view this device with caution until further research becomes available.

scholarly journals Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke

2020 ◽  
Vol 34 (5) ◽  
pp. 428-439 ◽  
Author(s):  
Ceren Tozlu ◽  
Dylan Edwards ◽  
Aaron Boes ◽  
Douglas Labar ◽  
K. Zoe Tsagaris ◽  
...  
Keyword(s):  
Machine Learning ◽  
Upper Extremity ◽  
Upper Limb ◽  
Motor Impairment ◽  
Chronic Stroke ◽  
Response To Therapy ◽  
Stroke Patients ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
The Difference

Background. Accurate prediction of clinical impairment in upper-extremity motor function following therapy in chronic stroke patients is a difficult task for clinicians but is key in prescribing appropriate therapeutic strategies. Machine learning is a highly promising avenue with which to improve prediction accuracy in clinical practice. Objectives. The objective was to evaluate the performance of 5 machine learning methods in predicting postintervention upper-extremity motor impairment in chronic stroke patients using demographic, clinical, neurophysiological, and imaging input variables. Methods. A total of 102 patients (female: 31%, age 61 ± 11 years) were included. The upper-extremity Fugl-Meyer Assessment (UE-FMA) was used to assess motor impairment of the upper limb before and after intervention. Elastic net (EN), support vector machines, artificial neural networks, classification and regression trees, and random forest were used to predict postintervention UE-FMA. The performances of methods were compared using cross-validated R2. Results. EN performed significantly better than other methods in predicting postintervention UE-FMA using demographic and baseline clinical data (median [Formula: see text] P < .05). Preintervention UE-FMA and the difference in motor threshold (MT) between the affected and unaffected hemispheres were the strongest predictors. The difference in MT had greater importance than the absence or presence of a motor-evoked potential (MEP) in the affected hemisphere. Conclusion. Machine learning methods may enable clinicians to accurately predict a chronic stroke patient’s postintervention UE-FMA. Interhemispheric difference in the MT is an important predictor of chronic stroke patients’ response to therapy and, therefore, could be included in prospective studies.

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