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Hemodynamic response function in patients with stroke-induced aphasia: implications for fMRI data analysis
B Bonakdarpour1, T B Parrish, C K Thompson
1Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL 60208, USA. borna@northwestern.edu
Abstract:
Functional MRI is based on changes in cerebral microvasculature triggered by increased neuronal oxidative metabolism. This change in blood flow follows a pattern known as the hemodynamic response function (HRF), which typically peaks 4-6 s following stimulus delivery. However, in the presence of cerebrovascular disease the HRF may not follow this normal pattern, due to either the temporal signal to noise (tSNR) ratio or delays in the HRF, which may result in misinterpretation or underestimation of fMRI signal. The present study examined the HRF and SNR in five individuals with aphasia resulting from stroke and four unimpaired participants using a lexical decision task and a long trial event-related design. T1-weighted images were acquired using an MP-RAGE sequence and BOLD T2*-weighted images were acquired using Echo Planar Imaging to measure time to peak (TTP) in the HRF. Data were analyzed using Brain Voyager in four anatomic regions known to be involved in language processing: Broca's area and the posterior perisylvian network (PPN) (including Wernicke's area, the angular and supramarginal gyri) and right hemisphere homologues of these regions. The occipital area also was examined as a control region. Analyses showed that the TTP in three out of five patients in the left perisylvian area was increased significantly as compared to normal individuals and the left primary visual cortex in the same patients. In two other patients no significant delays were detected. We also found that the SNR for BOLD signal detection may by insufficient in damaged areas. These findings indicate that obtaining physiologic (TTP) and quality assurance (tSNR) information is essential for studying activation patterns in brain-damaged patients in order to avoid errors in interpretation of the data. An example of one such misinterpretation and the need for alternative data analysis strategies is discussed.
Insights
Functional MRI (fMRI) signal changes in stroke patients with aphasia can be delayed or reduced due to cerebrovascular disease. Assessing hemodynamic response function (HRF) time to peak (TTP) and signal-to-noise ratio (SNR) is crucial for accurate fMRI interpretation.
Area of Science:
- Neuroimaging
- Cognitive Neuroscience
- Neurology
Background:
- Functional MRI (fMRI) relies on detecting hemodynamic responses linked to neuronal activity.
- The hemodynamic response function (HRF) typically peaks 4-6 seconds post-stimulus.
- Cerebrovascular disease can alter the HRF, potentially causing misinterpretation of fMRI data.
Purpose of the Study:
- To investigate the hemodynamic response function (HRF) and signal-to-noise ratio (SNR) in individuals with post-stroke aphasia.
- To determine if cerebrovascular disease affects the timing (time to peak - TTP) and quality of fMRI signals.
- To highlight the importance of physiological and quality assurance metrics in fMRI analysis for brain-damaged populations.
Main Methods:
- Employed a lexical decision task with a long-trial event-related design in fMRI.
- Acquired T1-weighted and BOLD T2*-weighted images to measure HRF time to peak (TTP).
- Analyzed data in language-processing regions (Broca's, posterior perisylvian network) and control areas using Brain Voyager.
Main Results:
- Significantly increased TTP was observed in the left perisylvian area of 3 out of 5 aphasia patients compared to controls.
- No significant HRF delays were detected in the remaining two patients.
- Signal-to-noise ratio (SNR) was found to be insufficient in some damaged brain areas.
Conclusions:
- Physiological (TTP) and quality assurance (tSNR) data are essential for accurate fMRI interpretation in brain-damaged individuals.
- Deviations in HRF timing and reduced SNR in stroke patients can lead to underestimation or misinterpretation of brain activation.
- Alternative data analysis strategies may be necessary to account for altered fMRI signal characteristics in clinical populations.
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