Hemodynamic response function in temporal lobe epilepsy with interictal regional slow wave: An EEG-fMRI study

Decoding neural events from fMRI BOLD signal: A comparison of existing approaches and development of a new algorithm

In the rodent brain the hemodynamic response to a brief external stimulus changes significantly during development. Analogous changes in human infants would complicate the determination and use of the hemodynamic response function (HRF) for functional magnetic resonance imaging (fMRI) in developing populations. We aimed to characterize HRF in human infants before and after the normal time of birth using rapid sampling of the Blood Oxygen Level Dependent (BOLD) signal. A somatosensory stimulus and an event related experimental design were used to collect data from 10 healthy adults, 15 sedated infants at term corrected post menstrual age (PMA) (median 41 + 1 weeks), and 10 preterm infants (median PMA 34 + 4 weeks). A positive amplitude HRF waveform was identified across all subject groups, with a systematic maturational trend in terms of decreasing time-to-peak and increasing positive peak amplitude associated with increasing age. Application of the age-appropriate HRF models to fMRI data significantly improved the precision of the fMRI analysis. These findings support the notion of a structured development in the brain's response to stimuli across the last trimester of gestation and beyond.

Multisite contributions are essential to improve the reliability and statistical power of imaging studies but introduce a complexity because of different acquisition protocols and scanners. The hemodynamic response function (HRF) is the transform that relates neural activity to the measured blood oxygenation level-dependent (BOLD) signal in MRI and contains information about the latency, amplitude, and duration of neuronal activations. Acquisition variabilities, without adding harmonization techniques, can severely limit our ability to characterize spatial effects. To address this problem, we propose to study and remove variabilities of the sampling rate and scanners on estimates of the HRF. We computed the HRF using a blind deconvolution method in 547 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) across 62 sites and 18 scanners. The approach consists of studying the changes of the response according to repetition times (TR) and scanner models. We applied ComBAT, a statistical multi-site harmonization technique, to evaluate and reduce the scanner and repetition time effects and used the Wilcoxon rank sum test to assess the performance of the harmonization. Results show high scanner and repetition time variabilities (|d| ≥ 0.38, p = 4.5 × 10-5) across features, indicating that using harmonization is crucial in multi-site studies. ComBAT successfully removes the sampling effects and reduces the variance between scanners for 7 out of 10 of the HRF features (|d| ≤ 0.05, p = 0.0052). Scanners effects have been characterized on multi-site datasets, but the repetition time impact has been less studied. We showed that the use of different values of repetition time leads to changes in HRF behavior. Regression modeling changes in the HRF on the harmonized data are not significant (p = 0.0401) which does not allow to conclude how HRF changes with aging.

In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level-dependent (BOLD) responses. Negative responses are also occasionally seen and have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding positive response might explain the negative BOLD seen in the focus. Eighty-two patients with focal epilepsy who underwent EEG-fMRI at 3T were retrospectively studied. Studies with a focal negative BOLD response in the region of the spike field were reanalyzed using models with hemodynamic response functions (HRFs) peaking from -9 to +9 s around the spike. Eight patients met the inclusion criteria, showing negative BOLD responses in the spike field on standard analysis. None had positive BOLD responses immediately adjacent to the areas of deactivation. Regions of deactivation were found to have congruent preceding positive responses in two cases. These early activations were seen at the combined maps of -5 to -9 s. This study indicates that in a small proportion of patients with focal epilepsy in whom the standard analysis reveals focal negative responses, an earlier positive BOLD response is probably the cause. The origin of negative BOLD signal changes in the focus as a result of an epileptic event remains, however, unexplained in most of the patients in whom it occurs.

The selection of the appropriate hemodynamic response function (HRF) for signal modeling in functional magnetic resonance imaging (fMRI) is important. Although the use of the boxcar-shaped hemodynamic response function (BHRF) and canonical hemodynamic response (CHRF) has gained increasing popularity in rodent fMRI studies, whether the selected HRF affects the results of rodent fMRI has not been fully elucidated. Here we investigated the signal change and t-statistic sensitivities of BHRF, CHRF, and impulse response function (IRF). The effect of HRF selection on different tasks was analyzed by using data collected from two groups of rats receiving either 3 mA whisker pad or 3 mA forepaw electrical stimulations (n = 10 for each group). Under whisker pad stimulation with large blood-oxygen-level dependent (BOLD) signal change (4.31 ± 0.42%), BHRF significantly underestimated signal changes (P < 0.001) and t-statistics (P < 0.001) compared with CHRF or IRF. CHRF and IRF did not provide significantly different t-statistics (P > 0.05). Under forepaw stimulation with small BOLD signal change (1.71 ± 0.34%), different HRFs provided insignificantly different t-statistics (P > 0.05). Therefore, the selected HRF can influence data analysis in rodent fMRI experiments with large BOLD responses but not in those with small BOLD responses.

Reliability of the depth-dependent high-resolution BOLD hemodynamic response in human visual cortex and vicinity

We present a new method for the calculation of a blood oxygen level dependent (BOLD) signal which is meaningful for a quantitative comparison with near infrared spectroscopy (NIRS) data. Since optical tomography of the human brain still poses several difficulties, in this study we propose a way to project the BOLD signal on a two-dimensional (2D) map for comparison with NIRS data. The underlying assumption is that fMRI and NIRS are sensitive to similar aspects of the hemodynamic changes occurring during a functional task, and therefore they should have similar spatial and temporal features. We present a case study of functional activation during a finger-tapping test where we used the new method for the calculation of BOLD signal. For every optical source-detector pair we calculated a weighted BOLD signal by using a photon hitting-density weight function, and by using a simple back-projection algorithm we were able to generate BOLD 2D maps. We found that the weighted BOLD signals calculated from different source-detector pairs scale in a similar way to the corresponding oxy and deoxy-hemeoglobin concentration changes calculated from NIRS data, for most of the time range of the task. Therefore the BOLD 2D maps were quantitatively similar to the optical maps calculated at different times during the protocol.

BOLD fMRI has become a prevalent method to study cerebral sensory processing in rodent disease models, including pain and mechanical hypersensitivity. fMRI data analysis is frequently combined with a general-linear-model (GLM) -based analysis, which uses the convolution of a hemodynamic response function (HRF) with the stimulus paradigm. However, several studies indicated that the HRF differs across species, sexes, brain structures, and experimental factors, including stimulation modalities or anesthesia, and hence might strongly affect the outcome of BOLD analyzes. While considerable work has been done in humans and rats to understand the HRF, much less is known in mice. As a prerequisite to investigate mechano-sensory processing and BOLD fMRI data in male and female mice, we (1) designed a rotating stimulator that allows application of two different mechanical modalities, including innocuous von Frey and noxious pinprick stimuli and (2) determined and statistically compared HRFs across 30 brain structures and experimental conditions, including sex and, stimulus modalities. We found that mechanical stimulation lead to brain-wide BOLD signal changes thereby allowing extraction of HRFs from multiple brain structures. However, we did not find differences in HRFs across all brain structures and experimental conditions. Hence, we computed a whole-brain mouse HRF, which is based on 88 functional scans from 30 mice. A comparison of this mouse-specific HRF with our previously reported rat-derived HRF showed significantly slower kinetics in mice. Finally, we detected pronounced differences in cerebral BOLD activation between male and female mice with mechanical stimulation, thereby exposing divergent processing of noxious and innocuous stimuli in both sexes.

The impact of temporal regularization on estimates of the BOLD hemodynamic response function: A comparative analysis

Accurate estimates of the BOLD hemodynamic response function (HRF) are crucial for the interpretation and analysis of event-related functional MRI data. To date, however, there have been no comprehensive measurements of the HRF in white matter (WM) despite increasing evidence that BOLD signals in WM change after a stimulus. We performed an event-related cognitive task (Stroop color-word interference) to measure the HRF in selected human WM pathways. The task was chosen in order to produce robust, distributed centers of activity throughout the cortex. To measure the HRF in WM, fiber tracts were reconstructed between each pair of activated cortical areas. We observed clear task-specific HRFs with reduced magnitudes, delayed onsets and prolonged initial dips in WM tracts compared with activated grey matter, thus calling for significant changes to current standard models for accurately characterizing the HRFs in WM and for modifications of standard methods of analysis of functional imaging data.

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function.

The hemodynamic response function (HRF) links neuronal activity to functional magnetic resonance imaging (fMRI) signals. While most fMRI studies use a canonical HRF, increasing evidence from studies of healthy subjects suggests that the HRF depends on anatomical location and disease states. Here, we investigate how HRF variability relates to anatomical location and pathology in the epileptic brain, using a large simultaneous electroencephalogram and fMRI dataset. Applying HRF deconvolution and temporal decomposition, we built the first whole-brain HRF library specific to epilepsy, identifying four distinct shape groups. We mapped HRF features across parcellations of two atlases using novel Bayesian hierarchical models. In non-epileptogenic regions, HRF shape and spatial distributions align with findings from healthy subjects. Within pathological regions, they vary significantly according to pathology. Our results indicate that HRF variability is associated with pathology, in addition to its dependence on anatomical location, motivating region- and pathology-based HRF modulation in epilepsy studies.

.SignificanceDeaf and hard-of-hearing infants’ hemodynamic response function (HRF) has not yet been characterized. However, without an appropriate estimate of their HRF, neuroimaging modalities relying on hemodynamic responses, e.g., functional magnetic resonance imaging (fMRI) or functional near-infrared spectroscopy (fNIRS), cannot be used reliably in this population, e.g., prior to and following cochlear implantation. We contribute to better theoretical models of and more suitable therapeutic interventions for the neural changes induced by auditory and language deprivation in deaf infants.AimWe aim to characterize the parameters of the HRF of deaf and hard-of-hearing infants in response to Italian.ApproachWe measured 2- to 20-month-old Italian-exposed infants’ HRF to Italian using fNIRS in the bilateral temporal, i.e., auditory, cortices. We characterized the HRF for all infants and for three clinically relevant subsets: (i) monolingual Italian infants, (ii) genetically deaf infants, and (iii) infants aged 5 to 12 months. We computed the following parameters: peak amplitude, time-to-peak, full width at half maximum, and where present, the amplitude and latency of the initial dip and/or the final undershoot, using a model-based parameter fitting approach. We statistically compared these HRF parameters to those of typically hearing infants.ResultsDeaf and typically hearing infants showed largely similar HRFs, with both groups reaching comparable main peak amplitudes. Minor differences have been found in the latencies of some response components.ConclusionsOur results provide the first detailed characterization of the hemodynamic response to native-language speech in deaf and hard-of-hearing infants, improving clinical and therapeutic approaches through more accurate analysis of fMRI and fNIRS data.

Multiple sclerosis (MS) results in inflammatory damage to white matter microstructure. Prior research using blood-oxygen-level dependent (BOLD) imaging indicates MS-related alterations to brain function. What is currently unknown is the extent to which white matter microstructural damage influences BOLD signal in MS. Here we assessed changes in parameters of the BOLD hemodynamic response function (HRF) in patients with relapsing-remitting MS compared to healthy controls. We also used diffusion tensor imaging to assess whether MS-related changes to the BOLD-HRF were affected by changes in white matter microstructural integrity. Our results showed MS-related reductions in BOLD-HRF peak amplitude. These MS-related amplitude decreases were influenced by individual differences in white matter microstructural integrity. Other MS-related factors including altered reaction time, limited spatial extent of BOLD activity, elevated lesion burden, or lesion proximity to regions of interest were not mediators of group differences in BOLD-HRF amplitude. Results are discussed in terms of functional hyperemic mechanisms and implications for analysis of BOLD signal differences.

The aim of this study was to investigate the delayed neuronal effects of acupuncture manipulations by observing blood oxygen level-dependent (BOLD) signal intensities. Fifteen (15) healthy, acupuncture-naive, right-handed subjects (all males; mean age, 23 years; range, 21-24 years) participated in this study. Each subject was scanned in eight sessions that consisted of two repeated baseline scans (Period 1), two repeated scans with acupuncture stimulation at right LR2 (Period 2), two repeated scans with retention (Period 3), and two repeated scans after removal of the needle (Period 4). Sixteen (16) regions of interest (ROI) were defined. The BOLD signals for each session were obtained for each ROI. A mixed-effects analysis of variance (ANOVA) test was performed in order to investigate the BOLD signal differences of the Periods in the 16 ROIs. The BOLD signal intensities increased in Periods 2 and 3, and then started to decrease in Period 4 in the right amygdala, supramarginal gyrus, temporal pole, and superior temporal gyrus. However, the BOLD signal intensity in Period 4 was significantly higher than that of Period 1. Especially, BOLD signal intensity was elevated promptly in the insula and the parahippocampal gyrus, whereas it was persistently elevated (delayed effect) in the amygdala. BOLD signals were persistently elevated for at least 8 minutes after removal of the acupuncture needle or for at least 19 minutes after rotation of an acupuncture needle in some specific brain areas previously linked with LR2. In those specific brain ROIs, neuronal activation accompanying and following acupuncture showed both prompt and delayed effects.