Effects of Hemodynamic Response Function Selection on Rat fMRI Statistical Analyses

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.

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

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

Most of the currently used methods for functional brain imaging do not visualize neuronal activity directly but rather rely on the elicited hemodynamic and/or metabolic responses. Glutamate, the major excitatory neurotransmitter, plays an important role in the neurovascular/neurometabolic coupling, but the specific mechanisms are still poorly understood. To investigate the role of the two major ionotropic glutamate receptors [NMDA receptors (NMDA-Rs) and AMPA receptors (AMPA-Rs)] for the generation of functional magnetic resonance imaging (fMRI) signals, we used fMRI [measurements of blood oxygenation level-dependent (BOLD), perfusion-weighted imaging (PWI), and cerebral blood volume (CBV)] together with recordings of somatosensory evoked potentials (SEPs) during electrical forepaw stimulation in the alpha-chloralose anesthetized rat. Intravenous injection of the NMDA-R antagonist MK-801 [(+)-5-methyl-10,11-dihydro-5H-dibenzo [a,d] cyclohepten-5,10-imine maleate] (0.06 mg/kg plus 3.6 microg x kg(-1) x h(-1)) significantly decreased BOLD (-51 +/- 19%; n = 5) and PWI (-57 +/- 26%; n = 5) responses but reduced the SEPs only mildly (approximately -10%). Systemic application of the AMPA-R antagonist GYKI-53655 [1-(4-aminophenyl)-3-methylcarbamyl-4-methyl-7,8-methylenedioxy-3,4-dihydro-5H-2,3-benzodiazepine] significantly decreased both the hemodynamic response (BOLD, -49 +/- 13 and -65 +/- 15%; PWI, -22 +/- 48 and -68 +/- 4% for 5 and 7 mg/kg, i.v., respectively; CBV, -80 +/- 7% for 7 mg/kg; n = 4) and the SEPs (up to -60%). These data indicate that the interaction of glutamate with its postsynaptic and/or glial receptors is necessary for the generation of blood flow and BOLD responses and illustrate the differential role of NMDA-Rs and AMPA-Rs in the signaling chain leading from increased neuronal activity to the hemodynamic response in the somatosensory cortex.

Functional magnetic resonance imaging (fMRI) is a unique window to the brain, enabling scientists to follow changes in brain activity in response to hormones, ageing, environment, drugs of abuse and other stimuli. There are two features that make fMRI unique when compared with other imaging modalities used in behavioural neuroscience. First, it can be entirely noninvasive: each animal can serve as its own control over the natural course of its life, vital for following neuroadaptation and other developmental processes critical to understanding behaviour. Second, fMRI has the spatial and temporal resolution to observe patterns of neuronal activity across the entire brain in less than a minute. Although fMRI does not have the cellular spatial resolution of immunostaining, nor the millisecond temporal resolution of electrophysiology, synchronised changes in neuronal activity across multiple brain areas seen with functional MRI can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviours. Thus, fMRI affords a systems approach to the study of the brain, complementing and building from other neurobiological techniques to understand how behaviour is organised across multiple brain regions. In this review, we present a general background to fMRI and the different imaging modalities that can be used in fMRI studies. Included are examples of the application of fMRI in behavioural neuroscience research, along with discussion of the advantages and disadvantages of this technology.

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.

We compared the blood oxygenation level dependent (BOLD) responses in reading tasks of three languages, Chinese, English and Pinyin, a form of Romanised Chinese in FMRI. We found distinct differences between the activation patterns of all three languages. Hemodynamic response functions were also extracted and analyzed and found to show more bilateral activations in the Chinese languages. The strength of the BOLD responses suggest that Romanised Chinese has an activation pattern not too different from those of the English and Chinese languages.

.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.

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 hemodynamic response function (HRF) describes the dynamic process of the blood oxygen level dependent (BOLD) signal evoked by a very short stimulus of unit intensity. Understanding HRF is a key issue for exploring the underlying dynamics of nervous system activation. Some researches suggested that the shape of HRF varied with different brain regions and different subjects, even at different time point in the same brain region of a subject. In this work, epilepsy discharges were adopted as markers of short stimuli, and then we use EEG-fMRI method to investigate HRF in temporal lobe epilepsy with interictal regional slow wave. Five patients with idiopathic temporal lobe epilepsy were enrolled in this study, the peak delay and amplitude of the estimated HRF was compared with Gamma, Glover and the SPM canonical HRF, and the results show that the delay of the estimated HRF is different from either one of the three theoretical model, thus further study on both theoretical model and real data estimation is needed.

The relation between electrophysiology and BOLD‐fMRI requires further elucidation. One approach for studying this relation is to find time‐frequency features from electrophysiology that explain the variance of BOLD time‐series. Convolution of these features with a canonical hemodynamic response function (HRF) is often required to model neurovascular coupling mechanisms and thus account for time shifts between electrophysiological and BOLD‐fMRI data. We propose a framework for extracting the spatial distribution of these time‐frequency features while also estimating more flexible, region‐specific HRFs. The core component of this method is the decomposition of a tensor containing impulse response functions using the Canonical Polyadic Decomposition. The outputs of this decomposition provide insight into the relation between electrophysiology and BOLD‐fMRI and can be used to construct estimates of BOLD time‐series. We demonstrated the performance of this method on simulated data while also examining the effects of simulated measurement noise and physiological confounds. Afterwards, we validated our method on publicly available task‐based and resting‐state EEG‐fMRI data. We adjusted our method to accommodate the multisubject nature of these datasets, enabling the investigation of inter‐subject variability with regards to EEG‐to‐BOLD neurovascular coupling mechanisms. We thus also demonstrate how EEG features for modelling the BOLD signal differ across subjects.

Non-parametric Bayesian models of response function in dynamic image sequences

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.

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.

Paired pulse depression in the somatosensory cortex: Associations between MEG and BOLD fMRI