Event-related Hemodynamic Response Research Articles

Individual-specific characterization of event-related hemodynamic responses during an auditory task: An exploratory study

Functional near-infrared spectroscopy (fNIRS) has been established as an informative modality for understanding the hemodynamic-metabolic correlates of cortical auditory processing. To date, such knowledge has shown broad clinical applications in the diagnosis, treatment, and intervention procedures in disorders affecting auditory processing; however, exploration of the hemodynamic response to auditory tasks is yet incomplete. This holds particularly true in the context of auditory event-related fNIRS experiments, where preliminary work has shown the presence of valid responses while leaving the need for more comprehensive explorations of the hemodynamic correlates of event-related auditory processing. In this study, we apply an individual-specific approach to characterize fNIRS-based hemodynamic changes during an auditory task in healthy adults. Oxygenated hemoglobin (HbO2) concentration change time courses were acquired from eight participants. Independent component analysis (ICA) was then applied to isolate individual-specific class discriminative spatial filters, which were then applied to HbO2 time courses to extract auditory-related hemodynamic features. While six of eight participants produced significant class discriminative features before ICA-based spatial filtering, the proposed method identified significant auditory hemodynamic features in all participants. Furthermore, ICA-based filtering improved correlation between trial labels and extracted features in every participant. For the first time, this study demonstrates hemodynamic features important in experiments exploring auditory processing as well as the utility of individual-specific ICA-based spatial filtering in fNIRS-based feature extraction techniques in auditory experiments. These outcomes provide insights for future studies exploring auditory hemodynamic characteristics and may eventually provide a baseline framework for better understanding auditory response dysfunctions in clinical populations.

Event-related changes of the prefrontal cortex oxygen delivery and metabolism during driving measured by hyperspectral fNIRS.

Recent technological advancements in optical spectroscopy allow for the construction of hyperspectral (broadband) portable tissue oximeters. In a series of our recent papers we have shown that hyperspectral NIRS (hNIRS) has similar or better capabilities in the absolute tissue oximetry as frequency-domain NIRS, and that hNIRS is also very efficient in measuring temporal changes in tissue hemoglobin concentration and oxygenation. In this paper, we extend the application of hNIRS to the measurement of event-related hemodynamic and metabolic functional cerebral responses during simulated driving. In order to check if hNIRS can detect event-related changes in the brain, we measured the concentration changes of oxygenated (HbO2) and deoxygenated (HHb) hemoglobin and of the oxidized state of cytochrome c oxidase, on the right and left prefrontal cortices (PFC) simultaneously during simulated driving on sixteen healthy right-handed participants (aged between 22-32). We used our in-house hNIRS system based on a portable spectrometer with cooled CCD detector and a driving simulator with a fully functional steering wheel and foot pedals. Each participant performed different driving tasks and participants were distracted during some driving conditions by asking general knowledge true/false questions. Our findings suggest that more complex driving tasks (non-distracted) deactivate PFC while distractions during driving significantly activate PFC, which is in agreement with previous fMRI results. Also, we found the changes in the redox state of the cytochrome C oxidase to be very consistent with those in the concentrations of HbO2 and HHb. Overall our findings suggest that in addition to the suitability of absolute tissue oximetry, hyperspectral NIRS may also offer advantages in functional brain imaging. In particular, it can be used to measure the metabolic functional brain activity during actual driving.

Investigating the neural bases for intra-subject cognitive efficiency changes using functional magnetic resonance imaging.

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-BOLD correlations, where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals.

Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces.

A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promisingneuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focusedon enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated theperformances of a variety of mental task combinations in order to determine the mental task pairs that are bestsuited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses whileseven participants performed eight different mental tasks. Classification accuracies were then estimated for allpossible pairs of the eight mental tasks (8C2 = 28). Based on this analysis, mental task combinations with relatively high classification accuracies frequently included the following three mental tasks: “mental multiplication,” “mental rotation,” and “right-hand motor imagery.” Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations.

A reference-channel based methodology to improve estimation of event-related hemodynamic response from fNIRS measurements

Functional near-infrared spectroscopy (fNIRS) uses near-infrared light to measure cortical concentration changes in oxygenated (HbO) and deoxygenated hemoglobin (HbR) held to be correlated with cognitive activity. Providing a parametric depiction of such changes in the classic form of stimulus-evoked hemodynamic responses (HRs) can be attained with this technique only by solving two problems. One problem concerns the separation of informative optical signal from structurally analogous noise generated by a variety of spurious sources, such as heart beat, respiration, and vasomotor waves. Another problem pertains to the inherent variability of HRs, which is notoriously contingent on the type of experiment, brain region monitored, and human phenotype. A novel method was devised in the present context to solve both problems based on a two-step algorithm combining the treatment of noise-only data extrapolated from a reference-channel and a Bayesian filter applied on a per-trial basis. The present method was compared to two current methods based on conventional averaging, namely, a typical averaging method and an averaging method implementing the use of a reference-channel. The result of the comparison, carried out both on artificial and real data, revealed a sensitive accuracy improvement in HR estimation using the present method relative to each of the other methods.

Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns

We investigated the decoding of ocular dominance stimulations with millisecond-order timing difference from the blood oxygen level dependent (BOLD) signal in human functional magnetic resonance imaging (fMRI). In our experiment, ocular dominance columns were activated by monocular visual stimulation with 500- or 100- ms onset differences. We observed that the event-related hemodynamic response (HDR) in the human visual cortex was sensitive to the subtle onset difference. The HDR shapes were related to the stimulus timings in various manners: the timing difference was represented in either the amplitude of positive peak, amplitude of negative peak, delay of peak time, or response duration of HDR. These complex relationships were different across voxels and subjects. To find an informative feature of HDR for discriminating the subtle timing difference of ocular dominance stimulations, we examined various characteristics of HDR including response amplitude, time to peak, full width at half-maximum response, as inputs for decoding analysis. Using a canonical HDR function for estimating the voxel's response did not yield good decoding scores, suggesting that information may reside in the variability of HDR shapes. Using all the values from the deconvolved HDR also showed low performance, which could be due to an over-fitting problem with the large data dimensionality. When using either positive or negative peak amplitude of the deconvolved HDR, high decoding performance could be achieved for both the 500ms and the 100ms onset differences. The high accuracy even for the 100ms difference, given that the signal was sampled at a TR of 250ms and 2×2×3-mm voxels, implies a possibility of spatiotemporally hyper-resolution decoding. Furthermore, both down-sampling and smoothing did not affect the decoding accuracies very much. These results suggest a complex spatiotemporal relationship between the multi-voxel pattern of the BOLD response and the population activation of neuronal columns. The demonstrated possibility of decoding stimulations for columnar-level organization with 100-ms onset difference using lower resolution imaging data may broaden the scope of application of the BOLD fMRI.

Detection of event-related hemodynamic response to neuroactivation by dynamic modeling of brain activity

This paper presents a state-space hemodynamic model by which any event-related hemodynamic prediction function (i.e., the basis function of the design matrix in the general linear model) is obtained as an output of the model. To model the actual event-related behavior during a task period (intra-activity dynamics) besides the contrasting behavior among the different task periods and against the rest periods (inter-activity dynamics), the modular system is investigated by parametric subspace-based state-space modeling of actual hemodynamic response to an impulse stimulus. This model provides a simple and computationally efficient way to generate the event-related basis function for an experiment by just convolving the developed hemodynamic model with the impulse approximation of the experimental stimuli. The demonstration of the stated findings is carried out by conducting finger-related experiments with slow- and fast-sampling near-infrared spectroscopy instruments to model and validate the cortical hemodynamic responses. The generated basis functions of the finger-related experiments are adapted from real data to validate the incorporation of non-delayed and real-time event-related features and to effectively demonstrate a dynamic-modeling-based online framework. The proposed method demonstrates potential in estimating event-related intra- and inter-activation dynamics and thereby outperforms the classical Gaussian approximation method.

Simultaneous EEG-fMRI in Patients with Unverricht-Lundborg Disease: Event-Related Desynchronization/Synchronization and Hemodynamic Response Analysis

We performed simultaneous acquisition of EEG-fMRI in seven patients with Unverricht-Lundborg disease (ULD) and in six healthy controls using self-paced finger extension as a motor task. The event-related desynchronization/synchronization (ERD/ERS) analysis showed a greater and more diffuse alpha desynchronization in central regions and a strongly reduced post-movement beta-ERS in patients compared with controls, suggesting a significant dysfunction of the mechanisms regulating active movement and movement end. The event-related hemodynamic response obtained from fMRI showed delayed BOLD peak latency in the contralateral primary motor area suggesting a less efficient activity of the neuronal populations driving fine movements, which are specifically impaired in ULD.

Investigating the post-stimulus undershoot of the BOLD signal—a simultaneous fMRI and fNIRS study

Measuring the hemodynamic response with functional magnetic resonance imaging (fMRI) together with functional near-infrared spectroscopy (fNIRS) may overcome limitations of single-method approaches. Accordingly, we measured the event-related hemodynamic response with both imaging methods simultaneously in young subjects during visual stimulation. An intertrial interval of 60 s was chosen to include the prolonged post-stimulus undershoot of the blood oxygenation level dependent (BOLD) signal. During visual stimulation, the BOLD signal, oxy-, and total hemoglobin (Hb) increased, whereas deoxy-Hb decreased. The post-stimulus period was characterized by an undershoot of the BOLD signal, oxy-Hb, and an overshoot of deoxy-Hb. Total Hb as measured by fNIRS returned to baseline immediately after the end of stimulation. Results suggest that the post-stimulus events as measured by fNIRS are dominated by a prolonged high-level oxygen consumption in the microvasculature. The contribution of a delayed return of blood volume to the BOLD post-stimulus undershoot in post-capillary veins as suggested by the Balloon and Windkessel models remains ambiguous. Temporal changes in the BOLD signal were highly correlated with deoxy-Hb, with lower correlation values for oxy- and total Hb. Furthermore, data show that fNIRS covers the outer 1 cm of the brain cortex. These results were confirmed by simultaneous fMRI/fNIRS measurements during rest. In conclusion, multimodal imaging approaches may contribute to the understanding of neurovascular coupling.

Spectral Analysis of Event-Related Hemodynamic Responses in Functional Near Infrared Spectroscopy

The goal of this paper is to design experiments that confirm the evidence of cognitive responses in functional near infrared spectroscopy and to establish relevant spectral subbands. Hemodynamic responses of brain during single-event trials in an odd-ball experiment are measured by functional near infrared spectroscopy method. The frequency axis is partitioned into subbands by clustering the time-frequency power spectrum profiles of the brain responses. The predominant subbands are observed to confine the 0-30 mHz, 30-60 mHz, and 60-330 mHz ranges. We identify the group of subbands that shows strong evidence of protocol-induced periodicity as well as the bands where good correlation with an assumed hemodynamic response models is found.

Functional neuroanatomy of auditory mismatch processing: an event-related fMRI study of duration-deviant oddballs

This study was designed to identify the neural networks underlying automatic auditory deviance detection in 10 healthy subjects using functional magnetic resonance imaging. We measured blood oxygenation level-dependent contrasts derived from the comparison of blocks of stimuli presented as a series of standard tones (50 ms duration) alone versus blocks that contained rare duration-deviant tones (100 ms) that were interspersed among a series of frequent standard tones while subjects were watching a silent movie. Possible effects of scanner noise were assessed by a “no tone” condition. In line with previous positron emission tomography and EEG source modeling studies, we found temporal lobe and prefrontal cortical activation that was associated with auditory duration mismatch processing. Data were also analyzed employing an event-related hemodynamic response model, which confirmed activation in response to duration-deviant tones bilaterally in the superior temporal gyrus and prefrontally in the right inferior and middle frontal gyri. In line with previous electrophysiological reports, mismatch activation of these brain regions was significantly correlated with age. These findings suggest a close relationship of the event-related hemodynamic response pattern with the corresponding electrophysiological activity underlying the event-related “mismatch negativity” potential, a putative measure of auditory sensory memory.

Reproducibility of the hemodynamic response to auditory oddball stimuli: a six-week test-retest study.

Determining the reliability and reproducibility of the hemodynamic response is important for the interpretation and understanding of the results of functional magnetic resonance imaging (fMRI) experiments. We describe a whole brain fMRI study designed to examine the reproducibility of the event-related hemodynamic response elicited by low-probability task-relevant target stimuli and low-probability task-irrelevant novel stimuli assessed 6 weeks apart. Reliable activation was observed during test and retest for processing of target stimuli in multiple frontal, temporal, parietal, cerebellar, and subcortical sites. Novel stimuli elicited reliable activation during test and retest in lateral frontal cortex, inferior parietal lobule, and lateral temporal cortex, though there was evidence of habituation at some cortical sites. The patterns of activation associated with target detection and novelty processing are consistent with the intracranial distribution of the neural sources generated during similar tasks and replicate the results of previous event-related fMRI studies. The observed pattern of results supports the hypothesis that the hemodynamic response to target and novel stimuli is highly reproducible over the 6-week test-retest period.

The Importance of Distributed Sampling in Blocked Functional Magnetic Resonance Imaging Designs

In this study we demonstrate the importance of distributed sampling of peristimulus time in blocked design fMRI studies. Distributed sampling ensures all the components of an event-related hemodynamic response are sampled and avoids the bias incurred when stimulus presentation is time-locked to data acquisition. We found that differences in the temporal offset between stimulus presentation and data acquisition had a significant effect on some language-related activations. These effects, induced by simply shifting stimulus presentation by a fraction of the interscan interval, suggest that fixed sampling does indeed bias estimated responses, even in blocked designs.

Estimation and detection of event-related fMRI signals with temporally correlated noise: A statistically efficient and unbiased approach

Recent developments in analysis methods for event-related functional magnetic resonance imaging (fMRI) has enabled a wide range of novel experimental designs. As with selective averaging methods used in event-related potential (ERP) research, these methods allow for the estimation of the average time-locked response to particular event-types, even when these events occur in rapid succession and in an arbitrary sequence. Here we present a flexible framework for obtaining efficient and unbiased estimates of event-related hemodynamic responses, in the presence of realistic temporally correlated (nonwhite) noise. We further present statistical inference methods based upon the estimated responses, using restriction matrices to formulate temporal hypothesis tests about the shape of the evoked responses. The accuracy of the methods is assessed using synthetic noise, actual fMRI noise, and synthetic activation in actual noise. Actual false-positive rates were compared to nominal false-positive rates assuming white noise, as well as local and global noise estimates in the estimation procedure (assuming white noise resulted in inappropriate inference, while both global and local estimates corrected false-positive rates). Furthermore, both local and global noise estimates were found to increase the statistical power of the hypothesis tests, as measured by the receiver operating characteristics (ROC). This approach thus enables appropriate univariate statistical inference with improved statistical power, without requiring a priori assumptions about the shape or timing of the event-related hemodynamic response.

Optimal experimental design for event-related fMRI

An important challenge in the design and analysis of event-related or single-trial functional magnetic resonance imaging (fMRI) experiments is to optimize statistical efficiency, i.e., the accuracy with which the event-related hemodynamic response to different stimuli can be estimated for a given amount of imaging time. Several studies have suggested that using a fixed inter-stimulus-interval (ISI) of at least 15 sec results in optimal statistical efficiency or power and that using shorter ISIs results in a severe loss of power. In contrast, recent studies have demonstrated the feasibility of using ISIs as short as 500 ms while still maintaining considerable efficiency or power. Here, we attempt to resolve this apparent contradiction by a quantitative analysis of the relative efficiency afforded by different event-related experimental designs. This analysis shows that statistical efficiency falls off dramatically as the ISI gets sufficiently short, if the ISI is kept fixed for all trials. However, if the ISI is properly jittered or randomized from trial to trial, the efficiency improves monotonically with decreasing mean ISI. Importantly, the efficiency afforded by such variable ISI designs can be more than 10 times greater than that which can be achieved by fixed ISI designs. These results further demonstrate the feasibility of using identical experimental designs with fMRI and electro-/magnetoencephalography (EEG/MEG) without sacrificing statistical power or efficiency of either technique, thereby facilitating comparison and integration across imaging modalities.

Event-Related fMRI: Characterizing Differential Responses

We present an approach to characterizing the differences among event-related hemodynamic responses in functional magnetic resonance imaging that are evoked by different sorts of stimuli. This approach is predicated on a linear convolution model and standard inferential statistics as employed by statistical parametric mapping. In particular we model evoked responses, and their differences, in terms of basis functions of the peri-stimulus time. This facilitates a characterization of the temporal response profiles that has a high effective temporal resolution relative to the repetition time. To demonstrate the technique we examined differential responses to visually presented words that had been seen prior to scanning or that were novel. The form of these differences involved both the magnitude and the latency of the response components. In this paper we focus on bilateral ventrolateral prefrontal responses that show deactivations for previously seen words and activations for novel words.