Evaluation of the early response in fMRI in individual subjects using short stimulus duration

Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution

Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.

The oxygen initial dip in the brain of anesthetized and awake mice

Sensory stimulation generates a robust decrease in oxygen concentration (pO₂ initial dip) in brain tissue of anesthetized cats and rodents. This dip reports local activation of neurons much better than the delayed pO₂ increase associated with functional hyperemia. Here, we reinvestigated the issue in animals that recovered from acute surgery using two-photon lifetime microscopy. Targeting a distinct neuronal network that is the site of strong activation and energy consumption, we show that in anesthetized animals the pO₂ initial dip is present but extremely small in juxtasynaptic capillaries. In awake animals, it is no longer detectable in vessels or in the neuropil. This demonstrates that in healthy animals, neurovascular coupling is too fast and efficient to reveal a pO₂ initial dip.

An ongoing controversy in brain metabolism is whether increases in neural activity cause a local and rapid decrease in oxygen concentration (i.e., the “initial dip”) preceding functional hyperemia. This initial dip has been suggested to cause a transient increase in vascular deoxyhemoglobin with several imaging techniques and stimulation paradigms, but not consistently. Here, we investigate contributors to this initial dip in a distinct neuronal network, an olfactory bulb (OB) glomerulus most sensitive to a specific odorant (ethyl tiglate [ET]) and a site of strong activation and energy consumption upon ET stimulation. Combining two-photon fluorescence and phosphorescence lifetime microscopy, and calcium, blood flow, and pO₂ measurements, we characterized this initial dip in pO₂ in mice chronically implanted with a glass cranial window, during both awake and anesthetized conditions. In anesthetized mice, a transient dip in vascular pO₂ was detected in this glomerulus when functional hyperemia was slightly delayed, but its amplitude was minute (0.3 SD of resting baseline). This vascular pO₂ dip was not observed in other glomeruli responding nonspecifically to ET, and it was poorly influenced by resting pO₂. In awake mice, the dip in pO₂ was absent in capillaries as well as, surprisingly, in the neuropil. These high-resolution pO₂ measurements demonstrate that in awake mice recovered from brain surgery, neurovascular coupling was too fast and efficient to reveal an initial dip in pO₂.

Laminar-specific functional connectivity mapping with multi-slice line-scanning fMRI

Despite extensive studies detecting laminar functional magnetic resonance imaging (fMRI) signals to illustrate the canonical microcircuit, the spatiotemporal characteristics of laminar-specific information flow across cortical regions remain to be fully investigated in both evoked and resting conditions at different brain states. Here, we developed a multislice line-scanning fMRI (MS-LS) method to detect laminar fMRI signals in adjacent cortical regions with high spatial (50 μm) and temporal resolution (100 ms) in anesthetized rats. Across different trials, we detected either laminar-specific positive or negative blood-oxygen-level-dependent (BOLD) responses in the surrounding cortical region adjacent to the most activated cortex under the evoked condition. Specifically, in contrast to typical Layer (L) 4 correlation across different regions due to the thalamocortical projections for trials with positive BOLD, a strong correlation pattern specific in L2/3 was detected for trials with negative BOLD in adjacent regions, which indicated brain state-dependent laminar-fMRI responses based on corticocortical interaction. Also, in resting-state (rs-) fMRI study, robust lag time differences in L2/3, 4, and 5 across multiple cortices represented the low-frequency rs-fMRI signal propagation from caudal to rostral slices. In summary, our study provided a unique laminar fMRI mapping scheme to better characterize trial-specific intra- and inter-laminar functional connectivity in evoked and resting-state MS-LS.

Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI

Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.

The Role of Cerebral Metabolism in Improving Time Pressured Decisions

Speed-accuracy tradeoff (SAT) theory dictates that decisions can be made more quickly by sacrificing accuracy. Here we investigate whether the human brain can operate in a brief metabolic overdrive to overcome SAT and successfully make decisions requiring both high levels of speed and accuracy. In the context of BOLD fMRI we expect “a brief metabolic overdrive” to involve an increase in cerebral oxygen metabolism prior to increased cerebral blood flow–a phenomenon known as the “initial dip” which results from a sudden drop in oxyhemoglobin in perfusing blood. Human subjects performed a motion discrimination task consisting of different difficulties while emphasizing either accuracy (i.e., without time pressure) or both speed and accuracy (i.e., with time pressure). Using simultaneous multi-slice fMRI, for very fast (333 ms) measurement of whole brain BOLD activity, revealed two modes of physiological overdrive responses when subjects emphasized both speed and accuracy. The majority of subjects exhibited the hypothesized enhancement of initial dip amplitude in posterior visual cortex (PVC) with the size of the enhancement significantly correlated with improvement in behavioral performance. For these subjects, the traditionally analyzed post-stimulus overshoot was not affected by task emphasis. These results demonstrate the complexity and variability of the BOLD hemodynamic response. The discovered relationships between BOLD response and behavior were only observed when subjects emphasized both speed and accuracy in more difficult trials suggesting that the brain can perform in a state of metabolic overdrive with enhanced neural processing of sensory information specifically in challenging situations.

Initial-Dip Existence and Estimation in Relation to DPF and Data Drift

Early de-oxygenation (initial dip) is an indicator of the primal cortical activity source in functional neuro-imaging. In this study, initial dip's existence and its estimation in relation to the differential pathlength factor (DPF) and data drift were investigated in detail. An efficient algorithm for estimation of drift in fNIRS data is proposed. The results favor the shifting of the fNIRS signal to a transformed coordinate system to infer correct information. Additionally, in this study, the effect of the DPF on initial dip was comprehensively analyzed. Four different cases of initial dip existence were treated, and the resultant characteristics of the hemodynamic response function (HRF) for DPF variation corresponding to particular near-infrared (NIR) wavelengths were summarized. A unique neuro-activation model and its iterative optimization solution that can estimate drift in fNIRS data and determine the best possible fit of HRF with free parameters were developed and herein proposed. The results were verified on simulated data sets. The algorithm is applied to free available datasets in addition to six healthy subjects those were experimented using fNIRS and observations and analysis regarding shape of HRF were summarized as well. A comparison with standard GLM is also discussed and effects of activity strength parameters have also been analyzed.

Existence of Initial Dip for BCI: An Illusion or Reality

A tight coupling between the neuronal activity and the cerebral blood flow (CBF) is the motivation of many hemodynamic response (HR)-based neuroimaging modalities. The increase in neuronal activity causes the increase in CBF that is indirectly measured by HR modalities. Upon functional stimulation, the HR is mainly categorized in three durations: (i) initial dip, (ii) conventional HR (i.e., positive increase in HR caused by an increase in the CBF), and (iii) undershoot. The initial dip is a change in oxygenation prior to any subsequent increase in CBF and spatially more specific to the site of neuronal activity. Despite additional evidence from various HR modalities on the presence of initial dip in human and animal species (i.e., cat, rat, and monkey); the existence/occurrence of an initial dip in HR is still under debate. This article reviews the existence and elusive nature of the initial dip duration of HR in intrinsic signal optical imaging (ISOI), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). The advent of initial dip and its elusiveness factors in ISOI and fMRI studies are briefly discussed. Furthermore, the detection of initial dip and its role in brain-computer interface using fNIRS is examined in detail. The best possible application for the initial dip utilization and its future implications using fNIRS are provided.

The effects of capillary transit time heterogeneity on the BOLD signal

Neurovascular coupling mechanisms give rise to vasodilation and functional hyperemia upon neural activation, thereby altering blood oxygenation. This blood oxygenation level dependent (BOLD) contrast allows studies of activation patterns in the working human brain by functional MRI (fMRI). The BOLD-weighted fMRI signal shows characteristic transients in relation to functional activation, such as the so-called initial dip, overshoot, and post-stimulus undershoot. These transients are modulated by other physiological stimuli and in disease, but the underlying physiological mechanisms remain incompletely understood. Capillary transit time heterogeneity (CTH) has been shown to affect oxygen extraction, and hence blood oxygenation. Here, we examine how recently reported redistributions of capillary blood flow during functional activation would be expected to affect BOLD signal transients. We developed a three-compartment (hemoglobin, plasma, and tissue) model to predict the BOLD signal, incorporating the effects of dynamic changes in CTH. Our model predicts that the BOLD signal represents the superposition of a positive component resulting from increases in cerebral blood flow (CBF), and a negative component, resulting from elevated tissue metabolism and homogenization of capillary flows (reduced CTH). The model reproduces salient features of BOLD signal dynamics under conditions such as hypercapnia, hyperoxia, and caffeine intake, where both brain physiology and BOLD characteristics are altered. Neuroglial signaling and metabolism could affect CBF and capillary flow patterns differently. Further studies of neurovascular and neuro-capillary coupling mechanisms may help us relate BOLD signals to the firing of certain neuronal populations based on their respective BOLD "fingerprints."

Characterization of the hemodynamic response function across the majority of human cerebral cortex

A brief (<4 s) period of neural activation evokes a stereotypical sequence of vascular and metabolic events to create the hemodynamic response function (HRF) measured using functional magnetic resonance imaging (fMRI). Linear analysis of fMRI data requires that the HRF be treated as an impulse response, so the character and temporal stability of the HRF are critical issues. Here, a simple audiovisual stimulus combined with a fast-paced task was used to evoke a strong HRF across a majority, ∼77%, of cortex during a single scanning session. High spatiotemporal resolution (2-mm voxels, 1.25-s acquisition time) was used to focus HRF measurements specifically on the gray matter for whole brain. The majority of activated cortex responds with positive HRFs, while ∼27% responds with negative (inverted) HRFs. Spatial patterns of the HRF response amplitudes were found to be similar across subjects. Timing of the initial positive lobe of the HRF was relatively stable across the cortical surface with a mean of 6.1 ± 0.6 s across subjects, yet small but significant timing variations were also evident in specific regions of cortex. The results provide guidance for linear analysis of fMRI data. More importantly, this method provides a means to quantify neurovascular function across most of the brain, with potential clinical utility for the diagnosis of brain pathologies such as traumatic brain injury.

Detection and classification of three-class initial dips from prefrontal cortex

In this paper, the use of initial dips using functional near-infrared spectroscopy (fNIRS) for brain-computer interface (BCI) is investigated. Features and window sizes for detecting initial dips are also discussed. Three mental tasks including mental arithmetic, mental counting, and puzzle solving are performed in obtaining fNIRS signals from the prefrontal cortex. Vector-based phase analysis method combined with a threshold circle, as a decision criterion, are used to detect the initial dips. Eight healthy subjects participate in experiment. Linear discriminant analysis is used as a classifier. To classify initial dips, five features (signal mean, peak value, signal slope, skewness, and kurtosis) of oxy-hemoglobin (HbO) and four different window sizes (0~1, 0~1.5, 0~2, and 0~2.5 sec) are examined. It is shown that a combination of signal mean and peak value and a time period of 0~2.5 sec provide the best average classification accuracy of 57.5% for three classes. To further validate the result, three-class classification using the conventional hemodynamic response (HR) is also performed, in which two features (signal mean and signal slope) and 2~7 sec window size have yielded the average classification accuracy of 65.9%. This reveals that fNIRS-based BCI using initial dip detection can reduce the command generation time from 7 sec to 2.5 sec while the classification accuracy is a bit sacrificed from 65.9% to 57.5% for three mental tasks. Further improvement can be made by using deoxy hemoglobin signals in coping with the slow HR problem.

fMRI at High Spatial Resolution: Implications for BOLD-Models

As high-resolution functional magnetic resonance imaging (fMRI) and fMRI of cortical layers become more widely used, the question how well high-resolution fMRI signals reflect the underlying neural processing, and how to interpret laminar fMRI data becomes more and more relevant. High-resolution fMRI has shown laminar differences in cerebral blood flow (CBF), volume (CBV), and neurovascular coupling. Features and processes that were previously lumped into a single voxel become spatially distinct at high resolution. These features can be vascular compartments such as veins, arteries, and capillaries, or cortical layers and columns, which can have differences in metabolism. Mesoscopic models of the blood oxygenation level dependent (BOLD) response therefore need to be expanded, for instance, to incorporate laminar differences in the coupling between neural activity, metabolism and the hemodynamic response. Here we discuss biological and methodological factors that affect the modeling and interpretation of high-resolution fMRI data. We also illustrate with examples from neuropharmacology and the negative BOLD response how combining BOLD with CBF- and CBV-based fMRI methods can provide additional information about neurovascular coupling, and can aid modeling and interpretation of high-resolution fMRI.

Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI

Functional magnetic resonance imaging (fMRI) measures brain activity by detecting the blood-oxygen-level dependent (BOLD) response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new, independent validation data. These results open the door to a new type of fMRI analysis that more accurately reflects the true neuronal activity.

Functional magnetic resonance imaging (fMRI) is a widely used technique for measuring brain activity. However, the signal registered by fMRI is not a direct measurement of the neuronal activity in the brain, but it is influenced by the interplay between the metabolism, blood flow and blood volume in the active area. This signal is called the blood-oxygen-level dependent (BOLD) response and occurs when the blood supply to the active area increases in response to neuronal activity. The mechanisms that the cells use to influence the blood supply are not fully known, and therefore it is difficult to know the true neuronal signalling only from inspection of the fMRI signal. In this article, we present a new mathematical model built on the physiological mechanisms thought to underlie the BOLD response. We could successfully fit the model to data and predict the activity caused by new stimuli. By using the validated model we investigated physiological mechanisms that cause different parts of the BOLD response.

Modulation of post-movement beta rebound by contraction force and rate of force development

Movement induced modulation of the beta rhythm is one of the most robust neural oscillatory phenomena in the brain. In the preparation and execution phases of movement, a loss in beta amplitude is observed [movement related beta decrease (MRBD)]. This is followed by a rebound above baseline on movement cessation [post movement beta rebound (PMBR)]. These effects have been measured widely, and recent work suggests that they may have significant importance. Specifically, they have potential to form the basis of biomarkers for disease, and have been used in neuroscience applications ranging from brain computer interfaces to markers of neural plasticity. However, despite the robust nature of both MRBD and PMBR, the phenomena themselves are poorly understood. In this study, we characterise MRBD and PMBR during a carefully controlled isometric wrist flexion paradigm, isolating two fundamental movement parameters; force output, and the rate of force development (RFD). Our results show that neither altered force output nor RFD has a significant effect on MRBD. In contrast, PMBR was altered by both parameters. Higher force output results in greater PMBR amplitude, and greater RFD results in a PMBR which is higher in amplitude and shorter in duration. These findings demonstrate that careful control of movement parameters can systematically change PMBR. Further, for temporally protracted movements, the PMBR can be over 7 s in duration. This means accurate control of movement and judicious selection of paradigm parameters are critical in future clinical and basic neuroscientific studies of sensorimotor beta oscillations. Hum Brain Mapp 37:2493–2511, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc

Reduction of Delay in Detecting Initial Dips from Functional Near-Infrared Spectroscopy Signals Using Vector-Based Phase Analysis

In this paper, we present a systematic method to reduce the time lag in detecting initial dips using a vector-based phase diagram and an autoregressive moving average with exogenous signals (ARMAX) model-based [Formula: see text]-step-ahead prediction algorithm. With functional near-infrared spectroscopy (fNIRS), signals related to mental arithmetic and right-hand clenching are acquired from the prefrontal and left primary motor cortices, respectively. The interrelationship between oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin and cerebral oxygen exchange are related to initial dips. Specifically, a threshold value from the resting state hemodynamics is incorporated, as a decision criterion, into the vector-based phase diagram to determine the occurrence of initial dips. To further reduce the time lag, a [Formula: see text]-step-ahead prediction method is applied to predict the occurrence of the dips. A combination of the threshold criterion and the prediction method resulted in the delay time of about 0.9[Formula: see text]s. The results demonstrate that rapid detection of initial dip is possible and therefore can be used for real-time brain–computer interfacing.

Reproducing the Hemoglobin Saturation Profile, a Marker of the Blood Oxygenation Level Dependent (BOLD) fMRI Effect, at the Microscopic Level

The advent of functional MRI in the mid-1990s has catalyzed progress pertaining to scientific discoveries in neuroscience. With the prospect of elucidating the physiological aspect of the Blood Oxygenation Level Dependent (BOLD) effect we present a computational capillary-tissue system capable of mapping venous hemoglobin saturation— a marker of the BOLD hemodynamic response. Free and facilitated diffusion and convection for hemoglobin and oxygen are considered in the radial and axial directions. Hemoglobin reaction kinetics are governed by the oxyhemoglobin dissociation curve. Brain activation, mimicked by dynamic transitions in cerebral blood velocity (CBv) and oxidative metabolism (CMR_O2), is simulated by normalized changes in m = (ΔCBv/CBv)/(ΔCMR_O2/CMR_O2) of values 2, 3 and 4. Venous hemoglobin saturation profiles and peak oxygenation results, for m = 2, based upon a 50% and a 25% increase in CBv and CMR_O2, respectively, lie within physiological limits exhibiting excellent correlation with the BOLD signal, for short-duration stimuli. Our analysis suggests basal CBv and CMR_O2 values of 0.6 mm/s and 200 μmol/100g/min. Coupled CBv and CMR_O2 responses, for m = 3 and m = 4, overestimate peak hemoglobin saturation, confirming the system’s responsiveness to changes in hematocrit, CBv and CMR_O2. Finally, factoring in neurovascular effects, we show that no initial dip will be observed unless there is a time delay in the onset of increased CBv relative to CMR_O2.

Imaging the Neocortex Functional Architecture Using Multiple Intrinsic Signals: Implications for Hemodynamic-Based Functional Imaging

Optical imaging based on intrinsic signals has provided a new level of understanding of the principles underlying cortical development, organization, and function, providing a spatial resolution of up to 20 µm for mapping cortical columns in vivo. This introduction briefly reviews the development of this technique, the types of applications that have been pursued, and the general implications of some findings for other neuroimaging techniques based on hemodynamic responses (e.g., functional magnetic resonance imaging).

Neuronal or hemodynamic? Grappling with the functional MRI signal

Magnetic resonance imaging (MRI) and functional MRI (fMRI) continue to advance because creative physicists, engineers, neuroscientists, clinicians, and physiologists find new ways for extracting more information from the signal. Innovations in pulse sequence design, paradigm design, and processing methods have advanced the field and firmly established fMRI as a cornerstone for understanding the human brain. In this article, the field of fMRI is described through consideration of the central problem of separating hemodynamic from neuronal information. Discussed here are examples of how pulse sequences, activation paradigms, and processing methods are integrated such that novel, high-quality information can be obtained. Examples include the extraction of information such as activation onset latency, metabolic rate, neuronal adaptation, vascular patency, vessel diameter, vigilance, and subvoxel activation. Experimental measures include time series latency, hemodynamic shape, MR phase, multivoxel patterns, ratios of activation-related R2* to R2, metabolic rate changes, fluctuation correlations and frequencies, changes in fluctuation correlations and frequencies over time, resting correlation states, echo time dependence, and more.

Chronic assessment of cerebral hemodynamics during rat forepaw electrical stimulation using functional ultrasound imaging

Functional ultrasound imaging is a method recently developed to assess brain activity via hemodynamics in rodents. Doppler ultrasound signals allow the measurement of cerebral blood volume (CBV) and red blood cells' (RBCs') velocity in small vessels. However, this technique originally requires performing a large craniotomy that limits its use to acute experiments only. Moreover, a detailed description of the hemodynamic changes that underlie functional ultrasound imaging has not been described but is essential for a better interpretation of neuroimaging data. To overcome the limitation of the craniotomy, we developed a dedicated thinned skull surgery for chronic imaging. This procedure did not induce brain inflammation nor neuronal death as confirmed by immunostaining. We successfully acquired both high-resolution images of the microvasculature and functional movies of the brain hemodynamics on the same animal at 0, 2, and 7 days without loss of quality. Then, we investigated the spatiotemporal evolution of the CBV hemodynamic response function (HRF) in response to sensory-evoked electrical stimulus (1 mA) ranging from 1 (200 μs) to 25 pulses (5s). Our results indicate that CBV HRF parameters such as the peak amplitude, the time to peak, the full width at half-maximum and the spatial extent of the activated area increase with stimulus duration. Functional ultrasound imaging was sensitive enough to detect hemodynamic responses evoked by only a single pulse stimulus. We also observed that the RBC velocity during activation could be separated in two distinct speed ranges with the fastest velocities located in the upper part of the cortex and slower velocities in deeper layers. For the first time, functional ultrasound imaging demonstrates its potential to image brain activity chronically in small animals and offers new insights into the spatiotemporal evolution of cerebral hemodynamics.

Temporal jitter of the BOLD signal reveals a reliable initial dip and improved spatial resolution

fMRI, one of the most important noninvasive brain imaging methods, relies on the blood oxygen level-dependent (BOLD) signal, whose precise underpinnings are still not fully understood. It is a widespread assumption that the components of the hemodynamic response function (HRF) are fixed relative to each other in time, leading most studies as well as analysis tools to focus on trial-averaged responses, thus using or estimating a condition- or location-specific "canonical HRF". In the current study, we examined the nature of the variability of the BOLD response and asked in particular whether the positive BOLD peak is subject to trial-to-trial temporal jitter. Our results show that the positive peak of the stimulus-evoked BOLD signal exhibits a trial-to-trial temporal jitter on the order of seconds. Moreover, the trial-to-trial variability can be exploited to uncover the initial dip in the majority of voxels by pooling trial responses with large peak latencies. Initial dips exposed by this procedure possess higher spatial resolution compared to the positive BOLD signal in the human visual cortex. These findings allow for the reliable observation of fMRI signals that are physiologically closer to neural activity, leading to improvements in both temporal and spatial resolution.

Auditory neuroimaging with fMRI and PET

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. This article is part of a Special Issue entitled Human Auditory Neuroimaging.

A novel method of combining blood oxygenation and blood flow sensitive magnetic resonance imaging techniques to measure the cerebral blood flow and oxygen metabolism responses to an unknown neural stimulus

Simultaneous implementation of magnetic resonance imaging methods for Arterial Spin Labeling (ASL) and Blood Oxygenation Level Dependent (BOLD) imaging makes it possible to quantitatively measure the changes in cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO₂) that occur in response to neural stimuli. To date, however, the range of neural stimuli amenable to quantitative analysis is limited to those that may be presented in a simple block or event related design such that measurements may be repeated and averaged to improve precision. Here we examined the feasibility of using the relationship between cerebral blood flow and the BOLD signal to improve dynamic estimates of blood flow fluctuations as well as to estimate metabolic-hemodynamic coupling under conditions where a stimulus pattern is unknown. We found that by combining the information contained in simultaneously acquired BOLD and ASL signals through a method we term BOLD Constrained Perfusion (BCP) estimation, we could significantly improve the precision of our estimates of the hemodynamic response to a visual stimulus and, under the conditions of a calibrated BOLD experiment, accurately determine the ratio of the oxygen metabolic response to the hemodynamic response. Importantly we were able to accomplish this without utilizing a priori knowledge of the temporal nature of the neural stimulus, suggesting that BOLD Constrained Perfusion estimation may make it feasible to quantitatively study the cerebral metabolic and hemodynamic responses to more natural stimuli that cannot be easily repeated or averaged.

Reproducibility of swallow-induced cortical BOLD positive and negative fMRI activity

Functional MRI (fMRI) studies have demonstrated that a number of brain regions (cingulate, insula, prefrontal, and sensory/motor cortices) display blood oxygen level-dependent (BOLD) positive activity during swallow. Negative BOLD activations and reproducibility of these activations have not been systematically studied. The aim of our study was to investigate the reproducibility of swallow-related cortical positive and negative BOLD activity across different fMRI sessions. We studied 16 healthy volunteers utilizing an fMRI event-related analysis. Individual analysis using a general linear model was used to remove undesirable signal changes correlated with motion, white matter, and cerebrospinal fluid. The group analysis used a mixed-effects multilevel model to identify active cortical regions. The volume and magnitude of a BOLD signal within each cluster was compared between the two study sessions. All subjects showed significant clustered BOLD activity within the known areas of cortical swallowing network across both sessions. The cross-correlation coefficient of percent fMRI signal change and the number of activated voxels across both positive and negative BOLD networks were similar between the two studies (r ≥ 0.87, P < 0.0001). Swallow-associated negative BOLD activity was comparable to the well-defined "default-mode" network, and positive BOLD activity had noticeable overlap with the previously described "task-positive" network. Swallow activates two parallel cortical networks. These include a positive and a negative BOLD network, respectively, correlated and anticorrelated with swallow stimulus. Group cortical activity maps, as well as extent and amplitude of activity induced by volitional swallowing in the cortical swallowing network, are reproducible between study sessions.

Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O(2) utilization (CMRO(2)), (5) dynamic responses of BOLD, CBF, CMRO(2), and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means.

Twenty years of functional MRI: the science and the stories

Since its inception over twenty years ago, the field of functional magnetic resonance imaging (fMRI) has grown in usage, sophistication, range of applications, and impact. After twenty years, it's useful to briefly look back as well as forward - to size up just how far we have come and speculate just how far we may go. This is an introduction to the special issue of "Twenty years of fMRI: the science and the stories." The one-hundred and three papers in this special issue highlight the major methodological developments and controversies of fMRI from a first person perspective over the past twenty years. The growth of this field is not just fascinating from a science and technology perspective, but also from a human perspective. Most who were fortunate enough to be part of this effort at the beginning, as well as those who jumped in along the way have their fair share of interesting stories consisting of top rate science as well as intense thought and effort, good or bad fortune, and some claim to a contribution. These stories are in the following papers, written by the current leaders in the field and the innovators throughout the twenty year history. The categories, designed to cover every aspect of the emergence and development of fMRI, include: pre-fMRI; the first BOLD brain activation results; developments in pulse sequences, imaging methods, and hardware for fMRI; methodological developments, issues, and mechanisms; new paradigm designs; education; and the future. Within this issue, we have a collage of overlapping, complementary, yet sometimes contradictory accounts of what happened during the breathtakingly diverse and intense development of this still growing field over the past twenty years.

The story of the initial dip in fMRI

Over the past 20 years much attention has been given to characterizing the spatial accuracy of fMRI based signals and to techniques that improve on its co-localization with neuronal activity. While the vast majority of fMRI studies have always used the conventional positive BOLD signal, alternative contrast options have demonstrated superior spatial specificity. One of these options surfaced shortly after the initial BOLD fMRI demonstrations and was motivated by optical imaging studies which revealed an early signal change that was much smaller but spatially more specific than the delayed positive response. This early signal change was attributed to oxygenation changes prior to any subsequent blood flow increases. After observation of this biphasic hemodynamic response in fMRI, because this early response resulted in a small MR signal decrease prior to the onset of the large signal increase, it became known as the "initial dip". While the initial dip in fMRI was subsequently reported by many studies, including those in humans, monkeys, and cats, there were conflicting views about the associated mechanisms and whether it could be generalized across brain regions or species, in addition to whether or not it would prove fruitful for neuroscience. These discrepancies, along with the implications that the initial dip might increase the spatial specificity of BOLD fMRI from 2 to 3mm to something more closely associated with neural activity, resulted in lot of buzz and controversy in the community for many years. In this review, the authors provide an account of the story of the initial dip in MR based functional imaging from the Minnesota perspective, where the first demonstrations, characterizations, and applications of the initial dip commenced.

The intravascular susceptibility effect and the underlying physiology of fMRI

In this article, I will first give a brief account of my work at MGH on characterizing the intravascular susceptibility effect. Then I will describe studies into the underlying physiology of BOLD-fMRI which has become of interest to my group in the following decade. I will touch issues such as signal source of BOLD fMRI, capillary recruitment, the elusive initial dip and others.

Using manganese-enhanced MRI to understand BOLD

The 1990s were designated "The Decade of the Brain" by U.S. Congress, perhaps in great anticipation of the impact that functional neuroimaging techniques would have on advancing our understanding of how the brain is functionally organized. While it is impossible to overestimate the impact of functional MRI in neuroscience, many aspects of the blood oxygenation level-dependent (BOLD) contrast remain poorly understood, in great part due to the complex relationship between neural activity and hemodynamic changes. To better understand such relationship, it is important to probe neural activity independently. Manganese-enhanced MRI (MEMRI), when used to monitor neural activity, is a technique that uses the divalent manganese ion, Mn(2+), as a surrogate measure of calcium influx. A major advantage of using Mn(2+) as a functional marker is that the contrast obtained is directly related to the accumulation of the ion in excitable cells in an activity dependent manner. As such, the contrast in MEMRI is more directly related to neural activity then hemodynamic-based fMRI techniques. In the present work, the early conceptualization of MEMRI is reviewed, and the comparative experiments that have helped provide a better understanding of the spatial specificity of BOLD signal changes in the cortex is discussed.

High-field FMRI for human applications: an overview of spatial resolution and signal specificity

In the last decade, dozens of 7 Tesla scanners have been purchased or installed around the world, while 3 Tesla systems have become a standard. This increased interest in higher field strengths is driven by a demonstrated advantage of high fields for available signal-to-noise ratio (SNR) in the magnetic resonance signal. Functional imaging studies have additional advantages of increases in both the contrast and the spatial specificity of the susceptibility based BOLD signal. One use of this resultant increase in the contrast to noise ratio (CNR) for functional MRI studies at high field is increased image resolution. However, there are many factors to consider in predicting exactly what kind of resolution gains might be made at high fields, and what the opportunity costs might be. The first part of this article discusses both hardware and image quality considerations for higher resolution functional imaging. The second part draws distinctions between image resolution, spatial specificity, and functional specificity of the fMRI signals that can be acquired at high fields, suggesting practical limitations for attainable resolutions of fMRI experiments at a given field, given the current state of the art in imaging techniques. Finally, practical resolution limitations and pulse sequence options for studies in human subjects are considered.

Linear coupling of undershoot with BOLD response in ER-fMRI and nonlinear BOLD response in rapid-presentation ER-fMRI

In event-related (ER) BOLD-fMRI brain activation studies, understanding the relationship between the elicited BOLD signal and its underlying neuronal activity is essential for any quantitative interpretation of the neural events from the BOLD measurements. This requires a better understanding of the dynamic BOLD response. Besides the neuronal activity-induced positive BOLD response, the dynamic response is also characterized by a profound post-stimulus undershoot. The relationship between the positive response and the post-stimulus undershoot, however, remains poorly understood. Earlier studies using block-design paradigms with long stimulation durations (>10s) do not suggest a quantitative relationship. Using an ER paradigm, this study revealed a linear coupling between the positive BOLD response and the post-stimulus undershoot across the human visual cortex. The voxelwise linear coupling across the visual cortex strongly supports a homogeneous hemodynamic response in ER paradigms, though the BOLD response magnitude varies substantially over a wide range across the visual cortex. Although underlying neuronal activity is responsible for a BOLD response, the blood volume fraction affects the magnitude of the BOLD response; the larger the blood volume fraction, the larger the magnitude. This effect needs to be accounted for in any quantitative interpretation of the BOLD measurements. In the absence of nonlinear neuronal activities, the nonlinear vascular response renders the estimated BOLD responses smaller in rapid presentation (RP) ER paradigms compared to that in ER paradigms, and this reduction effect also needs to be considered when interpreting the estimated BOLD responses in RP-ER paradigms. Interestingly, this nonlinear effect might be simply accounted for by a scaling factor across the visual cortex.

Neurovascular and Neurometabolic Couplings in Dynamic Calibrated fMRI: Transient Oxidative Neuroenergetics for Block-Design and Event-Related Paradigms

Functional magnetic resonance imaging (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping brain activity. Interest in quantitative fMRI has renewed awareness in importance of oxidative neuroenergetics, as reflected by cerebral metabolic rate of oxygen consumption(CMRO2), for supporting brain function. Relationships between BOLD signal and the underlying neurophysiological parameters have been elucidated to allow determination of dynamic changes inCMRO2 by "calibrated fMRI," which require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and volume (CBV). But how doCMRO2 changes, steady-state or transient, derived from calibrated fMRI compare with neural activity recordings of local field potential (LFP) and/or multi-unit activity (MUA)? Here we discuss recent findings primarily from animal studies which allow high magnetic fields studies for superior BOLD sensitivity as well as multi-modal CBV and CBF measurements in conjunction with LFP and MUA recordings from activated sites. A key observation is that while relationships between neural activity and sensory stimulus features range from linear to non-linear, associations between hyperemic components (BOLD, CBF, CBV) and neural activity (LFP, MUA) are almost always linear. More importantly, the results demonstrate good agreement between the changes inCMRO2 and independent measures of LFP or MUA. The tight neurovascular and neurometabolic couplings, observed from steady-state conditions to events separated by <200 ms, suggest rapid oxygen equilibration between blood and tissue pools and thus calibrated fMRI at high magnetic fields can provide high spatiotemporal mapping ofCMRO2 changes.

Looking for neuronal currents using MRI: an EEG-fMRI investigation of fast MR signal changes time-locked to frequent focal epileptic discharges

RATIONALE

Reproducible direct measurement of neuronal electrical activity using MRI signal changes due to local magnetic field perturbations would represent a step change in neuroimaging methods. While some previous studies using experiments based on evoked and spontaneous activity provided encouraging results no clear demonstration of neuronal current-related MR changes in the human brain has emerged to date. The availability of simultaneously acquired EEG-fMRI in patients with frequent interictal epileptic discharges (IED), which have significantly greater amplitude than evoked potentials, offers the opportunity to further investigate the phenomenon.

METHODS

We re-analysed simultaneously acquired EEG-fMRI data in 6 epilepsy patients with very frequent focal IED and a well-localised generator. A model of MRI signal changes due to fast activity and BOLD signal changes was used to identify fast MR signal changes, potentially directly reflecting neuronal activity. Simultaneously-acquired EEG allowed the comparison of electrical source localisation (ESI), clinical epilepsy localisation and BOLD signal changes with the fast MR signal changes.

RESULTS

Clusters of IED-related fast MR signal change were observed in all cases. Spatial correspondence between the IED-related fast MR, BOLD, ESI clusters and irritative zone (IZ) was observed in one slice of a single dataset. The other IED-related fast MR clusters were remote from electro-clinically determined generators of interictal activity. The sign and magnitude of the fast MR signal changes varied across regions and subjects.

CONCLUSION

The observed fast MR changes cannot be confidently attributed to the direct effect of neuronal currents due to lack of spatial concordance with generators of interictal activity, IED-related BOLD clusters and ESI estimates.

Improvement of spectral density-based activation detection of event-related fMRI data

For event-related data obtained from an experimental paradigm with a periodic design, spectral density at the fundamental frequency of the paradigm has been used as a template-free activation detection measure. In this article, we build and expand upon this detection measure to create an improved, integrated measure. Such an integrated measure linearly combines information contained in the spectral densities at the fundamental frequency as well as the harmonics of the paradigm and in a spatial correlation function characterizing the degree of co-activation among neighboring voxels. Several figures of merit are described and used to find appropriate values for the coefficients in the linear combination. Using receiver-operating characteristic analysis on simulated functional magnetic resonance imaging (fMRI) data sets, we quantify and validate the improved performance of the integrated measure over the spectral density measure based on the fundamental frequency as well as over some other popular template-free data analysis methods. We then demonstrate the application of the new method on an experimental fMRI data set. Finally, several extensions to this work are suggested.

Refinement of optical imaging spectroscopy algorithms using concurrent BOLD and CBV fMRI

We describe the use of the three dimensional characteristics of the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) and cerebral blood volume (CBV) MRI signal changes to refine a two dimensional optical imaging spectroscopy (OIS) algorithm. The cortical depth profiles of the BOLD and CBV changes following neural activation were used to parameterise a 5-layer heterogeneous tissue model used in the Monte Carlo simulations (MCS) of light transport through tissue in the OIS analysis algorithm. To transform the fMRI BOLD and CBV measurements into deoxy-haemoglobin (Hbr) profiles we inverted an MCS of extra-vascular MR signal attenuation under the assumption that the extra-/intravascular ratio is 2:1 at a magnetic field strength of 3 T. The significant improvement in the quantitative accuracy of haemodynamic measurements using the new heterogeneous tissue model over the original homogeneous tissue model OIS algorithm was demonstrated on new concurrent OIS and fMRI data covering a range of stimulus durations.

Nonlinear denoising of functional magnetic resonance imaging time series with wavelets

In functional magnetic resonance imaging (fMRI) the blood oxygenation level dependent (BOLD) effect is used to identify and delineate neuronal activity. The sensitivity of a fMRI-based detection of neuronal activation, however, strongly depends on the relative levels of signal and noise in the time series data, and a large number of different artifact and noise sources interfere with the weak signal changes of the BOLD response. Thus, noise reduction is important to allow an accurate estimation of single activation-related BOLD signals across brain regions. Techniques employed so far include filtering in the time or frequency domain which, however, does not take into account possible nonlinearities of the BOLD response. We here evaluate a previously proposed method for nonlinear denoising of short and transient signals, which combines the wavelet transform with techniques from nonlinear time series analysis. We adopt the method to the problem at hand and show that successful noise reduction and, more importantly, preservation of the shape of individual BOLD signals can be achieved even in the presence of in-band noise.

Oxidative neuroenergetics in event-related paradigms

Energetic basis of neural activity provides a solid foundation for noninvasive neuroimaging with calibrated functional magnetic resonance imaging (fMRI). Calculating dynamic changes in cerebral oxidative energy utilization (CMR(O(2))) is limited by uncertainties about whether or not the conventional blood oxygenation level-dependent (BOLD) model can be applied transiently using multimodal measurements of blood flow (CBF) and volume (CBV) that affect the BOLD signal. A prerequisite for dynamic calibrated fMRI is testing the linearity of multimodal signals within a temporal regimen, as assessed by signal strength (i.e., both intensity and width). If each hyperemic component (BOLD, CBV, CBF) is demonstrated to be linear with neural activity under various experimental conditions, then the respective transfer functions generated by deconvolution with neural activity should be time invariant and thus could potentially be used for calculating CMR(O(2)) transients. Hyperemic components were investigated at 11.7 T in alpha-chloralose-anesthetized rats and combined with electrophysiological recordings of local field potential (LFP) and multiunit activity (MUA) from the cortex during forepaw stimulation, in which stimulus number and frequency were varied. Although relationships between neural activity and stimulus features ranged from linear to nonlinear, associations between hyperemic components and neural activity were linear. Specific to each hyperemic component, a universal transfer function (with LFP or MUA) yielded predictions in agreement with experimental measurements. The results identified a component of the BOLD signal that can be attributed to significant changes in CMR(O(2)), even for temporal events separated by <200 ms.

Polarographic Electrode Measures of Cerebral Tissue Oxygenation: Implications for Functional Brain Imaging

The changes in blood flow, blood volume and oxygenation that accompany focal increases in neural activity are collectively referred to as the hemodynamic response and form the basis of non-invasive neuroimaging techniques such as blood oxygen level dependent (BOLD) functional magnetic resonance imaging. A principle factor influencing blood oxygenation, the cerebral metabolic rate of oxygen consumption is poorly understood and as such, data from imaging techniques are difficult to interpret in terms of the underlying neural activity. In particular how neurometabolic changes vary temporally, spatially and in magnitude remains uncertain. Furthermore knowledge of which aspects of neural activity are closely reflected by metabolic changes is essential for the correct interpretation of cognitive neuroscience studies in terms of information processing. Polarographic electrode measurements of cerebral tissue oxygenation in animal models following presentation of sensory stimuli have started to address these issues. Early studies demonstrated both increases and decreases in tissue oxygenation following neural activation. However a recent series of elegant studies in the cat visual system demonstrated a tight spatial and temporal coupling between evoked peri-synaptic activity and oxygen consumption following presentation of visual stimuli.

Analysis of fMRI data using improved self-organizing mapping and spatio-temporal metric hierarchical clustering

The self-organizing mapping (SOM) and hierarchical clustering (HC) methods are integrated to detect brain functional activation; functional magnetic resonance imaging (fMRI) data are first processed by SOM to obtain a primary merged neural nodes image, and then by HC to obtain further brain activation patterns. The conventional Euclidean distance metric was replaced by the correlation distance metric in SOM to improve clustering and merging of neural nodes. To improve the use of spatial and temporal information in fMRI data, a new spatial distance (node coordinates in the 2-D lattice) and temporal correlation (correlation degree of each time course in the exemplar matrix) are introduced in HC to merge the primary SOM results. Two simulation studies and two in vivo fMRI data that both contained block-design and event-related experiments revealed that brain functional activation can be effectively detected and that different response patterns can be distinguished using these methods. Our results demonstrate that the improved SOM and HC methods are clearly superior to the statistical parametric mapping (SPM), independent component analysis (ICA), and conventional SOM methods in the block-design, especially in the event-related experiment, as revealed by their performance measured by receiver operating characteristic (ROC) analysis. Our results also suggest that the proposed new integrated approach could be useful in detecting block-design and event-related fMRI data.

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

We measured blood oxygen level dependent (BOLD) responses to the onset of dynamic noise stimulation in defined regions of the primary retinotopic projection (V1) in visual cortex. The response waveforms showed a remarkable diversity across stimulus types, violating the basic assumption of a unitary general linear model of a uniform BOLD response function convolved with each stimulus sequence. We used independent component analysis (ICA) to analyze the component mechanisms contributing to these responses. The underlying neural responses for the components were estimated by nonlinear optimization through the Friston-Buxton hemodynamic model of the BOLD response. Our analysis suggests that one of the identified components reflected a sustained neural response to the stimulus and that another reflected an extremely slow neural response. A third component exhibited nonlinear change-specific transient responses. The first two components showed stable spatial structure in the V1 region of interest with respect to the eccentricity of the noise stimulus.

Strategies for molecular imaging dementia and neurodegenerative diseases

Dementia represents a heterogeneous term that has evolved to describe the behavioral syndromes associated with a variety of clinical and neuropathological changes during continuing degenerative disease of the brain. As such, there lacks a clear consensus regarding the neuropsychological and other constituent characteristics associated with various cerebrovascular changes in this disease process. But increasing this knowledge has given more insights into memory deterioration in patients suffering from Alzheimer's disease and other subtypes of dementia. The author reviews current knowledge of the physiological coupling between cerebral blood flow and metabolism in the light of state-of-the-art-imaging methods and its changes in dementia with special reference to Alzheimer's disease. Different imaging techniques are discussed with respect to their visualizing effect of biochemical, cellular, and/or structural changes in dementia. The pathophysiology of dementia in advanced age is becoming increasingly understood by revealing the underlying basis of neuropsychological changes with current imaging techniques, genetic and pathological features, which suggests that alterations of (neuro) vascular regulatory mechanisms may lead to brain dysfunction and disease. The current view is that cerebrovascular deregulation is seen as a contributor to cerebrovascular pathologies, such as stroke, but also to neurodegenerative conditions, such as Alzheimer's disease. The better understanding of these (patho) physiological mechanisms may open an approach to new interventional strategies in dementia to enhance neurovascular repair and to protect neurovascular coupling.

Coupling between neuronal activity and microcirculation: implications for functional brain imaging

In the neocortex, neurons with similar response properties are often clustered together in column-like structures, giving rise to what has become known as functional architecture-the mapping of various stimulus feature dimensions onto the cortical sheet. At least partially, we owe this finding to the availability of several functional brain imaging techniques, both post-mortem and in-vivo, which have become available over the last two generations, revolutionizing neuroscience by yielding information about the spatial organization of active neurons in the brain. Here, we focus on how our understanding of such functional architecture is linked to the development of those functional imaging methodologies, especially to those that image neuronal activity indirectly, through metabolic or haemodynamic signals, rather than directly through measurement of electrical activity. Some of those approaches allow exploring functional architecture at higher spatial resolution than others. In particular, optical imaging of intrinsic signals reaches the striking detail of approximately 50 mum, and, together with other methodologies, it has allowed characterizing the metabolic and haemodynamic responses induced by sensory-evoked neuronal activity. Here, we review those findings about the spatio-temporal characteristics of neurovascular coupling and discuss their implications for functional brain imaging, including position emission tomography, and non-invasive neuroimaging techniques, such as funtional magnetic resonance imaging, applicable also to the human brain.

Source of nonlinearity of the BOLD response revealed by simultaneous fMRI and NIRS

The nonlinearity of the blood oxygenation level-dependent (BOLD) response to stimuli of different duration, particularly those of short duration, has been well studied by functional magnetic resonance imaging (fMRI). This nonlinearity is assumed to be due to neural adaptation and the nonlinearity of the response in the oxygen extraction fraction (OEF); the latter has not been examined quantitatively in humans. To evaluate how the OEF response contributes to the nonlinearity of the BOLD response to neural activity, we used simultaneous fMRI and near-infrared spectroscopy (NIRS). The responses to visual stimuli of four different durations were measured as changes in the BOLD signal and the NIRS-derived hemoglobin concentrations. The hemodynamic response nonlinearity was quantified using an impulse response function model with saturation nonlinearity scaling in the response amplitude, assuming that the unknown neural adaptation parameters varied within a physiologically feasible range. Independent of the degree of neural adaptation, the BOLD response consistently showed saturation nonlinearity similar to that of the OEF response estimated from the NIRS measures, the nonlinearity of which was greater than that of the response in the total hemoglobin concentration representing the cerebral blood volume (CBV). We also found that the contribution of the OEF response to the BOLD response was four to seven times greater than the contribution of the CBV response. Thus, we conclude that the nonlinearity of the BOLD response to neural activity originates mainly from that of the OEF response.

Robust detection of ocular dominance columns in humans using Hahn Spin Echo BOLD functional MRI at 7 Tesla

Cells in the mammalian brain tend to be grouped together according to their afferent and efferent connectivity, as well as their physiological properties. The columnar structures of neocortex are prominent examples of such modular organization, and have been studied extensively in anatomical and physiological experiments in rats, cats and monkeys. The importance of noninvasive study of such structures, in particular in human subjects, cannot be overemphasized. Not surprisingly, therefore, many attempts were made to map cortical columns using functional magnetic resonance imaging (fMRI). Yet, the robustness, repeatability, and generality of the hitherto used fMRI methodologies have been a subject of intensive debate. Using differential mapping in a high magnetic field magnet (7 T), we demonstrate here the ability of Hahn Spin-Echo (HSE) BOLD to map the ocular dominance columns (ODCs) of the human visual cortex reproducibly over several days with a high degree of accuracy, relative to expected spatial patterns from post-mortem data. On the other hand, the conventional Gradient-Echo (GE) blood oxygen level dependent (BOLD) signal in some cases failed to resolve ODCs uniformly across the selected gray matter region, due to the presence of non-specific signals. HSE signals uniformly resolved the ODC patterns, providing a more generalized mapping methodology (i.e. one that does not require adjusting experimental approaches based on prior knowledge or assumptions about functional organization and vascular structure in order to avoid confounding large vessel effects) to map unknown columnar systems in the human brain, potentially paving the way both for the study of the functional architecture of human sensory cortices, and of brain modules underlying specific cognitive processes.

TMS orientation for NIRS-functional motor mapping

Functional near-infrared spectroscopic imaging (NIRS imaging) has the potential to elucidate the relationship between neuronal activity and oxygenation responses. However, its signal specificity to the functional cortex is sometimes spoiled by its rough spatial resolution. In this study we incorporated transcranial magnetic stimulation (TMS) motor mapping into an NIRS imaging study to enhance spatial specificity to the functional cortex. Distinctive biphasic responses in the cortical oxygenation status were observed in the center of the primary motor cortex during a motor task. The early response phase, occurring within 1 to 3 seconds after task initiation, represents a cortical deoxygenation which consists of a significant increase in deoxygenated hemoglobin concentration (HbR) and a nonsignificant decreasing tendency in oxygenated hemoglobin concentration (HbO(2)). The delayed response phase represents an excess of incoming blood flow, which appears as an increase in HbO(2)/total Hb (tHb) and a decrease in HbR following the early response. In the surrounding area, cortical oxygenation change showed a monophasic response consisting of an increase in HbO(2)/tHb and a decrease in HbR. Combining TMS mapping with NIRS imaging enabled us to specify the cortex with the strongest functional activity.

Phantom calibration method for improved temporal characterization of hemodynamic response in event-related fMRI

In event-related functional MRI, there exist limits on the time length of the experiments on human subjects and the imaging speed. Due to these limitations, data truncation and undersampling have to be used in functional MRI signal acquisition. The effect of these factors on the hemodynamic deconvolution is investigated experimentally and a phantom calibration method to improve the hemodynamic response is developed. It is observed that the high frequency components generated due to data truncation can fold back into low frequencies when the sampling rate is not sufficiently high. This aliasing can introduce significant noise in hemodynamic deconvolution and can reduce the accuracy of the temporal characterization of hemodynamic response. A SMARTPHANTOM BOLD simulator is used to calibrate the aliasing effect in an event-related functional MRI experiment. With the calibration, an anti-aliasing method is used to suppress the aliasing and this resulted in an improved temporal characterization of hemodynamic response in event-related fMRI.