The spatial extent of the BOLD response

Deep EEG source localization via EMD-based fMRI high spatial frequency

Brain imaging with a high-spatiotemporal resolution is crucial for accurate brain-function mapping. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two popular neuroimaging modalities with complementary features that record brain function with high temporal and spatial resolution, respectively. One popular non-invasive way to obtain data with both high spatial and temporal resolutions is to combine the fMRI activation map and EEG data to improve the spatial resolution of the EEG source localization. However, using the whole fMRI map may cause spurious results for the EEG source localization, especially for deep brain regions. Considering the head's conductivity, deep regions' sources with low activity are unlikely to be detected by the EEG electrodes at the scalp. In this study, we use fMRI's high spatial-frequency component to identify the local high-intensity activations that are most likely to be captured by the EEG. The 3D Empirical Mode Decomposition (3D-EMD), a data-driven method, is used to decompose the fMRI map into its spatial-frequency components. Different validation measurements for EEG source localization show improved performance for the EEG inverse-modeling informed by the fMRI's high-frequency spatial component compared to the fMRI-informed EEG source-localization methods. The level of improvement varies depending on the voxels' intensity and their distribution. Our experimental results also support this conclusion.

Whole-brain, gray, and white matter time-locked functional signal changes with simple tasks and model-free analysis

Recent studies have revealed the production of time-locked blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to tasks, challenging the existence of sparse and localized brain functions and highlighting the pervasiveness of potential false negative fMRI findings. "Whole-brain" actually refers to gray matter, the only tissue traditionally studied with fMRI. However, several reports have demonstrated reliable detection of BOLD signals in white matter, which have previously been largely ignored. Using simple tasks and analyses, we demonstrate BOLD signal changes across the whole brain, in both white and gray matters, in similar manner to previous reports of whole brain studies. We investigated whether white matter displays time-locked BOLD signals across multiple structural pathways in response to a stimulus in a similar manner to the cortex. We find that both white and gray matter show time-locked activations across the whole brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that, just like all gray matter, essentially all white matter in the brain shows time-locked BOLD signal changes in response to multiple stimuli, challenging the idea of sparse functional localization and the prevailing wisdom of treating white matter BOLD signals as artifacts to be removed.

Tracking spatial dynamics of functional connectivity during a task

Functional connectivity (FC) measured from functional magnetic resonance imaging (fMRI) provides a powerful tool to explore brain organization. Studies of the temporal dynamics of brain organization have shown a large temporal variability of the functional connectome, which may be associated with mental status transitions and/or adaptive process. Most dynamic studies, e.g. functional connectome and functional network connectivity (FNC), have focused on the macroscopic FC changes, i.e. the changes of temporal coherence across various brain network sources, nodes and/or regions of interest, where it is assumed within the network or node that the FC is static. In this paper, we develop a novel method to examine the spatial dynamics of FC, without the assumption of its intra-network stationarity. We applied our approach to fMRI data during an auditory oddball task (AOD) from twenty-two subjects, in an attempt to capture/validate the approach by evaluating whether spatial connectivity varies with task condition. The results showed that connectivity networks exhibit spatial variability over time, in addition to participating in conventional temporal dynamics, i.e. cross-network variability or dynamic functional network connectivity (dFNC). Furthermore, we studied the relationship of spatial dynamic in FC to cognitive processes, by performing a cluster analysis to evaluate an individual's functional correspondence towards the 'target' (oddball) detection from AOD task, and extracting cognitive task correspondence states as well as their dynamic FC spatial maps segregated by such states. We found a clear trend in different task-guided states, particularly, a prominent reduction of task stimulus synchrony state along with strong anticorrelation between default mode network (DMN) and cognitive attentional networks. We also observed an increasing occurrence of the task desynchrony state which showed an absence of DMN anticorrelation. The results highlight the impact of a well-studied cognitive task on the observed spatial dynamic structure. We also showed that the FC spatial dynamic pattern from our method largely corresponds to macroscopic dFNC patterns, but with more details and specifications over space, meanwhile the connectivity within the source itself provides novel information and varies over time. Overall, we demonstrate clear evidence of the presence of the (usually ignored) spatial dynamics of connectivity, its links to the task and implications of cognition/mental status.

Regional variation in neurovascular coupling and why we still lack a Rosetta Stone

Functional magnetic resonance imaging (fMRI) is the dominant tool in cognitive neuroscience although its relation to underlying neural activity, particularly in the human brain, remains largely unknown. A major research goal, therefore, has been to uncover a 'Rosetta Stone' providing direct translation between the blood oxygen level-dependent (BOLD) signal, the local field potential and single-neuron activity. Here, I evaluate the proposal that BOLD signal changes equate to changes in gamma-band activity, which in turn may partially relate to the spiking activity of neurons. While there is some support for this idea in sensory cortices, findings in deeper brain structures like the hippocampus instead suggest both regional and frequency-wise differences. Relatedly, I consider four important factors in linking fMRI to neural activity: interpretation of correlations between these signals, regional variability in local vasculature, distributed neural coding schemes and varying fMRI signal quality. Novel analytic fMRI techniques, such as multivariate pattern analysis (MVPA), employ the distributed patterns of voxels across a brain region to make inferences about information content rather than whether a small number of voxels go up or down relative to baseline in response to a stimulus. Although unlikely to provide a Rosetta Stone, MVPA, therefore, may represent one possible means forward for better linking BOLD signal changes to the information coded by underlying neural activity. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Impaired error awareness in healthy older adults: an age group comparison study

Aging is associated with reduced conscious error detection but the brain regions mediating these changes have yet to be clarified. The present study examined the neural correlates of error awareness in healthy older adults. Sixteen older participants (mean age = 75.5 years) and sixteen younger controls (mean age = 27.9 years) were administered the error awareness task, a go/no-go response inhibition paradigm, in which participants were required to signal commission errors. Compared with young adults, older adults were significantly poorer at consciously detecting performance errors, despite both groups being matched for overall accuracy. This age-related behavioral effect was associated with differences in error-related dorsal anterior cingulate cortex and insula activation, with younger adults showing significant differences between errors made with versus without awareness compared with older adults. By contrast, an age-specific modulation in right inferior parietal lobule activation emerged, with increased right inferior parietal lobule activity occurring in older adults during errors made with awareness compared with younger adults. These findings are consistent with theories of age-related deterioration in error processing mechanisms.

Following the Spreading of Brain Structural Changes in Alzheimer's Disease: A Longitudinal, Multimodal MRI Study

BACKGROUND

Longitudinal MRI studies in Alzheimer's disease (AD) are one of the most reliable way to track brain changes along the course of the disease.

OBJECTIVE

To investigate the evolution of grey matter (GM) atrophy and white matter (WM) damage in AD patients, and to assess the relationships of MRI changes with baseline clinical and cognitive variables and their evolution over time.

METHODS

Clinical, neuropsychological, and MRI assessments (T1-weighted and diffusion tensor [DT]-MRI) were obtained from 14 patients with AD at baseline and after a 16 ± 3 month period. Lumbar puncture was obtained at study entry. At baseline, AD patients were compared to 37 controls. GM atrophy progression was assessed with tensor-based morphometry and GM volumes of interest, and WM damage progression using tract-based spatial statistics and tractography.

RESULTS

At baseline, patients showed cortical atrophy in the medial temporal and parietal regions and a widespread pattern of WM damage involving the corpus callosum, cingulum, and temporo-occipital, parietal, and frontal WM tracts. During follow up, AD patients showed total GM atrophy, while total WM volume did not change. GM tissue loss was found in frontal, temporal, and parietal regions. In addition, AD patients showed a progression of WM microstructural damage to the corpus callosum, cingulum, fronto-parietal and temporo-occipital connections bilaterally. Patients with higher baseline cerebrospinal fluid total tau showed greater WM integrity loss at follow up. GM and WM changes over time did not correlate with each other nor with cognitive evolution.

CONCLUSION

In AD, GM atrophy and WM tract damage are likely to progress, at least partially, independently. This study suggests that a multimodal imaging approach, which includes both T1-weighted and DT MR imaging, may provide additional markers to monitor disease progression.

Functional Magnetic Resonance Imaging for Cranial Neuronavigation: Methods for Automated and Standardized Data Processing and Management

Preoperative fMRI is one of the best established clinical fMRI applications. Due to the difficulties in recording and coregistration of functional image data, we present methods to standardize and automate these procedures. We used a self-made interactive software package (AFI — Automated Functional Imaging) to automate the time consuming and complex analysis of fMRI data. AFI controls the BrainVoyager program, a postprocessing software package, and furthermore facilitates data management, anonymization of patient data, storage, documentation, data export to neuronavigation systems and the opportunity of spatial transformation of image data for use in group studies. By the end of 2006 we have used this method on 123 patients with brain tumors and 47 patients with trigeminal neuralgia. The fundamental basis of multimodal neuronavigation is precise coregistration. EPI images contain spatial distortions of 5–15 mm. We were able to reduce the misregistration of EPI and FLASH images in a selectable region of interest to 1–2 mm. Furthermore AFI reduces the average evaluation time for a standard clinical fMRI study (four functional measurements, one anatomical data set) by approx. 50% from 140 minutes to about 70 minutes in comparison to manual evaluation by an expert. More importantly, the personal attendance time required for the evaluation decreases by 84% to 23 minutes as the remainder of the program runs automatically. In comparison to currently available online postprocessing software tools which are more limited in use, BrainVoyager can be used for coregistration, data export to neuronavigation systems and spatial transformation.

Non-invasive detection of high gamma band activity during motor imagery

High gamma oscillations (70-150 Hz; HG) are rapidly evolving, spatially localized neurophysiological signals that are believed to be the best representative signature of engaged neural populations. The HG band has been best characterized from invasive electrophysiological approaches such as electrocorticography because of the increased signal-to-noise ratio that results when by-passing the scalp and skull. Despite the recent observation that HG activity can be detected non-invasively by electroencephalography (EEG), it is unclear to what extent EEG can accurately resolve the spatial distribution of HG signals during active task engagement. We have overcome some of the limitations inherent to acquiring HG signals across the scalp by utilizing individual head anatomy in combination with an inverse modeling method. We applied a linearly constrained minimum variance (LCMV) beamformer method on EEG data during a motor imagery paradigm to extract a time-frequency spectrogram at every voxel location on the cortex. To confirm spatially distributed patterns of HG responses, we contrasted overlapping maps of the EEG HG signal with blood oxygen level dependence (BOLD) functional magnetic resonance imaging (fMRI) data acquired from the same set of neurologically normal subjects during a separate session. We show that scalp-based HG band activity detected by EEG during motor imagery spatially co-localizes with BOLD fMRI data. Taken together, these results suggest that EEG can accurately resolve spatially specific estimates of local cortical high frequency signals, potentially opening an avenue for non-invasive measurement of HG potentials from diverse sets of neurologically impaired populations for diagnostic and therapeutic purposes.

Task Dependence, Tissue Specificity, and Spatial Distribution of Widespread Activations in Large Single-Subject Functional MRI Datasets at 7T

It was recently shown that when large amounts of task-based blood oxygen level-dependent (BOLD) data are combined to increase contrast- and temporal signal-to-noise ratios, the majority of the brain shows significant hemodynamic responses time-locked with the experimental paradigm. Here, we investigate the biological significance of such widespread activations. First, the relationship between activation extent and task demands was investigated by varying cognitive load across participants. Second, the tissue specificity of responses was probed using the better BOLD signal localization capabilities of a 7T scanner. Finally, the spatial distribution of 3 primary response types--namely positively sustained (pSUS), negatively sustained (nSUS), and transient--was evaluated using a newly defined voxel-wise waveshape index that permits separation of responses based on their temporal signature. About 86% of gray matter (GM) became significantly active when all data entered the analysis for the most complex task. Activation extent scaled with task load and largely followed the GM contour. The most common response type was nSUS BOLD, irrespective of the task. Our results suggest that widespread activations associated with extremely large single-subject functional magnetic resonance imaging datasets can provide valuable information about the functional organization of the brain that goes undetected in smaller sample sizes.

The role of the anterior insula in adolescent decision making

Much recent research on adolescent decision making has sought to characterize the neurobiological mechanisms that underlie the proclivity of adolescents to engage in risky behavior. One class of influential neurodevelopmental models focuses on the asynchronous development of neural systems, particularly those responsible for self-regulation and reward seeking. While this work has largely focused on the development of prefrontal (self-regulation) and striatal (reward processing) circuitry, the present article explores the significance of a different region, the anterior insular cortex (AIC), in adolescent decision making. Although the AIC is known for its role as a cognitive-emotional hub, and is included in some models of adult self-regulation and reward seeking, the importance of the AIC and its maturation in adolescent risk taking has not been extensively explored. In this article we discuss evidence on AIC development, and consider how age-related differences in AIC engagement may contribute to heightened risk taking during adolescence. Based on this review, we propose a model in which the engagement of adolescents in risk taking may be linked in part to the maturation of the AIC and its connectivity to the broader brain networks in which it participates.

The efficiency of fMRI region of interest analysis methods for detecting group differences

BACKGROUND

Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods.

NEW METHOD

We compared analyses of group differences when using standard versus native space ROIs using both volume and surface-based analyses. Collegiate and military-veteran participants completed a button press task and a digit-symbol verification task during fMRI acquisition. Data were analyzed within ROIs representing left and right motor and prefrontal cortices, in native and standard space. Volume and surface-based analysis results were also compared using both functional (i.e., percent signal change) and structural (i.e., voxel or node count) approaches.

RESULTS AND COMPARISON WITH EXISTING METHOD(S)

Results suggest that transformation into standard space can affect the outcome of structural and functional analyses (inflating/minimizing differences, based on cortical geography), and these transformations can affect conclusions regarding group differences with volumetric data.

CONCLUSIONS

Caution is advised when applying standard space ROIs to volumetric fMRI data. However, volumetric analyses show group differences and are appropriate in circumstances when time is limited. Surface-based analyses using functional ROIs generated the greatest group differences and were less susceptible to differences between native and standard space. We conclude that surface-based analyses are preferable with adequate time and computing resources.

Neuroimaging predictors of cognitive performance across a standardized neurocognitive battery

OBJECTIVE

The advent of functional MRI (fMRI) enables the identification of brain regions recruited for specific behavioral tasks. Most fMRI studies focus on group effects in single tasks, which limits applicability where assessment of individual differences and multiple brain systems is needed.

METHOD

We demonstrate the feasibility of concurrently measuring fMRI activation patterns and performance on a computerized neurocognitive battery (CNB) in 212 healthy individuals at 2 sites. Cross-validated sparse regression of regional brain amplitude and extent of activation were used to predict concurrent performance on 6 neurocognitive tasks: abstraction/mental flexibility, attention, emotion processing, and verbal, face, and spatial memory.

RESULTS

Brain activation was task responsive and domain specific, as reported in previous single-task studies. Prediction of performance was robust for most tasks, particularly for abstraction/mental flexibility and visuospatial memory.

CONCLUSIONS

The feasibility of administering a comprehensive neuropsychological battery in the scanner was established, and task-specific brain activation patterns improved prediction beyond demographic information. This benchmark index of performance-associated brain activation can be applied to link brain activation with neurocognitive performance during standardized testing. This first step in standardizing a neurocognitive battery for use in fMRI may enable quantitative assessment of patients with brain disorders across multiple cognitive domains. Such data may facilitate identification of neural dysfunction associated with poor performance, allow for identification of individuals at risk for brain disorders, and help guide early intervention and rehabilitation of neurocognitive deficits.

Massive modulation of brain areas after mechanical pain stimulation: a time-resolved FMRI study

To date, relatively little is known about the spatiotemporal aspects of whole-brain blood oxygenation level-dependent (BOLD) responses to brief nociceptive stimuli. It is known that the majority of brain areas show a stimulus-locked response, whereas only some are characterized by a canonical hemodynamic response function. Here, we investigated the time course of brain activations in response to mechanical pain stimulation applied to participants' hands while they were undergoing functional magnetic resonance imaging (fMRI) scanning. To avoid any assumption about the shape of BOLD response, we used an unsupervised data-driven method to group voxels sharing a time course similar to the BOLD response to the stimulus and found that whole-brain BOLD responses to painful mechanical stimuli elicit massive activation of stimulus-locked brain areas. This pattern of activations can be segregated into 5 clusters, each with a typical temporal profile. In conclusion, we show that an extensive activity of multiple networks is engaged at different time latencies after presentation of a noxious stimulus. These findings aim to motivate research on a controversial topic, such as the temporal profile of BOLD responses, the variability of these response profiles, and the interaction between the stimulus-related BOLD response and ongoing fluctuations in large-scale brain networks.

Recursive grid partitioning on a cortical surface model: an optimized technique for the localization of implanted subdural electrodes

Object

Precise localization of subdural electrodes (SDEs) is essential for the interpretation of data from intracranial electrocorticography recordings. Blood and fluid accumulation underneath the craniotomy flap leads to a nonlinear deformation of the brain surface and of the SDE array on postoperative CT scans and adversely impacts the accurate localization of electrodes located underneath the craniotomy. Older methods that localize electrodes based on their identification on a postimplantation CT scan with coregistration to a preimplantation MR image can result in significant problems with accuracy of the electrode localization. The authors report 3 novel methods that rely on the creation of a set of 3D mesh models to depict the pial surface and a smoothed pial envelope. Two of these new methods are designed to localize electrodes, and they are compared with 6 methods currently in use to determine their relative accuracy and reliability.

Methods

The first method involves manually localizing each electrode using digital photographs obtained at surgery. This is highly accurate, but requires time intensive, operator-dependent input. The second uses 4 electrodes localized manually in conjunction with an automated, recursive partitioning technique to localize the entire electrode array. The authors evaluated the accuracy of previously published methods by applying the methods to their data and comparing them against the photograph-based localization. Finally, the authors further enhanced the usability of these methods by using automatic parcellation techniques to assign anatomical labels to individual electrodes as well as by generating an inflated cortical surface model while still preserving electrode locations relative to the cortical anatomy.

Results

The recursive grid partitioning had the least error compared with older methods (672 electrodes, 6.4-mm maximum electrode error, 2.0-mm mean error, p < 10−18). The maximum errors derived using prior methods of localization ranged from 8.2 to 11.7 mm for an individual electrode, with mean errors ranging between 2.9 and 4.1 mm depending on the method used. The authors also noted a larger error in all methods that used CT scans alone to localize electrodes compared with those that used both postoperative CT and postoperative MRI. The large mean errors reported with these methods are liable to affect intermodal data comparisons (for example, with functional mapping techniques) and may impact surgical decision making.

Conclusions

The authors have presented several aspects of using new techniques to visualize electrodes implanted for localizing epilepsy. The ability to use automated labeling schemas to denote which gyrus a particular electrode overlies is potentially of great utility in planning resections and in corroborating the results of extraoperative stimulation mapping. Dilation of the pial mesh model provides, for the first time, a sense of the cortical surface not sampled by the electrode, and the potential roles this “electrophysiologically hidden” cortex may play in both eloquent function and seizure onset.

A sliding time-window ICA reveals spatial variability of the default mode network in time

Recent evidence on resting-state networks in functional (connectivity) magnetic resonance imaging (fcMRI) suggests that there may be significant spatial variability of activity foci over time. This study used a sliding time window approach with the spatial domain-independent component analysis (SliTICA) to detect spatial maps of resting-state networks over time. The study hypothesis was that the spatial distribution of a functionally connected network would present marked variability over time. The spatial stability of successive sliding-window maps of the default mode network (DMN) from fcMRI data of 12 participants imaged in the resting state was analyzed. Control measures support previous findings on the stability of independent component analysis in measuring sliding-window sources accurately. The spatial similarity of successive DMN maps varied over time at low frequencies and presented a 1/f power spectral pattern. SliTICA maps show marked temporal variation within the DMN; a single voxel was detected inside a group DMN map in maximally 82% of time windows. Mapping of incidental connectivity reveals centrifugally increasing connectivity to the brain cortex outside the DMN core areas. In conclusion, SliTICA shows marked spatial variance of DMN activity in time, which may offer a more comprehensive measurement of the overall functional activity of a network.

Evaluation and calibration of functional network modeling methods based on known anatomical connections

Recent studies have identified large scale brain networks based on the spatio-temporal structure of spontaneous fluctuations in resting-state fMRI data. It is expected that functional connectivity based on resting-state data is reflective of - but not identical to - the underlying anatomical connectivity. However, which functional connectivity analysis methods reliably predict the network structure remains unclear. Here we tested and compared network connectivity analysis methods by applying them to fMRI resting-state time-series obtained from the human visual cortex. The methods evaluated here are those previously tested against simulated data in Smith et al. (Neuroimage, 2011). To this end, we defined regions within retinotopic visual areas V1, V2, and V3 according to their eccentricity in the visual field, delineating central, intermediate, and peripheral eccentricity regions of interest (ROIs). These ROIs served as nodes in the models we study. We based our evaluation on the "ground-truth", thoroughly studied retinotopically-organized anatomical connectivity in the monkey visual cortex. For each evaluated method, we computed the fractional rate of detecting connections known to exist ("c-sensitivity"), while using a threshold of the 95th percentile of the distribution of interaction magnitudes of those connections not expected to exist. Under optimal conditions - including session duration of 68min, a relatively small network consisting of 9 nodes and artifact-free regression of the global effect - each of the top methods predicted the expected connections with 67-85% c-sensitivity. Correlation methods, including Correlation (Corr; 85%), Regularized Inverse Covariance (ICOV; 84%) and Partial Correlation (PCorr; 81%) performed best, followed by Patel's Kappa (80%), Bayesian Network method PC (BayesNet; 77%), General Synchronization measures (67-77%), and Coherence (CohB; 74%). With decreased session duration, these top methods saw decreases in c-sensitivities, achieving 59-76% for 17min sessions. With a short resting-state fMRI scan of 8.5min, none of the methods predicted the real network well, with Corr (65%) performing best. With increased complexity of the network from 9 to 36 nodes, multivariate methods including PCorr and BayesNet saw a decrease in performance. Artifact-free regression of the global effect increased the c-sensitivity of the top-performing methods. In an overall evaluation across all tests we performed, correlation methods (Corr, ICOV, and PCorr), Patel's Kappa, and BayesNet method PC set themselves somewhat above all other methods. We propose that data-based calibration based on known anatomical connections be integrated into future network studies, in order to maximize sensitivity and reduce false positives.

Intracranial electroencephalography reveals different temporal profiles for dorsal- and ventro-lateral prefrontal cortex in preparing to stop action

Preparing to stop an inappropriate action requires keeping in mind the task goal and using this to influence the action control system. We tested the hypothesis that different subregions of prefrontal cortex show different temporal profiles consistent with dissociable contributions to preparing-to-stop, with dorsolateral prefrontal cortex (DLPFC) representing the task goal and ventrolateral prefrontal cortex (VLPFC) implementing action control. Five human subjects were studied using electrocorticography recorded from subdural grids over right lateral frontal cortex. On each trial, a task cue instructed the subject whether stopping might be needed or not (Maybe Stop [MS] or No Stop [NS]), followed by a go cue, and on some MS trials, a subsequent stop signal. We focused on go trials, comparing MS with NS. In the DLPFC, most subjects had an increase in high gamma activity following the task cue and the go cue. In contrast, in the VLPFC, all subjects had activity after the go cue near the time of the motor response on MS trials, related to behavioral slowing, and significantly later than the DLPFC activity. These different temporal profiles suggest that DLPFC and VLPFC could have dissociable roles, with DLPFC representing task goals and VLPFC implementing action control.

Whole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysis

The brain is the body's largest energy consumer, even in the absence of demanding tasks. Electrophysiologists report on-going neuronal firing during stimulation or task in regions beyond those of primary relationship to the perturbation. Although the biological origin of consciousness remains elusive, it is argued that it emerges from complex, continuous whole-brain neuronal collaboration. Despite converging evidence suggesting the whole brain is continuously working and adapting to anticipate and actuate in response to the environment, over the last 20 y, task-based functional MRI (fMRI) have emphasized a localizationist view of brain function, with fMRI showing only a handful of activated regions in response to task/stimulation. Here, we challenge that view with evidence that under optimal noise conditions, fMRI activations extend well beyond areas of primary relationship to the task; and blood-oxygen level-dependent signal changes correlated with task-timing appear in over 95% of the brain for a simple visual stimulation plus attention control task. Moreover, we show that response shape varies substantially across regions, and that whole-brain parcellations based on those differences produce distributed clusters that are anatomically and functionally meaningful, symmetrical across hemispheres, and reproducible across subjects. These findings highlight the exquisite detail lying in fMRI signals beyond what is normally examined, and emphasize both the pervasiveness of false negatives, and how the sparseness of fMRI maps is not a result of localized brain function, but a consequence of high noise and overly strict predictive response models.

Anatomic and electro-physiologic connectivity of the language system: a combined DTI-CCEP study

Here we present a novel multimodal analysis of network connectivity in the language system. We assessed connectivity of Broca's area using tractography with diffusion tensor imaging (DTI), and with cortico-cortical evoked potentials (CCEPs) to measure the spread of artificial currents applied directly to human cortex. We found that both the amplitude and latency of CCEP currents significantly correlates (r(2)=0.41, p<10(-16)) with the number of DTI pathways connecting the stimulation and recording loci. This strategy of relating electrical information flow with the neural architecture will likely yield new insights into cognitive processes.

Variability of the relationship between electrophysiology and BOLD-fMRI across cortical regions in humans

The relationship between blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signal and the underlying neural electrical activity in humans is a topic of intense interest to systems neuroscience. This relationship has generally been assumed to be invariant regardless of the brain region and the cognitive task being studied. We critically evaluated these assumptions by comparing the BOLD-fMRI response with local field potential (LFP) measurements during visually cued common noun and verb generation in 11 humans in whom 1210 subdural electrodes were implanted. As expected, power in the mid-gamma band (60-120 Hz) correlated positively (r(2) = 0.16, p < 10(-16)) and power in the beta band (13-30 Hz) correlated negatively (r(2) = 0.09, p < 10(-16)) with the BOLD signal change. Beta and mid-gamma band activity independently explain different components of the observed BOLD signal. Importantly, we found that the location (i.e., lobe) of the recording site modulates the relationship between the electrocorticographic (ECoG) signal and the observed fMRI response (p < 10(-16), F(21,1830) = 52.7), while the type of language task does not. Across all brain regions, ECoG activity in the gamma and beta bands explains 22% of the fMRI response, but if the lobar location is considered, 28% of the variance can be explained. Further evaluation of this relationship at the level of individual gyri provides additional evidence of differences in the BOLD-LFP relationship by cortical locus. This spatial variability in the relationship between the fMRI signal and neural activity carries implications for modeling of the hemodynamic response function, an essential step for interregional fMRI comparisons.

Roles for the pre-supplementary motor area and the right inferior frontal gyrus in stopping action: electrophysiological responses and functional and structural connectivity

Both the pre-supplementary motor area (preSMA) and the right inferior frontal gyrus (rIFG) are important for stopping action outright. These regions are also engaged when preparing to stop. We aimed to elucidate the roles of these regions by harnessing the high spatio-temporal resolution of electrocorticography (ECoG), and by using a task that engages both preparing to stop and stopping outright. First, we validated the task using fMRI in 16 healthy control participants to confirm that both the preSMA and the rIFG were active. Next, we studied a rare patient with intracranial grid coverage of both these regions, using macrostimulation, diffusion tractography, cortico-cortical evoked potentials (CCEPs) and task-based ECoG. Macrostimulation of the preSMA induced behavioral motor arrest. Diffusion tractography revealed a structural connection between the preSMA and rIFG. CCEP analysis showed that stimulation of the preSMA evoked strong local field potentials within 30 ms in rIFG. During the task, when preparing to stop, there was increased high gamma amplitude (~70-250 Hz) in both regions, with preSMA preceding rIFG by ~750 ms. For outright stopping there was also a high gamma amplitude increase in both regions, again with preSMA preceding rIFG. Further, at the time of stopping, there was an increase in beta band activity (~16 Hz) in both regions, with significantly stronger inter-regional coherence for successful vs. unsuccessful stop trials. The results complement earlier reports of a structural/functional action control network between the preSMA and rIFG. They go further by revealing between-region timing differences in the high gamma band when preparing to stop and stopping outright. They also reveal strong between-region coherence in the beta band when stopping is successful. Implications for theories of action control are discussed.

An iterative two-threshold analysis for single-subject functional MRI of the human brain

OBJECTIVES

Current thresholding strategies for the analysis of functional MRI (fMRI) datasets may suffer from specific limitations (e.g. with respect to the required smoothness) or lead to reduced performance for a low signal-to-noise ratio (SNR). Although a previously proposed two-threshold (TT) method offers a promising solution to these problems, the use of preset settings limits its performance. This work presents an optimised TT approach that estimates the required parameters in an iterative manner.

METHODS

The iterative TT (iTT) method is compared with the original TT method, as well as other established voxel-based and cluster-based thresholding approaches and spatial mixture modelling (SMM) for both simulated data and fMRI of a hometown walking task at different experimental settings (spatial resolution, filtering and SNR).

RESULTS

In general, the iTT method presents with remarkable sensitivity and good specificity that outperforms all conventional approaches tested except for SMM in a few cases. This also holds true for challenging conditions such as high spatial resolution, the absence of filtering, high noise level, or a low number of task repetitions.

CONCLUSION

Thus, iTT emerges as a good candidate for both scientific fMRI studies at high spatial resolution and more routine applications for clinical purposes.

Neurophysiologic correlates of fMRI in human motor cortex

The neurophysiological underpinnings of functional magnetic resonance imaging (fMRI) are not well understood. To understand the relationship between the fMRI blood oxygen level dependent (BOLD) signal and neurophysiology across large areas of cortex, we compared task related BOLD change during simple finger movement to brain surface electric potentials measured on a similar spatial scale using electrocorticography (ECoG). We found that spectral power increases in high frequencies (65-95 Hz), which have been related to local neuronal activity, colocalized with spatially focal BOLD peaks on primary sensorimotor areas. Independent of high frequencies, decreases in low frequency rhythms (<30 Hz), thought to reflect an aspect of cortical-subcortical interaction, colocalized with weaker BOLD signal increase. A spatial regression analysis showed that there was a direct correlation between the amplitude of the task induced BOLD change on different areas of primary sensorimotor cortex and the amplitude of the high frequency change. Low frequency change explained an additional, different part of the spatial BOLD variance. Together, these spectral power changes explained a significant 36% of the spatial variance in the BOLD signal change (R(2) = 0.36). These results suggest that BOLD signal change is largely induced by two separate neurophysiological mechanisms, one being spatially focal neuronal processing and the other spatially distributed low frequency rhythms.

Mapping cortical representations of the rodent forepaw and hindpaw with BOLD fMRI reveals two spatial boundaries

Electrical stimulation of the rat forepaw and hindpaw was employed to study the spatial distribution of BOLD fMRI. Averaging of multiple fMRI sessions significantly improved the spatial stability of the BOLD signal and enabled quantitative determination of the boundaries of the BOLD fMRI maps. The averaged BOLD fMRI signal was distributed unevenly over the extent of the map and the data at the boundaries could be modeled with major and minor spatial components. Comparison of three-dimensional echo-planar imaging (EPI) fMRI at isotropic 300 μm resolution demonstrated that the border locations of the major spatial component of BOLD signal did not overlap between the forepaw and hindpaw maps. Interestingly, the border positions of the minor BOLD fMRI spatial components extended significantly into neighboring representations. Similar results were found for cerebral blood volume (CBV) weighted fMRI obtained using iron oxide particles, suggesting that the minor spatial components may not be due to vascular mislocalization typically associated with BOLD fMRI. Comparison of the BOLD fMRI maps of the forepaw and hindpaw to histological determination of these representations using cytochrome oxidase (CO) staining demonstrated that the major spatial component of the BOLD fMRI activation maps accurately localizes the borders. Finally, 2-3 weeks following peripheral nerve denervation, cortical reorganization/plasticity at the boundaries of somatosensory limb representations in adult rat brain was studied. Denervation of the hindpaw caused a growth in the major component of forepaw representation into the adjacent border of hindpaw representation, such that fitting to two components no longer led to a better fit as compared to using one major component. The border of the representation after plasticity was the same as the border of its minor component in the absence of any plasticity. It is possible that the minor components represent either vascular effects that extend from the real neuronal representations or the neuronal communication between neighboring regions. Either way the results will be useful for studying mechanisms of plasticity that cause alterations in the boundaries of neuronal representations.

Fixation based event-related fmri analysis: using eye fixations as events in functional magnetic resonance imaging to reveal cortical processing during the free exploration of visual images

Eye movements, comprising predominantly fixations and saccades, are known to reveal information about perception and cognition, and they provide an explicit measure of attention. Nevertheless, fixations have not been considered as events in the analyses of data obtained during functional magnetic resonance imaging (fMRI) experiments. Most likely, this is due to their brevity and statistical properties. Despite these limitations, we used fixations as events to model brain activation in a free viewing experiment with standard fMRI scanning parameters. First, we found that fixations on different objects in different task contexts resulted in distinct cortical patterns of activation. Second, using multivariate pattern analysis, we showed that the BOLD signal revealed meaningful information about the task context of individual fixations and about the object being inspected during these fixations. We conclude that fixation-based event-related (FIBER) fMRI analysis creates new pathways for studying human brain function by enabling researchers to explore natural viewing behavior.

Hemodynamic observation and spike recording explain the neuronal deactivation origin of negative response in rat

Functional brain research has shown that the cerebral response to an external stimulus contains positive and negative signals. The positive signals are well studied, whereas explanations for the negative signals remain controversial. In this study, negative response was investigated using intrinsic optical imaging (OI) and a multi-electrode array (MEA) in rat with a hindlimb stimulus. The negative hemodynamic response (NHR) signals were measured by OI in contralateral and ipsilateral primary somatosensory forelimb, primary and secondary motor, and primary and secondary visual cortex areas. The spatial presentation of NHR signals showed diversity across subjects under an identical experimental paradigm. The NHR signals in different cortical areas had similar time courses but were in the opposite direction of the positive hemodynamic response (PHR) signals, and the amplitude of NHR signals was significantly smaller than that of PHR signals. Electrophysiological recording using an MEA in an NHR cortex area showed that spike activities decreased significantly during external stimulation, suggesting that the neuronal activity reduction has a strong relationship with the NHR signals. Our results highlight the importance of a negative response in a hemodynamics-based interpretation of neuroimaging signals.

Impaired error awareness and anterior cingulate cortex hypoactivity in chronic cannabis users

Drug abuse and other psychiatric conditions (eg, schizophrenia) have been associated with a diminished neural response to errors, particularly in the anterior cingulate cortex (ACC) thought critical to error processing. A diminished capacity for detecting errors has been linked to clinical symptoms including the loss of insight, delusions, and perseverative behavior. A total of 16 active chronic cannabis users and 16 control participants were administered a Go/No-go response inhibition task during event-related fMRI data collection. The task provides measures of inhibitory control and error awareness. Cannabis users' inhibitory control performance was equivalent to that of the control group, but the former showed a significant deficit in awareness of commission errors. Cannabis users showed a diminished capacity for monitoring their behavior that was associated with hypoactivity in the ACC and right insula. In addition, increased levels of hypoactivity in both the ACC and right insula regions were significantly correlated with error-awareness rates in the cannabis group (but not controls). These difficulties are consistent with earlier reports of hypoactivity in the neural systems underlying cognitive control and the monitoring of interoceptive awareness in chronic drug users, and highlight the potential relationship between cognitive dysfunction and behavioral deficits that have the potential to contribute to the maintenance of drug abuse.

3D mapping of somatotopic reorganization with small animal functional MRI

There are few in vivo noninvasive methods to study neuroplasticity in animal brains. Functional MRI (fMRI) has been developed for animal brain mapping, but few fMRI studies have analyzed functional alteration due to plasticity in animal models. One major limitation is that fMRI maps are characterized by statistical parametric mapping making the apparent boundary dependent on the statistical threshold used. Here, we developed a method to characterize the location of center-of-mass in fMRI maps that is shown not to be sensitive to statistical threshold. Utilizing centers-of-mass as anchor points to fit the spatial distribution of the BOLD response enabled quantitative group analysis of altered boundaries of functional somatosensory maps. This approach was used to study cortical reorganization in the rat primary somatosensory cortex (S1) after sensory deprivation to the barrel cortex by follicle ablation (F.A.). FMRI demonstrated an enlarged nose S1 representation in the 3D somatotopic functional maps. This result clearly demonstrates that fMRI enables the spatial mapping of functional changes that can characterize multiple regions of S1 cortex and still be sensitive to changes due to plasticity.

Cholinergic enhancement reduces spatial spread of visual responses in human early visual cortex

Animal studies have shown that acetylcholine decreases excitatory receptive field size and spread of excitation in early visual cortex. These effects are thought to be due to facilitation of thalamocortical synaptic transmission and/or suppression of intracortical connections. We have used functional magnetic resonance imaging (fMRI) to measure the spatial spread of responses to visual stimulation in human early visual cortex. The cholinesterase inhibitor donepezil was administered to normal healthy human subjects to increase synaptic levels of acetylcholine in the brain. Cholinergic enhancement with donepezil decreased the spatial spread of excitatory fMRI responses in visual cortex, consistent with a role of acetylcholine in reducing excitatory receptive field size of cortical neurons. Donepezil also reduced response amplitude in visual cortex, but the cholinergic effects on spatial spread were not a direct result of reduced amplitude. These findings demonstrate that acetylcholine regulates spatial integration in human visual cortex.

Chronic smoking and the BOLD response to a visual activation task and a breath hold task in patients with schizophrenia and healthy controls

Many psychiatric patient groups smoke heavily, but little is known regarding the effects of this habit on functional brain imaging results. The present report assesses the effect of chronic smoking on the blood oxygen level-dependent (BOLD) response to a simple visual activation (VA) task and a breath hold (BH) task in patients with schizophrenia. Eight healthy controls and twelve patients with schizophrenia were studied. Half of each group had never smoked and the other half of each group had smoked for more than 10 pack years. Responses to the VA task were assessed in the visual cortex and responses to the BH task were assessed in gray matter generally. There were four fMRI-dependent measures: (1) median percent signal change; (2) activation volume (in voxels); (3) time-to-peak of the impulse response function (IRF); and (4) time-to-trough of the IRF. All measures were tested as dependent variables in an ANCOVA with diagnosis and smoking status as crossed factors and age as a covariate. Heavy smokers had 22% larger percent signal change for the VA task and 50% larger percent signal change for the BH task. Patients had a 40% larger percent signal change for the breath hold task. Other statistically significant effects of smoking history on activation volume and the timing of the brain responses were noted. If replicated, the results may have important implications for fMRI studies comparing groups with markedly different smoking habits, such as studies comparing patients with schizophrenia, 60-90% of whom smoke, and healthy controls, who smoke with a much lower frequency.

What is Involved and What is Necessary for Complex Linguistic and Nonlinguistic Auditory Processing: Evidence from Functional Magnetic Resonance Imaging and Lesion Data

We used functional magnetic resonance imaging (fMRI) in conjunction with a voxel-based approach to lesion symptom mapping to quantitatively evaluate the similarities and differences between brain areas involved in language and environmental sound comprehension. In general, we found that language and environmental sounds recruit highly overlapping cortical regions, with cross-domain differences being graded rather than absolute. Within language-based regions of interest, we found that in the left hemisphere, language and environmental sound stimuli evoked very similar volumes of activation, whereas in the right hemisphere, there was greater activation for environmental sound stimuli. Finally, lesion symptom maps of aphasic patients based on environmental sounds or linguistic deficits [Saygin, A. P., Dick, F., Wilson, S. W., Dronkers, N. F., & Bates, E. Shared neural resources for processing language and environmental sounds: Evidence from aphasia. Brain, 126, 928–945, 2003] were generally predictive of the extent of blood oxygenation level dependent fMRI activation across these regions for sounds and linguistic stimuli in young healthy subjects.

A comparison of the mean signal change method and the voxel count method to evaluate the sensitivity of individual variability in visuospatial performance

This study compared the mean signal change method and the voxel count method in evaluating the sensitivity of individual variability in visuospatial performance using functional Magnetic Resonance Imaging (fMRI). Sixteen right-handed male college students (mean age 23.2 years) participated in this study as subjects. Functional brain images were scanned with a 3T MRI single-shot EPI method during a visuospatial task. No correlation was found between visuospatial performance and the number of activated voxels in the activated brain areas. Significant positive correlations, however, were found between visuospatial performance and the mean signal changes of activated voxels in the parietal, frontal and other areas. In conclusion, the mean signal change is more sensitive to individual variability in visuospatial performance than the number of activated voxels.

Experimental design and analysis in functional MRI

As the experimental diversity of functional magnetic resonance imaging (fMRI) has grown since introduction of the technique in 1991, the appropriate application of statistical evaluation has become a significant research need. Advances in our understanding of both the dynamics of the underlying neurophysiology and the measurement process make fMRI a fertile ground for novel signal and image processing research. Recent analysis procedures seek to incorporate knowledge of the temporal and spatial characteristics of the blood oxygenation level dependent (BOLD) response measured by fMRI. Efforts that incorporate the nonstationary aspects of the BOLD response will become more important as future applications of fMRI are likely to be in conjunction with additional imaging modalities (e.g., fMRI combined with EEG) to acquire more complete physiologic data and permit greater refinement of our characterization of the central nervous system responses arising due to an applied stimulus.

Complex spatio-temporal dynamics of fMRI BOLD: A study of motor learning

Many studies have investigated the temporal properties of BOLD signal responses to task performance in regions of interest, often noting significant departures from the conventionally modelled response shape, and significant variation between regions. However, these investigations are rarely extended across the whole brain nor incorporated into the routine analysis of fMRI studies. As a result, little is known about the range of response shapes generated in the brain by common paradigms. The present study finds such temporal dynamics can be complex. We made a detailed investigation of BOLD signal responses across the whole brain during a two minute motor-sequence task, and tracked changes due to learning. The multi-component OSORU (Onset, Sustained, Offset, Ramp, Undershoot) linear model, developed by Harms and Melcher (J.Neurophysiology, 2003), was extended to characterise responses. In many regions, signal transients persisted for over thirty seconds, with large signal spikes at onset often followed by a dip in signal below the final sustained level of activation. Training altered certain features of the response shape, suggesting that different features of the response may reflect different aspects of neuro-vascular dynamics. Unmodelled, this may give rise to inconsistent results across paradigms of varying task durations. Few of the observed effects have been thoroughly addressed in physiological models of the BOLD response. The complex, extended dynamics generated by this simple, often employed task, suggests characterisation and modelling of temporal aspects of BOLD responses needs to be carried out routinely, informing experimental design and analysis, and physiological modelling.

Anxiety, respiration, and cerebral blood flow: implications for functional brain imaging

Brain functional imaging methods, such as fMRI, are sensitive to changes in cerebral blood flow (CBF) that are normally associated with changes in regional neural activation. However, other endogenous and exogenous factors can alter CBF independently of brain neural activity, thus complicating the interpretation of functional imaging data. The presence of an anxiety disorder, as well as change in state anxiety, is often accompanied by respiratory alterations that affect arterial CO(2) tensions and produce significant changes in CBF that are independent of task-related neural activation. Therefore, the effects of trait and state anxiety need to be given close consideration in interpreting functional imaging findings. In this paper, we review the dependence of most brain functional imaging methods on localized changes in CBF and the potentially confounding effects of anxiety-related alterations of respiration on interpreting patterns of functional activation. Approaches for addressing these effects are discussed.

How long to scan? The relationship between fMRI temporal signal to noise ratio and necessary scan duration

Recent advances in MRI receiver and coil technologies have significantly improved image signal-to-noise ratios (SNR) and thus temporal SNR (TSNR). These gains in SNR and TSNR have allowed the detection of fMRI signal changes at higher spatial resolution and therefore have increased the potential to localize small brain structures such as cortical layers and columns. The majority of current fMRI processing strategies employ multi-subject averaging and therefore require spatial smoothing and normalization, effectively negating these gains in spatial resolution higher than about 10 mm3. Reliable detection of activation in single subjects at high resolution is becoming a more common desire among fMRI researchers who are interested in comparing individuals rather than populations. Since TSNR decreases with voxel volume, detection of activation at higher resolutions requires longer scan durations. The relationship between TSNR, voxel volume and detectability is highly non-linear. In this study, the relationship between TSNR and the necessary fMRI scan duration required to obtain significant results at varying P values is determined both experimentally and theoretically. The results demonstrate that, with a TSNR of 50, detection of activation of above 2% requires at most 350 scan volumes (when steps are taken to remove the influence of physiological noise from the data). Importantly, these results also demonstrate that, for activation magnitude on the order of 1%, the scan duration required is more sensitive to the TSNR level than at 2%. This study showed that with voxel volumes of approximately 10 mm3 at 3 T, and a corresponding TSNR of approximately 50, the required number of time points that guarantees detection of signal changes of 1% is about 860, but if TSNR increases by only 20%, the time for detection decreases by more than 30%. More than just being an exercise in numbers, these results imply that imaging of columnar resolution (effect size=1% and assuming a TR of 1 s) at 3 T will require either 10 min for a TSNR of 60 or 40 min for a TSNR of 30. The implication is that at these resolutions, TSNR is likely to be critical for determining success or failure of an experiment.

Effects of single-trial averaging on spatial extent of brain activation detected by fMRI are subject and task dependent

Aim

The effects of single-trial averaging on the spatial extent of event-related fMRI activation may vary between subjects and tasks. The purpose of this study was to evaluate this variability using a visual task and a word generation task.

Patients, materials, and methods

Five Chinese right-handed male volunteers participated in the experiment. Experiments were conducted using a 1.5 T clinical MRI scanner with a T2*-weighted single-shot gradient-echo EPI sequence. Each task contained 150 trials that were separated into 5 runs. For each voxel, time courses averaged across different numbers of randomly selected trials, were obtained. They were applied for determining the voxels with significant activations, using a students’ t-test (p<0.001, uncorrected).

Results

Consistent with previous findings, the number of the activated voxels increased monotonically with the number of trials combined. The ascending rate and the maximum number of the activated voxels were different, however, between tasks and among subjects.

Conclusions

The effects of single-trial averaging were found to vary significantly between tasks and subjects. Therefore, we strongly advise to carefully consider such variability when using the spatial extent of activation as a measure in a group or a task comparison.

MDMA use is associated with increased spatial BOLD fMRI visual cortex activation in human MDMA users

Previous animal studies have demonstrated that 3,4-methylenedioxymethamphetamine (MDMA) exposure causes serotonin axotomy that is greatest in occipital cortex (including primary visual cortex) where serotonergic axons innervate neurons and blood vessels. Human MDMA users have altered serotonergic function and reduced gray matter density in occipital cortex. The fMRI BOLD method is potentially sensitive to both the neuronal and vascular consequences of MDMA-induced serotonin toxicity. To test the hypothesis that MDMA users have altered visual system function, we used the fMRI BOLD technique to assay visual cortical activation after photic stimulation in a group of adult MDMA users. Because MDMA users worldwide are polydrug users and therefore difficult to match to comparison groups in terms of polydrug exposure, we conducted a primary within-group analysis examining the correlation between lifetime episodes of MDMA exposure and measures of visual cortical activation. The within-group correlational analysis in the MDMA user group revealed that the degree of prior MDMA exposure was significantly positively correlated with the number of activated pixels for photic stimulation (r=0.582, p=0.007). A secondary between-group comparison of MDMA users with non-MDMA users found overall greater levels of polydrug exposure in the MDMA user cohort but no significant differences in visual cortical activation measures between the two groups. Additional research is needed to clarify the origin and significance of the current findings.

Age-related changes in brain activation during a delayed item recognition task

To test competing models of age-related changes in brain functioning (capacity limitation, neural efficiency, compensatory reorganization, and dedifferentiation), young (n=40; mean age=25.1 years) and elderly (n=18; mean age=74.4 years) subjects performed a delayed item recognition task for visually presented letters with three set sizes (1, 3, or 6 letters) while being scanned with BOLD fMRI. Spatial patterns of brain activity corresponding to either the slope or y-intercept of fMRI signal with respect to set size during memory set encoding, retention delay, or probe stimulus presentation trial phases were compared between elder and young populations. Age effects on fMRI slope during encoding and on fMRI y-intercept during retention delay were consistent with neural inefficiency; age effects on fMRI slope during retention delay were consistent with dedifferentiation. None of the other fMRI signal components showed any detectable age effects. These results suggest that, even within the same task, the nature of brain activation changes with aging can vary based on cognitive process engaged.

Deriving the optimal number of events for an event-related fMRI study based on the spatial extent of activation

Event-related fMRI is a powerful tool for localising psychological functions to specific brain areas. However, the number of events required to produce stable activation maps is a poorly investigated and understood problem. Huettel and McCarthy [Huettel, S.A., McCarthy, G., 2001. The effects of single-trial averaging upon the spatial extent of fMRI activation. NeuroReport 12, 2411-2416] have shown that the spatial extent of activation increases monotonically with the number of events in an analysis. In the present paper, this result is replicated and shown to be a consequence of the cross-correlation technique used to determine active voxels and does not hold, for example, for a GLM analysis. Another analysis technique, that does not depend on goodness-of-fit to the data, is also proposed. This technique calculates an impulse response function (IRF) for each voxel, finds the best fitting haemodynamic shape to the IRF and returns an area-under-the-curve (%AUC) activation measure. Using spatial extent as a measure, asymptotic behaviour is evident after as few as 25 events for the %AUC analysis technique in a finger-tapping task with non-overlapping haemodynamic responses and for both the GLM and %AUC techniques in a similar task that allows responses to overlap. The experimental validity of the %AUC technique to identify active brain regions while minimising false positive levels is demonstrated in a group study with 25 participants.

Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex

The spatial extent of the changes in oxy-hemoglobin (HbO), deoxy-hemoglobin (HbR), total hemoglobin concentration (HbT), cerebral blood flow (CBF), and the cerebral metabolic rate of oxygen (CMRO(2)) in response to forepaw and whisker stimulation were compared in the rat somatosensory cortex using a combination of multi-wavelength reflectance imaging and laser speckle contrast imaging of cerebral blood flow. The spatial extents of the response of each hemodynamic parameter and CMRO(2) were found to be comparable at the time of peak response, and at early times following stimulation onset, the spatial extent of the change in HbR was smaller than that of HbO, HbT, CBF, and CMRO(2). In addition, a slight spatial dependence was found in the power law coefficient relating changes in CBF and HbT. Although the CMRO(2) response is a metabolic measure and thus expected to have a more localized response than the hemodynamic parameters, the results presented here suggest that this may not be the case in general, possibly due to the increased sensitivity of optical imaging techniques to superficial cortical layers where the lateral extent of the metabolic and neuronal activation is larger compared to that in layer IV. In addition, we found that the measured spatial extent of the CMRO(2) changes was insensitive to assumptions made in the calculation of the CMRO(2) changes such as baseline hemoglobin concentrations, vascular weighting constants, and wavelength dependence of tissue scattering. Multi-parameter full field imaging of the functional response provides a more complete picture of the hemodynamic response to functional activation including the spatial and temporal estimation of CMRO(2) changes.

Enduring representational plasticity after somatosensory stimulation

Somatosensory stimulation (SS), leading to increases in motor cortical excitability, influences motor performance in patients with brain lesions like stroke. The mechanisms by which SS modulates motor function are incompletely understood. Here, we used functional magnetic resonance imaging (fMRI, blood-oxygenation-level-dependent (BOLD), and perfusion imagings simultaneously acquired in a 3 T magnet) to assess the effects of SS on thumb-movement-related activation in three regions of interest (ROI) in the motor network: primary motor cortex (M1), primary somatosensory cortex (S1), and dorsal premotor cortex (PMd) in healthy volunteers. Scans were obtained in different sessions before and after 2-h electrical stimulation applied to the median nerve at the wrist (MNS), to the skin overlying the shoulder deltoid muscle (DMS), and in the absence of stimulation (NOSTIM) in a counterbalanced design. We found that baseline perfusion intensity was comparable within and across sessions. MNS but not DMS nor NOSTIM led to an increase in signal intensity and number of voxels activated by performance of median nerve-innervated thumb movements in M1, S1, and PMd for up to 60 min. Task-related fMRI activation changes were most prominent in M1 followed by S1 and to a lesser extent in PMd. MNS elicited a displacement of the center of gravity for the thumb movement representation towards the other finger representations within S1. These results indicate that MNS leads to an expansion of the thumb representation towards other finger representations within S1, a form of plasticity that may underlie the influence of SS on motor cortical function, possibly supporting beneficial effects on motor control.

Statistical criteria in FMRI studies of multisensory integration

Inferences drawn from functional magnetic resonance imaging (fMRI) studies are dependent on the statistical criteria used to define different brain regions as "active" or "inactive" under the experimental manipulation. In fMRI studies of multisensory integration, additional criteria are used to classify a subset of the active brain regions as "multisensory." Because there is no general agreement in the literature on the optimal criteria for performing this classification, we investigated the effects of seven different multisensory statistical criteria on a single test dataset collected as human subjects performed auditory, visual, and auditory- visual object recognition. Activation maps created using the different criteria differed dramatically. The classification of the superior temporal sulcus (STS) was used as a performance measure, because a large body of converging evidence demonstrates that the STS is important for auditory-visual integration. A commonly proposed criterion, "supra-additivity" or "super-additivity", which requires the multisensory response to be larger than the summed unisensory responses, did not classify STS as multisensory. Alternative criteria, such as requiring the multisensory response to be larger than the maximum or the mean of the unisensory responses, successfully classified STS as multisensory. This practical demonstration strengthens theoretical arguments that the super-additivity is not an appropriate criterion for all studies of multisensory integration. Moreover, the importance of examining evoked fMRI responses, whole brain activation maps, maps from multiple individual subjects, and mixed-effect group maps are discussed in the context of selecting statistical criteria.

Neural mechanisms involved in error processing: A comparison of errors made with and without awareness

The ability to detect an error in one's own performance and then to improve ongoing performance based on this error processing is critical for effective behaviour. In our event-related fMRI experiment, we show that explicit awareness of a response inhibition commission error and subsequent post-error behaviour were associated with bilateral prefrontal and parietal brain activation. Activity in the anterior cingulate region, typically associated with error detection, was equivalent for both errors subjects were aware of and those they were not aware of making. While anterior cingulate activation has repeatedly been associated with error-related processing, these results suggest that, in isolation, it is not sufficient for conscious awareness of errors or post-error adaptation of response strategies. Instead, it appears, irrespective of awareness, to detect information about stimuli/responses that requires interpretation in other brain regions for strategic implementation of post-error adjustments of behaviour.

Effects of EPI readout bandwidth on measured activation map and BOLD response in fMRI experiments

The purpose of this study was to evaluate the effects of echo planar imaging (EPI) readout bandwidth and its interaction with data processing procedures on the measured blood oxygenation level dependent (BOLD) response and activation in fMRI experiments. Seventeen healthy subjects were scanned during a brief visual stimulation paradigm with two EPI pulse sequences having 'high' (1953 Hz/pixel) and 'low' (780 Hz/pixel) readout bandwidth. Functional data were analyzed with a general linear model including temporal filtering and a basic correlation model following (1) no preprocessing, (2) realignment, or (3) realignment and spatial smoothing. A range of statistical thresholds were used to generate activation maps. Despite slightly higher BOLD signal detected with the high bandwidth sequence from matched ROIs in the primary visual cortex, results showed that the low bandwidth pulse sequence was more sensitive under most conditions evaluated. That is, the low bandwidth sequence detected greater numbers of activated voxels with lower cluster average BOLD signal (e.g., low bandwidth detected 1.4 times more voxels, with average BOLD signal 30% lower compared to high bandwidth for P = 0.05 (corrected) with the 3rd preprocessing procedure using the general linear model). However, there was significant interaction between bandwidth and data preprocessing procedures. Of particular interest, the sensitivity advantage of the low bandwidth pulse sequence decreased for the smoothed data as the activation threshold became less conservative. For the frequently used threshold of P = 0.001 (uncorrected) and cluster size of at least 5 voxels, the bandwidth advantage became insignificant. These findings demonstrate that the effects of bandwidth should be considered carefully in the design, analysis, and interpretation of BOLD fMRI studies.

Neural correlates of high and craving during cocaine self-administration using BOLD fMRI

Modern theories of drug dependence hold the hedonic effects of drug-taking central to understanding the motivation for compulsive drug use. Previous neuroimaging studies have begun to identify brain regions associated with acute drug effects after passive delivery. In this study, a more naturalistic model of cocaine self-administration (SA) was employed in order to identify those sites associated with drug-induced high and craving as measures of reward and motivation. Non-treatment seeking cocaine-dependent subjects chose both when and how often i.v. cocaine administration occurred within a medically supervised SA procedure. Both functional magnetic resonance imaging (fMRI) data and real-time behavioral ratings were acquired during the 1-h SA period. Drug-induced HIGH was found to correlate negatively with activity in limbic, paralimbic, and mesocortical regions including the nucleus accumbens (NAc), inferior frontal/orbitofrontal gyrus (OFC), and anterior cingulate (AC), while CRAVING correlated positively with activity in these regions. This study provides the first evidence in humans that changes in subjective state surrounding cocaine self-administration reflect neural activity of the endogenous reward system.

Motor control in basal ganglia circuits using fMRI and brain atlas approaches

In this study, we examined how the motor, premotor and associative basal ganglia territories process movement parameters such as the complexity and the frequency of movement. Twelve right-handed volunteers were studied using EPI BOLD contrast (3 T) while performing audio-paced finger tapping tasks designed to differentiate basal ganglia territories. Tasks varied movement complexity (repetitive index tapping, simple sequence of finger movements and complex sequence of 10 moves) and frequency (from 0.5 to 3 Hz). Activation maps were coregistered onto a 3-D brain atlas derived from post-mortem brains. Three main patterns of activation were observed. In the posterior putamen and the sensorimotor cortex, signal increased with movement frequency but not with movement complexity. In premotor areas, the anterior putamen and the ventral posterolateral thalamus, signal increased regularly with increasing movement frequency and complexity. In rostral frontal areas, the caudate nucleus, the subthalamic nucleus and the ventral anterior/ventrolateral thalamus, signal increased mainly during the complex task and the high frequency task (3 Hz). These data show the different roles of motor, premotor and associative basal ganglia circuits in the processing of motor-related operations and suggest that activation can be precisely located within the entire circuitry of the basal ganglia.

Reading vascular changes in brain imaging: is dendritic calcium the key?

A key goal in functional neuroimaging is to use signals that are related to local changes in metabolism and blood flow to track the neuronal correlates of mental activity. Recent findings indicate that the dendritic processing of excitatory synaptic inputs correlates more closely than the generation of spikes with brain imaging signals. The correlation is often nonlinear and context-sensitive, and cannot be generalized for every condition or brain region. The vascular signals are mainly produced by increases in intracellular calcium in neurons and possibly astrocytes, which activate important enzymes that produce vasodilators to generate increments in flow and the positive blood oxygen level dependent signal. Our understanding of the cellular mechanisms of functional imaging signals places constraints on the interpretation of the data.

Comparing extent of activation: a robust permutation approach

The number of contiguous voxels activated in a brain image can differ between groups or conditions even though the amplitude of activation does not markedly differ. Existing techniques test for differences in amplitude given that extent (number of contiguous voxels) exceeds some threshold. We present a technique that tests for differences in extent of activation given that amplitude of activation exceeds some threshold. The technique was motivated by apparent differences in extent of regional cerebral blood flow (rCBF) between hypertensive and normotensive participants performing cognitive tasks. These data are used to illustrate our test for extent of activation. We threshold the estimated parameter map for each subject, count the number of voxels exceeding the threshold over a defined region enclosing activated cortical area, and test the hypothesis of difference in the number of activated voxels between the two groups. Due to the large number of zeros resulting from the thresholding and the occurrence of extreme observations, we use a Robust permutation test [Lambert, D., 1985. Robust two-sample permutation tests. Ann. Stat., 13, 606-625], which is based on the sum of censored log-likelihood ratios. This statistic has desirable properties relative to the usual permutation test in contaminated distributions, i.e., idealized histogram with outliers, and provides an appropriate and robust test of extent of activation between conditions or groups.