Task-free presurgical mapping using functional magnetic resonance imaging intrinsic activity

Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI

Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility.

Presurgical Assessment of the Sensorimotor Cortex Using Resting-State fMRI

BACKGROUND AND PURPOSE

The functional characterization of the motor cortex is an important issue in the presurgical evaluation of brain lesions. fMRI noninvasively identifies motor areas while patients are asked to move different body parts. This task-based approach has some drawbacks in clinical settings: long scanning times and exclusion of patients with severe functional or neurologic disabilities and children. Resting-state fMRI can avoid these difficulties because patients do not perform any goal-directed tasks.

MATERIALS AND METHODS

Nineteen patients with diverse brain pathologies were prospectively evaluated by using task-based and resting-state fMRI to localize sensorimotor function. Independent component analyses were performed to generate spatial independent components reflecting functional brain networks or noise. Three radiologists identified the motor components and 3 portions of the motor cortex corresponding to the hand, foot, and face representations. Selected motor independent components were compared with task-based fMRI activation maps resulting from movements of the corresponding body parts.

RESULTS

The motor cortex was successfully and consistently identified by using resting-state fMRI by the 3 radiologists for all patients. When they subdivided the motor cortex into 3 segments, the sensitivities of resting-state and task-based fMRI were comparable. Moreover, we report a good spatial correspondence with the task-based fMRI activity estimates.

CONCLUSIONS

Resting-state fMRI can reliably image sensorimotor function in a clinical preoperative routine. It is a promising opportunity for presurgical localization of sensorimotor function and has the potential to benefit a large number of patients affected by a wide range of pathologies.

3D interactive tractography-informed resting-state fMRI connectivity

In the past decade, the fusion between diffusion magnetic resonance imaging (dMRI) and functional magnetic resonance imaging (fMRI) has opened the way for exploring structure-function relationships in vivo. As it stands, the common approach usually consists of analysing fMRI and dMRI datasets separately or using one to inform the other, such as using fMRI activation sites to reconstruct dMRI streamlines that interconnect them. Moreover, given the large inter-individual variability of the healthy human brain, it is possible that valuable information is lost when a fixed set of dMRI/fMRI analysis parameters such as threshold values are assumed constant across subjects. By allowing one to modify such parameters while viewing the results in real-time, one can begin to fully explore the sensitivity of structure-function relations and how they differ across brain areas and individuals. This is especially important when interpreting how structure-function relationships are altered in patients with neurological disorders, such as the presence of a tumor. In this study, we present and validate a novel approach to achieve this: First, we present an interactive method to generate and visualize tractography-driven resting-state functional connectivity, which reduces the bias introduced by seed size, shape and position. Next, we demonstrate that structural and functional reconstruction parameters explain a significant portion of intra- and inter-subject variability. Finally, we demonstrate how our proposed approach can be used in a neurosurgical planning context. We believe this approach will promote the exploration of structure-function relationships in a subject-specific aspect and will open new opportunities for connectomics.

Functional Neuroimaging: Fundamental Principles and Clinical Applications

Functional imaging modalities, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), are rapidly changing the scope and practice of neuroradiology. While these modalities have long been used in research, they are increasingly being used in clinical practice to enable reliable identification of eloquent cortex and white matter tracts in order to guide treatment planning and to serve as a diagnostic supplement when traditional imaging fails. An understanding of the scientific principles underlying fMRI and DTI is necessary in current radiological practice. fMRI relies on a compensatory hemodynamic response seen in cortical activation and the intrinsic discrepant magnetic properties of deoxy- and oxyhemoglobin. Neuronal activity can be indirectly visualized based on a hemodynamic response, termed neurovascular coupling. fMRI demonstrates utility in identifying areas of cortical activation (i.e., task-based activation) and in discerning areas of neuronal connectivity when used during the resting state, termed resting state fMRI. While fMRI is limited to visualization of gray matter, DTI permits visualization of white matter tracts through diffusion restriction along different axes. We will discuss the physical, statistical and physiological principles underlying these functional imaging modalities and explore new promising clinical applications.

Neural mechanisms of acupuncture as revealed by fMRI studies

As an ancient therapeutic method, acupuncture has been used to treat many diseases as an adjunctive therapy. However, its clinical efficacy remains controversial and the neural mechanisms have not been well understood. Accumulating studies have revealed that fMRI has made it possible to study brain responses to acupuncture. This review aims to provide scientific evidence to support the notion and discuss how these findings contribute to the neural mechanisms of acupuncture.

Localizing hand motor area using resting-state fMRI: validated with direct cortical stimulation

BACKGROUND

Resting-state functional magnetic resonance imaging (R-fMRI) is a promising tool in clinical application, especially in presurgical mapping for neurosurgery. This study aimed to investigate the sensitivity and specificity of R-fMRI in the localization of hand motor area in patients with brain tumors validated by direct cortical stimulation (DCS). We also compared this technique to task-based blood oxygenation level-dependent (BOLD) fMRI (T-fMRI).

METHODS

R-fMRI and T-fMRI were acquired from 17 patients with brain tumors. The cortex sites of the hand motor area were recorded by DCS. Site-by-site comparisons between R-fMRI/T-fMRI and DCS were performed to calculate R-fMRI and T-fMRI sensitivity and specificity using DCS as a "gold standard". R-fMRI and T-fMRI performances were compared statistically

RESULTS

A total of 609 cortex sites were tested with DCS and compared with R-fMRI findings in 17 patients. For hand motor area localization, R-fMRI sensitivity and specificity were 90.91 and 89.41 %, respectively. Given that two subjects could not comply with T-fMRI, 520 DCS sites were compared with T-fMRI findings in 15 patients. The sensitivity and specificity of T-fMRI were 78.57 and 84.76 %, respectively. In the 15 patients who successfully underwent both R-fMRI and T-fMRI, there was no statistical difference in sensitivity or specificity between the two methods (p = 0.3198 and p = 0.1431, respectively)

CONCLUSIONS

R-fMRI sensitivity and specificity are high for localizing hand motor area and even equivalent or slightly higher compared with T-fMRI. Given its convenience for patients, R-fMRI is a promising substitute for T-fMRI for presurgical mapping.

Resting-state functional magnetic resonance imaging: review of neurosurgical applications

Recent research in brain imaging has highlighted the role of different neural networks in the resting state (ie, no task) in which the brain displays spontaneous low-frequency neuronal oscillations. These can be indirectly measured with resting-state functional magnetic resonance imaging, and functional connectivity can be inferred as the spatiotemporal correlations of this signal. This technique has proliferated in recent years and has allowed the noninvasive investigation of large-scale, distributed functional networks. In this review, we give a brief overview of resting-state networks and examine the use of resting-state functional magnetic resonance imaging in neurosurgical contexts, specifically with respect to neurooncology, epilepsy surgery, and deep brain stimulation. We discuss the advantages and disadvantages compared with task-based functional magnetic resonance imaging, the limitations of resting-state functional magnetic resonance imaging, and the emerging directions of this relatively new technology.

Visual mapping using blood oxygen level dependent functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is used clinically to map the visual cortex before brain surgery or other invasive treatments to achieve an optimal balance between therapeutic effect and the avoidance of postoperative vision deficits. Clinically optimized stimuli, behavioral task, analysis, and displays permit identification of cortical subregions supporting high-acuity central vision that is critical for reading and other essential visual functions. Emerging techniques such as resting-state fMRI may facilitate the use of fMRI-based vision mapping in a broader range of patients.

Resting-state blood oxygen level-dependent functional magnetic resonance imaging for presurgical planning

Resting-state functional MR imaging (rsfMR imaging) measures spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal and can be used to elucidate the brain's functional organization. It is used to simultaneously assess multiple distributed resting-state networks. Unlike task-based functional MR imaging, rsfMR imaging does not require task performance. This article presents a brief introduction of rsfMR imaging processing methods followed by a detailed discussion on the use of rsfMR imaging in presurgical planning. Example cases are provided to highlight the strengths and limitations of the technique.

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI.

A novel data-driven approach to preoperative mapping of functional cortex using resting-state functional magnetic resonance imaging

Supplemental Digital Content is Available in the Text.

BACKGROUND:

Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping.

OBJECTIVE:

To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks.

METHODS:

This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy.

RESULTS:

The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively.

CONCLUSION:

A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions.

ABBREVIATIONS:

AUC, area under the curve

BA, Brodmann area

BOLD, blood oxygen level dependent

ECS, electrocortical stimulation

fMRI, functional magnetic resonance imaging

ICA, independent component analysis

MLP, multilayer perceptron

MP-RAGE, magnetization-prepared rapid gradient echo

ROC, receiver-operating characteristic

rs-fMRI, resting-state functional magnetic resonance imaging

RSN, resting-state network

Preoperative mapping of the sensorimotor cortex: comparative assessment of task-based and resting-state FMRI

Resting state fMRI (rs-fMRI) has recently been considered as a possible complement or alternative to task-based fMRI (tb-fMRI) for presurgical mapping. However, evidence of its usefulness remains scant, because existing studies have investigated relatively small samples and focused primarily on qualitative evaluation. The aim of this study is to investigate the clinical usefulness of rs-fMRI in the context of presurgical mapping of motor functions, and in particular to determine the degree of correspondence with tb-fMRI which, while not a gold-standard, is commonly used in preoperative setting. A group of 13 patients with lesions close to the sensorimotor cortex underwent rs-fMRI and tb-fMRI to localize the hand, foot and mouth motor areas. We assessed quantitatively the degree of correspondence between multiple rs-fMRI analyses (independent-component and seed-based analyses) and tb-fMRI, with reference to sensitivity and specificity of rs-fMRI with respect to tb-fMRI, and centre-of-mass distances. Agreement with electro-cortical stimulation (ECS) was also investigated, and a traditional map thresholding approach based on agreement between two experienced operators was compared to an automatic threshold determination method. Rs-fMRI can localize the sensorimotor cortex successfully, providing anatomical specificity for hand, foot and mouth motor subregions, in particular with seed-based analyses. Agreement with tb-fMRI was only partial and rs-fMRI tended to provide larger patterns of correlated activity. With respect to the ECS data available, rs-fMRI and tb-fMRI performed comparably, even though the shortest distance to stimulation points was observed for the latter. Notably, the results of both were on the whole robust to thresholding procedure. Localization performed by rs-fMRI is not equivalent to tb-fMRI, hence rs-fMRI cannot be considered as an outright replacement for tb-fMRI. Nevertheless, since there is significant agreement between the two techniques, rs-fMRI can be considered with caution as a potential alternative to tb-fMRI when patients are unable to perform the task.

High-speed real-time resting-state FMRI using multi-slab echo-volumar imaging

We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting-state networks (RSNs) compared to echo-planar imaging (Posse et al., 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arterio-venous malformations, and detection of abnormal resting-state connectivity in epilepsy. In patients with motor impairment, resting-state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arterio-venous malformations and a trend toward reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting-state connectivity and cerebro-vascular pulsatility for clinical and neuroscience research applications.

Fast presurgical functional mapping using task-related intracranial high gamma activity

OBJECT

Electrocorticography (ECoG) is a powerful tool for presurgical functional mapping. Power increase in the high gamma band has been observed from ECoG electrodes on the surface of the sensory motor cortex during the execution of body movements. In this study the authors aim to validate the clinical usage of high gamma activity in presurgical mapping by comparing ECoG mapping with traditional direct electrical cortical stimulation (ECS) and functional MRI (fMRI) mapping.

METHODS

Seventeen patients with epilepsy participated in an ECoG motor mapping experiment. The patients executed a 5-minute hand/tongue movement task while the ECoG signal was recorded. All 17 patients also underwent extraoperative ECS mapping to localize the motor cortex. Eight patients also participated in a presurgical fMRI study. The high gamma activity on ECoG was modeled using the general linear model (GLM), and the regions showing significant gamma power increase during the task condition compared with the rest condition were localized. The maps derived from GLM-based ECoG mapping, ECS, and fMRI were then compared.

RESULTS

High gamma activity in the motor cortex can be reliably modulated by motor tasks. Localization of the motor regions achieved with GLM-based ECoG mapping was consistent with the localization determined by ECS. The maps also appeared to be highly localized compared with the fMRI activations. Using the ECS findings as the reference, GLM-based ECoG mapping showed a significantly higher sensitivity than fMRI (66.7% for ECoG, 52.6% for fMRI, p<0.05), while the specificity was high for both techniques (>97%). If the current-spreading effect in ECS is accounted for, ECoG mapping may produce maps almost identical to those produced by ECS mapping (100% sensitivity and 99.5% specificity).

CONCLUSIONS

General linear model-based ECoG mapping showed a superior performance compared to traditional ECS and fMRI mapping in terms of efficiency and accuracy. Using this method, motor functions can be reliably mapped in less than 5 minutes.

Individual variability in functional connectivity architecture of the human brain

The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging.

Defining language networks from resting-state fMRI for surgical planning--a feasibility study

Presurgical language mapping for patients with lesions close to language areas is critical to neurosurgical decision-making for preservation of language function. As a clinical noninvasive imaging technique, functional MRI (fMRI) is used to identify language areas by measuring blood-oxygen-level dependent (BOLD) signal change while patients perform carefully timed language vs. control tasks. This task-based fMRI critically depends on task performance, excluding many patients who have difficulty performing language tasks due to neurologic deficits. On the basis of recent discovery of resting-state fMRI (rs-fMRI), we propose a "task-free" paradigm acquiring fMRI data when patients simply are at rest. This paradigm is less demanding for patients to perform and easier for technologists to administer. We investigated the feasibility of this approach in right-handed healthy control subjects. First, group independent component analysis (ICA) was applied on the training group (14 subjects) to identify group level language components based on expert rating results. Then, four empirically and structurally defined language network templates were assessed for their ability to identify language components from individuals' ICA output of the testing group (18 subjects) based on spatial similarity analysis. Results suggest that it is feasible to extract language activations from rs-fMRI at the individual subject level, and two empirically defined templates (that focuses on frontal language areas and that incorporates both frontal and temporal language areas) demonstrated the best performance. We propose a semi-automated language component identification procedure and discuss the practical concerns and suggestions for this approach to be used in clinical fMRI language mapping.

"Awake" intraoperative functional MRI (ai-fMRI) for mapping the eloquent cortex: Is it possible in awake craniotomy?

As a promising noninvasive imaging technique, functional MRI (fMRI) has been extensively adopted as a functional localization procedure for surgical planning. However, the information provided by preoperative fMRI (pre-fMRI) is hampered by the brain deformation that is secondary to surgical procedures. Therefore, intraoperative fMRI (i-fMRI) becomes a potential alternative that can compensate for brain shifts by updating the functional localization information during craniotomy. However, previous i-fMRI studies required that patients be under general anesthesia, preventing the wider application of such a technique as the patients cannot perform tasks unless they are awake. In this study, we propose a new technique that combines awake surgery and i-fMRI, named “awake” i-fMRI (ai-fMRI). We introduced ai-fMRI to the real-time localization of sensorimotor areas during awake craniotomy in seven patients. The results showed that ai-fMRI could successfully detect activations in the bilateral primary sensorimotor areas and supplementary motor areas for all patients, indicating the feasibility of this technique in eloquent area localization. The reliability of ai-fMRI was further validated using intraoperative stimulation mapping (ISM) in two of the seven patients. Comparisons between the pre-fMRI-derived localization result and the ai-fMRI derived result showed that the former was subject to a heavy brain shift and led to incorrect localization, while the latter solved that problem. Additionally, the approaches for the acquisition and processing of the ai-fMRI data were fully illustrated and described. Some practical issues on employing ai-fMRI in awake craniotomy were systemically discussed, and guidelines were provided.

Functional and structural MR imaging in neuropsychiatric disorders, Part 1: imaging techniques and their application in mild cognitive impairment and Alzheimer disease

During the past decade, the application of advanced MR imaging techniques in neuropsychiatric disorders has seen a rapid increase. Disease-specific alterations in brain function can be assessed by fMRI. Structural GM and WM properties are increasingly investigated by DTI and voxel-based approaches like VBM. These methods provide neurobiologic correlates for brain architecture and function, evaluation tools for therapeutic approaches, and potential early markers for diagnosis. The aim of this review was to provide insight into the principles of functional and structural imaging and to delineate major findings in MCI, AD (Part 1), autism, and schizophrenia (Part 2), which are common psychiatric disorders covering different stages of the life span. Part 2 will conclude by summarizing current applications, limitations, and future prospects in the field of MR imaging-based neuroimaging.

Resting-state fMRI: a review of methods and clinical applications

SUMMARY

Resting-state fMRI measures spontaneous low-frequency fluctuations in the BOLD signal to investigate the functional architecture of the brain. Application of this technique has allowed the identification of various RSNs, or spatially distinct areas of the brain that demonstrate synchronous BOLD fluctuations at rest. Various methods exist for analyzing resting-state data, including seed-based approaches, independent component analysis, graph methods, clustering algorithms, neural networks, and pattern classifiers. Clinical applications of resting-state fMRI are at an early stage of development. However, its use in presurgical planning for patients with brain tumor and epilepsy demonstrates early promise, and the technique may have a future role in providing diagnostic and prognostic information for neurologic and psychiatric diseases.

A software tool for interactive exploration of intrinsic functional connectivity opens new perspectives for brain surgery

BACKGROUND

Functional connectivity analysis of resting-state functional magnetic resonance imaging data (fcrs-fMRI) has been shown to be a robust non-invasive method for localization of functional networks (without using specific tasks) and to be promising for presurgical planning. However, in order to transfer the approach to everyday clinical practice, fcrs-fMRI needs to be further validated and made easily accessible to neurosurgeons. This paper addresses the latter by presenting a software tool designed for neurosurgeons for analyzing and visualizing fcrs-fMRI data.

METHODS

A prototypical interactive visualization tool was developed to enable neurosurgeons to explore functional connectivity data and evaluate its usability. The implementation builds upon LIPSIA, an established software package for the assessment of functional neuroimaging data, and integrates the selection of a region-of-interest with the computation and visualization of functionally connected areas. The tool was used to explore data from a healthy participant and eight brain lesion patients. The usability of the software was evaluated with four neurosurgeons previously unacquainted with the methodology, who were asked to identify prominent, large-scale cortical networks.

FINDINGS

With this novel tool, previously published findings, such as tumor displacement of the sensorimotor cortex and other disturbances of functional networks, were reproduced. The neurosurgeons were able to consistently obtain results similar to the results of an expert, with the exception of the language network. Immediate feedback helped to pinpoint functional networks quickly and intuitively, with even inexperienced users requiring less than 3 min per network.

CONCLUSIONS

Although fcrs-fMRI is a nascent method still undergoing evaluation with respect to established standards, the interactive software is nonetheless a promising tool for non-invasive exploration of individual functional connectivity networks in neurosurgical practice, both for well-known networks and for those less typically addressed.

Special surgical considerations for functional brain mapping

The development of functional mapping techniques gives neurosurgeons many options for preoperative planning. Integrating functional and anatomic data can inform patient selection and surgical planning and makes functional mapping more accessible than when only invasive studies were available. However, the applications of functional mapping to neurosurgical patients are still evolving. Functional imaging remains complex and requires an understanding of the underlying physiologic and imaging characteristics. Neurosurgeons must be accustomed to interpreting highly processed data. Successful implementation of functional image-guided procedures requires efficient interactions between neurosurgeon, neurologist, radiologist, neuropsychologist, and others, but promises to enhance the care of patients.

Can resting-state functional MRI serve as a complement to task-based mapping of sensorimotor function? A test-retest reliability study in healthy volunteers

PURPOSE

To investigate if resting-state functional MRI (fMRI) reliably can serve as a complement to task-based fMRI for presurgical mapping of the sensorimotor cortex.

MATERIALS AND METHODS

Functional data were obtained in 10 healthy volunteers using a 3 Tesla MRI system. Each subject performed five bilateral finger tapping experiments interleaved with five resting-state experiments. Following preprocessing, data from eight volunteers were further analyzed with the general linear model (finger tapping data) and independent component analysis (rest data). Test-retest reliability estimates (hit rate and false alarm rate) for resting-state fMRI activation of the sensorimotor network were compared with the reliability estimates for task-evoked activation of the sensorimotor cortex. The reliability estimates constituted a receiver operating characteristics curve from which the area under the curve (AUC) was calculated. Statistical testing was performed to compare the two groups with respect to reliability.

RESULTS

The AUC was generally higher for the task experiments, although median AUC was not significantly different on a group level. Also, the two groups showed comparable levels of within-group variance.

CONCLUSION

Test-retest reliability was comparable between resting-state measurements and task-based fMRI, suggesting that presurgical mapping of functional networks can be a supplement to task-based fMRI in cases where patient status excludes task-based fMRI.

Resting-state brain networks: literature review and clinical applications

This review focuses on resting-state functional connectivity, a functional MRI technique which allows the study of spontaneous brain activity generated under resting conditions. This approach is useful to explore the brain's functional organization and to examine if it is altered in neurological or psychiatric diseases. Resting-state functional connectivity has revealed a number of networks which are consistently found in healthy subjects and represent specific patterns of synchronous activity. In this review, we examine the behavioral, physiological and neurological evidences relevant to this coherent brain activity and, in particular, to each network. The investigation of functional connectivity appears promising from a clinical perspective, considering the amount of evidence regarding the importance of spontaneous activity and that resting-state paradigms are inherently simple to implement. We also discuss some examples of existing clinical applications, such as in Alzheimer's disease, and emerging possibilities such as in pre-operative mapping and disorders of consciousness.

Functional connectivity MRI in infants: exploration of the functional organization of the developing brain

Advanced neuroimaging techniques have been increasingly applied to the study of preterm and term infants in an effort to further define the functional cerebral architecture of the developing brain. Despite improved understanding of the complex relationship between structure and function obtained through these investigations, significant questions remain regarding the nature, location, and timing of the maturational changes which occur during early development. Functional connectivity magnetic resonance imaging (fcMRI) utilizes spontaneous, low frequency (< 0.1 Hz), coherent fluctuations in blood oxygen level dependent (BOLD) signal to identify networks of functional cerebral connections. Due to the intrinsic characteristics of its image acquisition and analysis, fcMRI offers a novel neuroimaging approach well suited to investigation of infants. Recently, this methodology has been successfully applied to examine neonatal populations, defining normative patterns of large-scale neural network development in the maturing brain. The resting-state networks (RSNs) identified in these studies reflect the evolving cerebral structural architecture, presumably driven by varied genetic and environmental influences. Principal features of these investigations and their role in characterization of the tenets of neural network development during this critical developmental period are highlighted in this review. Despite these successes, optimal methods for fcMRI data acquisition and analysis for this population have not yet been defined. Further, appropriate schemes for interpretation and translation of fcMRI results remain unknown, a matter of increasing importance as functional neuroimaging findings are progressively applied in the clinical arena. Notwithstanding these concerns, fcMRI provides insight into the earliest forms of cerebral connectivity and therefore holds great promise for future neurodevelopmental investigations.

Navigated Brain Stimulation for Preoperative Cortical Mapping in Paretic Patients: Case Report of a Hemiplegic Patient

BACKGROUND AND IMPORTANCE:

Navigated brain stimulation (NBS) is an emerging technology that can be used for preoperative mapping of the motor cortex. It combines conventional transcranial magnetic stimulation with neuronavigation and achieves high precision by taking into account all relevant physical factors. In contrast to functional imaging technologies, NBS does not rely on voluntary patient movements for cortical mapping. Thus, NBS can be used even on patients with severe motor impairment.

CLINICAL PRESENTATION:

This article presents the case of a hemiplegic elderly woman with a brain tumor in the motor cortex. Preoperative NBS surprisingly demonstrated intact corticospinal tracts in the hemiplegic patient. The results modified the surgical strategy. Direct cortical stimulation was performed intraoperatively. The direct cortical stimulation results were in agreement with the preoperative NBS findings, and the clinical success of the surgery exceeded expectations.

CONCLUSION:

NBS can be used for preoperative mapping in plegic patients. Even more important, this case report discusses why tumor resection surgery based on NBS may sometimes lead to substantially better clinical outcomes than surgery planned according to functional imaging technologies.

Localization of focal epileptic discharges using functional connectivity magnetic resonance imaging

OBJECT

In patients with medically refractory epilepsy the accurate localization of the seizure onset zone is critical for successful surgical treatment. The object of this study was to investigate whether the degree of coupling of spontaneous brain activity as measured with functional connectivity MR imaging (fcMR imaging) can accurately identify and localize epileptic discharges.

METHODS

The authors studied 6 patients who underwent fcMR imaging presurgical mapping and subsequently underwent invasive electroencephalography.

RESULTS

Focal regions of statistically significant increases in connectivity were identified in 5 patients when compared with an ad hoc normative sample of 300 controls. The foci identified by fcMR imaging overlapped the epileptogenic areas identified by invasive encephalography in all 5 patients.

CONCLUSIONS

These results suggest that fcMR imaging may provide an effective high-spatial resolution and noninvasive method of localizing epileptic discharges in patients with refractory epilepsy.

Imaging the functional connectivity of the Periaqueductal Gray during genuine and sham electroacupuncture treatment

Background

Electroacupuncture (EA) is currently one of the most popular acupuncture modalities. However, the continuous stimulation characteristic of EA treatment presents challenges to the use of conventional functional Magnetic Resonance Imaging (fMRI) approaches for the investigation of neural mechanisms mediating treatment response because of the requirement for brief and intermittent stimuli in event related or block designed task paradigms. A relatively new analysis method, functional connectivity fMRI (fcMRI), has great potential for studying continuous treatment modalities such as EA. In a previous study, we found that, compared with sham acupuncture, EA can significantly reduce Periaqueductal Gray (PAG) activity when subsequently evoked by experimental pain. Given the PAG's important role in mediating acupuncture analgesia, in this study we investigated functional connectivity with the area of the PAG we previously identified and how that connectivity was affected by genuine and sham EA.

Results

Forty-eight subjects, who were randomly assigned to receive either genuine or sham EA paired with either a high or low expectancy manipulation, completed the study. Direct comparison of each treatment mode's functional connectivity revealed: significantly greater connectivity between the PAG, left posterior cingulate cortex (PCC), and precuneus for the contrast of genuine minus sham; significantly greater connectivity between the PAG and right anterior insula for the contrast of sham minus genuine; no significant differences in connectivity between different contrasts of the two expectancy levels.

Conclusions

Our findings indicate the intrinsic functional connectivity changes among key brain regions in the pain matrix and default mode network during genuine EA compared with sham EA. We speculate that continuous genuine EA stimulation can modify the coupling of spontaneous activity in brain regions that play a role in modulating pain perception.

Clinical applications of resting state functional connectivity

During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.

Intrinsic functional connectivity of the periaqueductal gray, a resting fMRI study

The periaqueductal gray (PAG) is known to play a crucial role in pain modulation and has shown a strong interaction with anterior cingulate cortex in previous functional imaging studies. We investigated the intrinsic functional connectivity of PAG using resting fMRI data from 100 subjects. The results showed that PAG is functionally connected to ACC (rostral and pregenual ACC) and also rostral ventromedial medulla (RVM), forming a core ACC-PAG-RVM network for pain modulation even no pain stimulus is applied. The comparison between genders showed that for the contrast of female minus male, significant difference was observed at mid-cingulate cortex; for the contrast of male minus female, significant differences were observed at left medial orbital prefrontal cortex, and uncus; right insula/operculum and prefrontal cortex. We believe eluciation of this intrinsic PAG network during the resting state will enhance our physiological and pathological understandings of the development and maintenance of chronic pain states.

The role of functional magnetic resonance imaging in brain surgery

New functional neuroimaging techniques are changing our understanding of the human brain, and there is now convincing evidence to move away from the classic and clinical static concepts of functional topography. In a modern neurocognitive view, functions are thought to be represented in dynamic large-scale networks. The authors review the current (limited) role of functional MR imaging in brain surgery and the possibilities of new functional MR imaging techniques for research and neurosurgical practice. A critique of current clinical gold standard techniques (electrocortical stimulation and the Wada test) is given.

Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization

Resting state functional connectivity MRI (fcMRI) is widely used to investigate brain networks that exhibit correlated fluctuations. While fcMRI does not provide direct measurement of anatomic connectivity, accumulating evidence suggests it is sufficiently constrained by anatomy to allow the architecture of distinct brain systems to be characterized. fcMRI is particularly useful for characterizing large-scale systems that span distributed areas (e.g., polysynaptic cortical pathways, cerebro-cerebellar circuits, cortical-thalamic circuits) and has complementary strengths when contrasted with the other major tool available for human connectomics-high angular resolution diffusion imaging (HARDI). We review what is known about fcMRI and then explore fcMRI data reliability, effects of preprocessing, analysis procedures, and effects of different acquisition parameters across six studies (n = 98) to provide recommendations for optimization. Run length (2-12 min), run structure (1 12-min run or 2 6-min runs), temporal resolution (2.5 or 5.0 s), spatial resolution (2 or 3 mm), and the task (fixation, eyes closed rest, eyes open rest, continuous word-classification) were varied. Results revealed moderate to high test-retest reliability. Run structure, temporal resolution, and spatial resolution minimally influenced fcMRI results while fixation and eyes open rest yielded stronger correlations as contrasted to other task conditions. Commonly used preprocessing steps involving regression of nuisance signals minimized nonspecific (noise) correlations including those associated with respiration. The most surprising finding was that estimates of correlation strengths stabilized with acquisition times as brief as 5 min. The brevity and robustness of fcMRI positions it as a powerful tool for large-scale explorations of genetic influences on brain architecture. We conclude by discussing the strengths and limitations of fcMRI and how it can be combined with HARDI techniques to support the emerging field of human connectomics.