Comparison of blocked and event-related fMRI designs for pre-surgical language mapping

Impact of data processing varieties on DCM estimates of effective connectivity from task-fMRI

Effective connectivity (EC) refers to directional or causal influences between interacting neuronal populations or brain regions and can be estimated from functional magnetic resonance imaging (fMRI) data via dynamic causal modeling (DCM). In contrast to functional connectivity, the impact of data processing varieties on DCM estimates of task-evoked EC has hardly ever been addressed. We therefore investigated how task-evoked EC is affected by choices made for data processing. In particular, we considered the impact of global signal regression (GSR), block/event-related design of the general linear model (GLM) used for the first-level task-evoked fMRI analysis, type of activation contrast, and significance thresholding approach. Using DCM, we estimated individual and group-averaged task-evoked EC within a brain network related to spatial conflict processing for all the parameters considered and compared the differences in task-evoked EC between any two data processing conditions via between-group parametric empirical Bayes (PEB) analysis and Bayesian data comparison (BDC). We observed strongly varying patterns of the group-averaged EC depending on the data processing choices. In particular, task-evoked EC and parameter certainty were strongly impacted by GLM design and type of activation contrast as revealed by PEB and BDC, respectively, whereas they were little affected by GSR and the type of significance thresholding. The event-related GLM design appears to be more sensitive to task-evoked modulations of EC, but provides model parameters with lower certainty than the block-based design, while the latter is more sensitive to the type of activation contrast than is the event-related design. Our results demonstrate that applying different reasonable data processing choices can substantially alter task-evoked EC as estimated by DCM. Such choices should be made with care and, whenever possible, varied across parallel analyses to evaluate their impact and identify potential convergence for robust outcomes.

fNIRS a novel neuroimaging tool to investigate olfaction, olfactory imagery, and crossmodal interactions: a systematic review

Olfaction is understudied in neuroimaging research compared to other senses, but there is growing evidence of its therapeutic benefits on mood and well-being. Olfactory imagery can provide similar health benefits as olfactory interventions. Harnessing crossmodal visual-olfactory interactions can facilitate olfactory imagery. Understanding and employing these cross-modal interactions between visual and olfactory stimuli could aid in the research and applications of olfaction and olfactory imagery interventions for health and wellbeing. This review examines current knowledge, debates, and research on olfaction, olfactive imagery, and crossmodal visual-olfactory integration. A total of 56 papers, identified using the PRISMA method, were evaluated to identify key brain regions, research themes and methods used to determine the suitability of fNIRS as a tool for studying these topics. The review identified fNIRS-compatible protocols and brain regions within the fNIRS recording depth of approximately 1.5 cm associated with olfactory imagery and crossmodal visual-olfactory integration. Commonly cited regions include the orbitofrontal cortex, inferior frontal gyrus and dorsolateral prefrontal cortex. The findings of this review indicate that fNIRS would be a suitable tool for research into these processes. Additionally, fNIRS suitability for use in naturalistic settings may lead to the development of new research approaches with greater ecological validity compared to existing neuroimaging techniques.

Evaluating the concordance of functional MRI-based language lateralization and Wada testing in epilepsy patients: A single-center analysis

BACKGROUND

For patients with drug-resistant epilepsy, surgery may be effective in controlling their disease. Surgical evaluation may involve localization of the language areas using functional magnetic resonance imaging (fMRI) or Wada testing. We evaluated the accuracy of task-based fMRI versus Wada-based language lateralization in a cohort of our epilepsy patients.

METHODS

In a single-center, retrospective analysis, we identified patients with medically intractable epilepsy who participated in presurgical language mapping (n = 35) with fMRI and Wada testing. Demographic variables and imaging metrics were obtained. We calculated the laterality index (LI) from task-evoked fMRI activation maps across language areas during auditory and reading tasks to determine lateralization. Possible scores for LI range from -1 (strongly left-hemisphere dominant) to 1 (strongly right-hemisphere dominant). Concordance between fMRI and Wada was estimated using Cohen's Kappa coefficient. Association between the LI scores from the auditory and reading tasks was tested using Spearman's rank correlation coefficient.

RESULTS

The fMRI-based laterality indices were concordant with results from Wada testing in 91.4% of patients during the reading task (κ = .55) and 96.9% of patients during the auditory task (κ = .79). The mean LIs for the reading and auditory tasks were -0.52 ± 0.43 and -0.68 ± 0.42, respectively. The LI scores for the language and reading tasks were strongly correlated, r(30) = 0.57 (p = 0.001).

CONCLUSION

Our findings suggest that fMRI is generally an accurate, low-risk alternative to Wada testing for language lateralization. However, when fMRI indicates atypical language lateralization (e.g., bilateral dominance), patients may benefit from subsequent Wada testing or intraoperative language mapping.

Resting state fMRI brain mapping in pediatric supratentorial brain tumors

Background

Functional mapping of eloquent brain areas is crucial for preoperative planning in patients with brain tumors. Resting state functional MRI (rs-fMRI) allows the localization of functional brain areas without the need for task performance, making it well-suited for the pediatric population. In this study the independent component analysis (ICA) rs-fMRI functional mapping results are reported in a group of 22 pediatric patients with supratentorial brain tumors. Additionally, the functional connectivity (FC) maps of the sensori-motor network (SMN) obtained using ICA and seed-based analysis (SBA) are compared.

Results

Different resting state networks (RSNs) were extracted using ICA with varying levels of sensitivity, notably, the SMN was identified in 100% of patients, followed by the Default mode network (DMN) (91%) and Language networks (80%). Additionally, FC maps of the SMN extracted by SBA were more extensive (mean volume = 25,288.36 mm3, standard deviation = 13,364.36 mm3) than those found on ICA (mean volume = 13,403.27 mm3, standard deviation = 9755.661 mm3). This was confirmed by statistical analysis using a Wilcoxon signed rank t test at p < 0.01.

Conclusions

Results clearly demonstrate the successful applicability of rs-fMRI for localizing different functional brain networks in the preoperative assessment of brain areas, and thus represent a further step in the integration of computational radiology research in a clinical setting.

Discrepant expressive language lateralization in children and adolescents with epilepsy

Neuronavigated transcranial magnetic stimulation (nTMS) has emerged as a presurgical language mapping tool distinct from the widely used functional magnetic resonance imaging (fMRI). We report fMRI and nTMS language-mapping results in 19 pediatric-epilepsy patients and compare those to definitive testing by electrical cortical stimulation, Wada test, and/or neuropsychological testing. Most discordant results occurred when fMRI found right-hemispheric language. In those cases, when nTMS showed left-hemispheric or bilateral language representation, left-hemispheric language was confirmed by definitive testing. Therefore, we propose nTMS should be considered for pediatric presurgical language-mapping when fMRI shows right-hemispheric language, with nTMS results superseding fMRI results in those scenarios.

fNIRS-based brain state transition features to signify functional degeneration after Parkinson's disease

OBJECTIVE

Parkinson's disease (PD) is a common neurodegenerative brain disorder, and early diagnosis is of vital importance for treatment. Existing methods are mainly focused on behavior examination, while the functional neurodegeneration after PD has not been well explored. This paper aims to investigate the brain functional variation of PD patients in comparison with healthy controls.

APPROACH

In this work, we propose brain hemodynamic states and state transition features to signify functional degeneration after PD. Firstly, a functional near-infrared spectroscopy (fNIRS)-based experimental paradigm was designed to capture brain activation during dual-task walking from PD patients and healthy controls. Then, three brain states, named expansion, contraction, and intermediate states, were defined with respect to the oxyhemoglobin and deoxyhemoglobin responses. After that, two features were designed from a constructed transition factor and concurrent variations of oxy- and deoxy-hemoglobin over time, to quantify the transitions of brain states. Further, a support vector machine classifier was trained with the proposed features to distinguish PD patients and healthy controls.

RESULTS

Experimental results showed that our method with the proposed brain state transition features achieved classification accuracy of 0:8200 and F score of 0:9091, and outperformed existing fNIRS-based methods. Compared with healthy controls, PD patients had significantly smaller transition acceleration and transition angle.

SIGNIFICANCE

The proposed brain state transition features well signify functional degeneration of PD patients and may serve as promising functional biomarkers for PD diagnosis.

Shedding light on pain for the clinic: a comprehensive review of using functional near-infrared spectroscopy to monitor its process in the brain

ABSTRACT

Pain is a complex experience that involves sensation, emotion, and cognition. The subjectivity of the traditional pain measurement tools has expedited the interest in developing neuroimaging techniques to monitor pain objectively. Among noninvasive neuroimaging techniques, functional near-infrared spectroscopy (fNIRS) has balanced spatial and temporal resolution; yet, it is portable, quiet, and cost-effective. These features enable fNIRS to image the cortical mechanisms of pain in a clinical environment. In this article, we evaluated pain neuroimaging studies that used the fNIRS technique in the past decade. Starting from the experimental design, we reviewed the regions of interest, probe localization, data processing, and primary findings of these existing fNIRS studies. We also discussed the fNIRS imaging's potential as a brain surveillance technique for pain, in combination with artificial intelligence and extended reality techniques. We concluded that fNIRS is a brain imaging technique with great potential for objective pain assessment in the clinical environment.

Early soft and flexible fusion of electroencephalography and functional magnetic resonance imaging via double coupled matrix tensor factorization for multisubject group analysis

Data fusion refers to the joint analysis of multiple datasets that provide different (e.g., complementary) views of the same task. In general, it can extract more information than separate analyses can. Jointly analyzing electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) measurements has been proved to be highly beneficial to the study of the brain function, mainly because these neuroimaging modalities have complementary spatiotemporal resolution: EEG offers good temporal resolution while fMRI is better in its spatial resolution. The EEG–fMRI fusion methods that have been reported so far ignore the underlying multiway nature of the data in at least one of the modalities and/or rely on very strong assumptions concerning the relation of the respective datasets. For example, in multisubject analysis, it is commonly assumed that the hemodynamic response function is a priori known for all subjects and/or the coupling across corresponding modes is assumed to be exact (hard). In this article, these two limitations are overcome by adopting tensor models for both modalities and by following soft and flexible coupling approaches to implement the multimodal fusion. The obtained results are compared against those of parallel independent component analysis and hard coupling alternatives, with both synthetic and real data (epilepsy and visual oddball paradigm). Our results demonstrate the clear advantage of using soft and flexible coupled tensor decompositions in scenarios that do not conform with the hard coupling assumption.

Mental Fatigue after Mild Traumatic Brain Injury in Relation to Cognitive Tests and Brain Imaging Methods

Most people recover within months after a mild traumatic brain injury (TBI) or concussion, but some will suffer from long-term fatigue with a reduced quality of life and the inability to maintain their employment status or education. For many people, mental fatigue is one of the most distressing and long-lasting symptoms following an mTBI. No efficient treatment options can be offered. The best method for measuring fatigue today is with fatigue self-assessment scales, there being no objective clinical tests available for mental fatigue. The aim here is to provide a narrative review and identify fatigue in relation to cognitive tests and brain imaging methods. Suggestions for future research are presented.

Functional magnetic resonance imaging based on Chinese tasks to protect language function in epileptics

OBJECTIVE

To evaluate the efficacy of functional magnetic resonance imaging (fMRI) based on Chinese tasks to protect the language function in epileptics.

MATERIALS AND METHODS

A total of 34 native Chinese patients with epilepsy were enrolled and examined with BOLD-fMRI scan based on six Chinese tasks. The epileptics were randomly divided into the control group (n = 15) and the experimental group (n = 19). The control group underwent the hollowing and multiple subpial transection operation only based on intraoperative EEG, while the experimental group was under notification of task-state fMRI results in addition. Whereafter, the language ability of patients was evaluated by ABC assessment.

RESULTS

The brain regions related to Chinese function activated by different tasks were remarkably distinct and mainly concentrated in the temporal lobe and frontal lobe. In ontoanalysis, the activation signals of the fusiform gyrus, parahippocampal gyrus, hippocampus, and precentral gyrus were generally low or even could not be detected. Unlike ontoanalysis, group analysis showed that the main effect regions of AN and PN task were in right superior temporal gyrus. The main effect regions of FF and VFC task were in right middle temporal gyrus. The main effect region of SF task was in left superior temporal gyrus. The main effect region of VFL task was in right middle frontal gyrus. The ABC assessment score of the control group 6 months after surgery was significantly lower than that 1 week before surgery (p < .05), while there was no significant difference in the experimental group, and the score of the experimental group was higher than that of the control group.

CONCLUSION

In the surgical treatment of epilepsy, a personalized surgical plan, based on task-state fMRI and intraoperative EEG, can be developed according to the difference of activation areas to protect the language function and improve the quality of life in postoperative patients.

Subject-independent decoding of affective states using functional near-infrared spectroscopy

Affective decoding is the inference of human emotional states using brain signal measurements. This approach is crucial to develop new therapeutic approaches for psychiatric rehabilitation, such as affective neurofeedback protocols. To reduce the training duration and optimize the clinical outputs, an ideal clinical neurofeedback could be trained using data from an independent group of volunteers before being used by new patients. Here, we investigated if this subject-independent design of affective decoding can be achieved using functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas. For this purpose, a linear discriminant analysis classifier was first trained in a dataset (49 participants, 24.65±3.23 years) and then tested in a completely independent one (20 participants, 24.00±3.92 years). Significant balanced accuracies between classes were found for positive vs. negative (64.50 ± 12.03%, p<0.01) and negative vs. neutral (68.25 ± 12.97%, p<0.01) affective states discrimination during a reactive block consisting in viewing affective-loaded images. For an active block, in which volunteers were instructed to recollect personal affective experiences, significant accuracy was found for positive vs. neutral affect classification (71.25 ± 18.02%, p<0.01). In this last case, only three fNIRS channels were enough to discriminate between neutral and positive affective states. Although more research is needed, for example focusing on better combinations of features and classifiers, our results highlight fNIRS as a possible technique for subject-independent affective decoding, reaching significant classification accuracies of emotional states using only a few but biologically relevant features.

Functional magnetic resonance imaging multivoxel pattern analysis reveals neuronal substrates for collaboration and competition with myopic and predictive strategic reasoning

Competition and collaboration are strategies that can be used to optimize the outcomes of social interactions. Research into the neuronal substrates underlying these aspects of social behavior has been limited due to the difficulty in distinguishing complex activation via univariate analysis. Therefore, we employed multivoxel pattern analysis of functional magnetic resonance imaging to reveal the neuronal activations underlying competitive and collaborative processes when the collaborator/opponent used myopic/predictive reasoning. Twenty‐four healthy subjects participated in 2 × 2 matrix‐based sequential‐move games. Searchlight‐based multivoxel patterns were used as input for a support vector machine using nested cross‐validation to distinguish game conditions, and identified voxels were validated via the regression of the behavioral data with bootstrapping. The left anterior insula (accuracy = 78.5%) was associated with competition, and middle frontal gyrus (75.1%) was associated with predictive reasoning. The inferior/superior parietal lobules (84.8%) and middle frontal gyrus (84.7%) were associated with competition, particularly in trials with a predictive opponent. The visual/motor areas were related to response time as a proxy for visual attention and task difficulty. Our results suggest that multivoxel patterns better represent the neuronal substrates underlying the social cognition of collaboration and competition intermixed with myopic and predictive reasoning than do univariate features.

Toward Comparison of Cortical Activation with Different Motor Learning Methods Using Event-Related Design: EEG-fNIRS Study

Recently, motor imagery brain-computer interface (MI-BCI) has been studied as a motor learning method and evaluated by comparing with conventional passive and active training. Most functional near-infrared spectroscopy (fNIRS) studies adopted block design for comparing those motor learning methods, including MI-BCI. Compared to the block design, event-related design would be more appropriate for estimating cortical activation in MI-BCI which provides feedback for each trial. This paper is a preliminary study to check the feasibility whether event-related design can be applicable for MI-BCI. To this end, three different motor learning methods involving MI-BCI were compared. In hemodynamic response, MI-BCI showed significantly stronger cortical activation than passive training (PT), and weaker than active training (AT), which conforms most existing studies. The results demonstrate that event-related design could be applied to investigate cortical effects of MI-BCI and comparing hemodynamic responses of different motor learning methods.

Human Discrimination and Categorization of Emotions in Voices: A Functional Near-Infrared Spectroscopy (fNIRS) Study

Functional Near-Infrared spectroscopy (fNIRS) is a neuroimaging tool that has been recently used in a variety of cognitive paradigms. Yet, it remains unclear whether fNIRS is suitable to study complex cognitive processes such as categorization or discrimination. Previously, functional imaging has suggested a role of both inferior frontal cortices in attentive decoding and cognitive evaluation of emotional cues in human vocalizations. Here, we extended paradigms used in functional magnetic resonance imaging (fMRI) to investigate the suitability of fNIRS to study frontal lateralization of human emotion vocalization processing during explicit and implicit categorization and discrimination using mini-blocks and event-related stimuli. Participants heard speech-like but semantically meaningless pseudowords spoken in various tones and evaluated them based on their emotional or linguistic content. Behaviorally, participants were faster to discriminate than to categorize; and processed the linguistic faster than the emotional content of stimuli. Interactions between condition (emotion/word), task (discrimination/categorization) and emotion content (anger, fear, neutral) influenced accuracy and reaction time. At the brain level, we found a modulation of the Oxy-Hb changes in IFG depending on condition, task, emotion and hemisphere (right or left), highlighting the involvement of the right hemisphere to process fear stimuli, and of both hemispheres to treat anger stimuli. Our results show that fNIRS is suitable to study vocal emotion evaluation, fostering its application to complex cognitive paradigms.

Pediatric Functional Neuroimaging: Practical Tips and Pearls

OBJECTIVE. Functional MRI (fMRI) is clinically used for localization of eloquent cortex before surgical intervention, most commonly motor and language function in patients with tumors or epilepsy. In the pediatric population, special considerations for fMRI relate to limited examination tolerance, small head size, developing anatomy and physiology, and diverse potential abnormalities. In this article, we will highlight pearls and pitfalls of clinical pediatric fMRI including blood oxygenation level-dependent imaging principles, patient preparation, study acquisition, data postprocessing, and examination interpretation. CONCLUSION. Clinical fMRI is indicated for presurgical localization of eloquent cortex in patients with tumors, epilepsy, or other neurologic conditions and requires a solid understanding of technical considerations and data processing. In children, special approaches are needed for patient preparation as well as study design, acquisition, and interpretation. Radiologists should be cognizant of developmental neuroanatomy, causes of neuropathology, and capacity for neuroplasticity in the pediatric population.

Clinical Utility of Preoperative Bilingual Language fMRI Mapping in Patients with Brain Tumors

BACKGROUND AND PURPOSE

Previous literature has demonstrated disparity in the postoperative recovery of first and second language function of bilingual neurosurgical patients. However, it is unclear to whether preoperative brain mapping of both languages is needed. In this study, we aimed to evaluate the clinical utility of language task functional MRI (fMRI) implemented in both languages in bilingual patients.

METHODS

We retrospectively examined fMRI data of 13 bilingual brain tumor patients (age: 23 to 59 years) who performed antonym generation task-based fMRIs in English and non-English language. The usefulness of bilingual language mapping was evaluated using a structured survey administered to 5 neurosurgeons. Additionally, quantitative comparison between the brain activation maps of both languages was performed.

RESULTS

Survey responses revealed differences in raters' surgical approach, including asleep versus awake surgery and extent of resection, after viewing the language fMRI maps. Additional non-English fMRI led to changes in surgical decision-making and bettered localization of language areas. Quantitative analysis revealed an increase in laterality index (LI) in non-English fMRI compared to English fMRI. The Dice coefficient demonstrated fair overlap (.458 ± .160) between the activation maps.

CONCLUSION

Bilingual fMRI mapping of bilingual patients allows to better appreciate functionally active language areas that may be neglected in single language mapping. Utility of bilingual mapping was supported by changes in both surgical approach and LI measurements, suggesting its benefit on preoperative language mapping.

Functional MRI Task Comparison for Language Mapping in Neurosurgical Patients

BACKGROUND AND PURPOSE

Language task-based functional MRI (fMRI) is increasingly used for presurgical planning in patients with brain lesions. Different paradigms elicit activations of different components of the language network. The aim of this study is to optimize fMRI clinical usage by comparing the effectiveness of three language tasks for language lateralization and localization in a large group of patients with brain lesions.

METHODS

We analyzed fMRI data from a sequential retrospective cohort of 51 patients with brain lesions who underwent presurgical fMRI language mapping. We compared the effectiveness of three language tasks (Antonym Generation, Sentence Completion (SC), and Auditory Naming) for lateralizing language function and for activating cortex within patient-specific regions-of-interest representing eloquent language areas, and assessed the degree of spatial overlap of the areas of activation elicited by each task.

RESULTS

The tasks were similarly effective for lateralizing language within the anterior language areas. The SC task produced higher laterality indices within the posterior language areas and had a significantly higher agreement with the clinical report. Dice coefficients between the task pairs were in the range of .351-.458, confirming substantial variation in the components of the language network activated by each task.

CONCLUSIONS

SC task consistently produced large activations within the dominant hemisphere and was more effective for lateralizing language within the posterior language areas. The low degree of spatial overlap among the tasks strongly supports the practice of using a battery of tasks to help the surgeon to avoid eloquent language areas.

Regions of Interest as nodes of dynamic functional brain networks

The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly, nodes are defined by Regions of Interest (ROIs), predetermined groupings of fMRI measurement voxels. Earlier, we demonstrated that the functional homogeneity of ROIs, captured by their spatial consistency, varies widely across ROIs in commonly used brain atlases. Here, we ask how ROIs behave as nodes of dynamic brain networks. To this end, we use two measures: spatiotemporal consistency measures changes in spatial consistency across time and network turnover quantifies the changes in the local network structure around an ROI. We find that spatial consistency varies non-uniformly in space and time, which is reflected in the variation of spatiotemporal consistency across ROIs. Furthermore, we see time-dependent changes in the network neighborhoods of the ROIs, reflected in high network turnover. Network turnover is nonuniformly distributed across ROIs: ROIs with high spatiotemporal consistency have low network turnover. Finally, we reveal that there is rich voxel-level correlation structure inside ROIs. Because the internal structure and the connectivity of ROIs vary in time, the common approach of using static node definitions may be surprisingly inaccurate. Therefore, network neuroscience would greatly benefit from node definition strategies tailored for dynamical networks.

Functional MRI on executive functioning in aging and dementia: A scoping review of cognitive tasks

Cognitive decline with aging and dementia is especially poignant with regard to the executive functioning that is necessary for activities of daily independent living. The relationship between age-related neurodegeneration in the prefrontal cortex and executive functioning has been uniquely investigated using task-phase functional magnetic resonance imaging (fMRI) to detect brain activity in response to stimuli; however, a comprehensive list of task designs that have been implemented to task-phase fMRI is absent in the literature. The purpose of this review was to recognize what methods have been used to study executive functions with aging and dementia in fMRI tasks, and to describe and categorize them. The following cognitive subdomains were emphasized: cognitive flexibility, planning and decision-making, working memory, cognitive control/inhibition, semantic processing, attention and concentration, emotional functioning, and multitasking. Over 30 different task-phase fMRI designs were found to have been implemented in the literature, all adopted from standard neuropsychological assessments. Cognitive set-shifting and decision-making tasks were particularly well studied in regard to age-related neurodegeneration, while emotional functioning and multitasking designs were found to be the least utilized. Summarizing the information on which tasks have shown the greatest usability will assist in the future design and implementation of effective fMRI experiments targeting executive functioning.

Brain function characteristics of chronic fatigue syndrome: A task fMRI study

The mechanism underlying neurological dysfunction in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) is yet to be established. This study investigated the temporal complexity of blood oxygenation level dependent (BOLD) changes in response to the Stroop task in CFS patients. 43 CFS patients (47.4 ± 11.8 yrs) and 26 normal controls (NCs, 43.4 ± 13.9 yrs) were included in this study. Their mental component summary (MCS) and physical component summary (PCS) from the 36-item Short Form Health Survey (SF-36) questionnaire were recorded. Their Stroop colour-word task performance was measured by accuracy and response time (RT). The BOLD changes associated with the Stroop task were evaluated using a 2-level general linear model approach. The temporal complexity of the BOLD responses, a measure of information capacity and thus adaptability to a challenging environment, in each activated region was measured by sample entropy (SampEn). The CFS patients showed significantly longer RTs than the NCs (P < 0.05) but no significant difference in accuracy. One sample t-tests for the two groups (Family wise error adjusted PFWE < 0.05) showed more BOLD activation regions in the CFS, although a two sample group comparison did not show significant difference. BOLD SampEns in ten regions were significantly lower (FDR-q < 0.05) in CFS patients. BOLD SampEns in 15 regions were significantly associated with PCS (FDR-q < 0.05) and in 9 regions were associated with MCS (FDR-q < 0.05) across all subjects. SampEn of the BOLD signal in the medioventral occipital cortex could explain 40% and 31% of the variance in the SF-36 PCS and MCS scores, and those in the precentral gyrus could explain an additional 16% and 7% across all subjects. This is the first study to investigate BOLD signal SampEn in response to tasks in CFS. The results suggest the brain responds differently to a cognitive challenge in patients with CFS, with recruitment of wider regions to compensate for lower information capacity.

Challenges and techniques for presurgical brain mapping with functional MRI

Functional magnetic resonance imaging (fMRI) is increasingly used for preoperative counseling and planning, and intraoperative guidance for tumor resection in the eloquent cortex. Although there have been improvements in image resolution and artifact correction, there are still limitations of this modality. In this review, we discuss clinical fMRI's applications, limitations and potential solutions. These limitations depend on the following parameters: foundations of fMRI, physiologic effects of the disease, distinctions between clinical and research fMRI, and the design of the fMRI study. We also compare fMRI to other brain mapping modalities which should be considered as alternatives or adjuncts when appropriate, and discuss intraoperative use and validation of fMRI. These concepts direct the clinical application of fMRI in neurosurgical patients.

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fMRI is increasingly used for presurgical brain mapping for surgical planning.

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Understanding of the limitations of fMRI is critical for its clinical use.

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Clinical fMRI's challenges and potential solutions are discussed.

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Intraoperative use and validation of fMRI are discussed.

A New Paradigm for Individual Subject Language Mapping: Movie-Watching fMRI

BACKGROUND

Functional MRI (fMRI) based on language tasks has been used in presurgical language mapping in patients with lesions in or near putative language areas. However, if patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or noninterpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping.

METHODS

A 7-minute movie clip with contrasting speech and nonspeech segments was shown to 22 right-handed healthy subjects. Based on all subjects' language functional regions-of-interest, 6 language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals' language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects.

RESULTS

Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of 2 brain tumor patients' movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier.

CONCLUSIONS

These results suggest that it is feasible to use this novel "task-free" paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation.

Passive fMRI mapping of language function for pediatric epilepsy surgical planning: validation using Wada, ECS, and FMAER

In this study we validate passive language fMRI protocols designed for clinical application in pediatric epilepsy surgical planning as they do not require overt participation from patients. We introduced a set of quality checks that assess reliability of noninvasive fMRI mappings utilized for clinical purposes. We initially compared two fMRI language mapping paradigms, one active in nature (requiring participation from the patient) and the other passive in nature (requiring no participation from the patient). Group-level analysis in a healthy control cohort demonstrated similar activation of the putative language centers of the brain in the inferior frontal (IFG) and temporoparietal (TPG) regions. Additionally, we showed that passive language fMRI produced more left-lateralized activation in TPG (LI=+0.45) compared to the active task; with similarly robust left-lateralized IFG (LI=+0.24) activations using the passive task. We validated our recommended fMRI mapping protocols in a cohort of 15 pediatric epilepsy patients by direct comparison against the invasive clinical gold-standards. We found that language-specific TPG activation by fMRI agreed to within 9.2mm to subdural localizations by invasive functional mapping in the same patients, and language dominance by fMRI agreed with Wada test results at 80% congruency in TPG and 73% congruency in IFG. Lastly, we tested the recommended passive language fMRI protocols in a cohort of very young patients and confirmed reliable language-specific activation patterns in that challenging cohort. We concluded that language activation maps can be reliably achieved using the passive language fMRI protocols we proposed even in very young (average 7.5 years old) or sedated pediatric epilepsy patients.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors.

Imaging and target volume delineation in glioma

Here we review current practices in target volume delineation for radical radiotherapy planning for gliomas. Current radiotherapy planning margins for glioma are informed by historic data of recurrence patterns using radiological imaging or post-mortem studies. Radiotherapy planning for World Health Organization grade II-IV gliomas currently relies predominantly on T1-weighted contrast-enhanced magnetic resonance imaging (MRI) and T2/fluid-attenuated inversion recovery sequences to identify the gross tumour volume (GTV). Isotropic margins are added empirically for each tumour type, usually without any patient-specific individualisation. We discuss novel imaging techniques that have the potential to influence radiotherapy planning, by improving definition of the tumour extent and its routes of invasion, thus modifying the GTV and allowing anisotropic expansion to a clinical target volume better reflecting areas at risk of recurrence. Identifying the relationships of tumour boundaries to important white matter pathways and eloquent areas of cerebral cortex could lead to reduced normal tissue complications. Novel magnetic resonance approaches to identify tumour extent and invasion include: (i) diffusion-weighted magnetic resonance metrics; (ii) diffusion tensor imaging; and (iii) positron emission tomography, using radiolabelled amino acids methyl-11C-L-methionine and 18F-fluoroethyltyrosine. Novel imaging techniques may also have a role together with clinical characteristics and molecular genetic markers in predicting response to therapy. Most significant among these techniques is dynamic contrast-enhanced MRI, which uses dynamic acquisition of images after injection of intravenous contrast. A number of studies have identified changes in diffusion and microvascular characteristics occurring during the early stages of radiotherapy as powerful predictive biomarkers of outcome.

Effect of disease and recovery on functional anatomy in brain tumor patients: insights from functional MRI and diffusion tensor imaging

Patients with brain tumors provide a unique opportunity to understand functional brain plasticity. Using advanced imaging techniques, such as functional MRI and diffusion tensor imaging, we have gained tremendous knowledge of brain tumor behavior, transformation, infiltration and destruction of nearby structures. Using these advanced techniques as an adjunct with more proven techniques, such as direct cortical stimulation, intraoperative navigation and advanced microsurgical techniques, we now are able to better formulate safer resection trajectories, perform larger resections at reduced risk and better counsel patients and their families about possible complications. Brain mapping in patients with brain tumors and other lesions has shown us that the old idea of fixed function of the adult cerebral cortex is not entirely true. Improving care for patients with brain lesions in the future will depend on better understanding of the functional organization and plasticity of the adult brain. Advanced noninvasive brain imaging will undoubtedly play a role in advancing this understanding.

Group independent component analysis and functional MRI examination of changes in language areas associated with brain tumors at different locations

Object

This study investigates the effect of tumor location on alterations of language network by brain tumors at different locations using blood oxygenation level dependent (BOLD) fMRI and group independent component analysis (ICA).

Subjects and Methods

BOLD fMRI data were obtained from 43 right handed brain tumor patients. Presurgical mapping of language areas was performed on all 43 patients with a picture naming task. All data were retrospectively analyzed using group ICA. Patents were divided into three groups based on tumor locations, i.e., left frontal region, left temporal region or right hemisphere. Laterality index (LI) was used to assess language lateralization in each group.

Results

The results from BOLD fMRI and ICA revealed the different language activation patterns in patients with brain tumors located in different brain regions. Language areas, such as Broca’s and Wernicke’s areas, were intact in patients with tumors in the right hemisphere. Significant functional changes were observed in patients with tumor in the left frontal and temporal areas. More specifically, the tumors in the left frontal region affect both Broca’s and Wernicke’s areas, while tumors in the left temporal lobe affect mainly Wernicke’s area. The compensated activation increase was observed in the right frontal areas in patients with left hemisphere tumors.

Conclusion

Group ICA provides a model free alternative approach for mapping functional networks in brain tumor patients. Altered language activation by different tumor locations suggested reorganization of language functions in brain tumor patients and may help better understanding of the language plasticity.

A wavelet-based Bayesian approach to regression models with long memory errors and its application to FMRI data

This article considers linear regression models with long memory errors. These models have been proven useful for application in many areas, such as medical imaging, signal processing, and econometrics. Wavelets, being self-similar, have a strong connection to long memory data. Here we employ discrete wavelet transforms as whitening filters to simplify the dense variance-covariance matrix of the data. We then adopt a Bayesian approach for the estimation of the model parameters. Our inferential procedure uses exact wavelet coefficients variances and leads to accurate estimates of the model parameters. We explore performances on simulated data and present an application to an fMRI data set. In the application we produce posterior probability maps (PPMs) that aid interpretation by identifying voxels that are likely activated with a given confidence.

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.

Extended Broca's area in the functional connectome of language in adults: combined cortical and subcortical single-subject analysis using fMRI and DTI tractography

Traditional models of the human language circuitry encompass three cortical areas, Broca's, Geschwind's and Wernicke's, and their connectivity through white matter fascicles. The neural connectivity deep to these cortical areas remains poorly understood, as does the macroscopic functional organization of the cortico-subcortical language circuitry. In an effort to expand current knowledge, we combined functional MRI (fMRI) and diffusion tensor imaging to explore subject-specific structural and functional macroscopic connectivity, focusing on Broca's area. Fascicles were studied using diffusion tensor imaging fiber tracking seeded from volumes placed manually within the white matter. White matter fascicles and fMRI-derived clusters (antonym-generation task) of positive and negative blood-oxygen-level-dependent (BOLD) signal were co-registered with 3-D renderings of the brain in 12 healthy subjects. Fascicles connecting BOLD-derived clusters were analyzed within specific cortical areas: Broca's, with the pars triangularis, the pars opercularis, and the pars orbitaris; Geschwind's and Wernicke's; the premotor cortex, the dorsal supplementary motor area, the middle temporal gyrus, the dorsal prefrontal cortex and the frontopolar region. We found a functional connectome divisible into three systems-anterior, superior and inferior-around the insula, more complex than previously thought, particularly with respect to a new extended Broca's area. The extended Broca's area involves two new fascicles: the operculo-premotor fascicle comprised of well-organized U-shaped fibers that connect the pars opercularis with the premotor region; and (2) the triangulo-orbitaris system comprised of intermingled U-shaped fibers that connect the pars triangularis with the pars orbitaris. The findings enhance our understanding of language function.

Functional magnetic resonance imaging for language mapping in temporal lobe epilepsy

Functional magnetic resonance imaging (fMRI) is a noninvasive technique that is increasingly used to understand the cerebral cortical networks and organizations. In this paper, we describe the role of fMRI for mapping language networks in the presurgical workup of patients with medically intractable temporal lobe epilepsy (TLE). Studies comparing fMRI with the intracarotid sodium amobarbital (Wada) test and fMRI with intraoperative cortical stimulation mapping for language lateralization and/or localization in medically intractable TLE are discussed.

Functional MRI applications in epilepsy surgery

Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique that has grown rapidly in popularity over the past decade. It is already prevalent in psychology, cognitive and basic neuroscience research and is being used increasingly as a tool for clinical decision-making in epilepsy. It has been used to determine language location and laterality in patients, sometimes eliminating the need for invasive tests. fMRI can been used pre-surgically to guide resection margins, preserving eloquent cortex. Other fMRI paradigms assessing memory, visual and somatosensory systems have limited clinical applications currently, but show great promise. Simultaneous recording of electroencephalogram (EEG) and fMRI has also provided insights into the networks underlying seizure generation and is increasingly being used in epilepsy centres. In this review, we present some of the current clinical applications for fMRI in the pre-surgical assessment of epilepsy patients, and examine a number of new techniques that may soon become clinically relevant.

Functional mapping of language networks in the normal brain using a word-association task

Background:

Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation.

Aim:

The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI) in normal human subjects.

Materials and Methods:

Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2*-weighted gradient-echo echo-planar imaging (GE-EPI) sequence (TR 4523 ms, TE 64 ms, flip angle 90°) with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s) with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2) with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD) signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps.

Results:

Single subject analysis of the functional data (FWE-corrected, P≤0.001) revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG), superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG), anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001) revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas.

Conclusions:

Group data analysis revealed a cerebellar–occipital–fusiform–thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these areas facilitate language comprehension by activating a semantic association network of words processed postlexical access. This finding is important when assessing the extent of cognitive damage and/or recovery and can be used for presurgical planning after optimization.

How much are clinical fMRI reports influenced by standard postprocessing methods? An investigation of normalization and region of interest effects in the medial temporal lobe

Recent evidence has indicated that standard postprocessing methods such as template-based region of interest (ROI) definition and normalization of individual brains to a standard template may influence final outcome of functional magnetic resonance imaging investigations. Here, we provide the first comprehensive investigation into whether ROI definition and normalization may also change the clinical interpretation of patient data. A series of medial temporal lobe epilepsy patients were investigated with a clinical memory paradigm and individually delineated as well as template-based ROIs. Different metrics for activation quantification were applied. Results show that the application of template-based ROIs can significantly change the clinical interpretation of individual patient data. This relates to sensitivity for brain activation and hemispheric dominance. We conclude that individual ROIs should be defined on nontransformed functional data and that use of more than one metric for activation quantification is beneficial.

FMRI language mapping in children: a panel of language tasks using visual and auditory stimulation without reading or metalinguistic requirements

In the context of presurgical mapping or investigation of neurological and developmental disorders in children, language fMRI raises the issue of the design of a tasks panel achievable by young disordered children. Most language tasks shown to be efficient with healthy children require metalinguistic or reading abilities, therefore adding attentional, cognitive and academic constraints that may be problematic in this context. This study experimented a panel of four language tasks that did not require high attentional skills, reading, or metalinguistic abilities. Two reference tasks involving auditory stimulation (words generation from category, "category"; auditory responsive naming, "definition") were compared with two new tasks involving visual stimulation. These later were designed to tap spontaneous phonological production, in which the names of pictures to be named involve a phonological difference (e.g. in French poule/boule/moule; "phon-diff") or change of segmentation (e.g. in French car/car-te/car-t-on; "phon-seg"). Eighteen healthy children participated (mean age: 12.7+/-3 years). Data processing involved normalizing the data via a matched pairs pediatric template, and inter-task and region of interest analyses with laterality assessment. The reference tasks predominantly activated the left frontal and temporal core language regions, respectively. The new tasks activated these two regions simultaneously, more strongly for the phon-seg task. The union and intersection of all tasks provided more sensitive or specific maps. The study demonstrates that both reference and new tasks highlight core language regions in children, and that the latter are useful for the mapping of spontaneous phonological processing. The use of several different tasks may improve the sensitivity and specificity of fMRI.

Threshold-independent functional MRI determination of language dominance: a validation study against clinical gold standards

Functional MRI (fMRI) is often used for presurgical language lateralization. In the most common approach, a laterality index (LI) is calculated on the basis of suprathreshold voxels. However, strong dependencies between LI and threshold can diminish the effectiveness of this technique; in this study we investigated an original methodology that is independent of threshold. We compared this threshold-independent method against the common threshold-dependent method in 14 patients with epilepsy who underwent Wada testing. In addition, clinical results from electrocortical language mapping and postoperative language findings were used to assess the validity of the fMRI lateralization method. The threshold-dependent methodology yielded ambiguous or incongruent lateralization outcomes in 4 of 14 patients in the inferior frontal gyrus (IFG) and in 6 of 14 patients in the supramarginal gyrus (SMG). Conversely, the threshold-independent method yielded unambiguous lateralization in all the patients tested, and demonstrated lateralization outcomes incongruent with clinical standards in 2 of 14 patients in IFG and in 1 of 14 patients in SMG. This validation study demonstrates that the threshold-dependent LI calculation is prone to significant within-patient variability that could render results unreliable; the threshold-independent method can generate distinct LIs that are more concordant with gold standard clinical findings.