fMRI Mapping Research Articles

EP 23. Cortical language mapping by rTMS compared to fMRI in healthy volunteers

Introduction Functional magnetic resonance imaging (fMRI) is considered to be the standard method regarding non-invasive language mapping. However, repetitive navigated transcranial magnetic stimulation (rTMS) gains increasing importance with respect to that purpose. However, comparisons between both methods are sparse. Objective To compare the results of rTMS and fMRI language mapping in healthy volunteers. Patients & methods We performed fMRI and rTMS language mapping of the left hemisphere in 40 healthy, right-handed subjects in combination with the tasks that are most commonly used in the neurosurgical context (fMRI: word-generation = WGEN task; rTMS: object-naming = ON task). Different rTMS error rate thresholds (ERTs) were calculated, and Cohen’s kappa coefficient and the cortical parcellation system (CPS) were used for systematic comparison of the two techniques. Results Overall, mean kappa coefficients were low, revealing no distinct agreement. We found the highest agreement for both techniques when using the 2-out-of-3 rule (CPS region defined as language-positive in terms of rTMS if at least 2 out of 3 stimulations led to a naming error). However, kappa for this threshold was only 0.24, indicating fair agreement. Conclusions Regarding the comparison of fMRI and rTMS, language mapping results seem to differ in a wide range, at least when the tasks of the present trials are used. Since it is not possible to verify the present results via direct cortical stimulation (DCS) as the gold standard method, we must be careful to call one of the two techniques the true one. However, this study yields valuable results regarding the comparison of these frequently used mapping techniques for the most common language tasks applied in the neurosurgical routine.

Physiological noise correction using ECG-derived respiratory signals for enhanced mapping of spontaneous neuronal activity with simultaneous EEG-fMRI

The study of spontaneous brain activity based on BOLD-fMRI may be seriously compromised by the presence of signal fluctuations of non-neuronal origin, most prominently due to cardiac and respiratory mechanisms. Methods used for modeling and correction of the so-called physiological noise usually rely on the concurrent measurement of cardiac and respiratory signals. In simultaneous EEG-fMRI recordings, which are primarily aimed at the study of spontaneous brain activity, the electrocardiogram (ECG) is typically measured as part of the EEG setup but respiratory data are not generally available. Here, we propose to use the ECG-derived respiratory (EDR) signal estimated by Empirical Mode Decomposition (EMD) as a surrogate of the respiratory signal, for retrospective physiological noise correction of typical simultaneous EEG-fMRI data. A physiological noise model based on these physiological signals (P-PNM) complemented with fMRI-derived noise regressors was generated, and evaluated, for 17 simultaneous EEG-fMRI datasets acquired from a group of seven epilepsy patients imaged at 3T. The respiratory components of P-PNM were found to explain BOLD variance significantly in addition to the cardiac components, suggesting that the EDR signal was successfully extracted from the ECG, and P-PNM outperformed an image-based model (I-PNM) in terms of total BOLD variance explained. Further, the impact of the correction using P-PNM on fMRI mapping of patient-specific epileptic networks and the resting-state default mode network (DMN) was assessed in terms of sensitivity and specificity and, when compared with an ICA-based procedure and a standard pre-processing pipeline, P-PNM achieved the best performance. Overall, our results support the feasibility and utility of extracting physiological noise models of the BOLD signal resorting to ECG data exclusively, with substantial impact on the simultaneous EEG-fMRI mapping of resting-state networks, and, most importantly, epileptic networks where sensitivity and specificity are still limited.

EP 32. Automated high resolution fMRI mapping of the cortical sensory fingertip somatotopy in group examinations

Objective The increasing spatial precision in functional brain mapping is a methodological key issue driving the progress in brain research. Mapping of previously invisible fine scale details permits the discovery of unknown functional brain properties. Currently, the available resolution of fMRI examinations is increasing rapidly. However, data analysis techniques lag behind this development, and achieve an effective resolution which is smaller as the maximum possible spatial precision. We present a data analysis technique with maximum spatial precision in group analyses of high resolution functional magnetic resonance imaging (fMRI) data. Methods The contralateral fingertip representations of thumb, index and middle finger were investigated in a group of 18 participants, for right and left hand. A block design was applied (absolute duration of 200 s) including long counting pulses as a temporal identification task for attention monitoring ( Fig. 1 ). Imaging was carried out with a 3 Tesla MRI-scanner (Verio, Siemens, Germany). FreeSurfer recommendations for the anatomy scans were followed (standard MPRAGE sequence). A standard gradient-echo EPI sequence was used for fMRI (resolution 1.5 × 1.5 × 2 mm 3 , 17 slices, field of view = 191 × 179 mm 2 , TE/TR = 3.6 ms/21 ms). Data analysis was performed with an automated protocol ( Pfannmoller et al., 2015 ), including vessel artefact removal. Cortical positions of the fingertips were computed on individual and MNI brains, using volume-based linear or surface-based non-linear normalization. An assessment of cortical distance measures, for mapping of functional properties, was carried out including straight-line distances, using the 3-D Euclidean measure, and shortest connections within the cortical surface, either with the Dijkstra or LOS-Floyd algorithms. Results In BA3b a distinct somatotopy was found for both hands. The maximum spatial fingertip spread in BA3b after linear normalization was at least two times larger than for the non-linear normalization. All properties of the BA3b fingertip somatotopy were left-right symmetric. Since the representation in BA1 did not exhibit any of those features it was neglected. The LOS-Floyd algorithm achieved an error free result for the distances within measurement accuracy. In contrast, Euclidean distances did not account for the relevant cortical properties. Dijkstra distances were sufficiently precise in the individual brains, but excessively overestimated the left-hand distances after non-linear normalization. Discussion & conclusion Since the representations in BA1 and BA3b are entirely different, the cytoarchitectonic divisions need to be accounted for. The convergence of the BA3b fingertip positions after non-linear normalization implies a removal of the anatomical variability, leaving exclusively functional variability. In the distance mapping, application of the LOS-Floyd algorithm was mandatory in the group template. The Dijkstra algorithm represents a fast alternative for distance mapping in individual brains, while the precision of Euclidean distances did not suffice for our purposes. In conclusion, our methodology improves the spatial precision of somatotopic mapping at 3 T. At larger field strengths improvements to even higher resolutions are anticipated.

FMRI mapping of the visual system in the mouse brain with interleaved snapshot GE-EPI

The use of functional magnetic resonance imaging (fMRI) in mice is increasingly prevalent, providing a means to non-invasively characterise functional abnormalities associated with genetic models of human diseases. The predominant stimulus used in task-based fMRI in the mouse is electrical stimulation of the paw. Task-based fMRI in mice using visual stimuli remains underexplored, despite visual stimuli being common in human fMRI studies. In this study, we map the mouse brain visual system with BOLD measurements at 9.4T using flashing light stimuli with medetomidine anaesthesia. BOLD responses were observed in the lateral geniculate nucleus, the superior colliculus and the primary visual area of the cortex, and were modulated by the flashing frequency, diffuse vs focussed light and stimulus context. Negative BOLD responses were measured in the visual cortex at 10Hz flashing frequency; but turned positive below 5Hz. In addition, the use of interleaved snapshot GE-EPI improved fMRI image quality without diminishing the temporal contrast-noise-ratio. Taken together, this work demonstrates a novel methodological protocol in which the mouse brain visual system can be non-invasively investigated using BOLD fMRI.

Marker-based ballistocardiographic artifact correction improves spike identification in EEG-fMRI of focal epilepsy patients.

Ballistocardiographic (BCG) artifacts resemble interictal epileptic discharges (IEDs) and can lead to incorrect IED identification in EEG-fMRI. This study investigates IEDs marked in EEGs corrected using information from a moiré phase tracking (MPT) marker. EEG-fMRI from 18 patients was processed with conventional methods for BCG removal, while 9 patients used a MPT marker. IEDs were marked first without ECG information. In a second review, suspicious IEDs synchronous with the BCG were discarded. After each review, an event-related fMRI analysis was performed on the marked IEDs. No difference was found in the proportion of suspicious IEDs in the 2 patient groups. However, the distribution of IED timings was significantly related to the cardiac cycle in 11 of 18 patients recorded without MPT marker, but only 2 of 9 patients with marker. In patients recorded without marker, failing to discard suspicious IEDs led to more inaccurate fMRI maps and more distant activations. BCG artifact correction based on MPT recordings allowed a more straightforward identification of IEDs that did not require ECG information in the large majority of patients. Marker-based ballistocardiographic artifact correction greatly facilitates the study of the generators of interictal discharges with EEG-fMRI.

SU‐G‐IeP1‐11: Resting‐State Fluctuation of BOLD Signal Amplitude for Mapping Cerebrovascular Reactivity in Presurgical Functional MRI

Purpose:Cerebrovascular reactivity (CVR) MRI with hypercapnia challenges, such as a breath‐hold (BH) task, has been proposed to indicate areas with neurovascular uncoupling potentials for presurgical functional MRI (fMRI). This study aimed to explore the use of resting‐state (RS) fMRI, in particular, the RS fluctuation of amplitude (RSFA) for detecting the impaired CVR and compare with BH MRI in patients with gliomas.Methods:The BH and RS fMRI from six patients as part of their presurgical fMRI studies were analyzed. Functional images were coregistered to the 3D T1‐weighted images and spatially smoothed using a 4‐mm Gaussian kernel. A band‐pass filter (0.01–0.08 Hz) was then applied to the RS time series. Temporal standard deviations of the BH and the filtered RS signal changes were computed for each voxel to indicate CVR and subsequently transformed to Z‐scores. For quantitative comparison, a region of interest (ROI) with significant CVR in the sensorimotor cortex on the contralateral side of the tumor was determined for each patient as Z‐scores greater than 50% of the local maxima. In addition, a tumor ROI was determined by referencing the T2 FLAIR and post‐contrast T1‐weighted images of each patient.Results:Significant cross‐subject correlations between the BH CVR and RSFA were found in both the sensorimotor and tumor ROIs (r=0.59, p<0.05 and r=0.83, p<0.05, respectively). Within individuals, voxel‐based analyses showed significant correlations between two methods in both ROIs in all patients. The spatial patterns of BH CVR and RSFA maps appeared similar across the brain with sparse local discrepancies.Conclusion:The RSFA derived from RS‐fMRI is a promising method for probing impaired CVR in presurgical fMRI mapping. Unlike BH, RS‐fMRI is less dependent on patient performance. In addition, with its proven relation to neural activity, RSFA of certain frequency bands has potentials to better indicate the neurovascular uncoupling.

OC-0464: Integration of fMRI and MEG functional maps into a Cyberknife planning system:a feasibility study

OC-0464: Integration of fMRI and MEG functional maps into a Cyberknife planning system:a feasibility study

A.52 - Integration of FMRI and MEG functional maps into a Cyberknife planning system: Feasibility study for motor activity localization and dose planning

A.52 - Integration of FMRI and MEG functional maps into a Cyberknife planning system: Feasibility study for motor activity localization and dose planning

Neuronal foundations of human numerical representations.

The human species has developed complex mathematical skills which likely emerge from a combination of multiple foundational abilities. One of them seems to be a preverbal capacity to extract and manipulate the numerosity of sets of objects which is shared with other species and in humans is thought to be integrated with symbolic knowledge to result in a more abstract representation of numerical concepts. For what concerns the functional neuroanatomy of this capacity, neuropsychology and functional imaging have localized key substrates of numerical processing in parietal and frontal cortex. However, traditional fMRI mapping relying on a simple subtraction approach to compare numerical and nonnumerical conditions is limited to tackle with sufficient precision and detail the issue of the underlying code for number, a question which more easily lends itself to investigation by methods with higher spatial resolution, such as neurophysiology. In recent years, progress has been made through the introduction of approaches sensitive to within-category discrimination in combination with fMRI (adaptation and multivariate pattern recognition), and the present review summarizes what these have revealed so far about the neural coding of individual numbers in the human brain, the format of these representations and parallels between human and monkey neurophysiology findings.

In Vivo Mapping of Cortical Columnar Networks in the Monkey with Focal Electrical and Optical Stimulation.

There are currently largescale efforts to understand the brain as a connection machine. However, there has been little emphasis on understanding connection patterns between functionally specific cortical columns. Here, we review development and application of focal electrical and optical stimulation methods combined with optical imaging and fMRI mapping in the non-human primate. These new approaches, when applied systematically on a large scale, will elucidate functionally specific intra-areal and inter-areal network connection patterns. Such functionally specific network data can provide accurate views of brain network topology.

Diversity of sharp-wave–ripple LFP signatures reveals differentiated brain-wide dynamical events

Sharp-wave-ripple (SPW-R) complexes are believed to mediate memory reactivation, transfer, and consolidation. However, their underlying neuronal dynamics at multiple scales remains poorly understood. Using concurrent hippocampal local field potential (LFP) recordings and functional MRI (fMRI), we study local changes in neuronal activity during SPW-R episodes and their brain-wide correlates. Analysis of the temporal alignment between SPW and ripple components reveals well-differentiated SPW-R subtypes in the CA1 LFP. SPW-R-triggered fMRI maps show that ripples aligned to the positive peak of their SPWs have enhanced neocortical metabolic up-regulation. In contrast, ripples occurring at the trough of their SPWs relate to weaker neocortical up-regulation and absent subcortical down-regulation, indicating differentiated involvement of neuromodulatory pathways in the ripple phenomenon mediated by long-range interactions. To our knowledge, this study provides the first evidence for the existence of SPW-R subtypes with differentiated CA1 activity and metabolic correlates in related brain areas, possibly serving different memory functions.

FMRI mapping of microvascular function and its implications in CBF regulation

fMRI mapping of microvascular function and its implications in CBF regulation

Quantifying randomness in real networks.

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

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.

EEG source localization constrained by time varying fMRI.

A novel approach for Electroencephalogram (EEG) and functional Magnetic Resonance Imaging (fMRI) integration analysis was developed, specifically designed to explore the spatial and temporal details of the "sequential multi-event-related potential" type of neural activities. The approach utilizes the high temporal resolution nature of EEG to compute a current density mapping of the cortical activity, informed by the high spatial resolution fMRI in a time-variant, spatially selective manner. This method was implemented in the analysis of an EEG/fMRI study on motor activation in responses to a visual stimulus that evoked an emotional response. The processed windowed EEG signals were analyzed to select the temporally relevant partial fMRI mapping, which in turn was used to inform EEG source localization calculation. The results were compared against traditional fMRI-informed EEG approaches to demonstrate the spatiotemporal variant fMRI constraints feature as well as the performance of the developed method.

Functional MRI of visual responses in the awake, behaving marmoset

The visual brain is composed of interconnected subcortical and cortical structures that receive and process image information originating in the retina. The visual system of nonhuman primates, in particular macaques, has been studied in great detail in order to elucidate principles of human sensation and perception. The common marmoset (Callithrix jacchus) is a small New World monkey of growing interest as a primate model for neuroscience. Marmosets have advantages over macaques because of their small size, lissencephalic cortex, and growing potential for viral and genetic manipulations. Previous anatomical studies and electrophysiological recordings in anesthetized marmosets have shown that this species’ cortical visual hierarchy closely resembles that of other primates, including humans. Until now, however, there have been no attempts to systematically study visual responses throughout the marmoset brain using fMRI. Here we show that awake marmosets readily learn to carry out a simple visual task inside the bore of an MRI scanner during functional mapping experiments. Functional scanning at 500μm in-plane resolution in a 30cm horizontal bore at 7T revealed robust positive blood oxygenation level-dependent (BOLD) fMRI responses to visual stimuli throughout visual cortex and associated subcortical areas. Nonvisual sensory areas showed negative contrasts to visual stimuli compared to the fixation dot only baseline. Structured images of objects and faces led to stronger responses than scrambled control images at stages beyond early visual cortex. Our study establishes fMRI mapping of visual responses in awake, behaving marmosets as a straightforward and valuable tool for assessing the functional organization of the primate brain at high resolution.

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

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. 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. 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. 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.

Mapping language area in the frontal lobe of the left-dominant hemisphere with high gamma electrocorticography

Abstract Localization of the language-related brain regions is a critical yet challenging issue for neurosurgery. In the present study, investigation of the language-related brain regions were carried out in fourteen patients with a left dominant hemisphere and left frontal or temporal epilepsy using high gamma electrocorticography (ECoG). The patients participated in an ECoG-based language mapping procedure, in which they were required to perform both a word-repeating task and a picture-naming task. Electrodes with significant high gamma (60–140 Hz) responses were regarded as language positive sites. fMRI and electrical cortical stimulation (ECS) with similar language tasks were also performed for comparison. In these fourteen patients, at total of 60, 81, and 105 language positive electrodes were identified with ECS, ECoG, and fMRI, respectively. Using the ECS mapping results as reference, the sensitivity and specificity of the ECoG mapping were 83.2 ± 4.5% and 97.2 ± 0.5%. These results were significantly better than fMRI mapping, which showed a sensitivity of 61.6 ± 6.5% and a specificity of 93.8 ± 0.8%. ECoG mapping was also a better predictor of post-surgery aphasia than fMRI (75% vs. 50%, for a total number of six patients with post-surgery aphasia). If excluding the isolated ECoG positive sites with no neighboring activations, the aphasia prediction accuracy by ECoG can be improved to 100% (six out of six patients). Our results suggest high gamma ECoG mapping as a useful tool for language function protection in epilepsy treatment.

Between-hand difference in ipsilateral deactivation is associated with hand lateralization: fMRI mapping of 284 volunteers balanced for handedness.

In right-handers (RH), an increase in the pace of dominant hand movement results in increased ipsilateral deactivation of the primary motor cortex (M1). By contrast, an increase in non-dominant hand movement frequency is associated with reduced ipsilateral deactivation. This pattern suggests that inhibitory processes support right hand dominance in right-handers and raises the issues of whether this phenomenon also supports left hand preference in left-handers (LH), and/or whether it relates to asymmetry of manual ability in either group. Thanks to the BIL&GIN, a database dedicated to the investigation of hemispheric specialization (HS), we studied the variation in M1 activity during right and left finger tapping tasks (FTT) in a sample of 284 healthy participants balanced for handedness. An M1 fMRI localizer was defined for each participant as an 8 mm diameter sphere centered on the motor activation peak. RH exhibited significantly larger deactivation of the ipsilateral M1 when moving their dominant hand than their non-dominant hand. In contrast, LH exhibited comparable ipsilateral M1 deactivation during either hand movement, reflecting a bilateral cortical specialization. This pattern is likely related to left-handers’ good performances with their right hand and consequent lower asymmetry in manual ability compared with RH. Finally, inter-individual analyses over the whole sample demonstrated that the larger the difference in manual skill across hands, the larger the difference in ipsilateral deactivation. Overall, we propose that difference in ipsilateral deactivation is a marker of difference in manual ability asymmetry reflecting differences in the strength of transcallosal inhibition when a given hand is moving.

Functional MRI compliance in children with attention deficit hyperactivity disorder.

We aimed to test the effect of prescan training and orientation in functional magnetic resonance imaging (fMRI) in children with attention deficit hyperactivity disorder (ADHD) and to investigate whether fMRI compliance was modified by state anxiety. Subjects included 77 males aged 6-12 years; there were 53 patients in the ADHD group and 24 participants in the healthy control group. Exclusion criteria included neurological and/or psychiatric comorbidities (other than ADHD), the use of psychoactive drugs, and an intelligence quotient outside the normal range. Children were individually subjected to prescan orientation and training. Data were acquired using a 1.5 Tesla scanner and an 8-channel head coil. Functional scans were performed using a standard neurocognitive task. The neurocognitive task led to reliable fMRI maps. Compliance was not significantly different between ADHD and control groups based on success, failure, and repetition rates of fMRI. Compliance of ADHD patients with extreme levels of anxiety was also not significantly different. The fMRI compliance of ADHD children is typically lower than that of healthy children. However, compliance can be increased to the level of age-matched healthy control children by addressing concerns about the technical and procedural aspects of fMRI, providing orientation programs, and performing on-task training. In patients thus trained, compliance does not change with the level of state anxiety suggesting that the anxiety hypothesis of fMRI compliance is not supported.