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Open accessJournal ArticleDOI: 10.3390/CANCERS13051116

The Frontal Aslant Tract and Supplementary Motor Area Syndrome: Moving towards a Connectomic Initiation Axis

05 Mar 2021-Cancers (Multidisciplinary Digital Publishing Institute)-Vol. 13, Iss: 5, pp 1116
Abstract: Connectomics is the use of big data to map the brain's neural infrastructure; employing such technology to improve surgical planning may improve neuro-oncological outcomes. Supplementary motor area (SMA) syndrome is a well-known complication of medial frontal lobe surgery. The 'localizationist' view posits that damage to the posteromedial bank of the superior frontal gyrus (SFG) is the basis of SMA syndrome. However, surgical experience within the frontal lobe suggests that this is not entirely true. In a study on n = 45 patients undergoing frontal lobe glioma surgery, we sought to determine if a 'connectomic' or network-based approach can decrease the likelihood of SMA syndrome. The control group (n = 23) underwent surgery avoiding the posterior bank of the SFG while the treatment group (n = 22) underwent mapping of the SMA network and Frontal Aslant Tract (FAT) using network analysis and DTI tractography. Patient outcomes were assessed post operatively and in subsequent follow-ups. Fewer patients (8.3%) in the treatment group experienced transient SMA syndrome compared to the control group (47%) (p = 0.003). There was no statistically significant difference found between the occurrence of permanent SMA syndrome between control and treatment groups. We demonstrate how utilizing tractography and a network-based approach decreases the likelihood of transient SMA syndrome during medial frontal glioma surgery. We found that not transecting the FAT and the SMA system improved outcomes which may be important for functional outcomes and patient quality of life.

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Topics: SMA* (61%), Superior frontal gyrus (60%), Supplementary motor area (60%) ... show more
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8 results found


Journal ArticleDOI: 10.1016/J.WNEU.2021.03.045
17 Mar 2021-World Neurosurgery
Abstract: Background The middle frontal gyrus (MFG) is involved in attention, working memory, and language-related processing. A detailed understanding of the subcortical white matter tracts connected within the MFG can facilitate improved navigation of white matter lesions in and around this gyrus and explain the postoperative morbidity after surgery. We aimed to characterize the fiber tracts within the MFG according to their connection to neuroanatomic structures through the use of diffusion spectrum imaging-based fiber tractography and validate the findings by gross anatomic dissection for qualitative visual agreement. Methods Tractography analysis was completed using diffusion imaging data from 10 healthy, adult subjects enrolled in the Human Connectome Project. We assessed the MFG as a whole component according to its fiber connectivity with other neural regions. Mapping was completed on all tracts within both hemispheres, with the resultant tract volumes used to calculate a lateralization index. A modified Klingler technique was used on 10 postmortem dissections to demonstrate the location and orientation of the major tracts. Results Two major connections of the MFG were identified: the superior longitudinal fasciculus, which connects the MFG to parts of the inferior parietal lobule, posterior temporal lobe, and lateral occipital cortex; and the inferior fronto-occipital fasciculus, which connected the MFG to the lingual gyrus and cuneus. Intra- and intergyral short association, U-shaped fibers were also identified. Conclusions Subcortical white matter pathways integrated within the MFG include the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. The MFG is implicated in a variety of tasks involving attention and memory, making it an important cortical region. The postoperative neurologic outcomes related to surgery in and around the MFG could be clarified in the context of the anatomy of the fiber bundles highlighted in the present study.

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Topics: Superior longitudinal fasciculus (61%), Middle frontal gyrus (55%), Lingual gyrus (55%) ... show more

3 Citations


Open accessJournal ArticleDOI: 10.3389/FNEUR.2021.711646
Abstract: The surgical management of brain tumors is based on the principle that the extent of resection improves patient outcomes. Traditionally, neurosurgeons have considered that lesions in "non-eloquent" cerebrum can be more aggressively surgically managed compared to lesions in "eloquent" regions with more known functional relevance. Furthermore, advancements in multimodal imaging technologies have improved our ability to extend the rate of resection while minimizing the risk of inducing new neurologic deficits, together referred to as the "onco-functional balance." However, despite the common utilization of invasive techniques such as cortical mapping to identify eloquent tissue responsible for language and motor functions, glioma patients continue to present post-operatively with poor cognitive morbidity in higher-order functions. Such observations are likely related to the difficulty in interpreting the highly-dimensional information these technologies present to us regarding cognition in addition to our classically poor understanding of the functional and structural neuroanatomy underlying complex higher-order cognitive functions. Furthermore, reduction of the brain into isolated cortical regions without consideration of the complex, interacting brain networks which these regions function within to subserve higher-order cognition inherently prevents our successful navigation of true eloquent and non-eloquent cerebrum. Fortunately, recent large-scale movements in the neuroscience community, such as the Human Connectome Project (HCP), have provided updated neural data detailing the many intricate macroscopic connections between cortical regions which integrate and process the information underlying complex human behavior within a brain "connectome." Connectomic data can provide us better maps on how to understand convoluted cortical and subcortical relationships between tumor and human cerebrum such that neurosurgeons can begin to make more informed decisions during surgery to maximize the onco-functional balance. However, connectome-based neurosurgery and related applications for neurorehabilitation are relatively nascent and require further work moving forward to optimize our ability to add highly valuable connectomic data to our surgical armamentarium. In this manuscript, we review four concepts with detailed examples which will help us better understand post-operative cognitive outcomes and provide a guide for how to utilize connectomics to reduce cognitive morbidity following cerebral surgery.

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Topics: Connectome (59%), Connectomics (53%), Cognition (51%)

2 Citations


Journal ArticleDOI: 10.1016/J.WNEU.2021.04.050
21 Apr 2021-World Neurosurgery
Abstract: Background The medial occipital lobe, composed of the lingual gyrus and cuneus, is necessary for both basic and higher level visual processing. It is also known to facilitate cross-modal, nonvisual functions, such as linguistic processing and verbal memory, after the loss of the visual senses. A detailed cortical model elucidating the white matter connectivity associated with this area could improve our understanding of the interacting brain networks that underlie complex human processes and postoperative outcomes related to vision and language. Methods Generalized q-sampling imaging tractography, validated by gross anatomic dissection for qualitative visual agreement, was performed on 10 healthy adult controls obtained from the Human Connectome Project. Results Major white matter connections were identified by tractography and validated by gross dissection, which connected the medial occipital lobe with itself and the adjacent cortices, especially the temporal lobe. The short- and long-range connections identified consisted mainly of U-shaped association fibers, intracuneal fibers, and inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, middle longitudinal fasciculus, and lingual–fusiform connections. Conclusions The medial occipital lobe is an extremely interconnected system, supporting its ability to perform coordinated basic visual processing, but also serves as a center for many long-range association fibers, supporting its importance in nonvisual functions, such as language and memory. The presented data represent clinically actionable anatomic information that can be used in multimodal navigation of white matter lesions in the medial occipital lobe to prevent neurologic deficits and improve patients' quality of life after cerebral surgery.

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Topics: Inferior longitudinal fasciculus (70%), Occipital lobe (66%), Lingual gyrus (63%) ... show more

1 Citations


Open accessJournal ArticleDOI: 10.1002/BRB3.2180
17 Jun 2021-Brain and behavior
Abstract: Background Transcranial magnetic stimulation is a noninvasive treatment used to modulate cortical excitability. Its use over the last two decades has expanded, ranging from psychiatric disorders to traumatic brain injury and poststroke rehabilitation. Objectives We present the case of a 59-year-old male patient who presented in a decreased state of consciousness due to a right frontal glioblastoma, wherein his state was not improved by a successful surgery and could not be explained by any other condition. Due to his poor prognosis, we examine the benefits of receiving transcranial magnetic stimulation treatment to improve his akinetic mutism. Methods We utilized independent component analysis with resting-state functional magnetic resonance imaging (rsfMRI) to better understand his cortical functionality. The imaging suggested absence of the default mode network (DMN). The patient underwent five sessions of navigated intermittent theta burst stimulation to the ipsilesional inferior parietal lobule and inferior frontal gyrus, with the aim of improving his default mode network functionality. Results No other treatments resulted in an improvement of this patient's condition; however, 3 weeks following transcranial magnetic stimulation treatment, the patient was more alert and interactive, and his follow-up rsfMRI scan demonstrated a partially intact default mode network. Conclusion This case raises important questions regarding the clinical utility of transcranial magnetic stimulation to improve the connectivity of important cerebral networks and subsequent related functional recovery.

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Topics: Transcranial magnetic stimulation (56%), Default mode network (55%), Akinetic mutism (54%) ... show more

1 Citations


Open accessJournal ArticleDOI: 10.1007/S11682-021-00529-1
Abstract: Purpose Advances in neuroimaging have provided an understanding of the precuneus’(PCu) involvement in functions such as visuospatial processing and cognition. While the PCu has been previously determined to be apart of a higher-order default mode network (DMN), recent studies suggest the presence of possible dissociations from this model in order to explain the diverse functions the PCu facilitates, such as in episodic memory. An improved structural model of the white-matter anatomy of the PCu can demonstrate its unique cerebral connections with adjacent regions which can provide additional clarity on its role in integrating information across higher-order cerebral networks like the DMN. Furthermore, this information can provide clinically actionable anatomic information that can support clinical decision making to improve neurologic outcomes such as during cerebral surgery. Here, we sought to derive the relationship between the precuneus and underlying major white-mater bundles by characterizing its macroscopic connectivity. Methods Structural tractography was performed on twenty healthy adult controls from the Human Connectome Project (HCP) utilizing previously demonstrated methodology. All precuneus connections were mapped in both cerebral hemispheres and inter-hemispheric differences in resultant tract volumes were compared with an unpaired, corrected Mann–Whitney U test and a laterality index (LI) was completed. Ten postmortem dissections were then performed to serve as ground truth by using a modified Klingler technique with careful preservation of relevant white matter bundles. Results The precuneus is a heterogenous cortical region with five major types of connections that were present bilaterally. (1) Short association fibers connect the gyri of the precuneus and connect the precuneus to the superior parietal lobule and the occipital cortex. (2) Four distinct parts of the cingulum bundle connect the precuneus to the frontal lobe and the temporal lobe. (3) The middle longitudinal fasciculus from the precuneus connects to the superior temporal gyrus and the dorsolateral temporal pole. (4) Parietopontine fibers travel as part of the corticopontine fibers to connect the precuneus to pontine regions. (5) An extensive commissural bundle connects the precuneus bilaterally. Conclusion We present a summary of the anatomic connections of the precuneus as part of an effort to understand the function of the precuneus and highlight key white-matter pathways to inform surgical decision-making. Our findings support recent models suggesting unique fiber connections integrating at the precuneus which may suggest finer subsystems of the DMN or unique networks, but further study is necessary to refine our model in greater quantitative detail.

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43 results found


Open accessJournal ArticleDOI: 10.1002/HBM.20718
Abstract: A widely used technique for coordinate-based meta-analyses of neuroimaging data is activation likelihood estimation (ALE). ALE assesses the overlap between foci based on modeling them as probability distributions centered at the respective coordinates. In this Human Brain Project/Neuroinformatics research, the authors present a revised ALE algorithm addressing drawbacks associated with former implementations. The first change pertains to the size of the probability distributions, which had to be specified by the used. To provide a more principled solution, the authors analyzed fMRI data of 21 subjects, each normalized into MNI space using nine different approaches. This analysis provided quantitative estimates of between-subject and between-template variability for 16 functionally defined regions, which were then used to explicitly model the spatial uncertainty associated with each reported coordinate. Secondly, instead of testing for an above-chance clustering between foci, the revised algorithm assesses above-chance clustering between experiments. The spatial relationship between foci in a given experiment is now assumed to be fixed and ALE results are assessed against a null-distribution of random spatial association between experiments. Critically, this modification entails a change from fixed- to random-effects inference in ALE analysis allowing generalization of the results to the entire population of studies analyzed. By comparative analysis of real and simulated data, the authors showed that the revised ALE-algorithm overcomes conceptual problems of former meta-analyses and increases the specificity of the ensuing results without loosing the sensitivity of the original approach. It may thus provide a methodologically improved tool for coordinate-based meta-analyses on functional imaging data.

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1,359 Citations


Open accessJournal ArticleDOI: 10.1016/J.NEUROIMAGE.2011.09.017
Simon B. Eickhoff1, Danilo Bzdok1, Danilo Bzdok2, Angela R. Laird3  +2 moreInstitutions (4)
01 Feb 2012-NeuroImage
Abstract: A widely used technique for coordinate-based meta-analysis of neuroimaging data is activation likelihood estimation (ALE), which determines the convergence of foci reported from different experiments. ALE analysis involves modelling these foci as probability distributions whose width is based on empirical estimates of the spatial uncertainty due to the between-subject and between-template variability of neuroimaging data. ALE results are assessed against a null-distribution of random spatial association between experiments, resulting in random-effects inference. In the present revision of this algorithm, we address two remaining drawbacks of the previous algorithm. First, the assessment of spatial association between experiments was based on a highly time-consuming permutation test, which nevertheless entailed the danger of underestimating the right tail of the null-distribution. In this report, we outline how this previous approach may be replaced by a faster and more precise analytical method. Second, the previously applied correction procedure, i.e. controlling the false discovery rate (FDR), is supplemented by new approaches for correcting the family-wise error rate and the cluster-level significance. The different alternatives for drawing inference on meta-analytic results are evaluated on an exemplary dataset on face perception as well as discussed with respect to their methodological limitations and advantages. In summary, we thus replaced the previous permutation algorithm with a faster and more rigorous analytical solution for the null-distribution and comprehensively address the issue of multiple-comparison corrections. The proposed revision of the ALE-algorithm should provide an improved tool for conducting coordinate-based meta-analyses on functional imaging data.

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Topics: Inference (51%)

901 Citations


Open accessJournal ArticleDOI: 10.1002/HBM.21186
Abstract: Activation Likelihood Estimation (ALE) is an objective, quantitative technique for coordinate- based meta-analysis (CBMA) of neuroimaging results that has been validated for a variety of uses. Stepwise modifications have improved ALE's theoretical and statistical rigor since its introduction. Here, we evaluate two avenues to further optimize ALE. First, we demonstrate that the maximum con- tribution of an experiment makes to an ALE map is related to the number of foci it reports and their proximity. We present a modified ALE algorithm that eliminates these within-experiment effects. How- ever, we show that these effects only account for 2-3% of cumulative ALE values, and removing them has little impact on thresholded ALE maps. Next, we present an alternate organizational approach to datasets that prevents subject groups with multiple experiments in a dataset from influencing ALE val- ues more than others. This modification decreases cumulative ALE values by 7-9%, changes the rela- tive magnitude of some clusters, and reduces cluster extents. Overall, differences between results of the standard approach and these new methods were small. This finding validates previous ALE reports against concerns that they were driven by within-experiment or within-group effects. We sug- gest that the modified ALE algorithm is theoretically advantageous compared with the current algo- rithm, and that the alternate organization of datasets is the most conservative approach for typical ALE analyses and other CBMA methods. Combining the two modifications minimizes both within- experiment and within-group effects, optimizing the degree to which ALE values represent concord- ance of findings across independent reports. Hum Brain Mapp 33:1-13, 2012. V C 2011 Wiley Periodicals, Inc.

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755 Citations


Journal ArticleDOI: 10.1109/TMI.2010.2045126
Abstract: Based on the Fourier transform relation between diffusion magnetic resonance (MR) signals and the underlying diffusion displacement, a new relation is derived to estimate the spin distribution function (SDF) directly from diffusion MR signals. This relation leads to an imaging method called generalized q-sampling imaging (GQI), which can obtain the SDF from the shell sampling scheme used in q-ball imaging (QBI) or the grid sampling scheme used in diffusion spectrum imaging (DSI). The accuracy of GQI was evaluated by a simulation study and an in vivo experiment in comparison with QBI and DSI. The simulation results showed that the accuracy of GQI was comparable to that of QBI and DSI. The simulation study of GQI also showed that an anisotropy index, named quantitative anisotropy, was correlated with the volume fraction of the resolved fiber component. The in vivo images of GQI demonstrated that SDF patterns were similar to the ODFs reconstructed by QBI or DSI. The tractography generated from GQI was also similar to those generated from QBI and DSI. In conclusion, the proposed GQI method can be applied to grid or shell sampling schemes and can provide directional and quantitative information about the crossing fibers.

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565 Citations


Journal ArticleDOI: 10.1385/NI:3:1:065
01 Jan 2005-Neuroinformatics
Abstract: Human brain mapping is an experimental discipline that establishes structure-function correspondences in the brain through the combined application of experimental psychology, human neuroscience, and noninvasive neuroimaging. A deep and diverse literature on the functional organization of the human brain is emerging, which has pushed neuroimaging squarely into the scientific mainstream. Because of this rapid growth, there is a great need to effectively collect and synthesize the body of literature in this field. The BrainMap database was created in response to this need as an electronic environment for modeling the human brain through quantitative meta-analysis of the brain mapping literature. BrainMap was originally conceived in 1987 and has received continuous funding from 1988 to 2004. During this time, BrainMap has consistently evolved to meet the challenges of an ever-changing field and continues to strive toward higher levels of applicability. In this article, we discuss BrainMap's structure and utility, and relate its progress and development as a neuroinformatics tool.

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436 Citations