Anatomically informed interpolation of fMRI data on the cortical surface

Grova, Christophe; Makni, Salima; Flandin, Guillaume; Ciuciu, Philippe; Gotman, Jean; Poline, Jean‐Baptiste

doi:10.1016/j.neuroimage.2006.02.049

Cited by 43 publications

(52 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…First, the interpolation effects related to the projection of 3-D volumes onto the cortical surface is a major challenge (Grova et al, 2006;Operto et al, 2008). Second, smoothing leads to spatial inaccuracy and artificial shift of activations, be it using conventional volume-based approaches (e.g., SPM) or CSM (Jo et al, 2007(Jo et al, , 2008Mikl et al, 2008).…”

Section: Comparison With Other Anatomically Constrained Methodsmentioning

confidence: 99%

Anatomically-adapted graph wavelets for improved group-level fMRI activation mapping

et al. 2015

View full text Add to dashboard Cite

A graph based framework for fMRI brain activation mapping is presented. The approach exploits the spectral graph wavelet transform (SGWT) for the purpose of defining an advanced multi-resolutional spatial transformation for fMRI data. The framework extends wavelet based SPM (WSPM), which is an alternative to the conventional approach of statistical parametric mapping (SPM), and is developed specifically for group-level analysis. We present a novel procedure for constructing brain graphs, with subgraphs that separately encode the structural connectivity of the cerebral and cerebellar gray matter (GM), and address the inter-subject GM variability by the use of template GM representations. Graph wavelets tailored to the convoluted boundaries of GM are then constructed as a means to implement a GM-based spatial transformation on fMRI data. The proposed approach is evaluated using real as well as semi-synthetic multi-subject data. Compared to SPM and WSPM using classical wavelets, the proposed approach shows superior type-I error control. The results on real data suggest a higher detection sensitivity as well as the capability to capture subtle, connected patterns of brain activity.

show abstract

Section: Comparison With Other Anatomically Constrained Methodsmentioning

confidence: 99%

Anatomically-adapted graph wavelets for improved group-level fMRI activation mapping

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Analysis involved a multiple HRFs approach (Bagshaw et al, 2004) to take into account the temporal variability of BOLD responses to spikes and to increase detection sensitivity. For each HRF, every cluster showing a significant BOLD response was selected using a cluster size test (Worsley et al, 2002) and its t-values were interpolated onto the cortical surface (Grova et al, 2006a). This interpolation method was designed to take into account the local morphology of the cortical surface and the distributed nature of the hemodynamic response.…”

Section: A New Methodology To Assess Eeg-fmri Concordance During Epilmentioning

confidence: 99%

“…We used the method recently proposed in Grova et al (2006a): each vertex of the cortical surface was associated to an interpolation kernel, i.e., a small local volume of interest, over which volumic fMRI t-values were integrated. The value resulting from this integration was associated to the corresponding vertex of the cortical surface.…”

Section: Fmri Preprocessingmentioning

confidence: 99%

“…Our overall objective was to demonstrate that the underlying structure of spike generators may be organized as a distributed network, where one can detect and classify concordant and discordant EEG sources and fMRI responses. Quantification of "EEG-fMRI concordance" remains a difficult task and the issues are twofold: (i) EEG sources and fMRI responses should be quantified on the same spatial support, such as the cortical surface, and appropriate comparison metrics are required; to address this issue, fMRI clusters showing a significant BOLD response to interictal spikes assessed by standard event-related analysis (Bagshaw et al, 2004) were selected and interpolated onto the cortical surface (Grova et al, 2006a) to be compared with EEG source localization results. (ii) As an ill-posed inverse problem, EEG source localization does not admit any unique solution, unless prior information is added.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes

et al. 2008

Self Cite

View full text Add to dashboard Cite

In order to analyze where epileptic spikes are generated, we assessed the level of concordance between EEG source localization using distributed source models and simultaneous EEG-fMRI which measures the hemodynamic correlates of EEG activity. Data to be compared were first estimated on the same cortical surface and two comparison strategies were used: (1) MEMconcordance: a comparison between EEG sources localized with the Maximum Entropy on the Mean (MEM) method and fMRI clusters showing a significant hemodynamic response. Minimal geodesic distances between local extrema and overlap measurements between spatial extents of EEG sources and fMRI clusters were used to quantify MEM-concordance. (2) fMRI-relevance: estimation of the fMRI-relevance index α quantifying if sources located in an fMRI cluster could explain some scalp EEG data, when this fMRI cluster was used to constrain the EEG inverse problem. Combining MEM-concordance and fMRI-relevance (α) indexes, each fMRI cluster showing a significant hemodynamic response (p <0.05 corrected) was classified according to its concordance with EEG data. Nine patients with focal epilepsy who underwent EEG-fMRI examination followed by EEG recording outside the scanner were selected for this study. Among the 62 fMRI clusters analyzed (7 patients), 15 (24%) found in 6 patients were highly concordant with EEG according to both MEM-concordance and fMRI-relevance. EEG concordance was found for 5 clusters (8%) according to α only, suggesting sources missed by the MEM. No concordance with EEG was found for 30 clusters (48%) and for 10 clusters (16%) α was significantly negative, suggesting EEG-fMRI discordance. We proposed two complementary strategies to assess and classify EEG-fMRI concordance. We showed that for most patients, part of the hemodynamic response to spikes was highly concordant with EEG sources, whereas other fMRI clusters in response to the same spikes were found distant or discordant with EEG sources.Corresponding

show abstract

“…The event-related fields were used to perform source localization, with the maximum entropy on the mean method (MEM : Amblard, Lapalme, & Lina, 2004;Grova, et al, 2006). This method is a cortically-constrained distributed source-localization approach.…”

Section: Insert Figure 1 Herementioning

confidence: 99%

Neural changes associated with semantic processing in healthy aging despite intact behavioral performance

et al. 2015

View full text Add to dashboard Cite

Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level.

show abstract

Anatomically informed interpolation of fMRI data on the cortical surface

Cited by 43 publications

References 16 publications

Anatomically-adapted graph wavelets for improved group-level fMRI activation mapping

Anatomically-adapted graph wavelets for improved group-level fMRI activation mapping

Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes

Neural changes associated with semantic processing in healthy aging despite intact behavioral performance

Contact Info

Product

Resources

About