Figures
Figure 1
fMRI activations and lateralization indices (LI) for Patient 1 and controls. (A) Picture naming fMRI activation maps of controls, Patient 1, and Patient 1 versus controls (statistical differences). Activation maps were presented at p < 0.05-corrected thresholds. (B) Lateralization indices (LI) for Patient 1 and the control group, based on t values (iterations). LI was computed on the basis of the number of activated voxels in the frontal region, reflecting the hemispheric specialization for language; the LI-tool implemented in SPM was used. In each graph. the red area indicates positive LI (from +0.2 to +1) and left hemispheric specialization, whereas the blue area indicates negative LI (from -0.2 to -1) and right hemispheric specialization; the green area pertains to the LI between -0.2 and +0.2 and indicates bilateral representation of language. The calculation of LI was based on the method described by Seghier (Baciu et al. , 2005; Seghier, 2008 ).
Figure 1
Figure 2
Multimodal data obtained in Patient 1. Cognitive scores, functional activation (projected in red on the anatomical normalized image for Patient 1, p FWE corrected ) and impaired white matter bundles based on the FA values (projected in blue) are represented. Regarding neuropsychological results, raw data as well as standardized scores (in brackets), are indicated. Pathological scores are highlighted in bold and red and correspond to a p value ≤ 0.05. ILF: inferior longitudinal fasciculus; Unc: uncinate fasciculus; ct: percentile rank; σ: standard deviation to the norm.
Figure 2
Figure 3
fMRI activations and lateralization indices (LI) for Patient 2 and controls. (A) Picture naming fMRI activation maps of controls, Patient 2, and Patient 2 versus controls (statistical differences). Activation maps were presented at p <0.05-corrected thresholds. (B) Lateralization indices (LI) for Patient 2 and the control group, based on t values (iterations). LI was computed on the basis of the number of activated voxels in the frontal region, reflecting the hemispheric specialization for language; the LI-tool implemented in SPM was used. For each graph, the red region indicates positive LI (from +0.2 to +1) and left hemispheric specialization; the blue region indicates negative LI (from -0.2 to -1) and right hemispheric specialization; the green region indicates LI between -0.2 and +0.2 and bilateral representation of language. The calculation of LI is based on the method described by Seghier (Baciu et al. , 2005; Seghier, 2008 ).
Figure 3
Figure 4
Multimodal data for Patient 2.Cognitive scores, functional activation (projected in red on the anatomical normalized image for Patient 2; p FWE corrected ) and impaired white matter bundles based on the FA values (projected in blue) are represented. Regarding neuropsychological results, raw data as well as standardized scores (in brackets) are indicated. Pathological scores are highlighted in bold and red and correspond to a value of p ≤ 0.05. Unc: uncinate fasciculus; BCC: body of the corpus callosum; Arc: arcuate fasciculus; ct: percentile rank; σ: standard deviation to the norm.
Figure 4
Tables
Authors
1 Univ. Grenoble Alpes, CNRS LPNC UMR 5105, Grenoble
2 Univ. Grenoble Alpes, Grenoble Institute of Neuroscience Team “Neuroimagerie fonctionnelle et perfusion cérébrale” & UMS IRMaGe CHU Grenoble
3 Univ. Grenoble Alpes, Univ. Savoie Mont-Blanc, Chambéry
4 Univ. Grenoble Alpes, Grenoble Institute of Neuroscience Team “Synchronisation et modulation des réseaux neuronaux dans l’épilepsie” & Neurology Department, Grenoble
5 Aix-Marseille Université, Institut des Neurosciences des Systèmes, Marseille
6 APHM, Hôpital de la Timone, Service de Neurophysiologie Clinique, Marseille, France
* Correspondence: Monica Baciu
Laboratoire de psychologie et neurocognition,
UMR CNRS 5105,
Université Grenoble Alpes
BP 47 38040 Grenoble Cedex 09, France
Aims We report two patients suffering from drug-resistant temporal lobe epilepsy to show how their neuroplasticity can be apprehended using a multimodal, integrative and clinically relevant approach.