In clinical practice the size of the lesion often does not correlate with the clinical deficits. It is probable that the difference is due to functional topography and connectivity in whole brain level. In this study, we aim to understand the brain connectivity in patients without deficits by comparing them with a group of clinically matched patients with clinical deficits.

24 patients with high grade glioma located in the left frontal lobe association with motor or brocas cortex were retrospectively selected for the study. There were 8 patients with deficits (moderate motor and language deficits) (Tumor-D) (Age: 28.86 ± 10.07years) and 16 patients without deficits (Tumor-WD) (Age: 29.06 ± 9.61 years). They were also compared with 24 age, gender and education matched healthy controls. The tumour size, location, grade of tumour, duration of lesion and other clinical characteristics were not significantly different between the two groups. 24 age, gender and education matched healthy controls were recruited for comparison. We acquired resting-state fMRI using a 3T scanner (Skyra, Siemens, Germany) using echo Echo-Planar Images with following parameters: 185 volumes, TR 3000ms, TE 35ms, 36 slices, voxel size-3 x 3 x 4mm. We also acquired T1-MPRAGE sequence for anatomical information (with the voxel size 1 x 1 x 1 mm, 192 x 192 x 256 matrix). The MRI imaging pre-processing was performed (realignment, normalization to MNI-152 standard space, smoothing with Gaussian kernel of FWHM 6mm, segmentation of the structural data, motion correction using Friston’s 24 motion parameter model regression, band-pas filtering to 0.009–0.09 Hz) and the fMRI data were segmented into 132 anatomic regions of interest using cortical and subcortical of FSL-Harvard-Oxford atlas (106 ROIs), Cerebellar parcellation from AAL Atlas (26 ROIs). After segmenting the fMRI data, a seed-to-voxel functional connectivity was performed by computing the temporal correlation between the BOLD signals to create a correlation matrix showing connectivity from the seed region to all other voxels in the brain by using the CONN toolbox [1,2]. The connectivity maps were generated using ROIs-to-voxel Fisher’s-r to Z-transformed connectivity maps using bivariate correlation. Random-effects modelling was used to look for group level connectivity differences. Between group differences were estimated using ANOVA, between Tumor-D, Tumor-WD and controls, thresholded above a cluster-level FDR corrected p-value< 0.001.

Tumor-D had diffuse decreased connectivity in many regions of the brain also involving the sensory motor area (SMN) in comparison with Tumor-WD and Control. Tumor-WD had decreased connectivity only involving the SMN with increased connectivity in medial frontal, thalamus, anterior and posterior cingulate regions.Understanding of brain function in patients with glioma, especially when lesion is located in the eloquent area is crucial in neuro-oncology for preoperative planning to choose the best surgical/therapeutic approach and also to predict the surgical outcome. The deterioration of existing deficits or newly developed motor and cognitive deficits does not only reduces the quality of life but also reduces overall survival of the affected patients independent of the extent of resection and the adjuvant therapy. For achieving this, a detailed knowledge of the functional topography and connectivity in whole brain level might be ideal. Studies have looked at the brain functional localisation of sensory motor network and language network using various modalities such as task related functional MRI, resting state functional MRI, DTI and SPECT. [3,4,5,6]. Brain functional network and there connectivity is found altered in gliomas [7]. Here, we found that patients with high grade gliomas without deficits shows increased connectivity in several non-eloquent areas compared to those with deficits and also with healthy controls, which could indicate a compensatory mechanism - so called brain plasticity. We find that the high grade glioma patients without motor or language deficits had widespread compensatory hyperconnectivity of the brain in comparison with patients with deficits. Clinical manifestation of focal deficit might also depend on the whole brain functional connectivity apart from the anatomical location.