Exploring the neural basis of non-invasive prehabilitation in brain tumour patients: An fMRI-based case report of language network plasticity.

Primary brain neoplasms are associated with elevated mortality and morbidity rates. Brain tumour surgery aims to achieve maximal tumour resection while minimizing damage to healthy brain tissue. Research on Neuromodulation Induced Cortical Prehabilitation (NICP) has highlighted the potential, before neurosurgery, of establishing new brain connections and transfer functional activity from one area of the brain to another. Nonetheless, the neural mechanisms underlying these processes, particularly in the context of space-occupying lesions, remain unclear. A patient with a left frontotemporoinsular tumour underwent a prehabilitation protocol providing 20 sessions of inhibitory non-invasive neuromodulation (rTMS and multichannel tDCS) over a language network coupled with intensive task training. Prehabilitation resulted in an increment of the distance between the tumour and the language network. Furthermore, enhanced functional connectivity within the language circuit was observed. The present innovative case-study exposed that inhibition of the functional network area surrounding the space-occupying lesion promotes a plastic change in the network's spatial organization, presumably through the establishment of novel functional pathways away from the lesion's site. While these outcomes are promising, prudence dictates the need for larger studies to confirm and generalize these findings.

Real-Time Semi-Automated and Automated Voxel Placement using fMRI Targets for Repeated Acquisition Magnetic Resonance Spectroscopy.

BACKGROUND: Currently, magnetic resonance spectroscopy (MRS) is dependent on the investigative team to manually prescribe, or demarcate, the desired tissue volume-of-interest. The need for a new method to automate precise voxel placements is warranted to improve the utility and interpretability of MRS data. NEW METHOD: We propose and validate robust and real-time methods to automate MRS voxel placement using functionally defined coordinates within the prefrontal cortex. Data were collected and analyzed using two independent prospective studies: 1) two independent imaging days with each consisting of a multi-session sandwich design (MRS data only collected on one of the days determined based on scan time) and 2) a longitudinal design. Participants with fibromyalgia syndrome (N = 50) and major depressive disorder (N = 35) underwent neuroimaging. MRS acquisitions were acquired at 3-tesla. Evaluation of the reproducibility of spatial location and tissue segmentation was assessed for: 1) manual, 2) semi-automated, and 3) automated voxel prescription approaches RESULTS: Variability of voxel grey and white matter tissue composition was reduced using automated placement protocols. Spatially, post- to pre-voxel center-of-gravity distance was reduced and voxel overlap increased significantly across datasets using automated compared to manual procedures COMPARISON WITH EXISTING METHODS: Manual prescription, the current standard in the field, can produce inconsistent data across repeated acquisitions. Using automated voxel placement, we found reduced variability and more consistent voxel placement across multiple acquisitions CONCLUSIONS: These results demonstrate the within subject reliability and reproducibility of a method for reducing variability introduced by spatial inconsistencies during MRS acquisitions. The proposed method is a meaningful advance toward improved consistency of MRS data in neuroscience and can be utilized for multi-session and longitudinal studies.

Volitional control of neuromagnetic coherence.

Coherence of neural activity between circumscribed brain regions has been implicated as an indicator of intracerebral communication in various cognitive processes. While neural activity can be volitionally controlled with neurofeedback, the volitional control of coherence has not yet been explored. Learned volitional control of coherence could elucidate mechanisms of associations between cortical areas and its cognitive correlates and may have clinical implications. Neural coherence may also provide a signal for brain-computer interfaces (BCI). In the present study we used the Weighted Overlapping Segment Averaging method to assess coherence between bilateral magnetoencephalograph sensors during voluntary digit movement as a basis for BCI control. Participants controlled an onscreen cursor, with a success rate of 124 of 180 (68.9%, sign-test p < 0.001) and 84 out of 100 (84%, sign-test p < 0.001). The present findings suggest that neural coherence may be volitionally controlled and may have specific behavioral correlates.