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Re-Mapping the Numerical Brain.

Periodic Reporting for period 1 - Re-MAPMATH (Re-Mapping the Numerical Brain.)

Reporting period: 2018-06-01 to 2020-05-31

Re-MAPMATH aimed to uncover brain plasticity for numerical functions. We initially focused on plasticity occurring as a consequence of the growth of a brain tumor (mostly low-grade glioma – LGG). As a consequence of the slow growth of LLGs, the brain has time to reorganize so that behavior is majorly unaffected [1,2].

While brain reorganization has been mostly studied for the language domain [3,4], our project focused on the mathematical system: from core math functions to calculation. Our overarching goal was to delineate possible redundancies and alternative configurations existent in the mathematical brain, allowing for efficient numerical behavior. For that, we used neuroimaging methods (magnetoencephalography - MEG, structural, and diffusion MRI) to these neural changes, including the contrast to the healthy population.

Specific objectives implied firstly, group studies, where default brain activations and functional connectivity in healthy populations were described. They also involved mapping the brain basis for the same functions in brain-damaged patients (brain tumors) and a track of the behavior and its brain basis for post-surgically. Finally, and overall, we aimed to contrast the reorganized brain system to the normative one.

The information obtained from this action will be valuable for rehabilitation techniques in developmental disorders or brain injury and the well-being of the patients. A good understanding of the reorganization capacities of the numerical system at the group and the single case level should benefit the future patient quality of life when numerical brain areas were affected. In turn, we targeted a deep understanding of the functional complexity inside the neurocognitive math system.

[1] Desmurget, M., Bonnetblanc, F. & Duffau, H. Brain 130, 898–914 (2006).
[2] Duffau, H. In Cognitive Plasticity in Neurologic Disorders (eds. Tracy, J., Hampstead, B. & Sathian, K.) 125 (Oxford University Press. 2015).
[3] Duffau, H. et al. J. Neurol. Neurosurg. Psychiatry 74, 901–907 (2003).
[4] Sarubbo, S., Le Bars, E., Moritz-Gasser, S. & Duffau, H. Neurosurg. Rev. 35, 287–292 (2012).
Normative Data:

Neuroimaging normative studies have been conducted on the proposed numerical processes: simple calculation, visual number form, approximate number system, and symbolic numerical processing. Note that these studies already imply an important advance in the state of the art, given its used techniques. As such, results have been submitted for publication, or are about to be sent, to high impact factor journals.

We have described two very similar brain networks in each brain hemisphere for simple arithmetic. We also studied the functional connectivity between the brain areas within each system (i.e. how the different brain sites are orchestrated in time and their causal dependencies). Finally, we also illustrate how specific behavior is linked to individual brain sites during arithmetic. The same approach has been taken

Another scientific achievement regards the information obtained regarding the very early perceptual processing of number form (i.e. Arabic digits). This work is currently submitted for publication.

Brain Reorganization:

As an extension of the project, we have contrasted numerical and language processes after brain reorganization. Our normative data allow the contrast between a healthy brain and a reorganized brain. For arithmetic, we show bilateral parietal activations after a neural reorganization that does not appear in the normative sample. This bilateral neural recruitment combines with the normative system, however. In our study, a more major reorganization occurs for language. We observed that a classical area for language in the left inferior frontal gyrus (IFG) was replaced for the homolog area in the right hemisphere [5]. This work is in preparation for publication.
Another set of data on patient population regards the structural and functional reorganization due to brain tumor during calculation, in combination with awake surgery data.

Moreover, we have extended our patient sample to early-onset epilepsy for which a new project has been initiated and for which preliminary data are available.

[5] Salillas, E. et al. Front. Hum. Neurosci. 13, (2019).
Thanks to our methodological approach and the novel rationale of Re-MAPMATH, the above-outlined results imply significant advances to the state of the art.

Normative Data:

First, the vast majority of neuroimaging studies of math and calculation are based on fMRI [6,7]. Our normative sample's time-dependent information using MEG implies crucial information (see also Salillas, Korostenskaja, et al. 2019). We were able to describe a succession of processing stages for simple arithmetic and their brain sources. Crucially, we were able to explain how the detected brain sources speak to each other across time. This approach was applied to a complete set of numerical functions beyond calculation.

We also had some surprising and unexpected addition to the study of symbolic brain decoding. Here, our work on the early processing of numerical symbols (submitted work) implies a new approach to studying its brain bases.

Brain Reorganization:

Notably, the proposed paths for reorganization in tumor and epilepsy patients are the first systematic studies of brain reorganization for mathematical functions (work in preparation for publication). We added the extra information provided by combining structural and diffusion MRI, and functional information provided during the awake surgery procedure. We further contrasted reorganization for mathematical functions vs. linguistic functions, covering both cognitive domains, but also implying better a control condition for each of them.

Expected Potential Impact:

We have paid particular attention to the implications of our results for the actual surgical process during the development of the project. In turn, our studies provided and will keep providing necessary information on possible alternative neural paths for the recovery of math functions.

According to our results, the divergent roles of the two hemispheres for calculation might have implications for recovery. The collected evidence about the role of the corpus callosum for math reorganization should prime the training for (alternative) functions, still present in the spared hemisphere.

For example, it applies to cases where the retrieval component of calculation is fundamentally altered. An example is arithmetic disabilities. Another is the cases in which the left-hemisphere network serving to that function is acutely damaged in brain stroke patients. Overall, our results significantly impact those brain-injured patients' well-being or people suffering from math learning disabilities.

[6] Arsalidou, M. & Taylor, M. J. Neuroimage 54, 2382–2393 (2011).
[7] Menon, V. In The Oxford Handbook of Numerical Cognition (eds. Cohen Kadosh, R. & Dowker, A.) 502–531 (Oxford University Press, 2015).
[8] Salillas, E. et al. Front. Psychol. 10, 139 (2019)