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Updated: Mar 7, 2026

Combining Transcranial Magnetic Stimulation and fMRI to Examine the Default Mode Network
Published on: December 28, 2010
Effect of topiramate and zonisamide on fMRI cognitive networks
Britta Wandschneider1, Jane Burdett1, Lucy Townsend1
1From the Department of Clinical and Experimental Epilepsy (B.W., J.B., A.H., P.J.T., J.S.D., M.J.K.), UCL Institute of Neurology, London; and MRI Unit (B.W., J.B., L.T., A.H., P.J.T., J.S.D., M.J.K.), Epilepsy Society, Chalfont St. Peter, UK.
Objective:
To investigate the effects of topiramate (TPM), zonisamide (ZNS), and levetiracetam (LEV) on cognitive network activations in patients with focal epilepsy using an fMRI language task.
Methods:
In a retrospective, cross-sectional study, we identified patients from our clinical database of verbal fluency fMRI studies who were treated with either TPM (n = 32) or ZNS (n = 51). We matched 62 patients for clinical measures who took LEV but not TPM or ZNS. We entered antiepileptic comedications as nuisance variables and compared out-of-scanner psychometric measures for verbal fluency and working memory between groups.
Results:
Out-of-scanner psychometric data showed overall poorer performance for TPM compared to ZNS and LEV and poorer working memory performance in ZNS-treated patients compared to LEV-treated patients. We found common fMRI effects in patients taking ZNS and TPM, with decreased activations in cognitive frontal and parietal lobe networks compared to those taking LEV. Impaired deactivation was seen only with TPM.
Conclusions:
Our findings suggest that TPM and ZNS are associated with similar dysfunctions of frontal and parietal cognitive networks, which are associated with impaired performance. TPM is also associated with impaired attenuation of language-associated deactivation. These studies imply medication-specific effects on the functional neuroanatomy of language and working memory networks.
Classification Of Evidence:
This study provides Class III evidence that in patients with focal epilepsy, TPM and ZNS compared to LEV lead to disruption of language and working memory networks.

