.. _codex_fmri_2024_BeynelEtal: **Beynel et al. (2024).** *Lessons learned from an fMRI-guided rTMS study ...* ************************************************************************************************** .. contents:: :local: .. highlight:: Tcsh Introduction ============ Here we present commands used in the following paper: * | Beynel L, Gura H, Rezaee Z, Ekpo EC, Deng ZD, Joseph JO, Taylor P, Luber B, Lisanby SH (2024). Lessons learned from an fMRI-guided rTMS study on performance in a numerical Stroop task. PLoS One 19(5):e0302660. doi: 10.1371/journal.pone.0302660. | ``_ **Abstract:** The Stroop task is a well-established tool to investigate the influence of competing visual categories on decision making. Neuroimaging as well as rTMS studies have demonstrated the involvement of parietal structures, particularly the intraparietal sulcus (IPS), in this task. Given its reliability, the numerical Stroop task was used to compare the effects of different TMS targeting approaches by Sack and colleagues (Sack AT 2009), who elegantly demonstrated the superiority of individualized fMRI targeting. We performed the present study to test whether fMRI-guided rTMS effects on numerical Stroop task performance could still be observed while using more advanced techniques that have emerged in the last decade (e.g., electrical sham, robotic coil holder system, etc.). To do so we used a traditional reaction time analysis and we performed, post-hoc, a more advanced comprehensive drift diffusion modeling approach. Fifteen participants performed the numerical Stroop task while active or sham 10 Hz rTMS was applied over the region of the right intraparietal sulcus (IPS) showing the strongest functional activation in the Incongruent > Congruent contrast. This target was determined based on individualized fMRI data collected during a separate session. Contrary to our assumption, the classical reaction time analysis did not show any superiority of active rTMS over sham, probably due to confounds such as potential cumulative rTMS effects, and the effect of practice. However, the modeling approach revealed a robust effect of rTMS on the drift rate variable, suggesting differential processing of congruent and incongruent properties in perceptual decision-making, and more generally, illustrating that more advanced computational analysis of performance can elucidate the effects of rTMS on the brain where simpler methods may not. **Study keywords:** task-based FMRI, EPI, MPRAGE, human, adult, rTMS **Main programs:** ``afni_proc.py``, ``@SSwarper`` | **Github page:** | See these authors' github page for descriptions and downloads of codes and supplementary text files: | ``_ Download scripts ================ To download, either: * \.\.\. click the link(s) in the following table (perhaps Rightclick -> "Save Link As..."): .. list-table:: :header-rows: 0 * - |s01| - run ``@SSwarper`` for nonlinear alignment to a template, and skullstripping of the subject's T1w anatomical volume * - |s02| - run ``afni_proc.py`` for task-based FMRI analysis (Stroop task); this uses nonlinear warps estimated with ``@SSwarper`` * \.\.\. or copy+paste into a terminal:: curl -O https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/media/2024_BeynelEtal/do_13_ssw.bash curl -O https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/media/2024_BeynelEtal/do_20_ap_targeting.bash View scripts ============ ``do_13_ssw.bash`` ------------------------------------------- .. literalinclude:: /codex/fmri/media/2024_BeynelEtal/do_13_ssw.bash :linenos: ``do_20_ap_targeting.bash`` ------------------------------------------- .. literalinclude:: /codex/fmri/media/2024_BeynelEtal/do_20_ap_targeting.bash :linenos: .. aliases for scripts, so above is easier to read .. |s01| replace:: :download:`do_13_ssw.bash ` .. |s02| replace:: :download:`do_20_ap_targeting.bash `