Lessons learned from an fMRI-guided rTMS study on performance in a numerical Stroop task.

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Computational Psychiatry

Background:

• The Stroop task is a standard method for studying how conflicting information affects decision-making.
• Previous research, including neuroimaging and repetitive transcranial magnetic stimulation (rTMS) studies, has implicated the intraparietal sulcus (IPS) in the Stroop task.
• Individualized functional magnetic resonance imaging (fMRI) targeting has previously shown superior results for rTMS in the numerical Stroop task.

Purpose of the Study:

• To investigate if fMRI-guided rTMS effects on numerical Stroop task performance persist with modern techniques.
• To compare traditional reaction time analysis with advanced drift diffusion modeling in assessing rTMS efficacy.
• To explore the impact of rTMS on perceptual decision-making using advanced computational methods.

Main Methods:

• Fifteen participants completed the numerical Stroop task.
• Active or sham 10 Hz rTMS was applied over the right IPS, identified via individualized fMRI.
• Performance was analyzed using traditional reaction time measures and drift diffusion modeling.

Main Results:

• Standard reaction time analysis showed no significant difference between active and sham rTMS, potentially due to practice effects or cumulative stimulation.
• Drift diffusion modeling revealed a significant effect of rTMS on the drift rate, indicating altered processing of congruent and incongruent stimuli.
• Advanced computational modeling successfully elucidated rTMS effects on brain function where simpler analyses failed.

Conclusions:

• While traditional analyses may not detect subtle effects, advanced computational modeling can reveal rTMS impacts on cognitive processes.
• The study demonstrates that rTMS over the IPS influences decision-making parameters in the numerical Stroop task.
• This underscores the importance of sophisticated analytical approaches in neurostimulation research for a deeper understanding of brain function.