Quantifying reward with transcranial magnetic stimulation (Commentary on Gupta and Aron)


  • Miguel Alonso-Alonso

    1. Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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Motivational processes shape our actions, adjusting effort according to anticipated reward size. The current knowledge about the neurocognitive bases and dynamics of such mechanisms in humans is still fragmentary. An important limitation is that objective detection of reward-related signals in human subjects is difficult with existing methods.

Transcranial magnetic stimulation (TMS) is emerging as a potentially valuable research tool in this context. A recent study published in this journal showed, for the first time, that reward modulated TMS-induced motor-evoked potentials (MEPs), an index of motor cortex excitability (Kapogiannis et al., 2008). Specifically, the authors showed greater cortical inhibition during reward expectation, using a task that simulated a slot machine. This approach opens a new window for the study of reward signals through the motor cortex with TMS, quantitatively and non-invasively. In this issue of EJN, new evidence is provided in this area, demonstrating MEP modulation by reward value (Gupta & Aron, 2010). TMS pulses were delivered during a task in which participants had to rate food items and, in a second experiment, select monetary amounts. Gupta and Aron found that stimuli that were more strongly wanted elicited an increase in motor cortex excitability (larger MEPs), as compared with less desired or neutral ones. The time resolution of TMS allowed the authors to show that this occurred at a specific time before action was taken. Collectively, these two studies suggest that reward signals modulate motor output in the cortex and that MEPs could be used as objective correlates of motivation, at least in controlled experimental settings.

The origin of these effects on motor cortex excitability is intriguing. One possibility is that they could reflect influences from related brain areas that are also involved in reward circuits, such as the basal ganglia (Pessiglione et al., 2007). Alternatively, they could arise from direct projections of midbrain dopaminergic neurons to the motor cortex, which are known to be present in the primate brain (Gaspar et al., 1992). The latter pathway has been proposed to explain the reported reward-related changes in intracortical inhibition (Kapogiannis et al., 2008). In this regard, an advantage of the approach taken by Gupta and Aron is that their food-rating paradigm was similar to the one used in a previous functional magnetic resonance imaging (fMRI) study showing that activation in the ventromedial prefrontal cortex correlated with reward value (Hare et al., 2009). This suggests, at least indirectly, that this area could be linked to the observed facilitation of motor cortex excitability. However, the limited time resolution of fMRI as compared with TMS leaves many questions still open. To find more answers, future studies should consider simultaneous TMS/fMRI experiments, the study of patients with brain damage, and the effects of centrally acting drugs.

The application of TMS to the study of reward in humans has largely been focused on offline repetitive TMS to disrupt underlying brain areas and examine behavioral consequences, (e.g. Knoch et al., 2006). Complementary to this approach, the application of single and/or paired-pulse TMS in carefully controlled paradigms that allow separation of cognitive processes is a novel and promising strategy in this research area.

The use of MEP changes as objective correlates of motivation also has implications for translational and clinical neuroscience. Future studies should explore how these reported modulations differ in patients with obesity, eating disorders and gambling, as well as their sensitivity and specificity, and how well they perform longitudinally. These are critical steps before these new approaches can be validated and ultimately used as biomarkers, for example in drug discovery.