Journal
NEUROIMAGE
Volume 226, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2020.117541
Keywords
Predictive coding; Temporal expectation; Sensory attenuation; Motor system; Transcranial magnetic stimulation
Funding
- Australian Research Council [DP190100410]
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Research shows that the brain's response to stimuli from one's own actions and predictable stimuli can both be attenuated, indicating that predictive coding may be governed by domain-general mechanisms. This has important methodological implications for designing TMS experiments that control for the predictability of TMS pulses.
The brain's response to sensory input is modulated by prediction. For example, sounds that are produced by one's own actions, or those that are strongly predicted by environmental cues, elicit an attenuated N1 component in the auditory evoked potential. It has been suggested that this form of sensory attenuation to stimulation produced by one's own actions is the reason we are unable to tickle ourselves. Here we examined whether the neural response to direct stimulation of the brain is attenuated by prediction in a similar manner. Transcranial magnetic stimulation (TMS) applied over primary motor cortex can be used to gauge the excitability of the motor system. Motor-evoked potentials (MEPs), elicited by TMS and measured in peripheral muscles, are larger when actions are being prepared and smaller when actions are voluntarily suppressed. We tested whether the amplitude of MEPs was attenuated under circumstances where the TMS pulse can be reliably predicted, even though control of the relevant motor effector was never required. Self-initiation of the TMS pulse and reliable cuing of the TMS pulse both produced attenuated MEP amplitudes, compared to those generated programmatically in an unpredictable manner. These results suggest that predictive coding may be governed by domain-general mechanisms responsible for all forms predictive learning. The findings also have important methodological implications for designing TMS experiments that control for the predictability of TMS pulses.
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