bioRxivNeurosciencePreprint
Short-term transcutaneous vagus nerve stimulation increases pupil size but does not affect EEG alpha power: a replication
Beth LloydiD, Franz WurmiD, Roy de KleijniD, Sander NieuwenhuisiD
Abstract
BackgroundTranscutaneous auricular vagus nerve stimulation (taVNS) is a promising brain stimulation method for the treatment of pharmaco-resistant epilepsy and depression. Its clinical efficacy is thought to depend on taVNS-induced activation of the locus coeruleus. However, unlike for invasive VNS, there is little evidence for an effect of taVNS on noradrenergic activity. ObjectiveWe attempted to replicate recently published findings by Sharon et al. (2021), showing that short bursts of taVNS transiently increased pupil size and decreased EEG alpha power, two correlates of central noradrenergic activity. MethodsFollowing the original study, we used a single-blind, sham-controlled, randomized cross-over design. We applied short-term (3.4 s) taVNS in healthy human volunteers (n=29), while collecting resting-state pupil-size and EEG data. To analyze the data, we used scripts provided by Sharon and colleagues. ResultsConsistent with Sharon et al. (2021), pupil dilation was significantly larger during taVNS than during sham stimulation (p = .009; Bayes factor supporting the difference = 7.45). However, we failed to replicate the effect of taVNS on EEG alpha power (p = .37); the data were four times more likely under the null hypothesis (BF10 = 0.28). ConclusionOur findings support the effectiveness of short-term taVNS in inducing transient pupil dilation, a correlate of phasic noradrenergic activity. However, we failed to replicate the recent finding by Sharon et al. (2021) that taVNS attenuates EEG alpha activity. Overall, this study highlights the need for continued research on the neural mechanisms underlying taVNS efficacy and its potential as a treatment option for pharmaco-resistant conditions. It also highlights the need for direct replications of influential taVNS studies.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 5
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