In recent years there has been an increase in the number of portable low-cost electroencephalographic (EEG) systems available to researchers. However, to date the validation of the use of low-cost EEG systems has focused on continuous recording of EEG data and/or the replication of large system EEG setups reliant on event-markers to afford examination of event-related brain potentials (ERP). Here, we demonstrate that it is possible to conduct ERP research without being reliant on event markers using a portable MUSE EEG system and a single computer. Specifically, we report the results of two experiments using data collected with the MUSE EEG system—one using the well-known visual oddball paradigm and the other using a standard reward-learning task. Our results demonstrate that we could observe and quantify the N200 and P300 ERP components in the visual oddball task and the reward positivity (the mirror opposite component to the feedback-related negativity) in the reward-learning task. Specifically, single sample t-tests of component existence (all p's < 0.05), computation of Bayesian credible intervals, and 95% confidence intervals all statistically verified the existence of the N200, P300, and reward positivity in all analyses. We provide with this research paper an open source website with all the instructions, methods, and software to replicate our findings and to provide researchers with an easy way to use the MUSE EEG system for ERP research. Importantly, our work highlights that with a single computer and a portable EEG system such as the MUSE one can conduct ERP research with ease thus greatly extending the possible use of the ERP methodology to a variety of novel contexts.
The tryptophan (Trp) biosynthetic pathway leads to the production of many secondary metabolites with diverse functions, and its regulation is predicted to respond to the needs for both protein synthesis and secondary metabolism. We have tested the response of the Trp pathway enzymes and three other amino acid biosynthetic enzymes to starvation for aromatic amino acids, branched-chain amino acids, or methionine. The Trp pathway enzymes and cytosolic glutamine synthetase were induced under all of the amino acid starvation test conditions, whereas methionine synthase and acetolactate synthase were not. The mRNAs for two stress-inducible enzymes unrelated to amino acid biosynthesis and accumulation of the indolic phytoalexin camalexin were also induced by amino acid starvation. These results suggest that regulation of the Trp pathway enzymes under amino acid deprivation conditions is largely a stress response to allow for increased biosynthesis of secondary metabolites. Consistent with this hypothesis, treatments with the oxidative stress-inducing herbicide acifluorfen and the abiotic elicitor alpha-amino butyric acid induced responses similar to those induced by the amino acid starvation treatments. The role of salicylic acid in herbicide-mediated Trp and camalexin induction was investigated.
Human learning, at least in part, appears to be dependent on the evaluation of how outcomes of our actions align with our expectations. Over the past 23 years, electroencephalography (EEG) has been used to probe the neural signatures of feedback processing. Seminal work demonstrated a difference in the human event‐related potential (ERP) dependent on whether people were processing correct or incorrect feedback. Since then, these feedback evoked ERPs have been associated with reinforcement learning and conflict monitoring, tied to subsequent behavioral adaptations, and shown to be sensitive to a wide range of factors (e.g., Parkinson's disease). Recently, research has turned to frequency decomposition techniques to examine how changes in the EEG power spectra are related to underlying learning mechanisms. Although the literature on the neural correlates of feedback processing is vast, there are still methodological discrepancies and differences in results across studies. Here, we provide reference results and an investigation of methodological considerations for the ERP (reward positivity) and frequency (delta and theta power) correlates of feedback evaluation with a large sample size. Specifically, participants (n = 500) performed a two‐armed bandit task while we recorded EEG. Our findings provide key information about the data characteristics and relationships that exist between the neural signatures of feedback evaluation. Additionally, we conclude with selected methodological recommendations for standardization of future research. All data and scripts are freely provided to facilitate open science.
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