Aquili, Luca

Lim, Lei Wei

Prowacki, Michael

Sheffield Hallam University Research Archive

Eyeblink rate, a putative dopamine marker, predicts negative reinforcement learning by tDCS of the dlPFC.PROWACKI, Michael, LIM, Lei Wei and AQUILI, Luca <http://orcid.org/0000-0003-4930-1536>Available from Sheffield Hallam University Research Archive (SHURA) at:http://shura.shu.ac.uk/29848/This document is the author deposited version.  You are advised to consult the publisher's version if you wish to cite from it.Published versionPROWACKI, Michael, LIM, Lei Wei and AQUILI, Luca (2022). Eyeblink rate, a putative dopamine marker, predicts negative reinforcement learning by tDCS of the dlPFC. Brain Stimulation, 15 (3), 533-535. Copyright and re-use policySee http://shura.shu.ac.uk/information.htmlSheffield Hallam University Research Archivehttp://shura.shu.ac.uklable at ScienceDirectBrain Stimulation 15 (2022) 533e535Contents lists avaiBrain Stimulationjournal homepage: http: / /www.journals .e lsevier .com/brain-st imulat ionEyeblink rate, a putative dopamine marker, predicts negativereinforcement learning by tDCS of the dlPFCKeywords:Transcranial direct current stimulationtDCSDopamineEyeblinkProbabilistic learningExtraversionImpulsivityhttps://doi.org/10.1016/j.brs.2022.02.0091935-861X/© 2022 The Authors. Published by Elsevierapplied oover theStudies have shown that anodal transcranial direct current stim-ulation (tDCS) applied to the dorsolateral prefrontal cortex (dlPFC)increases extracellular dopamine (DA) levels in the striatum [1].Furthermore, pharmacological and genetic investigations indicatethat different DA levels interact with tDCS of the dlPFC to modulateperformance in reinforcement learning (RL) tasks [2e4]. The resultsof these studies suggest an inverted U-shaped relationship be-tween DA concentration and cognitive performance [5].To determine differences between positive and negative RL,Frank and colleagues developed a probabilistic selection task(PST). They investigated a sample of Parkinson's disease (PD) pa-tients on and off DA medication. They found those on DA medica-tion displayed impairments in the negative reinforcement trials,whereas those off medication performed poorly in the positivereinforcement trials [6]. These data support the theory of DAreward prediction error, whereby the DA medication prevents DAdips that are necessary to learn from worse than expected out-comes (i.e., negative prediction error), whereas those without DAmedication do not have sufficient DA available to produce burstsof DA signalling when an outcome is better than expected (i.e., pos-itive prediction error) [7].To further test the relationship among DA availability, tDCS, andRL, we utilized putative physiological and psychological markers ofDA availability (namely eyeblink rate (EBR) [8], extraversion [9],and impulsivity [10]) to predict the effects of anodal tDCS of thedlPFC in the PST. In agreement with Frank's findings, we hypothe-sized that anodal tDCS would be detrimental to those with highDA (as characterized by our physiological/psychological measure-ments) during the negative reinforcement trials (Fig. 1A).The present study was a double-blind, crossover, sham-controlled randomized trial with counterbalancing of conditions(registered at ClinicalTrials.gov; identifier: NCT04798105). Thirty-three healthy participants from the university community tookpart in this study. Anodal tDCS (1.5 mA for 20 minutes) and ShamtDCS (1.5 mA faded in for 30 seconds, then off) of the dlPFC wasInc. This is an open access article uver two experimental sessions. The anode was positionedleft dlPFC centered on F3 in the 10e20 electroencephalog-raphy (EEG) system and the cathode was positioned on the contra-lateral supraorbital ridge (Fp2). We used the PST to measurepositive and negative RL. The PST was administered four times,before and after each of the sham and anodal tDCS. Measures of in-terest included accuracy and reaction times (RT) in the positivereinforcement ‘approach’ trials and the negative reinforcement‘avoidance’ trials. The positive reinforcement trials of the PST mea-sure the ability to select the stimulus that has the highest probabil-ity of reinforcement (out of six stimuli), whereas the negativereinforcement trials measure the ability to avoid the least rein-forced stimulus (see Fig. 1B for more details). Eyeblink rate, as a pu-tative marker of DA concentration, was measured in participantsover a 5-min period during the two experimental sessions. Theimpulsivity and extraversion questionnaires were administered aspsychological proxies for DA. The median split for these putativeDA markers (low and high) was established, which were thenentered in a series of 2*(2*2) factorial mixed design ANOVAs (seeSupplementary Materials 1.1e1.8).We report here the most salient findings. The full results of thisstudy are available in the supplementary files (see SupplementaryMaterials 1.9). There was a significant Eyeblink*tDCS*Time interac-tion for the avoidance trials [F (1, 31) ¼ 7.44, p ¼ .010, h2p ¼ .194].This interaction could be broken down by splitting tDCS*Time intolow and high EBR. There was no significant interaction effect in thelow EBR group (Fig. 1C), whereas a significant effect was observedin the high EBR group [F (1, 15) ¼ 4.87, p ¼ .043, h2p ¼ .245]. Theseresults were further examined with two planned comparisons.Although there was no difference in the accuracy between pre-anodal tDCS versus post-anodal tDCS, the accuracy scores weresignificantly lower for anodal tDCS compared with sham tDCS(p ¼ .038, d ¼ 0.57) (Fig. 1D). A similar pattern of results wasseen for RT, although none of the planned comparisons were signif-icant. There was no significant three-way interaction in theapproach trials.There was a significant Impulsivity*tDCS*Time interaction inthe avoidance trials [F (1, 31) ¼ 5.44, p ¼ .026, h2p ¼ .149], althoughfollow up showed no significant two-way interactions (tDCS*Time)in the low and high impulsivity groups. Extraversion did not signif-icantly determine the tDCS*Time interaction for either avoidanceor approach trials.Overall, we found that neither the psychological trait of impul-sivity nor extraversion could act as useful putative DA markers pre-dictive of the tDCS effects on RL. However, low and high EBRparticipants responded differently to tDCS stimulation duringavoidance trials, but not during approach trials. Specifically, therender the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Fig. 1. A. Hypothetical model based on the theory of DA reward prediction error and the findings of Frank et al. on PD patients who completed the PST on and off DA medication [6].Based on the above, we predicted the effects of tDCS on PST performance based on low, medium, and high EBR. The black, red, and green lines represent putative DA firing for thethree EBR groups depending on whether approach trials (i.e., positive RL: top row) or avoidance trials (i.e., negative RL: bottom row) were presented. During sham tDCS and when acorrect response was made in the approach trials, there would be a positive prediction error, which would be greatest in the high EBR participants. During anodal tDCS of the dlPFC,this signal would be amplified across all the three groups. Therefore, the low EBR group would be predicted to benefit from anodal tDCS given its presumed lower baseline DA, andhence, performance in the approach trials would be comparable to the medium and high EBR groups. During sham tDCS and when an incorrect response was made in the avoidancetrials, there would be a negative prediction error, which would be greatest in the low EBR group. During anodal tDCS, DA activity would become less inhibitory across all threegroups. Therefore, the high EBR group would be negatively affected by anodal tDCS, as DA activity may be too high to produce a negative prediction error required for learning.B. Representation of the PST paradigm. Participants are required to select between pairs of visual stimuli (Japanese characters which have been mirrored, flipped, and rotated) whichare associated with different probabilities of reinforcement. During training, only three different pairs of stimuli are presented. In AB, A has an 80% chance of being reinforced(correct feedback), whereas B has only a 20% chance; for CD, C has a 70% and D has a 30% chance; and for EF, E has a 60% and F has a 40% chance. During testing, all other stimulicombinations are presented. Of particular interest are accuracy rates and RT during the approach trials, where the most positively reinforced stimulus A is paired in AC, AD, AE, andAF trials. Similarly, of interest in the avoidance trials is the least positive reinforced stimulus B paired in BC, BD, BE, and BF trials. C. Three-way significant interaction effects(Time*tDCS*EBR) were broken down into two-way factorial ANOVAs split by low and high EBR. There was a non-significant interaction between Time*tDCS for avoidance trials inthe low EBR group (accuracy). D. There was a significant interaction between time*tDCS for the avoidance trials in the high EBR group. This was further investigated by plannedcomparisons. Accuracy rates were significantly lower during anodal tDCS compared to sham tDCS. Error bars as SEM. * represents p < .05. (For interpretation of the references tocolour in this figure legend, the reader is referred to the Web version of this article.)M. Prowacki, L.W. Lim and L. Aquili Brain Stimulation 15 (2022) 533e535was an impairment in their performance (i.e., lower accuracy foravoidance trials) following anodal tDCS of the dlPFC comparedwith sham tDCS. These findings parallel those reported by Frank'sgroup on PD patients on and off DA medication [6]. That is, thehigher putative DA of the high EBR group in combination withanodal tDCS of the dlPFC, which has been shown to increase DArelease in the striatum [1], may have blocked DA neurons' abilityto produce an inhibitory signal required for learning about stimulithat are poor predictors of reinforcement. This interpretation of thedata is based on the theory of DA reward prediction error [7],although the obvious caveat is that we did not measure DA neuronfiring or DA concentrations.Eyeblink rate has been shown to be associated with striatal DAactivity, and importantly, it has been reported to be a useful predic-tor of reward-driven behaviour, cognitive flexibility, inhibitory con-trol, and working memory involving DA function [8]. Although EBRis a non-distinctive method of measuring DA, it has the advantagesof being non-invasive and easy to quantify compared to neuroimag-ing (e.g., PET) and genetic approaches (e.g., DA gene534polymorphisms). As the effects of tDCS on cognitive function arehighly variable due tomethodological and biological heterogeneity,EBR may act as a useful marker to help identify who will benefitfrom tDCS in the context of tasks and processes that depend onDA activity. For example, based on the results of our study, wemay predict that cathodal (inhibitory) tDCS applied to those withlow EBR may impair approach behaviour, as a burst of DA signalis required for learning. This would allow for designing tDCS studiesthat are better tailored to individual characteristics to achieve morehomogenous outcomes.Author contributionsLA designed the study. MP performed the research. LA and MPanalysed the data. MP, LWL, and LA wrote the manuscript.Declaration of competing interestNone.M. Prowacki, L.W. Lim and L. Aquili Brain Stimulation 15 (2022) 533e535AcknowledgementsWewould like to thank the College of Health & Human Sciencesat Charles Darwin University for funding this research.Appendix A. Supplementary dataSupplementary data to this article can be found online athttps://doi.org/10.1016/j.brs.2022.02.009.References[1] Fonteneau C, Redoute J, Haesebaert F, Le Bars D, Costes N, Suaud-Chagny M-F,et al. Frontal transcranial direct current stimulation induces dopamine releasein the ventral striatum in human. Cerebr Cortex 2018;28(7):2636e46.[2] Borwick C, Lal R, Lim LW, Stagg CJ, Aquili L. Dopamine depletion effects oncognitive flexibility as modulated by tDCS of the dlPFC. Brain Stimulation2020;13(1):105e8.[3] Dennison O, Gao J, Lim LW, Stagg CJ, Aquili L. Catecholaminergic modulationof indices of cognitive flexibility: a pharmaco-tDCS study. Brain Stimulation2019;12(2):290e5.[4] Nieratschker V, Kiefer C, Giel K, Krüger R, Plewnia C. The COMT val/met poly-morphism modulates effects of tDCS on response inhibition. Brain Stimulation2015;8(2):283e8.[5] Cools R, D'Esposito M. Inverted-Ueshaped dopamine actions on human work-ing memory and cognitive control. Biol Psychiatr 2011;69(12):e113e25.[6] Frank MJ, Seeberger LC, O'Reilly RC. By carrot or by stick: cognitive reinforce-ment learning in parkinsonism. Science 2004;306(5703):1940e3.[7] Schultz W, Dayan P, Montague PR. A neural substrate of prediction andreward. Science 1997;275(5306):1593e9.[8] Jongkees BJ, Colzato LS. Spontaneous eye blink rate as predictor of dopamine-535related cognitive functionda review. Neurosci Biobehav Rev 2016;71:58e82.[9] Smillie LD, Jach HK, Hughes DM, Wacker J, Cooper AJ, Pickering AD. Extraver-sion and reward-processing: consolidating evidence from an electroencepha-lographic index of reward-prediction-error. Biol Psychol 2019;146:107735.[10] Petzold J, Kienast A, Lee Y, Pooseh S, London ED, Goschke T, et al. Baselineimpulsivity may moderate L-DOPA effects on value-based decision-making.Sci Rep 2019;9(1):5652.Michael ProwackiCollege of Health & Human Sciences, Charles Darwin University,Darwin, AustraliaLee Wei LimSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, TheUniversity of Hong Kong, Pokfulam, Hong Kong, SAR, ChinaLuca Aquili1,*College of Health & Human Sciences, Charles Darwin University,Darwin, AustraliaSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, TheUniversity of Hong Kong, Pokfulam, Hong Kong, SAR, China* Corresponding author.E-mail address: Luca.Aquili@murdoch.edu.au (L. Aquili).9 February 2022Available online 25 February 20221 Current address: College of Science, Health, Engineering and Education, Disci-pline of Psychology, Murdoch University, Perth, Australia.

Eyeblink rate, a putative dopamine marker, predicts negative reinforcement learning by tDCS of the dlPFC.

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Eyeblink rate, a putative dopamine marker, predicts negative reinforcement learning by tDCS of the dlPFC.

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