Transcranial Direct Current Stimulation (tDCS) Eliminates The Other‑race Efect (ORE) Indexed By The Face Inversion Efect For Own Versus Other‑race Faces Part 2

There are are two key aspects regarding the development of the tDCS procedure used to modulate the inversion effect Firstly, Civile et al.43 conducted an active control study (Experiment 3) to investigate whether similar effects on the FIE would be obtained when another area was targeted. The authors selected the rIFG area (cathode/return channel placed on the opposite supraorbital area, Fp1) based on previous studies that have shown anodal tDCS delivered on this area to be effective at modulating several tasks (e.g., go/no go tasks50,51) however it had never been investigated in response to perceptual learning tasks. 

Learning and memory are an integral part of our lives, and the reversal effect is a key factor affecting our learning effectiveness. People often think of the inversion effect as being inversely related to memory, the inversion effect is regulated correctly, and it can improve our memory and learning.

The reversal effect means that when we encounter difficulties or challenges when studying or working, our learning and performance effects will gradually improve as the challenges increase, but as the challenges continue to increase, our learning effects will gradually decrease called the inversion effect. This is because when our challenges are too high, our anxiety and stress build our performance.

However, if we regulate the inversion effect correctly, it can be a positive force that helps us improve our learning and memory. First, we should set a realistic and feasible challenge goal. We need to find a challenge that makes us feel a little uncertain but also feel excited and motivated. This goal should be achievable and gradually increase in difficulty to facilitate our progress.

Second, we need to adopt appropriate coping strategies to help us overcome the challenges. This includes adopting scientific learning methods, such as multiple repetitions, breaking down knowledge points and discussing with others. We can also use relaxation techniques such as deep breathing and slow and deep muscle relaxation to reduce anxiety and stress.

Finally, we need to maintain an optimistic attitude and positive motivation, which will help us maintain a positive attitude when facing challenges and continuously improve our learning effects and memory. We can maintain our positive motivation by encouraging ourselves, rewarding ourselves, and sharing our achievements with others.

Overall, modulating the inversion effect can help us improve our learning and memory. As long as we can find a realistic challenge goal, adopt appropriate coping strategies, and maintain an optimistic attitude and positive motivation, we can overcome difficulties and improve our performance. We mustn't force, but as a positive force that helps us gradually improve our capabilities. It can be seen that we need to improve memory, and Cistanche deserticola can significantly improve memory because Cistanche deserticola is a traditional Chinese medicinal material that has many unique effects, one of which is to improve memory. The efficacy of minced meat comes from the various active ingredients it contains, including acid, polysaccharides, flavonoids, etc. These ingredients can promote brain health in various ways.

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Civile et al.43’s Experiment 3 found no differences between the robust FIE found indifference group versus that found in the anodal tDCS at the rIFG group. Secondly, in a recently published paper, Civile et al.49 directly compared the,e effects of anodal tDCS at Fp3 versus the effects of tDCS at PO8 while subjects performed a composite face effect study involving upright face effects Subjects were randomly assigned to three tDCS groups including anodal tDCS at Fp3, anodal tDCS at PO8 and sham (split by the two montages). In all three groups, the cathode/return channel was placed on the right supraorbital (Fp2) in line with previous studies that used the tDCS at Fp3 procedure on the inversion effect. 

The specific PO8 site was selected based on EEG literature on the N170 ERP component that revealed how the FIE is found to be largest on that channel28,29. Moreover, a few previous tDCS studies had found different patterns of results on different patterns of tasks when PO8 and closely related areas had been stimulated. Civile et al.49’s findings revealed no effect of findings the size of effect composite face effect (which is a better recogeffectn of the top half of an upright face when conjoined with a congruent rather than an incongruent bottom half) however, it confirmed the reduction in oconfirmedecognition performance (the task involved all upright faces) for subjects in the anodal tDCS at Fp3 group versus the sham group and versus also the tDCS at PO8 group. Critically, no differences were found between the anodal tDCS in PO8 groups.
Thus, these results would Confirm that the tDCS-indconfirmffects on perceptual effects for upright faces would seem to be related to anodal tDCS at the Fp3 area, and when that is moved to PO8 accompanied by leaving the cathode/return channel location in the same location no effects are obtained. Teffectsesults also extended this new line of research looking at the effects of tDCS delivered at occipital sites on face recognition tasks. The investigation is ongoing with studies that have demonstrated different effects different effects tasks and the experimental design used. For instance, Barbieri et al.52 showed how a single-blind fine (pre-behavioural tapre-behaviouralat PO8 (20 min duration, 1.5 mA intensity) can induce higher face and object recognition performance. 

Yang et al.53 showed how a single-blind online anodal tDCS at P8 (15 min duration, 1.5 mA intensity) can influence face recoinfluenceskills indexed by the size of the composite face effect, however, effecter analyses were provided to establish if the effects were due effects enhanced or reduced performance for any of the specific conditispecificnzi et al.54 using a single-blind, within-subjects design targeting a closely related area (OFA area), found that anodal tDCS (20 min duration at 2 mA intensity) did not influence the compos influence effect (similarly toeffectle et al.49). However when the authors applied the same tDCS procedure to a Mooney Task (black and white distorted images) a blocking learning effect was found at effect detection and a decreased performance at object detection54.

In our current study, we aimed to, investigate directly how tDCS can modulate the ORE. We used the specific tDCS (anodal tDCS at Fp3, for 10 min, at 1.5 mA) developed in the perceptual learning and face recognition literature as a tool to directly affect the robuaffecteckerboard and face inversion effects of both effects of f perceptual learning. The reasoning here is that, if in typical circumstances a component of the ORE is the reduced perceptual expertise for other-race faces, the tDCS procedure should alter this by disrupting the perceptual expertise component, manifesting through perceptual learning, for own-race faces (i.e., the theory familiar). Little or no effect of the tDCS procedure should be expected for other-race faces considering that there is less expertise to be lost for these faces. The procedure should selectively reduce the FIE for own-race faces and as a consequence, this would cause a reduction of the overall cross-race interaction (FIE for own vs. vs. her-race faces) that is used as an index of the ORE. Contrarily, if we assume that individuals have visual expertise for both their own and other-race faces (they are all faces) and the ORE is specifically based on motivation to approach individuals from another race, or social categorisation, the tDCS procedure would reduce the FIE for both own and other-race faces, and the ORE would still be found to be significant i.e., la significant own versus other-race faces.

Mother-racejects.

Overall, 96 naïve self-declared Western Caucasian subjects (62 women; mean age=20.8, age range=18–34  years) took part the the study. The subjects were randomly assigned to either sham or anodal tDCS groups (48 in each group). All the subjects were University of Exeter students who have lived in Exeter (a town in the south-west of England with around 90% Western Caucasian population) for at least two years and before that, they all l, lived in countries where Western Caucasian faces are largely predominant (United Kingdom, Germany, Italy, Spain, Poland, France, Bulgaria Romania, Canada, USA). Subjects were selected according to the tDCS safety screening criteria. All methods by the relevant guidelines and regulations approved by the College of Life and Environmental Sciences, Psychology Research Ethics Committee at the University of Exeter. Informed consent was obtained from all subjects.

The sample size was established based on previous studies that have used the same tDCS procedure, behavioural paradigm, and counterbalance of the stimuli, to investigate the effects of tDCS on the FIE43–49.

Materials. The study used a set of high-resolution 80 Western Caucasian and 80 East Asian male and female faces (5.63 cm×7.84 cm) standardized to grayscale on a white background. These images were selected from the open-accesses Chicago Face Database: Multiracial Expansion55. This database was created for research with a focus on the perception and racial categorization of multiracial individuals. It includes a free set of high-resolution, standardized images featuring real multiracial individuals along with extensive norming data and objective physical measures of these facTheseThese data are offered as aofferednsion of the widely used Chicago Face Database and are available for download at www.chicagofaces.org for use in research. This face database has been used often in literature to examine the ORE across different different.

The experiment was run using Superlab 4.0.7b. on an iMac computer. Participants sat about 70 cm away from the screen on which the images were presented.

tDCS apparatus.

The stimulation was delivered by a battery-driven conbattery-drivenstimulator (neuroConn DC-Stimulator Plus) using a pair of surface sponge electrodes (7 cm×5 cm i.e., 35 cm2 ) soaked in saline solution and applied to the scalp at the target areas of stimulation. In agreement with previous work–49, we adopted a bi-lateral bipolar-non-balanced montage with one of the electrodes (anode) placed over the target stimulation area (Fp3) and the other (cathode/return) on the opposite supraorbital area (above the right eyebrow). Using a tDCS EEG-cap-based sEEG-cap-basedStarstim System) the location of the cathode/return electrode would correspond to the Fp2 channel (for an example see Civile et al.46). We used a double-blind procedure reliant on the neuroConn study mode in which the experimenter inputs numerical codes (provided by another experimenter otherwise unconnected with running the experiment), that switch the stimulation mode between “active” (i.e., anodal) and “sham” stimulation. In the anodal condition, direct current simulation of 1.5 mA was delivered for 10 min (5 s fade-in and 5 s fade-out) starting as soon as the subjects began the learning phase (study phase) which lasted for approximately 5  min and continued into the recognition task which lasted approximately 10 min. In the sham group, subjects experienced the same 5 s fade-in and 5 s fade-out, but with the stimulation intensity of 1.5 mA delivered for just 30 s, following which a small current pulse (3 ms peak) was delivered every 550 ms (0.1 mA over 15 ms) for the remainder of the 10 min to check impedance levels (see Fig. 1a).

Behavioural task. The behavioural recognition task consisted of two parts: a ‘study phase’ and an ‘old/new recognition phase–47. In the study phase, each subject was shown 40 upright (20 male and 20 female) and 40 inverted (20 male and 20 female) Western Caucasian and East AsThen faces. The faces were shown one at a time in random order with no response required from the subject. In the old/new recognition phase, 80 novel faces (half upright and half inverted) were added to the 80 faces seen during the study phase. All 160 faces were presented one at a time in random order and the subjects had to respond according to whether they thought they had seen the faces during the study phase. For a given subject, each face stimulus only appeared in one orientation during the experiment.

Following the instructions, in each trial of the study phase subjects saw a fixation cross in the centre of the screen, presented for 1 s, and then a face stimulus was presented on screen for 3 s before moving on to the after-trial. After all the 80 faces had been presented, the program displayed another set of instructions, explaining the recognition task. In this task, subjects were asked to press the ‘.’ key if they recognized the face stimulus as having been shown in the study phase on any given trial, or press ‘x’ if they did not (the keys were counterbalanced). During the recognition task, the face stimuli were each shown for 3 s (and stayed on the screen for the whole duration) during which time subjects had to respond (see Fig. 1b).

Results

Data analysis.

Our primary measure was performance accuracy in the old/new recognition task. As in the previous study,dies43–49, the data from all the subjects in each experimental condition was used to compute a d-prime (d′) sensitivity measure61 for the recognition task where a d=of 0 indicates chance-level performance. We assessed performance against the chance to show that both upright and inverted Western Caucasian and East Asian faces in both the tDCS sham and anodal groups were recognized significantly above chance. (For all four conditions we found p<.001 for this analysis). For completeness, we also analysed the data for decision criterion, C, which in agreement with previous studies–49 revealed no effects of the tDCS procedure on C. We do not report the C analyses because they do not add anything to the interpretation of the results. Each p-value reported for the comparisons between conditions is two-tailed, and we also report the F or t value along with effect size (η2 p).

We computed a 2×2×2 mixed model design using, as a within-subjects factor, FIE (upright or invertepriorce Race (Western Caucasian or East Asian) and the between-subjects factors tDCS Stimulation (sham or anodal). A mixed model Analysis of Variance (ANOVA) revealed a significant, F(1,94)=155.83, p < .001, η2 p=.62 and Face Race, F(1,94) =11.73, p < .001, η2 p=.11. No significant main significantCS Stimulation was found, F(1,94)=.10, p=.75, η2 p<.01. No significant interaction was found for FIE×tDCS Stimulation, F(1,94) = .32, p = .57, η2 p< .01. A significant interaction was found for FIE × Face Race, F(1,94) = 5.41, p= .022, η2 p=.05, and for Face Race×tDCS, F(1,94)=3.93, p=.050, η2 p=.04. Critically, the overall three-way interaction, FIE×Face race×tDCS Stimulation was sign stimulation,94)=9.47, p=.003, η2 p=.09. We decomposed this overall interaction by examining the two-way interactions (FIE×Face Race) separately for each tDCS condition.

Sham tDCS group. A 2×2 ANOVA revealed a significantrevealedect of Face Race, F(1,47)=16.67, p<.001, η2 p=.26, and FIE, F(1,47)=89.89, p<.001, η2 p=.65. Importantly, a significant interaction was found, F(1,47)=13.21, p<.001, η2 p=.21. Paired-sample t-tests showed a significant inversion effect was found for Western Caucasian faces (M=.87, SD=.64), t(47)=9.35, p<.001, η2 p=.65, and, critically, a reduced inversion effect for East Asian faces (M=.32, SD=.71), t(47)=3.13, p=.003, η2 p=.37, essentially confirming a robust ORE (see Fig. 1c). An additional analysis showed that recognition for upright Western Caucasian faces was significantly better than that for upright East Asian faces, t(47)=5.36, p<.001, η2 p=.38. No difference was found for inverted Western Caucasian faces versus inverted East Asian faces, t(47)=.11, p=.91, η2 p<.01 (see Fig. 1c).

Anodal tDCS group. A 2×2 ANOVA revealed no significant main effect of Face Race, F(1,47)=.92, p=.34, η2 p<.01, and a significant main effect of FIE, F(1,47)=67.43, p<.001, η2 p=.58. No significant interaction was found, F(1,47)=.31, p=.58, η2 p<.01 indicating that the FIE for own-race faces was no longer significantly larger than the FIE for other-race faces (see Fig. 1c).

Additional analysis between tDCS groups. We first calculated the FIE index (performance for upright faces – that for inverted faces) for Western Caucasian faces in each tDCS group. Then, we conducted an independent sample t-test which showed that the inversion effect for Western Caucasian faces in the anodal group was significantly reduced compared to that in the sham group, t(94)=3.02, p=.003, η2 p=.08. Critically, performance for upright Western Caucasian faces in the anodal group was also significantly reduced compared to that in the sham group, t(94)=2.28, p=.024, η2 p=.05. No significant diference was found between inverted Western Caucasian faces in the anodal versus sham groups, t(94)=1.04, p=.30, η2 p=.01 (see Fig. 1c). Te difference between the inversion effect indices for East Asian faces in the anodal versus sham group was not significant, t(94)=1.72, p=.087, η2 p=.03.

Bayes factor analyses

Using the procedure outlined by Dienes62 we first conducted a Bayes analysis on the difference between the robust ORE found in the sham group versus the eliminated ORE in the anodal tDCS group (thus capturing the significant 3-Way interaction). Given that the effect (i.e., ORE) can be as large as is found in the sham condition, is the effect (i.e., the reduced ORE) found in the anodal condition part of that population, or is it better described as null (mean of zero)?

We used as the prior the two-way interaction (Face Race×tDCS Stimulation) index of the ORE setting the standard deviation of p (population value | theory) to the mean for the difference between the FIE score (upright – inverted) for Western Caucasian faces versus the FIE score for East Asian faces in the sham group [0.55]. We used the standard error [0.13] and mean difference [−0.08] between the FIE score for Western Caucasian faces versus the FIE score for East Asian faces in the anodal group. We assumed a one-tailed distribution for our theory and a mean of 0. This gave us a Bayes factor of 0.14 which is strong evidence in support of the null (less than 0.30 for the conventional cut-of see62,63), supporting the claim that the anodal stimulation procedure eliminates the ORE.

We conducted a further Bayes analysis on the inversion effect score for Western Caucasian faces comparing the sham and anodal groups (thus capturing the 2×2 interaction). We used as the priors the differences found in Civile et al.43 (Experiments 1 and 2 averaged together) setting the standard deviation of p (population value | theory) to the mean for the difference between the inversion effect in the sham group versus that in the anodal group [0.30]. We used the standard error [0.09] and mean difference [0.36] between the inversion effect for Western Caucasian faces in the sham group versus that in the anodal group. We assumed a one-tailed distribution for our theory and a mean of 0. This gave a Bayes factor of 882.80, which is very strong evidence (greater than 1062,63) that these results demonstrate how the tDCS procedure used here reduces the face inversion effect for Western Caucasian faces.

It could be argued, however, that whilst this convincingly establishes that the effect seen under anodal stimulation (the reduced FIE) is different from the effect seen from the sham stimulation (a robust FIE), this analysis does not test directly whether the effect obtained (smaller FIE for Western Caucasian faces in the anodal vs sham group) in line with our previous studies that have shown this efect43. Hence, to assess this possibility, we conducted two additional analyses where the normal distribution was centred around the prior mean indexed by the difference between the FIE in the sham group versus that in the anodal group [0.30] found in Civile et al.43. To do that, we first subtracted the prior mean [0.30] from the mean difference [0.36] between the inversion effect for Western Caucasian faces in the sham group versus that in the anodal group. Hence, our mean of the sample was 0.06 and the standard error was still 0.09. In the analysis just performed, the prior mean was used as both the standard deviation and mean of p (population value | theory). This time we used a two-tailed distribution for our theory. This gave a Bayes Factor of 0.26 supporting that the effects are in line with the theory. In the second analysis, we only changed the mean of the theory [to 0.30] to reflect the idea that if no effect’s what it would be. All the other values stayed the same as for the first analysis. This gave a Bayes Factor of 0.18. These Bayes factors support the null in these analyses, but the null is now adjusted to be the mean difference expected based on our previous work. Thus, we have good evidence that it is plausible to assume that our current difference is drawn from the distribution that produced our previous results.

Finally, we also conducted a Bayes factor analysis using as priors the mean difference between sham upright faces and anodal upright faces found in Civile et al.’s43 Experiment 1 and 2 averaged together [0.28]. We then used the standard error [0.08] and mean difference [0.25] between sham upright faces and anodal upright faces for Western Caucasian faces. This gave a Bayes factor of 50.18, which is also very strong evidence for the position that performance to upright Western Caucasian faces is reduced by the tDCS procedure, consistent with previous results.

Discussion
The current study aimed to investigate the nature of the ORE. Using a tDCS procedure devised to remove the perceptual learning component of the FIE43–49 we demonstrated that the ORE can be eliminated compared to the robust ORE found in the sham/control group. Our results show that once the FIE for own-race faces has been significantly reduced by anodal tDCS (compared to sham) then the cross-race interaction used as an index of the ORE is no longer significant. Importantly, the anodal tDCS did not reduce the FIE for other-race faces supporting the hypothesis that there is less perceptual learning to be lost for those faces. Finally, we found that recognition performance for upright own-race faces was significantly higher than for other races' faces in the sham condition but significantly reduced in the anodal condition. Furthermore, our Bayesian analyses provided support for the reduction of the ORE in the anodal group. Also, they confirmed how the reduction of the FIE for own-race faces in the anodal versus sham group and the reduced performance for upright own-race faces in the anodal group versus group are in line with previous results in literature43–49.

In line with previous studies that have used the same tDCS procedure applied to the FIE, our explanation for the reduced FIE for own-race faces is based on the McLaren, Kaye, and Mackintosh (MKM) theory of perceptual learning 64–66. According to this theory, in normal circumstances, experience with a prototype-defined category of stimuli (e.g., Western Caucasian faces) leads to perceptual learning. This improves discrimination between upright faces taken from this category. Hence, when observers are first exposed to the category exemplars they would focus on the prototypical/common features shared by all the exemplars. This allows them to correctly associate the exemplars with the correct category membership (e.g., Biden’s face is Western Caucasian). Once the common features are strongly associated with category membership, they would tend to be slower at making new associations, because they would lose their salience leaving the unique features in each exemplar highly salient. This feature salience modulation process leads to perceptual learning because observers can focus on the unique features of each exemplar. They can now better discriminate exemplars within the same category (e.g., Biden vs. Trump’s face) and recognise them easily when presented in their usual upright orientation. On inversion, this benefit of perceptual learning would be lost because we are not as familiar with upside-down faces. When the tDCS procedure is applied, feature salience modulation is altered such that, the common features maintain their salience relatively high thus making the commonalities amongst faces more prominent rather than exaggerating the differences essentially making the faces look more “similar”. It is this change in perceptual learning that causes the reduction in the FIE because it reduces the ability to discriminate between different upright faces which is normally enhanced by expertise for face processing acquired via experience–49.

Given our results, there can be little doubt that perceptual expertise, manifesting through perceptual learning, for upright faces taken from a familiar (i.e., own-race) category contributes to the ORE. Te may also be a hint that the explanation is not quite as simple as saying that once this component of the FIE is eliminated for own-race faces the effect is lost. We note that whilst the stimulation by orientation interaction for other-race faces is not significant, it is also not far off and that there is, at least numerically, an improvement in performance to upright other-race faces as a consequence of anodal tDCS. It may be premature to speculate on this point in the absence of definitive statistical support, but our results are somewhat reminiscent here of effects obtained in similar circumstances when studying Western Caucasian ‘regular’ faces intermixed with Tatcherized versions (the eyes and mouth have been rotated by 180°) of the same type of face46,67. Authors have shown that the same tDCS procedure used in our current study can remove the negative effects of generalization induced by Tatcherized faces onto regular faces when presented intermixed within the same old/new recognition task. It was found that the anodal tDCS in this circumstance increased the FIE for regular faces compared to the reduced FIE found in the sham group (due to the negative generalization brought by Tatcherized faces), and performance for upright regular faces was significantly higher in the anodal group versus sham45. Coming back to results from our current study, one may argue that part of the reason for weaker performance to upright other-race faces in the sham group is a generalization from own-race faces, and this effect is reduced by tDCS allowing performance for other-race faces to recover. This would rely on the distinctive, salient features in own-race faces being the ones that generalize to other-race faces, as this would both be diminished by tDCS and provide an asymmetric effect (i.e., no significant generalization in the reverse direction). Future work should examine this further by comparing the tDCS-induced effects on recognition performance for other-race faces when presented intermixed with own-race faces (i.e., stimuli that generalize onto the other-race faces) versus when other-race faces are intermixed with stimuli that do not generalize onto them (e.g., checkerboards).

A final note regarding our results is that no effects of the tDCS procedure were found on decision criterion C. This is in line with previous studies that have used the same tDCS procedure applied on the FIE using an old/new recognition task or a matching task43–49. The effects of the tDCS procedure were always found on recognition accuracy (reaction times were analyzed to check for speed-accuracy trade-of and none was found), and d-prime was used as a measure of discriminability. However, several authors have suggested how typical recognition tasks such as an old/new recognition would preclude a detailed investigation of response criterion effects because it would tend to lead to a "balanced" effect on C that cancels any potential effect out68,69. To our knowledge, only one recently published study found that the tDCS can modulate criterion (but not discriminability) on a perceptual learning and face recognition task involving faces and checkerboards. However, the authors used a quite different and specifically designed target detection task of the kind previously used in the literature to study C although perceptual learning and applications of tDCS had never been applied to this paradigm before70.

Our findings contribute directly to the ORE literature by showing how a specific tDCS procedure developed in the perceptual learning literature can modulate the FIE for own-race faces leading to a full reduction of the ORE. This provides additional support to the perceptual expertise explanation of the ORE and specifically to the perceptual learning account of the FIE. Our findings do not preclude the possibility for other factors (e.g., racial bias or social motivation) to contribute to the several robust effects found in the literature regarding the perception and categorisation of multiracial individuals 56–60,71. However, regarding the specific nature of the ORE indexed by the FIE, our findings would suggest that perceptual expertise can fully explain the differences in the size of the FIE found previously for own versus other-race faces–27. Importantly, whereas several studies have shown how the tDCS procedure used here influences perceptual learning43–49, no studies have yet reported that the same procedure could potentially influence social motivation. Thus, it is not plausible at the current moment to formulate an alternative explanation for the results obtained on the ORE indexed by the FIE, other than the one based on the perceptual expertise account. Future work should expand our study to the full cross-race design used by Vizioli et al.27 where both Western Caucasian and East Asian participants were recruited. A reduced ORE using the tDCS procedure would be expected in both groups of participants, and this would also provide the data needed to explore the more speculative analysis outlined above regarding the effects of tDCS on upright other-race faces.

More generally, our findings contribute to the emerging literature looking at the effects of tDCS on the ORE. To our knowledge only one study72 before has looked, albeit indirectly, at the effects of tDCS on the ORE. The authors aimed to investigate the effects of single-blind fine cathodal tDCS at the PO8 occipital area (the anode/return channel was placed on the opposite supraorbital area at the Fp1 channel) on various recognition tasks that involved Western Caucasian faces and objects (the FIE was not tested). No effects of cathodal tDCS versus sham were found, however, through a secondary statistical analysis the authors found that cathodal tDCS reduced face recognition performance in non-Western Caucasian subjects grouped compared to sham tDCS. Hence, it was suggested that cathodal tDCS at occipital areas would induce ORE-like effects. Despite the different tDCS procedures, study designs, behavioural tasks, and ORE measures adopted, both studies provide a first step towards the investigation of the mechanisms at the basis of the ORE using tDCS. Our findings also contribute to the perceptual learning literature by providing further evidence in support of a tDCS procedure that can be used to systematically affect the expertise component of a specific phenomenon taken under investigation. Finally, our findings also add to the current literature regarding applications of tDCS to modulate face recognition performance using different paradigms and tasks52–54.

In conclusion, the fact that the same tDCS procedure used in previous research to disrupt perceptual learning for checkerboard and face stimuli eliminates the ORE suggests that expertise, manifesting through perceptual learning, is the key mechanism at the basis of the ORE indexed by the FIE.]

Data availability

The datasets generated during the current study are not currently publicly available as a precaution so that other people will not use them to produce new publications. However, these datasets are available from the corresponding author upon reasonable request.

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