No effects of anodal transcranial direct current stimulation on contrast sensitivity function

Abstract

Background:

Transcranial direct current stimulation (tDCS) is a well-established non-invasive brain stimulation technique that has been widely applied to modulate cortical excitability in human brain. The results of previous tDCS studies on modulating contrast sensitivity, one of the most fundamental visual functions, were mixed.

Objective:

We aim to systematically investigate the effects of anodal tDCS on contrast sensitivity functions (CSF), evaluate the responsiveness explanation of tDCS effects, and discuss results along with measurement precision.

Methods:

We designed a single-blinded, sham-controlled within-subject study. Twenty-seven healthy adult subjects received three sets of 15 min tDCS (two 2-mA anodal and one sham) that delivered at Oz, with CSF measured before and after each tDCS stimulation. Experimental sessions were separated by at least twenty-four hours. CSF was assessed with a Bayesian procedure that accurately estimated CSF within minutes. The anodal tDCS-induced effect was gauged with the change in CSF after stimulation; responsiveness was indexed by correlation between CSF changes in different stimulation; precision was calculated from resampling.

Results:

Our results indicated that neither the first nor the second session anodal tDCS altered the CSF significantly. Responsiveness was inconsistent between the two anodal sessions, indicating the usual responder/non-responder explanation of tDCS effects was unconvincing. Precision was less than 2 dB and constant throughout the whole experiment.

Conclusions:

The anodal tDCS, at least with two sessions, has no effect on modulating CSF. The absence of anodal tDCS effect on CSF was not due to subject’s responsiveness to tDCS or measurement precision. More studies were needed to determine the optimal vision modulation configuration.

Keywords

Transcranial direct current stimulation tDCS contrast sensitivity function CSF vision non-invasive brain stimulation

1. Introduction

Transcranial direct current stimulation (tDCS), a promising non-invasive tool to modulate brain activity, has gained intense attention in both clinical and laboratory studies over the last decade due to its easy operation (Gandiga et al., 2006) and safety (Bikson et al., 2009; Kessler et al., 2012; Poreisz et al., 2007). It involves a stimulating device that delivers a weak and yet constant current between two polarity-opposite electrodes (anodal and cathodal) placed on the scalp of a subject. Likely through modulating the excitation and inhibition level of human brain by putative alterations of the membrane potential of neurons in a polarity-dependent manner (Stagg & Nitsche, 2011), tDCS has been found to be effective to modulate vision (Antal et al., 2004; Antal et al., 2006; Battaglini et al., 2017; Spiegel et al., 2013b), motor (Batsikadze et al., 2013; Nitsche & Paulus, 2000; Nitsche et al., 2003), working memory (Fregni et al., 2005), naming (Ferrucci et al., 2008), and decision making in both normal and clinical populations (Fregni et al., 2006; Kekic et al., 2016).

In the current study, we focused on the effects of tDCS on contrast sensitivity, one of the most fundamental visual functions (Lovegrove et al., 1982; Lovegrove et al., 1980; Peli, 2001; Robson, 1966). Since the first manifestation of tDCS effects on visual contrast sensitivity by Antal et al. (2001), a few studies have also evaluated the efficacy of tDCS on contrast sensitivity and its corresponding neural activity (Ding et al., 2016; Spiegel et al., 2013a) with different settings but got mixed results (Table 1). In brief, the effects of anodal/cathodal tDCS can be either positive/negative or neutral in either normal (Antal et al., 2001; Chaieb et al., 2008; Costa et al., 2015; Reinhart et al., 2016; Richard et al., 2015) or clinical populations (Ding et al., 2016; Spiegel et al., 2013a), and the magnitude, if effective, was mostly less than 15%. In addition, contrast sensitivity was usually estimated at single spatial frequency or a few spatial frequencies with method of adjustment (Antal et al., 2001) or staircase method (Costa et al., 2015; Ding et al., 2016; Richard et al., 2015; Spiegel et al., 2013a), which was known to be difficult in balancing measurement precision and efficiency during CSF estimation (Lesmes et al., 2010). Since the after-effects of tDCS modulation may not last long (Accornero et al., 2006; Antal et al., 2003a; Antal et al., 2003b; Lang et al., 2007; Nitsche & Paulus, 2000), it’s mandatory to accurately measure CSF with acceptable time and precision in checking the effects of tDCS on contrast sensitivity. In the current study, we used a quick CSF procedure developed by Lu & his colleagues that can precisely and efficiently measure CSF with 100 trials (less than 5 minutes) to determine the effects of anodal tDCS on contrast sensitivity over a broad range of spatial frequencies (Hou et al., 2010; Hou et al., 2015; Hou et al., 2016; Lesmes et al., 2010). The qCSF has been successfully applied in fovea vision, periphery, aging, and amblyopia screening (Hou et al., 2010; Jia et al., 2018; Jia et al., 2015; Kalia et al., 2014; Vedamurthy et al., 2015). Since we are more concerned with the enhancing effect of tDCS, we focused on anodal stimulation. In addition, we also tested if two sessions’ anodal tDCS application has accumulative effects on contrast sensitivity.

Table 1
Overview of tDCS effect on CSF^a

SF (cpd) Methods Polarity^e Duration (min) Density (mA) F/P^d Main results Imp% ^f

Antal, et al. (2001) ^b 4 adjustment A/C 7 1.0 F reduced during and immediately after cathodal tDCS. –5%

Spiegel, et al. (2013) ^c Cut-off SF 2-down 1-up A/C 15 2.0 F CSF decreased after cathodal tDCS in fellow eye of amblyopia, and increased after anodal tDCS in amblyopic eye of responder –15%

Costa, et al. (2015) 0.5, 4, 16 2-down 1-up A/C/S 30 1.5 F no effect on grating CSF. 0

Richard, et al. (2015) 0.5, 4, 8, 12 2-down 1-up A/C 21.05±2.74 2.0 F cathodal increased and anodal tDCS decreased CS at 8 cpd. ±10%

Ding, et al. (2016) ^c 10 2-down, 1-up A/C/S 20 2.0 F Anodal tDCS enhanced CSF in amblyopic eyes. 10%

Reinhart, et al. (2016) 0.5–20 qCSF A/S 20 2.0 P CSF at high SF were enhanced in one hemisphere 15%

	SF (cpd)	Methods	Polarity^e	Duration (min)	Density (mA)	F/P^d	Main results	Imp% ^f
Antal, et al. (2001) ^b	4	adjustment	A/C	7	1.0	F	reduced during and immediately after cathodal tDCS.	–5%
Spiegel, et al. (2013) ^c	Cut-off SF	2-down 1-up	A/C	15	2.0	F	CSF decreased after cathodal tDCS in fellow eye of amblyopia, and increased after anodal tDCS in amblyopic eye of responder	–15%
Costa, et al. (2015)	0.5, 4, 16	2-down 1-up	A/C/S	30	1.5	F	no effect on grating CSF.	0
Richard, et al. (2015)	0.5, 4, 8, 12	2-down 1-up	A/C	21.05±2.74	2.0	F	cathodal increased and anodal tDCS decreased CS at 8 cpd.	±10%
Ding, et al. (2016) ^c	10	2-down, 1-up	A/C/S	20	2.0	F	Anodal tDCS enhanced CSF in amblyopic eyes.	10%
Reinhart, et al. (2016)	0.5–20	qCSF	A/S	20	2.0	P	CSF at high SF were enhanced in one hemisphere	15%

^aElectrode position is Oz, and reference electrode position is Cz for all but Reinhart et al., in which they posited active electrode at P1/P2, and the reference electrode is contralateral cheek; ^bDynamic contrast sensitivity results were not included; ^cPatients with amblyopia were studied; ^dF/P: stimulus display location, foveal or periphery; ^eA/C/S, anodal, cathodal, and sham, respectively; ^fPercentage of modulation was estimated (relative to the baseline and/or sham conditions) from relative researches.

2. Methods

2.1. Participants

Twenty-seven healthy right-handed volunteers (11 females, 23.4±1.9 years) participated in the study. All subjects had normal or corrected-to-normal vision and no experience of transcranial electrical or magnetic stimulation experiment, no history of neurological, psychiatric conditions or brain trauma, no metal implants, no history of visual disorder or significant refractive aberration, and no history of other major medical problems. Female subjects were not currently pregnant. Written informed consent was obtained from all subjects prior to study beginning. The study was approved by Ethics Review Board of Institute of Psychology, Chinese Academy of Sciences.

2.2. Apparatus

All stimuli were generated by a PC running MATLAB (Mathworks, Natick, MA) and PsychToolBox extensions version 3.0 (Brainard, 1997; Pelli, 1997) and presented on a gamma-calibrated 20 inch Dell monitor with a vertical refresh rate of 85 Hz, a resolution of 1600×1200 pixels, and mean luminance of 30.6 cd/m². To enable display of high-precision gray levels, we used a special circuit to combine two 8-bit output channels of the video card to produce 14-bits resolution (Li et al., 2003).

2.3. qCSF implementation

The quick contrast sensitivity function (qCSF) method is a novel and reliable procedure for rapid measurement of contrast sensitivity function, which has been successfully applied in both normal and clinical populations (Hou et al., 2010; Hou et al., 2015; Hou et al., 2016; Jia et al., 2018; Jia et al., 2015; Vedamurthy et al., 2015; Yan et al., 2017; Zhao et al., 2017). The qCSF method uses the truncated log-parabola function to characterize the CSF curve with four parameters (i.e., peak sensitivity or gain, peak spatial frequency, bandwidth in octaves, and low-frequency sensitivity truncation level; Lesmes et al., 2010). A four-dimensional probability density function is used to assign probabilities for each combination of the parameters. The probability density function determines the spatial frequency and contrast value of the presented sinewave grating for each trial, which is updated trial-to-trial with a Bayesian rule based on the subject’s response in the prior trial.

The stimuli were 3°×3° sine-wave gratings, oriented±45° from vertical. A half-Gaussian edge ramp (σ= 0.5°) was added to minimize edge effects. The stimulus space consisted of gratings with contrasts ranging from 0.1% to 99% in steps of 1.50 dBs and spatial frequencies from 0.5 to 16 cycles per degree (cpd) in steps of 3 dBs. Each CSF was obtained with 100 trials in a two-alternative forced choice (2AFC) paradigm.

2.4. Transcranial direct current stimulation (tDCS)

TDCS were applied using the DC-STIMULATOR MC (neuroConn GmbH, Ilmenau, Germany) through a pair of rubber electrodes of 5×5 cm². The electrodes were adhered on a soaked sponge (0.9% saline solution) and placed on the Oz (active electrode position) and Cz (reference electrode position), as defined by the international 10–20 electroencephalogram system (Antal, Kincses, Nitsche et al., 2004). During the anodal tDCS, the current intensity ramped up to 2.0 mA in 31 seconds, kept constant at 2.0 mA for 15 minutes, and ramp down to zero in 31 seconds. The resistance was lower than 10 kΩ during stimulation. The placement of electrodes under sham condition was identical to anodal stimulation condition. To avoid a sudden release or stop of stimulation in the sham stimulation, the current ramped up to max density (i.e. 2 mA) in 31 seconds, maintained at 2 mA for 10 seconds, and then faded out to zero in 31 seconds.

2.5. Procedure

This was a single-blind, sham-controlled within-subject experiment. All participants took part in two anodal stimulation sessions and one sham condition in three consecutive days, and the order of stimulation was counter-balanced across subjects. During tDCS session, subjects just seated in the dim room and had a rest. CSF measurement was implemented before and immediately after tDCS session. Participants viewed the center of the monitor at a distance of 186 cm in a dim room with the monitor as the only light source. In qCSF trials, each trial consisted of an initial 294 ms fixation in the center of the display and one 141 ms stimulus intervals, which were separated by a blank screen interval lasting 153 ms. A brief tone signaled the onset of signal grating. The grating was only presented with one of the two possible orientations (–45° VS. 45° relative to the meridian). After stimulus presentation, subject made a keypress to report grating orientation. No feedback was provided. After subject submitting their responses, a 588 ms inter-trial blank screen interval presented. All subjects were given practice trials to familiarize them with the qCSF task and stimulation procedures. During and at the end of the stimulation, all subjects were asked to report their sensation and tolerance they experienced during stimulations.

2.6. Data analysis

The expectation value of contrast threshold at individual spatial frequency was estimated from the four-dimensional probability density function that was obtained after 100 trials in each qCSF measurement. Contrast thresholds at each sample spatial frequency were converted to log₁₀ contrast sensitivity (i.e. log₁₀(1/contrast threshold)). In the current study, we also calculated the area under CSF curve (AUC) by integrating CSF in the range from 0.5 to 16 cpd, an aggregate index of spatial vision (Hou et al., 2015; Hou et al., 2016; Lee et al., 2014; Lesmes et al., 2010; Rosén et al., 2014; Venkataraman et al., 2015), to characterize potential contrast sensitivity changes following tDCS stimulation.

We conducted a 3 (Stimulation Condition, i.e. the first, the second anodal, and the sham tDCS session)×2 (Test Session, i.e. pre-and post-test)×6 (Spatial Frequencies, i.e., 0.5, 1, 2, 4, 8, 16 cpd) Repeated-Measure ANOVA on estimated contrast sensitivity. In order to test the overall effect of anodal tDCS on CSF, a two-way Repeated-Measure ANOVA was conducted to evaluate the effects of anodal tDCS on AUC, with Stimulation Condition and Test Session as independent variables.

Previous studies have demonstrated that the effects of tDCS on cognitive functions have significant inter-subject variability, leading to a responsiveness explanation of tDCS effects (Dyke et al., 2016; Spiegel et al., 2013a; Strube et al., 2016). We hypothesized that if responsiveness indeed contributed significantly to the effects of tDCS on a particular subject, the effects should be largely consistent between the two anodal sessions. To test the hypothesis, we calculated the correlation between AUCs changes in the two stimulation sessions. To rule out the variability of qCSF across tDCS session contributed to the responsiveness variance, we also made Pearson correlation analyses across tDCS session for each pre-stimulation baseline.

As qCSF method is implemented with different algorithm compared with previous studies that adopted method of constant stimulus, or adaptive staircase method. To quantify the actual measurement precision, we resampled CSF 1000 times in the parameter space based on subject’s response in each trial and determined the standard deviation of resampled sensitivity distribution (more details, ref. Hou et al., 2015; Hou et al., 2016; Lesmes et al., 2010; Yan et al., 2017). A repeated measurement ANOVA was conducted with Test session and Stimulation as within-subject variables.

3. Results

3.1. TDCS-induced cutaneous sensation

TDCS-induced sensations included modest itching or a little bit hot on their vertex for most subjects (Poreisz et al., 2007; Woods et al., 2016). All our subjects well tolerated the stimulation effects; none of the experimental sessions were interrupted due to side effects of the stimulation. All the participants were unable to distinguish anodal stimulation from sham stimulation by inquiry and self-report.

3.2. The effect of tDCS on contrast sensitivity across all spatial frequencies

CSFs at the first anodal, the second anodal, and the sham conditions were shown in Fig. 1. The Three-Way Repeated-Measure ANOVA on contrast sensitivity revealed significant main effects of Stimulation Condition (F_(2,52) = 6.05, p = 0.004, $η_{p}^{2} = 0.19$ ) and Spatial Frequency (F_(5,130) = 433.20, p < 0.00001, $η_{p}^{2} = 0.94$ ) but not Test Session (F_(1,26) = 1.03, p = 0.32, $η_{p}^{2} = 0.04$ ). Interaction of all these variables were not significant (specifically, F_(2,52) = 0.92, p = 0.40, $η_{p}^{2} = 0.03$ , for Stimulation Condition×Test Session; F_(10,260) = 1.21, p = 0.28, $η_{p}^{2} = 0.05$ , for Stimulation Condition×Test Session; F_(5,130) = 0.55, p = 0.74, $η_{p}^{2} = 0.02$ , for Test Session×Spatial Frequency; F_(10,260) = 0.55, p = 0.85, $η_{p}^{2} = 0.02$ , for Stimulation Condition×Test Session×Spatial Frequency, respectively). A further analysis of Stimulation Condition showed that CSFs obtained from the second anodal tDCS session were higher than the sham condition and the first tDCS session (log contrast sensitivity of 1.806±0.02 vs 1.762±0.022 and 1.767±0.024, averaged across subjects, test sessions, and spatial frequencies, p = 0.002 and p = 0.009, respectively). A simple effect analysis of Test session (i.e., paired t-tests) on each Stimulation Condition shown that there was no significant changes in contrast sensitivity before and after the first anodal (t₍₂₆₎ = 0.13, p = 0.73, $η_{p}^{2} = 0.005$ ), the second anodal (t₍₂₆₎ = 0.07, p = 0.80, $η_{p}^{2} = 0.003$ ), and the sham stimulation (t₍₂₆₎ = 2.62, p = 0.12, $η_{p}^{2} = 0.092$ ). Since the interaction of simulation condition and test session was not significant, our results suggested there was no significant effect of anodal tDCS on contrast sensitivity function in the two sessions and the observation of mild contrast sensitivity enhancement that related to the 2nd anodal stimulation, on the other hand, may reflect a slight practice effect.

Fig.1

Contrast sensitivity function (CSF) before (dotted line) and after (solid line) the first anodal (Left, red), the second anodal (Middle, blue), and the sham stimulation (Right, black). The gray-shaded region denotes S.E.M.

3.3. The Effect of tDCS on Area Under CSF (AUC)

AUC for each subject was shown in Fig. 2. AUC significantly varied with Stimulation Condition (F_(2,52) = 5.69, p = 0.006, $η_{p}^{2} = 0.18$ ), but not Test Session (F_(1,26) = 0.66, p = 0.43, $η_{p}^{2} = 0.03$ ) and the interaction between Test Session and Stimulation Condition (F_(2,52) = 1.37, p = 0.26, $η_{p}^{2} = 0.05$ ). Post-Hoc analysis revealed a mild and yet significant increase of AUC in the second anodal tDCS stimulation (2.84±0.03 and 2.86±0.03 for pre-and post-stimulation, respectively) as opposed to that in the first anodal stimulation (2.80±0.03 and 2.79±0.04) and sham condition (2.82±0.04 and 2.77±0.04), consistent with the analysis on isolated frequencies. A paired t-tests shown that there were no significant changes in AUC before and after tDCS for all conditions (t₍₂₆₎ = 0.06, p = 0.81, $η_{p}^{2} = 0.002$ , for the first anodal tDCS session; t₍₂₆₎ = 0.624, p = 0.44, $η_{p}^{2} = 0.023$ , for the second anodal tDCS session; t₍₂₆₎ = 2.61, p = 0.12, $η_{p}^{2} = 0.09$ , for the sham condition).

Fig.2

The area under CSF (AUC) before (circle) and after (dot) the first anodal (red), the second (blue), and sham stimulation (black) conditions. The dash line indicates individual data, the solid line indicates averaged results across all the subjects. Errorbar:±1 S.D.

3.4. Responsiveness to tDCS

There’s no significant correlation between AUC changes in sham and the 1st anodal stimulation (r = –0.20, p = 0.34), sham and the 2nd anodal stimulation (r = 0.17, p = 0.42), and the 1st and the 2nd anodal stimulation conditions (r = –0.15, p = 0.47), shown in Fig. 3, indicating of no consistent pattern in response to tDCS across subjects.

Fig.3

Correlation between area under CSF (AUC) changes for different stimulation types. Triangle scatter: correlation between AUC changes in sham and the 1st anodal stimulation; Square scatter: correlation between AUC changes in sham and the 2nd anodal stimulation; Circle scatter: correlation between AUC changes in the 1st and the 2nd anodal sessions.

3.5. Correlation between baseline measurement

The Pearson correlation analysis for pre-stimulation CSF measures (i.e. baseline) across tDCS sessions showed that there were significant and strong correlations between them (r = 0.69, 0.77, and 0.71 for sham vs the first anodal, sham vs the second anodal, and the first vs the second anodal stimulation, respectively, all p < 0.0001; See Fig. 4). Our results suggested that subject’s variability in baseline CSF performance was nicely captured by the quick procedure and maintained across sessions.

Fig.4

Correlation analysis on baseline between tDCS stimulation session. The triangle scatter figure denotes the correlation between sham and the first anodal tDCS session; the square scatter figure denotes correlation between sham and the second anodal tDCS session; the circle scatter figure denotes correlation between the first and the second anodal tDCS session.

3.6. Precision of qCSF Measurement

Averaged over spatial frequencies and observers, the measurement precision was 0.091±0.027, 0.088±0.021, 0.090±0.022, 0.087±0.021, 0.083±0.026, and 0.088±0.024 log10 units for pre-test CSF in the 1st tDCS session, post-test in the 1st tDCS, pre-test in the 2nd tDCS, post-test in the 2nd tDCS, pre-test in sham tDCS, and post-test in sham tDCS, respectively (Fig. 5). A repeated-measurement analysis of variance found that precision didn’t differ significantly with Test session (F_(1,26) = 0.01, p = 0.94, $η_{p}^{2} < 0.001$ ), Stimulation Condition (the 1st, the 2nd, and sham tDCS session; F_(2,52) = 0.46, p = 0.64, $η_{p}^{2} = 0.02$ ), and the interaction of the two variables (F_(2,52) = 0.38, p = 0.69, $η_{p}^{2} = 0.01$ ).

Fig.5

Measurement precision for 100 quick CSF trials. Mean CSFs estimates obtained from different stimulation conditions and test sessions. Sensitivity was plotted as a function of spatial frequency. The red, blue, and black lines are CSFs under the first anodal tDCS session, the second session, and sham session, respectively; The dash-dot and solid lines represent pre-test and post-test, respectively. The gray-shaded region reflects the variability of qCSF estimates.

Taken together, our results suggested there was no significant effect of anodal tDCS on contrast sensitivity function, either in the first or the second stimulation period, and responsiveness to tDCS may not be a reliable subject characteristic.

4. Discussion

With an efficient Bayesian CSF measurement (Lesmes et al., 2010), the current study revealed no significant off-line effects of two-session 15 min anodal tDCS on contrast sensitivity in healthy adults, although the changes in CSF varied across subjects. There was no significant correlation between CSF changes in the two anodal tDCS sessions and the sham session, unfavoring a responsiveness explanation of tDCS effects across subjects (Dyke et al., 2016; Spiegel et al., 2013a; Strube et al., 2016).

Our results were consistent with previous studies that found no significant CSFs changes in normal central vision after anodal tDCS (Antal et al., 2001; Costa et al., 2015), but were inconsistent with studies that observed improved CSFs in amblyopia (Ding et al., 2016; Spiegel et al., 2013b) and normal periphery vision (Reinhart et al., 2016) after anodal tDCS. Whether degraded vision (e.g., periphery) or abnormal vision (e.g., amblyopia) is more viable to tDCS stimulation remains to be elucidated. Moreover, there was a counterintuitive study in which contrast sensitivity at 8 cpd was attenuated after anodal tDCS (Richard et al., 2015).

Since the tDCS effect might be mild and may not last long, it is necessary to ensure CSF measurement of efficiency and precision. In the current study, we adopted an efficient Bayesian algorithm to estimate CSF (i.e., qCSF) within 100 trials (Lesmes et al., 2010). From the precision analysis mentioned above, we concluded that the effects of tDCS on contrast sensitivity cannot be reliably detected with a threshold estimation method of less than 2 dB precision. Meanwhile, the measurement precision of previous studies that adopted method of constant stimulus or adaptive staircase method was not accessible.

The qCSF method had two assumptions: (1) CSF can be characterized by a log-parabolic function (four parameters); (2) the slope of contrast response function is constant across all the spatial frequencies. Although Reinhart et al. (2016) successfully detected peripheral contrast sensitivity enhancement at high spatial frequency with same procedure (Reinhart et al., 2016), there is chance (albeit less likely) that anodal tDCS only affects contrast sensitivity at one particular frequency or some of the tested spatial frequencies, which may not be well captured by the quick procedure and needs to be further examined. In the current study, we fixed the psychometric slope at 3.5 across spatial frequencies based on the QUEST method’s slope assumptions (Yan et al., 2017). Simulation and real experimental practice have confirmed that the qCSF method works well without precise knowledge of the true slope (ranges from 1 to 3.5). Improved method that targeted at detecting sensory changes following treatment (e.g. electrical stimulation or training) shall be introduced in the future (e.g. Zhao et al., 2017).

Another potential factor that contributed to the previously observed tDCS effects was subject’s responsiveness to electrical stimulation. Previous studies usually divided all subjects into two groups according to their responsiveness, e.g. responder VS non-responder (Spiegel et al., 2013a). We argued if it is true, the so-called “responsiveness” for each individual should be consistent across multiple anodal tDCS sessions. Our correlation analysis between different stimulation sessions did not reveal any consistent CSF change in response to tDCS, suggesting that the lack of within-session tDCS effect on CSF could not be solely explained by responsiveness.

Although we did not find significant improvement in CSF after two anodal tDCS stimulation, we have no intention of denying the efficiency of tDCS in modulating visual functions. There are many factors that may impact tDCS modulation efficiency, e.g. current strength (Nitsche & Paulus, 2000), electrode position (Im et al., 2008), electrode shape (Abhishek et al., 2008), and stimulation duration (Nitsche & Paulus, 2001). By combining with other methods, e.g. repetitive training (Camilleri et al., 2014; Campana et al., 2014; Fertonani et al., 2011; Koganemaru et al., 2015), transcranial electrical stimulation had shown positive effect on modulating brain excitation. Repetition of electrical stimulation over several consecutive days can activate LTP-like molecular mechanisms (Fritsch et al., 2010). With more session’s anodal tDCS, the cellular excitability induced by tDCS might accumulate and behavioral CSF might improve. In addition to direct current stimulation, other type of transcranial electrical stimulation also showed potential to modulate brain excitation (Bola et al., 2014; Camilleri et al., 2016; Camilleri et al., 2014; Campana et al., 2014; Cancelli et al., 2015; Fertonani et al., 2011; Gall et al., 2016; Sergeeva et al., 2015). It might be interesting (and challenging) to test all these possibilities to figure out the most optimal configuration of using transcranial electrical stimulation in modulating a particular visual function.

Footnotes

Acknowledgments

This research was supported by the National Natural Science Foundation of China grant NSFC 31470983 to Chang-Bing Huang the Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences grant Y7CX332008, and Beijing Postdoctoral Research Foundation to Fang-Fang Yan, CAS Key Laboratory of Behavioral Science, Institute of Psychology.

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