Transcranial alternating current stimulation (tACS) is considered a promising non-invasive brain stimulation technique that rhythmically interacts with ongoing brain oscillations in a frequency-specific manner (Antal et al., 2008). By applying a weak sinusoidal current with alternating polarity through the scalp, tACS can entrain endogenous neural activity, potentially modulating sensory, cognitive, and affective processes (Antal and Paulus, 2013; Herrmann et al., 2013; Wischnewski et al., 2023). However, tACS is regarded as a relatively mild intervention, often yielding inconsistent results (Biačková et al., 2024; Chuderski and Chinta, 2024), facing reproducibility issues (Veniero et al., 2017), and being highly susceptible to individual variability (Krause and Cohen Kadosh, 2014; Zanto et al., 2021; Steinmann et al., 2022). Therefore, the technique would greatly benefit from using objective measures to assess brain activity dynamics during and after stimulation.

For this purpose, electroencephalography (EEG) or magnetoencephalography (MEG) is often utilized in tACS studies (Koninck et al., 2023). One particularly promising EEG/MEG paradigm to probe the effects of tACS is the steady-state response (SSR) - a periodic brain response elicited by rhythmic sensory stimulation (Tobimatsu et al., 1999; Brenner et al., 2009; Vialatte et al., 2010). SSRs can be evoked through various modalities, including visual (steady-state visually evoked potentials, SSVEPs), auditory (auditory steady-state responses, ASSRs), and somatosensory (steady-state somatosensory evoked potentials, SSSEPs) stimulation. These responses are highly reliable (Pang and Mueller, 2014; Roach et al., 2019; Fong et al., 2020) and frequency-specific (Tobimatsu et al., 1999; Ding et al., 2006; Roach et al., 2019), making them well-suited for evaluating the frequency-dependent effects of tACS. Studies have shown that tACS may modulate the magnitude and phase consistency of SSRs (Ruhnau et al., 2016a; Baltus et al., 2018; Ahn et al., 2021), potentially reflecting underlying mechanisms such as neural entrainment, resonance, and plasticity (Huang et al., 2021; Agboada et al., 2025).

The translation of tACS into clinical applications depends on identifying reliable biomarkers that index stimulation effects. Biomarkers serve as objective indicators of neuromodulatory efficacy, helping to validate mechanisms, monitor responses, and optimize individualized interventions (Wischnewski et al., 2023). SSRs are particularly attractive in this regard: they are highly reliable, frequency-specific, and can be easily recorded using non-invasive EEG/MEG during periodic sensory stimulation. Moreover, SSRs have been widely used in clinical research as markers of sensory and cognitive dysfunction in conditions such as schizophrenia (Thuné et al., 2016; Schielke and Krekelberg, 2022) or autism spectrum disorder (Pei et al., 2014; Seymour et al., 2020). At the same time, the mechanistic basis of both tACS and SSRs remains debated, and SSRs can theoretically have multiple biomarker roles - they could serve as index of (un)successful entrainment by tACS at individual level, but also be used as a biomarker for behavioral and clinical effects of tACS in the therapeutic context. Thus, a systematic review of how SSRs are modulated by tACS is needed to clarify their potential as biomarkers of stimulation effects.

Although the number of studies investigating SSR neuromodulation by tACS is still relatively limited, the field has grown considerably in recent years. Therefore, the present scoping review aims to synthesize the available tACS–SSR literature, critically evaluate the current empirical findings, identify methodological strengths and limitations, outline key directions and provide guidance for future research.

This study was conducted in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) (Tricco et al., 2018). Original research articles written in English that addressed tACS effects on SSR were included in the review. Conference papers were considered for inclusion only if they contained sufficient information regarding methods. Only works with a sample size of at least 10 participants were selected to ensure that included studies provide sufficient statistical reliability, since small pilot studies (n < 10) are particularly prone to inflated effect sizes and poor reproducibility (Button et al., 2013).

The eligibility was assessed according to PICO criteria (Table 1): (P) subjects were humans, healthy or diagnosed with neuropsychiatric disorders; (I) steady-state stimulation (visual, auditory and/or somatosensory) and tACS in any frequency were applied; (C) sham-tACS condition or SSR without tACS condition or SSR measurement pre- and post-tACS were used as control procedures; (O) changes in EEG/MEG measures (amplitude, power and/or inter-trial phase-locking) in the frequency range corresponding to steady-state stimulation frequency were assessed.

The search was carried out in February 2025. To identify relevant articles, PubMed, Scopus and Web of Science were searched for the keywords “steady state response,” “steady state evoked potential,” “sensory entrainment,” “auditory steady state response,” “ASSR,” “steady state visual evoked potential,” “steady state visually evoked potential,” “visually evoked steady state response,” “SSVEP,” “steady state somatosensory evoked potential,” “SSSEP” in combination with “tACS,” “transcranial alternating current stimulation.” To ensure that other relevant articles were not missed, bibliographies of the works identified via databases were screened, and an additional non-systematic search was carried out in Google Scholar using keywords “steady state” and “transcranial alternating current stimulation”.

After removing the duplicates, titles and abstracts of the identified articles were screened to exclude irrelevant works. Methods part and, if necessary, the whole text and supplementary materials of the remaining records were checked to be evaluated according to eligibility criteria (Table 1).

From each included study, the following information was extracted: (1) sample (type, size, age, gender composition); (2) tACS settings (montage, intensity, frequency, duration); (3) control group/condition; (4) experimental design; (5) auditory stimulation settings (frequency, intensity, duration); (6) methods to measure SSR; (7) SSR results; (8) behavioral outcomes. If the publication included multiple studies/experiments, each was analyzed separately.

In total, the database search yielded 61 entries (Figure 1). Duplicates were removed, and titles and abstracts of 27 articles were screened. Nine papers were excluded after the initial screening: two reviews, two works in which tACS was not utilized, a study protocol, an already-published preprint (i.e., duplicate publication), a paper presenting a dataset, one work where the SSR paradigm was not used, and one study unrelated to the topic. After thoroughly screening the remaining eighteen articles, six works were excluded due to small sample sizes (n = 2) or the absence of SSR amplitude, power, or phase-locking analysis (n = 4). Seven other papers were found via bibliography search and Google Scholar, of which three were conference abstracts and were excluded due to insufficient information. A total of sixteen articles were included in the present review. Eleven of the included studies evaluated ASSR, and the remaining five assessed SSVEP. The information extracted from the studies is summarized separately for ASSR and SSVEP.

The present review shows that research combining tACS with SSR paradigms has grown substantially in recent years offering a unique opportunity for probing oscillatory brain dynamics. Since the last review on tES effects on ASSR (Griskova-Bulanova et al., 2020), the number of works investigating the modulation of ASSR using tACS has increased from 3 to 11. In addition, five tACS-SSVEP studies were featured in this review. TACS-SSR is a promising paradigm that could provide valuable insights into tACS neurophysiological and behavioral effects, yet the variability in reported effects underscores the need for a clearer mechanistic framework.

A key point concerns the neurophysiological basis of both tACS and SSRs. While entrainment of endogenous oscillations has often been proposed as the common mechanism underlying both phenomena (Thut et al., 2011), accumulating evidence suggests a more complex picture. For tACS, recent critical review of neurocognitive, physiological, and biophysical effects highlights entrainment of endogenous oscillations as a central mechanism but also presents evidence of additional effects, including shifts in neural spike timing, alterations in interregional coherence and connectivity, and even broader homeostatic or metabolic changes (Wischnewski et al., 2023). Similarly, the after-effects of tACS have been attributed to multiple forms of plasticity, such as spike-timing-dependent plasticity, spike-phase and oscillation coupling, homeostatic and state-dependent modulation (Agboada et al., 2025).

The neurophysiological basis of SSRs is likewise not unitary (Bánki et al., 2022). Several works showed a high correspondence between recorded SSRs and a synthesized waveform of linearly summated transient evoked responses to discrete stimuli (Azzena et al., 1995; Bohórquez and Özdamar, 2008; Capilla et al., 2009, 2011), suggesting that SSRs may rely on the same underlying mechanism as sensory evoked potentials and occur independently of the ongoing intrinsic oscillations. However, a larger body of evidence favors the entrainment of ongoing activity via resonant frequencies (Johnson et al., 2024) or the activation of separate rhythms by stimulation (Welle and Contreras, 2016; Duecker et al., 2021). Moreover, SSRs (1) reflect changes in neural activity in neuropsychiatric conditions (Yamasaki, 2021; Grent-‘t-Jong et al., 2023) or due to pharmacological modulation (Bale et al., 2005; Sullivan et al., 2015), (2) are associated with behavioral measures (Richard et al., 2020; Parciauskaite et al., 2021), and (3) are stronger and more synchronized at frequencies matching intrinsic individual-specific frequencies (Zaehle et al., 2010; Notbohm et al., 2016). Furthermore, prolonged rhythmic sensory stimulation has shown promise in modulating neurobiological (Martorell et al., 2019; Rodrigues-Amorim et al., 2024), neurophysiological (Lin et al., 2021; Pinardi et al., 2024) and behavioral (Sharpe et al., 2020; Cimenser et al., 2021) outcomes in both animals and humans. Together, these findings point to the potential interaction of periodic sensory stimulation with intrinsic brain oscillations.

Motivated by the notion of shared neural entrainment mechanisms hypothesized for both tACS and SSRs (Thut et al., 2011), several of the reviewed studies combined SSRs with tACS, aiming to investigate various factors related to tACS effects mechanistically. Among ASSR studies, low-frequency tACS was generally used to probe cross-frequency interactions (Hyvärinen et al., 2018; Wang et al., 2021, 2023; Mockevicius et al., 2025), while gamma tACS was utilized to study how tACS affects endogenous oscillations at a matched frequency (Jones et al., 2020; Wang et al., 2023). SSVEP paradigm was employed to evaluate the impact of tACS intensity (Dowsett et al., 2020), frequency (Ruhnau et al., 2016a; Dowsett et al., 2020; Liu et al., 2021), and phase (Fiene et al., 2020; Haslacher et al., 2023) on rhythmic brain activity. In addition, among the reviewed studies, SSRs were evaluated as biomarkers, assessing the link between SSRs and behavioral effects of tACS, including symptom severity in patients with MdDS (Ahn et al., 2021), schizophrenia (Ahn et al., 2019), and dyslexia (Marchesotti et al., 2020; Rufener et al., 2023) or sensory task performance in healthy participants (Baltus et al., 2018).

Given that tACS is oscillatory in nature, the frequency of stimulation is a fundamental parameter. The selection of tACS frequency among the reviewed studies mainly differed based on goals and the putative mechanisms of action. In ASSR studies, gamma tACS was delivered to enhance synchronized neural activity at specific gamma-range frequencies. However, the results are mixed as studies showed either a predicted increase (Baltus et al., 2018; Jones et al., 2020; Marchesotti et al., 2020; Rufener et al., 2023) or no change (Wang et al., 2023; de la Salle et al., 2024). Due to the general inhibitory role of alpha activity (Jensen and Mazaheri, 2010; Mathewson et al., 2011), potentially mediated via alpha-gamma cross-frequency interactions, alpha tACS was primarily selected to suppress gamma synchronization. While this alpha tACS effect was reported in MdDS patients (Ahn et al., 2021) as well as healthy participants (Hyvärinen et al., 2018; Wang et al., 2023), an increase in ASSR was also shown in schizophrenia patients (Ahn et al., 2019). de la Salle et al. (2024) expected increased gamma ASSR due to theta tACS based on theta-gamma phase-amplitude coupling, but the authors observed an ASSR reduction. Other studies showed no theta tACS effects on gamma ASSR (Hyvärinen et al., 2018; Mockevicius et al., 2025). Among the studies assessing SSVEP, the general aim was to enhance theta or alpha activity using a congruent tACS frequency; however, the effect was shown to depend on the phase lag between visual flicker and tACS delivered online (Fiene et al., 2020; Haslacher et al., 2023). When the frequencies of visual flicker and tACS did not match, no change in SSVEP was reported (Ruhnau et al., 2016a; Dowsett et al., 2020).

Overall, the reviewed findings suggest that tACS effects on SSRs depend on sensory and electrical stimulation frequencies. However, there is a substantial variability in the reported findings, especially among ASSR studies, which likely arose due to differences in methodology and sample characteristics. When gamma tACS was used, promising results were reported in studies with specific a priori hypotheses about disturbances of gamma oscillations in clinical groups or the relationship of gamma activity with targeted sensory processing. In two studies, the applied approaches were based on the hypothesis of reduced peak frequency of gamma oscillations in dyslexia. Marchesotti et al. (2020) showed an increase in 30-Hz ASSR after 30-Hz tACS, while Rufener et al. (2023) reported an increase in both IGF and response at IGF after 40-Hz tACS. Improvements in language task performance were also shown in both studies. In addition, Baltus et al. (2018) hypothesized that IGF can be related to auditory temporal acuity and showed that tACS applied at a frequency slightly above IGF increased ASSR at the corresponding frequency and improved auditory gap detection performance in healthy subjects. Other studies targeted the classical 40-Hz ASSR using the same frequency tACS in healthy young subjects. Of them, only Jones et al. (2020) reported an increase in ASSR, while in two studies ASSR remained unchanged (Wang et al., 2023; de la Salle et al., 2024). The latter two studies are characterized by small sample sizes (23 and 11 subjects), which could have contributed to a lack of significant effects. TACS is a relatively mild non-invasive intervention that is generally characterized by modest to moderate effect sizes (Grover et al., 2023). In addition, healthy participants are expected to be more resilient to external perturbations (Hall et al., 2020), which is likely applicable to ASSR due to its high individual stability (Van Eeckhoutte et al., 2018; Roach et al., 2019). Due to these factors, larger sample sizes may be needed to detect ASSR changes after matched frequency tACS.

Similarly, studies using low-frequency tACS and gamma ASSR also showed inconsistent outcomes. Patient sample characteristics may explain the differences in clinical studies using alpha tACS. Given that MdDS is characterized by gamma hypersynchrony, alpha entrainment by tACS may have normalized excessive gamma activity, potentially due to its inhibitory influence (Ahn et al., 2021). Conversely, since schizophrenia patients exhibit inadequate oscillatory activity in both alpha and gamma bands (Uhlhaas et al., 2008), alleviating alpha disturbances may have also contributed to improved gamma synchronization due to alpha-gamma interactions (Jensen and Mazaheri, 2010) as evidenced by increased ASSR (Ahn et al., 2019).

Theta tACS was used in three studies, showing either reduced (de la Salle et al., 2024) or unchanged (Hyvärinen et al., 2018; Mockevicius et al., 2025) ASSR. Montage choice may have contributed to mixed results. Despite the overall low focality of tACS, the induced electric field strength differs substantially across configurations (Guidetti et al., 2022), and this variability likely contributes to inconsistent outcomes. Hyvärinen et al. (2018) and De la Salle et al. (2024) applied theta tACS over bilateral temporal regions, whereas Mockevicius et al. (2025) targeted posterior parietal cortex. Since ASSR is mainly generated in the auditory cortex (Pantev et al., 1996), ASSR may have been less sensitive to tACS applied over a more distant location from its primary source. Also, authors highlight the role of individual variability as contributing to insignificant findings at the group level (Mockevicius et al., 2025). Meanwhile, the study by Hyvärinen et al. (2018), contains methodological limitations that hinder clear interpretation of the findings. Online theta and alpha tACS were applied for different durations - 1 min and 5 min, respectively. Although the authors partly accounted for this by comparing ASSR during theta and alpha tACS in 1-min time window, ASSR during alpha tACS was compared to no-tACS ASSR over the whole 5-min window, likely resulting in different signal-to-noise ratios and differences in the overall state. Both tACS conditions showed ASSR suppression descriptively, but only alpha tACS produced a statistically significant effect. However, ASSR did not differ between theta and alpha tACS conditions, suggesting no frequency-specific effects on ASSR (Hyvärinen et al., 2018).

Studies combining visual flicker with tACS were more methodologically homogeneous and reported consistent findings. All studies recruited only healthy participants and targeted posterior areas (occipital or parietal) using low frequency (alpha and/or theta) tACS, unanimously showing significant tACS effects when flicker and tACS frequencies were matched. In addition, four out of five studies used online tACS combined with visual stimulation. Three works used artifact-removal methods (Ruhnau et al., 2016a; Dowsett et al., 2020; Haslacher et al., 2023), whereas Fiene et al. (2020) analyzed uncontaminated parts of the signal immediately following online tACS. These approaches allowed for more precise and robust mechanistic investigations, such as phase-dependence of tACS-SSVEP outcomes (Fiene et al., 2020; Haslacher et al., 2023). In addition, given that tES effects are network-activity-dependent (Fertonani and Miniussi, 2017), online tACS in SSVEP studies could have contributed to more pronounced and thus more consistent effects when compared to ASSR studies that applied tACS offline. While analyzing ASSR recorded during simultaneous tACS application could be challenging due to inherently weaker gamma response as compared to low-frequency SSVEP, assessing ASSR immediately following online tACS (Fiene et al., 2020) or using non-overlapping tACS and ASSR frequencies and their harmonics (Hyvärinen et al., 2018) may be promising strategies for future online tACS-ASSR studies.

However, it is essential to mention that only one tES-SSVEP study reported significant changes in behavioral measures (Haslacher et al., 2023), likely due to the generally mechanistic nature of the studies. Firstly, only healthy participants were recruited. It has been suggested that tACS may be more beneficial for patients with psychiatric disorders as compared to healthy individuals (Lee et al., 2022). In line with this, among ASSR studies, significant behavioral effects of tACS were mainly evident in clinical populations (Ahn et al., 2019, 2021; Marchesotti et al., 2020; Rufener et al., 2023), with only Baltus et al. (2018) reporting changes in auditory perception in healthy participants. These findings fit the inverted U-shaped relationship between baseline neural activity and stimulation outcomes (Rufener et al., 2016; Ruhnau et al., 2016b; Tseng et al., 2018; Krause et al., 2022). Namely, tACS appears most effective when intrinsic oscillatory activity is suboptimal, as observed in clinical populations with reduced or dysregulated neural synchrony. In contrast, when baseline activity in healthy brains is already near optimal, tACS may have little or even disruptive effects. This principle may help reconcile why tACS robustly enhanced ASSRs in dyslexia or schizophrenia, yet yielded inconsistent effects in healthy participants. Secondly, in two studies (Fiene et al., 2020; Ruhnau et al., 2016a), the intermittent pattern of tACS might have been inadequate for behavioral modulation as it may require longer-lasting entrainment (Strüber et al., 2015). Furthermore, the differences in behavioral tasks should be taken into consideration. For example, Haslacher et al. (2023) studied binocular dominance and observed its relationship with SSVEP modulation. Conversely, Liu et al. (2021) analyzed Go/NoGo performance, showing no changes after tACS. While the former assessed lower-level perceptual processing, the Go/NoGo task in the latter study relies on multiple higher-order cognitive processes (e.g., inhibitory control, Bokura et al. (2001)), potentially making it less sensitive to tACS applied over the occipital region.

Given the complex and still-explored mechanisms underlying both tACS effects and SSRs, the heterogeneous findings are no surprise. At a neurophysiological level, tACS may interact with SSRs in multiple ways: (1) by entraining intrinsic neural oscillators at the stimulation frequency, thereby enhancing resonance phenomena, supported by cross-frequency interactions in ASSR studies and the reported relationships with behavioral measures; (2) by modulating the amplitude of repetitive evoked responses without necessarily engaging endogenous oscillators, which is in line with more consistent results when tACS frequency and phase were matched with those of SSRs; or (3) by periodically biasing membrane potential fluctuations, which can alter responsiveness to incoming rhythmic sensory input. Distinguishing these mechanisms remains challenging, yet it is critical for interpreting whether reported SSR modulations index genuine entrainment or altered evoked responses.

Taken together, the reviewed evidence suggests that tACS exerts neurophysiological effects which may be reflected in changes to SSR amplitude, power, or phase-locking, likely indexing the entrainment of intrinsic oscillations or the modulation of evoked responses. These tACS-induced changes may manifest behaviorally, e.g., as improved clinical symptoms, auditory gap detection or reading performance, which appear to be more consistent when tACS restores or enhances oscillatory activity in populations with atypical baseline activity (e.g., dyslexia, schizophrenia). These differences highlight that tACS effects are not uniform but depend on the interplay between stimulation parameters and the brain state of the participant. This mechanistic perspective can explain why SSRs may serve as both biomarkers of neural entrainment and predictors of behavioral outcomes, adding to their translational value.

The findings reviewed in the present work contribute to the existing literature by showing that tACS neurophysiological and behavioral effects depend on both extrinsic (methodology-related) and intrinsic (brain-activity-related) factors. Accordingly, future studies should focus on adapting tACS-SSR procedures to the specific aims and participant populations. When investigating tACS mechanisms of action using SSRs, online tACS would be preferred due to the possibility of applying precise experimental manipulations. Offline tACS may be suitable when assessing its potential as a biomarker of tACS-induced behavioral changes. In particular, tACS protocols aiming to improve a specific sensory or cognitive domain may include the combination of tACS with online behavioral tasks (e.g., Bjekić et al., 2022). Therefore, SSRs would be limited to offline use in these approaches. However, based on the reviewed findings, offline tACS may require a careful and theoretically grounded selection of protocol parameters as well as higher sample sizes.

In summary, this review advances the field by summarizing up to date literature on tACS-SSR interaction. This review synthesizes cross-study patterns and identifies three converging insights: (1) congruence between sensory and electrical stimulation frequencies is the most reliable determinant of tACS effects on SSRs; (2) variability in baseline oscillatory dynamics is expected to modulate the effects of tACS-SSR applications, which may result in differential outcomes across healthy and clinical populations; and (3) methodological differences, particularly online vs. offline designs, account for the variability and heterogeneity of the observed effects. Together, these insights advance a conceptual framework for using SSRs not only as mechanistic probes of entrainment but also as candidate biomarkers of tACS efficacy.