Here, we describe a protocol for using transcranial direct current stimulation for psycho- and neurolinguistic experiments aimed at studying, in a naturalistic yet fully controlled way, the role of cortical areas of the human brain in word learning, and a comprehensive set of behavioral procedures for assessing the outcomes.
Language is a highly important yet poorly understood function of the human brain. While studies of brain activation patterns during language comprehension are abundant, what is often critically missing is causal evidence of brain areas' involvement in a particular linguistic function, not least due to the unique human nature of this ability and a shortage of neurophysiological tools to study causal relationships in the human brain noninvasively. Recent years have seen a rapid rise in the use of transcranial direct current stimulation (tDCS) of the human brain, an easy, inexpensive and safe noninvasive technique that can modulate the state of the stimulated brain area (putatively by shifting excitation/inhibition thresholds), enabling a study of its particular contribution to specific functions. While mostly focusing on motor control, the use of tDCS is becoming more widespread in both basic and clinical research on higher cognitive functions, language included, but the procedures for its application remain variable. Here, we describe the use of tDCS in a psycholinguistic word-learning experiment. We present the techniques and procedures for application of cathodal and anodal stimulation of core language areas of Broca and Wernicke in the left hemisphere of the human brain, describe the procedures of creating balanced sets of psycholinguistic stimuli, a controlled yet naturalistic learning regime, and a comprehensive set of techniques to assess the learning outcomes and tDCS effects. As an example of tDCS application, we show that cathodal stimulation of Wernicke's area prior to a learning session can impact word learning efficiency. This impact is both present immediately after learning and, importantly, preserved over longer time after the physical effects of stimulation wear off, suggesting that tDCS can have long-term influence on linguistic storage and representations in the human brain.
The neurobiological mechanisms of human language function are still poorly understood. As the bedrock of our communication ability, this unique human neurocognitive trait plays a particularly important role in our personal and socio-economic lives. Any deficits affecting speech and language are devastating for the sufferers and expensive for the society. At the same time, in the clinic, procedures for treatment of speech deficits (such as aphasia) remain suboptimal, not least due to poor understanding of the neurobiological mechanisms involved1. In research, the recent advent and rapid development of neuroimaging methods have led to multiple discoveries describing activation patterns; yet, causal evidence is often still lacking. Furthermore, language areas of the brain are located somewhat suboptimally for application of mainstream neurostimulation approaches which can provide causal evidence, most importantly the transcranial magnetic stimulation technique (TMS). Whereas offline TMS protocol, such as theta burst stimulation, can cause pain due to the close proximity of the muscles to the point of stimulation, "online" TMS protocols can introduce sound artifacts from stimulation, which is undesirable due to interference with linguistic stimulus presentation2. Even though TMS is widely used in language studies despite such inconveniences, a welcome alternative may be provided by other stimulation methods, most notably transcranial direct-current stimulation (tDCS). In recent years, tDCS has seen a remarkable growth in its use due to its accessibility, ease of use, relative safety and often rather striking outcomes3. Even though the exact mechanisms underpinning tDCS influence on neural activity are not understood completely, the mainstream view is that, at least at low intensity levels (typically 1-2 mA for 15-60 min), it does not cause any neural excitation or inhibition per se, but instead modulates the resting transmembrane potential in a graded way towards de- or hyperpolarization, shifting the excitation thresholds up or down and thereby making the neural system more or less susceptible to modulations by other events, stimuli, states or behaviors4,5. Whereas most of the applications reported to date have focused on the motor function6 and/or motor system deficits, it has been increasingly applied to higher-level cognitive functions and their respective disabilities. There has been a rise in its application to speech and language, mostly in research aimed at the recovery of post-stroke aphasia7,8,9, even though it has so far led to mixed results with respect to the therapeutic potential, stimulation sites and hemispheres, and optimal current polarity. As this research, and particularly the application of tDCS in cognitive neurobiology of normal language function, is still in its infancy, it is crucial to delineate procedures for stimulating at least the core language cortices (most importantly Wernicke's and Broca's areas) using tDCS, which is one of the main aims of the current report.
Here, we will consider application of tDCS to language areas in a word-learning experiment. In general, the case of word learning is taken here as one example of a neurolinguistic experiment, and the tDCS part of the procedure should not change substantially for other types of language experiments targeting the same areas. Yet, we use this opportunity to also highlight major methodological considerations in a word acquisition experiment per se, which is the second main aim of the current protocol description. Brain mechanisms underpinning word acquisition – a ubiquitous human capacity at the core of our linguistic communication skill – remain largely unknown10. Complicating the picture, existing literature differs widely in how experimental protocols promote word acquisition, in control over stimulation parameters, and in tasks used to assess learning outcomes (see, e.g., Davis et al.11). Below, we describe a protocol that uses highly controlled stimuli and presentation mode, while ensuring a naturalistic context-driven acquisition of novel vocabulary. Furthermore, we use a comprehensive battery of tasks to assess the outcomes behaviorally at different levels, both immediately after learning and following an overnight consolidation stage. This is combined with sham and cathodal tDCS of language areas (we make a particular example using Wernicke's area stimulation) which can provide causal evidence on underlying neural processes and mechanisms.
All procedures were approved by the local research ethics committee of St. Petersburg State University, St. Petersburg, with consent obtained from all participants.
NOTE: All participants must sign the informed consent and fill in a questionnaire to attest the absence of any contraindications for tDCS stimulation (see Technique and Considerations in the Use of 4 x 1 Ring High-definition Transcranial Direct Current Stimulation (HD-tDCS) by Willamar and colleagues12) and to collect other data relevant to the study such as vision acuity, demographics, language experience and handedness. For the latter, the seminal work by Oldfield13 is recommended.
1. Subjects and experimental environment
2. Stimulus preparation
3. Sentence stimuli for contextual semantic learning
4. Tasks to assess acquisition of new word forms and novel meanings
NOTE: Use several tasks to assess different levels of acquisition and comprehension of both surface word forms and lexical semantics. Five tasks are used in the present protocol: free recall, cued recognition, lexical decision, semantic definition and semantic matching. The tasks are applied in the order they are listed below, which was optimized to reduce any carryover between successive tasks.
5. Procedures
6. Data analysis
While the data were analyzed for the specific set of tasks, it should be emphasized that the developed set of tests and the paradigm could be adapted to a variety of psycholinguistic experiments. The results were analyzed in terms of accuracy scores (number of correct answers) and the reaction time (RT) using non-parametric Wilcoxon signed rank test and Mann-Whitney U test across groups (cathodal and sham stimulation conditions). Significant differences for tasks within each group are presented in Table 3; below, we highlight the main stimulation-related results (for descriptive statistic see Table 2).
The comparison of performance in lexical decision task between the two groups (cathodal versus sham stimulation conditions) showed differences on the first day between accuracy for competitor pseudowords: accuracy increased more after cathodal than after sham stimulation (р ≤ 0.041), suggesting reduced lexical competition after cathodal stimulation. In the recognition task, accuracy for novel words was better after sham than after cathodal stimulation both on the first (р ≤ 0.034) and on the second (р ≤ 0.09) day, suggesting reduced lexical learning efficiency after stimulation. Neither of the tasks showed differences in RT between groups. The results of the semantic tasks showed the matching between the novel form meaning and the surface form was more successful for cathodal group over sham on the second day only (р ≤ 0.011).
Within each group, there were notable differences in accuracy scores and reaction times between the two assessment sessions. In the sham group, novel word recognition was better on the first than on the second day (р ≤ 0.049). In the cathodal group, RT in the recognition task was significantly shorter for novel words than for competitor pseudowords on the first day (р ≤ 0.042), but not on the second one. The results of lexical decision task showed that after cathodal stimulation on the first (р ≤ 0.003) and on the second day (р ≤ 0.001), there was better performance for novel words than for pseudoword competitors. In the sham group, however, this effect was observed on the second day only (р ≤ 0.002).
Figure 1: Experimental chamber. Please click here to view a larger version of this figure.
Figure 2: Procedure for presenting stimuli in contextual learning sequence. (A) Making stimulus groups: Groups of word/pseudoword stimuli. (B) Diagram of stimulus presentation in contextual learning block. Please click here to view a larger version of this figure.
Figure 3: Location of stimulation electrode for the Wernicke's and Broca's areas. Left panel: Side view and projection on brain areas. Brain zones, EEG electrodes (system 10-20%) corresponding to them, and red rectangles representing the location of stimulating electrodes are marked. The reference electrode is shown at the base of the neck. Right panel: Projection of the stimulating electrode on the EEG 10-20% system layout. Please click here to view a larger version of this figure.
Figure 4: tDCS equipment. (A) Stimulator; (B) saline; (C) electrodes Please click here to view a larger version of this figure.
Examples of sentences |
Нашим бабушкам было неведомо такое чувство как мушкелак. Our grandmothers did not know such a feeling as mushkelak. |
Благодаря своей хорошей памяти, Маша не чувствовала мушкелак. Thanks to her good memory, Masha never experienced any mushkelak. |
Заведя сразу несколько аккаунтов, я начал испытывать мушкелак. Having got a few accounts, I started suffering from mushkelak. |
Секретный блокнот поможет решить такую проблему как мушкелак. A secret notebook could help you solve the problem of mushkelak. |
Петр устанавливал одинаковые пароли, не желая ощущать мушкелак. Peter always set the same password as he did not want to have any mushkelak. |
Table 1: Examples of sentences for contextual learning of novel words.
Sham stimulation | Cathodal stimulation | ||||
Mean | SD | Mean | SD | ||
Task 1: free recall | |||||
Day 1 | Accuracy | 4.91 | 2.22 | 5.69 | 1.49 |
Day 2 | Accuracy | 2.53 | 2.44 | 2.84 | 2.26 |
Task 2: recognition. Accuracy scores | |||||
Day 1 | Novel words | 3.06 | 0.89 | 1.96 | 1.68 |
Competitor words | 3.63 | 1.14 | 3.73 | 1.29 | |
Competitor pseudowords | 2.60 | 1.15 | 2.69 | 1.39 | |
Control pseudowords | 3.79 | 1.32 | 3.92 | 1.41 | |
Control words | 4.67 | 1.05 | 4.29 | 1.16 | |
Day 2 | Novel words | 2.58 | 0.93 | 1.56 | 1.47 |
Competitor words | 4.40 | 0.74 | 4.10 | 1.39 | |
Competitor pseudowords | 3.13 | 1.25 | 3.31 | 1.00 | |
Control pseudowords | 4.33 | 0.92 | 4.50 | 1.14 | |
Control words | 4.58 | 1.02 | 4.38 | 1.44 | |
Task 2: recognition. Reaction time (ms) | |||||
Day 1 | Novel words | 793 | 167 | 858 | 183 |
Competitor words | 804 | 151 | 845 | 179 | |
Competitor pseudowords | 883 | 261 | 962 | 306 | |
Control pseudowords | 849 | 201 | 833 | 234 | |
Control words | 699 | 131 | 767 | 196 | |
Day 2 | Novel words | 836 | 200 | 933 | 272 |
Competitor words | 816 | 239 | 818 | 213 | |
Competitor pseudowords | 859 | 281 | 924 | 236 | |
Control pseudowords | 818 | 280 | 866 | 265 | |
Control words | 734 | 212 | 817 | 234 | |
Task 3: lexical decision. Accuracy scores | |||||
Day 1 | Novel words | 2.42 | 1.63 | 1.96 | 1.68 |
Competitor words | 4.13 | 0.78 | 4.10 | 0.90 | |
Competitor pseudowords | 3.46 | 1.17 | 4.02 | 1.33 | |
Control pseudowords | 4.21 | 1.02 | 4.25 | 1.26 | |
Control words | 4.54 | 0.72 | 4.54 | 0.78 | |
Day 2 | Novel words | 2.04 | 1.47 | 1.56 | 1.47 |
Competitor words | 4.38 | 0.56 | 4.46 | 0.61 | |
Competitor pseudowords | 3.81 | 1.08 | 3.94 | 1.39 | |
Control pseudowords | 4.54 | 0.78 | 4.58 | 1.28 | |
Control words | 4.42 | 0.72 | 4.63 | 0.71 | |
Task 3: lexical decision. Reaction time (ms) | |||||
Day 1 | Novel words | 817 | 244 | 921 | 248 |
Competitor words | 747 | 181 | 797 | 201 | |
Competitor pseudowords | 927 | 307 | 910 | 265 | |
Control pseudowords | 891 | 291 | 852 | 213 | |
Control words | 737 | 217 | 784 | 221 | |
Day 2 | Novel words | 878 | 287 | 963 | 292 |
Competitor words | 743 | 174 | 811 | 197 | |
Competitor pseudowords | 914 | 290 | 918 | 244 | |
Control pseudowords | 871 | 286 | 853 | 244 | |
Control words | 719 | 189 | 756 | 234 | |
Task 4: semantic definition | |||||
Day 1 | Matching | 1.27 | 0.75 | 1.87 | 1.45 |
Accuracy | 7.97 | 4.03 | 8.71 | 5.66 | |
Day 2 | Matching | 0.52 | 0.79 | 1.39 | 1.44 |
Accuracy | 2.82 | 2.73 | 5.86 | 5.74 | |
Task 5: semantic matching | |||||
Day 1 | Accuracy | 3.16 | 0.97 | 3.18 | 1.03 |
Reaction time (ms) | 10914 | 3391 | 10856 | 6039 | |
Day 2 | Accuracy | 2.41 | 1.07 | 2.89 | 1.25 |
Reaction time (ms) | 8798 | 2488 | 8908 | 3419 |
Table 2: Descriptive statistics.
Sham stimulation | p-value | Cathodal stimulation | p-value | |
Task 1: free recall. Accuracy scores | ||||
Between days | Accuracy scores Day 1 vs. accuracy scores Day 2 | 0.001 | Accuracy scores Day 1 vs. accuracy scores Day 2 | <0.001 |
Task 2: recognition. Accuracy scores | ||||
Day 1 | Novel words vs. | ─ | Novel words vs. | ─ |
Competitor words | 0.042 | Competitor words | 0.004 | |
Control pseudowords | 0.041 | Competitor pseudowords | 0.045 | |
Control words | 0.001 | Control pseudowords | 0.002 | |
─ | ─ | Control words | <0.001 | |
Day 2 | Novel words vs. | ─ | Novel words vs. | ─ |
Competitor words | 0.001 | Competitor words | <0.001 | |
Control pseudowords | 0.001 | Competitor pseudowords | 0.001 | |
Control words | 0.001 | Control pseudowords | <0.001 | |
─ | ─ | Control words | <0.001 | |
Between days | Novel words | 0.049 | Competitor words | 0.036 |
Competitor words | 0.011 | Competitor pseudowords | 0.024 | |
Competitor pseudowords | 0.034 | Control pseudowords | 0.020 | |
Control pseudowords | 0.030 | ─ | ─ | |
Recognition. Reaction time (ms) | ||||
Day 1 | Novel words vs. Control words | 0.005 | Novel words vs. | ─ |
Competitor pseudowords | 0.042 | |||
Control words | 0.006 | |||
Day 2 | Novel words vs. Control words | 0.007 | Novel words vs. | ─ |
Competitor words | 0.001 | |||
Control pseudowords | 0.045 | |||
Control words | 0.014 | |||
Task 3: lexical decision. Accuracy scores | ||||
Day 1 | Novel words vs. | ─ | Novel words vs. | ─ |
Competitor words | 0.001 | Competitor words | <0.001 | |
Control pseudowords | 0.001 | Competitor pseudowords | 0.003 | |
Control words | 0.001 | Control pseudowords | 0.001 | |
─ | ─ | Control words | <0.001 | |
Day 2 | Novel words vs. | ─ | Novel words vs. | ─ |
Competitor words | 0.001 | Competitor words | <0.001 | |
Competitor pseudowords | 0.002 | Competitor pseudowords | 0.001 | |
Control pseudowords | 0.001 | Control pseudowords | <0.001 | |
Control words | 0.001 | Control words | <0.001 | |
Between days | No significant differences | ─ | Control pseudowords | 0.033 |
Lexical decision. Reaction time (ms) | ||||
Day 1 | Novel words vs. | Novel words vs. | ─ | |
Competitor words | 0.022 | Competitor words | 0.001 | |
Competitor pseudowords | <0.001 | Control words | 0.013 | |
Control pseudowords | 0.033 | ─ | ─ | |
Day 2 | Novel words vs. | ─ | Novel words vs. | ─ |
Competitor words | 0.003 | Competitor words | 0.003 | |
Control words | 0.008 | Control words | 0.001 | |
Task 4: semantic definition. Matching and Accuracy scores | ||||
Between days | Matching scores Day 1 vs. matching scores Day 2 | 0.001 | Matching scores Day 1 vs. matching scores Day 2 | 0.006 |
Accuracy scores Day 1 vs. accuracy scores Day 2 | 0.001 | Accuracy scores Day 1 vs. accuracy scores Day 2 | <0.001 | |
Task 5: semantic matching. Accuracy scores | ||||
Between days | Accuracy scores Day 1 vs. accuracy scores Day 2 | 0.006 | No significant differences | ─ |
Semantic matching. Reaction time (ms) | ||||
Between days | Reaction time Day 1 vs. reaction time Day 2 | 0.002 | Reaction time Day 1 vs. reaction time Day 2 | 0.015 |
Table 3: Significant differences in accuracy scores and reaction times within each group (sham and cathodal stimulations). The values in parentheses are the mean scores and the reaction times.
The results highlight a few important points that need to be taken into account when conducting psycholinguistic research in general, and neurolinguistics tDCS studies in particular. Stimulation of language cortices (exemplified here by Wernicke's area) produces a complex pattern of behavioral outcomes. Unlike the TMS technique, where it is possible to fully disrupt speech processing (e.g., the so-called "speech arrest" protocol)21, this method enables a possibly more complex, graded and subtle influence on the language processing mechanisms. We have found a variety of both accuracy and reaction time differences which diverged substantially between conditions, tests and assessment days. The technical implications of the protocol reported are briefly discussed below.
To disengage the various effects, a battery of different tests is needed, which could test for processes at different levels of short- and long-term memory, lexical access, semantic processing, etc. For example, the effects here include different performance in recall and recognition for different stimulus types and stimulation conditions, which suggests differential lexical competition effects for novel and old items, and diverging effects of tDCS at lexical and semantic levels. Our results confirm sensitivity of the utilized tasks to efficiency of novel word acquisition at different levels, including recognition, understanding of a word meaning and free recall.
In the same way, a tDCS condition (e.g., anodal, cathodal stimulation) requires a proper control condition (or control group), sham (placebo) stimulation being the most appropriate baseline. Unlike electrical stimulation of the motor cortex, the effects may not always be unambiguous22, they strongly depend on the tests used, or may not appear at all23.
Another very important point is that only one type of stimulation could be applied in each individual subject in the context of a single experimental session. This normally entails a between-group design, for instance, an anodal stimulation group, a cathodal stimulation group, and a placebo (sham) control group. For within-group designs, use different tDCS protocol on different days, at least 24 h apart (in learning studies, this also entails using different linguistic stimuli on different days to avoid contamination of results by repetition effects). The present report uses an experiment with cathodal stimulation of Wernicke's areas as an example, but similar procedures apply to other polarities/sites.
Contextual presentation of new words significantly expands the possibilities of simultaneous study of acquisition of word form per se and of its semantics. Traditionally, these processes are studied separately focusing either on the acquisition of a new word form or on the correlation of a meaning of a familiar word with other semantic units24,25,26. The proposed protocol combines both aims; therefore, it is possible to compare the dynamics of a new concept acquisition at the level of word form perception and that of mastering its content, which is achieved by using a comprehensive set of tests. The need for such a comparison is emphasized here by diverging dynamics of performance on novel surface forms recall and recognition as opposed to semantic matching.
It is important to remember the main differences between tDCS and other non-invasive brain stimulation methods, such as TMS. Since there is no simple way to determine individual sensitivity to tDCS by threshold assessment, a single protocol is applied for all subjects. It is very difficult to accurately estimate the stimulation area – one can only speak about the approximate/hypothetical area being stimulated. It is also difficult to estimate the duration of offline stimulation effects after the current is turned off. Presumably, the main effects of stimulation are observed up to one hour after the termination of stimulation. However, the effects can sometimes be detected even one day after the stimulation20.
Yet, compared with TMS, the relative ease of application of tDCS, the substantially lower risk of side effects and the absence of acoustic artifacts make this protocol attractive for studying the speech and language function. It is also worth noting that the combination of electrical stimulation with other methods, for example with TMS, fMRI, EEG or pharmacological intervention, allows studying neuronal mechanisms of tDCS in more detail27,28.
Since tDCS stimulation is not highly localized, a non-specific effect is possible. This is obvious from the existing evidence, where very different or even opposite protocols may sometimes lead to similar results. This may be due to the general impact on other cognitive functions and processes such as attention, retrieval from memory, and so on. A specialized battery of tests is needed to detect the effects associated with a particular language feature. Following the proposed steps of the stimulus material creation (verification of the surface or lemma frequency of the words, length of words and sentences, etc.), it is necessary to consider the grammatical and phonetic structure of a language. For instance, the number of words in a sentence and the length of the words can vary depending on the exact need. In addition, the words used in the experiment should be controlled for both spelling and sound. In an orthographically transparent language such as Russian, this is relatively straightforward, but it may be difficult to attain in other languages (e.g., English, Danish or Mandarin).
In line with a body of previous studies, we find different effects of acquisition immediately after the learning block and after an overnight sleep, which highlights effects of overnight consolidation. Importantly, we also find group differences (sham versus cathode) on the second day. It is generally accepted that the physical effect of stimulation of the cortex is relatively short-lasting, on the order of minutes to several hours. This implies that the cognitive effects achieved during the transient stimulation phase are nevertheless maintained over a longer period and may therefore be possibly used for modulating word acquisition and processing in practical settings. Obviously, not only the core language areas of Broca and Wernicke are involved in the language function; adoption of the protocol described above is possible for any area of the brain, while a battery of psycholinguistic tests fine-tuned for specific experimental purposes is still needed to assess the stimulation impact on a specific neurolinguistic trait.
The authors have nothing to disclose.
Supported by RF Government grant contract No.14.W03.31.0010. We wish to thank Ekatarina Perikova and Alexander Kirsanov for their support in preparing this publication. We are grateful to Olga Shcherbakova and Margarita Filippova for their help in stimulus selection and to Anastasia Safronova and Pavel Inozemcev for their assistance in the production of video materials.