Background ---------- The decrease of vigilance as a function of time is a phenomenon that we all are familiar with and which – depending on the situation – could lead from mild to severe consequences. In these latter situations, an erroneous or missed response to a key stimulus of the environment could lead to grave consequences, underlining the importance of studying ways to diminish this gradual dissipation of attention. An example of these consequences is portrayed by railway accidents, where the driver often has a supervisory role that requires vigilant monitoring of key stimuli in the environment: stop signals, signals indicating dangerous curves where speed ought to be reduced, etc. (please see for example: http://www.rtve.es/noticias/20190313/maquinista-cargo-adif-quedan-como-unicos-acusados-del-caso-alvia/1901480.shtml). Whilst other factors do contribute, the human error in detecting signals on time, has been frequently identified as a culprit in these situations (Edkin & Pollock, 1997; Read, Lenné, & Moss, 2012). Vigilance refers to sustaining the focus of attention over time on a given task and can be conceptualized through two components (Langner & Eickhoff, 2013; Luna, Marino, Roca, & Lupiáñez, 2018): an executive vigilance (EV) component (Luna et al., 2018), which concerns those cases where one is scanning the environment for a target stimulus and responding to it requires taking a decision (is this stimulus the target or not?), and an arousal vigilance (AV) component (Luna et al., 2018), which refers to the more basic state of activation and preparation of the individual that, once a relevant stimulus appears in the environment, allows fast responding to it, automatically, without much control. A recent study (Luna, Román-Caballero, Barttfeld, Lupiáñez, & Martín-Arévalo, submitted) aimed to explore whether High Definition tDCS (HD-tDCS, from now on) over the right frontal and parietal cortex – two core regions of the attentional networks system – could modulate the vigilance decrement; and if so, if the two components of vigilance could be dissociated in terms of the applied neuromodulation. For this purpose, behavioral measures of vigilance were obtained via the ANTI-Vea task (Luna et al., 2018): a novel version of the classic ANT task which allows a simultaneous assessment ofthe three classic attentional components along with the decrements in the executive (EV) and arousal vigilance (AV) components. A detailed explanation of the stimulation protocol and the ANTI-Vea task is provided below in Method. The following findings were observed (Luna et al., submitted; for a public report see: Román-Caballero, 2018): 30 minutes of online anodal stimulation (at 1.5 mA) over frontal and parietal regions led to a reduction of the executive vigilance decrement over time on task. Arousal vigilance however was not significantly modulated by HD-tDCS on either of the cortical sites. Interestingly, comparing EEG recordings at the beginning and at the end of the experimental task showed that stimulation of the parietal cortex (but not frontal) led to a reduction of alpha oscillations, independently of the participants’ performance on the task. These results seem to indicate that an efficient reduction of the vigilance decrement in terms of cerebral oscillations, was only found in the parietal stimulation group. Another result of interest here was obtained by Luna et al. (2019) in a study that aimed to dissociate the structural brain connectivity underlying the functioning of attentional networks. This was explored by correlating the behavioral data obtained from the ANTI-V task (another version of the classic ANT task which measures the three attentional networks and executive vigilance; Roca, Castro, López-Ramón, & Lupiáñez, 2011) with the microstructure connectivity of branches I, II and III of the Superior Longitudinal Fasciculus (SLF) (Schotten et al., 2011). It was observed that higher integrity in either the left or right first branch of the right SLF correlated with better executive vigilance performance (detection of infrequent but critical stimuli) (Luna, 2019). Lastly, it has been shown that people’s judgment of their state of vigilance or fatigue during a task, may not always be in accordance to the real measures of their attentional state. For example, Schmidt et al. (2009) showed that after 3h of an automated driving simulation, vigilance decreased continuously over time. However, participants reported a subjective increase in vigilance towards the end of the task, that did not match with the objectively recorded data (Schmidt et al., 2009). On the other hand, it has been argued that mindfulness practice can have a positive impact on executive control (Cásedas, Pirruccio, Vadillo, & Lupiáñez, n.d.); and thus, people with a higher dispositional mindfulness could also show a different pattern of decrement of their executive vigilance. Furthermore, it would be interesting to explore whether neuromodulation leads to quantitative differences in vigilance performance based on this mindfulness predisposition. In this context, the current study will serve mainly to replicate and extend the findings of the above mentioned study (Luna et al, submitted). Importantly, some aspects will be simplified while several additional measures will be collected. In particular: On the one hand, the experiment will be simplified in terms of the stimulation regions, as HD-tDCS will only be applied in the right posterior parietal cortex (PPC), as it was the only region wherein the neuromodulation seemed to be effective to reduce the alpha power increment over time. On the other hand, additional data will be collected prior and after the experiment: (i) we aim at exploring whether SLFs integrity can predict the outcomes of neuromodulation on executive vigilance; (ii) we aim to explore whether participants’ perceived vigilance state matches with the observed vigilance measures; and (iii) lastly, we also aim to explore the relationship between participant’s dispositional mindfulness and their vigilance performance. Hypotheses and Aims ------------------- As we mainly aim to replicate the findings of the study mentioned above (Luna et al., submitted), we propose that applying the same protocol, with the above-mentioned modifications, will lead to the following hypothethical results: 1. Reduction of vigilance decrement throughout time by stimulation (i.e., in the parietal stimulation group as compared to sham stimulation group), solely in the executive component, in the absence of an effect over arousal vigilance. 2. Reduced increase of alpha power oscillations over the parietal cortex in the parietal stimulation group as compared to the sham group, comparing pre- and post-task EEG meassures. 3. Additionally, as in Luna et al. (submitted) we do not only expect an effect of parietal stimulation over tonic alertness (in the executive component, as described above), but also over phasic alterness. Specifically, we expect to replicate the findings of a reduced effect of the auditory cue (which signals the imminent appearance of a target on the subsequent performance in responding to said target) in the parietal stimulation group. Furthermore, we expect this effect to take place in absence of a modulation of the other attentional components (i.e.: orienting and executive control). Furthermore, we aim to explore the relationship of these measures with: 1. Diffusion tensor imaging (DTI) analysis to explore whether the integrity of the branches of the superior longitudinal fasciculus (SLFs) modulates the effect that HD-tDCS has on the performance in executive vigilance. 2. Questionnaires screening for dispositional mindfulness and mindwandering tendencies (detailed below in Method); which would allow to explore whether there is a relationship between low/high mindfulness disposition and the participants performance in the ANTI-Vea Task. 3. Subjective fatigue rating to be completed by the participant at different stages of the experiment. This would allow to explore whether participants are aware of their own decrement in vigilance, when comparing behavioral and neurophysiological data with subjective ratings. Method ------ **Participants** A power analysis conducted with G*Power (Faul, Erdfelder, Lang, & Buchner, 2007) of the effect size (η2p = .05) observed in the critical interaction Block (1-6) x Group (sham vs. parietal stimualtion) with α = .05 and 1-β = .95, provided an estimation of a minimum sample of 22 participants per group. Therefore, we decided to collect 30 particpants per group as inthe original study. Signed consent will be obtained from all 60 participants, following ethical standards of the 1964 Declaration of Helsinki (last update: Seoul, 2008). Participants will have normal or corrected to normal vision and they will be naïve as to the purpose of the experiment. A reward of 10€/hour offered in exchange for participation. This study is embedded in a larger research project (PSI2017-84926-P) approved by the University of Granada Ethical Committee (175/CEIH/2017). **Apparatus and Stimuli** *The ANTI-Vea task* As described above, behavioral measures of the vigilance decrements will be recorded through the ANTI-Vea Task (Luna et al., 2018). This recent version of the classical task features 60 % of trials with ANTI trials (to obtain measures of the function and interaction of the classical attentional networks) (Callejas, Lupiáñez, & Tudela, 2004), and two additional modulations that lead to direct measures of each component of vigilance. At a rate of 20 % of the trials, the target arrow of the flanker task is vertically displaced from the rest of arrows, requiring a different response from the participant. Moreover, the task also includes a red countdown that appears at a rate of 20 % of the trials, and to which responding as fast as possible is required. These additions to the task offer direct measures of the EV and AV components, respectively. See Fig. 1 for a visual representation of the task procedure. ![enter image description here][2] Figure 1. Visual representation of the ANTI-Vea task procedure. Panel “a” depicts the general time procedure of the task in ANTI and EV trials, where the row of arrows could match with the previous visual cue or not. Panel “b” shows the AV trials. In Panel “c” we can see examples of each trial and the correct responses to be given in each case. *HD-tDCS and EEG recordings* In HD-tDCS, the electrical current is applied through a 4x1 electrode design, comprised of one central electrode with 4 surrounding return-electrodes distributed in a ring-like array (each one situated over identified EEG locations). This design allows for a more focal stimulation and less dissipation or shunting of the electrical current. The polarity of the central electrode determines the direction of neuromodulation, so an anode surrounded by a ring of cathodes will lead to anodal stimulation under the area of the electrode ring. The specific protocol for parietal stimulation and EEG recordings will be the same used in Luna et al. (submitted), in particular: - HD-tDCS will be applied over the right Posterior Parietal Cortex (PPC): placing the anode on P4 and the surrounding cathodes at PO4, PO8, CP6 and CP2. Both anode and cathodes will be set at 1.5 mA. In all conditions (real/sham HD-tDCS) we will use a 30 sec of ramp up/ramp down. - EEG recordings will be collected from electrodes over AF4, F4 and FC2, and over PO4, PO8, CP6 and CP2. ![enter image description here][1] Figure. 2. Left: representaton of the stimulation and recording setup of electrodes. The anode is marked in red and the cathodes in black. All marked electrodes (red, black and gray) will be used for EEG recordings. Right: simulated stimulation field for HD-tDCS over the right PPC. Image taken from Luna et al. (in prep). *Subjective Fatigue Ratings* We will record a subjective rating of mental and physical fatigue from each participant at three timeframes throughout the experiment: at baseline (before instructions are provided), pre-task (after the practice block, before the first experimental block) and post-task (after completing the experimental blocks). As in Luna et al. (2019) the order in which mental and physical fatigue are assessed, will be counterbalanced across participants (Luna, Barttfeld, Martín-Arévalo, & Lupiáñez, 2019). Responses will be recorded through an analog scale (a line that ranges from a minimum located on the left side of the screen to a maximum located on the right of perceived fatigue). *Mindfulness, mindwandering and lifestyle and their relationship with vigilance performance* Two questionnaires will be used to assess participants’ dispositional mindfulness relation to their performance on the ANTI-Vea Task, and further, to assess whether it correlates with different effects of stimulation over performance. Participants will complete the following questionnaires online before the experimental session: - Spanish-language Mindful Attention Awareness Scale (MAAS-SP, Johnson, Wiebe, & Morera, 2013) - Five Facets of Mindfulness Questionnaire (FFMQ) in its Spanish version (Cebolla, Soler, Guillen, Baños, & Botella, 2012) - Attentional Control Scale (ACS) - Cognitive Failures Questionnaire (CFQ) - Mindwandering Questionnaire (MWQ) Furthermore, an additional general survey will be completed (likewise through online administration), which inquires about the participants socioeconomic niveau, as well as habits of physical excersice, musical practice and habits of meditation. *SLF integrity and its relationship with the neuromodulation of vigilance* Before completing the experiment, DTI measures of the participants will be obtained. These in vivo dissections of white matter tracts of each participant will be assessed to explore whether the integrity of the branches (especially the first) of the superior longitudinal fasciculus (SLF) modulates the effect of HD-tDCS on the executive vigilance component. DTI will be reconstructed by using the spherical deconvolution approach, and the Hindrance Modulated Orientational Anisotropy index (or HMOA; Dell’Acqua, Simmons, Williams, & Catani, 2013) will be used as the proxy for the tract microstructural organization. No further changes will be made to the experiment’s main architecture, as we seek to test the replicability of the previous findings. As a summary: the only aspects which will be added to the current study in comparison to the previous study are the following, as stated below: - Stimulation groups will be restricted to right parietal and sham stimulation, as right parietal stimulation showed the most promising results, supported by our recorded behavioral and EEG data. - Collection of DTI data (prior to the experiment) - Collection of subjective fatigue measurements (before/after the experiment) - Collection of data regarding disposition to mindful attention (before the experiment) - Note that the duration of experimental blocks and block number is the same as in the previous study. **Procedure** Security questionnaires that scan for MRI and tDCS inclusion/exclusion criteria will be mailed to participants. Only those participants that fulfill inclusion criteria for a safe application of neuromaging and tDCS will be contacted with further details of the experiment. The participants will then receive an online survey to complete at home: online mindfulness, mindwandering and lifestyle questionnaires will be administered as detailed above. Once the questionnaires have been completed, participants will be contacted to schedule their on-site session. This session will begin by collecting DTI measures. Afterwards, participants will be led to the room where the experimental task will be performed. At this point, the first fatigue assessment will be conducted (baseline). Right after, participants will receive general instructions for the ANTI-Vea task and complete the practice block. In between this practice block and the experimental block, the participant will complete the pre-task fatigue assessment. Then, electrode setup will take place. The baseline EEG recordings will be completed during the 1st experimental block. Either HD-tDCS or Sham HD-tDCS over the right PPC will be applied, from the 2nd to the 6th experimental block. During the 7th and last experimental block, the post-task EEG measures will be recorded. Right after completion of the experimental block, the last fatigue assessment will be completed (post-task). Finally, the participant will complete a tES Survey, in order to record their subjective experience during stimulation (Fertonani, Ferrari, & Miniussi, 2015). **Design** To test the functioning of the ANTI-Vea, repeated measure ANOVAs will be conducted over the ANTI-trials, considering the following three within-participant factors: - Phasic alertness (with 2 levels: tone, no tone) - Orientation (with 3 levels: valid cue, invalid cue, no cue) - Executive control (with 2 levels: congruent or incongruent). Global scores of the groups will be analyzed, collapsing ANTI trials of all experimental blocks together; to analyze participants’ performance in terms of: - Reaction Time (for these analyses incorrect responses will be excluded, as well as responses below 200 ms or above 1500 ms). - Percentage of Errors. To analyze the effect of HD-tDCS on the participant vigilance: - The effect on the EV component will be analyzed via repeated measures ANOVA considering the hits (correctly identified vertically displaced target), false alarms (incorrectly identifying non-displaced target as being vertically displaced), sensitivity and response bias as dependent variables; whilst the experimental blocks will be considered as a within participant factor. - The effect on the AV component will be analyzed likewise through repeated measures ANOVA that considers the Reaction Time’s mean and standard deviation as dependent variables, and – as for EV – the blocks will be included as a within-participant factor. Regarding the EEG data, alpha power will be analyzed through a repeated measures ANOVA that considers the stimulation group (HD-tDCS or sham tDCS over the right PPC) as a between participant factor and the moment of measurement (baseline or post-task) as a within participant factor. Finally, we will also analyze whether the effect of neuromodulation on task performance is modulated by: - DTI Data: SLF integrity by using the HMOA index. - Subjective fatigue ratings - Dispositional mindfulness Thus, we will perform correlational or covariate analyses in order to explore the potential relationship between SLFs, subjective fatigue and disposition to mindfulness and different measures extracted by the ANTI-Vea. References ---------- Callejas, A., Lupiáñez, J., & Tudela, P. (2004). The three attentional networks: On their independence and interactions. Brain and Cognition, 54(3), 225–227. https://doi.org/10.1016/j.bandc.2004.02.012 Cásedas, L., Coll-Martín, T., Martínez-Montero, T., Luna, F. G., Román-Caballero, R., Martín-Arévalo, E., … Lupiáñez, J. (2019). Cuantificando los procesos atencionales: la tarea ANTI-Vea [Quantifying the attentional processes: ANTI-Vea task]. Cásedas, L., Pirruccio, V., Vadillo, M. A., & Lupiáñez, J. (n.d.). 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