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The demands of today’s society for interventions that optimize cognitive abilities and prevent their decline have motivated the translation of scientific findings into applied programs. Ordinary activities such as physical exercise, chess, meditation, playing video games or a musical instrument, as well as specific cognitive programs, have witnessed the growth of evidence emphasizing their cognitive benefits. Here, we outline several issues that need consideration before speculating on the implications of this literature: (a) the magnitude and costs of the effect, (b) the robustness of the effect, (c) testing causality, (d) the identification of moderator variables, and (e) the underlying mechanisms. We consider that this would contribute to a critical appraisal of the extant findings by the interested researchers, to reduced overstatements in the media reports about the applicability and public relevance of the effects reported in scientific articles, and to potentially help designing new interventions.

Following our preregistered design and hypotheses, we found interesting results in the second experiment. Thus, we have decided to conduct a third experiment following the simpler design used by Marotta et al. (2018), with the addition of a peripheral visual cue 100 ms before the target onset and, in an alternative block, an alert sound 450 ms before the target onset.

The causal relationship between regular physical exercise and cognition during childhood seems unquestionable, based on the systematic reviews and meta-analyses published to date. However, there are also studies that question these claims, showing that the evidence is not as strong as it would seem. A recent study carried out by our research group has shown that, once corrected for relevant moderators and publication bias, the effect of exercise on cognition (in healthy people of all ages) provided by randomized controlled intervention studies is practically 0. A Bayesian analysis reveals that the data available to date from intervention studies do not provide evidence either for or against the existence of the effect. The present project is based on the rationale that intervention studies may not be adequate to capture such a causal relationship, if it exists, and proposes instead to test a causal model to be evaluated by means of a longitudinal study. This causal model takes into account both variables that could mediate the relationship between physical exercise and cognition during childhood, moderating variables, as well as confounding variables and colliders. We hope therefore to contribute to the knowledge about whether regular physical exercise during childhood really provides benefits beyond physical health.

Rhythmic contexts are ubiquitous in our lives, influencing our behavior significantly. Music, dance, speech, and even natural events such as sea waves have an inherent temporal structure, understood as rhythms. The Dynamic Attending Theory (DAT) states that attention can be entrained to external rhythms, enhancing our behavior in terms of preparation (e.g.., faster responses) and/or perception (e.g., better discrimination). Notwithstanding the great influence of the DAT, several studies actually failed to observe entrainment effects in tasks measuring either accuracy or response speed. The present study aims to further explore this issue by trying to replicate a seminal work by McAuley and Fromboluti (2014), which confirmed the predictions of the DAT using an oddball auditory paradigm. Extending this original study, we will also incorporate eye-tracking measures of attention as well as measures of musical skills and spontaneous motor tempo to assess the role of individual differences in the supposed entrainment effects. Overall, we expect to replicate the original study by McAuley and Fromboluti (2014) and to provide complementary evidence about rhythmic entrainment that takes into account interindividual differences. Keywords Dynamic Attending Theory, rhythm, oscillation cycles, foreperiod effect, timing, eye-tracker, pupillometry

There is currently a growing interest in ways to enhance and preserve our cognitive skills through changes in lifestyle. Extensive scientific evidence links several behavioral and environmental factors, such as smoking, alcohol and drug abuse, a sedentary lifestyle, and inadequate nutrition, to an increased risk of cognitive impairment, dementia, and accelerated aging. On the other side, education, physical exercise, and cognitively stimulating occupations and leisure activities have all been associated with neurocognitive benefits and the prevention of the pervasive consequences of neural aging. Among them, a wealth of studies has associated musical training, and particularly learning to play an instrument, with differences in auditory and sensorimotor skills, as well as in multiple non-musical cognitive capacities: intelligence, visuospatial abilities, processing speed, executive control, attention and vigilance, episodic and working memory, and language. In addition, anatomical and functional changes have been documented in several brain networks, some of them related to higher-order cognitive processing or non-musical skills. A priori, the characteristics of playing a musical instrument make it a promising candidate for producing a transfer effect. It involves multiple sensory and motor systems, and requires a wide variety of higher-level cognitive processes. Moreover, a regular and motivated practice of progressive difficulty is necessary to master the technique of an instrument. The wide range of observed differences between musicians and nonmusicians suggests that musical practice might produce near and far transfer. However, some voices have argued against the causal role of musical training and hypothesized that the advantages are the consequence of the lack of control of cross-sectional studies. Skeptic authors rather propose that high-functioning children, with higher musical aptitude, higher socioeconomic status, and high openness to experience are more likely to be interested in music. Therefore, the idea that learning to play a musical instrument is the cause of a broad cognitive enhancement is still controversial. The research program in the present thesis dissertation aimed to contribute with answers to the debate. First, in a comprehensive meta-analysis of intervention studies (i.e., with a pre-posttest assessment), we showed that the available evidence of randomized controlled trials with children and adolescents supports a small benefit of musical training (d = 0.26). Interestingly, a small advantage at baseline was observed in studies with self-selection (d = 0.28), indicating that participants who had the opportunity to select the activity consistently showed a slightly superior performance prior to the beginning of the intervention. However, baseline performance did not fully explain the differences between children/adolescents with and without musical training, which rules out the effect being a methodological artifact (e.g., regression toward the mean). In addition, some moderators of the effect were observed: (a) the larger the baseline difference, the smaller the observed effect of musical training; (b) participants with lower socioeconomic status showed greater improvements compared to those with middle-high socioeconomic status; (c) the earlier the age of commencement, the larger the effect. Second, we conducted a meta-analysis regardless of the age of the participants to examine the impact of learning to play an instrument on music-related skills. The available intervention studies also suggested near transfer, but they are still scarce to reach firm conclusions. One explanation for the potential broad benefits of musical training might be its impact on attention and executive functions, as they are necessary functions for many cognitive tasks and daily activities. Indeed, in a well-controlled crosssectional study with a preregistered design, we found superior vigilance and psychomotor speed for musicians than non-musicians. Importantly, our extensive control of confounders led to smaller effects in contrast to the previous literature. These results are consistent with a nature and nurture hypothesis, in which expert musicians might have preexisting advantages (cognitive, personality, and/or musical aptitudes) that would promote the acquisition of musical skills and motivation to practice, while at the same time, this long-term engagement would also result in multiple neural and cognitive changes. Finally, we meta-analyzed the literature on musical training in healthy aging. We included both cross-sectional and experimental studies as they are complementary: experimental methodology involves randomization and thus allows the establishment of causal relationships, while correlational designs analyze samples with longer musical training. We observed benefits in both types of designs, although the experimental evidence is less abundant. Taken all together, it seems that musical training might have a protective effect in some functions and, mostly, an enhancing effect throughout life. Thus, musicians would present a superior cognitive performance at all stages of life. I proposed here several non-exclusive mechanisms to explain cognitive benefits of musical training. Given the high demands that musical practice places on multiple cognitive functions (e.g., memory), learning to play an instrument could specifically enhance cognitive abilities through neuroplasticity as a consequence of the increased use of those abilities. However, it might promote the use of more efficient strategies (e.g., improved rehearsal mechanism and semantic organization). As it is a multisensory activity, it might lead to multimodal representations of reallife events (e.g., spatial or visual representation of auditory words), enriching them with complementary inputs. Also, the characteristics of musical training might build a greater propensity for effort (i.e., learned industriousness), making effortful tasks less aversive and more engaging. Finally, the enhancements on domain-general cognitive functions, especially attention and executive control, might spread their benefits on other cognitive tasks, such as preventing the interference of irrelevant events in working memory. Overall, the contribution of musical training to cognitive skills seems to be rather small and probably makes very little difference in daily life, so it might be not one of the first-choice interventions if the only purpose is cognitive enhancement. However, learning to play an instrument is an enriching activity in itself and can become an important source of pleasure in the player's life. In addition to the social and emotional benefits of playing, practicing this activity for long periods (several decades) could also have significant implications for the development of basic cognitive skills, especially in samples with lower cognitive performance, low socioeconomic status or suffering from neurological conditions., El interés por las formas de mejorar y preservar nuestras capacidades cognitivas a través de los estilos de vida ha crecido en los últimos años. Una abundante evidencia científica vincula ciertos factores ambientales y ciertos hábitos, como el tabaquismo, el abuso de alcohol y drogas, el sedentarismo y una nutrición inadecuada, con un mayor riesgo de deterioro cognitivo, una mayor prevalencia de demencias y un envejecimiento acelerado. En el lado contrario, la educación, el ejercicio físico, y las profesiones y actividades de ocio mentalmente estimulantes se han asociado a beneficios neurocognitivos y a la prevención de las consecuencias del envejecimiento cerebral. Una de esas actividades ha sido la práctica musical, y en particular aprender a tocar un instrumento, la cual se ha relacionado con diferencias en las habilidades auditivas y sensoriomotoras, así como en múltiples habilidades cognitivas que no son específicas de la música: la inteligencia, las habilidades visuoespaciales, la velocidad de procesamiento, el control ejecutivo, la atención, la capacidad de vigilancia, la memoria episódica, la memoria de trabajo y el lenguaje. También se han documentado cambios anatómicos y funcionales en varias redes cerebrales, algunas de ellas involucradas en procesos cognitivos de orden superior o capacidades no musicales. Tocar un instrumento musical es una actividad con unas características que, a priori, la convierten en una candidata prometedora para producir efectos de transferencia. Tocar un instrumento implica múltiples sistemas sensoriales y motores, y requiere una gran variedad de procesos cognitivos de nivel superior. Además, dominar la técnica de un instrumento conlleva una práctica regular y motivada con una dificultad progresiva. La amplia gama de aspectos cognitivos que se ven mejorados en las personas con formación musical sugiere que la práctica musical podría producir una transferencia cercana y lejana. Sin embargo, algunas voces han argumentado en contra del papel causal de la formación musical y plantean que todas las ventajas son consecuencia de la falta de control de los estudios transversales. Esas voces escépticas han propuesto que ciertas variables predisponen a que las personas se interesan y se impliquen en la práctica musical: un mayor rendimiento cognitivo previo al comienzo de la formación musical, mayores capacidades musicales, un mayor estatus socioeconómico y una mayor apertura a la experiencia como rasgo de personalidad. Por lo tanto, aún existe controversia en torno a la idea de que aprender a tocar un instrumento musical cause beneficios cognitivos. El conjunto de estudios que conforman esta tesis pretende aportar respuestas a este debate. En primer lugar, en un metaanálisis exhaustivo de los estudios de intervención (es decir, aquellos con un diseño pre-postest), encontramos que la evidencia disponible de los ensayos controlados aleatorizados con niños y adolescentes respaldan la existencia de un beneficio cognitivo pequeño de la práctica musical (d = 0,26). También observamos una pequeña ventaja al inicio del estudio en los estudios sin aleatorización (d = 0,28), lo que confirma que las personas que seleccionaron la práctica musical en base a sus propias motivaciones tenían un rendimiento superior antes del comienzo de la intervención. Sin embargo, el rendimiento inicial de los participantes no explicaba totalmente las diferencias entre los niños/adolescentes con y sin formación musical, lo que descarta que el efecto sea un artefacto metodológico (por ejemplo, la regresión a la media). Además, el efecto de la práctica musical estaba moderado por algunas variables: (a) el beneficio de la práctica musical disminuía cuanto mayor era la diferencia entre los dos grupos al principio del estudio (antes de la intervención); (b) los participantes con un estatus socioeconómico más bajo mostraban mayores mejoras en comparación con aquellos con un estatus socioeconómico medio-alto; y (c) cuanto más temprana era la edad de inicio, mayor era el efecto. En segundo lugar, realizamos un metaanálisis en todas las edades sobre el impacto de aprender a tocar un instrumento en las capacidades auditivas relacionadas con la música. Los estudios de intervención disponibles sugirieron una transferencia cercana, pero su número era escaso para conducir a conclusiones firmes. Una explicación de los amplios beneficios de la práctica musical podría ser a través de los beneficios que produciría en la atención y las funciones ejecutivas, ya que son funciones esenciales en muchas tareas cognitivas y actividades cotidianas. De esta forma, en un estudio transversal con un diseño prerregistrado y en el que controlamos una lista extensa de variables de confusión, un grupo de músicos adultos mostraron ventajas en la capacidad de vigilancia y la velocidad psicomotora en comparación a un grupo de personas sin formación musical. Destaca que los efectos observados tras el exhaustivo control de variables de confusión fueron menores que los encontrados en múltiples estudios transversales anteriores. Estos resultados son coherentes con una explicación de las diferencias cognitivas basada tanto en factores innatos como en la experiencia, es decir, las ventajas encontradas en los músicos expertos pueden ser consecuencia de factores anteriores a la práctica musical (ventajas cognitivas previas, rasgos de personalidad y/o aptitudes musicales anteriores a la formación musical) que promoverían la adquisición de las habilidades musicales y la motivación para practicar, mientras que la práctica musical a lo largo del tiempo también daría lugar, por su parte, a múltiples cambios neuronales y cognitivos. Por último, se realizó un metaanálisis de los estudios en el envejecimiento saludable. Incluimos tanto estudios transversales como experimentales, ya que son dos metodologías complementarias: los diseños experimentales implican la aleatorización de los participantes y, por tanto, permiten establecer relaciones causales, mientras que los diseños correlacionales analizan muestras con un entrenamiento musical más prolongado. Nuestro metaanálisis mostró beneficios en ambos tipos de diseño, aunque la evidencia experimental fue menos abundante. En conjunto, parece que la práctica musical podría tener un efecto protector en algunas funciones cognitivas, pero sobre todo tendría un efecto potenciador a lo largo de la vida. Por tanto, las ventajas en el rendimiento cognitivo de los músicos estarían presentes en todas las etapas de la vida. Propongo la existencia de varios mecanismos no excluyentes para explicar los beneficios cognitivos del entrenamiento musical. Dadas las demandas elevadas de la práctica musical sobre múltiples funciones cognitivas (por ejemplo, la memoria), aprender a tocar un instrumento podría mejorar específicamente las capacidades mentales a través de la neuroplasticidad desencadena por un mayor uso de esas capacidades. Sin embargo, podría promover el uso de estrategias más eficientes (por ejemplo, mejoras en el mecanismo de ensayo y la organización semántica). También, al tratarse de una actividad multisensorial, podría dar lugar a representaciones multimodales de los acontecimientos de la vida real (por ejemplo, representando espacial o visualmente las palabras auditivas), enriqueciéndolas con una información complementaria. Además, las características del entrenamiento musical podrían convertir a quienes la practican en personas con una mayor propensión al esfuerzo (es decir, con una mayor laboriosidad aprendida), por lo que las tareas que requieren esfuerzo podrían ser menos aversivas y más atractivas. Por último, las mejoras en funciones cognitivas generales, especialmente la atención y el control ejecutivo, podrían extender sus beneficios a otras tareas cognitivas, como la prevención de la interferencia de eventos irrelevantes en la memoria de trabajo. En general, la contribución del entrenamiento musical a las habilidades cognitivas parece ser bastante pequeña y probablemente marque una diferencia reducida en la vida diaria, por lo que podría no ser una de las intervenciones de primera elección si el único propósito es la mejora cognitiva. Sin embargo, aprender a tocar un instrumento es una actividad enriquecedora en sí misma y puede convertirse una fuente importante de placer en la vida de quien lo toca. Lo interesante es que, además de los beneficios sociales y emocionales de tocar, podría tener además implicaciones significativas en el desarrollo de habilidades cognitivas básicas tras largos periodos de práctica (de varias décadas) y en muestras con un menor rendimiento cognitivo, un bajo nivel socioeconómico o que sufren alguna afección neurológica., Tesis Univ. Granada., Spanish Ministry of Education, Culture and Sport to RRC (FPU17/02864), Grant from the Autonomous Community of Madrid to MAV (2016-T1/SOC-1395), The Spanish Ministry of Economy, Industry, and Competitiveness to JL (PSI2017-84926-P), MAV (PSI2017-85159-P), Universidad de Granada / CBUA

Following our preregistered design and hypotheses, we found interesting results in the third experiment. Thus, we have decided to conduct a fourth experiment following the same design, with the addition of two rectangular placeholders, one on each side of the fixation point during the whole task.

The aim of the present study is to investigate whether a pre-cueing manipulation is also effective to reduce the standard congruency effect wit arrows (in valid trials) and at the same time make more negative the reversed congruency effect with eye gaze. We therefore expect similar results to the ones observed in the two experiments in Román-Caballero et al. (2021b) with the manipulation of the target–background synchrony.

Data (see Files section) reported in the manuscript "A High-Definition tDCS and EEG study on attention and vigilance: Brain stimulation mitigates the executive but not the arousal vigilance decrement" by Fernando G. Luna (Universidad Nacional de Córdoba, Argentina, and Universidad de Granada, España), Rafael Román-Caballero (Universidad de Granada, España), Pablo Barttfeld (Universidad Nacional de Córdoba, Argentina), Juan Lupiáñez (Universidad de Granada, España), and Elisa Martín-Arévalo (Universidad de Granada, España).

Influence of a rhythmic context on the foreperiod effect: A behavioral and eye-tracker approach Rafael Román-Caballero, Elisa Martín-Arévalo, and Juan Lupiáñez Mind, Brain, and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain; and Department of Experimental Psychology, University of Granada, Granada, Spain Introduction Attention fluctuates over time. In the long-term, it seems to wax and wane throughout the day concerning the sleep-wake cycle (Oken et al., 2006) and, when exercised in a sustained way, it is usual to observe a decrease in performance (i.e., vigilance decrement; Luna et al., 2018; Thomson et al., 2015). Several theories (Jones, 1976; Large & Jones, 1999; Fiebelkorn & Kastner, 2019) extend this idea and propose that attention acts as an oscillatory system that alternate, following an intrinsic period (1–4 Hz), between moments of enhanced perceptual sensitivity with instants of attentional disengagement. Moreover, fluctuations of attention can be synchronized with rhythmic environmental stimuli through entrainment (Dynamic Attending Theory, DAT; Jones, 1976). In particular, the regularity of the external rhythm is a key factor in the degree of attentional coupling. Periodic sequences of stimuli promote a tight phase coupling and allow the perceiver to anticipate the nature (e.g., modality, quality) and precise timing of a future event (Henry & Herrman, 2014). Therefore, the presence of a rhythmic context can benefit the perceptual discrimination and response preparation for stimuli occurring in phase with the rhythm (Henry & Herrman, 2014). On the other hand, the DAT proposes that the attentional oscillation is self-sustained, that is, the oscillator decays back to its intrinsic period when the external rhythm disappears. However, evidence about the lasting effect of entrainment is still scarce. A recent study (Trapp et al., 2020) suggests that the benefits of a rhythmic background can remain some minutes after it discontinues. One example of the impact of rhythmic contexts on perceptual performance can be found in Chang et al. (2019). They presented deviants tones (higher or lower in pitch) embedded in rhythmic (isochronous) or arrhythmic (non-isochronous) sequences of standard tones (500 Hz). Pitch deviations (500 ± Δ Hz) were near to the higher and lower discrimination thresholds. During the task, participants benefitted from rhythmic contexts and showed faster responses and superior pitch discrimination for target tones than in arrhythmic sequences. Moreover, electroencephalographic (EEG) signals from bilateral auditory cortices (filtered with a dipole source model) were entrained to rhythms. Delta (1–3 Hz) frequency bands showed power peaks at 2 Hz and harmonic frequencies (4 and 6 Hz) exclusively in rhythmic sequences, according to the isochronous presentation of stimuli each 500 ms. Rhythmic regularity also modulated delta phase, beta (15–25 Hz) power, and delta-beta coupling. More importantly, those EEG changes were correlated with changes in behavioral outcomes (i.e., pitch sensitivity and response speed). Rhythm is not the only type of temporal structure that can support attention (Nobre & van Ede, 2018). One of them is the passage of time itself when there is the certainty that the target will appear after an interval (i.e., when the target is presented in all trials). The probability that an event will occur given that it has not yet occurred increases over time and, therefore, the temporal expectation. As a consequence, reaction time (RT) decreases as the foreperiod (i.e., the interval between the cue and the target) becomes longer, which is usually known as the foreperiod effect (Niemi & Näätänen, 1981; Triviño et al., 2010). Previous studies have explored the interaction between rhythmic structures and the foreperiod effect. Martin et al. (2005) found clear effects of foreperiod and rhythm in a task in which the participants had to discriminate the color of circles. In half of the trials, a single white circle preceded the target (serving as a warning cue), leaving a silent interval of 1000, 1500, or 2000 ms. In the other half, that interval was filled with extra white circles forming an isochronous sequence (with an interonset interval, IOI, of 500 ms between each cue, and between the last of them and the target). Although in both conditions RTs decreased as the cue-target intervals became longer, in the rhythmic condition the reduction was more pronounced. The advantage of the isochronous context disappeared when its pace was drastically slowed down, with an IOI of 4000 ms (Martin et al., 2005; Experiment 2). However, one possibility is that the improved performance in the rhythmic condition could be driven by a higher alerting state due to the greater number of cues. In their third experiment, Martin et al. found that both isochronous sequences and complex rhythmic context lead to allocate attention to moments in time in contrast to random sequences. Similarly, Ellis and Jones (2010) observed a foreperiod effect with RTs in an auditory pitch discrimination task when a scrambled context preceded the target. That is, participants were faster responding to targets that appeared 1000 ms after than those that occurred 500 ms after (and even faster than those appearing after only 250 ms). Interestingly, the use of a complex but metrical rhythm (with a beat each 1000 ms) before the target reversed the foreperiod effect. It was interpreted as a consequence of the rhythm reducing the uncertainty in all the temporal moments, as it elicited increases in temporal expectation to 1000 ms and their subdivisions, 500 and 250 ms. Thus, the better precision to estimate short intervals than longer (250 vs. 1000 ms) would explain the increase of RTs over time. Therefore, simple and complex rhythmic contexts seem to influence the foreperiod effect, at least with response speed outcomes. Nevertheless, in the previous studies, the target always appeared in phase with the period of the entrained rhythm and just one period after the cueing sequence (e.g., 500 ms following the offset of the 500-ms isochronous sequence; Martin et al., 2005, Experiment 1). To probe the oscillatory nature of the rhythm entrainment and the extension of its effect over time, one possibility is to include targets out of phase (e.g., 250 or 750 ms in the last example) along with cue-target intervals of several periods (e.g., since 250 to 2250 ms). Another issue with the aforementioned studies is the presence of remarkably low perceptual demands (Ellis & Jones, 2010, Experiment 2; Martin et al., 2005, Experiment 1) or high (75% of accuracy; Ellis & Jones, 2010, Experiment 1). With those designs, a great percentage of participants might respectively have reached a ceiling effect or performed under the discrimination threshold. Thus, it seems relevant to adjust the demands to the perceptual skills of each participant to assess with enough sensitivity the influence of rhythm. Finally, along with behavioral measures, recent research has shown that temporal expectation can be observed through eye-tracker measures. In two visual tasks of sustained attention, Shalev and Nobre (2020) found that the discrimination and processing speed of the participants improved in the rhythmic blocks (isochronous sequence with an IOI of 3500 ms), compared to blocks where stimuli appeared after a variable interval (2500–4500 ms). In addition, rhythmic regularity reduced pupil size across the tasks, suggesting an arousal adjustment to the conditions of high temporal certainty and the achieving of a more efficient energetic state. Interestingly, pupil size also exhibited a foreperiod-like pattern in variable blocks, with transient increases of the pupil as a function of time (i.e., larger pupil size in intervals close to 4500 than 2500 ms). However, the existence of a single cue-target interval did not allow assessing that pupil-dilation index of the foreperiod effect under a rhythmic context. It has been proposed that pupil size changes can be a sensitive measure of temporal expectation as they vary according to the locus coeruleus-noradrenergic response (via parasympathetic and sympathetic pathways: pupil constriction and dilation, respectively; Wang & Munoz, 2015). A reduced uncertainty such as that in rhythmic contexts would promote reduced tonic arousal along with marked short-scale phasic increases contingent on relevant stimuli (Aston-Jones & Cohen, 2005; Shalev & Nobre, 2020). On the other hand, high uncertainty (i.e., arrhythmic contexts) favors a continuous state of high tonic arousal and slight transient increases. In another visual vigilance task, Dankner et al. (2017) found that saccades were inhibited prior to the target onset at predictable compared with less predictable moments, given by the use of fixed (2000 ms) and variable (1000, 1500, 2000, or 2500 ms) IOI, respectively. The prestimulus saccadic inhibition (PSSI) was absent in most participants with attention-deficit/hyperactivity disorder (ADHD) and it was reduced in those (both neurotypical and with ADHD) with poorer sustaining attention scores. Thus, the PSSI-predictability effect is a sensitive measure of temporal expectation that can be related to suppression mechanisms to prevent image motion on the retina. By reducing eye motion for a short interval of time prior to the target, it may prevent transient visual distortions and enhance acuity. Even more, it has been observed an increase in saccade rates 200 ms after the saccadic suppression, which correlated with PSSI: the higher the PSSI, the higher the post-stimulus saccade rate (Dankner et al., 2017). This post-stimulus rate increase was interpreted as a rebound-like effect that could have pervasive consequences if the target appeared in an unpredictable moment, a few hundred milliseconds later. The PSSI effect has not yet been investigated with non-visual paradigms, such as auditory foreperiod tasks, as in the present research project. The present study aims to investigate the modulating effect of rhythms over the foreperiod effect, as well as its extension over time, in behavioral outcomes (RTs and accuracy) and eye-tracker measures (pupil size and PPSI-predictability effect). We will use a pitch discrimination task with a sequence of standard tones before the target onset. In one block, the IOI will be fixed at 500 ms forming a rhythmic context, while in another block the IOI will be randomly varied between 250 and 750 ms (arrhythmic context). To adjust the perceptual demands in each participant, at the same time that we leave a large proportion of correct responses, a 1-up/4-down procedure will be used to estimate the 84.1% correct pitch discrimination threshold (Levitt, 1971). Moreover, we will use variable cue-target intervals up to 2250 ms and targets in phase with the rhythmic sequence (i.e., n 500 ms after the last tone of a 500-ms isochronous sequence) and targets out of phase (i.e., n 500 +/− 250). This manipulation will allow observing whether attention is devoted more to the moments predicted by the entrained rhythm than those out of phase. Hypotheses We expect a classic foreperiod effect will appear in response speed and accuracy. That is, the later the target onset, the faster the response and the better discrimination (higher accuracy) of the participants. Moreover, and crucially for this study, the presence of a rhythmic context before the target will enhance the perceptual sensitivity and the preparation to the critical moment, and will modulate the foreperiod effect. The presentation of several isochronous standard tones will lead to better performance at moments in phase with the entrained rhythm (500, 1000, 1500, and 2000 ms after the last standard tone). Moreover, we predict that although those effects will extend to the later in-phase moments (1000, 1500, and 2000 ms), it is probable that the alignment with the rhythm will decay over time. Regarding eye-tracker measures, we also expect a modulation of the rhythmic context over the foreperiod effect. Specifically, we hypothesize a decrease of the pupil size at the beginning of the sequence of standard tones along with an increase before the target onset, that will be more marked in the rhythmic block. Furthermore, whether the PSSI is a cross-modal effect, it would be possible to find a similar block modulation over the PSSI: a higher saccade rate just before (−100 ms) the appearance of in-phase targets during the variable-IOI block than in the fixed-IOI block. Finally, the impact of the rhythmic context might decay with the pass of time, being greater in the first periods than in the last ones. Method Participants We have selected the three-way interaction [block (2) × period (4) × phase (2); for details, see below] to estimate the sample size in the present experiment. In a previous pilot study with 11 participants, we found an effect size of f2 = 0.12. Using the Superpower R package (Caldwell et al., 2020), we have found that at least 43 participants will be necessary for a small-to-medium effect size of f2 = 0.09 (similar to that observed in the pilot) with an alpha of .05 and a power of .80. Accordingly, we have chosen a sample size of 45 participants due to the possibility of some missing participants as a consequence of technical issues or misunderstandings of the instructions. All the participants will be students from the University of Granada that will receive 15€ for participating. All will have a self-reported normal or corrected-to-normal vision and will be naïve as to the purpose of the experiment. The study will be conducted following the ethical guidelines laid down by the University of Granada (536/CEIH/2018), in accordance with the ethical standards of the 1964 Declaration of Helsinki (last update: Seoul, 2008). Outlier detection will be based on performance (i.e., mean reaction times and accuracy) identified as poor in terms of meeting all the following indices: standard deviation from the mean of the sample (> 2.5), studentized deleted residuals (> 3), and Cook’s Di (> 4/n). Apparatus and Stimuli The stimulus presentation, timing, and data collection will be controlled by a program written using E-Prime 2.0 (Schneider et al., 2002), run on a standard Pentium 4 PC. During the task, a light gray fixation cross will be presented on the center of a 17-inch widescreen monitor with a 1,280 × 1024-pixel resolution and 60 Hz of refresh rate. Auditory stimuli will be sine wave tones created with Audacity. Tones will last 60 ms with 10 ms rise and 10 ms fall times. Standard tones will have 500 Hz of frequency and will be presented at 70 dB. Whereas, comparison higher and lower tones will have 500 ± Δ Hz and 78 dB, where Δ represents the 84.1% correct pitch discrimination threshold estimated with a 1-up/4-down procedure (Levitt, 1971). We will use a video-based eye-tracker (EyeLink 1000 Plus, SR Research, Ontario, Canada) to measure pupil diameter monocularly as well as microsaccades and blinks at 1000 Hz. Procedure The study will be carried out after preregistration, during June of 2021. The experiment will take place in a dimly-light room and using glasses or contact lenses if needed. The session will last approximately 1 hour and 15 minutes. Prior to the experimental task, participants will complete a questionnaire (Appendix A) with items about demographic information, the fatigue and vigor scales of the Spanish abbreviated version of the Profile of Mood States questionnaire (Andrade et al., 2013; original version, Grove & Prapavessis, 1992), musical training background, and exclusion criteria: vision or hearing problems, neurological or psychiatric illness, diabetes, drug abuse, or chronic use of psychoactive medication. After that, participants will sit 64 cm from the monitor, and a chin rest will be used to keep their head still. First, the individual pitch discrimination threshold will be estimated using a 1-up/4-down procedure (84.1% correct pitch discrimination, following Levitt, 1971). In each trial, a standard tone will be presented followed by a comparison tone 500 ms after. The participants will be required to judge whether they perceive the second stimulus higher or lower in pitch than the standard (pressing “8” or “2” keys, respectively). The estimation of the discrimination threshold will comprise two blocks, one for the upper threshold and beginning with a 515-Hz tone and a lower threshold block beginning with a tone of 485 Hz of frequency (the order of the blocks will be counterbalanced). We will estimate the discrimination threshold by averaging the frequency of all the peaks and valleys in each type of block. Peaks and valleys are the frequency values at which a change in the perceptual trend occurs (for instance, when the individual perceives that the second tone has a lower pitch after a series of trials in which it was judged as higher). To reach a reliable discrimination threshold in each participant, the 1-up/4-down procedure will finish after the occurrence of ten peaks or valleys in each block. After the estimation of the discrimination threshold, participants will carry out the pitch discrimination task. The instructions will appear on the screen and will be explained to the participant by the experimenter, who will also answer any questions about the procedure. In each trial, the participants will hear five, six, or seven standard tones with an IOI of 500 ms or a random value between 250 and 750 ms, depending on the block (fixed vs. variable block; see Figure A in the OSF project https://osf.io/cw93r/). After the sequence of standard tones, a comparison tone will appear with an IOI randomly selected from 250, 500, 750, 1000, 1250, 1500, 1750, 2000, and 2250 ms. The participants will be required to discriminate as fast and accurately as possible whether the comparison tone has a higher or lower pitch than the standard tones, pressing “z” or “m” (the meaning of what indicates each key will be counterbalanced across participants). The discrimination task will begin with two practice blocks of eight trials each. Feedback for incorrect responses will be provided only during practice blocks. Then, participants will complete one block of 252 trials with fixed IOIs of 500 ms for the sequence of standard tones or with variable IOIs between 250 and 750 ms (the order will be counterbalanced across participants). As there are nine possible IOIs between the last standard tone and the target, and two pitches, there will be 14 trials for each type (with the same IOI and the same pitch). Subsequently, participants will be asked about the difficulty of the last task block (Appendix B). After 1 or 2 minutes of rest, they will carry out a second task block, with variable IOIs if the first block was with fixed IOIs or with fixed if the previous were variable. Finally, the participants will complete the question about the difficulty. The experimental task will compromise 28 trials for each experimental condition. Design and Statistical Analyses The experiment has a (2 × 4 × 2) three-factor repeated-measures design: block (fixed vs. variable), period (500–750/1000–1250/1500–1750/2000–2250 ms), and phase (in-phase: 500, 1000, 1500, and 2000 ms; vs. out-of-phase target: 750, 1250, 1750, and 2250 ms). For behavioral measures, we will conduct repeated-measures ANOVAs with mean RTs and accuracy as dependent variables. Moreover, paired t-tests will be used for comparison between conditions. We expect a higher number of misses in the cue-target interval of 250 ms, and, subsequently, a reduced proportion of trials to be analyzed. Regarding eye-tracker measures, blink intervals will be identified following Hershman et al.’s procedure (2018) and will be removed from the analyses. For analyses with trial time series, raw pupil size will be converted to z scores, by calculating the mean and standard deviation of each separate block for each participant. Then, the time series before the target onset of both blocks will be compared with permutation t-tests based on 10,000 samples. In addition, the slopes of the increase in the pupil size during foreperiod will be analyzed with a regression model, including block (fixed vs. variable) as a categorical factor. For saccade analyses, gaze-position data will be segmented into epochs from –500 to 500 ms relative to the target onset. For saccades detection, we will use a similar procedure to Dankner et al. (2017): saccades are identified by eye moments that exceed a threshold of 4 standard deviations from the median velocity during 7 ms (seven consecutive eye-position samples). The dependent variable will be the saccade rate at –100 to 0 ms relative to the onset of targets for PSSI and the saccade rate at 0 to 500 ms for the post-stimulus effect. We will exclude every trial in which a blink interval overlaps with that interval or in which a saccade larger than 3° occurs at that interval. Permutation t-tests for each time point based on 10,000 samples will be used. In addition, we will use two repeated-measures ANOVAs with block (fixed vs. variable) and phase (in phase vs. out of phase) as factors: one with the mean saccade rates at the pre-stimulus interval (–100 to 0 ms) as dependent variable, and another with the mean saccade rates at the post-stimulus interval 200 to 500 ms). References Andrade, E., Arce, C., De Francisco, C., Torrado, J., & Garrido, J. (2013). Abbreviated version in Spanish of the POMS questionnaire for adult athletes and general population. Revista de Psicología del Deporte, 22(1), 95–102. Aston-Jones, G., & Cohen, J. D. (2005). An integrative theory of locus coeruleus- norepinephrine function: Adaptive gain and optimal performance. Annual Review of Neuroscience, 28(1), 403–450. https://doi.org/10.1146/annurev.neuro.28.061604.135709 Caldwell, A., Lakens, D., DeBruine, L., & Love, J. (2020). 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McCarley and Yamani (2021) proposed a new psychometric-curve analysis offers three (or four) potential indices of the executive vigilance decrement, which greatly improves the two-parameters approach of Signal Detection Theory: scale, associated with sensitivity; shift, related to response criterion; and lapse rate, proposed as an index of task disengagement or mind wandering (a forth parameters, i.e., guess, can also be computed). The ANTI-Vea task (Attentional Networks Test for Interactions and Vigilance – executive and arousal components; Luna et al., 2018) parametrically manipulate the similarity between the infrequent signal (a vertical displacement equal or larger than 6) and the frequent noise (a vertical displacement equal of smaller than 4), which allows the psychometric-curve analysis of the data. In this project, psychometric-curve analysis of different data set of the ANTI-Vea task are made available.

The aims of the present project are: 1) to examine the evidential value of primary studies included in previous meta-analyses and recent articles that have been published afterwards; 2) to estimate the statistical power achieved by individuals studies published up to date using the new meta-analytic effect size estimate obtained from the new meta-analysis